iGEM 2025 — Team hubu-wuhan

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{% block title %}Lab Notebook{% endblock %}
{% block lead %}Experimental Progress and Laboratory Records{% endblock %}
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[Introduction](#introduction)
[February - March 2025](#feb-mar)

Literature Review and Training

[April 2025](#april)

Initial DNA Extraction and Cloning

[May 2025](#may)

V0-V1 Plasmid Construction

[June 2025](#june)

V2 Plasmid Construction

[July 2025](#july)

V3-V4 Plasmid Construction

[August 2025](#august)

Optimization and Testing

[September 2025](#september)

Promoter Engineering and Self-Assembly

## Experimental Progress and Laboratory Records

#### Introduction

This page documents the chronological progress of our arsenic biosensor development project, including laboratory procedures, experimental results, and methodology refinements throughout the research timeline.

#### February - March 2025: Literature Review and Laboratory Training

2025.2.21 - 2025.3.4

##### Literature Review and Analysis

Retrieve literature from Web of Science, categorize it based on impact factor and content, select representative biosensor models, and analyze their design principles and practical performance.

2025.3.1 - 2025.4.1

##### Laboratory Technique Training

The experimental group was divided into three study teams, each consisting of two individuals. They entered the laboratory to learn experimental procedures, with each session lasting one hour. The training focused on molecular biology techniques.

#### April 2025: Initial DNA Extraction and Gene Cloning

2025.4.15 - 2025.4.27

##### ArsR Gene Amplification and Cloning

Rapidly extracted genomic DNA from *Cupriavidus metallidurans* CML2 using microwave heating, designed primers, and amplified the gene encoding the ArsR protein from CML2 genomic DNA via polymerase chain reaction (PCR). Subsequently, the PCR product was cloned into the pET-46a expression vector using DNA recombination techniques and sent for sequencing.

2025.04.27 - 2025.05.05

##### Construction of Recombinant pET46a-ArsR-sfGFP-V0

Construction of recombinant pET46a-ArsR-sfGFP-V0: Genomic DNA from *Cupriavidus metallidurans* CML2 was extracted using the microwave method. PCR amplification of the ArsR protein gene was performed using forward primer and and reverse primer. The PCR product was then ligated into the pET-46a vector, which had been pre-cloned with sfGFP, using DNA recombination techniques.

#### May 2025: V0-V1 Plasmid Construction and Initial Testing

2025.05.05 - 2025.05.15

##### Construction of Recombinant Vector pET-46a-PlacV-ArsR-ParsOC2-sfGFP-V1

Identify the promoters for ArsR and sfGFP through literature review, then design forward and reverse primers accordingly. Clone these into the pET46a-ArsR-sfGFP-V0 recombinant vector via homologous recombination.

2025.05.15 - 2025.05.25

##### Detection Biosensor-V1 Performance Testing

E. coli was inoculated at 1:50 into 5 mL LB medium and cultured overnight. After induction with varying concentrations of NaAsO₂, the culture was incubated at 37°C for 6 hours. One milliliter of the culture was then centrifuged at 12,000 rpm for 1 minute, and the supernatant was discarded. The pellet was resuspended in 1 mL of PBS. A 200 μL aliquot was transferred to a black-bottomed 96-well plate.

**Measurement Protocol:**

* Measure OD600 (cell growth) and fluorescence at 485/525 nm (GFP expression) using a microplate reader
* Subtract PBS background (n=3) and GFP-negative control (n≥3) to obtain Fluo/OD600
* Calculate fluorescence fold change using the formula

**Results:** DH5α detection of co-transfected V1 plasmid: At 37°C, 0 and 300 ppb (0.13 μM) arsenic induction for 6h yielded fluorescence values of 5.10×10⁶ and 8.80×10⁶, respectively. The 300 ppb group showed a 1.7-fold increase but with elevated background, suggesting incomplete ArsR expression. Subsequent induction with varying arsenic concentrations showed the 20 μM group at 6 hours exhibited the highest fluorescence, yet this did not correlate positively with concentration. Results at 24 hours were consistent, indicating ArsR may not be expressed. Given the suspected correlation between sfGFP's high background and ArsR, the V1 construct was modified into V2 and V3.

#### June 2025: V2 Plasmid Construction and Evaluation

2025.05.25 - 2025.06.10

##### Construction and Evaluation of pET46a-ParsOC2-ArsR-sfGFP-V2

Using designed forward and reverse primers, construct the truncated construct pET46a-ParsOC2-sfGFP (deleting PlacV-ArsR) via reverse PCR using pET-46a-PlacV-ArsR-ParsOC2-sfGFP-V1 as template; Based on this truncated construct, primers were designed to insert the ArsR protein-encoding gene into the ParsOC2 promoter via homologous recombination cloning. After successfully transforming the V1 plasmid into E. coli DH5α, performance testing was conducted.

#### July 2025: V3-V4 Plasmid Construction and Optimization

2025.06.10 - 2025.07.12

##### Construction and Evaluation of pET46a-PlacV-ArsR-ParsOC2-sfGFP-V3

Based on the recombinant pET-46a-ParsOC2-sfGFP (deleting PlacV-ArsR), primers were designed to amplify the sequence encoding the ArsR protein, its promoter, and the ribosomal binding site designated as PlacV-RBS (arsR). Using homologous recombination cloning, this sequence was inserted upstream of the ParsOC2 promoter. Following successful transformation of the V1 plasmid into E. coli DH5α, performance testing was conducted.

