iGEM 2024 — Team gec-guangzhou

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CONTENT

[Sensing System](#a1)
[Daily Summary Plan for Sencing System Experiment (June 1- July 4, 2024)](#b1)
[Lab notebook - Sensory system（Total 56 pages）](#b2)
[Therapeutic System](#a2)
[Daily Summary Plan for Therapeutic System Experiment (July 10 - 30, 2024)](#b3)
[Lab notebook - Treatment system（Total 29 pages）](#b4)
[Suicide System](#a3)
[Daily Summary Plan for Suicide System Experiment (August 1-15, 2024)](#b5)
[Lab notebook - Suicide system（Total 38 pages）](#b6)

As members of the GEC-Guangzhou team, we have conducted a series of experiments focusing on three major systems: a sensing system, a therapeutic system, and a suicide system. These systems were developed and tested using engineered E. coli strains, with each system designed to address specific functional goals within our project.

Sensing System

The sensing system aimed to develop a mechanism in E. coli capable of detecting Initially, we designed a sensing system targeting tetrathionate, incorporating a plasmid with inducible promoters to express mRFP (red fluorescent protein) as the reporter gene. After conducting experiments with varying tetrathionate concentrations, we found that the response was insufficient and inconsistent, leading to a decision to shift our focus toward developing a thiosulfate sensor. In the new system targeting thiosulfate, we constructed a more sensitive plasmid incorporating improved promoters and downstream linkage to LacZ. LacZ enzymatically breaks down X-gal, producing a visible blue product that allowed for easier detection and measurement of the sensor’s performance. Extensive tests were conducted with different concentrations of sodium thiosulfate demonstrating a robust, dose-dependent increase in fluorescence and colorimetric output.

Daily Summary Plan for Sencing System Experiment (June 1- July 4, 2024)

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Date |

Experiment |

Details |

Notes |

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June 1, 2024 |

Synthesis and Plasmid Construction of TtrS/R |

Synthesize the Tetrathionate operon (TtrS/R) and clone it into a plasmid. Verify sequence using gel electrophoresis. |

Successful synthesis and plasmid extraction. Next step: cloning into different vectors. |

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June 2, 2024 |

Cloning of TtrS/R with mRFP into pSB1A3 |

Perform double digestion of TtrS, TtrR, mRFP, and pSB1A3, followed by ligation of fragments into the pSB1A3 plasmid. |

Successful ligation, next step: sequencing for verification. |

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June 3, 2024 |

Sequencing Verification and Transformation |

Verify accuracy of plasmid through sequencing, then transform into E. coli DH5α. |

Sequence verified, successful transformation observed with colony formation. |

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June 4, 2024 |

Amplification and Colony PCR |

Amplify E. coli DH5α colonies, extract plasmid, and perform colony PCR to verify correct insertion of TtrS/R-mRFP. |

PCR showed clear bands confirming correct insertion. |

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June 5, 2024 |

LB Media Preparation and Plasmid Extraction |

Prepare solid and liquid LB media and extract plasmid DNA from previously cultured E. coli DH5α. |

Successful media preparation and plasmid extraction (150 ng/µL). |

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June 6, 2024 |

Preparation of Tetrathionate Solutions |

Prepare 1 M sodium tetrathionate stock solution and serial dilutions (0 µM to 1000 µM). |

Standard solutions prepared successfully. |

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June 7, 2024 |

Transformation of E. coli BL21 with TtrS/R-mRFP |

Transform E. coli BL21 with the TtrS/R-mRFP plasmid for sensor development. |

Successful transformation, colonies observed on ampicillin plates. |

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June 8, 2024 |

Culture Amplification and Glycerol Stock Storage |

Amplify E. coli BL21 cultures and prepare glycerol stocks for long-term storage. |

10 glycerol stocks stored at -80°C. |

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June 9, 2024 |

Growth of E. coli in Tetrathionate Media |

Culture BL21 in LB with varying tetrathionate concentrations (0 µM to 1000 µM) for fluorescence testing. |

Cultures ready for fluorescence testing. |

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June 10, 2024 |

Fluorescence and OD600 Measurements |

Measure fluorescence and OD600 to assess sensor response to tetrathionate concentrations. |

Strong positive correlation between tetrathionate levels and fluorescence intensity. |

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June 11, 2024 |

Data Analysis and Validation |

Analyze fluorescence data and validate the sensor's response to tetrathionate. |

Consistent data across replicates, strong sensor response confirmed. |

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June 12-14, 2024 |

Report and Presentation Preparation |

Summarize experimental results, prepare the report, and create a PowerPoint presentation on sensor development and results. |

Initial draft of the report and PPT presentation completed. |

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June 15, 2024 |

Gene Synthesis and PCR for Thiosulfate Sensor |

Synthesize the Thiosulfate operon, extract the plasmid, and amplify gene fragments (ThsS, ThsR) via PCR. |

PCR products observed with correct band sizes on gel electrophoresis. |

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June 16, 2024 |

Restriction Digestion and Ligation |

Perform restriction digestion and ligation of Thiosulfate genes into pSB1A3 plasmid. |

Efficient ligation, ready for transformation into E. coli. |

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June 17, 2024 |

Transformation into E. coli DH5α |

Verify plasmid by sequencing and transform into E. coli DH5α for amplification. |

Transformation successful, colonies observed. |

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June 18, 2024 |

Transformation into E. coli BL21 |

Transform the Thiosulfate Sensor plasmid into E. coli BL21 for expression testing. |

Transformation successful, ready for sensor testing. |

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June 19, 2024 |

Initial Testing of Thiosulfate Sensor |

Test sensor response in E. coli BL21 by measuring fluorescence in response to thiosulfate concentrations. |

Significant increase in fluorescence at higher thiosulfate levels. |

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June 20, 2024 |

Design of Optimized Thiosulfate Sensor B |

Redesign promoter and RBS sequences to optimize sensor expression. |

New sequences submitted for gene synthesis. |

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June 21, 2024 |

Material Preparation for Sensor B Construction |

Prepare LB media, organize data, and ensure necessary materials are available for Sensor B construction. |

Lab ready for further experiments upon delivery of new DNA sequences. |

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June 22, 2024 |

Assembly of Thiosulfate Sensor B |

Integrate new promoter and RBS sequences with the thiosulfate operon into the pSB1A3 plasmid using Gibson Assembly. |

Gibson Assembly successful, plasmid extracted. |

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June 23, 2024 |

Transformation of Thiosulfate Sensor B |

Transform Sensor B plasmid into E. coli DH5α and extract for sequencing verification. |

Successful transformation and plasmid verification. |

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June 24, 2024 |

Transformation of Thiosulfate Sensor B into BL21 |

Transform the verified Sensor B plasmid into E. coli BL21 for functional testing. |

Multiple colonies observed, ready for functional sensor testing. |

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June 26, 2024 |

Dose-Dependence Analysis |

Evaluate dose-dependent fluorescence response of Sensor B to thiosulfate concentrations. |

Sensor B shows enhanced fluorescence at higher thiosulfate concentrations. |

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June 28-30, 2024 |

Data Compilation，Graphing，Statistical Analysis |

Writing the report |

no |

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July 1, 2024 |

Design and Construction of Thiosulfate Reporter System |

Designed the LacZα gene sequence regulated by the thiosulfate operon for β-galactosidase expression. Cloned LacZα into the pSB1A3 plasmid. |

Transformation into E. coli DH5α and sequencing successful |

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July 2, 2024 |

Transformation of pSB1A3-LacZα into BL21 |

Extracted the pSB1A3-LacZα plasmid and transformed it into E. coli BL21 for β-galactosidase activity testing. |

Multiple colonies observed on LB plates |

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July 3, 2024 |

Standard Curve Preparation for ONPG Assay |

Prepared standard solutions for p-nitrophenol (12.5-300 nM) and measured OD400 values to generate a standard curve for future β-galactosidase activity measurements. |

Standard curve successfully generated |

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July 4, 2024 |

ONPG β-galactosidase Assay |

Conducted ONPG assay to quantify β-galactosidase activity in BL21 cells containing pSB1A3-LacZα across different thiosulfate concentrations (0 to 1 mM). |

Successful assay, β-galactosidase activity measured |

Lab notebook - Sensory system（Total 56 pages）

Therapeutic System

Our therapeutic system focused on constructing plasmids capable of expressing therapeutic proteins, such as hEGF (human epidermal growth factor), in E. coli. The goal was to optimize the expression and secretion of hEGF using engineered secretion pathways. Various plasmid constructs were created, including those with inducible promoters controlling the expression of hEGF. The experiments included testing the protein's secretion levels in the bacterial cultures and assessing the biological activity of hEGF on mammalian cell lines. ELISA assays confirmed the presence of secreted hEGF, and subsequent activity tests showed significant positive effects on cell growth and viability, validating the system’s potential as a therapeutic tool.

