iGEM 2025 — Team bnds-china

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## Menu

[Overview](#overview)
[Cycle #1](#cycle-1)
[Cycle #2](#cycle-2)
[Cycle #3](#cycle-3)
[Cycle #4](#cycle-4)
[Cycle #5](#cycle-5)
[References](#references)

## Overview

This section of our wiki describes how we iterated our design for the taurocholic acid (TCA) sensor, which serves as the overall "switch" of our probiotic platform.

Cycles #1-4 describe our attempts to improve the CmeR-pCmeR sensor design, which is based on TCA's ability to bind to CmeR and dissociate it from cmeO, therefore allowing downstream gene expression. We used the design-build-test-learn cycle four times to find the optimal positioning of cmeO, -35 region, and -10 region inside pCmeR, the appropriate RBS strength in cooperation with the promoter, as well as constitutive promoter upstream of CmeR (Figure 1A). At the end of Cycle #4, however, our experimental data and published literature collectively indicated that TCA has very limited ability to cross the plasma membrane and thus cannot effectively act as a cytoplasmic ligand for CmeR.

This limitation of the CmeR-based TCA sensors drove our design for another TCA sensor in Cycle #5, in which we incorporated the transmembrane detector TcpP as the core component of our TCA sensor. Further, we replaced TcpP's DNA-binding domain with that of CadC, which is compatible with *E. coli*, and expressed TcpH as a protection against TcpP degradation. In the presence of TCA, the CadC-TcpP fusion protein will dimerize and activate promoter pCadBA. (Figure 1B) At the end of Cycle #5, our experimental results showed that this TcpP-based TCA sensor succeeded in detecting TCA with a >20-fold dynamic range.

![](https://static.igem.wiki/teams/5605/es/1.avif)

*Figure 1. The plasmid designs of TCA sensors in our engineering process. A, plasmid designs of CmeR-based TCA sensors used in Cycles #1-4; the first 4 cycles aim to optimize the performance of this TCA sensor by tuning the switchable components (including the promoter upstream of CmeR, the promoter upstream of GFP, and the RBS upstream of GFP). B, plasmid design of the TcpP-based TCA sensor used in Cycle #5. Created by biorender.com.*

## Cycle #1

### Design

Our TCA sensor was constructed to detect bile acids, which serve as an indicator of food presence. We first selected the TetR-family repressor CmeR as a critical component due to its strong, well-characterized binding affinity for TCA (with a dissociation constant of 1.5 μM) [(Lei, 2011)](#ref3), making it ideal for modulating gene expression in response to TCA.

In our initial design, CmeR was placed under the control of the constitutive promoter J23119. J23119 was chosen for its ability to drive high-level transcription, ensuring substantial expression of CmeR. The CmeR-regulated promoter, pCmeR, was constructed from pQacR ([BBa\_J428050](https://parts.igem.org/Part%3ABBa_J428050)) by replacing the operator sequence *qacO* with *cmeO* [(Nasr et al., 2022)](#ref6). GFP was placed downstream of pCmeR to enable monitoring of CmeR's regulatory function. When TCA binds to CmeR, it disrupts CmeR's inhibitory function, leading to the expression of GFP (Figure 2). This interaction provides a visual representation of our system's response to TCA levels.We call this plasmid pJ23119-CmeR\_pCmeR(-10)-B0031-GFPmut2, in which the major functioning device is [BBa\_25F4UCQM](https://registry.igem.org/parts/bba-25f4ucqm).

![](https://static.igem.wiki/teams/5605/es/2.webp)

*Figure 2. The genetic circuit of the initially designed TCA sensor, pJ23119-CmeR\_pCmeR(-10)-B0031-GFPmut2. Created by biorender.com.*

### Build

We integrated this design into the plasmid backbone pUC57-Kan (Figure 3), and ordered the plasmid from Tsingke.

During the synthesis process, the company was unable to produce the correct sequence. To address this problem, they explored various strategies, including conducting several rounds of experimental repairs, substituting with a special competent strain, and culturing at low temperatures. Nevertheless, after multiple failed attempts, the best result they produced still contained a point mutation in the sequence (Figure 4).

![](https://static.igem.wiki/teams/5605/es/3.webp)

*Figure 3. Plasmid map of pCmeR\_GFPmut2\_pUC57-Kan.*

![](https://static.igem.wiki/teams/5605/es/4.webp)

*Figure 4. Sequence comparison of the designed and mutated plasmids. The red box indicates a nonsense mutation in the cmeR gene.*

### Test

To investigate the mutations in *cmeR*, we performed *in silico* analyses to predict the transcription initiation and translation rates of the *cmeR* gene within the plasmid using the Promoter Calculator and RBS Calculator algorithms of De Novo DNA [(LaFleur et al., 2022; Salis et al., 2009)](#ref2). First, the predicted transcription initiation rates across the entire plasmid revealed a significant peak of 40055 au at 1245 bp on the reverse strand, corresponding to the site of J23119-CmeR transcriptional unit (Figure 5). Second, a high translation rate of the full-length CmeR protein was also identified by prediction (Figure 6). They collectively confirmed that CmeR could be expressed at significantly high levels.

![](https://static.igem.wiki/teams/5605/es/5.webp)

*Figure 5. The De Novo DNA PromoterCalculator result of originally designed pJ23119-CmeR\_pCmeR(-10)-B0031-GFPmut2. The black circle indicates the peak in transcription initiation rate of theJ23119-CmeR transcriptional unit.*

![](https://static.igem.wiki/teams/5605/es/6.webp)

*Figure 6. Translation initiation rates ofthe mRNA encoding CmeR. The red circle suggests a peak in CmeR translationinitiation, indicating the translation of the full-length CmeR protein.*

### Learn

The combined insights from these *in silico* analyses suggest that the high transcription and translation levels of CmeR might result in a significant level of CmeR within the cell. Meanwhile, a high-copy plasmid also contributes to the elevated CmeR levels. This may have led to an excessively high level of the transcriptional repressor, potentially resulting in toxicity to the host cell and killing it [(Barneda-Zahonero et al., 2015)](#ref1). Hence, we ultimately concluded that this was the reason why only the variants incorporating a mutation in the *cmeR gene* survived.

## Cycle #2

### Design

As indicated in the "learn" part of Cycle #1, we identified a possible reason for the infeasibility in synthesizing our target plasmid to be the usage of the J23119 promoter, which might lead to toxic levels of CmeR in cells with the correct sequence. Therefore, in this cycle, we aimed to address two problems: we tried to fix the unwanted stop codon and to turn down the transcriptional activity of the constitutive promoter upstream of CmeR. Since J23119 is the strongest member of a family of constitutive promoters, we decided to mutate promoter J23119 and choose a mutant with suitable transcriptional strength.

To achieve this, we designed primers that keep the same spacer sequences of J23119 but have degenerate nucleotides for the -35 and -10 regions (Figure 7). In doing so, we obtained a library of constitutive promoters of varying strength. We called this plasmid pJ23119(lib)-CmeR\_pCmeR(-10)-B0031-GFPmut2. After switching to a promoter of weaker strength, correct transcription of the plasmid and suitable levels of expression of CmeR should be achieved in *E. coli*. Therefore, we hypothesized that after using a weaker promoter, CmeR expression can be well-tolerated by *E. coli*.

![](https://static.igem.wiki/teams/5605/es/7.webp)

*Figure 7. Degenerate nucleotides thatmodify J23119's -10 and -35 regions in the J23119 promoter library. The"Y", "R", "M", "W", and "K"notations are degenerate nucleotides that respectively represent thenucleotides: C or T, A or G, A or C, A or T, G or T.*

### Build

PCR and Golden Gate assembly using specially designed primers were performed to introduce mutations in the promoter sequence, creating a J23119 library, and to fix the stop codon into the original amino acid. Agarose gel electrophoresis (AGE) was performed, and the bands indicate the correctness of the components' and the assembled product's length (Figure 8), verified by whole-plasmid sequencing.

![](https://static.igem.wiki/teams/5605/es/8.webp)

*Figure 8. The AGE result of the PCRproducts (A and B) and Golden Gate assembly product (C) for the construction ofthe plasmid pJ23119(lib)-CmeR\_pCmeR(-10)-B0031-GFPmut2. The bands indicate thecorrectness of the components' and the assembly product's length.*

### Test

The plasmid library of J23119 mutants was transformed into *E. coli* Trelief 5α, and solid inoculation was carried out. Most colonies had significant levels of green fluorescence. Because no TCA was added into the plate, the result contradicted our expectation that there would be no fluorescence, suggesting a high leaky expression of our design.

### Learn

Our results suggest that while our mutant promoter from the J23119 library is successfully incorporated and can correctly express CmeR in *E. coli*, leaky expression of GFP is a severe issue. This may be caused by CmeR not being able to sufficiently block pCmeR from transcription factors' binding and elongation. In order to prevent leaky expression of GFP, it is necessary to enhance the repression effect of CmeR on pCmeR. This can be achieved by increasing the dominance of CmeR in its competition with transcriptional factors at PcmeR. However, CmeR expression should not be elevated due to its toxicity to *E. coli* at high levels. In the next cycle, we will try to alter the location of *cmeO* on pCmeR in order to enable CmeR to have complete control.

## Cycle #3

### Design

The plasmid design in this cycle was based on one variant ([BBa\_25A12OMH](https://registry.igem.org/parts/bba-25a12omh)) of the J23119 library built in Cycle #2, called J23119(mut). To increase CmeR's ability to inhibit transcription, we moved the *cmeO* region in pCmeR to make it overlap with the -35 region (indicated by the red boxes in Figure 9), meanwhile changing the sequence in the -35 region to be compatible with this overlap (Figure 9). In this cycle, we also changed the GFP used, from GFPmut2 into superfolder GFP (sfGFP, [BBa\_K4850004](https://parts.igem.org/Part%3ABBa_K4850004)), in order to achieve consistency across all reporter proteins used in our project.

![](https://static.igem.wiki/teams/5605/es/9.webp)

*Figure 9. The comparison ofpCmeR(-10)-B0031 and pCmeR(-35)-RBS(Bgl). The red boxes indicate the same cmeOsequence but at different locations. The blue boxes indicate the samespacer-(-10) sequence at the same locations.*

The above change in the -35 sequence turns down the transcriptional rate of pCmeR by more than two-fold, which was verified by the *in silico* analysis in Figure 10. The transcriptional rate in this plasmid would even be lower considering the inhibition of CmeR, which occupies the transcriptional factor-binding region.

![](https://static.igem.wiki/teams/5605/es/10.webp)

*Figure 10. The comparison of predictedtranscriptional rates of GFP under pCmeR(-10) and pCmeR(-35). The yellow boxesand the yellow arrow indicate the pCmeR's location on the plasmid map. The redcircles indicate the peaks in transcriptional rates of the pCmeR region.*

However, we did not want to lower the GFP expression in the presence of TCA. We therefore changed the upstream RBS sequence from B0031 into a stronger RBS, called RBS(Bgl) (Figure 9). This RBS was from the standard BglBrick plasmid library [(Lee et al., 2011)](#ref5). We then ran an *in silico* analysis of translation rates, which verified the intended 15-fold increase in the RBS strength (Figure 11). All the above changes to the previous design eventually resulted in the plasmid named pJ23119(mut)-CmeR\_pCmeR(-35)-RBS(Bgl)-sfGFP, in which the major functioning device is [BBa\_25E1I21E](https://registry.igem.org/parts/bba-25e1i21e).