2025.07.12 - 2025.07.31

##### Construction and Testing of pET-46a-PJ100-ArsR-ParsOC2-sfGFP-V4

Construct the recombinant vector pET-46a-PJ100-ArsR-ParsOC2-sfGFP-V4 and conduct preliminary performance testing of the biosensor-V4: First, the target promoter sequence PJ100 was obtained from the online website Promoters/Catalog - parts.igem.org. Using reverse PCR, the PlacV element in the recombinant vector pET46a-PlacV-ArsR-ParsOC2-sfGFP-V3 was replaced. The resulting V1 plasmid was successfully transformed into E. coli DH5α for performance testing.

2025.08.04 - 2025.08.09

##### Dose-Response Curve Construction

Construction of Dose-Response Curves for V3 and V4 Sensors: Attempts were made to construct dose-response curves for all available data, with subsequent discussions of the results. The outcomes were unsatisfactory.

#### August 2025: Optimization and Natural Promoter Strategy

2025.08.11 - 2025.08.20

##### Natural Promoter Strategy Development

Optimization Strategy: Isolate the natural promoter ParsCML2 from the rice endophytic bacterium *Cupriavidus metallidurans* CML2, and clarify its co-evolutionary characteristics with the homologous ArsR protein (enhanced adaptability). Retain the core architecture of "PJ100 driving ArsR," replacing only the ParsOC2 promoter in the original vector pET-46a-PJ100-ArsR-ParsOC2-sfGFP with ParsCML2. The target is to construct the recombinant plasmid pET-46a-PJ100-ArsR-ParsCML2-sfGFP-V4.

2025.08.20 - 2025.08.27

##### Optimization Strategy Implementation

Optimization Strategy: Isolate the natural promoter ParsCML2 from the rice endophytic bacterium *Cupriavidus metallidurans* CML2, and clarify its co-evolutionary characteristics with the homologous ArsR protein (enhanced adaptability). Retain the core architecture of "PJ100 driving ArsR," replacing only the ParsOC2 promoter in the original vector pET-46a-PJ100-ArsR-ParsOC2-sfGFP with ParsCML2. The target is to construct the recombinant plasmid pET-46a-PJ100-ArsR-ParsCML2-sfGFP-V4.

2025.08.27 - 2025.09.07

##### V4 Plasmid Performance Testing

**Testing Protocol:**

* Inoculate a single colony of E. coli containing the recombinant V4 plasmid into 5 mL LB broth containing 50 μg/mL benzylpenicillin
* Incubate overnight at 37°C with shaking at 200 rpm
* Transfer to fresh LB broth at a 1:50 ratio
* Add 0--300 μM analytical-grade NaAsO₂ during the logarithmic phase and continue incubation under Module 1 conditions
* After incubation, take 1 mL of culture, centrifuge at 12,000 rpm for 1 min, discard supernatant, and resuspend pellet in 1 mL PBS
* Transfer 200 μL to a black-bottomed 96-well plate
* Measure OD600 (cell growth) and fluorescence (485/525 nm, sfGFP expression) using a microplate reader
* Calculate Fluo/OD600 (after subtracting PBS background and GFP-negative control), comparing the background leakage (no arsenic fluorescence) and induced fluorescence intensity (50--300 μM arsenic) between ParsCML2 and ParsOC2

#### September 2025: Promoter Engineering and Self-Assembly System

2025.09.07 - 2025.09.10

##### ParsCML2 Promoter Mutagenesis Strategy

Mutagenesis Method (ParsCML2 Promoter Engineering): Employ error-prone PCR to introduce random mutations into the ParsCML2 promoter, including base substitutions, insertions, or deletions. Focus on the core functional regions of the ParsCML2 promoter (-35 region, -10 region). Establish a library size of 1000+ clones to ensure sufficient sequence diversity coverage.

2025.09.07 - 2025.09.17

##### ParsCML2 Promoter Library Construction

**Library Construction Protocol:**

* Verify the correct ParsCML2 gene fragment as a template
* Prepare an error-prone PCR reaction system containing high concentrations of Mg²⁺ and Mn²⁺, adjusting the dNTP ratio to enhance mutation efficiency
* Perform error-prone PCR amplification, validate the amplified products via agarose gel electrophoresis, and recover and purify the target mutant fragment
* Ligate the purified mutant fragment with the restriction-digested pET-46a-PJ100-ArsR-sfGFP vector
* Transform the ligation product into E. coli competent cells
* Plate onto LB solid medium containing 50 μg/mL carbenicillin and incubate overnight at 37°C on an inverted incubator
* Count colonies on the plate to ensure library cloning reaches ≥1000
* Randomly select 10--20 single colonies, extract plasmids, and sequence them to verify mutation site distribution (whether covering the -35 region and -10 region), confirming library validity

2025.09.18 - 2025.09.22

##### Self-Assembly System Design

Determine the self-assembly component and vector construction strategy: Select split-GFP fragments (GFP1-10, GFP11) and establish the "dual-signal dependency" logic (fluorescence is produced only when both "arsenic-induced ArsR repression release" and "GFP fragment self-assembly" occur simultaneously). Using pET46a-PlacV-ArsR-ParsOC2 as the base vector, clone GFP1-10 and GFP11 downstream of the ParsOC2 promoter to ensure synchronous expression of both fragments. Determine the induction timing as bacterial culture reaching OD600=0.6 (logarithmic phase).