Daily Summary Plan for Therapeutic System Experiment (July 10 - 30, 2024)

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Date |

Experiment |

Details |

Notes |

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July 10, 2024 |

Plasmid Synthesis and Preparation |

Synthesis of pSB-PEA plasmid (with hEGF and secretion elements) and pSB-PE control plasmid. Prepared LB medium, ampicillin plates, and competent cells (E. coli DH5α, EcN). |

All materials and competent cells prepared for transformation. |

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July 11, 2024 |

Transformation of pSB-PEA into E. coli |

Transformed pSB-PEA and pSB-PE into E. coli DH5α and E. coli Nissle 1917. |

Plates incubated overnight for colony formation. |

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July 12, 2024 |

Colony Selection and Plasmid Extraction |

Selected colonies, performed plasmid extraction, and verified via PCR for gene insertion (hlyB, hlyD, hEGF). |

Correct PCR bands confirmed plasmid construction. |

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July 13, 2024 |

Plasmid Ligation and Amplification |

Amplified pSB-PEA plasmid, performed double digestion, and ligated hEGF and secretion elements into the plasmid backbone. |

Ligation product ready for transformation. |

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July 14, 2024 |

Failed Transformation Attempt |

Transformation of pSB-PEA into E. coli DH5α failed, no colonies observed. |

Planned adjustments: increased ligation time and fresh competent cells. |

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July 15, 2024 |

Successful Transformation into E. coli DH5α |

After adjusted ligation and transformation, colonies successfully formed on ampicillin plates. |

Proceed to plasmid extraction and verification. |

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July 16, 2024 |

Plasmid Verification and Amplification |

Amplified bacterial cultures, extracted plasmids, and verified gene insertion via PCR. |

PCR results confirmed correct plasmid insertion. |

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July 17, 2024 |

Failed hEGF Expression Induction |

Attempted to induce hEGF expression but no secretion detected via ELISA. |

Plan to optimize sodium thiosulfate concentration. |

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July 18, 2024 |

Re-induction of hEGF Expression |

Adjusted sodium thiosulfate concentration and repeated induction, successfully detected hEGF secretion in extracellular samples. |

Highest hEGF levels observed in EcN/pSB-PEA. |

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July 19, 2024 |

Intracellular hEGF Detection |

Detected intracellular hEGF via ELISA in induced strains (EcN/pSB-PEA and EcN/pSB-PE). |

Intracellular hEGF confirmed, especially in EcN/pSB-PEA. |

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July 20, 2024 |

hEGF Activity Test on 293T Cells |

Prepared EcN-derived hEGF samples and began treatment of 293T cells. |

Initial setup, CCK8 assay to follow the next day. |

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July 21-22, 2024 |

293T Cell Viability Detection |

CCK8 assay on 293T cells treated with hEGF, but no significant improvement in cell viability was detected. |

Adjust concentration and incubation time. |

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July 23, 2024 |

Optimized 293T Cell Viability Assay |

Retested 293T cell viability with optimized hEGF concentrations and incubation time. |

Significant improvement in cell viability for EcN/pSB-PEA group. |

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July 24-26, 2024 |

Data Analysis and Graph Generation |

Organized and analyzed data from ELISA and CCK8 assays, generated graphs showing hEGF expression levels and cell viability. |

Clear evidence of hEGF expression and its impact on cell viability. |

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July 27-30, 2024 |

Report Writing and Presentation Preparation |

Compiled experimental data into a report and prepared a PowerPoint presentation. |

Finalized report and presentation for submission. |

Lab notebook - Treatment system（Total 29 pages）

Suicide System

The suicide system was designed as a safety mechanism to control bacterial growth. It employed the mazE-mazF toxin-antitoxin system, where the toxin gene mazF was activated by an arabinose-inducible promoter, while the antitoxin mazE was controlled by a rhamnose-inducible promoter. Upon activation, mazF expression led to cell death unless counterbalanced by mazE expression. The system was rigorously tested through growth inhibition assays, which measured OD600 to track bacterial survival under various induction conditions. The results confirmed that the system functioned as intended, with induced expression of mazF leading to significant bacterial cell death, providing an effective biocontainment strategy.

These three systems—sensing, therapeutic, and suicide—form the core of our project, each playing a critical role in demonstrating the versatility and safety of engineered bacterial systems for potential applications in environmental sensing and therapeutic delivery.

Daily Summary Plan for Suicide System Experiment (August 1-15, 2024)

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Date |

Experiment |

Details |

Notes |

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Aug 1, 2024 |

Preparation of Competent Cells |

Prepare competent E. coli BL21 cells using the calcium chloride method. |

Keep the cells on ice throughout the procedure |

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Aug 2, 2024 |

Construction of Recombinant Plasmid |

Perform double enzyme digestion on pSB1A3-mRFP plasmid and the synthesized PRha gene. Ligate the digested products to create the recombinant plasmid pSB1A3-PRha-mRFP. |

Ensure efficient digestion and ligation, run agarose gel to confirm digestion |

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Aug 3, 2024 |

Transformation and Screening of Positive Colonies |

Transform the pSB1A3-PRha-mRFP recombinant plasmid into competent E. coli BL21 cells. Plate on LB-ampicillin plates and incubate overnight at 37°C. |

Include positive and negative controls during transformation |

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Aug 4, 2024 |

Colony PCR for Positive Colony Screening |

Perform colony PCR on selected colonies to confirm successful insertion of the PRha-mRFP cassette. Extract plasmids from positive colonies using a plasmid mini-prep kit for further testing and storage. |

Select 4-6 positive colonies for PCR, ensure high plasmid yield for downstream experiments |

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Aug 5, 2024 |

Rhamnose-Inducible Promoter Testing |

Inoculate a 1:100 dilution of overnight cultures into M9 medium supplemented with ampicillin and 0.4% glucose. Add varying concentrations of rhamnose (0.1%-1%). Incubate at 37°C for 5 hours, then measure OD600 and fluorescence using a microplate reader. |

Ensure all samples are mixed well and include appropriate controls (no rhamnose and varying rhamnose concentrations) |

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Aug 6, 2024 |

Fluorescence Data Analysis |

Analyze the normalized fluorescence (Fluorescence/OD600) data to assess the effect of rhamnose on gene expression. Compare results for different concentrations. |

Plot the results to visualize dose-response to rhamnose |

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Aug 7, 2024 |

Construction of Suicide System Plasmid |

Clone the mazE (antitoxin) and mazF (toxin) genes into the pSB1A3 vector under rhamnose and arabinose promoters, respectively. Sequence the plasmid to verify successful cloning. |

Ensure correct assembly and sequence verification |

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Aug 8, 2024 |

Transformation of Suicide System Plasmid |

Transform the suicide system plasmid into E. coli BL21 and plate on LB-ampicillin agar. Incubate at 37°C overnight. |

Check transformation efficiency by colony count |

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Aug 9, 2024 |

Colony PCR |

Perform colony PCR on selected colonies to verify the presence of the mazE-mazF system. |

Use specific primers for mazE and mazF |

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Aug 10, 2024 |

Suicide System Testing |

Inoculate 1:100 dilutions of confirmed positive colonies into M9 medium with ampicillin, 1% rhamnose, 0.2% arabinose, and 0.4% glucose. Monitor OD600 hourly over 5 hours to assess the impact of the suicide system on cell growth. |

Ensure OD600 measurements are consistent across samples |

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Aug 11, 2024 |

Growth Curve Analysis |

Analyze the OD600 data to evaluate growth inhibition caused by the mazE-mazF system. Compare growth with and without inducers. |

Plot growth curves for comparison |

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Aug 12, 2024 |

Re-transformation & Additional Testing |

An errors occur during colony PCR or testing, re-transform the suicide plasmid and repeat necessary tests (colony PCR, growth assay). |

Focus on troubleshooting any issues in cloning or transformation |

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Aug 13, 2024 |

Induction Optimization |

Test different concentrations of rhamnose and arabinose to optimize the induction of the suicide system. Measure OD600 at regular intervals to track the system's effect on bacterial growth. |

Analyze how varying inducer concentrations affect growth |

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Aug 14, 2024 |

Data Compilation & Analysis |

Compile all collected data from fluorescence measurements, OD600 readings, and PCR results. Perform statistical analysis to confirm significance of results. |

Prepare figures and graphs for presentation. |

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Aug 15, 2024 |

Final Report & Presentation Preparation |

Summarize all experimental results. Prepare a detailed report with all figures, growth curves, and statistical analysis for the suicide system. |

Ensure all documentation is clear and ready for submission |

Lab notebook - Suicide system（Total 38 pages）

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{% block title %}Engineering Success{% endblock %}
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CONTENT

[Abstract](#a1)
[System 1: Sensing system](#a2)
[Cycle 1: Design and Optimization Using Tetrathionate as a Biomarker](#b1)
[Cycle 2: Design and Optimization Using Thiosulfate as a Biomarker](#b2)
[Cycle3: Thiosulfate Biosensor Optimization and Evaluation](#b3)
[Cycle 4: Visualizing Inflammation Detection via Color Change](#b4)
[System 2: Therapeutic System](#a3)
[Cycle 5: Development and Testing of the Therapeutic System](#b5)
[System 3: Suicide System](#a4)
[Cycle 6: Development and Testing of Rhamnose-Inducible Reporter Strain](#b6)
[Cycle 7: Construction and Evaluation of Rhamnose-Inducible Reporter Strain](#b7)
[Reference：](#a5)

Abstract

We aimed to develop a comprehensive bacterial system with three core functions: sensing, therapy, and a safety suicide mechanism. First, we designed a biosensor to detect gut inflammation, initially using tetrathionate as a biomarker, but later shifting to thiosulfate for improved stability. Through iterative cycles, we optimized the sensing system by incorporating the ThsS/ThsR operon and developing Thiosulfate biosensor-B, which showed enhanced sensitivity and specificity. To make the detection visually accessible, we added the lacZ gene, allowing the bacteria to turn blue upon sensing inflammation. For the therapeutic component, we engineered bacteria to secrete human epidermal growth factor (hEGF) in response to inflammation, which significantly improved 293T cell viability in vitro. Our next step involves integrating these systems into E. coli Nissle 1917, using CRISPR-Cas9 to knock out its native β-galactosidase, thus ensuring the entire system can function safely and effectively as an oral therapy for gut inflammation, with a suicide mechanism to prevent environmental release.

![](https://static.igem.wiki/teams/5084/engineering/img1.png)

The construction of the three systems—the sensing system, the therapeutic system, and the suicide system—follows engineering design principles.

System 1: Sensing system

Cycle 1: Design and Optimization Using Tetrathionate as a Biomarker

**Design**

In the initial phase, we aimed to create a biosensor for detecting tetrathionate, a key biomarker of inflammatory bowel disease (IBD). We designed the biosensor by incorporating the TtrS/TtrR operon, which enables the detection of tetrathionate, along with the red fluorescent protein mRFP1 as a reporter. This setup would allow us to detect tetrathionate levels in real time based on fluorescence signals.

![](https://static.igem.wiki/teams/5084/engineering/img2.png)

Figure 1. The gene circuit of Tetrathiosulfate biosensor.

**Build**

We synthesized the TtrS (BBa\_K5084000) and TtrR (BBa\_K5084001) operon and used the PphsA promoter (BBa\_K5084002) to drive the expression of mRFP1. These genetic components were then cloned into the pSB1A3 plasmid to form a recombinant construct. After assembling the plasmid, it was transformed into E. coli DH5α and cultured in LB medium with ampicillin (100 μg/mL) to ensure stable growth and expression of the tetrathionate biosensor.