![](https://static.igem.wiki/teams/5605/es/11.webp)

*Figure 11. The comparison of predictedtranslation rates of GFP downstream of B0031 and RBS(Bgl). Red circles indicatethe correct peaks in the translation of full-length GFP.*

Further, we designed another plasmid, pJ23119(mut)-CmeR(2\*TAA)\_pCmeR(-35)-RBS(Bgl)-sfGFP (in which the major functioning device is [BBa\_256FO3O6](https://registry.igem.org/parts/bba-256fo3o6)), as a control to evaluate the effect of the CmeR protein. In this plasmid, most of the sequence is the same as the plasmid designed earlier in this section, except that it includes nonsense mutations on the second and third triplets of the *cmeR* sequence (Figure 12). This new plasmid will not express functional CmeR protein but has other parts the same, therefore serving as an appropriate control to pJ23119(mut)-CmeR\_pCmeR(-35)-RBS(Bgl)-sfGFP.

![](https://static.igem.wiki/teams/5605/es/12.webp)

*Figure 12. The comparison between sequences of CmeR and CmeR(2\*TAA). The red box indicates the introduction of the 2\*TAA nonsense mutation.*

### Build

PCR was performed to acquire most parts of pJ23119(mut)-CmeR\_pCmeR(-35)-RBS(Bgl)-sfGFP. For the region depicted in Figure 9, however, there was no ready-made template in previous plasmids, and it was too long (about 60 bp) to be carried in Golden Gate Assembly primers. Therefore, we annealed two ssDNA primers together to form our desired DNA segment, together with sticky ends compatible with other fragments in the Golden Gate Assembly (Figure 13).

![](https://static.igem.wiki/teams/5605/es/13.webp)

*Figure 13. Annealed DNA product. The top and bottom strands are two ssDNA primers.*

We then performed the Golden Gate Assembly using 2 fragments from PCR and the above annealing product. Agarose gel electrophoresis (AGE) was performed, and the bands indicated the correctness of the PCR products' and the assembled product's lengths (Figure 14). The plasmid sequence was verified by whole-plasmid sequencing.

![](https://static.igem.wiki/teams/5605/es/14.webp)

*Figure 14. The AGE result of the PCRproducts (A) and Golden Gate assembly product (B) for the construction of theplasmid pJ23119(mut)-CmeR\_pCmeR(-35)-RBS(Bgl)-sfGFP. The bands indicate thecorrectness of the components' and the assembly product's length.*

The construction of pJ23119(mut)-CmeR(2\*TAA)\_pCmeR(-35)-RBS(Bgl)-sfGFP was done in a similar way, with two fragments derived from PCR and one fragment being the annealing product. We then performed the Golden Gate Assembly and agarose gel electrophoresis. The bands indicated the correctness of the PCR products' and the assembled product's lengths (Figure 15). The plasmid sequence was verified by whole-plasmid sequencing.

![](https://static.igem.wiki/teams/5605/es/15.webp)

*Figure 15. The AGE result of the PCR products (A) and Golden Gate assembly product (B) for the construction of the plasmid pJ23119(mut)-CmeR(2\*TAA)\_pCmeR(-35)-RBS(Bgl)-sfGFP. The bands indicate the correctness of the components' and the assembly product's length.*

### Test

We transformed both plasmids into *E. coli* Trelief 5α for cloning, and the one without the 2\*TAA mutation into *E. coli* Nissle 1917 for the kinetics assay. The detailed plate setup in the assay is shown in Figure 16.

![](https://static.igem.wiki/teams/5605/es/16.webp)

*Figure 16. Plate layout of kinetics assay for pJ23119(mut)-CmeR\_pCmeR(-35)-RBS(Bgl)-sfGFP.*

The results of the kinetics assay were used to calculate the fluorescence / ABS600 curve. The normalized curve of the groups and the stationary phase result both showed no statistical differences as TCA concentration changes (Figure 17).

![](https://static.igem.wiki/teams/5605/es/17.webp)

*Figure 17. GFP expression of pJ23119(mut)-CmeR\_pCmeR(-35)-RBS(Bgl)-sfGFP in the kinetics and the stationary phase. Fluorescence / ABS600 was used to represent GFP expression. Error bars represent SD. The red box indicates the data used in plotting the stationary phase result.*

To explore the underlying reason for this unexpected result, we looked at the solid inoculation result of pJ23119(mut)-CmeR(2\*TAA)\_pCmeR(-35)-RBS(Bgl)-sfGFP, the plasmid with the 2\*TAA mutation and without functional CmeR. All colonies showed little or no green fluorescence.

### Learn

The results suggest that integrating *cmeO* directly into the -35 region of pCmeR weakens the promoter too severely. As a result, transcription was minimal regardless of whether CmeR was functional or inhibited by TCA. This explains why pJ23119(mut)-CmeR\_pCmeR(-35)-RBS(Bgl)-sfGFP showed little induction by TCA, and why the 2\*TAA control showed little fluorescence. While this design improved repression potential, it also disrupted RNA polymerase recruitment, leaving the promoter unable to generate measurable GFP expression.

To maintain repression while preserving basal promoter strength, *cmeO* should be shifted into the spacer region between -35 and -10 in future cycles. This placement would still allow CmeR to effectively block transcription when bound, but also permit RNA polymerase binding and initiation once CmeR is released by TCA.

## Cycle #4

### Design

The results from Cycle #3 revealed that placing *cmeO* directly within the −35 region of pCmeR largely lowers promoter activity to the extent that no measurable GFP expression could be induced, regardless of CmeR function. To balance promoter strength and repression efficiency, in Cycle #4 we redesigned the regulatory region by shifting *cmeO* into the spacer between the -35 and -10 sites (Figure 18). This positioning was chosen because it allows CmeR to physically obstruct RNA polymerase progression when bound, while still permitting basal promoter activity (by not disrupting the key sequence to recruit transcription factor) and full transcriptional activation once CmeR is released by TCA. This change led to the plasmid called pJ23119(mut)-CmeR\_pCmeR(spacer)-RBS(Bgl)-sfGFP, in which the major functioning device is [BBa\_25RC9Z6P](https://registry.igem.org/parts/bba-25rc9z6p).

![](https://static.igem.wiki/teams/5605/es/18.webp)

*Figure 18. The comparison of pCmeR-RBS region between pCmeR(-10)-B0031, pCmeR(-35)-RBS(Bgl), and pCmeR(spacer)-RBS(Bgl). The red boxes indicate the movement of the same cmeO sequence as we improved our design.*

The above change in the -35 sequence increases the transcriptional rate of pCmeR by more than 4-fold, even larger than the original design of pCmeR(-10), which was verified by the *in silico* analysis in Figure 19. We expected that this design could allow high GFP expression when CmeR is not blocking *cmeO*.

![](https://static.igem.wiki/teams/5605/es/19.webp)

*Figure 19. The comparison of predicted transcriptional rates of GFP under pCmeR(-10), pCmeR(-35), and pCmeR(spacer). The yellow boxes and the yellow arrow indicate the pCmeR's location on the plasmid map. The red circles indicate the peaks in transcriptional rates of the pCmeR region.*

Similar to what we have done in Cycle #3, we additionally designed a plasmid without full-length CmeR, called pJ23119(mut)-CmeR(2\*TAA)\_pCmeR(spacer)-RBS(Bgl)-sfGFP (in which the major functioning device is [BBa\_25UQXNE7](https://registry.igem.org/parts/bba-25uqxne7)) , by introducing a 2\*TAA mutation in the second and third amino acid loci (the same change as in Figure 12). This serves as an appropriate control to pJ23119(mut)-CmeR\_pCmeR(spacer)-RBS(Bgl)-sfGFP.

### Build

PCR and Golden Gate Assembly were performed to build the correct plasmids. Agarose gel electrophoresis (AGE) was performed, and the bands indicated the correctness of the PCR products' and the assembled products' lengths (Figure 20). Similar to the building of pJ23119(mut)-CmeR\_pCmeR(-35)-RBS(Bgl)-sfGFP in Cycle #3, we annealed two ssDNA primers together as the third fragment in the Golden Gate assembly of pJ23119(mut)-CmeR(2\*TAA)\_pCmeR(spacer)-RBS(Bgl)-sfGFP. The sequence of plasmids was verified by whole-plasmid sequencing.

![](https://static.igem.wiki/teams/5605/es/20.webp)

*Figure 20. The AGE result of the PCR products (A) and Golden Gate assembly product (B) for pJ23119(mut)-CmeR\_pCmeR(spacer)-RBS(Bgl)-sfGFP; the AGE result of the PCR products (C) and Golden Gate assembly product (D) for pJ23119(mut)-CmeR(2\*TAA)\_pCmeR(spacer)-RBS(Bgl)-sfGFP. The bands indicate the correctness of the components' and the assembly product's length.*

### Test

The plasmid with 2\*TAA mutation was transformed into *E. coli* Trelief 5α, and solid inoculation was performed. Since no full-length CmeR was expressed and therefore no repressor was blocking GFP expression, all colonies showed green fluorescence as expected. This shows that pCmeR's transcriptional rate is high enough without the binding of CmeR to activate downstream expression.

However, in our qualitative test of pJ23119(mut)-CmeR\_pCmeR(spacer)-RBS(Bgl)-sfGFP, the group with TCA++ showed no induction compared to the group without TCA, and neither of the two groups showed green fluorescence (Figure 21).

![](https://static.igem.wiki/teams/5605/es/21.webp)

*Figure 21. Qualitative test of pJ23119(mut)-CmeR\_pCmeR(spacer)-RBS(Bgl)-sfGFP using TCA. TCA (++), 1mM TCA added. TCA (-), no TCA added.*

Comparing the TCA- group of the above qualitative test and the solid inoculation of the plasmid with 2\*TAA mutation, we could conclude that the presence of CmeR protein could successfully bind to *cmeO* and block downstream gene expression. The problem, then, might lie in the interaction between CmeR and TCA.

Therefore, we set up another qualitative test of pJ23119(mut)-CmeR\_pCmeR(spacer)-RBS(Bgl)-sfGFP using salicylate, another inducer of pCmeR. In previous characterizations of CmeR in literature, adding 1mM salicylate can increase downstream expression by 8-fold [(Nasr et al., 2022)](#ref6). As shown in Figure 22, the tube in the presence of salicylate showed higher green fluorescence.

![](https://static.igem.wiki/teams/5605/es/22.webp)

*Figure 22. Qualitative test of pJ23119(mut)-CmeR\_pCmeR(spacer)-RBS(Bgl)-sfGFP using salicylate. Salicylate (++), 1mM salicylate added. Salicylate (-), no salicylate added.*

### Learn

The results above confirmed several important aspects of the CmeR-pCmeR sensor system. First, as already mentioned in the "test" part, we could conclude that CmeR successfully binds to *cmeO* and blocks downstream gene expression. The test with salicylate as the inducer further helped us conclude that CmeR stops blocking downstream gene expression when binding to its ligands. However, although structural studies and literature indicate that TCA can bind to CmeR with high affinity and change its 3D structure [(Lei, 2011)](#ref3), our experimental data showed that TCA was not able to turn on repression *in vivo*. This confirmed that the regulatory logic of our construct was correct, but that TCA itself was not available to cytoplasmic CmeR.

Taken together, we concluded that the CmeR-pCmeR system cannot be directly used as a TCA sensor inside *E. coli* because of TCA's poor membrane permeability, which was tested in literature [(Elkins & Savage, 2003)](#ref7). This learning marks a turning point in our design strategy: instead of attempting further optimizations of intracellular CmeR regulation, we needed to incorporate a sensor that detects extracellular TCA.