2025.09.22 - 2025.09.28

##### Self-Assembly Circuit Construction

Synthesize the GFP1-10 and GFP11 gene sequences and design specific primers containing homologous arms (matching the downstream sequence of the ParsOC2 vector). Amplify the GFP1-10 and GFP11 fragments via PCR, then digest the pET46a-PlacV-ArsR-ParsOC2 vector with restriction enzymes. Subsequently, the amplified GFP fragments were ligated to the digested vector via homologous recombination. The ligation products were transformed into E. coli competent cells and spread onto LB solid medium containing 50 μg/mL carbenicillin. The plates were incubated at 37°C overnight. Finally, single colonies were picked for colony PCR screening. Positive colonies were expanded, and plasmids were extracted. Sequencing validated the insertion position and sequence accuracy of the GFP fragment, confirming the successful construction of the "ArsR-ParsOC2-GFP fragment" self-assembling circuit.

2025.09.28 - 2025.10.08

##### Self-Assembly System Testing and Optimization

**Testing Protocol:**

* Inoculate E. coli with self-assembling circuit into 5 mL LB (50 μg/mL carbenicillin), 37°C, 200 rpm shaking overnight
* Transfer to fresh LB at 1:50, same conditions to OD₆₀₀=0.6, then incubate in 0--300 μM NaAsO₂ for 3 h
* Transfer 200 μL to black-bottomed 96-well plate, measure fluorescence (485 nm excitation, 525 nm emission) via microplate reader for leakage efficiency, "arsenic concentration-fluorescence intensity" curve and system specificity assessment

**Optimization Strategies:**

* SUMO tag on GFP11 N-terminus (anti-degradation)
* Gly4Ser3 linker for GFP1-10/GFP11 (MW >30 kDa, anti-column clogging)
* Fusion gene sequences with tags/linkers (no self-assembly impact)

#### Project Timeline Summary

The experimental timeline demonstrates a systematic approach to arsenic biosensor development, progressing from initial literature review and training through multiple rounds of plasmid construction and optimization, culminating in advanced promoter engineering and self-assembly system development.

##### Key Development Milestones

* **February-April:** Literature review, laboratory training, and initial gene cloning
* **May-June:** V0-V2 plasmid construction and initial performance testing
* **July-August:** V3-V4 optimization and natural promoter strategy development
* **September:** Promoter library construction and self-assembly system development

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{% block lead %}Full-Process Engineering Development of Arsenic Biosensor Based on DBTL Closed-Loop{% endblock %}
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[Introduction](#introduction)
[Module 1: Construction and Optimization of Sensing Circuits Driven by Constitutive Promoters](#module1)

Cycle 1: First-Round DBTL Development of Basic Plasmids V0-V1-V2

Cycle 2: Second-Round DBTL Iteration of V3-V4 Driven by Constitutive Promoters

Cycle 3: DBTL Verification of Multi-Gradient Induction Experiments

[Module 2: Natural Promoter Engineering and Component Innovation](#module2)

Cycle 4: DBTL Verification of CML2 Natural Promoter

Cycle 5: DBTL Construction and Planning of Promoter Library (In Progress)

[Module 3: Self-Assembly System and System-Level Optimization](#module3)

Cycle 6: First-Round DBTL of the "AND-Gate-Like" Self-Assembly System

Cycle 7: DBTL for GFP Fragment Stability Optimization (In Progress)

[Conclusion](#conclusion)

## Full-Process Engineering Development of Arsenic Biosensor Based on DBTL Closed-Loop

#### Introduction

This study adopts "Design-Build-Test-Learn (DBTL)" as the core engineering logic, attempting to gradually address key issues of arsenic biosensors (such as high basal leakage and low component interaction efficiency) through 3 modules and 7 iterative cycles. Meanwhile, innovative strategies including "niche matching" and "AND-gate-like logic circuit" are integrated to provide an engineering paradigm for the development of synthetic biology environmental sensing systems.

#### Module 1: Construction and Optimization of Sensing Circuits Driven by Constitutive Promoters (3 Cycles: C1-C3)

In this module, we focus on "construction of basic arsenic-responsive circuits - problem localization - interference elimination". Through three rounds of DBTL iterations, we identify the core cause of high basal expression, laying a foundation for subsequent optimization.

##### Cycle 1: First-Round DBTL Development of Basic Plasmids V0-V1-V2

###### Design: Initial Design Focused on "Component Function Verification"

Core objective: Construct the basic framework of "ArsR repressor protein - sfGFP reporter gene", and investigate the source of basal expression through differentiated promoter combinations.