![](https://static.igem.wiki/teams/5084/engineering/img3.png)

Figure 2. Agarose gel electrophoresis of TtrS and TtrR.

**Test**

To evaluate the performance of the Tetrathiosulfate biosensor, E. coli strains were inoculated into LB media containing different concentrations of tetrathionate (0 µM to 1000 µM). After 8 hours of incubation, fluorescence intensity and OD600 were measured, and the normalized fluorescence ratio (Fluorescence/OD600) was calculated. Results showed a rapid increase in fluorescence at lower concentrations (0 to 50 µM), indicating high sensitivity, with a significant response between 10 µM and 50 µM. Beyond 100 µM, the signal plateaued, suggesting saturation.

![](https://static.igem.wiki/teams/5084/engineering/img4.png)

Figure 3. Tetrathionate biosensor response to varying tetrathionate concentrations.

**Learn**

Although our sensor performed well in detecting tetrathionate in vitro, literature review revealed that tetrathionate is rapidly metabolized by gut microbiota, reducing its effectiveness as an IBD biomarker in vivo. This led us to reconsider tetrathionate as the primary marker, shifting our focus to thiosulfate for more stable detection in future designs.

Cycle 2: Design and Optimization Using Thiosulfate as a Biomarker

**Design**

To address the limitations of tetrathionate, we switched to thiosulfate, a more stable biomarker for gut inflammation. We designed a new biosensor named Thiosulfate biosensor-A, using the ThsS/ThsR operon to specifically detect thiosulfate. The sensor is coupled with mRFP1, which is driven by the PphsA promoter, allowing us to visually track thiosulfate levels through fluorescence.

![](https://static.igem.wiki/teams/5084/engineering/img5.png)

Figure 4. The gene circuit of Thiosulfate biosensor-A.

**Build**

We synthesized the ThsS (BBa\_K5084010) and ThsR (BBa\_K5084011) operon and used the PphsA promoter to drive the expression of mRFP1. These components were cloned into the pSB1A3 plasmid, forming the thiosulfate biosensor construct. The plasmid was transformed into E. coli DH5α and cultured in LB medium containing ampicillin (100 μg/mL) to generate the engineered strain.

![](https://static.igem.wiki/teams/5084/engineering/img6.png)

Figure 5. Agarose gel electrophoresis of ThsS, ThsR and PphsA.

**Test**

To validate the function of Thiosulfate biosensor-A, we inoculated the strain into LB medium with varying concentrations of sodium thiosulfate (0 mM, 0.2 mM, and 1 mM) and incubated it at 37°C for 8 hours. After incubation, fluorescence intensity (excitation wavelength at 584 nm, emission wavelength at 607 nm) and OD600 values were measured, and the normalized fluorescence ratio (Fluorescence/OD600) was calculated. The results showed that in the absence of sodium thiosulfate, the sensor displayed very low fluorescence, indicating minimal background noise and a low likelihood of false positives. At 0.2 mM sodium thiosulfate, fluorescence increased significantly, indicating clear sensor activation. At 1 mM, fluorescence further increased, demonstrating a strong concentration-dependent response.

![](https://static.igem.wiki/teams/5084/engineering/img7.png)

Figure 6. Tetrathionate biosensor response to varying tetrathionateconcentrations.

**Learn**

This round of development demonstrated that our sensor reliably detects thiosulfate and exhibits a strong response to increasing concentrations. However, to improve the sensor’s performance further, future work will focus on optimizing its sensitivity to lower concentrations of thiosulfate and testing it in more complex biological environments.

Cycle3: Thiosulfate Biosensor Optimization and Evaluation

**Design**

To enhance the sensitivity and accuracy of our thiosulfate biosensor, we optimized Thiosulfate biosensor-A and developed an improved version, Thiosulfate biosensor-B (BBa\_K5084013). The primary optimization strategy involved modifying the promoter of ThsR and adjusting the ribosome binding site (RBS) sequences for both ThsS and ThsR. These changes were designed to balance the expression of the sensing system, improving both the response speed and sensitivity to thiosulfate (Figure 7).

![](https://static.igem.wiki/teams/5084/engineering/img8.png)

Figure 7. The plasmid map of Thiosulfate biosensor-B.

**Build**

During the optimization process, we replaced the promoter of ThsR and adjusted the RBS sequences of both ThsS and ThsR to enhance their translation efficiency and sensing capabilities. This fine-tuning of the regulatory elements allowed Thiosulfate biosensor-B to detect changes in thiosulfate concentrations more efficiently and sensitively than Thiosulfate biosensor-A (Figure 8).

![](https://static.igem.wiki/teams/5084/engineering/img9.png)

Figure 8. Comparison of the key differences between Thiosulfate biosensor-A and Thiosulfate biosensor-B.

**Test**

To evaluate the performance of Thiosulfate biosensor-B, we conducted multiple rounds of screening and functional testing under conditions identical to those used for Thiosulfate biosensor-A. The engineered bacterial strains were inoculated into LB medium containing different concentrations of sodium thiosulfate (0 mM and 1 mM) and incubated at 37°C for 8 hours. After incubation, we measured the fluorescence intensity (excitation at 584 nm, emission at 607 nm) and OD600 using a microplate reader. The normalized fluorescence ratio (Fluorescence/OD600) was calculated to assess the biosensor’s sensitivity. The results demonstrated that both Thiosulfate biosensor-A and B exhibited low and comparable fluorescence signals in the absence of thiosulfate, indicating minimal background noise. However, Thiosulfate biosensor-B showed a significantly higher response to 1 mM sodium thiosulfate, with markedly increased fluorescence intensity compared to Thiosulfate biosensor-A. This indicates that the modifications to the promoter and RBS sequences successfully enhanced the sensitivity of Thiosulfate biosensor-B (Figure 9).

![](https://static.igem.wiki/teams/5084/engineering/img10.png)

Figure 9. Comparison of normalized fluorescence ratios before and after the optimization of the thiosulfate biosensor.

To evaluate the dose-dependence of Thiosulfate biosensor-B, we measured its fluorescence response under different concentrations of sodium thiosulfate. The engineered strain was inoculated into LB medium containing 0, 0.125, 0.25, 0.5, and 1 mM of sodium thiosulfate and incubated at 37°C for 8 hours. After incubation, fluorescence intensity was measured using a microplate reader, and the values were normalized to OD600 (Fluorescence/OD600) to account for variations in cell growth. The results showed a clear increase in the normalized fluorescence ratio as the concentration of sodium thiosulfate increased. At 0 mM, the fluorescence signal was very low, indicating that the sensor was inactive. At 0.125 mM, the fluorescence ratio rose sharply, demonstrating the sensor’s responsiveness to low concentrations of thiosulfate. As the concentration increased to 0.25 mM, the fluorescence signal continued to strengthen, nearing saturation at 0.5 mM. Beyond 1 mM, the response plateaued, indicating that the sensor’s response had stabilized at higher concentrations. These results demonstrate that Thiosulfate biosensor-B exhibits clear dose-dependence, with saturation occurring around 0.5 mM and stabilization at 1 mM, suggesting optimal performance at approximately 0.5 mM.

![](https://static.igem.wiki/teams/5084/engineering/img11.png)

Figure 10. Dose-Dependence Analysis of the Thiosulfate Biosensor-B.

To evaluate the specificity of Thiosulfate biosensor-B, we tested its response to various sulfate-based compounds, including sodium sulfate, sodium sulfite, sodium tetrathionate, and sodium thiosulfate, all at 1 mM concentration. After 8 hours of incubation at 37°C, fluorescence values were measured and normalized to OD600. The results showed very low responses to sulfate and sulfite, indicating that the biosensor was not activated by these compounds. There was a moderate response to tetrathionate, suggesting some cross-reactivity, but given its role as an inflammatory biomarker, this level is acceptable. The strongest response was observed with thiosulfate, confirming that the biosensor is highly specific to thiosulfate and minimally affected by structurally similar compounds. These findings demonstrate the high specificity and reliability of the biosensor for detecting thiosulfate.

![](https://static.igem.wiki/teams/5084/engineering/img12.png)

Figure 11. Normalized fluorescence response of the thiosulfate biosensor to various sulfate-based compounds.

**Learn**

Through optimization, we successfully developed Thiosulfate biosensor-B and conducted dose-dependence and specificity experiments. The results demonstrated that the sensor’s sensitivity and specificity for detecting thiosulfate met our expectations and performed well. Moving forward, we plan to further improve the sensor by making the detection results visually accessible, enhancing its practical application.

Cycle 4: Visualizing Inflammation Detection via Color Change

**Design**

In this phase, our goal was to visually confirm the detection of gut inflammation. We designed a system where, upon detecting inflammation, the patient's stool would turn blue. This was achieved by incorporating the lacZ gene downstream of our sensory system, as lacZ encodes β-galactosidase, an enzyme capable of breaking down X-gal to produce a blue color. This design allows for a clear, visual indicator of inflammation.

![](https://static.igem.wiki/teams/5084/engineering/img13.png)

Figure 12. The gene circuit of Tetrathiosulfate biosensor.

**Build**

We constructed the lacZ system by synthesizing the thiosulfate operon (including ThsS and ThsR) and coupling it with the lacZ gene under the control of the PphsA promoter. The gene fragments were cloned into the pSB1A3 plasmid and successfully validated through sequencing. The plasmid was then transformed into E. coli DH5α, creating the engineered strain capable of producing β-galactosidase upon sensing thiosulfate.

![](https://static.igem.wiki/teams/5084/engineering/img14.png)

Figure 13. Agarose gel electrophoresis of LacZα.

**Test**

To determine the β-galactosidase activity, we used the ONPG method. The engineered bacteria were cultured in LB medium and treated with varying concentrations of thiosulfate. After incubation, we measured β-galactosidase activity by assessing the hydrolysis of ONPG into ortho-nitrophenol (ONP), which can be quantified at OD400. Also, 1 mL sample of the bacterial culture was collected into a centrifuge tube, and an appropriate amount of X-gal was added. The culture was incubated at 37°C, and color changes were observed to determine β-galactosidase activity, which indicates the degradation of X-gal. The results showed a direct correlation between thiosulfate concentration and enzyme activity, confirming that the sensor activates β-galactosidase production in response to thiosulfate. Through the addition of X-gal, we successfully observed the blue color reaction produced by β-galactosidase.

