iGEM 2023 — Team ucas-china

{% extends "layout.html" %}
{% block title %}Notebook{% endblock %}
{% block lead %}Document the dates you worked on your project. This should be a detailed account of the work done each day for your project.{% endblock %}
{% block page\_content %}

![](https://static.igem.wiki/teams/4619/wiki/web-assets/front/notebook.png)

# Overview

In order to correctly understand the daily wet-lab progress of our team and analyze the experimental results timely, we record the experimental contents for every experiment, and finally organize them. The compiled notebook is as follows.

Week1, May 2023

* Preliminary investigation of all three modules in our project.
* Find feasible protocols for wet lab experiments.

Week2, May 2023

Project Determination

* Decide the framework and technical route of our projects.
* Scheme the upcoming wet lab experiments.

Week1, June 2023

Pathway Design and Module Viability Assurance:

* Conduct an in-depth analysis of the chosen pathway to ensure its efficiency and viability.
* Evaluate the compatibility of individual modules within the pathway.

Week2, June 2023

Plasmid Design and Codon Optimization:

* Optimize codons to enhance protein expression levels.
* Prioritize plasmid designs that facilitate downstream processes.

Week1, July 2023

Plasmid Processing and Transformation:

* Place an order for plasmids from Genscript.
* Employ heat shock transformation in E. coli.
  -Conduct monoclonal screening and extend culture for transformed E. coli.

Week2, July 2023

Primer Design and PCR Verification:

* Design primers for targeted gene sequences with high specificity.
* Order primers from a reliable supplier.
  -Perform PCR and agarose gel electrophoresis verification to confirm the correct transformation of the target gene.

Week3, July 2023

Plasmid Extraction and Standard Curve Construction:

* Extract Opener Top10 plasmid for further experiments.
* Construct a standard curve for GFP protein concentration, aligning it with Relative Fluorescence Units (RFU).
* Initiate preliminary quorum sensing experiments.

Week4, July 2023

Monoclonal Screening and Microplate Reader Calibration:

* Repeat monoclonal screening and extend incubation for successfully transformed BL21(DE3).
* Test and optimize the measurement conditions of the microplate reader for accurate readings.

Week1, August 2023

Plasmid Verification and QS Plasmid Extraction:

* Verify successful plasmid transformation through PCR and Agarose gel electrophoresis.
* Extract QS plasmid from BL21(DE3)
* Incubation of BL21(DE3) (QS contained)

Week2, August 2023

Plasmid Correction and Target Gene Construction:

* Improve some fragments in the plasmid design.
* Construct target genes (PobR and TcpH) using precise primers and PCR techniques.

Week3, August 2023

Transformation, Induction, and Fluorescence Testing:

* Transform the improved plasmid and perform monoclonal screening.
* Induce gene expression and conduct fluorescence tests for QS characterization.

Week1, September 2023

Threshold Guard Switch Modification and Inducer Gradient Concentration Test:

* Modify the Threshold Guard Switch.
* Conduct inducer gradient concentration tests and find the threshold level.

Week2, September 2023

Plasmid Reconstruction and Gel Electrophoresis:

* Reconstruct plasmids using primers and PCR for improved performance.
* Verify the reconstructed plasmids using agarose gel electrophoresis.

Week3, September 2023

Transformation, Monoclonal Screening, and Expression Induction:

* Transform reconstructed plasmids and perform monoclonal screening.
* Induce gene expression and extend incubation for optimal protein production.

Week4, September 2023

Fluorescence Testing for PobR, Nanoluc, and Threshold Guard Switch:

* Perform comprehensive fluorescence tests to evaluate the expression levels of PobR, Nanoluc, and the modified Threshold Guard Switch.

Week1, October 2023

Nanoluc Plasmid Extraction and IPTG Induction Measurement:

* Extract Nanoluc plasmid for downstream experiments.
* Measure the effectiveness of IPTG induction for controlled gene expression.

Week2, October 2023

Protein Purification and SDS-PAGE:

* Purify the proteins expressed in PobR, QS, and QNS experiments for further analysis.
* Determine and identify protein concentrations using SDS-PAGE.