Design logic: Introduce regulatory components in phases --

**V0** (no specific promoter, only ArsR-sfGFP): Verify the "basal level without regulation"

**V1** (PlacV promoter drives ArsR + ParsOC2 promoter regulates sfGFP): Establish the basic "repression-response" circuit

**V2** (ParsOC2 promoter drives ArsR + ParsOC2 regulates sfGFP): Test the compatibility of "homologous promoter - repressor protein" and initially explore the impact of component matching on circuit performance

###### Build: Plasmid Assembly via Standardized Molecular Cloning

Operation procedure: Successively construct recombinant plasmids pET46a-ArsR-sfGFP-V0, pET-46a-PlacV-ArsR-ParsOC2-sfGFP-V1, and pET46a-ParsOC2-ArsR-sfGFP-V2. Digest the pET46a vector with restriction endonucleases, directionally insert the ArsR, sfGFP, and corresponding promoter fragments, ligate them, and transform into E. coli competent cells. After antibiotic resistance screening, colony PCR, and sequencing verification, confirm the successful construction of the three plasmids.

###### Test: Quantitative Detection of Circuit Response Performance by Microplate Reader

Detection protocol: According to common parameters in literature, set up multiple gradient NaAsO₂ treatment groups (0 ppb (0 μM) ... 300 ppb (300 μM)). Use a microplate reader to determine the sfGFP fluorescence intensity (Fluo) and bacterial OD600 value respectively, and calculate the "Fluo/OD600" ratio to correct the interference of bacterial density.

**Key results:** As shown in Figure a, under the condition of 300 ppb arsenic concentration, the fluorescence intensity of V1 increased by 1.7-fold compared with the control group at 0 ppb. However, the basal expression was relatively high, and the fluorescence response change was small after 6 hours of gradient induction. In the absence of arsenic, V2 showed high GFP basal expression; after arsenic treatment, the fluorescence induction error was large, the fold did not meet expectations, and the "signal-to-noise ratio" of the circuit was poor.

###### Learn: Localize the Core Issue of "Promoter Regulation Imbalance"

**Conclusion deduction:** Combined with literature reports, confirm that the "expression level of ArsR driven by constitutive promoters" is a key variable -- either excessively high or low expression of ArsR will weaken the repression effect on the ParsOC2 promoter, leading to downstream sfGFP leakage.

It is necessary to optimize the constitutive promoter to improve the binding efficiency between ArsR and ParsOC2, and reduce the basal level from the perspective of "component expression level".

![](https://static.igem.wiki/teams/5621/img/engineering/91.avif)

##### Cycle 2: Second-Round DBTL Iteration of V3-V4 Driven by Constitutive Promoters

###### Design: Targeted Design Focused on "Promoter Optimization"

Core objective: Address the "promoter regulation imbalance" identified in the Learn phase of C1, and replace the promoter type to improve the expression compatibility of ArsR.

Design logic: Retain the core framework of "ArsR-ParsOC2-sfGFP" and only replace the promoter driving ArsR --

**V3** (continue to use the PlacV promoter, optimize the ArsR coding sequence to improve protein stability)

**V4** (adopt strong constitutive promoters PJ100, PJ101, PJ102, PJ104, and PJ111 to drive ArsR, enhancing the expression level of repressor protein)

By comparing V3 and V4, exclude the independent effects of "promoter strength" and "protein sequence"

###### Build: Precise Plasmid Assembly and Verification

Operation procedure: Construct recombinant plasmids pET46a-PlacV-ArsR-ParsOC2-sfGFP-V3 and pET-46a-PJ100-ArsR-ParsOC2-sfGFP-V4. Adopt the same molecular cloning process as C1, and confirm the successful construction of the two optimized plasmids through enzyme digestion, ligation, transformation, and sequencing verification.

###### Test: Continuous Performance Detection and Data Comparison

Detection protocol: Conduct multi-gradient NaAsO₂ treatment consistent with C1, determine the Fluo/OD600 value using a microplate reader, and focus on comparing the basal differences between V3, V4 and V1, V2 in C1.

**Key results:** As a sensing component of the whole-cell arsenic sensor, PJ100 enables arsenic detection with high sensitivity (×2.5), low background, and high signal-to-noise ratio.

###### Learn: Explore the New Issue of "Protein-Promoter Binding Efficiency"

**Conclusion deduction:** Through the prediction of the binding effect between promoter and repressor protein, combined with the consistent data from C1 and C2, infer that "high basal level" does not originate from the expression level of ArsR, but from the low binding efficiency between ArsR and ParsOC2.

It is necessary to verify whether "ArsR-ParsOC2 binding efficiency" is a key factor, and at the same time exclude the interference of induction conditions (concentration, time).

![](https://static.igem.wiki/teams/5621/img/engineering/92.avif)

![](https://static.igem.wiki/teams/5621/img/engineering/93.avif)

![](https://static.igem.wiki/teams/5621/img/engineering/94.avif)

##### Cycle 3: DBTL Verification of Multi-Gradient Induction Experiments

###### Design: Control Design for Eliminating "Induction Condition Interference"

Core Objective: Verify whether "ArsR-ParsOC2 binding efficiency" is the primary cause of high basal levels, while ruling out environmental interferences such as inducer concentration and induction time.

Design Logic: Using DH5α strains transfected with V3 and V4 plasmids as research subjects, set up "multi-gradient induction conditions" -- NaAsO₂ concentration (0~300 μM), induction time (4h/8h/12h/24h), and initial induction OD value (0.4/0.6/0.8). Investigate the impact of non-core variables through comprehensive controls.

###### Build: Establishment of Multi-Gradient Experimental System

Operation Procedure: Prepare seed cultures of V3 and V4 strains, inoculate them at different initial OD values, add gradient concentrations of NaAsO₂ respectively, and sample at different time points to construct a "concentration-time-OD" three-dimensional control system.

