iGEM 2024 — Team bnds-china

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

![cover-back](https://static.igem.wiki/teams/5127/head/note.png)

[Press here to download](https://static.igem.wiki/teams/5127/notebook.pdf)

[Press here to download](https://static.igem.wiki/teams/5127/addition-const.pdf)

{% endblock %}

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

![cover-back](https://static.igem.wiki/teams/5127/head/es.png)

## Menu

[Engineering Success: bile acid sensor utilizing the VFA0359 repressor](#1)
[Engineering success: SCFA biosensor](#2)
[Reference](#3)

## **Engineering Success: bile acid sensor utilizing the VFA0359 repressor**

### **Background**

Our engineered probiotic platform is designed to monitor intestinal microbiome metabolite concentrations in real time and respond accordingly. However, metabolite levels within the intestinal lumen can fluctuate throughout the day due to the host's dietary intake and intestinal movements. For instance, low butyrate levels may be expected in places where food residues are absent, as the intestinal microbiome lacks a carbon source for metabolite production. Therefore, our probiotic must differentiate between the presence and absence of food residues when responding to metabolite levels. Bile acids, released by the gallbladder during digestion, can serve as an indicator of food presence. To address this, we plan to incorporate a biosensor capable of detecting and responding to changes in bile acid concentrations into our probiotic platform. This will enable our probiotic to regulate the gut metabolites profile based on real-time environmental signals effectively.

### **Design (Cycle #1)**

After research, we selected the bile acid sensor designed by Mao Taketani et al. (2020) for integration into our probiotic. This biosensor has low basal activity, high dynamic range, and no observable cross-talk with other common sensor systems, which makes it an ideal choice for our platform (Mao Taketani et al., 2020). This bile acid sensor was constructed in *Bacteroides thetaiotaomicron* by placing the gene of the TetR-family repressor VFA0359 under the control of a constitutive promotor and placing the operator sequence between the −33 and −7 region of a constitutive promoter that regulates the expression of a reporter gene (Figure 1). The biosensor responds to multiple kinds of bile acids but showed highest response to deoxycholic acid (DCA), a representative compound in bile acids (Mao Taketani et al., 2020). Thus, we chose DCA as our inducer to test the induction of our bile acid sensor based on the VFA0359 repressor.

![](https://static.igem.wiki/teams/5127/engineering/new/1.png)

*Figure 1. The genetic circuit of the bile acid sensor designed by Mao Taketani et al. Created by biorender.com.*

Before obtaining the sequence of this bile acid sensor and testing it in our probiotic, *E. coli* Nissle 1917, we first ran an *in silico* stimulation of the transcription Initiation rates of this sensor in Escherichia coli str. K-12 substr. MG1655 using the Promoter Calculator function of De Novo DNA (LaFleur, T. L., 2022). The results (Figure 2) showed that the transcriptional activity of PcfxA is too low (blue box and arrow) and that there are numerous unwanted transcription start sites. This could be because this bile acid promotor is designed for *B. thetaiotaomicron* instead of *E. coli.*

![](https://static.igem.wiki/teams/5127/engineering/new/2.png)

*Figure 2. De Novo DNA Promotor Calculator result of the bile acid sensor designed by Mao Taketani et al. in comparison with the sequence of the sensor. Sequence obtained from plasmid pMT447 (Addgene Plasmid #139387).*

Due to the low desired transcriptional activity and numerous unwanted transcription start sites of this bile acid sensor, we decided to engineer this bile acid sensor to fit the transcription and translation environment of *E. coli*. VFA0359 used in this bile acid sensor belongs to the TetR-family repressors, the same family as the repressor EilR in the Jungle Express repressor system. The Jungle Express repressor system is a tight transcriptional control system built for *E. coli* by Thomas L. Ruegg et al. (2018). We used this repressor system in our 2022 project ([BBa\_K4204016](https://parts.igem.org/Part%3ABBa_K4204016)). Considering the structural similarity and compatibility shared between proteins within the same family, we decided to use the framework (everything except the repressor and operator) of the jungle express system as a substitute for the framework of the DCA sensor system. We adopted SnowPrint (d’Oelsnitz, S. et al., 2024) to predict the palindromic operator sequence of VFA0359 and inserted two operator sequences in the phage early promoter, one overlapping with -10/-35 region and another one downstream -10 hexamer. The resulting new design and De Novo DNA Promoter Calculator (LaFleur, T. L., 2022) results of the new design are shown in Figures 3 and 4. The transcription rate peaks in regions with blue boxes and arrows show that this design has a desired transcriptional activity at promoters driving the expression of the VFA0359 regulator and the target gene (GFP\_mut2).

![](https://static.igem.wiki/teams/5127/engineering/new/3.png)

*Figure 3. New design of the bile acid sensor utilizing the Jungle Express framework. Created by biorender.com.*

![](https://static.igem.wiki/teams/5127/engineering/new/4.png)

*Figure 4. The new design of the bile acid sensor utilizing the Jungle Express framework and its De Novo DNA Promotor Calculator result. The blue boxes and arrows highlight the desired regions of transcriptional activity.*

See more details on [design page](https://2024.igem.wiki/bnds-china/design).

### **Build (Cycle #1)**

The bile acid sensor design is then integrated into the plasmid backbone pUC57, the codons of the two proteins were optimized for expression in *E. coli* using algorism provided by Genscript, and the plasmid (pUC57\_Kan\_pDCA\_VFA0359) was then obtained from Genscript (Plasmid map see Figure 5).

![](https://static.igem.wiki/teams/5127/engineering/new/5.png)

*Figure 5. Plasmid map of pUC57\_Kan\_pDCA-VFA0359.*

### **Test (Cycle #1)**

After Obtaining the plasmid pUC57\_Kan\_pDCA\_VFA0359 from Genscript, we transformed it into *E. coli* trelief 5α and performed a kinetic assay to characterize our new bile acid sensor design (detailed protocol of kinetics assay are in protocol page). Overnight cultures of pUC57\_Kan\_pDCA\_VFA0359 transformed trelief 5α cells in LB media at 37**°**C were 1:250 (v/v) inoculated into fresh M9 media (M9 media with 0.4% (w/v) glucose, 0.2% (w/v) casamino acid, and 1 mM thiamine, the same below), cultured for 3 hours and diluted to OD=0.01 using M9 media. The resulting culture was then separated into aliquots, and different concentrations of DCA were added to the aliquots. Then, the aliquots were plated onto a well black/clear bottom 96-well plate with three repeats each and 150 µL culture in each plate. Positive/negative control *E. coli* cultures with different plasmids were also processed using the same above-mentioned method. The positive control used is a J23100-sfGFP on a pSB1C3 backbone ([BBa\_K515105](https://parts.igem.org/Part%3ABBa_K515105)). The negative control used is a tes4 gene on a pET-28a(+) backbone ([BBa\_K3838613](https://parts.igem.org/Part%3ABBa_K3838613)). The detailed plate setup is shown below in Table 1, and the kinetics assay was performed as described in the protocol.

