1. Overview

Figure 1: The Overview Genetic Circuit

We designed a genetic circuit capable of switching between different types of logic gates based on user requirements, essentially creating a programmable logic device (PLD) using genetic circuits in organisms. By utilizing inducible promoters, CRISPRi, and recombinases, we can modify gene pathways according to specific targets, ultimately implementing programmable logic gates.

Our circuit consists of four components:

1. The Tangram section contains different recombinases attached to different inducible promoters.
2. The Register section is where recombinases perform their functions, and where the desired logic gate is generated.
3. The Output section collects information from the Register circuits and delivers the final output of the logic gate.
4. The Patch section is designed to avoid the steric hindrance effect of the dCas9 protein.

2. Logic gates

2.1 16 ⊆ 6*6

Consider a Boolean function of 2 variables, use A and B as input variables, and Z as the output variable. The functions f(1,1), f(1,0), f(0,1) and f(0,0) in Z column can take values of 0 or 1. So the total Boolean function has 2^2^2=16 possibilities.

There are two ways to present the 16 possible 2-input, 1-output logic gates: logic functions and Boolean algebra. For logic functions, each set of 4 numbers in the Logic functions column below represents f(1,1), f(1,0), f(0,1), and f(0,0). For example, 1001 represents f(1,1)=1, f(1,0)=0, f(0,1)=0, and f(0,0)=1. For Boolean algebra, A and B represent the inputs:

A' and B' represent the complement of A and B (not-A and not-B)

A*B=A AND B

A+B=A OR B.

Thus, the function has 2×2×2×2=16 possibilities as listed above. However, it is too complex to express the 16 possibilities in a single cell with one gene circuit. So we split these 16 logic gates into two genetic pathways, each pathway can function as any of these 6 basic logic gates: A, A', A+B, A+B', A'+B, or A'+B'. Intersection from any two elements from this set: {A, A', A+B, A'+B, A+B', A'+B'} can yield all 15 possibilities except for 1.

2.2 Implementation of A and not-A

Next, how to implement A & not-A in genetic circuits? We decide to use inducible promoters and CRISPRi. As mentioned in the Description, CRISPRi is an excellent NOT gate for the implementation of A and not-A required in our design for its high efficiency and specificity.

For example, taking IPTG as input A, GFP as output Z, a single inducible promoter equals an A logic gate. Then we design a sgRNA that binds to a constant promoter and interferes with the binding of RNA polymerase to the promoter. The sgRNA is attached to an IPTG-inducible promoter, thus achieving a not-A logic gate.

Figure 2: Implementation of A

Figure 3: Implementation of not-A

3. Circuit Design

As stated in the Overview, our genetic circuit consists of 4 components.

3.1 Tangram

Tangram is a dissection puzzle consisting of seven flat polygons that can be put together to form various shapes. We found this concept highly analogous to our design, where recombinases play the role of altering the shape of the genetic circuits, thus enabling the execution of different logic gates.

The Tangram section contains four recombinases: tp901(Guiziou et al., 2019), bxbI(Neil et al., 2019), a118(Roquet et al., 2016), phiC31(Guiziou et al., 2019), each preceded by an inducible promoter. When the corresponding inducer is present, the respective recombinase is expressed. For example, the addition of the inducer Ara leads to the expression of the recombinase tp901.

Figure 4: Tangram Section

3.2 Register A & B

To better illustrate the function of our program, here we use IPTG to denote input1, rha for input2, and GFP to represent output Z. Different inputs and output may be alternated according to specific needs.

As previously stated, we can utilize two elements to create 16 possible logic gates. The first element can be one of the following: A, A+B, A+B', A'+B, or A'+B'; the second element can be: A', A+B, A+B', A'+B, or A'+B'. Our two registers, along with a patch system, enable us to achieve all possible logic gates.

For Register A, the output will be A'+B if no inducers are added. Adding Ara (blue) results in A+B', and adding ATc (red) yields A'. Adding both inducers is also an option, but the order of addition is crucial. If Ara is added first followed by ATc, the output will be A+B. Conversely, if ATc is added before Ara, the output will be A.