###### Test: Systematic Investigation of Interfering Factors

Detection Protocol: Perform microplate reader detection consistent with C1 and C2, record Fluo/OD600 values under different induction conditions, and plot the "induction condition-fluorescence basal level" correlation curve.

**Key Results:** Regardless of adjustments to induction concentration or time, the arsenic-free basal levels of V3 and V4 did not decrease significantly, ruling out the interference of "unreasonable induction conditions".

###### Learn: Locking "Component Interaction Efficiency" and Introducing Computational Assistance

**Conclusion Deduction:** Combined with protein-DNA binding prediction results from AlphaFold3, confirm that "low binding efficiency between ArsR and ParsOC2" is the core cause -- amino acid conflicts at the binding interface weaken the repression effect, leading to downstream gene leakage.

It is necessary to move beyond the limitation of "promoter replacement" and shift to "promoter sequence screening", and construct a promoter library to explore variants with high binding efficiency.

![](https://static.igem.wiki/teams/5621/img/engineering/95-1.avif)

#### Module 2: Natural Promoter Engineering and Component Innovation (2 Cycles: C4-C5)

Based on the Learn conclusions of Module 1, this module introduces the innovative "niche matching" strategy and develops novel promoter components with stronger compatibility through DBTL cycles of "natural promoter testing -- library construction".

##### Cycle 4: DBTL Verification of CML2 Natural Promoter

###### Design: Innovative Design Practicing "Niche Matching"

Core Objective: Break the inertia of "universal components for model strains" and directly isolate the natural promoter ParsCML2 from the native host (rice endophyte CML2) in the target habitat (paddy field). ParsCML2 co-evolves with homologous ArsR, resulting in lower binding free energy, and can maintain high repression and low leakage in the paddy microenvironment (pH 6.2--6.8, microaerobic, rich in organic matter). Retain the "main switch" architecture where PJ100 drives arsR, and only replace the downstream ParsOC2 with ParsCML2 to obtain the plasmid pET-46a-PJ100-ArsR-ParsCML2-sfGFP-V4, enabling the "homologous promoter-repressor protein" pairing test.

###### Build: Cloning and Assembly of Novel Components

Operation Procedure: Amplify the ParsCML2 promoter fragment from the CML2 strain by PCR, insert it into the pET-46a-PJ100-ArsR-sfGFP vector to replace the original ParsOC2 sequence; confirm the successful construction of the recombinant plasmid pET-46a-PJ100-ArsR-ParsCML2-sfGFP-V4 through sequencing verification.

###### Test: Performance Evaluation of Natural Promoter

Detection Protocol: Conduct multi-gradient NaAsO₂ treatment consistent with Module 1, determine the Fluo/OD600 value using a microplate reader, and compare the basal level control effects between ParsCML2 and ParsOC2.

**Key Results:** Compared with the ParsOC2 system, ParsCML2 exhibits stronger binding ability with ArsR derived from the rice endophyte CML2, thereby significantly reducing the basal leakage expression of GFP to 8%. Under induction conditions in the range of 50--300 μM, the fluorescence intensity of ParsCML2 is 4785--6000 a.u., which is 2.3--3.1 times that of ParsOC2, achieving higher signal-to-noise ratio and detection sensitivity.

###### Learn: Clarifying the Necessity of "Library Screening"

**Conclusion Deduction:** Although the CML2 natural promoter has compatibility advantages, a single variant cannot fully solve the binding efficiency issue; it is necessary to obtain better promoter variants through "random mutation + high-throughput screening".

Construct a ParsCML2 promoter mutant library, and screen components with high repression efficiency through DBTL cycles.

![](https://static.igem.wiki/teams/5621/img/engineering/96.avif)

##### Cycle 5: DBTL Construction and Planning of Promoter Library (In Progress)

###### Design: Library Design Targeting "High-Throughput Screening"

Core Objective: Construct a ParsCML2 promoter mutant library to provide a resource pool for screening promoter variants with "high binding efficiency and low leakage".

Design Logic: Adopt error-prone PCR technology to introduce random mutations into ParsCML2 (including base substitutions, insertions, or deletions), and construct a mutant library covering the core regions of the promoter (-35 region, -10 region); the library size is set to more than 1000 clones to ensure sufficient sequence diversity.

![](https://static.igem.wiki/teams/5621/img/engineering/97.avif)

#### Module 3: Self-Assembly System and System-Level Optimization (2 Cycles: C6-C7)

Based on the Learn conclusions of the previous two modules, this module integrates the innovative strategy of "AND-gate-like circuit" and attempts to solve the basal leakage problem from the "system level" through two rounds of DBTL iteration, while developing new split-GFP fusion components.

##### Cycle 6: First-Round DBTL of the "AND-Gate-Like" Self-Assembly System

###### Design: System Design Innovating "AND-Gate-Like Logic"

Core Objective: To address the "intrinsic leakage" of repressive circuits, introduce a split-GFP self-assembly system and construct an "AND-gate-like" circuit, shifting from "passive repression" to "actively neutralizing leakage".

Design Logic: Define "leakage efficiency = leakage brightness / total brightness" and propose a "dual-signal-dependent" mechanism -- strong fluorescence is only produced when "arsenic relieves ArsR repression (Signal 1)" and "GFP fragment self-assembly (Signal 2)" occur simultaneously; in the absence of arsenic, even if ArsR repression is incomplete (leakage), a single GFP fragment has no fluorescent activity, thereby blocking the basal level.