![](https://static.igem.wiki/teams/5127/engineering/new/6.png)

*Table 1. Plate layout of kinetics assay.*

The results of the kinetics assay were used to calculate the fluorescence/ABS600 (GFP/OD) curve. The GFP/OD curve of the groups shows that there are no significant differences in GFP expression levels between the groups with different concentrations of DCA (Figure 6). This suggests that our biosensor design did not function as we hypothesized.

![](https://static.igem.wiki/teams/5127/engineering/new/7.png)

*Figure 6 .The kinetics assay result of the new bile acid sensor, plasmid pUC57\_Kan\_pDCA\_VFA0359. Unit of time is seconds.*

We also compared the fluorescence value of our bile aid sensor pUC57\_Kan\_pDCA\_VFA0359 with the positive control, which is a constitutively expressed GFP on a pSB1C3 backbone. The results show that our biosensor has a very low level of GFP expression compared to that of a control.

![](https://static.igem.wiki/teams/5127/engineering/new/8.png)

*Figure 7. The fluorescence value graphed against time of the new bile acid sensor on the plasmid pUC57\_Kan\_pDCA\_VFA0359 and of the positive control. Unit of time is seconds, and "2002p" is the plasmid that has a constitutively expressed GFP on a pSB1C3 backbone.*

### **Learn (Cycle #1)**

The results show that our sensor is not able to report the difference between different concentrations of DCA and that the basal expression rate of our sensor system is fairly low. Given that there is proof that the repressor VFA0359 can bind to the operator and that DCA can release the repressor from the operator (Mao Taketani et al., 2020), Several factors could contribute to the observed result. One possibility is that the VFA0359 repressor may be overexpressed and/or the repressor has an exceptionally strong binding affinity for the operator. This could hinder the ability of DCA to effectively release the repressor from the operator, preventing the activation of the output promoter. Alternatively, DCA might be unable to reach the repressor to exert its result. Also, the output promoter, after the addition of the two operators, could malfunction, failing to initiate GFP expression even when the repressor is released. Further investigation is necessary to pinpoint the cause of the observed results.

### **Design (Cycle #2)**

As pointed out in the "learn" part of the first cycle, one possible reason for the malfunctioning of our bile acid sensor could be because of the output promoter. Thus, in this cycle, we aim to test whether the output promotor, O1O2+PjexD, or PVFA0359, functions as normal. We decided to mutate the repressor VFA0359 to stop its expression by changing the two codons after the start codon to the stop codon TAA. We hypothesize that after this silencing mutation to the VFA0359 repressor, the GFP expression level of *E. coli* with the plasmid pUC57\_Kan\_pDCA\_VFA0359 would significantly increase, which suggests that the output promotor functions as desired and that VFA0359 does exert a repression effect on the transcription initiation activity of the output promotor. The mutated plasmid is named pUC57\_Kan\_pDCA\_VFA0359\_2TAA.

![](https://static.igem.wiki/teams/5127/engineering/new/9.png)

*Figure 8. The difference between pUC57\_Kan\_pDCA\_VFA0359 (Top) and pUC57\_Kan\_pDCA\_VFA0359\_2TAA (bottom).*

See more details on [design page](https://2024.igem.wiki/bnds-china/design).

### **Build (Cycle #2)**

PCR and Golden Gate assembly were performed to achieve the change in sequence. Agarose gel electrophoresis was performed and the bands indicate the correctness of the components' length (Figure 9).

![](https://static.igem.wiki/teams/5127/engineering/new/10.png)

*Figure 9. The AGE result of the PCR product for the construction of plasmid pUC57\_Kan\_pDCA\_VFA0359\_2TAA The bands indicate the correctness of each component's length. pUC57\_Kan\_pDCA\_VFA0359\_2TAA is abbreviated to pDCA-2TAA.*

### **Test (Cycle #2)**

The plasmid pUC57\_Kan\_pDCA\_VFA0359\_2TAA was transformed into *E. coli* trelief 5α. Figure 10 shows the colonies that are successfully transformed with pUC57\_Kan\_pDCA\_VFA0359\_2TAA (with a yellow circle) exhibit fluorescence under blue light. The single colonies were inoculated in LB media and cultured overnight at 37 °C and 220 rpm. The overnight cultures were then centrifuged at 3000 g to obtain cell pellets to observe fluorescence. The results show that pUC57\_Kan\_pDCA\_VFA0359\_2TAA has a significantly higher basal fluorescence than pUC57\_Kan\_pDCA\_VFA0359 and is close to that of pJump47-2A (Addgene Plasmid #126991). However, the picture of the result of this experiment is missing at the time when writing this wiki page. Our team will experiment again and update our results.

![](https://static.igem.wiki/teams/5127/engineering/new/11.png)

*Figure 10. LB Agar plates with colonies of pUC57\_Kan\_pDCA\_VFA0359\_2TAA (right) and pJump47-2A (left) under the blue light of a blue LED transilluminator. The circles indicate colonies successfully transformed with pUC57\_Kan\_pDCA\_VFA0359\_2TAA (verified by Sanger sequencing).*

### **Learn (Cycle #2)**

Our results suggest that the output promoter, PVFA0359, with the two operators inserted, could initiate GFP transcription as we desired. This also provides proof that VFA0359 repressed the expression of GFP in our previous bile acid sensor design. Thus, the possible explanation regarding our bile acid sensor pUC57\_Kan\_pDCA\_VFA0359 not functioning is that the VFA0359 repressor may be overexpressed and/or the repressor has an exceptionally strong binding affinity for the operator. To solve this problem, we decided to weaken the expression of VFA0359 and weaken its binding with the output promotor in the next engineering cycle.

### **Design (Cycle #3)**

To weaken the expression of VFA0359 and weaken its binding with the output promotor, we planned to engineer the RBS that regulates the translation of VFA0359 for weaker translation initiation and delete the first of the two operators on the output promoter. The original GSG RBS used to express the repressor EliR in the Jungle express system was mutated *in silico* by the RBS calculator on De Novo DNA (Salis, H. M.,2009). A mutant with a translation initial rate of 1000 au was selected from multiple mutants and named GSG RBSmut1000. We deleted the operator in between the -35 and -10 motif and replaced the -10 motif with a stronger one. The resulting plasmid after the two changes is named pUC57\_Kan\_pDCA\_VFA0359\_mut1000\_operator (abbreviated to pDCA\_mut1000\_operator)(Figure 11). The two changes are shown in Figure 12.