![](https://static.igem.wiki/teams/5084/engineering/img15.png)

Figure 14. The β-galactosidase activity of PphsA-LacZα. (A) ONPG standard curve. (B) The OD400 values at different concentrations of thiosulfate. (C)The enzyme activity under different concentration of thiosulfate. (D)Generation of o-Nitrophenol in ONPG Assay for β-Galactosidase. (E)X-gal reaction: blue product intensity as an indicator of enzyme activity.

**Learn**

With the successful construction of the sensory system, we confirmed that the engineered bacteria can detect gut inflammation and produce β-galactosidase in response, which degrades X-gal, leading to the production of a blue color. Moving forward, we aim to integrate this system with in-situ therapeutic mechanisms, allowing the engineered bacteria not only to detect inflammation but also to treat it at the site of infection.

System 2: Therapeutic System

Cycle 5: Development and Testing of the Therapeutic System

**Design**

In this cycle, we aimed to develop a therapeutic system that could be activated upon detecting gut inflammation. We constructed two recombinant plasmids: pSB-PE and pSB-PEA. The pSB-PE plasmid contains the thiosulfate sensing system (ThsS/R) and the Hly-EGF expression module (encoding human epidermal growth factor, hEGF). In contrast, pSB-PEA includes the complete α-hemolysin secretion system (hlyB BBa\_K5084015 and hlyD BBa\_K5084016 genes) to promote hEGF secretion. These constructs were used to test the secretion efficiency of hEGF in engineered E. coli strains under simulated colitis conditions.

![](https://static.igem.wiki/teams/5084/engineering/img16.png)

Figure 15. Construction of pSB-PE and pSB-PEA. (A) The gene circuit of pSB-PE. (B)The plasmid map of pSB-PE

**Build**

The plasmids were successfully constructed and transformed into both E. coli DH5α and E. coli Nissle 1917 (EcN). The pSB-PE strain served as a control, lacking the secretion system, while the pSB-PEA strain included the α-hemolysin system to enhance hEGF secretion. Both strains were tested for hEGF production and secretion efficiency.

![](https://static.igem.wiki/teams/5084/engineering/img17.png)

Figure 16. Agarose gel electrophoresis of Hly-EGF, hlyB and hlyD

**Test**

To assess the secretion efficiency of hEGF in different cellular environments, E. coli Nissle 1917 (EcN) expressing hEGF was cultured in LB medium with varying concentrations of sodium thiosulfate (0 mM and 1 mM). The extracellular and intracellular hEGF levels were measured using ELISA after cell lysis and separation of supernatant. Results showed that at 1 mM thiosulfate, the EcN/pSB-PEA strain, which incorporates the α-hemolysin secretion system, significantly increased extracellular hEGF levels (19.92 ± 1.67 μg/L) compared to EcN/pSB-PE (2.37 ± 0.44 μg/L). Simultaneously, intracellular hEGF was reduced in the EcN/pSB-PEA strain (8.16 ± 1.19 μg/L) compared to EcN/pSB-PE (17.15 ± 1.18 μg/L), indicating that the α-hemolysin secretion system enhances secretion efficiency by promoting hEGF release into the extracellular environment.

![](https://static.igem.wiki/teams/5084/engineering/img18.png)

Figure 17. EGF secretion test of pSB-PE and pSB-PEA. (A) Periplasmic sample. (B) Intracellular sample.

To evaluate the impact of hEGF secretion on 293T cell viability, E. coli Nissle 1917 (EcN) strains expressing hEGF (pSB-PE and pSB-PEA) were cultured in LB medium with 1 mM sodium thiosulfate, followed by collection of extracellular supernatant and bacterial content samples. These were applied to 293T cells cultured to 70% confluency, and after 8 hours of incubation, cell viability was measured using a CCK8 assay. Results showed that in the supernatant group, the EcN/pSB-PEA strain (with the α-hemolysin secretion system) had the highest A450 value (2.87 ± 0.41), indicating improved 293T cell viability due to enhanced extracellular hEGF secretion. In the bacterial content group, the EcN/pSB-PE strain had a higher A450 value (4.75 ± 0.49), suggesting more intracellular hEGF accumulation. Overall, the α-hemolysin system in the EcN/pSB-PEA strain significantly boosted hEGF secretion, enhancing extracellular activity and cell viability.

![](https://static.igem.wiki/teams/5084/engineering/img19.png)

**Learn**

The successful construction and testing of our therapeutic system showed promising results in cell-based experiments. The engineered EcN/pSB-PEA strain significantly increased the extracellular secretion of hEGF, leading to enhanced cell viability. Moving forward, our next step is to develop a safety suicide system to prevent the accidental release of engineered strains and their genetic material into the environment.

**Future Work**

Currently, our sensory system is developed in E. coli DH5α, while the therapeutic system is tested in EcN. However, EcN naturally produces β-galactosidase, which can break down X-gal, rendering our color-based sensory system ineffective. To address this, we plan to use CRISPR-Cas9 technology to knock out the β-galactosidase gene in EcN, allowing us to integrate both the sensory and therapeutic systems into this strain. Since EcN is non-toxic and suitable for oral administration, this will make the system safer and more effective for real-world applications.

System 3: Suicide System

Cycle 6: Development and Testing of Rhamnose-Inducible Reporter Strain

**Design**

The goal of constructing a rhamnose-inducible reporter strain was to develop a controllable gene expression system, using L-rhamnose as the inducer. The design began with selecting the rhamnose-inducible promoter (PRha) and ribosome binding site (RBS) B0034. These genetic elements were synthesized and cloned into the pSB1A3 plasmid using the XbaI and SpeI restriction sites. The coding sequence of the red fluorescent protein (mRFP) was inserted downstream of the promoter, serving as the reporter. This gene circuit, as depicted in Figure 15, allows the measurement of fluorescence as an output signal in response to L-rhamnose.

.

![](https://static.igem.wiki/teams/5084/engineering/img20.png)

Figure 20. The gene circuit of rhamnose-inducible reporter strain

**Build**

After successful cloning, the recombinant plasmid was transformed into E. coli BL21 cells using the calcium chloride heat-shock method, ensuring that the bacterial strain would express mRFP in the presence of L-rhamnose.

**Test**

During the test phase, we evaluated the response of the E. coli BL21 strain with the rhamnose-inducible system to different concentrations of L-rhamnose. First, a 1:100 dilution of the strain was inoculated into LB medium and cultured overnight at 37°C. The next day, the overnight culture was further diluted 1:50 into fresh M9 medium containing 50 μg/mL ampicillin and 0.4% glucose. Simultaneously, L-rhamnose at concentrations ranging from 0.1% to 1% was added to induce the system. After 5 hours of incubation at 37°C, 1 mL of the culture was sampled, and the OD600 was measured. Fluorescence was measured using a microplate reader (excitation at 584 nm, emission at 607 nm). The normalized fluorescence intensity (Fluorescence/OD600) was calculated to assess the reporter strain’s activity. The results showed that the strain exhibited very low fluorescence in the absence of L-rhamnose. When 0.1% L-rhamnose was added, the fluorescence signal increased significantly, indicating successful system activation. As the concentration of L-rhamnose increased to 0.5% and 1%, the fluorescence intensity further increased, demonstrating a concentration-dependent response (Figure 21).

![](https://static.igem.wiki/teams/5084/engineering/img21.png)

Figure 21. Rhamnose-inducible reporter strain response to varying L-rhamnose concentrations

**Learn**

When different concentrations of L-rhamnose were added, the fluorescence signal increased proportionally, demonstrating a clear dose-dependent response. At 0.1% L-rhamnose, the system was successfully activated, and at higher concentrations (0.5% and 1%), the fluorescence intensity further increased. This result demonstrates that the system is a reliable tool for controlling gene expression based on L-rhamnose concentration, making it suitable for future applications.

Cycle 7: Construction and Evaluation of Rhamnose-Inducible Reporter Strain

**Design**

To create a controllable suicide system, a two-component circuit was designed. The antitoxin gene (mazE) was placed under the control of the rhamnose-inducible promoter (PRha) and RBS B0034, while the toxin gene (mazF) was regulated by the arabinose-inducible promoter (pBAD). This design allows precise control over the balance between toxin and antitoxin expression depending on the presence of rhamnose and arabinose, as depicted in Figure 22. The system’s modular structure enables selective bacterial cell death based on specific environmental conditions.

![](https://static.igem.wiki/teams/5084/engineering/img22.png)

Figure 22. The gene circuit of rhamnose-inducible reporter strain

**Build**

The synthesized mazE and mazF genes were cloned into the pSB1A3 plasmid, and the construction was verified through sequencing and gel electrophoresis (Figures 17B and 17C). The recombinant plasmid (Rha-MazTox) was then transformed into E. coli BL21 cells, preparing the strain for functional testing.

![](https://static.igem.wiki/teams/5084/engineering/img23.png)

Figure 23 Agarose gel electrophoresis of mazE and mazF

**Test**

To validate the functionality of the suicide system, the engineered E. coli BL21 strain with the rhamnose-inducible suicide system (BL21/PBAD-mazE-PRha) was inoculated into LB medium and cultured overnight at 37°C. The next day, the overnight culture was diluted 1:50 into fresh M9 medium containing 50 μg/mL ampicillin, 1% rhamnose, 0.2% arabinose, and 0.4% glucose. The OD600 was continuously monitored using a microplate reader to evaluate the impact of the suicide system on bacterial growth. The results showed that both the BL21 and BL21/PBAD-mazE-PRha strains (with 1% L-rhamnose) grew normally during the 8-hour period, reaching an OD600 value of approximately 0.7, indicating that these strains were unaffected by the suicide system. However, the BL21/PBAD-mazE-PRha strain(without 1% L-rhamnose) exhibited a significant decline in growth after 3 hours, indicating that the suicide system had been activated, leading to cell death (Figure 24).