## Cycle #5

### Design

The "test" and "learn" parts in Cycle #4 drove our design of the second TCA sensor, which is based on the transmembrane sensor TcpP.

TcpP is responsible for bile salt sensing in *Vibrio cholerae*; in the presence of ligands, TcpP dimerizes and acts as a transcriptional factor, therefore activating downstream gene expression [(Xue et al., 2016)](#ref8). Its subcellular localization (on the membrane with its ligand-binding domain oriented towards the extracellular side) addresses the problem identified in Cycle #4 with the previous TCA sensor.

We also integrated a protective protein, TcpH, to slow down the degradation of TcpP by a RseP homolog in *E. coli*, as suggested by past research [(Yang et al., 2013; Chang et al, 2021)](#ref9). This TcpP-TcpH TCA sensor has shown high compatibility to *E. coli* after being integrated into a previously well-characterized, widely-applicable synthetic receptor platform called EMeRALD (short for **E**ngineered **M**odulariz**e**d **R**eceptors **A**ctivated via **L**igand-induced **D**imerization) [(Chang et al, 2021)](#ref10). In the design of this TcpPH-EMeRALD system, since the transcriptional factor in *V. cholerae* might not be compatible with promoters and RNA polymerases in *E. coli*, the DNA-binding domain of the native TcpP was replaced by the DNA-binding domain of CadC, a membrane-bound pH sensor in *E. coli* that regulates the promoter pCadBA [(Lindner & White, 2014)](#ref11). The fusion protein CadC-TcpP, composed of the ligand-binding and transmembrane domains of TcpP and the DNA-binding domain of CadC, keeps the function both as a TCA sensor and as a transcriptional factor endogenous to *E. coli*. This TcpPH-EMeRALD system has shown a promising sensing ability in *E. coli* [(Chang et al, 2021)](#ref10).

In our plasmid design, we put CadC-TcpP and TcpH downstream of two different constitutive promoters, P9 and apFAB339, because the relative expression levels of CadC-TcpP and TcpH proteins under this combination of promoters were tested to show the optimal sensing performance [(Chang et al, 2021)](#ref10). We placed sfGFP as the reporter protein downstream of pCadBA, which will be expressed upon binding with CadC DNA-binding domain in the presence of TCA. (Figure 23) This eventually gives rise to the major functioning device [BBa\_25XJ1XUG](https://registry.igem.org/parts/bba-25xj1xug) in the plasmid pTcpP-sfGFP.

![](https://static.igem.wiki/teams/5605/es/23.webp)

*Figure 23. Plasmid design of TcpP-based TCA sensor. Created by biorender.com.*

### Build

We ordered the CadC-TcpP and TcpH sequences from Tsingke. PCR and Golden Gate Assembly were then performed to build the correct plasmids. AGE was performed, and the bands indicated the correctness of the assembled product's length (Figure 24).

![](https://static.igem.wiki/teams/5605/es/24.webp)

*Figure 24. The AGE result of the Golden Gate assembly product for the construction of the plasmid pTcpP-sfGFP. The bands indicate the correctness of the components' and assembly product's length.*

### Test

We transformed both the TcpP-based TCA sensor into *E. coli* Trelief 5α for cloning, and into *E. coli* Nissle 1917 for the kinetics assay. The detailed plate setup in the assay is shown in Figure 25.

![](https://static.igem.wiki/teams/5605/es/25.webp)

*Figure 25. Plate layout of the kinetics assay for TcpP-based TCA sensor.*

The results of the kinetics assay were used to calculate the fluorescence / ABS600 curve. The normalized curve of the groups and the stationary phase result indicate that fluorescence level is positively correlated with TCA concentration with low concentrations of TCA (below 125 μM). Above 125 μM, however, the fluorescence level stays the same regardless of TCA concentration. Overall, this sensor has achieved a >20-fold dynamic range. (Figure 26)

![](https://static.igem.wiki/teams/5605/es/26.webp)

*Figure 26. GFP expression of TcpP-based TCA sensor in the kinetics and the stationary phase. Fluorescence / ABS600 was used to represent GFP expression. Error bars represent SD. The red box indicates the data used in plotting the stationary phase result.*

### Learn

Our sensor design finally succeeded at detecting changes in TCA concentrations. Although this sensor works only at low TCA concentrations, it is sufficient to act as a TCA sensor in the feline gut, considering the small amount of bile acid diluted into the entire intestinal lumen [(Washizu et al., 1990)](#ref12). However, there are many possible future experiments and improvements. First, we could set up a 2\*TAA-mutated version of this TcpP-based TCA sensor, just like what we have done in Cycles #3-4, to test the theoretical limit of this sensor's dynamic range. Further optimizations could be done by tuning RBS strengths for the three RBS used in the plasmid, as well as engineering the positioning of different sub-components of pCadBA. Even without further engineering and optimization, this sensor has already shown its promising functionality to be integrated into our overall platform.

## References

[↑](#overview) Barneda-Zahonero, B., Collazo, O., Azagra, A. *et al.* The transcriptional repressor HDAC7 promotes apoptosis and c-Myc downregulation in particular types of leukemia and lymphoma. *Cell Death Dis* *6*, e1635 (2015). <https://doi.org/10.1038/cddis.2014.594>

[↑](#cycle-1) LaFleur, T. L., Hossain, A., & Salis, H. M. (2022). Automated model-predictive design of synthetic promoters to control transcriptional profiles in bacteria. *Nature Communications*, *13*(1). <https://doi.org/10.1038/s41467-022-32829-5>

[↑](#cycle-1) Lei, H. T., Shen, Z., Surana, P., Routh, M. D., Su, C. C., Zhang, Q., & Yu, E. W. (2011). Crystal structures of CmeR-bile acid complexes from Campylobacter jejuni. *Protein Science: A Publication of the Protein Society*, *20*(4), 712–723. <https://doi.org/10.1002/pro.602>

[↑](#cycle-3) Lee, T.S., Krupa, R.A., Zhang, F. *et al.* BglBrick vectors and datasheets: A synthetic biology platform for gene expression. *J Biol Eng* *5*, 12 (2011). <https://doi.org/10.1186/1754-1611-5-12>

[↑](#cycle-1) Salis, H. M., Mirsky, E. A. & Voigt, C. A. (2009). Automated design of synthetic ribosome binding sites to control protein expression. *Nature Biotechnology*, *27*(10), 946–950. <https://doi.org/10.1038/nbt.1568>

[↑](#cycle-4) Nasr, M. A., Timmins, L. R., Martin, V. J. J., & Kwan, D. H. (2022). A Versatile Transcription Factor Biosensor System Responsive to Multiple Aromatic and Indole Inducers. *ACS Synthetic Biology, 11*(4), 1692–1698. <https://doi.org/10.1021/acssynbio.2c00063>

[↑](#cycle-4) Elkins, C. A., & Savage, D. C. (2003). CbsT2 from Lactobacillus johnsonii 100-100 is a transport protein of the major facilitator superfamily that facilitates bile acid antiport. *Journal of molecular microbiology and biotechnology*, *6*(2), 76–87. <https://doi.org/10.1159/000076738>

[↑](#cycle-5) Xue, Y., Tu, F., Shi, M., Wu, C. Q., Ren, G., Wang, X., Fang, W., Song, H., & Yang, M. (2016). Redox pathway sensing bile salts activates virulence gene expression in Vibrio cholerae. *Molecular microbiology*, *102*(5), 909–924. <https://doi.org/10.1111/mmi.13497>

[↑](#cycle-5) Yang, M., Liu, Z., Hughes, C., Stern, A. M., Wang, H., Zhong, Z., Kan, B., Fenical, W., & Zhu, J. (2013). Bile salt-induced intermolecular disulfide bond formation activates Vibrio cholerae virulence. *Proceedings of the National Academy of Sciences of the United States of America*, *110*(6), 2348–2353. <https://doi.org/10.1073/pnas.1218039110>

[↑](#cycle-5) Chang, H.-J., Zúñiga, A., Conejero, I., Voyvodic, P. L., Gracy, J., Fajardo-Ruiz, E., Cohen-Gonsaud, M., Cambray, G., Pageaux, G.-P., Meszaros, M., Meunier, L., & Bonnet, J. (2021). *Programmable receptors enable bacterial biosensors to detect pathological biomarkers in clinical samples*. *Nature Communications, 12*, 5216. [Programmable receptors enable bacterial biosensors to detect pathological biomarkers in clinical samples | Nature Communications](https://doi.org/10.1038/s41467-021-25538-y)

[↑](#cycle-5) Lindner, E., & White, S. H. (2014). Topology, dimerization, and stability of the single-span membrane protein CadC. *Journal of molecular biology*, *426*(16), 2942–2957. <https://doi.org/10.1016/j.jmb.2014.06.006>

[↑](#cycle-5) Washizu, T., Ikenaga, H., Washizu, M., Ishida, T., Tomoda, I., & Kaneko, J. J. (1990). Bile acid composition of dog and cat gall-bladder bile. *The Japanese Journal of Veterinary Science*, *52*(2), 423–425. <https://doi.org/10.1292/jvms1939.52.423>

{% endblock %}

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{% block lead %}Describe the research, experiments, and protocols you used in your project. It is designed to provide sufficient information for other teams to replicate our work.{% endblock %}
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## What Should this Page Contain?

---

Provide comprehensive, step-by-step protocols for all experiments conducted. Include a list of materials, reagents, and equipment used. Specify concentrations, volumes, incubation times, temperatures, and other critical parameters. Document any modifications or optimizations made to standard protocols.

Explain the purpose of each experiment and its relevance to your project goals. Describe the experimental design, including controls and replicates. Provide a clear rationale for the chosen methods and approaches.

Document any troubleshooting steps taken and optimizations made during the experimental process. Share any lessons learned that could benefit future teams.

## Inspirations

---

* [2024 Heidelberg](https://2024.igem.wiki/heidelberg/experiments)
* [2024 Marburg](https://2024.igem.wiki/marburg/experiments)
* [2024 EPFL](https://2024.igem.wiki/epfl/experiments)
* [2023 Estonia-TUIT](https://2023.igem.wiki/estonia-tuit/experiments)

{% endblock %}

{% extends "layout.html" %}
{% block page\_content %}

![cover-back](https://static.igem.wiki/teams/5605/results/result.webp)

## Menu

[Food Input Detection](#food-input-detection)

[Design and Construction of CmeR-based TCA Biosensors](#design-and-construction-of-cmer-based-tca-biosensors)
[The First Iteration of CmeR-Based TCA Biosensors](#the-first-iteration-of-cmer-based-tca-biosensors)
[The Second Iteration of CmeR-Based TCA Biosensors](#the-second-iteration-of-cmer-based-tca-biosensors)
[The Third Iteration of CmeR-Based TCA Biosensors](#the-third-iteration-of-cmer-based-tca-biosensors)
[The Fourth Iteration of CmeR-Based TCA Biosensors](#the-fourth-iteration-of-cmer-based-tca-biosensors)
[Design and Construction of the TcpP-Based TCA Biosensor](#design-and-construction-of-the-tcpp-based-tca-biosensor)
[Characterization of the TcpP-Based TCA Biosensor](#characterization-of-the-tcpp-based-tca-biosensor)

[IBD Biomarker Detection](#ibd-biomarker-detection)

[Design and Construction of Calprotectin Biosensors](#design-and-construction-of-calprotectin-biosensors)
[Characterization of Calprotectin Biosensors](#characterization-of-calprotectin-biosensors)

[Information Processing Module](#information-processing-module)

[Design and Construction of pAND](#design-and-construction-of-pand)
[Characterization of pAND](#characterization-of-pand)
[Design and Construction of Split T7-Based AND Gates](#design-and-construction-of-split-t7-based-and-gates)
[Characterization of Split T7-Based AND Gates](#characterization-of-split-t7-based-and-gates)
[Design and Construction of One-Plasmid Split T7 AND Gate](#design-and-construction-of-one-plasmid-split-t7-and-gate)
[Characterization of One-plasmid Split T7 AND Gate](#characterization-of-one-plasmid-split-t7-and-gate)

[Functional Output Module](#functional-output-module)

[Keratin Degradation](#keratin-degradation)
[Expression and purification of different keratinases](#expression-and-purification-of-different-keratinases)
[Verification of hairball degradation by keratinases](#verification-of-hairball-degradation-by-keratinases)
[Surface-display Results](#surface-display-results)
[Color Visual Display](#color-visual-display)

[Data Storage Module](#data-storage-module)

[Scheme, Design, and Construction](#scheme-design-and-construction)
[Recording the Orders of Transcriptional Events](#recording-the-orders-of-transcriptional-events)
[Characterizing Insertion Efficiencies of Cas1 Variants](#characterizing-insertion-efficiencies-of-cas1-variants)
[Troubleshooting Retron-Derived Spacer Acquisition](#troubleshooting-retron-derived-spacer-acquisition)
[Design and Construction of Genome Integration-Related Plasmids](#design-and-construction-of-genome-integration-related-plasmids)
[Insertion of CRISPR Array](#insertion-of-crispr-array)
[Plasmid Curing](#plasmid-curing)

[References](#reference)

### Food Input Detection

For the food detection module, we built and tested 4 CmeR-based TCA biosensors and 1 TcpP-based TCA biosensor.