![](https://static.igem.wiki/teams/5127/engineering/new/12.png)

*Figure 11. The genetic circuit of the new bile acid sensor design pDCA\_mut1000\_operator. Created by biorender.com.*

![](https://static.igem.wiki/teams/5127/engineering/new/13.png)

*Figure 12. Comparison of the changes made in the design of this cycle. "Before" refers to the plasmid pUC57\_Kan\_pDCA\_VFA0359 and "After" refers to the plasmid pUC57\_Kan\_pDCA\_VFA0359\_mut1000\_operator.*

See more details on [design page](https://2024.igem.wiki/bnds-china/design).

### **Build (Cycle #3)**

We designed primers to perform PCR on the original plasmid pUC57\_Kan\_pDCA\_VFA0359 and obtained fragments with the desired changes in sequence. Then, we utilized Golden Gate Assembly to assemble the new plasmid pDCA\_mut1000\_operator from the fragments.

### **Test (Cycle #3)**

Upon successful Golden Gate Assembly of the plasmid pDCA\_mut1000\_operator, we transformed it into *E. coli* trelief 5α. Single colonies of pDCA\_mut1000\_operator and pUC57\_Kan\_pDCA\_VFA0359 were picked from LB agar plates and inoculated in LB media with 1000 µM, 200 µM, or 0 µM DCA and cultured overnight at 37 °C and 220 rpm, each with three repeats. The overnight cultures were plated onto wells of a well black/clear bottom 96-well plate and placed into the microplate reader to obtain Abs600 and fluorescence value (settings of the microplate reader are the same as the kinetics protocol). The average net fluorescence/ABS600 (FL/ABS) values were calculated and plotted in Figure 13. The results showed that the overnight culture of pDCA\_mut1000\_operator exhibited a GFP expression level even lower than before (compared to pUC57\_Kan\_pDCA\_VFA0359). This suggests that there must be some flaws in our design.

![](https://static.igem.wiki/teams/5127/engineering/new/14.png)

*Figure 13. The average net FL/ABS value of overnight cultures of pDCA\_mut1000\_operator and pUC57\_Kan\_pDCA\_VFA0359 in E. coli Trelief.*

### **Learn (Cycle #3)**

To better identify the problem shown in the results section of the plasmid design pDCA\_mut1000\_operator, we used De Novo DNA promoter calculator (LaFleur, T. L., 2022) to calculate transcription initiation rates of the sensor sequence of pDCA\_mut1000\_operator. The results show that there is a missing forward transcription peak at the position of the PjexD promoter, and there is an unwanted peak above the RiboJ-RBS-GFP region.

![](https://static.igem.wiki/teams/5127/engineering/new/15.png)

*Figure 14. The bile acid sensor on pDCA\_mut1000\_operator and its De Novo DNA Promotor Calculator result. The red box indicates a missing peak, and the blue box indicates an unwanted peak.*

We looked into the details in sequence view to find the reason for the missing and unwanted peak. It turns out that the missing peak is because we accidentally deleted one bp, an adenine, from the -35 motif of the PVFA0359 promotor (see Figure 14) when removing the operator and did not realize it. The unwanted peak is due to the codon optimization done in the "build" section of cycle 1 of the GFP gene, which uses 5'-TCA-3' instead of the original 5'-AGT-3' for the second amino acid serine and creates a strong -35 motif at the start of GFP (see Figure 15). This strong -35 motif, together with the -10 motif on the preceding RBS, creates the unwanted peak that we see in Figure 15.

![](https://static.igem.wiki/teams/5127/engineering/new/16.png)

*Figure 15. The unwanted promoter and its -35 and -10 motifs were created accidentally by codon optimization.*

### **Design & Build (Cycle #4)**

To correct the two mistakes identified in the learn section above, we designed two sequential Golden Gate Assemblies, the first one fixing the missing "A" on the -35 motif of the output promotor (plasmid called pDCA\_Fix\_1), and the second one changing the codon that codes for the second amino acid, serine, back to 5'-AGT-3' (plasmid called pDCA\_Fix\_2).

![](https://static.igem.wiki/teams/5127/engineering/new/17.png)

*Figure 16. The AGE result of the PCR products for the Golden Gate Assemblies of the plasmids pDCA\_Fix\_1 (A) and pDCA\_Fix\_2 (B). The bands indicate the correctness of each component's length.*

See more details on [design page](https://2024.igem.wiki/bnds-china/design).

### **Test (Cycle #4)**

Upon successful Golden Gate Assembly of the plasmid pDCA\_Fix\_2, we transformed it into *E. coli* Nissle 1917. Single colonies of pDCA\_Fix\_2 were picked from LB agar plates and inoculated in LB media overnight. GFP fluorescence kinetic assay was done using the pDCA\_Fix\_2 EcN overnight culture following the steps in the protocol. The detailed plate setup is shown below in Table 2.

![](https://static.igem.wiki/teams/5127/engineering/new/18.png)

*Table 2. Plate layout of kinetics assay for pDCA\_Fix\_2.*

The results of the fluorescence kinetic assay (Figure 17) show that higher DCA concentration in media results in stronger GFP expression levels. This suggests that our bile acid sensor utilizing the VFA0359 repressor succeeded in detecting and reporting changes in bile acid concentration quantitatively. The dynamic range of this sensor system (pDCA\_Fix\_2) at 500 µM was about 2.2-fold at 1000μM DCA, which is relatively low.

![](https://static.igem.wiki/teams/5127/engineering/new/19.png)

*Figure 17. The fluorescence kinetics assay result of the plasmid pDCA\_Fix\_2.*

### **Learn (Cycle #4)**

Our sensor design finally succeeded at detecting changes in bile acid (DCA) concentrations. However, there are many future experiments and possible improvements. Repeats of the fluorescence kinetics assay could be done with another positive control, pUC57\_Kan\_pDCA\_VFA0359\_2TAA, to predict the potential upper limit of the dynamic range of our sensor design. Then, optimizations could be done regarding the expression of the VFA0359 repressor, the sequence and position of the VFA0359 operator, and the strength of the output promotor, PVFA0359, to enlarge the current dynamic range (or control it to reach a desired value) of our bile acid sensor.