![](https://static.igem.wiki/teams/5084/engineering/img24.png)

Figure 24. Effect of rhamnose-induced suicide system on bacterial growth

**Learn**

The results demonstrated that the rhamnose-inducible suicide system effectively controlled cell death. In the presence of L-rhamnose, the mazE antitoxin gene was expressed, allowing the strain to grow normally. However, in the absence of L-rhamnose, the mazF toxin gene was activated, causing a significant reduction in cell growth and eventually leading to cell death. This result confirms that the suicide system can be finely regulated by the presence of L-rhamnose, providing a potential biosafety strategy to prevent the engineered strain from uncontrolled proliferation or environmental release.

Reference：

[1] Wang C, Zeng H S, Liu K X, et al. Biosensor-based therapy powered by synthetic biology[J]. Smart Materials in Medicine, 2023, 4: 212-224.

[2] Wang X G, Zou Z P, Du Y, et al. Construction of an Engineered Escherichia coli with Efficient Chemotactic and Metabolizing Ability toward Tetrathionate[J]. ACS Synthetic Biology, 2023, 12(11): 3414-3423.

[3] Daeffler K N M, Galley J D, Sheth R U, et al. Engineering bacterial thiosulfate and tetrathionate sensors for detecting gut inflammation[J]. Molecular systems biology, 2017, 13(4): 923.

[4] Zammit C M, Quaranta D, Gibson S, et al. A whole-cell biosensor for the detection of gold[J]. PloS one, 2013, 8(8): e69292.

[5] Woo S G, Moon S J, Kim S K, et al. A designed whole-cell biosensor for live diagnosis of gut inflammation through nitrate sensing[J]. Biosensors and Bioelectronics, 2020, 168: 112523.

[6] Pardee A B, Jacob F, Monod J. The genetic control and cytoplasmic expression of “inducibility” in the synthesis of β-galactosidase by E. coli[J]. Journal of Molecular Biology, 1959, 1(2): 165-178.

[7] Matthews B W. The structure of E. coli β-galactosidase[J]. Comptes rendus. Biologies, 2005, 328(6): 549-556.

[8] Wiles T J, Mulvey M A. The RTX pore-forming toxin α-hemolysin of uropathogenic Escherichia coli: progress and perspectives[J]. Future microbiology, 2013, 8(1): 73-84.

[9] Li C, Li Y, Zhuang M, et al. Long noncoding RNA H19 act as a competing endogenous RNA of Let‐7g to facilitate IEC‐6 cell migration and proliferation via regulating EGF[J]. Journal of cellular physiology, 2021, 236(4): 2881-2892.

[10] Hu W, Zheng S, Guo H, et al. PLAGL2‐EGFR‐HIF‐1/2α signaling loop promotes HCC progression and erlotinib insensitivity[J]. Hepatology, 2021, 73(2): 674-691.

[11] Zhang L, Jia R, Palange N J, et al. Large genomic fragment deletions and insertions in mouse using CRISPR/Cas9[J]. PloS one, 2015, 10(3): e0120396.

[11] Engelberg-Kulka H, Hazan R, Amitai S. mazEF: a chromosomal toxin-antitoxin module that triggers programmed cell death in bacteria[J]. Journal of cell science, 2005, 118(19): 4327-4332.

[12] Guzman L M, Belin D, Carson M J, et al. Tight regulation, modulation, and high-level expression by vectors containing the arabinose PBAD promoter[J]. Journal of bacteriology, 1995, 177(14): 4121-4130.

[13] Giacalone M J, Gentile A M, Lovitt B T, et al. Toxic protein expression in Escherichia coli using a rhamnose-based tightly regulated and tunable promoter system[J]. Biotechniques, 2006, 40(3): 355-364.

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{% block title %}Experiments{% endblock %}
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CONTENT

[Building a Thiosulfate Biosensor](#a1)
[Biosensor Measurement](#a2)
[Biosensor Specificity Analysis](#a3)
[Construction of the β-galactosidase Reporter System](#a4)
[Determination of β-Galactosidase Activity in Engineered Strains Using the ONPG Method](#a5)
[Testing the X-gal Degradation Ability of Engineered Strains](#a6)
[Construction of hEGF Secreting Engineering Strain](#a7)
[In Vitro Testing of hEGF Secreting Engineered Strains](#a8)
[Effect of EGF-Secreting Engineered Strains on 293T Cell Activity](#a9)
[Construction of Rhamnose-Inducible Promoter](#a10)
[Rhamnose-Inducible Promoter Testing](#a11)
[Suicide System Construction](#a12)
[Suicide System Testing](#a13)
[Statistical Analysis](#a14)
[Related kit instructions](#a15)

Building a Thiosulfate Biosensor

E. coli  DH5α was purchased from Takara (Japan). First, the thiosulfate operon sequence was synthesized, coupled with mRFP, and cloned into the pSB1A3 plasmid (Genewiz, USA) to obtain pSB-PphsA-mRFP. After sequence verification (Qingke, China), the plasmid was extracted using a plasmid extraction kit (Tiangen, China). The recombinant plasmid was then transformed into E. coli DH5α. The engineered strain was cultured in LB medium containing ampicillin (Amp) at a concentration of 100 μg/mL at 37℃.

Biosensor Measurement

The engineered bacteria were inoculated into fresh LB medium containing different concentrations of sodium thiosulfate pentahydrate (Sorlabio, S5280) and cultured for 8 hours. A microplate reader (Multiskan GO, Thermo Fisher Scientific, USA) was used to measure the OD600 value (absorbance at 600 nm), and the OD600 was then adjusted to around 1 using LB medium. The microplate reader was subsequently used to measure fluorescence values (excitation wavelength 584 nm, emission wavelength 607 nm) and OD600 values. The normalized fluorescence ratio (Fluorescence/OD600) was then calculated.

Biosensor Specificity Analysis

The cultures were inoculated into LB medium containing 1 mM of sodium sulfate (MACKLIN, 7757-82-6), sodium sulfite anhydrous (MACKLIN, 7757-83-7), sodium tetrathionate dihydrate (MACKLIN, 13721-29-4), and thiosulfate, then incubated for 8 hours. Afterward, the OD600 was measured using a microplate reader and adjusted to approximately 1. Fluorescence values (excitation wavelength 584 nm, emission wavelength 607 nm) and OD600 were then recorded. The normalized fluorescence ratio (Fluorescence/OD600) was calculated for further analysis.

Construction of the β-galactosidase Reporter System

The thiosulfate operon sequence was synthesized, linked to LacZα, and cloned into the pSB1A3 plasmid (Genewiz, USA) to construct pSB-PphsA-LacZα. After verifying the sequence (Qingke, China), the recombinant plasmid was transformed into E. coli DH5α. The engineered strain was then cultured at 37℃ in LB medium containing 100 μg/mL of ampicillin (Amp).

Determination of β-Galactosidase Activity in Engineered Strains Using the ONPG Method

Overnight cultures were diluted 1:100 into fresh LB medium with varying concentrations of thiosulfate and incubated at 37℃ until reaching the logarithmic growth phase (OD600 = 0.6). A 1 mL sample of the bacterial culture was collected into a centrifuge tube, and 1 mL of lysis buffer was added. The cells were disrupted by ultrasonic treatment on ice (200 W power, 3 s ultrasonication, 10 s intervals, repeated 30 times). The lysate was centrifuged at 15,000 g for 20 minutes at 4℃, and the supernatant was collected and kept on ice for further analysis. β-galactosidase activity was measured using a β-galactosidase reporter gene detection kit (AKSU042M, boxbio). After a 30-minute reaction, the OD400 of the samples was recorded, and a standard curve was generated using the standard solution. The enzyme activity unit was defined as OD600 = 1 bacteria producing 1 nM p-Nitrophenyl-β-D-galactopyranoside (ONPG) per hour.

Testing the X-gal Degradation Ability of Engineered Strains

To test the ability of engineered strains to degrade X-gal via β-galactosidase activity, overnight cultures were diluted 1:100 into fresh LB medium containing different concentrations of thiosulfate and incubated at 37°C until the bacteria reached the logarithmic growth phase (OD600 = 0.6). X-gal was dissolved in dimethyl sulfoxide (DMSO). A 1 mL sample of the bacterial culture was collected into a centrifuge tube, and an appropriate amount of X-gal was added. The culture was incubated at 37°C, and color changes were observed to determine β-galactosidase activity, which indicates the degradation of X-gal.

Construction of hEGF Secreting Engineering Strain

E. coli Nissle 1917 (EcN) was purchased from Biobw (China). A recombinant plasmid, pSB-PEA (Genewiz, USA), was then synthesized. This plasmid includes the thiosulfate-responsive ThsS/R system (with promoters Pj23104/Pj23100), Hly-EGF (under the PphsA promoter), and the α-hemolysin secretion system (hlyB and hlyD) (driven by promoter Pj23104). In parallel, a control plasmid, pSB-PE, lacking the α-hemolysin secretion system, was also synthesized. The recombinant plasmids were subsequently transformed into E. coli DH5α and EcN, respectively. The engineered strains were cultured at 37℃ in LB medium containing 100 μg/mL of ampicillin (Amp).

In Vitro Testing of hEGF Secreting Engineered Strains

EcN expressing hEGF was inoculated into 50 mL of LB medium containing different concentrations of sodium thiosulfate (0 mM, 1 mM) and cultured overnight. The following day, 5 mL of the bacterial culture was collected, adjusted to OD600 = 1, and centrifuged at 10,000 x g for 1 minute. The supernatant was transferred to a new centrifuge tube to serve as the extracellular component sample. The bacterial pellet was resuspended in 1 mL of PBS and lysed by ultrasonic disruption (75 W, 1 s ultrasonic pulse, 3 s intervals, for a total of 20 minutes). The lysed cell suspension was transferred to a new centrifuge tube as the intracellular component sample. Finally, the hEGF content was measured using an ELISA kit (mlbio, China).