**Specific Design:** Construct split-GFP (GFP1-10, GFP11) downstream of the ParsOC2 promoter respectively, and initiate induction when the system reaches the logarithmic growth phase to ensure synchronous expression of the fragments.

###### Build: System Establishment of the Self-Assembly Circuit

Operation Procedure: Insert GFP1-10 and GFP11 downstream of ParsOC2 in the pET46a-PlacV-ArsR-ParsOC2 vector respectively via molecular cloning to construct the "ArsR-ParsOC2-GFP fragment" self-assembly circuit; confirm the successful construction of the circuit through sequencing verification.

###### Test: Functional Verification of the Self-Assembly System

Detection Protocol: After culturing the system to OD600 = 0.6, add gradient concentrations of NaAsO₂ for induction. After 3 hours, determine the fluorescence intensity using a microplate reader and plot the "arsenic concentration-fluorescence" curve.

**Key Results:** The improved split-GFP variant system (Variant) has a leakage efficiency of less than 1%, with almost no spontaneous basal fluorescence. When detecting low-concentration arsenic, it can more accurately distinguish between "basal level" and "arsenic-induced signal", improving the detection specificity. The disadvantage is that as the arsenic concentration increases, the fluorescence intensity is weak, and the fluorescence response characteristics need to be optimized.

###### Learn: Investigating Dual Possibilities of "Fragment Expression/Assembly"

**Conclusion Deduction:**

1. GFP fragments are normally expressed but self-assembly is poor (complementary interface blocked)
2. fragments are not effectively expressed (or degraded after expression)

It is necessary to verify the function of the fragments through "in vitro expression and purification" to rule out expression/assembly issues.

![](https://static.igem.wiki/teams/5621/img/engineering/98.avif)

##### Cycle 7: DBTL for GFP Fragment Stability Optimization (In Progress)

###### Design: Plasmid Structure Optimization Targeting "Anti-Degradation"

Core Objective: To address the "fragment degradation" identified in the Learn phase of C7, improve the stability of GFP fragments through "tag addition + linker connection" while retaining the self-assembly function.

Design Logic: Adopt two major optimization strategies --

Add a SUMO tag to the N-terminus of GFP11 (capping protection to reduce degradation)

Connect GFP1-10 and GFP11 via a flexible linker (Gly4Ser3) to construct a "GFP1-10-linker-GFP11" fusion structure (increase molecular weight to > 30 kDa to avoid column penetration; meanwhile, the linker does not affect fragment complementation)

#### Summary: Project Innovation and Value Driven by the DBTL Closed Loop

Through modular design, we conducted the engineering development of arsenic biosensors from "basic construction" to "system optimization" in three separate modules and a total of seven DBTL (Design-Build-Test-Learn) cycles, while demonstrating three core values:

###### Methodological Innovation

* Explore environment-adaptable components through "niche matching"
* Solve intrinsic leakage with "AND-gate-like circuits"
* Achieve precise iteration via "multiple DBTL closed loops"
* Form a complete methodology from design concepts to optimization strategies

###### Component Contribution

* Develop two novel components -- CML2-derived ArsR-promoter (high environmental adaptability) and GFP1-10-linker-GFP11 fusion protein (high stability), enriching the synthetic biology toolbox

###### Engineering Paradigm

* Each cycle takes "problem localization -- design optimization -- verification and learning" as its core, solving problems such as high basal levels, component interaction, and fragment degradation step by step, and providing a reusable DBTL path for the engineering development of environmental sensing systems

![](https://static.igem.wiki/teams/5621/img/engineering/99.avif)

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

---

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

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

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

## Inspirations

---

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

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{% extends "layout.html" %}
{% block title %}Experimental Results{% endblock %}
{% block lead %}DBTL Experimental Results from Cycle 1 to Cycle 7{% endblock %}
{% block page\_content %}

[Introduction](#introduction)
[Module 1: Construction and Preliminary Optimization of Basic Sensing Circuit](#module1)

Cycle 1: First-Round DBTL Development of Basic Plasmids V0-V1-V2

Cycle 2: Second-Round DBTL Iteration of Optimized Plasmids V3-V4

Cycle 3: DBTL Verification of Multi-Gradient Induction Experiments

[Module 2: Promoter Engineering and Component Innovation](#module2)

Cycle 4: DBTL Verification of CML2 Natural Promoter

Cycle 5: DBTL Construction and Planning of Promoter Library (In Progress)

[Module 3: Self-Assembly System and System-Level Optimization](#module3)

Cycle 6: First-Round DBTL of AND-Gate-Like Self-Assembly System

Cycle 7: DBTL for In Vitro Verification of GFP Fragments

## DBTL Experimental Results from Cycle 1 to Cycle 7

#### Introduction

This page presents the experimental results from our DBTL (Design-Build-Test-Learn) cycles for arsenic biosensor development. The results are organized into three modules covering basic circuit construction, promoter engineering, and system-level optimization.

#### Module 1: Construction and Preliminary Optimization of Basic Sensing Circuit

This module focuses on the construction and initial optimization of basic arsenic-responsive circuits through three DBTL cycles, identifying core issues and eliminating interference factors.