#### Design and Construction of CmeR-based TCA Biosensors

In our plasmid design, we placed CmeR downstream of a constitutive promoter J23119(mut), and placed sfGFP as a reporter gene downstream of pCmeR. The design of pCmeR upstream to sfGFP has undergone additional rounds of engineering. First, a prototype of pCmeR was designed by using pQacR ([BBa\_J428050](https://parts.igem.org/Part%3ABBa_J428050)) as the template and then replacing *qacO* with *cmeO* (Nasr et al., 2022). Since the relative positioning of *cmeO* with -35 and -10 hexamers can greatly affect the interaction between transcription factor, CmeR repressor, and promoter region, we designed and tested multiple variants with different *cmeO* positioning, including downstream to -10 hexamer, overlapping with -35 hexamer, and within the spacer between the two hexamers (more details are described in our [Engineering Success](https://2025.igem.wiki/bnds-china/engineering) section). (Figure 1)

![](https://static.igem.wiki/teams/5605/hotfix/hotfix.webp)

*Figure 1. Plasmid designs for CmeR-based TCA sensors. Over the course of engineering and optimization, we tried different promoters upstream to CmeR [J23119 and J23119(mut)], pCmeR promoter with different cmeO placing, and different RBS upstream to GFP [B0031 and RBS(Bgl)]. For constitutive promoters and RBS, darker red color represents higher transcriptional or translational activity. Created by biorender.com.*

#### The First Iteration of CmeR-Based TCA Biosensors

We first tried to construct our first iteration of the CmeR-based TCA biosensor, pJ23119-CmeR\_pCmeR(-10)-B0031-GFPmut2 ([BBa\_25F4UCQM](https://registry.igem.org/parts/bba-25f4ucqm)). After we ordered the plasmid sequence from Tsingke, the company was unable to produce the correct sequence. To investigate the cause, we conducted *in silico* analyses using the Promoter Calculator and RBS Calculator algorithms of De Novo DNA (LaFleur et al., 2022; Salis et al., 2009). First, the predicted transcription initiation rates across the entire plasmid revealed a significant peak of 40055 au at 1245 bp on the reverse strand, corresponding to the site of J23119-CmeR transcriptional unit (Figure 2). Second, a high translation rate of the full-length CmeR protein was also identified by prediction (Figure 3). Based on these predictions and previous literature results (Barneda-Zahonero et al., 2015), we hypothesized that CmeR is expressed at excessively high levels, which may lead to cellular toxicity.

![](https://static.igem.wiki/teams/5605/results/2.webp)

*Figure 2. The De Novo DNA Promoter Calculator result of the original design, pJ23119-CmeR\_pCmeR(-10)-B0031-GFPmut2. The black circle indicates the peak in transcription initiation rate of the J23119-CmeR transcriptional unit.*

![](https://static.igem.wiki/teams/5605/results/3.webp)

*Figure 3. Translation initiation rates of the mRNA encoding CmeR. The red circle suggests a peak in CmeR translation initiation, indicating the translation of the full-length CmeR protein.*

#### The Second Iteration of CmeR-Based TCA Biosensors

Hence, we turned down CmeR expression in our second TCA biosensor, pJ23119(mut)-CmeR\_pCmeR(-10)-B0031-GFPmut2 ([BBa\_25A12OMH](https://registry.igem.org/parts/bba-25a12omh)), by mutating the strong constitutive promoter J23119 into a weaker variant. This plasmid was successfully constructed and transformed into *E. coli* Trelief 5α, which indicates that placing CmeR under the control of a weaker promoter effectively alleviated the toxicity issue. In solid inoculation, however, the colonies showed significant levels of green fluorescence in the absence of inducers. This result indicates that our second design has a high leaky expression of GFP.

#### The Third Iteration of CmeR-Based TCA Biosensors

We then designed and constructed our third iteration of the CmeR-based TCA biosensor, pJ23119(mut)-CmeR\_pCmeR(-35)-RBS(Bgl)-sfGFP ([BBa\_25E1I21E](https://registry.igem.org/parts/bba-25e1i21e)), where we changed the positioning of *cmeO* from downstream of -10 motif into overlapping with -35 motif, and replaced the RBS downstream to pCmeR into a stronger one to ensure significant GFP expression in the presence of TCA. Further, we designed and constructed pJ23119(mut)-CmeR(2\*TAA)\_pCmeR(-35)-RBS(Bgl)-sfGFP ([BBa\_256FO3O6](https://registry.igem.org/parts/bba-256fo3o6)) as a control without full-length CmeR.

We transformed both plasmids into *E. coli* Trelief 5α for cloning, and the former into *E. coli* Nissle 1917 for the kinetics assay. The detailed plate setup in the assay is shown in Figure 4.

![](https://static.igem.wiki/teams/5605/results/4.webp)

*Figure 4. Plate layout of kinetics assay for pJ23119(mut)-CmeR\_pCmeR(-35)-RBS(Bgl)-sfGFP.*

The results of the kinetics assay were used to calculate the fluorescence / ABS600 curve. The normalized curve of the groups and the stationary phase result both showed no significant differences in fluorescence as TCA concentration changes (Figure 5).

![](https://static.igem.wiki/teams/5605/results/5.webp)

*Figure 5. GFP expression of pJ23119(mut)-CmeR\_pCmeR(-35)-RBS(Bgl)-sfGFP in the kinetics and the stationary phase. Fluorescence / ABS600 was used to represent GFP expression. Error bars represent SD. The red box indicates the data used in plotting the stationary phase result.*

We then conducted a solid inoculation of the control plasmid, pJ23119(mut)-CmeR(2\*TAA)\_pCmeR(-35)-RBS(Bgl)-sfGFP. All colonies showed little or no green fluorescence. The results collectively suggest that placing *cmeO* overlapping with the -35 region of pCmeR excessively weakens promoter activity, leading to very low GFP expression even in the absence of repression by CmeR.

#### The Fourth Iteration of CmeR-Based TCA Biosensors

We then considered another positioning of *cmeO* by putting it in the spacer region between the -10 and -35 motifs in pCmeR. Following this, we designed and constructed our fourth CmeR-bassed biosensor, pJ23119(mut)-CmeR\_pCmeR(spacer)-RBS(Bgl)-sfGFP ([BBa\_25RC9Z6P](https://registry.igem.org/parts/bba-25rc9z6p)). Similar to the third iteration, we also constructed a control plasmid without full-length CmeR, pJ23119(mut)-CmeR(2\*TAA)\_pCmeR(spacer)-RBS(Bgl)-sfGFP ([BBa\_25UQXNE7](https://registry.igem.org/parts/bba-25uqxne7)).

The plasmid with 2\*TAA mutation was transformed into *E. coli* Trelief 5α, and solid inoculation was performed. All colonies showed green fluorescence as expected. This shows that pCmeR's transcriptional rate is high enough without the binding of CmeR to activate downstream expression.

We then conducted a qualitative characterization of pJ23119(mut)-CmeR\_pCmeR(spacer)-RBS(Bgl)-sfGFP. The group with TCA++ showed no induction compared to the group without TCA, and neither of the two groups showed green fluorescence (Figure 6).

![](https://static.igem.wiki/teams/5605/results/6.webp)

*Figure 6. Qualitative test of pJ23119(mut)-CmeR\_pCmeR(spacer)-RBS(Bgl)-sfGFP using TCA. TCA (++), 1mM TCA added. TCA (-), no TCA added.*

To explore the unexpected result, we set up another qualitative test of this sensor using salicylate, which has been shown to be another inducer of pCmeR (Nasr et al., 2022). As shown in Figure 7, the tube in the presence of salicylate showed higher green fluorescence. These results indicate that our sensor can respond to salicylate but not TCA.

![](https://static.igem.wiki/teams/5605/results/7.webp)

*Figure 7. Qualitative test of pJ23119(mut)-CmeR\_pCmeR(spacer)-RBS(Bgl)-sfGFP using salicylate. Salicylate (++), 1mM salicylate added. Salicylate (-), no salicylate added.*

After analyzing our experimental results and reviewing relavent literature (Elkins & Savage, 2003; Lei, 2011), we concluded that the problem likly lies in the poor membrane permeability of TCA. This suggest that this sensor design relying on the cytoplasmic repressor CmeR is unlikely to function.

#### Design and Construction of the TcpP-Based TCA Biosensor

Driven by the limitations of the CmeR-based TCA sensor, we designed another TCA biosensor based on the transmembrane sensor CadC-TcpP and its regulated promoter pCadBA.

In our plasmid design, CadC-TcpP and TcpH were placed downstream of two distinct constitutive promoters, P9 and apFAB339, because the relative expression levels of CadC-TcpP and TcpH under this combination of promoters were tested to have optimal sensing performance (Chang et al, 2021). sfGFP was used as the reporter and was placed downstream of pCadBA. In the presence of TCA, the CadC DNA-binding domain binds to pCadBA, initiating transcription of sfGFP. (Figure 8). The resulting plasmid was designated pTcpP-sfGFP ([BBa\_25XJ1XUG](https://registry.igem.org/parts/bba-25xj1xug)).

![](https://static.igem.wiki/teams/5605/results/8.webp)

*Figure 8. Plasmid design of TcpP-based TCA sensor, pTcpP-sfGFP. Created by biorender.com.*

#### Characterization of the TcpP-Based TCA Biosensor

We transformed the TcpP-based TCA sensor into *E. coli* Trelief 5α for plasmid construction and verification, and into *E. coli* Nissle 1917 for the kinetics assay. The detailed plate setup in the assay is shown in Figure 9.