Effect of EGF-Secreting Engineered Strains on 293T Cell Activity

EcN expressing hEGF was inoculated into 50 mL of LB medium containing 1 mM sodium thiosulfate and cultured overnight. The following day, 5 mL of the bacterial culture was collected and adjusted to OD600 = 1. The culture supernatant and bacterial content samples were obtained through ultrasonic disruption and centrifugation. EcN containing only an empty vector served as a control. Human embryonic kidney 293T cells were seeded into 24-well plates at a density of 5×10^5 cells per well in DMEM medium containing 10% fetal bovine serum (FBS) and 1% penicillin-streptomycin. The cells were cultured at 37℃ in a humidified atmosphere with 5% CO2 until they reached 70% confluence. Then, 100 μL of the bacterial content and filtered supernatant from the engineered bacteria were added to the DMEM medium. After 8 hours of incubation, cell viability was assessed using the CCK8 assay. Specifically, 100 µL of CCK8 solution was added to each well and incubated at 37℃ for 3 hours. Absorbance at 450 nm was then measured using a microplate reader.

Construction of Rhamnose-Inducible Promoter

The sequence of the rhamnose-inducible promoter PRha and the ribosome binding site (RBS) B0034 was obtained through gene synthesis and cloned into the pSB1A3 vector at the XbaI and SpeI restriction sites, upstream of the fluorescent protein gene mRFP. The recombinant plasmid was then transformed into E. coli BL21 using the calcium chloride heat-shock method.

Rhamnose-Inducible Promoter Testing

A 1:100 dilution of the rhamnose biosensor strain was inoculated into LB medium and cultured overnight at 37℃. The next day, the overnight culture was diluted 1:50 into fresh M9 medium containing 50 μg/mL ampicillin and supplemented with 0.4% glucose. Simultaneously, a rhamnose solution at concentrations ranging from 0.1% to 1% was added to the medium. The culture was induced at 37℃ for 5 hours, and 1 mL of the culture was sampled. OD600 and fluorescence values (excitation wavelength 584 nm, emission wavelength 607 nm) were measured using a microplate reader. The normalized fluorescence ratio (Fluorescence/OD600) was calculated.

Suicide System Construction

The mazF and mazE genes were synthesized and cloned into the pSB1A3 recombinant vector containing the rhamnose promoter. The antitoxin protein gene mazE was placed downstream of the pRha-B0034 promoter and regulated by rhamnose, while the toxin protein gene mazF was placed downstream of the pBAD promoter and regulated by arabinose. After sequencing verification of the recombinant plasmid, it was transformed into E. coli BL21.

Suicide System Testing

A 1:100 dilution of the engineered BL21 strain containing the rhamnose-responsive suicide system was inoculated into LB medium and cultured overnight at 37℃. The next day, the overnight culture was diluted 1:50 into fresh M9 medium containing 50 μg/mL ampicillin, 1% rhamnose, and 0.2% arabinose, supplemented with 0.4% glucose. The OD600 values were monitored over time using a microplate reader.

Statistical Analysis

Data were analyzed and visualized using GraphPad Prism software. Results are presented as mean ± standard deviation (SD). One-way ANOVA followed by Tukey’s post hoc test was performed to analyze differences between groups. A p-value of less than 0.05 was considered statistically significant.

Related kit instructions

![]({{ url_for('static', filename = 'pdf.svg') }})

### Boxbio-aksu042m-β-galactosidase (β-GAL) activity detection kit.pdf

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{% block title %}Results{% endblock %}
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CONTENT

[Abstract](#a1)
[Tetrathionate Biosensor Construction and Evaluation](#a2)
[Thiosulfate Biosensor Construction and Evaluation](#a3)
[Thiosulfate Biosensor Optimization and Evaluation](#a4)
[Dose-Dependence Analysis of the Thiosulfate Biosensor-B](#a5)
[Specificity Analysis of Thiosulfate Biosensor](#a6)
[β-Galactosidase Activity in Engineered Strains Using the ONPG Method](#a7)
[Analysis of hEGF Secretion and Intracellular/Extracellular Distribution](#a8)
[Effect of hEGF-Secreting Engineered Strains on 293T Cell Activity](#a9)
[Rhamnose-Inducible Reporter Strain Construction and Evaluation](#a10)
[Construction and Testing of the Suicide System](#a11)
[Reference：](#a12)

Abstract

Tetrathionate, a key biomarker for inflammatory bowel disease (IBD). However, due to tetrathionate's rapid degradation in the gut, we shifted focus to thiosulfate, creating a thiosulfate-specific sensor using the ThsS/R system. This biosensor was further optimized to enhance its sensitivity and accuracy. We tested its dose-dependence and specificity, demonstrating strong responses at higher thiosulfate concentrations and minimal interference from other sulfate-based compounds. Next, we incorporated lacZ downstream of the sensing system to test β-galactosidase activity using the ONPG method. This enabled us to visually detect the sensor’s activity, offering a clearer readout for thiosulfate detection.

For the therapeutic system, we engineered bacteria to secrete human epidermal growth factor (hEGF) . We measured the differences in intracellular and extracellular hEGF levels. Additionally, we assessed the impact of these engineered strains on 293T cell viability.

For the suicide system, we developed a mazE/mazF toxin-antitoxin system controlled by rhamnose. Growth tests showed normal growth in the presence of rhamnose, while its absence triggered cell death, confirming the system’s functionality. This ensures controlled regulation of engineered bacteria for future applications

![](https://static.igem.wiki/teams/5084/{{self.title()|lower}}/img1.png)

The construction of the three systems—the sensing system, the therapeutic system, and the suicide system—follows engineering design principles.

Tetrathionate Biosensor Construction and Evaluation

Tetrathionate is an important biomarker for inflammatory bowel disease (IBD). To develop a biosensor for detecting tetrathionate, we designed and synthesized the TtrS (BBa\_K5084000) and TtrR(BBa\_K5084001) operon system, incorporating the red fluorescent protein mRFP1 as a reporter gene. This construct was cloned into the pSB1A3 plasmid. After plasmid extraction, it was successfully transformed into E. coli  DH5α. The engineered strain, referred to as the tetrathionate biosensor(BBa\_K5084003), was cultured in LB medium with ampicillin (Amp, 100 μg/mL) at 37℃ (Figure 1).

![](https://static.igem.wiki/teams/5084/{{self.title()|lower}}/img2.png)

**Figure 1.** Construction of Tetrathiosulfate biosensor. (A) The plasmid map of tetrathiosulfate biosensor. (B) Agarose gel electrophoresis of TtrS. (C) Agarose gel electrophoresis of TtrR. (D) The gene circuit of Tetrathiosulfate biosensor.

To assess the Tetrathiosulfate biosensor’s ability to detect different tetrathionate concentrations, we performed functional tests by inoculating the E. coli  strain into LB media containing varying concentrations of tetrathionate (0 µM, 10 µM, 50 µM, 100 µM, 500 µM, and 1000 µM). After 8 hours of incubation at 37℃, we measured the fluorescence intensity (excitation at 584 nm and emission at 607 nm) and OD600 using a microplate reader. The normalized fluorescence ratio (Fluorescence/OD600) was calculated to evaluate the Tetrathiosulfate biosensor’s response.

![](https://static.igem.wiki/teams/5084/{{self.title()|lower}}/img3.png)

**Figure 2.** Tetrathionate biosensor response to varying tetrathionate concentrations.

The results demonstrated a clear increase in the normalized fluorescence ratio as tetrathionate concentrations rose. At lower concentrations (0 µM to 50 µM), the fluorescence ratio increased rapidly, indicating the Tetrathiosulfate biosensor’s high sensitivity in this range. Between 10 µM and 50 µM, the fluorescence ratio more than doubled, reflecting a significant response (p < 0.01). However, as the concentration increased beyond 100 µM, the fluorescence signal continued to rise but began to plateau between 500 µM and 1000 µM, suggesting that the Tetrathiosulfate biosensor’s response was nearing saturation at higher concentrations (Figure 2).

Despite strong in vitro results, literature indicates a key limitation: tetrathionate is rapidly metabolized by gut microbiota, reducing its stability as an IBD biomarker in vivo. This compromises the biosensor’s ability for long-term inflammation monitoring. To overcome this, we will shift to thiosulfate, a more stable biomarker, and redesign the biosensor for thiosulfate detection, aiming for improved performance in IBD monitoring applications.

Thiosulfate Biosensor Construction and Evaluation

Thiosulfate is an important biomarker for IBD. To develop a biosensor capable of sensitively detecting changes in thiosulfate concentration, we constructed a system that incorporates two key components, ThsS(BBa\_K5084010) and ThsR(BBa\_K5084011), designed to sense thiosulfate. The system uses the PphsA(BBa\_K5084002) promoter to drive the expression of the red fluorescent protein mRFP as a reporter for thiosulfate detection. The construct was cloned into the pSB1A3 plasmid, forming the recombinant plasmid pSB-PphsA-mRFP. This plasmid was then transformed into E. coli  DH5α (purchased from Takara), and the engineered strain was cultured in LB medium containing ampicillin (Amp, 100 μg/mL) at 37℃. The successfully engineered strain was named Thiosulfate biosensor-A(BBa\_K5084012) (Figure 3).

![](https://static.igem.wiki/teams/5084/{{self.title()|lower}}/img4.png)

**Figure 3.** Construction of Thiosulfate biosensor-A. (A) The plasmid map of Thiosulfate biosensor-A. (B) Agarose gel electrophoresis of ThsS and ThsR. (C) Agarose gel electrophoresis of PphsA. (D) The gene circuit of Thiosulfate biosensor-A.

To validate the function of Thiosulfate biosensor-A, we inoculated the strain into LB medium containing varying concentrations of sodium thiosulfate and incubated it at 37℃ for 8 hours. Fluorescence signals were measured at concentrations of 0 mM, 0.2 mM, and 1 mM sodium thiosulfate. After incubation, fluorescence intensity (excitation wavelength at 584 nm, emission wavelength at 607 nm) and OD600 values were measured using a microplate reader, and the normalized fluorescence ratio (Fluorescence/OD600) was calculated.

![](https://static.igem.wiki/teams/5084/{{self.title()|lower}}/img5.png)

**Figure 4.** Tetrathionate biosensor response to varying tetrathionate concentrations.

In the absence of sodium thiosulfate, Thiosulfate biosensor-A displayed very low fluorescence, indicating that the sensor was not activated without thiosulfate. This also suggests that the background noise is minimal, which reduces the likelihood of false positives in future applications. At a concentration of 0.2 mM, the fluorescence signal increased significantly, indicating that the sensor was activated and responded clearly to the presence of thiosulfate. At 1 mM sodium thiosulfate, the fluorescence signal further increased, demonstrating a strong response to higher concentrations of thiosulfate (Figure 4).