Week3, October 2023

Data analysis and Visualization

* Accomplish the analysis of the data from previous experiments and visualize the results by graphic.
* Photograph the fluorescence expression of the Threshold Guard Switch and Quorum Sensing.

Full records

For more detailed notebook description, please [download the PDF](https://static.igem.wiki/teams/4619/wiki/wetlab/lab-record.pdf) of our lab record on benchling.

{% endblock %}

{% extends "layout.html" %}
{% block title %}Engineering Success{% endblock %}
{% block lead %}Demonstrate engineering success in a part of your project by going through at least one iteration of the
engineering design cycle.{% endblock %}
{% block page\_content %}

![](https://static.igem.wiki/teams/4619/wiki/web-assets/front/essss.png)

Methodology in synthetic biology reflects basic principles in engineering, and the engineering cycle reigns
amongst one of the most significant ones. The engineering cycle offers comprehensive and systematic guidance
on
the design and test of biological systems and consists of four stages: **design, build, test, and
learn.**

We propose a trace chemical detection platform combining modeling and hardware design. We are fully aware
that a
standardized engineering cycle is even more critical to our cross-disciplinary work, and we followed it
strictly
and explored it innovatively.

We have reached decent results with the implementation of it, and a summary is as follows.

1. In the first stage, we designed the genetic circuits, possible optimal strategies, and models.
2. In the second stage, we constructed a designed circuit with modeling assistance.
3. In the third stage, we implemented as desired and collected the data carefully.
4. In the last stage, we feed the result to modeling, hardware design, and experiment, gaining precious
   experience to initiate a new cycle.

![](https://static.igem.wiki/teams/4619/wiki/web-assets/eng/fcf.png)

We have also done more beside the key engineering stages and parts listed here. For more information regarding the experiment and modeling, please refer to our [Results](https://2023.igem.wiki/ucas-china/results) and [Model](https://2023.igem.wiki/ucas-china/model) page.

# Cycle 1: The Threshold Guard Switch

## Iteration 1

![]()

### Design

We first decided to design the basic circuit with typical and representative inducers, benzoic
acid
and 3-methyl
benzoate (3MBz), to identify the basic features and conditions required for the best
performance.

Moreover, we are aware of the fabulous mathematical properties of the circuit and decided to
develop
models based
on it.

### Build

To modify the function of the threshold guard, we initially inserted it downstream of the XylS/Pm
expression
module in plasmid pET28a(+) after codon optimization. The plasmid was then transformed and
expressed
in *E.
coli* BL21(DE3).

Moreover, we built a model upon the digitalizer's threshold and the repressor's strength,
giving guidance
to the experiment threshold control (see page [Model](https://2023.igem.wiki/ucas-china/model)),
mainly using numerical simulation on differential equations on Simulink. We calculated the rough
interval of the
threshold of our digitalizer and designed a series of experiments for our wet lab to locate the
absolute entry.

### Test

To evaluate the performance of the threshold guard, a series of tests were carried out on the
gradient
concentration of the inducer to find the turning-on threshold of the guard switch. We used
benzoic
acid and
3-methyl benzoate (3MBz) as inducers (input), recorded the time span, and fluorescence intensity
as
output. All
the measurement was done by synergy HTX microplate reader.

After collecting the data, we fit it and compared it with the model.

### Learn

We found that a small amount of inducer will turn on the guard switch (between 100~150 μM benzoic
acid), allowing
us to detect small molecules at a precise degree. Therefore, we replaced the downstream to the
PobR
system
(described in the next part of this cycle). The time required to ultimately peak was not that
promising, with
the minimum time 99 minutes under the induction of benzoic acid for 900 μM.However, this is
correlated to the
category and the concentration of the inducer. We hope to improve this by promoting the affinity
of
the
capturing process, as described in the [Design](https://2023.igem.wiki/ucas-china/design)
page.