Figure 5: How Register A transforms into different logic gates. Ara is the inducer of recombinase tp901, while ATc is the inducer of recombinase bxbI. Different sizes of triangles represent different pairs of recombinase-recognition sites. Once the inducers are added, the corresponding recombinases will bind to its specific recognition sites, catalyze inversion (when the sites are anti-aligned) or excision (when the sites are aligned).

Register B operates similarly to Register A but uses different inducers and recombinases. While Ara is replaced with DAPG (yellow) and ATc with xylose (purple), the principle of inducing different outputs by sequentially adding inducer remains the same.

Figure 6: How Register B transforms into different logic gates. DAPG is the inducer of recombinase a118, while Xylose is the inducer of recombinase φC31. Different sizes of triangles represent different pairs of recombinase-recognition sites. Once the inducers are added, the corresponding recombinases will bind to its specific recognition sites, catalyze inversion (when the sites are anti-aligned) or excision (when the sites are aligned).

By combining the CRISPRi system, the recombinase expression system (Tangram section), and the designed sequences above (Register A & B), we can achieve the transformation of logic gates by adding recombinases in different orders (Figure 7-8).

Figure 7: Register A

Figure 8: Register B

3.3 Output

The Output GFP is linked to a lux promoter, which turns on only when AHL & LuxR both exist, utilized by the 2023 UCAS-China team. By using the Lux promoter, we can achieve the intersection of the Register A and Register B pathways (Figure 9).

Figure 9: Output

3.4 Patch

In the design-build-learn-test cycle, we found that in the original pathway, if we inhibit the downstream promoter using CRISPRi, the normal expression of the gene of interest (GOI) cannot be achieved due to the steric hindrance effect of the dCas9 protein, even when the upstream promoter is actively initiating transcription. Therefore, we additionally designed a patch system (Figure 10).

Figure 10: A patch system using Cre/loxP system and fimE inversion system

In the original pathway, to achieve the output of A' + B', the dCas9 protein at B' inhibits the normal expression of A'. Therefore, we separately express B' in the Patch system to realize A' + B'.

We introduced a cumate-inducible cymR promoter to express the Cre recombinase in the pathway; upon adding cumate, the expressed Cre recombinase recognizes the loxP sequence, allowing the LuxI gene sequence to invert and be expressed by the constitutive promoter. This constitutes the Patch portion of Register A. Similarly, in the Register B pathway, we incorporated the PobR promoter used by the 2023 UCAS-China team and the fimE inversion system from E. coli (Ham et al., 2006) to complement the expression of the LuxR gene.

4. Experiment verification

4.1 Workflow

To verify our system, we first constructed the plasmids for the verification using PCR and homologous recombination. Next, we qualitatively validated the orthogonality of four recombinases by using colony PCR. To evaluate the efficiency and precision of the recombinases, we used qPCR to measure the recombinase efficiency, and confirmed the inverted sequence accuracy by sequencing. Then, we tested the functionality of the OR gate by arranging two promoters in series and utilized modeling to optimize the Register sequences. Finally, we devised three directed evolution strategies to enhance the efficiency of the recombinases: epPCR mutagenesis, eMutaT7 continuous directed evolution system, and semi-rational design.

Figure 11: Workflow of the experiment verification

4.2 Orthogonality matrix

Figure 12: An orthogonality verification system

To validate that the six recombinases selected for our project are mutually orthogonal, we designed an orthogonality verification experiment(Figure 12). We create two plasmids: one plasmid expressing a specific recombinase under the T7 promoter and the other plasmid expressing the inverted gfp using the constitutive promoter J23119. Both the ribosome binding site (RBS) and the gfp have recognition sites for a specific recombinase. We vary the recombinase genes and recognition site sequences in the two plasmids and transformed them into E. coli by pair, then we have two methods to assess orthogonality. On the DNA level, we can use colony PCR to check whether the segments have been inverted. On the protein level, we can measure the intensity of green fluorescence.

4.3 Register 0 induction

Register 0 is a regulation part that can be used to verify the feasibility of our Register system. It can verify whether two or more promoters can work together and whether it is effective to take regulatory proteins like LacI apart from promoters like Plac. Register 0 consists of four promoters (constant promoter J23111, trc promoter, and inducible promoter lac operon, Rha promoter) with different directions, Three pairs of DNA recognition sites(A118B-GG_A118P-GG, A118B-CC_A118P-CC, PhiC31B-AA_PhiC31P-AA), a Ribosome binding site, and msfGFP(Figure 13).