The data show that Thiosulfate biosensor-A exhibits a concentration-dependent response to sodium thiosulfate, with significant fluorescence increases at 0.2 mM and 1 mM, particularly at the higher concentration. This indicates high sensitivity to thiosulfate. Future efforts will focus on optimizing the sensor for lower concentrations and testing its performance in more complex biological environments to evaluate practical applications.

Thiosulfate Biosensor Optimization and Evaluation

To further enhance the sensitivity and detection accuracy of the thiosulfate biosensor, we optimized the original Thiosulfate biosensor-A and developed a new version, Thiosulfate biosensor-B(BBa\_K5084013). The primary strategy involved modifying the promoter of ThsR and adjusting the ribosome binding site (RBS) sequences of both ThsS and ThsR. These modifications were aimed at balancing the expression of the sensing system, thereby improving its response speed and sensitivity to thiosulfate (Figure 5).

![](https://static.igem.wiki/teams/5084/{{self.title()|lower}}/img6.png)

**Figure 5.** The plasmid map of Thiosulfate biosensor-B.

During the optimization process, we replaced the promoter of ThsR and adjusted the RBS sequences of ThsS and ThsR to enhance their translation efficiency and sensing capability. By fine-tuning the regulatory mechanisms of ThsR and ThsS, Thiosulfate biosensor-B was expected to detect changes in thiosulfate concentration more efficiently and sensitively than the original version (Figure 6).

![](https://static.igem.wiki/teams/5084/{{self.title()|lower}}/img7.png)

**Figure 6.** Comparison of the key differences between Thiosulfate biosensor-A and Thiosulfate biosensor-B.

To evaluate the performance of Thiosulfate biosensor-B, we conducted multiple rounds of screening and functional tests. The testing method was identical to that used for Thiosulfate biosensor-A: the engineered bacteria were inoculated into LB medium containing varying concentrations of sodium thiosulfate (0 mM and 1 mM) and incubated at 37℃ for 8 hours. After incubation, fluorescence intensity (excitation at 584 nm, emission at 607 nm) and OD600 were measured using a microplate reader, and the normalized fluorescence ratio (Fluorescence/OD600) was calculated.

![](https://static.igem.wiki/teams/5084/{{self.title()|lower}}/img8.png)

**Figure 7.** Comparison of normalized fluorescence ratios before and after the optimization of the thiosulfate biosensor.

The results demonstrated that both biosensors, A and B, exhibited low and comparable fluorescence signals in the absence of thiosulfate, indicating minimal background noise without the target molecule. However, Thiosulfate biosensor-B showed a significantly higher response to 1 mM sodium thiosulfate compared to Thiosulfate biosensor-A, with markedly increased fluorescence intensity. This indicates that the adjustments to the promoter and RBS sequences successfully enhanced the sensitivity of Thiosulfate biosensor-B (Figure 7).

In conclusion, by optimizing the promoter and RBS, we developed Thiosulfate biosensor-B with improved sensitivity. Further testing will assess its performance in more complex environments and conditions.

Dose-Dependence Analysis of the Thiosulfate Biosensor-B

To evaluate the dose-dependence of the constructed Thiosulfate biosensor-B, we measured the fluorescence response at different concentrations of sodium thiosulfate. We used the Thiosulfate biosensor-B and inoculated the engineered strain into LB medium containing various concentrations of sodium thiosulfate (0, 0.125, 0.25, 0.5, and 1 mM). After 8 hours of incubation at 37℃, the fluorescence intensity of the cultures was measured using a microplate reader. The fluorescence values were normalized to the OD600 (Fluorescence/OD600) to account for cell growth differences.

![](https://static.igem.wiki/teams/5084/{{self.title()|lower}}/img9.png)

**Figure 8.** Dose-Dependence Analysis of the Thiosulfate Biosensor-B.

As shown in the Figure 8, the normalized fluorescence ratio increased as the concentration of thiosulfate increased. At 0 mM thiosulfate, the fluorescence signal is very low, with an average of 15.79, indicating that the sensor is not activated. At a concentration of 0.125 mM, the fluorescence ratio increases sharply to 3449.43, showing a clear response to low concentrations of thiosulfate. At 0.25 mM, the fluorescence signal continues to increase, reaching an average of 4900.49, demonstrating a stronger dose-dependence. At 0.5 mM, the fluorescence signal nears saturation, with an average of 6079.88, indicating that the sensor’s response is close to its maximum. At 1 mM thiosulfate, the fluorescence signal is 6236.64, and the curve begins to plateau, suggesting that the sensor’s response has stabilized at high concentrations.

The data show a strong dose-dependent response in biosensor B, with fluorescence increasing as thiosulfate concentration rises. The sensor reaches optimal performance at 0.5 mM, with signal growth plateauing around 1 mM.

Specificity Analysis of Thiosulfate Biosensor

To assess the specificity of the thiosulfate biosensor and determine whether it could be falsely triggered by structurally similar compounds, we conducted a specificity test using various sulfate-based substrates. The goal was to ensure the biosensor would not produce false-positive results in the presence of these compounds.

We inoculated the engineered E. coli  strain into LB medium containing 1 mM of different sulfate compounds, including sodium sulfate (MACKLIN, 7757-82-6), sodium sulfite (MACKLIN, 7757-83-7), sodium tetrathionate (MACKLIN, 13721-29-4), and sodium thiosulfate. After 8 hours of incubation at 37℃, OD600 values were measured and adjusted to approximately 1. The fluorescence intensity (excitation at 584 nm, emission at 607 nm) and OD600 values were then measured using a microplate reader. The normalized fluorescence ratio (Fluorescence/OD600) was calculated for each compound.

![](https://static.igem.wiki/teams/5084/{{self.title()|lower}}/img10.png)

**Figure 9.** Normalized fluorescence response of the thiosulfate biosensor to various sulfate-based compounds.

The specificity analysis shows distinct differences in the biosensor’s response to various sulfate-based compounds: The biosensor exhibited very low responses to sulfate and sulfite, with average normalized fluorescence ratios of 22.23 ± 3.61 and 25.08 ± 7.28, respectively. These results confirm that the biosensor is not activated by these compounds, demonstrating high specificity and minimal false-positive potential. The biosensor showed a moderate response to tetrathionate, with an average fluorescence ratio of 1027.88 ± 96.92. This response indicates some cross-reactivity, but given that tetrathionate is also an important biomarker for inflammatory conditions, this level of response is acceptable. The biosensor exhibited a strong response to thiosulfate, with an average normalized fluorescence ratio of 5853.38 ± 360.09, significantly higher than the responses to other compounds. This confirms that the biosensor is highly sensitive and specific to thiosulfate, with minimal interference from structurally similar compounds (Figure 9).

Specificity tests show that the thiosulfate biosensor accurately detects thiosulfate with minimal or no response to sulfate and sulfite. A slight response to tetrathionate is acceptable due to its relevance as an inflammation marker. Overall, the biosensor demonstrates high specificity and reliability for thiosulfate detection.

β-Galactosidase Activity in Engineered Strains Using the ONPG Method

In order to colourise human stool, we added LacZ downstream of the sensory system (BBa\_K5084024). We first synthesized the thiosulfate operon, including the ThsS and ThsR genes, and coupled them with the LacZ gene (encoding β-galactosidase) using the PphsA promoter. These gene fragments were cloned into the pSB1A3 plasmid. The plasmid construction was verified through sequencing (Qingke, China). After successful validation, the plasmid was transformed into E. coli  DH5α (Figure 10).

![](https://static.igem.wiki/teams/5084/{{self.title()|lower}}/img11.png)

**Figure 10.** Construction of PphsA-LacZα. (A) The plasmid map of PphsA-LacZα.. (B) Agarose gel electrophoresis of LacZα. (C)The gene circuit of PphsA-LacZα.

Appropriate amount of overnight cultured bacterial solution was inoculated into fresh LB medium at 1:100 ratio, and different concentrations of thiosulfate were added. β-galactosidase activity was measured using a β-galactosidase reporter gene assay kit (AKSU042M, boxbio).The yellow product (ortho-nitrophenol, ONP) from the hydrolysis of ONPG was used to measure the fluorescence value (OD400), allowing the calculation of enzyme activity. A standard curve (3 repetitions) was established using a standard material, and the unit of enzyme activity was defined as OD600=1 1 nM ONPG produced by bacteria per hour.

![](https://static.igem.wiki/teams/5084/{{self.title()|lower}}/img12.png)

**Figure 11.** The β-galactosidase activity of PphsA-LacZα. (A) ONPG standard curve. (B) The OD400 values at different concentrations of thiosulfate. (C)The enzyme activity under different concentration of thiosulfate. (D) Generation of o-Nitrophenol in ONPG Assay for β-Galactosidase. (E) X-gal reaction: blue product intensity as an indicator of enzyme activity.

The Figure 11A shows a positive correlation between OD400 and the amount of ONPG substrate hydrolyzed. The linear regression equation is Y=0.004543X-0.06551, which means we can caculate the concentration of ONPG by mesure the OD400. The Figure 11B shows the OD400 values at different concentrations of thiosulfate. By bringing it into the linear regression equation, we can get the ONPG concentration corresponding to each sample. According to the formula of enzyme activity unit, the enzyme activity under different concentration of thiosulfate was calculated(Figure 11C).With the increase of thiosulfate concentration, the enzyme activity also increased.Through the addition of X-gal, we successfully observed the blue color reaction produced by β-galactosidase.(Figure 11E).

We successfully expressed β-galactosidase in engineered E. coli  DH5α and confirmed its ability to degrade X-gal. Future work will focus on expressing it in E. coli  Nissle 1917 to optimize its use as an oral product.

Analysis of hEGF Secretion and Intracellular/Extracellular Distribution

To verify the expression and secretion of hEGF in the constructed smart probiotic strains under simulated colitis conditions, we developed two recombinant plasmids: pSB-PE and pSB-PEA.