![image-20231012054057650](https://static.igem.wiki/teams/4619/wiki/wetlab/lbwnb/response-time-threshold.png)

We were also delighted to find out that the curve found the model very well, surprisingly found
the
actual
threshold, determined its strength to be 680 \mu, and further estimated the repressor strength
to be
more than
10 in terms of the relative strength intervals we divided. Then, we improved the model on the
threshold of the
digitalizer and the strength of the repressor, giving prediction to the PobR experiment
threshold
control (see
page [Model](https://2023.igem.wiki/ucas-china/model)).

![Model_Result](https://static.igem.wiki/teams/4619/wiki/wetlab/lbwnb/model-result.png)

## Iteration 2

![]()

### Design

Once we understood how the guard switch worked and confirmed that it was functional, we decided
to modify the
switch to better suit our requirements and assisted with modeling. By merging the pobR and
digitizer components,
we were able to create the pobR-digitalizer using the process dewtailed in our design section
(See page [Design](https://2023.igem.wiki/ucas-china/design)) , which included
removing certain sections of
two strands of DNA and joining together the remaining pieces.

### Build

The pobR-digitizer switch was established in pET-28a (+) with a Kanamycin resistance gene and
cloned and
expressed in *E. coli* Fast-T1 after codon optimization.

### Test

We measured the intensity of GFP expression at a gradient concentration of 4-HBA over time. All
the measurement
was done by synergy HTX microplate reader. We normalized the data to better convey the actual
expression status.

![image-20231010221417423](https://static.igem.wiki/teams/4619/wiki/wetlab/finewu/pobr-concentration.png)

### Learn

We were thrilled that the threshold corresponded as we predicted, and the overall fluorescence
change obeyed the
model.

We plan to replace GFP with *luxI*, producing VAI to trigger the downstream Quorum sensing
system at a
meager level. If LuxI is efficiently expressed, the reaction time and intensity could be
promoted.

Lastly, we narrowed down the threshold range by feeding it back to the model, trying to further
improve the
performance of both the model and the biosensor.

# Cycle 2: NOX Kit Optimization

## Iteration 1

![]()

### Design

Low cost and high sensitivity are not contradictory goals. To achieve this, we opted not to
depend on existing
development boards but instead started from the chip level, designing from basic detection
components.

### Build

We chose the STC8G1K08A chip as the main controller for the NOX Kit. For rapid iteration, we used
a breadboard to
quickly prototype the circuit and 3D printing to construct a basic reaction chamber shell.

![image-20231012054553662](https://static.igem.wiki/teams/4619/wiki/hardware/prototype-of-the-shell.jpeg)

**Developing the Prototype Shell Design through team discussion**

### Test

Through a portable host computer program reading data from the NOX Kit's sensors, we verified
that the device
can capture variations in temperature and luminosity.

![image-20231012054603462](https://static.igem.wiki/teams/4619/wiki/hardware/detect-device-prototype.png)

**A Single Detector Prototype in Standalone Mode**

### Learn

Through testing the prototype and modeling simulations, we confirmed the feasibility of the
current technical
approach and began a second iteration based on requirements from biological experiments.

## Iteration 2

![]()

### Design

In the design process, we drew on lessons from the first prototype and adjusted the reaction
chamber volume based
on experiment and modeling feedback. We also chose more sensitive detection resistors around the
normal
operating point. Finally, we optimized the NOX Kit user interface for greater usability.

### Build

We redesigned the circuit with a PCB for greater compactness and reduced component exposure for
safety and
reliability. For the reaction chamber, we reused the original shell to reduce 3D printing waste
and only
replaced the core reaction vessel. For the user interface, we introduced more control buttons
and encapsulated
the Python calling interface so any developer can build their own detection programs based on
the NOX Kit. We
also introduced the I2C bus protocol, enabling developers to build high-throughput detector
arrays based on the
bus.

![image-20231012054614791](https://static.igem.wiki/teams/4619/wiki/wetlab/lbwnb/pcb-improve.jpeg)

**PCB Design of the circuit**

### Test

In the circuit prototype design, we used EDA built-in trace checking to ensure design validity.
For developers,
we provided Python encapsulation with dummy\_nox for debugging and nox classes for actual
development. Through
repeated debugging, we ensured the user control logic was correct with no bugs during use.