![](https://static.igem.wiki/teams/5605/results/9.webp)

*Figure 9. Plate layout of the kinetics assay for pTcpP-sfGFP.*

The results of the kinetics assay were used to calculate the fluorescence / ABS600 curve. The normalized curve of the groups and the stationary phase result indicate that fluorescence level is positively correlated with TCA concentration with TCA concentration below 125 μM. Above 125 μM, however, the fluorescence level stays the same regardless of TCA concentration. Overall, this sensor has achieved a >20-fold dynamic range, showing promising functionality to be integrated into our overall platform. (Figure 10)

![](https://static.igem.wiki/teams/5605/results/10.webp)

*Figure 10. GFP expression of pTcpP-sfGFP in the kinetics and the stationary phase. Fluorescence / ABS600 was used to represent GFP expression. Error bars represent SD. The red box indicates the data used in plotting the stationary phase result.*

### IBD Biomarker Detection

#### Design and Construction of Calprotectin Biosensors

We built two constructs of ykgMO-based calprotectin biosensor in *E. coli* Nissle 1917, which was described in previous literature (Zhu et al., 2025; Figure 11). In the first design, the reporter plasmid carries a ykgMO promoter-driven sfGFP on the ColE1 backbone, while Zur expression is supplied only from its native locus on the EcN genome. In the second design, supplemental Zur expression was provided by expressing Zur under the constitutive promoter J23109 on the same backbone as the reporter. This supplemental Zur expression is intended to reduce basal expression and expand the dynamic range of the sensor.

![](https://static.igem.wiki/teams/5605/results/11.webp)

*Figure 11. Constructs of ykgMO-based calprotectin sensor. A, ykgMO-GFP without supplemental Zur expression on a ColE1 backbone. B, ykgMO-GFP with supplemental Zur expression by placing the CDS of Zur downstream to a J23109 promoter. Created by biorender.com.*

#### Characterization of Calprotectin Biosensors

Due to the high cost and difficulty in obtaining calprotectin, we chose N,N,N,N-Tetrakis(2-pyridylmethyl)ethylenediamine (TPEN) as a substitute for calprotectin in our assays, which is supported by previous research (Zhu et al., 2025).

First, we performed a fluorescence intensity kinetics assay to quantitatively test the effectiveness of the ykgMO-GFP sensor. Cultures of *E. coli* Nissle 1917 transformed with the constructed plasmid were grown across a gradient of TPEN concentrations. The value of fluorescene / ABS600 was recorded over time with a plate reader to quantify GFP expression levels (Figure 12).

As shown in Figure 12, the ykgMO-GFP sensor showed a significant induction by TPEN. The fluorescent levels remained near baseline for TPEN concentrations below 2μM; as the TPEN concentration increased to 4μM and above, the fluorescent levels exhibited a significant rise from the baseline, indicating the construction of ykgMO-sfGFP to be successful (Figure 12). However, since this sensor has a high leaky expression due to insufficient Zur expression, the dynamic range of this detection system was only about 3-fold.

![](https://static.igem.wiki/teams/5605/results/12.webp)

*Figure 12. GFP expression of ykgMO-GFP in the kinetics and the stationary phase. Fluorescence / ABS600 was used to represent GFP expression. Error bars represent SD. The red box indicates the data used in plotting the stationary phase result.*

We then aimed to enhance the dynamic range of our biosensor. Inspired by Zhu et al. (2025), we supplemented Zur expression in our plasmid by placing it downstream of the constitutive promoter J23109. We called this plasmid Zur-ykgMO-sfGFP.

We again perform a fluorescence intensity kinetics assay to quantitatively test the performance of this biosensor. As shown in Figure 13, the results aligned with our expectations, in which the dynamic range of our Zur-ykgMO-GFP sensor was about 134-fold, much higher compared to that of the former system. Therefore, the Zur-ykgMO-GFP system demonstrated its ability to be integrated into our platform design as the calprotectin biosensor.

![](https://static.igem.wiki/teams/5605/results/13.webp)

*Figure 13. GFP expression of Zur-ykgMO-sfGFP in the kinetics and the stationary phase. Fluorescence / ABS600 was used to represent GFP expression. Error bars represent SD. The red box indicates the data used in plotting the stationary phase result.*

## Information Processing Module

We constructed and tested two systems that achieve the AND gate logic. The first is a promoter-repressor transcriptional system, which combines transcriptional control elements to enforce dual-input dependence (Stanton et al., 2014). The second is a split T7 RNA polymerase (RNAP)-based protein-level system, in which functional RNAP activity is restored only when both inputs are present (Schaerli et al., 2014).

### Design and Construction of pAND

In our plasmid design of pAND ([BBa\_25NC4UDH](https://registry.igem.org/parts/bba-25nc4udh)), the constitutively expressed LacI repressor inhibits the Tac promoter, while TetR repressor inhibits the Tet promoter. The PhIF and QacR coding sequences were placed downstream of the pTac and pTet promoters, respectively. Their cognate promoters, pPhlF and pQacR, are arranged in series to control the expression of BetI, which in turn represses pBetI and thereby controls the expression of reporter gene downstream of pBetI (Figure 14).

Upon induction of IPTG and aTc, LacI and TetR are inactivated, allowing transcription from pTac and pTet and enabling production of PhlF and QacR. These repressors then bind to their targets upstream of betI, suppressing its transcription. As a result, under double induction, BetI is not expressed, pBetI repression is relieved, and fluorescent protein is expressed.

![](https://static.igem.wiki/teams/5605/results/14.webp)

*Figure 14. Plasmid design of pAND. Created by biorender.com.*

### Characterization of pAND

To verify the functionality of pAND, we first conducted a qualitative assay. Four cultures of *E. coli Trelief* 5α transformed with the pAND plasmid were grown under different induction conditions: no inducers, aTc (200nM) only, IPTG (1000μM) only, and both aTc (200nM) and IPTG (1000μM). Visible green fluorescence was only observed in the group treated with both inducers, while no fluorescence was detected in any of the other groups (Figure 15).

![](https://static.igem.wiki/teams/5605/results/15.webp)

*Figure 15. Qualitative assay results for pAND. (-/-), no inducer added. (+/-), 1000μM IPTG added. (-/+), 200nM aTc added. (+/+), 1000μM IPTG and 200nM aTc added.*

To further assess the inducibility and logical performance of the pAND circult, we conducted a quantitative kinetics assay to characterize its input-output activity. Gradients of aTc/IPTG concentrations was applied to *E. coli* *EcN* cultures, and the fluorescence/Abs600 values were measured over time using a plate reader. The resulting heatmap illustrates the steady-state fluorescence/Abs600 ratio. (Figure 16)

![](https://static.igem.wiki/teams/5605/results/16.avif)

*Figure 16: Heat map displaying the steady-state fluorescence response of the pAND circult under varying IPTG and aTc concentrations.*

The data revealed a **~60-fold** dynamic range, with maximum induction at 200nM aTc and 1mM IPTG, indicating that the system could effectively switch between on and off states.

### Design and Construction of Split T7-Based AND Gates

To evaluate the split T7-based AND gate, we designed and constructed four plasmids. The first two plasmids encode the two subunits of split T7 RNA polymerase, regulated respectively by the Lac operon and the L-arabinose operon, and they vary in RBS strength: pT7-RNAP strong ([BBa\_25IM9T2N](https://registry.igem.org/parts/bba-25im9t2n)) and pT7-RNAP weak ([BBa\_25TBOJB2](https://registry.igem.org/parts/bba-25tbojb2)). The other two plasmids expresses sfGFP under the control of T7 promotor, also with varied RBS strength: pT7-reporter strong ([BBa\_25UKROJT](https://registry.igem.org/parts/bba-25ukrojt)) and pT7-reporter weak ([BBa\_2538U45C](https://registry.igem.org/parts/bba-2538u45c)). Figure 17 shows the details of plasmid designs.

![](https://static.igem.wiki/teams/5605/results/17.avif)

*Figure 17. Plasmid designs of the split T7 system with different RBS strengths. The two pT7-RNAP plasmids are shown as the circular system at the top, and the two pT7-reporter plasmids are shown as the linear system at the bottom. Created with BioRender.com.*

The four possible plasmid combinations, each consisting of one pT7-RNAP plasmid and one pT7-reporter plasmid, yielded four functional systems implementing the AND gate logic. These combinations were designated as follows:

T7-split\_strong–strong ([BBa\_25IM9T2N](https://registry.igem.org/parts/bba-25im9t2n) + [BBa\_25UKROJT](https://registry.igem.org/parts/bba-25ukrojt))
T7-split\_strong–weak ([BBa\_25IM9T2N](https://registry.igem.org/parts/bba-25im9t2n) + [BBa\_2538U45C](https://registry.igem.org/parts/bba-2538u45c))
T7-split\_weak–strong ([BBa\_25TBOJB2](https://registry.igem.org/parts/bba-25tbojb2) + [BBa\_25UKROJT](https://registry.igem.org/parts/bba-25ukrojt))
T7-split\_weak–weak ([BBa\_25TBOJB2](https://registry.igem.org/parts/bba-25tbojb2) + [BBa\_2538U45C](https://registry.igem.org/parts/bba-2538u45c)).

We then tested the effectiveness of each system by co-transforming plasmid pairs with the respective RBS strengths and measuring their output.

### Characterization of Split T7-Based AND Gates

We first performed qualitative fluorescence assays under UV light for all four systems. We set up four different groups of inducers for each system: no inducers; IPTG only; arabinose only and both IPTG and arabinose. Ideally, green fluorescence should only appear when both inducers are present. (Figure 18)

The qualitative assays indicated successful induction when both IPTG and arabinose are present for all constructs, but with different degrees of leakage. For the strong-strong combination (Figure 18A), fluorescence is present in the no inducers group and arabinose only groups, indicating leakage from both IPTG and arabinose inducible promoters. In the strong-weak and weak-strong constructs (Figure 18B and 18C), fluorescence is observed in the group with both inducers and the arabinose only group. This might be the result of IPTG-inducible promoter leakage. The weak-weak construct showed detectable fluorescence only in the group with both inducers (Figure 18D), indicating tighter control. However, the fluorescence is weaker compared to others, which may be caused by the weak RBS strength in both plasmids.

![](https://static.igem.wiki/teams/5605/results/18.webp)

*Figure 18. Qualitative assay results of four combinations of split T7 RNAP system. (-/-), no inducer added. (+/-), 100μM IPTG added. (-/+), 10000μM arabinose added. (+/+), 100μM IPTG and 10000μM arabinose added. A, T7-split\_strong–strong. B, T7-split\_strong–weak. C, T7-split\_weak–strong. D, T7-split\_weak–weak.*

We further conducted kinetics assays and quantitatively evaluated the performances of all four systems by testing them across a matrix of arabinose and IPTG concentrations.

Successful induction was confirmed for each construct, with maximum normalized signal at 10,000µM arabinose and 100 µM IPTG. **T7-split\_strong–strong** shows a relatively high dynamic range of **~328-fold**. The T7-split\_strong-weak construct exhibited a maximum normalized fluorescence of approximately 215 units, resulting in a dynamic range of **~215-fold**. **T7-split\_weak–weak** produced the weakest response, only **~55-fold** induction, consistent with the weak fluorescence shown in the qualitative assay. The strongest response and highest dynamic range is for **T7-split\_weak–strong.** It reached a maximum of 562 normalized fluorescent level units, giving a dynamic range of 562-fold.

![](https://static.igem.wiki/teams/5605/results/19.webp)

*Figure 19. Heat map displaying quantitative kinetics results of four combinations in split T7 RNAP system. A, T7-split\_strong–strong. B, T7-split\_strong–weak. C, T7-split\_weak–strong. D, T7-split\_weak–weak.*

Based on both the qualitative and the quantitative assays, we considered the system T7-split\_weak–strong as the optimal combination.