Plasmid pSB-PE(BBa\_K5084018): Contains the ThsS/R sensing system (Pj23104/Pj23100 promoters) and the Hly-EGF(BBa\_K5084017) expression module (PphsA promoter encoding hEGF), but lacks the α-hemolysin secretion system. This was used as a control to measure hEGF secretion efficiency.

Plasmid pSB-PEA(BBa\_K5084019): In addition to the ThsS/R system, it includes the Hly-EGF expression module and a complete α-hemolysin secretion system (hlyB BBa\_K5084015 and hlyD BBa\_K5084016 genes, Pj23104 promoter) to evaluate the role of the α-hemolysin secretion system in promoting hEGF secretion.

The recombinant plasmids were verified by sequencing (Qingke, China) and then transformed into E. coli  DH5α and E. coli  Nissle 1917 (EcN) to generate the engineered strains expressing and secreting hEGF (Figure 12).

![](https://static.igem.wiki/teams/5084/{{self.title()|lower}}/img13.png)

**Figure 12.**Construction of pSB-PE and pSB-PEA. (A) The gene circuit of pSB-PE. (B)The plasmid map of pSB-PE. (C) The gene circuit of pSB-PEA. (D) The gene circuit of pSB-PEA. (E)Agarose gel electrophoresis of Hly-EGF. (F)Agarose gel electrophoresis of hlyB. (G)Agarose gel electrophoresis of hlyD.

To assess the secretion efficiency of hEGF in different cellular environments, E. coli  Nissle 1917 (EcN) expressing hEGF was inoculated into 50 mL LB medium containing different concentrations of sodium thiosulfate (0 mM and 1 mM) and cultured overnight. The following day, 5 mL of the bacterial culture was collected and adjusted to OD600 = 1, followed by centrifugation at 10,000 x g for 1 minute. The supernatant was taken as the extracellular sample, while the bacterial pellet was resuspended in 5 mL PBS and sonicated to lyse the cells. The resulting cell lysate was used as the intracellular sample. The hEGF content was measured using an ELISA kit (mlbio, China).

![](https://static.igem.wiki/teams/5084/{{self.title()|lower}}/img14.png)

**Figure 13.** EGF secretion test of pSB-PE and pSB-PEA. (A) Periplasmic sample. (B) Intracellular sample.

At 1 mM thiosulfate, the extracellular hEGF content in the EcN/pSB-PE strain was 2.37 ± 0.44 μg/L, while the EcN/pSB-PEA strain showed a significant increase, with hEGF levels reaching 19.92 ± 1.67 μg/L. These results demonstrate that the α-hemolysin secretion system greatly enhanced the extracellular secretion of hEGF, improving secretion efficiency (Figure 13A).

At 1 mM thiosulfate, the intracellular hEGF content in the EcN/pSB-PE strain was 17.15 ± 1.18 μg/L, while in the EcN/pSB-PEA strain it was 8.16 ± 1.19 μg/L. This indicates that the introduction of the α-hemolysin secretion system in the EcN/pSB-PEA strain significantly reduced intracellular hEGF levels compared to the EcN/pSB-PE strain, suggesting that more hEGF was secreted to the extracellular environment (Figure 13B).

The α-hemolysin secretion system in the EcN/pSB-PEA strain significantly enhances extracellular hEGF secretion while reducing intracellular levels, indicating its key role in improving secretion efficiency, especially in a simulated colitis environment.

Effect of hEGF-Secreting Engineered Strains on 293T Cell Activity

The E. coli  Nissle 1917 (EcN) strain expressing hEGF(pSB-PE and pSB-PEA) was inoculated into 50 mL LB medium containing 1 mM sodium thiosulfate and cultured overnight at 37℃. The next day, 5 mL of the bacterial culture was collected and adjusted to OD600 = 1. The supernatant was collected as the extracellular sample by centrifugation at 10,000 x g for 1 minute. The bacterial pellet was subjected to ultrasonic disruption (75 W, 1s sonication, 3s intervals, for 20 min) to obtain bacterial content samples. The same procedure was applied to the EcN strain containing the empty vector as a control.

Human embryonic kidney 293T cells were seeded in 24-well plates at a density of 5×10^5 cells per well. Cells were cultured in DMEM containing 10% fetal bovine serum (FBS) and 1% penicillin-streptomycin at 37℃ in 5% CO2 until 70% confluency was reached. Once cells reached 70% confluency, 100 μL of either the bacterial content or filtered supernatant from the engineered strains was added to the DMEM medium in each well. After 8 hours of incubation, cell viability was assessed using the CCK8 kit. 100 μL of CCK8 solution was added to each well and incubated for 3 hours at 37℃. Absorbance at 450 nm (A450) was measured using a microplate reader to assess cell viability.

![](https://static.igem.wiki/teams/5084/{{self.title()|lower}}/img15.png)

The impact of the supernatant and bacterial content from different strains on 293T cell viability was measured, with the absorbance (A450) values.The supernatant group showed that the EcN/pSB-PEA strain, containing the α-hemolysin secretion system, exhibited the highest A450 value (2.87 ± 0.41), significantly higher than the EcN/pSB-PE strain (2.24 ± 0.24), indicating that the secretion system effectively enhanced hEGF secretion, thereby improving 293T cell viability. In the bacterial content group, the EcN/pSB-PE strain exhibited a higher A450 value (4.75 ± 0.49) compared to the EcN/pSB-PEA strain (3.16 ± 0.40), suggesting that without the secretion system, hEGF predominantly accumulated intracellularly. In contrast, in the EcN/pSB-PEA strain, hEGF was efficiently secreted extracellularly.

The results show that the EcN/pSB-PEA strain, which includes the α-hemolysin secretion system, significantly increased extracellular hEGF secretion, enhancing 293T cell viability. In contrast, in the EcN/pSB-PE strain, hEGF largely remained intracellular, resulting in lower extracellular activity.

Rhamnose-Inducible Reporter Strain Construction and Evaluation

The rhamnose-inducible promoter PRha(BBa\_K914003), along with the ribosome binding site (RBS) B0034, was synthesized and cloned into the pSB1A3 plasmid using the XbaI and SpeI restriction sites. This construct was placed upstream of the coding sequence for the red fluorescent protein (mRFP). The recombinant plasmid was then transformed into E. coli  BL21 cells using the calcium chloride heat-shock method.

![](https://static.igem.wiki/teams/5084/{{self.title()|lower}}/img16.png)

**Figure 15.** The gene circuit of rhamnose-inducible reporter strain.

A 1:100 dilution of the rhamnose-inducible reporter strain was inoculated into LB medium and cultured overnight at 37°C. The following day, the overnight culture was further diluted 1:50 into fresh M9 medium containing 50 μg/mL ampicillin and supplemented with 0.4% glucose. Simultaneously, a rhamnose solution (final concentration ranging from 0.1% to 1%) was added to the medium to induce the reporter strain. The cultures were incubated at 37°C for 5 hours. After induction, 1 mL of the culture was sampled, and the OD600 value was measured using a microplate reader. Fluorescence was also measured at an excitation wavelength of 584 nm and an emission wavelength of 607 nm. The normalized fluorescence intensity (Fluorescence/OD600) was then calculated to assess reporter strain activity.

![](https://static.igem.wiki/teams/5084/{{self.title()|lower}}/img17.png)

**Figure 16.** Rhamnose-inducible reporter strain response to varying L-rhamnose concentrations.

In the absence of L-rhamnose, Rhamnose-inducible reporter strain displayed very low fluorescence, indicating that the reporter strain was not activated without L-rhamnose. At a concentration of 0.1%, the fluorescence signal increased significantly, indicating that the reporter strain was activated and responded clearly to the presence of L-rhamnose. At 0.5% and 1% L-rhamnose, the fluorescence signal further increased, demonstrating a strong response to higher concentrations of L-rhamnose (Figure 16).

The rhamnose-inducible system shows a clear, dose-dependent response to L-rhamnose, making it a reliable tool for controlled gene expression.

Construction and Testing of the Suicide System

To construct a controllable suicide system, the antitoxin gene mazE and toxin gene mazF were synthesized and cloned into the pSB1A3 plasmid. The antitoxin gene mazE was placed downstream of the rhamnose-inducible promoter PRha and RBS B0034, regulated by rhamnose. The toxin gene mazF was positioned downstream of the arabinose-inducible promoter PBAD and regulated by arabinose. After sequencing verification, the recombinant plasmid Rha-MazTox (BBa\_K5084020) was transformed into E. coli  BL21 to validate the functionality of the suicide system.

![](https://static.igem.wiki/teams/5084/{{self.title()|lower}}/img18.png)

**Figure 17.** Construction of Rha-MazTox. (A) The gene circuit of rhamnose-inducible reporter strain. (B)Agarose gel electrophoresis of mazE. (C) Agarose gel electrophoresis of mazF.

To evaluate the effectiveness of the suicide system, the engineered E. coli  BL21 strain was inoculated at a 1:100 ratio into LB medium and cultured overnight at 37°C. The next day, the culture was diluted 1:50 into fresh M9 medium containing 50 μg/mL ampicillin, 1% rhamnose, 0.2% arabinose, and 0.4% glucose. The OD600 values were monitored over time using a microplate reader to assess the impact of the suicide system.

![](https://static.igem.wiki/teams/5084/{{self.title()|lower}}/img19.png)

**Figure 18.** Effect of rhamnose-induced suicide system on bacterial growth

The results show clear differences in the growth of the tested strains. Both the BL21 strain and the BL21/PBAD-mazE-PRha strain (with 1% L-rhamnose) displayed normal growth over the 8-hour period, with OD600 values reaching approximately 0.7 by the end of the experiment, indicating healthy bacterial growth. In contrast, the BL21/PBAD-mazE-PRha strain (without 1% L-rhamnose) exhibited a marked reduction in OD600 over time. By 3 hours, its growth had already begun to decline compared to the control strains (Figure 18). This suggests that the rhamnose-induced suicide system was successfully activated in the absence of L-rhamnose, leading to bacterial cell death.

The rhamnose-induced suicide system worked as expected. With 1% L-rhamnose, the strain grew normally, but without it, growth declined by 3 hours, confirming activation of the system and cell death.

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