## **Engineering success: SCFA biosensor**

### **Introduction**

Short-chain fatty acids (SCFA), such as propionate and butyrate, produced by the gut microbiota, are crucial metabolites. Microbiome dysbiosis, leading to changed SCFA profiles, is linked to some diseases, such as IBD, which is marked by a drop in butyrate levels and heightened intestinal inflammation. Our project aimed to detect the insufficiency in levels of SCFA in the human gut and compensate for it by producing SCFA. We plan to achieve this by designing a genetic circuit that links SCFA-sensing biosensors to a "NOT" gate. This circuit would monitor SCFA levels and express Tes4, an enzyme responsible for SCFA production, inversely proportional to SCFA levels, to compensate for the insufficiency in SCFA. The work of previous iGEM teams provided us choices for SCFA sensors, one of which is PpchA promoter that comes from the registry BBa\_K4442001 ([iGEM23\_NMU-China](https://parts.igem.org/Part%3ABBa_K4442001)).  Here, we engineer this SCFA sensor with the cI repressor system(NOT gate) together to create a functional genetic circuit.

### **Cycle #1: PpchA-cI biosensor validation**

### **Design (Cycle #1)**

Ppcha/Lrp is a butyrate biosensor system originating from Escherichia coli strain O157:H7 (Kineret et al., 2023). The pPcha/Lrp system has already been tested by previous iGEM teams, confirming it could be activated with the presence of butyrate ([iGEM23\_NMU-China](https://parts.igem.org/Part%3ABBa_K4442001)).

We plan to examine the efficiency of the Ppcha sensor system by engineering *E. coli* and expressing it under controlled conditions. To achieve this goal, we designed plasmid pPcha\_cI. In our design, leucine-responsive regulatory protein (Lrp) is constitutively expressed using the J23101 promoter, while plam controls expression of desired output genes. When butyrate is not present, plam express genes successfully. When Lrp binds to the pPcha promoter with presence of butyrate, it activates the expression of cI regulator, which then inhibits promoter pLam, and stops expression of output genes.

![](https://static.igem.wiki/teams/5127/engineering/new/20.png)

*Figure 18. The genetic circuit of the pPcha\_cI butyrate sensor. Created by biorender.com.*

![](https://static.igem.wiki/teams/5127/engineering/new/21.jpg)

*Figure 19. Plasmid map of pUC57\_Kan\_pPcha\_cI.*

See more details on [design page](https://2024.igem.wiki/bnds-china/design).

### **Build (Cycle #1)**

We integrated this design into the plasmid backbone pUC57-Kan, and ordered the plasmid from a commercial company. However, the plasmid synthesized by the company contained a point mutation on the ribosome binding site (RBS), which might effect the expression of Lrp.

![](https://static.igem.wiki/teams/5127/engineering/new/22.jpg)

*Figure 20. Point mutation on the RBS for Lrp expression.*

### **Test (Cycle #1)**

We transformed pUC57\_Kan\_pPcha\_cI into *E. coli* Trelief 5α. Single colonies of *pUC57\_Kan\_pPcha\_cI* were picked from LB agar plates and inoculated in LB media overnight. GFP fluorescence kinetic assay was done using the *pUC57\_Kan\_pPcha\_cI* Trelief overnight culture following the steps in the protocol. The detailed plate setup is shown below in Table 3.

![](https://static.igem.wiki/teams/5127/engineering/new/23.png)

*Table 3. Plate layout of kinetics assay for pUC57\_Kan\_pPcha\_cI.*

The results of the kinetics assay were used to calculate the fluorescence/ABS600 curve. The normalized curve of the groups showed slight differences and a correct trend as the gradient of inducer was added, though the dynamic range was suboptimal (Figure 21).

![](https://static.igem.wiki/teams/5127/engineering/new/24.png)

*Figure 21. Kinetics of PpchA before fixing with multiple butyrate concentrations over 18 hours. Fluorescence / ABS was used to represent GFP expression; higher fluorescence represented lower PpchA activity. The butyrate concentration ranges from 0 to 70mM.*

### **Learn (Cycle #1)**

From the results we found that there isn't significant induction of the biosensor by addition of SCFA butyrate. Given that the effect of the system has been proven by previous iGEM teams, one possible source of error could be the point mutation on RBS of Lrp, affecting its expression so the dynamic range is low. To address this, we utilized the promoter calculator function by De novo DNA (LaFleur, T. L., 2022)(Salis et al., 2009)(Figure 22). The results confirmed that Lrp expression was significantly below our expectations.

![](https://static.igem.wiki/teams/5127/engineering/new/25.png)

*Figure 22. Translation rates with and without the RBS point mutation. A, Translation rate without the RBS point mutation. B, The decreased translation rate affected by the RBS point mutation.*

Thus, we decide to fix this mutation.

**Cycle #2: PpchA-RBS-Fixed biosensor validation**

### **Design (Cycle #2)**

We designed primers to fix the "T" of mutated RBS to "C" as the following.

![](https://static.igem.wiki/teams/5127/engineering/new/26.png)

*Figure 23. Difference of the two plasmids.*

See more details on [design page](https://2024.igem.wiki/bnds-china/design).

### **Build (Cycle #2)**

PCR and Golden Gate assembly were performed to achieve the change in sequence, fixing the wrong "T" back to "C". Agarose gel electrophoresis was performed and the bands indicate the correctness of the components' length.

![](https://static.igem.wiki/teams/5127/engineering/new/27.png)

*Figure 24. The AGE result of the PCR product for the construction of plasmid PpchA-RBS-fixed. A, materials of the construction. B, Goldengate assembly result of plasmid construction. The band at 5278bp in (B) indicated the success in plasmid construction.*

### **Test (Cycle #2)**

The RBS-fixed version of the plasmid is tranformed into E.coli strain Trelief 5α, and performed the same kinetics analysis as the previous plasmid verification.

Overnight cultures of PpchA-RBS-fixed transformed Trelief 5α cells in LB media at 37**°**C were 1:250 (v/v) inoculated into fresh M9 media with glucose,casamino and 1 thiamine, cultured for 3 hours and diluted to OD=0.01 using M9 media. Sodium butyrate was added to gain final concentrations of 100mM, 50mM, 25mM, 12.5mM, 6.25mM, 3.125mM, 1,5mM, 0.75mM, 0.38mM and 0mM as control (see protocol). The detailed plate setup is shown below in Table 4.

The results of the kinetics assay were used to calculate the fluorescence/OD curve (Figure 25). The fluorescence/OD curve of the groups showed a more significant difference, and a dynamic range that is around twice of the previous result. This shows that our fix was successful, and the pPcha/Lrp system could sense butyrate to some extent.