Figure 13: Design of Register 0

4.4 Directed Evolution

We use directed evolution to enhance recombinases efficiency for the unsatisfactory of recombinases in experiments.

4.4.1 Traditional Mutagenesis

In our first directed evolution system, we used error-prone PCR (epPCR) to generate a random mutant library of the whole recombinases and selected the φX174 E phage lysis gene (Din et al., 2016) for selection and GFP gene for fluorescence screening. We designed an expression module, which drives recombinase expression via IPTG induction (Figure 14) and a selection module, which utilizes the φX174 E phage lysis gene and GFP gene (Figure 15).

We utilized epPCR to amplify the recombinase expression module to generate a random mutant library. The resulting mutant expression plasmids were transformed with selection plasmids together and the efficient recombinase variants were identified through a combination of growth selection and fluorescence screening in the selection module.

Figure 14: Expression module of traditional mutagenesis

Figure 15: Selection module of traditional mutagenesis

4.4.2 Epi-hypermutation Architectures of continuous directed evolution

Given the low efficiency of traditional mutagenesis, we developed an autonomous directed evolution system based on MutaT7, which was originally a fusion of cytosine deaminase and T7 RNA polymerase (Figure 16) (Park et al., 2021). In the expression section, the gene for the recombinase is placed between the T7 promoter and T7 terminator, allowing transcription by T7 polymerase while utilizing cytosine deaminase for mutations.

Using recombinase A118 as an example, our autonomous directed evolution system consists of three plasmids:

• pHyo094 (eMutaT7): The eMutaT7 enzyme is expressed under the control of the PBAD promoter, which is induced by arabinose (Ara).
• Target plasmid: We designed a bistable switch system focused on regulating the expression of the A118 recombinase and the Gp44 protein, which can can enhance the excision or inversion reaction of A118 between attL and attR sites (Mandali et al.,2017). The "Turn over" switch is controlled by the lactose operon, while the "Turn back" switch is regulated by the tetR protein.
• Selection plasmid: A constitutive promoter, J23119, is used to express the inverted gfp gene.

Figure 16: Continuous directed evolution system

4.4.3 Semi-rational Design

Mutagenesis methods are often limited to small-scale random variations, which can is difficult to achieve significant functional improvements. Semi-rational design is a better choice for mutant exact point of the recombinases function area, which can largely reduce the size of the mutant library. We used the A118 recombinase as a model and predicted its composite structure with the attP site using AlphaFold 3 (fig. 15). Molecular docking was then performed to analyze their interactions, guiding more precise mutagenesis.

Figure 17: Predicted structure of A118 and attP

5. References

1. Din, M., Danino, T., Prindle, A. et al. Synchronized cycles of bacterial lysis for in vivo delivery. Nature 536, 81–85 (2016).
2. Park, H., & Kim, S. (2021). Gene-specific mutagenesis enables rapid continuous evolution of enzymes in vivo. Nucleic acids research, 49(6), e32.
3. Mandali, S., Gupta, K., Dawson, A. R., Van Duyne, G. D., & Johnson, R. C. (2017). Control of Recombination Directionality by the Listeria Phage A118 Protein Gp44 and the Coiled-Coil Motif of Its Serine recombinase. Journal of bacteriology, 199(11), e00019-17.
4. Ham, T.S., Lee, S.K., Keasling, J.D. and Arkin, A.P. (2006), A tightly regulated inducible expression system utilizing the fim inversion recombination switch. Biotechnol. Bioeng., 94: 1-4.
5. Guiziou, S., Maranas, C.J., Chu, J.C. et al. (2023). An recombinase toolbox to record gene-expression during plant development. Nat Commun 14, 1844 .
6. Roquet, N., Soleimany, A. P., Ferris, A. C., Aaronson, S., & Lu, T. K. (2016). Synthetic recombinase-based state machines in living cells. Science (New York, N.Y.), 353(6297), aad8559.
7. Guiziou, S., Mayonove, P., & Bonnet, J. (2019). Hierarchical composition of reliable recombinase logic devices. Nature communications, 10(1), 456.