### Design and Construction of One-Plasmid Split T7 AND Gate

We wanted to assess the performance of the split T7 system when put into one single plasmid. Based on the previous kinetics assay results, we integrated the optimal combination ,pT7-RNAP weak and pT7-reporter strong, to construct the one-plasmid split T7 AND gate ([BBa\_25YVR8VN](https://registry.igem.org/parts/bba-25yvr8vn), Figure 20).

![](https://static.igem.wiki/teams/5605/results/20.avif)

*Figure 20. Plasmid design of split T7 system with optimal RBS combination. Created by biorender.com.*

### Characterization of One-plasmid Split T7 AND Gate

To confirm the functionality of one-plasmid split T7 RNAP system, we first conducted a qualitative assay with four treatment conditions: absence of inducers, arabinose only, IPTG only, and both arabinose and IPTG together. The (+/+) group showed the most significant fluorescence. However, in groups with IPTG or arabinose only, faint fluorescence was also observed, indicating the problem of leakage still persists. (Figure 21)

![](https://static.igem.wiki/teams/5605/results/21.webp)

*Figure 21. Qualitative assay results for All-in-one Split T7 RNAP system; (-/-), no inducer added. (+/-), 100μM IPTG added, (-/+), 10000μM arabinose added, (+/+), 100μM IPTG and 10000μM arabinose added.*

We further conducted a kinetics assay and quantitatively evaluated the performances of this system by testing it across a matrix of arabinose and IPTG concentrations. The quantitative assay showed successful induction, with a **~39-fold** dynamic range (Figure 22). However, this dynamic range is significantly lower compared to the two-plasmid construct. There is also significant leakage in GFP expression in the absence of arabinose. (Figure 22) One plausible explanation is that, after combining the modules into a single plasmid, the replication origin was changed from a high-copy ColE1 to a medium-copy p15A backbone. This alteration could disrupt the expression balance between the split T7 components and the reporter gene, leading to uncoordinated transcriptional output. Additionally, the presence of multiple inducible promoters on the same plasmid may cause promoter interference and transcriptional leakage, jointly contributing to the elevated basal expression and reduced dynamic range.

![](https://static.igem.wiki/teams/5605/results/22.webp)

*Figure 22. Heat map displaying quantitative kinetics results of one-plasmid Split T7 system.*

## Functional Output Module

### Keratin Degradation

We identified four keratinase variants and constructed seven expression plasmids encoding each keratinase with or without its native signal peptide. The expressed proteins were purified and verified by SDS–PAGE analysis. Successfully expressed and purified keratinases were subsequently characterized through cat hair degradation assays to evaluate their enzymatic activity.

### Expression and purification of different keratinases

In our plasmid design of keratinases, IPTG was added to induce their expression (Figure 23). All keratinase DNA sequences and the vector pET-28a(+) were synthesized and obtained from Tsingke.

![](https://static.igem.wiki/teams/5605/results/23.webp)

*Figure 23. Plasmid design of 7 plasmids that express different keratinases with or without the native signal peptide. Created by biorender.com.*

To evaluate the expression of keratinase candidates from different bacterial sources, the proteome of IPTG-induced *E. coli* cultures was analyzed by SDS–PAGE (Figure 24).

In the initial two rounds of expression and analysis, temperature optimization was conducted to compare induction at 25 °C and 37 °C (Figures 24A and 24C). A markedly stronger and thicker band near 40kDa was observed at 37 °C, indicating a higher expression. Therefore, 37 °C was selected as the optimal induction temperature for subsequent experiments.

Previous studies have shown that the presence of a native signal peptide can interfere with the expression and catalytic activity of keratinases. To test this effect, we constructed both full-length and signal-peptide-removed variants for each keratinase candidate. Distinct bands at approximately 40 kDa corresponded to the successful expression of keratinases KrMKU3, KrLCB12, KrMKU3-signal-peptide-removed, and KrLCB12-signal-peptide-removed (Figure 24C, Lanes 3, 5, 9; Figure 24D, Lane 3). Theoretical molecular weights of each keratinase are summarized in Table 1. For KrOcL9, only the signal peptide–removed variant was successfully expressed (Figure 24B, Lane 7), while the full-length construct showed no expression (Figure 24B, Lane 3). This suggests that the native *Ornithinibacillus caprae* signal peptide may not be efficiently recognized or processed by *E. Coli*. In contrast, KrUS575 exhibited no detectable expression across multiple induction and analysis attempts (Figures 24A–D), implying low expression efficiency or instability of the protein in *E. coli*.

![](https://static.igem.wiki/teams/5605/results/24.webp)

*Figure 24. SDS–PAGE analysis of recombinant keratinase expression in E. coli induced with 1 mM IPTG. Expression of keratinases was analyzed after induction under different temperatures. (A) Expression of KrLCB12, KrMKU3, their signal-peptide-removed variants (ΔSP), KrOcL9, KrUS575, and wild-type (WT) at 25 °C. (B) Expression of KrOcL9, KrUS575, and KrOcL9 ΔSP at 37 °C. (C) Expression of KrLCB12, KrMKU3, their ΔSP variants, KrOcL9, KrUS575, and WT at 37 °C. (D) Expression of KrLCB12 ΔSP, KrOcL9, and KrUS575 at 37 °C.*

|  |  |
| --- | --- |
| Keratinase | Molecular weight (kDa) |
| KrLCB12 | 40.985 |
| KrMKU3 | 40.989 |
| KrLCB12-signal-peptide-removed | 37.862 |
| KrMKU3-signal-peptide-removed | 37.831 |
| KrOcL9 | 44.743 |
| KrUS575 | 41.737 |
| KrOcL9-signal-peptide-removed | 42.055 |

*Table 1. The theoretical molecular weights of each keratinase.*

To obtain purified keratinases for downstream enzyme activity assays, Ni²⁺-NTA affinity chromatography was employed. (see protocol) Crude lysates from IPTG-induced *E. coli* cultures were loaded onto the column, followed by sequential washes with increasing concentrations of imidazole (10–1000 mM). Eluted fractions were collected and analyzed by SDS–PAGE.

Distinct bands at approximately 40 kDa confirmed the successful purification of KrMKU3, KrMKU3-signal-peptide-removed, and KrOcL9-signal-peptide-removed (Figure 25A-B and 25D-E). These purified samples were subsequently used for enzymatic assays. When purifying KrLCB12, we used two imidazole concentrations (10mM and 350mM) only. Multiple bands were seen in every purified sample (Figure 3C), indicating failure in purification. We did not do further testing on it due to time constraints.

![](https://static.igem.wiki/teams/5605/results/25.webp)

*Figure 25. SDS–PAGE analysis of purified keratinases. Purified keratinases were analyzed by SDS–PAGE to confirm expression and integrity. (A) KrMKU3; (B) KrMKU3 with its signal peptide removed; (C) KrLCB12; (D) KrOcL9 with signal peptide removed; (E) KrOcL9 with signal peptide removed eluted under a higher imidazole concentration.*

In contrast, KrLCB12-signal-peptide-removed exhibited abnormal behavior during purification. After cell lysis, the crude lysate formed a whitish, viscous pellet, suggestive of inclusion body formation. To confirm this, both soluble (supernatant) and insoluble (pellet) fractions were analyzed by SDS–PAGE. The target protein band (~40 kDa) was observed only in the pellet (Figure 26), confirming that KrLCB12-signal-peptide-removed version was expressed predominantly in an insoluble form.

![](https://static.igem.wiki/teams/5605/results/26.avif)

*Figure 26. SDS–PAGE verification of KrLCB12-signal-peptide-removed pellet and supernatant.*

Given that our probiotic chassis must express keratinases in a soluble and active conformation for in vivo keratin degradation, proteins forming inclusion bodies are unsuitable for application. Therefore, the krLCB12-signal-peptide-removed version was excluded from subsequent analyses.

### Verification of hairball degradation by keratinases

The effect of hair degradation is measured by Folin-Ciocalteous (FC) reagent. It can detect tyrosine, and the phenolic group of tyrosine reduces the reagent’s tungstate and molybdate components, which generates a blue chromophore. When the keratinase degrades hair, tyrosine is released, thus the blue color-change will be more significant (Figure 27).

![](https://static.igem.wiki/teams/5605/results/27.avif)

*Figure 27. Folin-Ciocalteous reagent principle.*

We performed a BCA assay to measure the concentration of the keratinases. The standard curve exhibits strong linear correlation, with R²=0.9714 and formula y=2.051+0.325. Based on the standard curve (Figure 28), the concentration of krMKU3 is 12.14 mg/mL, krMKU3-signal-peptide-removed is 7.10 mg/mL, krOcL9-signal-peptide-removed is 11.49 mg/mL. For subsequent enzymatic assays, all samples were diluted to 2 mg/mL to ensure consistent substrate loading.

![](https://static.igem.wiki/teams/5605/results/28.avif)

*Figure 28.* *Standard curve* *of BCA protein quantification.*

We first established a standard curve calibration for the FC assay. As a qualitative demonstration, we tested L-tyrosine samples at concentrations of 0, 27.5, 55, 110, 165, 220, 275, 550, and 1100 µM, which exhibited a clear blue color gradient that intensified with increasing tyrosine concentration (Fig.29). For quantitative calibration, we refined the concentration range to 0, 27.5, 55, 110, 220, 275, 550, 825, and 1100 µM to ensure optimal curve fitting and dynamic range coverage. The absorbance at 660 nm of each sample was measured using a spectrophotometer, and the resulting standard curve showed a strong linear correlation between absorbance and tyrosine concentration (R² = 0.9959, Fig. 29b), confirming the reliability of the calibration for converting measured absorbance values into corresponding tyrosine concentrations.

![](https://static.igem.wiki/teams/5605/results/29.avif)

*Figure 29. Folin-Ciocalteous assay standard curve. Calibration of the Folin–Ciocalteu assay using L-tyrosine standards. A, The color gradient of L-tyrosine solutions at concentrations of 0–1100 µM after reacting with the Folin–Ciocalteu reagent. Deeper blue coloration was produced as the tyrosine concentration increased. The 15 mL tubes were arranged across two racks and later combined into a single image for display. All samples were processed simultaneously in the same experiment. B, Standard curve generated by plotting Abs600 against tyrosine concentration, showing a strong linear correlation (R² = 0.9959)*

The keratinolytic activities of krMKU3, krMKU3-signal-peptide-removed, and krOcL9-signal-peptide-removed were assessed using shed cat hair as a natural keratin substrate, which had been approved for use by the iGEM Safety Committee. All three enzymes generated a distinct blue coloration upon reaction with the Folin–Ciocalteu reagent, confirming their ability to degrade keratin (Figure 30A). Quantitative measurements of absorbance at 660 nm (A₆₆₀) indicated comparable catalytic efficiency among the three, with krMKU3 exhibiting the highest specific activity (81 U mg⁻¹) (Figure 30B, Table 2). However, KrOcL9 (no signal peptide) exhibited a noticeably larger standard deviation, primarily due to one abnormally low outlier measurement (Fig. 30B).

![](https://static.igem.wiki/teams/5605/results/30.avif)

*Figure 30. Keratinase activity characterization by Folin–Ciocalteu (FC) assay using cat hair as the substrate. A, Colorimetric results of FC assay reactions. B, Quantification of keratinase activity based on Abs660 (left axis) and the corresponding amount of released tyrosine in nmol (right axis).*

One unit of enzyme activity was defined as the amount of enzyme activity required to increase the absorbance at 660 nm by 0.01. The enzymes in each group were all supplied at 1 mg (0.33mg/mL for 3mL). All three enzymes showed activity in degrading cat hair. With activity at 81 U/mg, krMKU3 showed the highest activity among the three enzymes. This is further confirmed by calculation of tyrosine released as a more absolute term (Table 2). Thus, we will choose KrMKU3 as our output keratinase to ensure maximum effect.