![](https://static.igem.wiki/teams/5127/engineering/new/28.png)

*Table 4. Plate layout of kinetics assay for PpchA-RBS-Fixed.*

![](https://static.igem.wiki/teams/5127/engineering/new/29.png)

*Figure 25. Kinetics of GFP expression over 16.7 hours. Fluorescence / ABS600 was used to represent GFP expression.*

### **Learn (Cycle #2)**

We successfully integrated the pPcha/Lrp sensor system with the cI repressor system (NOT gate) together to create a functional SCFA sensor, which could induce the expression of the gene of interest that is inversely proportional to the concentration of SCFA. However, through this result, we found the dynamic range of the pPcha promoter to be relatively small, only around 2 folds, which would raise certain limitations in our future product design. Thus, we want to explore some different possibilities of sensing butyrates. We chose to characterise pHpdH/HpdR from Pseudomonas putida.

## **Reference**

d’Oelsnitz, S., Stofel, S. K., Love, J. D., & Ellington, A. D. (2024). Snowprint: a predictive tool for genetic biosensor discovery. *Communications Biology*, *7*(1). <https://doi.org/10.1038/s42003-024-05849-8>

Kineret Serebrinsky-Duek, Barra, M., Danino, T., & Garrido, D. (2023). Engineered Bacteria for Short-Chain-Fatty-Acid-Repressed Expression of Biotherapeutic Molecules. *Microbiology Spectrum*, *11*(2). <https://doi.org/10.1128/spectrum.00049-23>

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>

Ruegg, T. L., Pereira, J. H., Chen, J. C., DeGiovanni, A., Novichkov, P., Mutalik, V. K., Tomaleri, G. P., Singer, S. W., Hillson, N. J., Simmons, B. A., Adams, P. D., & Thelen, M. P. (2018). Jungle Express is a versatile repressor system for tight transcriptional control. *Nature Communications*, *9*(1). <https://doi.org/10.1038/s41467-018-05857-3>

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>

Taketani, M., Zhang, J., Zhang, S., Triassi, A. J., Huang, Y.-J., Griffith, L. G., & Voigt, C. A. (2020). Author Correction: Genetic circuit design automation for the gut resident species Bacteroides thetaiotaomicron. *Nature Biotechnology*, *38*(8), 1001–1001. <https://doi.org/10.1038/s41587-020-0545-9>

{% endblock %}


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

![cover-back](https://static.igem.wiki/teams/5127/head/res.png)

## Menu

[Food Detection Module](#food-detection-module)
[Butyrate Sensing and Production Module](#butyrate-sensing-and-production-module)
[IAA Sensing and Degradation Module](#iaa-sensing-and-degradation-module)
[Reference](#reference)

## **Food Detection Module**

### Design and Construction of VFA0359-pDCA

In our platform design, DCA was adopted as food intake signal. To verify the inducibility of the DCA promoter (pVFA0359) in the presence of constitutive VFA0359 expression driven by apFAB254, GFP was inserted downstream of pVFA0359 as a reporter gene, which gives the overall plasmid named VFA0359-pDCA (Figure 1).

![](https://static.igem.wiki/teams/5127/results/figure-1.png)

*Figure 1.* *Plasmid design of* *VFA0359-pDCA. Created by* *biorender.com.*

The VFA0359, apFAB254, and pVFA0359 were synthesized by Genescript. We used Golden Gate Assembly assay to assemble the full plasmid, pDCA. PCR and Gel Electrophoresis were performed to verify the success in the fragment and backbone of the overall pDCA plasmid (Figure 2).

![](https://static.igem.wiki/teams/5127/results/2.jpg)

*Figure 2. The* *AGE* *result of the* *PCR* *products of* *VFA0359-pDCA construction. A, materials to construct pDCA. B, golden gate assembly result of* *VFA0359-pDCA construction. The band at 4544bp* *in (B) indicated the success in plasmid construction.*

### Characterization of DCA biosensor using pDCA

To assess DCA's inducibility on downstream genes, we quantified the relationship between DCA concentration and pVFA0359 activity. A gradient of DCA concentration was added to bacterial cultures, and the fluorescence / ABS600 values were measured over time using a plate-reader to assess promoter activity. The fluorescence exhibited concentration-dependent behavior. As the concentration of DCA in the medium increased, higher expression of GFP was induced in the bacteria (Figure 3).

![](https://static.igem.wiki/teams/5127/results/3.jpg)

*Figure 3.* *A kinetics* *assay for* *VFA0359-pDCA* *was conducted over 18 hours using various DCA concentrations. GFP expression was quantified by measuring fluorescence* */* *ABS600.* *Black, 1000μM DCA. Purple, 500μM DCA. Blue, 250μM DCA.* *Cyan, 125μM DCA. Green, 62.5μM DCA. Yellow, 31.25μM DCA. Orange, no DCA added.*

From this, it can be concluded that the activity of the pVFA0359 promoter can be induced by bile acid in *E.* *coli*, which demonstrated the biosensing capacity of this construct.

Nevertheless, it was also observed that the output in normalized fluorescence level at the highest induction concentration, 1000µM bile acid, was still low. This suggests a limited dynamic range for this biosensor. Thus, our team constructed an alternative DCA sensor for further investigation.

### Characterization of DCA biosensor using pBreR

We developed an alternative design for DCA detection. In this device, DCA inhibits the ability of the constitutively expressed repressor BreR to regulate the transcriptional activity of pBreR, therefore leading to the expression of downstream reporter gene. (Figure 4).

![](https://static.igem.wiki/teams/5127/results/4.jpg)

*Figure 4. Plasmid design of pBreR plasmid. Created by biorender.com.*

We used Golden Gate Assembly to construct pBreR plasmid. PCR and HGel Electrophoresis were performed to verify the materials of the assembly (Figure 5).

![](https://static.igem.wiki/teams/5127/results/5.jpg)

*Figure 5. The* *AGE* *result of the* *PCR* *products of materials to construct pBreR plasmid.*

To evaluate the inducibility of the downstream gene, we used GFP as the reporter gene to monitor promoter activity. Two cultures of *E. coli* transformed with the BreR plasmid were prepared, with DCA added to one. The DCA-treated culture exhibited strong green fluorescence, qualitatively demonstrating that our design can detect DCA. (Figure 6).

![](https://static.igem.wiki/teams/5127/results/6.jpg)

*Figure 6. Observation of pBreR with DCA+ (left) or DCA- (right). The left* *bacteria culture with DCA treatment* *showed* *strong* *green fluorescence.*

We quantified the relationship between DCA concentration and pBreR promoter activity. The dynamic range of BreR sensor system was about 6-fold with the maximum signal achieved at 500μM DCA; above 500μM, the change in promoter activity became subtle (Figure 7).