##### Cycle 1: First-Round DBTL Development of Basic Plasmids V0-V1-V2

###### Plasmid Construction Results

Three recombinant plasmids were successfully assembled (pET46a-ArsR-sfGFP-V0, pET46a-PlacV-ArsR-ParsOC2-sfGFP-V1, pET46a-ParsOC2-ArsR-sfGFP-V2). Verification through restriction enzyme digestion, antibiotic resistance screening, colony PCR, and sequencing confirmed correct insertion of the elements (ArsR, sfGFP, and corresponding promoters) without sequence mutations or assembly errors.

###### Performance Testing Results

Using a multi-gradient NaAsO₂ treatment (0-300 ppb, 0-300 μM), the "fluorescence value (Fluo)/cell density (OD600)" correction ratio was measured by a microplate reader, yielding key data:

**Key Findings:**

* **V0** (No specific promoter, only ArsR-sfGFP): Primarily used to validate the "baseline level without regulation," it did not exhibit an effective arsenic response and served only as baseline control data.
* **V1** (PlacV-driven ArsR+ParsOC2 regulating sfGFP): At 300 ppb arsenic concentration, fluorescence intensity increased only 1.7-fold compared to the 0 ppb control. Background expression was high under arsenic-free conditions, and fluorescence response remained minimal after 6 hours of gradient induction, with insufficient signal amplification.
* **V2** (ParsOC2 drives ArsR+ParsOC2 regulating sfGFP): GFP background expression was significantly elevated in the absence of arsenic. Following arsenic treatment, fluorescence induction exhibited substantial error, failing to achieve the expected induction multiple. The overall "signal-to-noise ratio" was poor, rendering it unsuitable for sensing applications.

![Cycle 1 Results](https://static.igem.wiki/teams/5621/img/result/parts1.avif)

Figure 1: The simplified construction of V0, V1, V2 plasmid and result

###### Problem Identification

**Core Conclusion:** Based on literature reports and experimental data, it was determined that the "constitutive promoter-driven ArsR expression level" is the core variable. Both excessively high and low ArsR expression levels weaken the repression effect on the ParsOC2 promoter, leading to "background leakage" in downstream sfGFP expression. This finding provides direction for subsequent promoter optimization.

##### Cycle 2: Second-Round DBTL Iteration of Optimized Plasmids V3-V4

###### Plasmid Construction Results

Two optimized plasmids were successfully constructed (pET46a-PlacV-ArsR-ParsOC2-sfGFP-V3, pET-46a-PJ100-ArsR-ParsOC2-sfGFP-V4). Following C1's standardized molecular cloning workflow (restriction digestion, ligation, transformation, sequencing), it was confirmed that the ArsR coding sequence in V3 was optimally positioned, and the strong constitutive promoters (PJ100/PJ101/PJ102/PJ104/PJ111) was correctly inserted.

###### Performance Testing Results

Using the same multi-gradient NaAsO₂ treatment and "Fluo/OD600" detection method as C1, the performance differences between V3, V4, and C1's V1, V2 were compared. Key data are as follows:

**Key Findings:**

* **V3** (PlacV promoter + optimized ArsR coding sequence): No breakthrough performance improvement observed; residual background leakage persists, ruling out "ArsR protein sequence stability" as a core factor affecting background.
* **V4** (strong constitutive promoter driving ArsR): Significant performance variations among promoters, with PJ100 promoter yielding optimal results—enabling high-sensitivity detection (fluorescence induction up to 2.5-fold) while substantially reducing background expression under arsenic-free conditions, significantly improving signal-to-noise ratio and meeting fundamental arsenic sensing requirements; Other promoters (PJ101/PJ102/PJ104/PJ111) demonstrated inferior sensitivity and background control compared to PJ100.

![Promoter Sequences](https://static.igem.wiki/teams/5621/img/result/parts2.avif)

Figure 2: Five different test promoter sequences

![Promoter Results](https://static.igem.wiki/teams/5621/img/result/parts3.avif)

Figure 3: The result of 5 different promoters

![Reaction Mechanism](https://static.igem.wiki/teams/5621/img/result/parts4.avif)

Figure 4: Reaction mechanism construction and results

###### In-depth Analysis Findings

**Core Conclusion:** Integrating "promoter-repressor binding efficiency predictions" with consistent C1 and C2 data refutes the preliminary C1 conclusion — The core cause of high background leakage is not insufficient or excessive ArsR expression, but rather "inefficient binding of the ArsR repressor protein to the ParsOC2 promoter." Concurrently, further investigation is needed to rule out interference from induction conditions (arsenic concentration, induction duration) on response stability.

##### Cycle 3: DBTL Verification of Multi-Gradient Induction Experiments

###### Core Findings

Regardless of adjustments to induction concentration, duration, or initial OD values, the arsenic-free background levels in V3 and V4 showed no significant reduction, completely ruling out "unreasonable induction conditions" as a confounding factor.

###### Problem Identification

**Core Conclusion:** Based on AlphaFold3 protein-DNA binding predictions, it was confirmed that "amino acid conflicts exist at the ArsR-ParsOC2 binding interface," leading to weakened repression and downstream gene leakage. This necessitates shifting focus to "promoter sequence screening" rather than merely replacing promoter types.

