Engineering Success
Methodology in synthetic biology reflects basic principles in engineering, and the engineering cycle reigns amongst one of the most significant ones. The engineering cycle offers comprehensive and systematic guidance on the design and test of biological systems and consists of four stages: design, build, test, and learn.
We propose a programmable logic framework capable of switching between different types of logic gates based on user requirements. We are fully aware that a standardized engineering cycle is even more critical to our cross-disciplinary work, and we followed it strictly and explored it innovatively.
We have reached decent results with the implementation of it, and a summary is as follows.
- In the first stage, we designed and refined the genetic circuits utilizing CRISPRi & recombinases.
- In the second stage, we conducted orthogonality verification to test the orthogonality of recombinases.
- In the third & forth stage, we implemented directed evolution to improve the efficiency of recombinases.
Cycle 1: Genetic Circuit Completion
Design
Our initial circuit design incorporates 4 recombinases and CRISPRi to implement 16 possible logic gates (Figure 1).
Moreover, we recognize the fabulous mathematical properties of the circuit. So we decided to first develop an in silico design to verify the project's feasibility while proceeding with plasmid construction.
Build
Based on the mechanism of CRISPR interference, we establish reaction equations to demonstrate the inhibitory effect of dcas9 and sgRNA on the expression of GFP. We used simbiology to solve ODE and simulate the production of GFP protein.
Test
We obtained the change curves of GFP in two conditions: with and without expression of dcas9 & sgRNA (Figure 2-3). Our results confirmed that the combination of dCas9 and sgRNA effectively inhibits GFP expression, indicating that CRISPRi functions as anticipated in this context and implements the NOT gate function in our circuit.
However, during discussions among our wet lab and modeling team regarding the application of CRISPRi in the genetic circuit, a challenge emerged: if the downstream promoter is inhibited by CRISPRi, normal expression of the gene of interest (GOI) cannot be achieved due to the steric hindrance caused by the dCas9 protein, even when the upstream promoter is actively initiating transcription.
Learn
While CRISPRi successfully implements the NOT gate function in our circuit, a patch is needed to ensure the desired outcomes. So we added a patch (Figure 4) utilizing another two recombinases (Cre & fimE) to Registers, thus completing our genetic circuit design.
Cycle 2: Efficiency and orthogonality of recombinases
Iteration 1: Verification of recombinase efficiency and orthogonality
Design
Our project is based on the site-specific recombination system of six recombinases, so the orthogonality between different recombinases is particularly important. We designed twelve plasmids: six 'recombinase plasmids' which can individually express the 6 recombinases under IPTG induction (Figure 5), and six 'verification plasmids' each containing the recognition site for one of the 6 recombinases (Figure 6). We double-transformed them into bl21(DE3), obtaining 36 types of double-transformed colonies.
By designing specific primers, we can perform colony PCR to verify whether the verification plasmid has been inverted by the recombinase.
Build
We successfully constructed the above twelve plasmids by PCR and homologous recombination. Then we double-transformed the six recombinase plasmids expressing recombinase and the last six plasmids with recombinase sites into the bl21(DE3) strain for inducible expression using IPTG and verified our results using colony PCR.
Test
After induction with IPTG, we used colony PCR to verify the effect of recombinase inversing. According to the analysis (Figure 7), the orthogonality between our six recombinases is good, and almost no inversing of non-specific sites will occur. However, we found that the inversing effect of A118, Bxb1, TP901, and PhiC31 recombinases was not ideal, and some uninverted fragments still existed after the recombinase action.
The red coded fragments are the results of PCR using Test_F1_sk and Test_R1_sk. The target fragment length should be 1556bp.
Learn
From the results, the effect of A118 recombinase was not very effective, and only some of the plasmids containing the recombinase action site were inverted under the action of A118 recombinase. So we decided to perform directed evolution using A118 as an example in order to improve the flipping efficiency of the A118 recombinase.
Iteration 2: Directed evolution of A118 recombinase
Design
We designed an expression module and an selection module. The expression module induces recombinase expression with IPTG, while the selection module uses a phage lysis gene φX174 E.
Build
To characterize our design, we introduced the expression module into the pET-28a(+) vector and the selection module into the pET-22b(+) vector, and we plan to use E. coli as the host.
Test
We used epPCR to amplify the expression module in order to generate a random mutant library for the recombinases. The mutation and selection modules were then introduced into E. coli, and the screening plan was designed as follows:
Initial screening: The growth of E. coli on the medium indicates whether the φX174 E gene has been successfully inverted. If the recombinase mutant retains biological function, the φX174 E gene will not express, allowing for colony growth on the plate. Conversely, if the mutant loses biological function, the φX174 E gene will express, lysing E. coli., resulting in no observable colonies.
Secondary screening: The brightness of GFP was measured using a microplate reader. The higher the recombinase's recombination efficiency, the greater the proportion of RNA transcribed from the inverted GFP gene to the total RNA, visually represented by increased unit brightness of GFP (assuming transcription levels before and after gene inversion remain constant).
Learn
We found that although Traditional Mutagenesis allows for some mutations that have high efficiency, the process of constructing recombinase mutants and transferring them into E. coli is too tedious and labor-intensive. Therefore, we considered whether we could reduce the workload by using a continuous directed evolution approach.
Iteration 3: Continuous directed evolution
Design
Due to the autonomous reproduction of bacteria, we can construct a persistent high-mutation system within bacteria, allowing for continuous mutations during DNA replication. Therefore, we designed a bistable switch that allows our reporter GFP to be inverted by the A118 recombinase under certain conditions and then inverted back by the Gp44 protein under different conditions, enabling a continuous selection process. To achieve continuous high mutation rates inside E. coli, we introduced eMutaT7, a fusion of cytosine deaminase (AID) and T7 RNA polymerase (T7RNAP).
Build
We designed three plasmids: pHyo094, Target plasmid, and Selection plasmid, each with different antibiotic resistance genes—Chloramphenicol (Chl), Kanamycin (Kana), and Ampicillin (Amp)—to facilitate co-transformation into E. coli.
Test
We transferred the above three plasmids into E. coli. First, we added IPTG and arabinose to activate the "Turnover" switch, inducing the expression of eMutaT7 and mutating the A118 recombinase sequence. If the expressed A118 mutant retains its biological function as a recombinase, the GFP gene will be inverted and normally expressed. After sampling the strain, we removed IPTG and arabinose and added ATc to activate the "Turn back" switch, relieving tetR repression on the PLtetRO promoter, which allows Gp44 protein expression to invert the GFP gene back to its original state. After multiple cycles, we can screen for mutant recombinases.
Learn
It has been demonstrated that the efficiency of recombinases can be improved through directed evolution. We plan to apply this approach to other suboptimal recombinases. With these enhanced recombinases, we will conduct further verification at the total circuit level.