![](https://static.igem.wiki/teams/5127/results/7.jpg)

*Figure 7. Quantitative relationship between DCA concentration and fluorescence level.* *The* *GFP expression was quantified by measuring fluorescence / ABS600.*

Further, we characterized the kinetic behavior of this biosensor. A gradient of DCA concentration was added into bacterial cultures, and fluorescence / ABS600 values were measured over time using a plate-reader to assess promoter activity (Figure 8).

![](https://static.igem.wiki/teams/5127/results/8.jpg)

*Figure 8. A* *kinetic assay for GFP expression was conducted over 18 hours using various DCA concentrations. GFP expression was quantified by measuring fluorescence / ABS600\_\_.*

The results aligned with our expectations, in which bacteria cultures added with higher DCA concentration had stronger GFP expression levels. The dynamic range of BreR sensor system was about 5-fold at 1000μM DCA, much higher compared to that of pDCA system (about 2-fold).

This trend was especially clear when DCA concentration was above 62.5μM. When DCA concentration was below 62.5μM, the difference in DCA concentration between groups might be too small to be reflected in significant difference in GFP expression.

## **Butyrate** **Sensing** **and Production** **Module**

### Design and Construction of PpchA

The butyrate sensing device includes three promoters: J23101, PpchA, and pLam. The leucine-responsive regulatory protein Lrp was constitutively expressed as driven by J23101. Then, Lrp activates the expression of cI repressor in the presence of butyrate, and the cI protein inhibits promoter pLam activity (Figure 9). The pCI-Lam, PpchA, protein CI, and GFP were synthesized by Genscript. The Lrp protein was supported by NMU-China.

![](https://static.igem.wiki/teams/5127/results/figure-9.jpg)

*Figure 9. Plasmid design of PpchA. Created by biorender.com.*

### Characterization of butyrate biosensor using PpchA

Initially, our plasmid's RBS component, synthesized by Genscript, had an unwanted point mutation. But we did characterization to see whether it could still function well (Figure 10).

![](https://static.igem.wiki/teams/5127/results/10.jpg)

*Figure 10. Kinetics of PpchA (with* *RBS* *point mutation) with multiple butyrate concentrations over 18 hours. Fluorescence / ABS600 was used to represent GFP expression; higher fluorescence represented lower PpchA activity.*

The kinetics results of this error-containing plasmid did not achieved a desired performance: the dynamic range of this system was less than 1.5-fold at after added a gradient of butyrate concentration. Therefore, we've tried to fix the point mutation.

We used GoldenGate Assembly to construct PpchA-RBS-fixed. PCR and Gel Electrophoresis were performed to verify the success in constructing each component and the plasmid (Figure 11).

![](https://static.igem.wiki/teams/5127/results/11.jpg)

*Figure 11. The AGE results* *of the* *PCR* *products of PpchA construction. A, materials to construct PpchA. B,* *Goldengate assembly result of PpchA construction. The band at 5278bp* *in (B) indicated the success in plasmid construction.*

We again used kinetics to quantitatively test the effectiveness of the above design for butyrate detection. A gradient of butyrate concentration was added into *E. coli* transformed with PpchA, and the value of fluorescence / ABS600 over time was detected using the plate-reader to represent GFP expression levels (Figure 12).

![](https://static.igem.wiki/teams/5127/results/12.jpg)

*Figure 12. Kinetics of PpchA (RBS fixed) with multiple butyrate concentrations over 16.7 hours. Fluorescence / ABS600 was used to represent GFP expression; higher fluorescence represented lower PpchA activity.*

The overall performance of the PpchA-Lrp sensor is sufficient to demonstrate its ability to detect and respond to the presence of butyrate accurately at most butyrate concentrations. However, the sensor exhibits low sensitivity in distinguishing between small variations in butyrate levels; furthermore, the dynamic range of this detection system was only about 2-fold. This is likely attributed to the inherent limitation of this system, as a similar noisy butyrate induction pattern of PpchA-Lrp has been previously reported in literature (Serebrinsky-Duek et al., 2023). To address those limitations, we developed an alternative sensor, pHdpH, for further investigation.

### Characterization of butyrate biosensor using pHpdH

In our plasmid design for pHpdH, butyrate activates pHpdH in the presence of the constitutively expressed hpdR (Figure 13).

![](https://static.igem.wiki/teams/5127/results/figure-13.jpg)

*Figure 13. Plasmid design of pHpdH. Created by biorender.com.*

The hpdR, phpdH, and phpdR were synthesized from Gensript. We used Golden Gate Assembly to construct pHdpH. PCR and Gel Electrophoresis were performed to verify the success in constructing the fragment and backbone of the overall pHdpH plasmid (Figure 14).

![](https://static.igem.wiki/teams/5127/results/14.jpg)

*Figure 14. The* *AGE* *result of the* *PCR* *products of pHdpH construction. A, materials to construct pHdpH. B, golden gate assembly result of pHdpH construction. The band at 4555bp* *in (B) indicated the success in plasmid construction.*

We used kinetics to quantitatively test the effectiveness of this butyrate detection system. A gradient of butyrate concentration was added into *E. coli* transformed with pHpdH, and the value of fluorescence / ABS600 over time was detected using the plate-reader to represent GFP expression (Figure 15).

![](https://static.igem.wiki/teams/5127/results/15.jpg)

*Figure 15. Kinetics of GFP expression over 16.7 hours. Fluorescence / ABS600 was used to represent GFP expression.*

When the butyrate concentration was below 20mM, our system showed the desired trend, as fluorescence increases proportionally with butyrate concentration. Above this point, however, the system failed to distinguish between 20mM, 40mM, and 86mM butyrate. This might be because 20mM butyrate was sufficient to activate PhpdH to its highest activity. Since our goal was to detect the shortage of butyrate in the gut system, this result showed that our design was successful and achieved our goal.

### Characterization of butyrate biosensor using pHpdH-CI

To integrate the butyrate biosensor into our ultimate project goal, we designed the CI gene into the pHpdH sensing system plasmid. In this system, when butyrate levels are low, the output of GFP will be higher (Figure 16). This design enables us to monitor and respond to butyrate concentration effectively within our system.

![](https://static.igem.wiki/teams/5127/results/figure-16.jpg)

Figure 16. Plasmid design of HpdR-pHpdH-cI-GFP *Created by* *biorender.com.*

![](https://static.igem.wiki/teams/5127/results/17.jpg)

*Figure* *17. The* *AGE* *results of the* *PCR* *products of pHpdH-CI construction. The materials used to construct pHpdH-CI.*

We require additional time to further characterize and evaluate the degradation function to ensure optimal performance and reliability in our system.