![AlphaFold Predictions](https://static.igem.wiki/teams/5621/img/result/parts5.avif)

Figure 5: Basic framework and AlphaFold predictions

#### Module 2: Promoter Engineering and Component Innovation

This module introduces the innovative "niche matching" strategy and develops novel promoter components with stronger compatibility through DBTL cycles.

##### Cycle 4: DBTL Verification of CML2 Natural Promoter

###### Key Findings

ParsCML2 exhibits stronger co-evolutionary adaptation and lower binding free energy compared to the CML2-derived ArsR, significantly reducing GFP background leakage to 8% under arsenic-free conditions. At arsenic concentrations ranging from 50 to 300 μM, its fluorescence intensity reached 4785–6000 a.u., representing 2.3–3.1 times that of the ParsOC2 system, while maintaining stable performance in the rice paddy microenvironment (pH 6.2–6.8, microaeric conditions).

###### Issue Identification

**Core Conclusion:** A single ParsCML2 variant cannot fully eliminate background fluorescence. A promoter library must be constructed via "random mutation + high-throughput screening" to identify variants with higher binding efficiency.

![CML2 Natural Promoter Results](https://static.igem.wiki/teams/5621/img/result/parts6.avif)

Figure 6: Application principles, results evaluation, and experimental findings

##### Cycle 5: DBTL Construction and Planning of Promoter Library (In Progress)

###### Core Findings

Currently, only library construction design and preliminary operations have been completed; screening and testing have not yet commenced.

###### Expected Objectives

**Future Goals:** Screen for ParsCML2 mutants exhibiting "higher ArsR binding efficiency and lower background leakage" to provide high-quality promoter elements for subsequent sensor optimization.

![Promoter Library Sequences](https://static.igem.wiki/teams/5621/img/result/parts7.avif)

Figure 7: Sequences of ParsCML2 mutants

#### Module 3: Self-Assembly System and System-Level Optimization

This module integrates the innovative strategy of "AND-gate-like circuit" and attempts to solve the basal leakage problem from the "system level" through DBTL iteration.

##### Cycle 6: First-Round DBTL of AND-Gate-Like Self-Assembly System

###### Key Findings

The improved split-GFP variant system exhibits leakage efficiency below 1%, with negligible spontaneous background fluorescence in the absence of arsenic. It accurately distinguishes between "background signals" and "arsenic-induced signals" when detecting low arsenic concentrations, significantly enhancing detection specificity. However, a drawback is that fluorescence intensity increases slowly with rising arsenic concentrations (e.g., 200–300 μM), resulting in a relatively weak overall response signal.

###### Problem Identification

**Hypothesis:** We hypothesize two reasons for the weak fluorescence: First, although GFP fragments are expressed normally, impaired complementary interfaces lead to poor self-assembly. Second, GFP fragments degrade readily after expression, preventing sufficient accumulation for self-assembly.

![Self-Assembly System](https://static.igem.wiki/teams/5621/img/result/parts8.avif)

Figure 8: Schematic diagram of the system

##### Cycle 7: DBTL for In Vitro Verification of GFP Fragments

###### Core Findings

Currently, plasmid structure design and preliminary construction have been completed. We purified the GFP1-10 (52.49 kDa) and the GFP11 (3.96kDa). Stability testing and fluorescence detection have not yet been conducted.

![GFP Purification Results](https://static.igem.wiki/teams/5621/img/result/parts9.avif)

Figure 9: Expression and purification of green fluorescent protein (GFP1-10+GFP11): (A) PAGE gels of pre - and post-induction samples and PAGE gels of supernatant and pellet samples for each of GFP 1-10 +GFP 11.: lane 1,ladder ; lane 2, Pre-induction of GFP1-10; lane3, post-induction of GFP1-10; lane4,Pre-induction of GFP11; lane5, post-induction of GFP11; lane6 , precipitation of GFP1-10; lane7, precipitation GFP11; lane8, supernatant GFP1-10; lane9 , supernatant GFP11; lane10, mixed supernatant; (B) PAGE gels of purifying the target protein after mixing the two supernatants.: lane 1,ladder ; lane2, mixed supernatant; lane 3, flow through; lane 4, 20 mM imidazole eluent ; lane 5, 100 mM imidazole eluent ; lane 6, 200 mM imidazole eluent ; lane 7, 300 mM imidazole eluent ; lane 8, 500 mM imidazole eluent .

###### Expected Objectives

**Future Goals:** Significantly enhance fragment stability while preserving the self-assembly function of the GFP fragment, thereby addressing the issue of weak fluorescence intensity under high arsenic concentrations.

#### Summary of Experimental Progress

Through seven DBTL cycles organized into three modules, we have systematically addressed key challenges in arsenic biosensor development:

##### Key Achievements

* **Module 1:** Identified the core issue of "inefficient ArsR-ParsOC2 binding" as the primary cause of high background leakage
* **Module 2:** Demonstrated the superior performance of natural ParsCML2 promoter and initiated library construction for further optimization
* **Module 3:** Developed an AND-gate-like self-assembly system with extremely low leakage (<1%) and initiated fragment stability optimization

##### Future Directions

* Complete screening of ParsCML2 promoter library for higher binding efficiency variants
* Optimize GFP fragment stability to enhance fluorescence response at high arsenic concentrations
* Integrate optimized components into a final biosensor system for environmental testing

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