### Learn

During development, we found the NOX Kit could not only be applied in the current project but
also be modularly
expanded for other detection capabilities in the future, with great extensibility. With
accumulating experience,
the NOX Kit shows promise to evolve into a versatile, low-cost bio detection platform.

# References

[1] Calles, B., Goñi-Moreno, Á., & de Lorenzo, V. (2019). Digitalizing heterologous gene expression in
Gram-negative bacteria with a portable ON/OFF module. Molecular systems biology, 15(12), e8777. <https://doi.org/10.15252/msb.20188777>

[2] Arrow icons from [loading.io](https://loading.io/icon/).

{% endblock %}

{% extends "layout.html" %}
{% block title %}Experiments{% endblock %}
{% block lead %}Describe the research, experiments, and protocols you used in your iGEM project.{% endblock %}
{% block page\_content %}

![](https://static.igem.wiki/teams/4619/wiki/web-assets/front/experiments.png)

In the experimental stage of UCAS-China, we actively employed, developed, and refined a variety of protocols.
Recognizing the value of a well-structured protocol collection to benefit all iGEM teams, we have written a total
of fourteen protocols for the iGEM community.

# Protocols

* 1
  ![Chemical Transformation (Heat Shock)](https://static.igem.wiki/teams/4619/wiki/wetlab/logos/01.png)

  [Chemical Transformation (Heat Shock)](https://static.igem.wiki/teams/4619/wiki/wetlab/protocols/protocol1-chemical-transformation-heat-shock.pdf)
* 2
  ![Monoclonal & Enlarge Incubation](https://static.igem.wiki/teams/4619/wiki/wetlab/logos/02.png)

  [Monoclonal & Enlarge Incubation](https://static.igem.wiki/teams/4619/wiki/wetlab/protocols/protocol2-monoclonal-enlarge-incubation.pdf)
* 3
  ![PCR](https://static.igem.wiki/teams/4619/wiki/wetlab/logos/03.png)

  [PCR](https://static.igem.wiki/teams/4619/wiki/wetlab/protocols/protocol3-pcr.pdf)
* 4
  ![Agarose Gel Electrophoresis](https://static.igem.wiki/teams/4619/wiki/wetlab/logos/04.png)

  [Agarose Gel Electrophoresis](https://static.igem.wiki/teams/4619/wiki/wetlab/protocols/protocol4-agarose-gel-electrophoresis.pdf)
* 5
  ![Protein Expression of PobR](https://static.igem.wiki/teams/4619/wiki/wetlab/logos/05.png)

  [Protein Expression of PobR](https://static.igem.wiki/teams/4619/wiki/wetlab/protocols/protocol5-protein-expression-of-pobr.pdf)
* 6
  ![Protein Expression of Digitalized Module](https://static.igem.wiki/teams/4619/wiki/wetlab/logos/06.png)

  [Protein Expression of Digitalized Module](https://static.igem.wiki/teams/4619/wiki/wetlab/protocols/protocol6-protein-expression-of-digitalized-module.pdf)
* 7
  ![Protein Purification](https://static.igem.wiki/teams/4619/wiki/wetlab/logos/07.png)

  [Protein Purification](https://static.igem.wiki/teams/4619/wiki/wetlab/protocols/protocol7-protein-purification.pdf)
* 8
  ![IPTG Induction Expression](https://static.igem.wiki/teams/4619/wiki/wetlab/logos/08.png)

  [IPTG Induction Expression](https://static.igem.wiki/teams/4619/wiki/wetlab/protocols/protocol8-iptg-induction-expression.pdf)
* 9
  ![DNA Extraction](https://static.igem.wiki/teams/4619/wiki/wetlab/logos/09.png)

  [DNA Extraction](https://static.igem.wiki/teams/4619/wiki/wetlab/protocols/protocol9-dna-extraction.pdf)
* 10
  ![SDS-PAGE + Coomassie Brilliant Blue Staining](https://static.igem.wiki/teams/4619/wiki/wetlab/logos/10.png)