### Verification of butyrate production by Tes4

In our plasmid design of Tes4, IPTG was added to induce the expression of Tes4 (Figure 18). The Tes4 DNA sequence and the vector pET-28a(+) were synthesized and obtained from Genscript.

![](https://static.igem.wiki/teams/5127/results/figure-18.jpg)

*Figure 18. Plasmid design of Tes4. Created by biorender.com.*

To verify the successful expression of Tes4 and its effectiveness to produce butyrate, we performed SDS-PAGE to the proteome of *E. coli* expressing Tes4. The band at 19.5kDa represented the successful expression of Tes4 (Figure 19).

![](https://static.igem.wiki/teams/5127/results/19.jpg)

*Figure 19. SDS-PAGE result of Tes4 production. Lane 1, Protein ladder. Lane 2, Tes4 plasmid with IPTG added. Lane 3, BL21 WT. Lane 4, Tes4 plasmid without IPTG added. Lane 6, Protein ladder.*

We also performed GC-MS to verify our system's ability to produce butyrate by Tes4. The peak at 11.39 min in (D) suggested the successful production of butyrate (Figure 20).

![](https://static.igem.wiki/teams/5127/results/20.jpg)

*Figure* *20. GC-MS results of butyrate production. Peaks at about 11.4 min represented butyrate. A, pET28a(+)-Tes4 IPTG(-). B, pET28a(+)-Tes4 IPTG(+) without lysis. C, LB blank (Maybe contaminated). D, pET28a(+)-Tes4 IPTG(+) after lysis. E,1mmol/3mL butyrate standard solution. F, 10mmol/3mL butyrate standard solution. The peaks at 11.25-11.45 min indicated the presence of butyrate.*

### Tes4 Genome Integration Test

We wish to incorporate Tes4 enzyme encoding genes into the genome of our bacteria to lower its burden and maintain better ability of butyrate production. Thus, we developed a genome integration technique using Lambda Red recombinase, and tested it.

#### Phase I

The pRed-Aspink expresses the Lambda Red recombinase under the control of an arabinose-inducible promoter. The plasmid also constitutively expresses the pigment protein asPink, which serves as a visual marker to confirm the presence of the plasmid in the host cells.

![](https://static.igem.wiki/teams/5127/results/21.jpg)

*Figure* *21. Plasmid design of pRed-Aspink. Created by* *biorender.com.*

The Lambda Red recombinase proteins was derived from BNDS-China previous plasmid stock, and Aspink protien was derived from 2023 iGEM distribution kit. We used Golden Gate Assembly to construct pRed-Aspink. PCR and Gel Electrophoresis were performed to verify the success in constructing the fragment and backbone of the full plasmid (Figure 22).

![](https://static.igem.wiki/teams/5127/results/22.jpg)

*Figure* *22.* *The Agarose gel electrophoresis result of the* *PCR* *products of pReplace construction. A,B, materials to construct pReplace. C, golden gate assembly result of pReplace construction. The band at 6910bp in (C) indicated the success in plasmid construction.*

The plasmid was transformed into *E. Coli* MG1655, with the colonies displaying a pink color, indicating the successful construction and transformation of the plasmid.

#### Phase II

The second plasmid, pDual-Select, was designed to facilitate both positive and negative selection. Initially, chloramphenicol resistance is used for positive selection, enabling the identification of colonies with successful transformation of pDual-Select. Following recombination by the Lambda Red system, the expression of SacB protein allows for negative selection, as SacB is lethal in the presence of sucrose. This step ensures that only colonies with the correct integration of the gene of interest into the genome survive.

![](https://static.igem.wiki/teams/5127/results/23.jpg)

*Figure* *23. Plasmid design of pDual-Select. Created by* *biorender.com.*

The sequence of homology arms and R6K Ori were obtained from BNDS-China's previous plamids. We used Golden Gate Assembly to construct pReplace. PCR and Gel Electrophoresis were performed to verify the success in constructing the fragment and backbone of the full plasmid (Figure 24).

![](https://static.igem.wiki/teams/5127/results/24.jpg)

*Figure* *24.* *The Agarose gel electrophoresis result of the PCR products of pReplace construction. A,materials to construct pReplace. B, golden gate assembly result of pReplace construction. The band at 5831bp in (B) indicated the success in plasmid construction.*

The plasmid was transformed into *E. Coli* Trelief 5-alpha for contruction, by plating them on the Kanamycin plates, the construction of this plasmid was being confirmed.

At the same time, the phase I cells were prepared as chemically competnet cells and induced with arabinose for a 3-hour resuscitation. The pDual-Select plasmid was then transformed into these Phase I competent cells, which were subsequently plated on chloramphenicol plates for selection. Only bacteria with successful genome integration of the plasmid will grow on the plate, due to the lost of the second plasmid (Figure 25).

![](https://static.igem.wiki/teams/5127/results/25.jpg)

*Figure* *25. The plating result of phase II cells.*

#### Phase III

The third plasmid we constructed was designed to facilitate the integration of the Gene of Interest (GOI) into the genome. This plasmid includes a barcode for colony PCR verification post-integration.

![](https://static.igem.wiki/teams/5127/results/26.jpg)

*Figure* *26. Plasmid design of pReplace.*

The sequence of homology arms and R6K Ori were obtained from BNDS-China's previous plamids. We used Golden Gate Assembly to construct pReplace. PCR and Gel Electrophoresis were performed to verify the success in constructing the fragment and backbone of the full plasmid (Figure 27).

![](https://static.igem.wiki/teams/5127/results/27.jpg)

*Figure* *27.* *The* *Agarose gel electrophoresis* *result of the* *PCR* *products of pReplace construction. A, B, materials to construct pReplace. C, golden gate assembly result of pReplace construction. The band at 2932bp in (C) indicated the success in plasmid construction.*

After transforming pReplace into Phase II competent cells, we initially observed a bacterial lawn on the plate (Figure 28A). After incubating the plate at 37 degree Celcius for three days, we identified single bacterial colony (Figure 28B). Then, we inoculated colonies and performed colony PCR, which showed the correct length, indicating successful integration (Figure 28C). However, due to limitations in sequencing capabilities in our lab, we were unable to obtain sequencing results for successful PCR products.