<style> td {white-space:nowrap;border:0.5pt solid #dee0e3;font-size:10pt;font-style:normal;font-weight:normal;vertical-align:middle;word-break:normal;word-wrap:normal;}</style>

|  |  |  |  |  |
| --- | --- | --- | --- | --- |
| Sample name | Blank control | KrMKU3 | KrMKU3-signal-peptide-removed | KrOcL9-signal-peptide-removed |
| OD660 | 0.23 | 1.04 | 0.954 | 0.879 |
| change in OD660 | - | 0.81 | 0.724 | 0.649 |
| Enzyme Activity (U/mg) | - | 81 | 72.4 | 64.9 |
| Tyrsoine released (nmol) | - | 972 | 868.8 | 778.8 |

*Table 2. Calculated enzyme activity for different keratinases*

#### Surface-display Results

We examined the fluorescence emitted from *E. coli* cells that expressed sfGFP plasmids with or without the INPNC tag. Cells transformed with pET28a(+)-INPNC-linker-sfGFP showed a distinct peripheral ring of fluorescence surrounding a dark intracellular region. (Figure 31C), indicating successful surface localization of sfGFP via the INPNC tag. By contrast, cells harboring the pET28a (+) - sfGFP without the INPNC linker showed uniform intracellular fluorescence, consistent with cytoplasmic localization rather than membrane anchoring. (Figure 31B) These results confirm that the INPNC tag is essential for achieving surface display of sfGFP.

Interestingly, the dotted fluorescent background around the rod-shaped cells likely reflects leakage or release of unanchored fluorescent proteins resulting from overexpression of the INPNC fusion construct. This observation is also consistent with our PI's previous experimental findings reported during the iGEM 2018 project ([https://2018.igem.org/Team:BJRS\_China/Results](https://2018.igem.org/Team%3ABJRS_China/Results))

![](https://static.igem.wiki/teams/5605/results/31.avif)

*Figure 31: Super-resolution microscopy of INPNC-mediated surface display. Captured using Opera Phenix Plus High-Content Imaging System, parameters: 63xfluorescent microscopy,excitation:488nm; emission filter: 500-550nm; laser power:100%; exposure time: 100ms A, Negative control: cells transformed with empty pET28a(+) vector show no detectable fluorescence but only background noise; B, sfGFP control: cells expressing pET28a(+)-sfGFP exhibit uniform intracellular fluorescence; C, INPNC surface display: cells expressing pET28a(+)-INPNC-linker-sfGFP display a distinct peripheral fluorescence ring surrounding a dark intracellular region, confirming successful surface localization of sfGFP via the INPNC tag. The surrounding fluorescence is the secreted GFP.*

### Color Visual Display

We expressed 25 fluorescent proteins and 9 chromoproteins from the iGEM distribution kit by constructing 34 plasmids with pSB1C3 backbone, each constitutively expressing one protein under J23110. (Figure 32)

![](https://static.igem.wiki/teams/5605/results/32.avif)

*Figure 32. Plasmid designs of the color visual display module and the proteins involved. A, plasmid design of color signal module. B, proteins involved. Created by biorender.com.*

We first conducted an initial screening under either normal or UV light conditions to assess the degree of color visibility. All 25 fluorescent proteins were placed under UV light for excitation. In addition, the chromoprotein amajLime ([BBa\_K1033916](https://parts.igem.org/Part%3ABBa_K1033916)) was also placed under UV light, since its characterization by previous iGEM team UAlberta 2019 showed that the color was most visible under UV light. Apart from that, all 8 other chromoproteins were placed under normal light. (Figure 33)

![](https://static.igem.wiki/teams/5605/results/33.avif)

*Figure 33. The initial screening of 25 fluorescent proteins and 9 chromoproteins.*

Based on the results shown in Figure 1002, we selected the nine most visible proteins for the next round of selection: SYFP2, TannenRFP, amilRFP, spisPink, aeBlue, gfasPurple, amilCP; eechGFP3, and afraGFP.

The secondary screening was performed by mixing color signaling *E. coli* with fake feline feces, made by mixing 2.0g curry powder, 100μL soy sauce and 500μL water. We compared the mixtures under both UV and normal lighting conditions to evaluate both fluorescence and color change. Our results indicated that amilRFP and gfasPurple exhibited the most significant color change under normal light, while afraGFP displayed the most prominent fluorescence. (Figure 34)

![](https://static.igem.wiki/teams/5605/results/34.avif)

*Figure 34. The second screen of bacteria-curry mixtures of 5 fluorescent proteins and 4 chromoproteins. A, under normal light. B, under UV light.*

Thus, in our final product, we will use these three proteins as our reporters to meet the need for color display and the color preference of different customers.

## Data Storage Module

### Scheme, Design, and Construction

Retro-Cascorder harnesses the Cas1–Cas2 adaptation machinery together with a retron module to capture transcriptional events in real time (Figure 35A). When a promoter of interest is activated, it drives transcription of a non-coding RNA (retron-ncRNA) containing specific barcodes, which is then reverse-transcribed by a constitutively expressed retron reverse transcriptase (retron-RT) into complementary DNA. These DNA fragments are subsequently integrated into the CRISPR array as new spacers. Besides retron-derived spacers, Cas1–Cas2 also incorporates spacers derived from other double-stranded DNA sources such as the host genome or plasmids. These non-retron-derived spacers, collectively referred to “N,” accumulate alongside retron-derived spacers during the course of recording. Thus, each array can contain three types of spacers: retron-derived spacers corresponding to signal A or B, and background spacers denoted as N. Over time, the sequential acquisition of A, B, and N spacers forms a chronological record within the CRISPR array, which can be decoded by sequencing to reconstruct the order of transcriptional events. (Bhattarai-Kline et al., 2022)

This scheme was implemented by two plasmids that together enable the generation of retron-derived DNA barcodes and their integration into the CRISPR array (Figure 35B-C). The first plasmid is called expression plasmid, which carries the Cas1–Cas2 adaptation machinery along with the Eco1 retron reverse transcriptase (RT). The expression of Cas1 and Cas2 is controlled by a LacI-regulated T7 promoter, and the Eco1 RT is constitutively expressed by the J23115 promoter. The T7 RNA Polymerase (RNAP) is expressed on *E. coli* BL21(AI) genome, which is induced by arabinose. Therefore, both arabinose and IPTG are required to activate the integration machinery by turning on Cas1 and Cas2 expression. The second plasmid is called signal plasmid, which provides the signal-responsive retron ncRNAs. Barcode A and barcode B are placed under the control of inducible promoters responsive to aTc and choline, respectively. Their expression is regulated by TetR and BetI, enabling external stimuli to selectively trigger transcription of the corresponding retron ncRNAs. Together, these plasmids couple input signals to retron DNA barcode production and subsequent Cas1–Cas2 integration, thereby realizing Retro-Cascorder’s ability to encode transcriptional histories directly into CRISPR arrays.

![](https://static.igem.wiki/teams/5605/results/35.avif)

*Figure 35. Principles of Retro-Cascorder transcriptional recording. A, upon activation of a promoter of interest by signal A or B, the downstream retron non-coding RNA (RT-ncRNA) would be transcribed, which is reverse-transcribed by retron reverse transcriptase (RT, shown in blue) into complementary DNA. The Cas1–Cas2 integrase complex (yellow and brown) then integrates DNA sequentially into the CRISPR array as spacer A (green) or B (purple). Meanwhile, double-stranded DNA from other sources like genome or plasmids could also be incorporated by Cas1-Cas2 as spacer N (yellow). Over time, different signals are captured as new spacers, creating a chronological transcriptional history that can be read out by sequencing. B, the plasmid expressing Cas1, Cas2, and Eco1 retron-specific RT. The LacI-regulated T7 promoter drives the expression of Cas1 and Cas2, while Eco1 RT is constitutively expressed by the J23115 promoter. C, retron ncRNA encoding barcode A and B were expressed by aTc- or Cho-inducible promoters regulated by TetR and BetI. Created by biorender.com.*

### Recording the Orders of Transcriptional Events

In this experiment, we tested the ordering of transcriptional events using the Retro-Cascorder system in *E. coli* BL21(AI) carrying the signal and expression plasmids (Figure 36A). Six single colonies were picked to establish independent biological replicates, which were cultured in LB medium supplemented with chloramphenicol (Cm) and ampicillin (Amp) to maintain plasmids, along with IPTG and L-arabinose (Ara) to induce the expression of the recording machinery throughout the experiment. Anhydrotetracycline (aTc) was used as an inducer to trigger the expression of barcode A, while choline chloride (Cho) was used to trigger barcode B. These six cultures were then split into three groups with different inducer conditions: (i) aTc followed by Cho (aTc–Cho), (ii) Cho followed by aTc (Cho–aTc), and (iii) no inducers as a negative control. Each group was maintained in the initial condition for 24 hours before switching to the second condition for another 24 hours. For the control group, all cultures remained uninduced for 48 hours. Following growth, samples were processed for next-generation sequencing (NGS) library preparation using both KAPA High-Fidelity DNA Polymerase and T8 High-Fidelity Master Mix. This allowed us to compare whether PCR reagent choice influences the outcome of Retro-Cascorder event recording.

The resulting spacer acquisition profiles were analyzed to calculate A/N, B/N, and A/B scores for all groups (Figure 36B-C). Ideally, the aTc–Cho (AB) condition should yield positive values across all three scores, whereas the Cho–aTc (BA) condition should give uniformly negative values. However, the violin plots showed that the distributions were highly noisy, with scores either spreading broadly between –1.0 and 1.0 or even displaying opposite trends in both of the two libraries prepared by KAPA (Figure 36B) and T8 (Figure 36C). Additionally, the A/B scores were left blank because no informative arrays with the expected A → B → leader or B → A → leader patterns were observed. These results suggest that the failure to produce cleanly separated scores arises from low recording efficiency, leaving too few informative arrays to confidently resolve event order.

To further investigate this issue, we examined the percentage of arrays expanded with spacers A, B, and N (Figure 36D-E). The frequency of arrays carrying A or B spacers was on the order of 0.001%, which is two orders of magnitude lower than the ~0.1% reported in the original Retro-Cascorder study (Bhattarai-Kline et al., 2022). The incorporation frequency of N spacers was also slightly lower than the reported ~10%. Together, these results indicate that inefficient spacer acquisition underlies the noisy and inconsistent temporal determination observed in this experiment.

![](https://static.igem.wiki/teams/5605/results/36.avif)

*Figure 36. Recording the orders of transcriptional events by Retro-Cascorder. A, Schematic of the experimental workflow. Six independent E. coli BL21(AI) colonies carrying pSBK.134 (ncRNA) and pSBK.079 (retron-RT and Cas1-Cas2) were picked and tested in aTc→Cho (AB), Cho→aTc (BA), and uninduced conditions. After 48 hours of recording, NGS libraries were prepared using both KAPA and T8 enzymes. B, Violin plots of A/N, B/N, and A/B scores from the KAPA-prepared library. C, Violin plots of A/N, B/N, and A/B scores from the T8-prepared library. D, Bar plots of the fraction of arrays incorporating spacers A, B, or N in the KAPA-prepared library. E, Bar plots of the fraction of arrays incorporating spacers A, B, or N in the T8-prepared library. Mean values from six replicates were shown for all data points in D-E, with error bars representing standard deviation. Individual replicate values are shown as black dots. Created by biorender.com.*

### Characterizing Insertion Efficiencies of Cas1 Variants

To improve the spacer acquisition efficiency of the Cas1–Cas2 complex, we tested three previously reported variants with enhanced activity (Yosef et al., 2023), E269G, V76L, and the double mutant E269G–V76L, and compared them to the wild-type Cas1 (Figure 37A). For each variant, the Cas1–Cas2 plasmid was co-transformed with an ncRNA plasmid carrying the aTc-inducible expression of barcode A. Cultures were grown in the presence of IPTG and L-arabinose (Ara) to activate the recording machinery, and each culture was split into two conditions: one induced with aTc to trigger barcode A expression and one left uninduced. Three biological replicates were performed for each Cas1 variant. Samples were collected at 12-hour intervals (0, 12, 24, 36, and 48 hours after induction) for NGS library preparation (Figure 37B).