  [SDS-PAGE + Coomassie Brilliant Blue Staining](https://static.igem.wiki/teams/4619/wiki/wetlab/protocols/protocol10-sds-page-coomassie-brilliant-blue-staining.pdf)
* 11
  ![Quorum Sensing](https://static.igem.wiki/teams/4619/wiki/wetlab/logos/11.png)

  [Quorum Sensing](https://static.igem.wiki/teams/4619/wiki/wetlab/protocols/protocol11-quorum-sensing.pdf)
* 12
  ![Gibson Assemble](https://static.igem.wiki/teams/4619/wiki/wetlab/logos/12.png)

  [Gibson Assemble](https://static.igem.wiki/teams/4619/wiki/wetlab/protocols/protocol12-gibson-assemble.pdf)
* 13
  ![PCR Amplification of Target Fragments](https://static.igem.wiki/teams/4619/wiki/wetlab/logos/13.png)

  [PCR Amplification of Target Fragments](https://static.igem.wiki/teams/4619/wiki/wetlab/protocols/protocol13-pcr-amplification-of-target-fragments.pdf)
* 14
  ![Nanoluc Detection](https://static.igem.wiki/teams/4619/wiki/wetlab/logos/14.png)

  [Nanoluc Detection](https://static.igem.wiki/teams/4619/wiki/wetlab/protocols/protocol14-nanoluc-detection.pdf)

{% endblock %}

{% extends "layout.html" %}
{% block title %}Results{% endblock %}
{% block lead %}You can describe the results of your project and your future plans here.{% endblock %}
{% block page\_content %}

![](https://static.igem.wiki/teams/4619/wiki/web-assets/front/results.png)

# Overview

After carefully designing and planning the experiment, we initiated the experimental part of our project. We
mainly focused on characterizing the threshold guard in different signal-capturing systems, the orthogonality and
efficiency of the quorum sensing module, the final signaling decay process, the kill switch, and computational
results. We then collected our data and analyzed it according to the Engineering cycle (See page [Engineering Success](https://2023.igem.wiki/ucas-china/engineering)) to improve our experiment.

Detailed information regarding how we implement it and the record kept in the wet lab can be found in the [Experiments](https://2023.igem.wiki/ucas-china/experiments) part and the [Notebook](https://2023.igem.wiki/ucas-china/notebook) part.

# Original XylS Threshold Guard Switch

As described by Ángel and Víctor, the "Digitalizer module" they built has a clearly defined on-and-off
status. As mentioned in Design, we used it as a threshold guard switch that only allowed a specific inducer of a
specific concentration to open our promoter. To verify this switch's functionality and minimum threshold, we
conducted a series of gradient concentration tests using classical inducers of the Xyls/Pm system: Benzoic acid
and 3MBz.

1. Inducer: Benzoic acid

Initially, a wide range of 2000 to 0µM benzoic acid was added to *E. coli* BL21(DE3) (initial OD value =
0.688) that had the switch sequence ([BBa\_K3202045](http://parts.igem.org/Part%3ABBa_K3202045)). msfGFP
fluorescence was measured by a synergy HTX microplate reader with excitation at 485 nm (±20 nm) and emission at
520 nm (±20 nm). Fluorescence was normalized to the OD after the background fluorescence value was subtracted from
all RFU data. Continually Measuring every 2 minutes for 12 hours, we surprisingly found that the turning-on
threshold of this lay at a low level—between 150 μM and 100 μM.

![threshold-test-xyls](https://static.igem.wiki/teams/4619/wiki/wetlab/lbwnb/oct-10-11/xyls/threshold-test-xyls.png)

Overall threshold test of guard switch (benzoic acid)

Besides, the time that this switch needed to turn on was collected when the relative fluorescent units (RFU)
reached above 200, providing strong evidence that when the concentration of benzoic acid was above 150μM can be
regarded as a line separating the switch's on-and-off status. However, the response time might not be as
promising as we thought. The minimum time our switch cost to reach the on-status was 74.33 minutes at 2000μM Benz.
Acid.