![](https://static.igem.wiki/teams/5127/results/28.jpg)

*Figure* *28. Observation and* *PCR* *verification of Phase III cells.* *A,* *The bacterial lawn of Phase III cells.* *B,* *The single colonies occur after being cultured at 37 degree Celsius for several days.* *C,* *The AGE result for Phase III colony PCR verification. The band at 1753bp* *indicates a successful amplification from* *genome.*

### Coupling the butyrate bioproduction to food detection

To implement our overall design, we placed Tes4 downstream to promoter pBreR to make the butyrate production responsive to the food availability. In this way, the presence of bile acid will trigger the expression of Tes4 and produce butyrate. We replaced the GFP reporter gene in the BreR-mediated DCA biosensor with the coding frame of Tes4 (Figure 29).

![](https://static.igem.wiki/teams/5127/results/figure-29.jpg)

*Figure 29. Plasmid design of BreR-Tes4. Created by biorender.com.*

We used Golden Gate Assembly to construct BreR-Tes4 from BreR backbone and Tes4 fragment. PCR and Gel Electrophoresis were performed to verify the success in constructing each component and the full plasmid (Figure 30).

![](https://static.igem.wiki/teams/5127/results/30.jpg)

*Figure 30. The* *AGE* *results* *of the* *PCR* *products of* *BreR* *construction. A and B, materials to construct BreR-Tes4. C,* *Golden gate assembly result of BreR-Tes4 construction. The band at 4372bp* *in (C) indicated the success in plasmid construction.*

We performed SDS-PAGE to verify the presence of Tes4. The band representing Tes4 (19.5kDa) was thicker in the DCA-treated group, showing the successful induction of Tes4 by DCA (Figure 31).

![](https://static.igem.wiki/teams/5127/results/31.jpg)

*Figure 31. The* *SDS-PAGE result of successful Tes4 expression induced by DCA.*

We are trying to further test the BreR-Tes4 plasmid with GC-MS assay to find out if there is any butyrate produced.

## IAA Sensing and Degradation Module

### Characterization of IAA biosensor

IAA was detected through its inducibility to the promoter pIacR. In our plasmid design, IAA activates pIacR in the presence of constitutively expressed iacR, therefore inducing the expression of the downstream gene (Figure 32).

![](https://static.igem.wiki/teams/5127/results/figure-32.jpg)

*Figure 32. Plasmid design of pIacR. Created by biorender.com.*

The iacR and PiacR that were used in this plasmid were synthesized by Genscript. We used kinetics to quantitatively test the effectiveness of IAA detection using the designed system above. A gradient of IAA concentration, from 0μM to 100μM was added into E. coli transformed with pIacR, and the value of fluorescence / ABS600 over time was detected using the microplate reader to represent GFP expression (Figure 33).

![](https://static.igem.wiki/teams/5127/results/33.jpg)

*Figure 33. Kinetics of pIacR over* *16.7* *hours. Fluorescence / ABS600 was used to represent GFP expression. The darker blue color, the higher* *IAA* *concentration. The numbers represent the concentration (in μM) of IAA added.*

After cultured at 37 ℃ for 18 hrs, the normative fluorescence/ABS 600 values increased as IAA concentration increased, showing the successful design of the IAA detection module.

### Verification of IAA degradation

In the IAA degradation module, we used IPTG to induce the expression of iadC, iadD, and iadE. They function together to degrade IAA (Figure 34).

![](https://static.igem.wiki/teams/5127/results/figure-34.jpg)

*Figure 34. Plasmid design of PiadCDE. Created by biorender.com.*

The iadC, iadD, and iadE were synthesized by Genscript. To verify the successful expression of iadC, iadD, and iadE, we performed PAGE to the expressed protein of E. coli transformed with PiadCDE with or without IPTG added. The bands at indicated lengths showed the successful expression of iadCDE (Figure 35).

![](https://static.igem.wiki/teams/5127/results/35.jpg)

*Figure 35. SDS-PAGE result of iadCDE expression. Lane 1, 6.5-200kDa protein ladder. Lane 2-4, PiadCDE with IPTG(+). Lane 5, PiadCDE with IPTG(**-**). Lane 6, 6.5-200kDa protein ladder. Lane 7-8 PiadCDE with IPTG(-).*

To verify the effectiveness of iadCDE degrading IAA, we used the Salkowski reagent to quantitatively detect the amount of IAA (Gordon et al, 1951). First, we constructed an IAA standard curve to show the feasibility of using the reagent to detect IAA. A gradient of IAA was mixed with Salkowski reagent (see our protocols) and waited for 1 hour for color formation. The absorbance at 530 nm was measured to indicate the IAA concentration, which shows an approximately linear relationship and thus validated the effectiveness of the Salkowski reagent in IAA concentration measurement (Figure 36).

![](https://static.igem.wiki/teams/5127/results/36.jpg)

*Figure 36. IAA* *standard curve.*

After ensuring the usefulness of the reagent, we cultured transformed bacteria together with IAA and made an IAA degradation curve. After induction, the group with PiadCDE but without IPTG showed higher IAA concentration than BL21 WT, while the group with PiadCDE with IPTG added showed a much lower amount of IAA compared to BL21 WT (Figure 37). This result showed our system could successfully degrade IAA by expressing iadCDE.

![](https://static.igem.wiki/teams/5127/results/37.jpg)

*Figure 37.* *IAA* *degradation curve. Black, BL21 WT. Red, E. coli transformed with PiadCDE with IPTG added. Blue, E. coli transformed with PiadCDE without IPTG added.*

### Verification of J23119-iadCDE

To optimize the IAA degradation efficiency, we constructed a second plasmid that replaces the inducible T7 promoter with the constitutive promoter J23119. This modification ensures continuous expression of the IAA degradation pathway, potentially enhancing its overall effectiveness.

![](https://static.igem.wiki/teams/5127/results/figure-38.jpg)

*Figure* *38. Plasmid design of J23119-iadCDE. Created by* *biorender.com.*

![](https://static.igem.wiki/teams/5127/results/39.jpg)

*Figure* *39. The AGE results of the* *PCR* *products of J23119-iadCDE construction. A, materials to construct J23119-iadCDE. B, Golden gate assembly result of J23119-iadCDE construction. The band at 7947bp in (B) indicated the success in plasmid construction.*

We require additional time to further characterize and evaluate the degradation function to ensure optimal performance and reliability in our system.

## Reference

Gordon, S. A., & Weber, R. P. (1951). Colorimetric Estimation of indoleacetic Acid. *Plant Physiology*, *26*(1), 192–195. <https://doi.org/10.1104/pp.26.1.192>

Kineret Serebrinsky-Duek, Barra, M., Danino, T., & Garrido, D. (2023). Engineered Bacteria for Short-Chain-Fatty-Acid-Repressed Expression of Biotherapeutic Molecules. *Microbiology Spectrum*, *11*(2). <https://doi.org/10.1128/spectrum.00049-23>

{% endblock %}