Sequencing results suggested that the percentage of arrays with spacer A incorporation remained extremely low across all variants, in both uninduced (Figure 37C) and aTc-induced (Figure 37D) conditions. Among them, WT and V76L exhibited slightly higher A array incorporation compared to E269G and the E269G–V76L double mutant. Because barcode A incorporation was limited, we next examined barcode N, which is assumed to be generated at a constant rate (Bhattarai-Kline et al., 2022) and can therefore serve as a proxy for Cas1-mediated integration efficiency. Similar incorporation frequencies of N arrays were observed under uninduced (Figure 37E) and induced (Figure 37F) conditions. Consistent with the A array data, V76L showed higher N array incorporation than WT, whereas E269G and the double mutant unexpectedly showed lower incorporation, despite previous reports suggesting that these mutations enhance spacer acquisition efficiency. These discrepancies might be due to differences in measurement methods between our study and the original report, or the possibility that N array generation rates were not identical across all conditions.

![](https://static.igem.wiki/teams/5605/results/37.avif)

*Figure 37. Characterization of Cas1 variants in Retro-Cascorder recording. A, Schematic showing the Cas1 variants tested: WT, E269G, V76L, and the double mutant E269G–V76L. Each Cas1–Cas2 plasmid was co-transformed with an ncRNA plasmid carrying the aTc-inducible barcode A. B, Experimental workflow. Three colonies of E. coli BL21(AI) harboring the two plasmids in A were cultured under IPTG and L-arabinose (Ara) induction, with or without aTc to trigger barcode A expression. Samples were collected every 12 hours (0, 12, 24, 36, and 48 h) for NGS library preparation. C, Percentage of arrays incorporating barcode A without aTc induction. D, Percentage of arrays incorporating barcode A with aTc induction. E, Percentage of arrays incorporating barcode N without aTc induction. F, Percentage of arrays incorporating barcode N with aTc induction. Mean values from three replicates were shown for all data points in C-F, with error bars representing standard deviation. Created by biorender.com.*

### Troubleshooting Retron-Derived Spacer Acquisition

To troubleshoot the low efficiency of retron-derived spacer acquisition, we tested whether both barcode A and B could be incorporated under induction conditions (Figure 38A). Three colonies of *E. coli* BL21(AI) harboring the original Cas1–Cas2 plasmid and the ncRNA plasmid carrying barcodes A and B were used. This time, the expression plasmid was electroporated into BL21(AI) harboring the signal plasmid to ensure efficient transformation. Cultures were then split into three conditions: (i) IPTG + Ara + aTc + Cho, where spacers A, B, and N were expected to be incorporated simultaneously; (ii) IPTG + Ara only, where only spacer N was expected; and (iii) no inducers, serving as a negative control. After 24 hours of culture, samples were collected for NGS.

Sequencing results revealed clear differences in spacer acquisition across conditions (Figure 38B). For spacer N, we observed an approximately 7-fold increase in incorporation when IPTG and Ara were added, confirming that the Cas1 and Cas2 were induced and functional. For spacer A, its incorporation also increased upon IPTG and Ara induction, indicating not only active Cas1–Cas2 but also a functional retron-RT capable of reverse-transcribing ncRNA into DNA spacers for integration. However, additional induction with aTc did not further enhance incorporation, suggesting that spacer A was largely derived from transcriptional leakage of the TetR-regulated promoter and that aTc failed to effectively drive barcode A expression. For spacer B, the BetI-regulated promoter is known to exhibit high basal leakage, and Cho induction resulted in about a 2-fold increase in incorporation, which is consistent with previously reported values (Bhattarai-Kline et al., 2022). Taken together, these results indicate that the poor performance of retron-derived spacer acquisition stems primarily from weak or ineffective induction of barcode A by aTc, rather than from dysfunction of the Cas1–Cas2 complex or the retron-RT. This finding accounts for the insufficient barcode A incorporation observed in both the event-ordering and Cas1 variant characterization experiments, which in turn led to noisy and inconclusive results.

![](https://static.igem.wiki/teams/5605/results/38.avif)

*Figure 38. Troubleshooting retron-derived spacer acquisition. A, troubleshooting experiment workflow. Three colonies of E. coli BL21(AI) carrying the original Cas1–Cas2 plasmid and an ncRNA plasmid encoding barcodes A and B were picked. Cultures were divided into three conditions: IPTG + Ara + aTc + Cho , IPTG + Ara only , and no inducers. After 24 hours, samples were collected for NGS library preparation. B, Spacer acquisition results. The percentage of arrays incorporating spacers A, B, or N was shown for all three conditions. Bar heights represent the mean of three replicates, with error bars showing standard deviation. Individual replicate values are shown as black dots; replicates with zero values are not visible due to the log scale. Created by biorender.com*

Since aTc is known to be light-sensitive, a possible explanation for the poor incorporation of spacer A is that the reagent had degraded during storage. To test whether the aTc stock was still active, we used a positive control strain from the Marionette collection (Meyer et al., 2019), which carries a plasmid expressing EYFP under the control of an aTc-inducible promoter (Figure 39A). Cultures were grown with and without aTc, and fluorescence was compared. No yellow fluorescence was detected upon aTc induction (Figure 39B), indicating that the reagent had lost activity. We then repeated the assay using a freshly prepared aTc solution, and this time robust yellow fluorescence was observed (Figure 39C). These results suggest that the experimental failures were caused by degradation of the aTc stock. For future experiments, freshly prepared aTc should be used to ensure reliable recording performance.

![](https://static.igem.wiki/teams/5605/results/39.avif)

*Figure 39. Verifying aTc activity using an aTc-inducible EYFP reporter strain. A, schematic of the Marionette plasmid in which EYFP is expressed under control of an aTc-inducible promoter. B, the fluorescence image of cultures grown with or without the original aTc stock. C, the fluorescence image of cultures grown with freshly prepared aTc. Created by biorender.com.*
Integrating CRISPR Array into EcN Genome

---

#### Design and Construction of Genome Integration-Related Plasmids

As described in our [Design](https://2025.igem.wiki/bnds-china/design) section, the genome integration was performed using a two-plasmid editing system (Figure 40). The first plasmid, pEcgRNA, is a high-copy ColE1 plasmid that constitutively expresses a single guide RNA (sgRNA) under a strong constitutive promoter; the sgRNA contains a 20-nt spacer complementary to the intended EcN genomic target, which is fused to the conserved gRNA scaffold required for Cas9 recognition. The second plasmid, pEcCas, is a low-copy pSC101-based vector carrying both the Cas9 nuclease and the λ-Red recombination system (Gam, Bet, Exo). In this design, Cas9 is expressed constitutively to ensure efficient cleavage, whereas λ-Red recombinases are placed under the arabinose-inducible araBAD promoter to provide temporal control of recombination activity. To facilitate subsequent plasmid curing, pEcCas also encludes a rhamnose-inducible gRNA (gRNA-pBM1 under the rhaBAD promoter, activated by RhaS/RhaR in the presence of rhamnose) that directs Cas9 cleavage of pEcgRNA, and a *sacB* counter-selectable marker for sucrose-based elimination of pEcCas itself.

![](https://static.igem.wiki/teams/5605/results/40.webp)

*Figure 40. Plasmid design for a CRISPR-Cas9/Lambda Red based genome integration system. Some constitutive promoters and terminators are emitted for simplicity. Created by biorender.com.*

#### Insertion of CRISPR Array

After constructing and cloning two plasmids, we started by transforming pEcCas into EcN and preparing electrocompetent cells of EcN harboring pEcCas. We then conducted an electroporation, transforming both pEcgRNA and the CRISPR array in BL21(AI) genome into the pEcCas-harboring EcN strain. Now we expect the strain to include pEcCas, pEcgRNA, and the CRISPR array to be integrated into the genome, which should be sufficient for the successful genome integration.

To test whether genome integration succeeded, we isolated 16 colonies and conducted colony PCR along with the WT EcN strain as a control. We then run an AGE of PCR products. As shown in Figure 41, the PCR products from colonies #2, #3, #8, and #12 had expected lengths. Hence, we sent them for sequencing.

From the sequencing results, colony #12 had two point mutations on the first repeat of the CRISPR array; colonies #2, #3, and #8 had the correct CRISPR array integrated into the genome, but with some mutations in the intergenic region, which would not influence the function of the inserted CRISPR array. Since colony #8 had the correct CRISPR array and the lowest number of mutations in the intergenic region, we proceeded with this colony for the following experiments of plasmid curing.

![](https://static.igem.wiki/teams/5605/results/41.avif)

*Figure 41. The AGE results of the colony PCR.*

#### Plasmid Curing

Next, we tried to eliminate the plamids used for genome integration. Note that the starting strain in this section is colony #8 in the above section, and the colonies #1-16 described in this section are different from those in the above section. We first tried to eliminate pEcgRNA. Following the plasmid design in Figure 40, we induced gRNA-pMB1 expression by adding 10mM rhamnose into the bacterial culture. Then, we extracted 16 single colonies and conducted two sets of solid inoculation of them. The first set only contained kanamycin as antibiotics, while the second set contained both kanamycin and spectinomycin. (Figure 42) Since the resistance to spectinomycin is expressed in pEcgRNA, the colonies without pEcgRNA should survive on the first set of solid inoculation but not on the second set. According to Figure 42, the colonies #11 and #15 had their pEcgRNA plasmid cured. We chose to proceed with colony #15 for the next steps.

![](https://static.igem.wiki/teams/5605/results/42.avif)

*Figure 42. Solid inoculation of 16 colonies in curing pEcgRNA with and without spectinomycin. A, kanamycin added. B, both kanamycin and spectinomycin added.*

Lastly, we wanted to eliminate pEcCas through counter-selection by sucrose. Note that the starting strain in this section is colony #15 in the above part, and the colonies #1-9 described in this part are different from those in the above part. We added 10mg/mL sucrose into the bacterial culture and extracted 9 single colonies. We then conducted two sets of solid inoculation of them. The first set did not contain antibiotics, while the second set contained kanamycin. (Figure 43) Since the resistance to kanamycin is expressed in pEcCas, the colonies without pEcCas should survive on the first set of solid inoculation but not on the second set. According to Figure 43, colonies #2-9 all had their pEcCas plasmid cured. We chose to proceed with colony #8.

![](https://static.igem.wiki/teams/5605/results/43.avif)

*Figure 43. Solid inoculation of 9 colonies in curing pEcCas with and without kanamycin. A, no antibiotics added. B, kanamycin added.*

To make sure the plasmid curing steps did not affect the CRISPR array inserted into EcN genome, we further conducted a colony PCR and sequencing for the colony #8 described in the above part. The sequencing result indicated that there was no mutation in the inserted CRISPR array.

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