![xyls/time](https://static.igem.wiki/teams/4619/wiki/wetlab/lbwnb/oct-10-11/xyls/time.png)

Response time of guard switch (benzoic acid)

Being curious about what happened when benzoic acid concentration changed from 100μM to 150μM, we performed a
detailed threshold test around this range (80μM~150μM). Using the same bacteria (initial OD value = 0.480) and
following the same protocol, we obtained the detailed situation shown in the figure below. Although the absolute
value of RFU might be different from the previous test due to the initial growth status, we still found it
distinguishable between the on (above 100 μM) and off (below 100 μM) models of this switch.

![xyls/detailed](https://static.igem.wiki/teams/4619/wiki/wetlab/lbwnb/oct-10-11/xyls/detailed.png)

Detailed threshold test of guard switch (benzoic acid)

2. Inducer: 3MBz

In order to ensure the on-and-off status on our threshold guard switch is non-specific to benzoic acid, we used
3MBz as another inducer. The result also provided an on-and-off threshold line at 10μM and aligned with the work
done by Ángel and Víctor.

![xyls/threshold-test-3mbz](https://static.igem.wiki/teams/4619/wiki/wetlab/lbwnb/oct-10-11/xyls/threshold-test-3mbz.png)

Overall threshold test of guard switch (3MBz)

# PobR Threshold Guard Switch

1. Determination of the Threshold of Our Switch

We grew *E. coli* (Fast-T1) with a chimeric PobR Threshold Guard Switch (msfGFP version, [BBa\_K4619010](http://parts.igem.org/Part%3ABBa_K4619010)). We measured the quantity of msfGFP expression
over time at different concentrations of 4-HBA using a synergy HTX microplate reader with excitation at 485 nm
(±20 nm) and emission at 520 nm (±20 nm). The initial OD600 is 0.9.

![rfu1.png (2077×1418) (igem.wiki)](https://static.igem.wiki/teams/4619/wiki/wetlab/finewu/rfu1.png)

The diagram shows the changes in msfGFP fluorescence levels over time for varying concentrations of
4-HBA.

After removing the control group and dividing it by OD600, we obtained the following results from our analysis.
We observed that concentrations above 0.25mM efficiently activate the switch, leading to a relative fluorescent
unit (RFU) more significant than 140 after a certain period. Conversely, intensities below 140 are considered
non-activated, as 140 represents the asymptote of the curve with a concentration of 0.25mM, and the proteins
produced at that concentration are just enough.

An experiment with smaller concentrations of 4-HBA was conducted to determine the specific threshold of the PobR
Threshold Guard Switch. The experiment involved varying concentrations of 4-HBA at 0.6mM, 0.3mM, 0.25mM, and
0.2mM. The results indicate that the expected putative threshold, as predicted in the model, is between 0.2mM and
0.3mM.

![Threshold](https://static.igem.wiki/teams/4619/wiki/wetlab/finewu/threshold.png)

Detailed threshold test of the PobR Threshold Guard Switch.

We believe the detection threshold can be lowered by replacing msfGFP with *luxI* in the final work. LuxI
produces VAI, activating the downstream Quorum sensing system as a signal amplifier.

2. Time Needed to Trigger the Switch

In addition, We need to analyze how long it takes to trigger the switch successfully. We define it as open when
the RFU level reaches 140.

![pobR_time](https://static.igem.wiki/teams/4619/wiki/wetlab/finewu/pobr-time.png)

The diagram shows the time needed to trigger the switch at different concentrations.

By analyzing the data in the figure, we can observe that a concentration ranging from 0.5mM to 10mM requires
approximately 120 minutes. Despite this duration being slightly longer than our initial estimates, it should have
minimal impact on the final products because only a tiny quantity of LuxI is required to initiate the quorum
sensing system.

3. Specificity of PobR Threshold Guard Switch

We confirmed that our PobR system is specific to 4-HBA by testing its response with other inducer, such as
benzoic acid. To demonstrate this, we incubated E. coli with either 5 mM 4-HBA or 5 mM benzoic acid and measured
the fluorescence intensity.

![4-HBA_Specificity](https://static.igem.wiki/teams/4619/wiki/wetlab/finewu/4-hba-specificity.png)

Responses of our PobR system to 4-HBA and Benzoic Acid.

