Team:ShanghaiTech/Project Overview
Overview
Why precise control is needed?
Nowadays, car-T therapy is hailed as a cure for cancer since only a small quantity of car-T cells will induce the immunologic cascade, which would inhibit and kill cancer cells effectively. However, the over activate of the immune system will cause cytokine release syndrome, which is a kind of potentially life-threatening toxicity. Hence, we need a control system with time precision to solve this problem.
Not only for the drug delivery like car-T therapy, precise control system is needed in various fields, such as environment detection and scientific research. The system cannot work as expected when the output is not able to catch up with the input signal for a specific expression of the target gene.
Why systems with time precision is not used yet?
The precise input-to-output control may fail at times mainly due to the delayed responses from input signals to output signals. This delay may cause the output signal stimulating, which means the expression of the target output gene is more than expected. Otherwise, the unexpected interactions between the host and exogenous circuits will also cause the disorder of output signals. For example, previous iGEM projects primarily focused on the single time response of systems, which underestimated the fact that continuously changing inputs may cause the disorder of output signals. Therefore, a system needs to be constructed for rapidly responding to the changing input signals and eliminating the superposition between outputs from different input signals.
What are we doing?
We design a high-fidelity control system allowing the outputs to respond precisely to the changing input signals. We envision that our control system will offer the synthetic biology community a novel solution to manipulate uncertain input.
Our control system is divided into two levels, the transcription level and the translation level. When the input signal comes, it will first go through a negative feedback loop (NFBL) in the transcription level, and then output in the translation level where we induced a component called orthogonal ribosome. By making these two levels co-working, we can eventually reach our precise control.
The negative feedback loop contains three parts – part A, part B and part C. We test the GFP expression under control of each part over a period of time. Besides, for Lux, the part A in our negative feedback loop, we measure the expression of GFP under different concentration of AHLs. Moreover, we compare the part C – pT181 – with previous iGEM parts submitted in 2013. We also compare it with the standard plasmid in iGEM Interlab. Using the expression of the plasmid in iGEM Interlab, we find that the repression level of our pT181 is much better than the old version, even though we cannot get their control plasmid. Meanwhile, we can compare the repression effect of pT181 with other repressors using the expression of plasmid in Interlab as measures.
As for the orthogonal ribosome, we examine the characteristic of the orthogonal ribosome, including feasibility, orthogonality and compatibility with the ribosome of the host and the other orthogonal ribosomes by testing the expression of GFP with different orthogonal 16s rRNAs and orthogonal RBS in the cell.
In addition to the circuit, we have produced a software tool, which helps scientists get the corresponding solution closer to a specified waveform by searching proper parameter combinations for user-input parameterized differential equations.