The results align with the engineering article cited, demonstrating the superior specificity of our system
towards 4-HBA compared to its analogs.

4. Leakage Control Performance of Our Switch

We conducted an experiment to test the effectiveness of our threshold guard switch in controlling leaks. We
incubated two groups of E. coli - one with the threshold guard switch and the other without it. We then measured
the A.U. (A.U. = (Intensity of Fluorescence -Basal Fluorescence)/OD600) of msf-GFP emitted by both groups of E.
coli at different time when there was no inducer added.

![Leakage](https://static.igem.wiki/teams/4619/wiki/wetlab/finewu/leakage.png)

The A.U. of msf-GFP in two groups of E. coli (Note: A.U. = RFU/OD600, same after)

We observed a significant reduction in leakage with our Threshold Guard Switch. The following photo shows that we
can even see the difference between these two groups with our naked eyes.

![image-20231209224933361](https://static.igem.wiki/teams/4619/wiki/wetlab/finewu/leakagephoto.png)

The fluorescence Photos of these two groups of E. coli.

These results indicate that most of the leakage and false positive phenomena can be eliminated with the help of
our threshold guard switch.

# Orthogonal Quorum Sensing

Here, we designed AHL-induced quorum sensing systems without a positive feedback system.

We conducted an experiment to compare the efficiency of our quorum sensing systems with and without a positive
feedback circuit. We achieved this by measuring the change in fluorescence values at different concentrations.
First, we cultured E. coli containing plasmid [BBa\_K4619012](https://parts.igem.org/Part%3ABBa_K4619012)
in LB medium until their OD600 reached 0.5-1.0. We then induced them with AHL (VAI) dissolved in DMSO medium and
added 200 µl aliquots of each sample to a 96-well plate for 3 hours. Finally, we recorded fluorescence spectra
using a fluorescence spectrometer at 485 and 528 nm for excitation and emission wavelengths, respectively. The
results are as follows.

![quorum-sensing-efficiency-test-1.png (1656×1258) (igem.wiki)](https://static.igem.wiki/teams/4619/wiki/wetlab/qs/quorum-sensing-efficiency-test-1.png)

Quorum sensing efficiency test. Note: QS1-Circuit with *luxI* , QS2: Circuit without
*luxI*.

As shown above, there are no significant differences between these two quorum sensing systems. Therefore, we
finally chose the shorter circuit, non-positive feedback quorum sensing system. After that, we tested the
Signal-noise performance of our quorum sensing system.

![signal-noise-ratio-vs-time-1.png (1590×1122) (igem.wiki)](https://static.igem.wiki/teams/4619/wiki/wetlab/qs/signal-noise-ratio-vs-time-1.png)

Signal-noise ratio vs. Time of our quorum sensing system.

As shown in the figure, at a concentration of 100 μM, a particular induction effect has been produced.

In order to test the orthogonality of our quorum sensing system, we compared the colonies' relative
fluorescence intensity and OD value after adding the correct AHL (VAI) and the incorrect AHL (PAI).

![orthogonality-test-between-vai-and-pai.png (1590×1122) (igem.wiki)](https://static.igem.wiki/teams/4619/wiki/wetlab/qs/orthogonality-test-between-vai-and-pai-1.png)

Orthogonality test between VAI and PAI.

As can be seen from the above, after four hours of induction, the induction effect of adding AHL that matches the
system is better than that of adding mismatched AHL, indicating that our system is not susceptible to interference
and the LuxR has specificity;

Besides, we also observed the quorum sensing effect under the monitor of a fluorescence microscope.

![the-quorum-sensing-effect-under-the-monitor-of-fluorescence-microscope.png (841×841) (igem.wiki)](https://static.igem.wiki/teams/4619/wiki/wetlab/qs/the-quorum-sensing-effect-under-the-monitor-of-fluorescence-microscope.png)

The quorum sensing effect under the monitor of the fluorescence microscope.

# Nanoluc

We separate Nanoluc into one plasmid to investigate the signal process. Nanoluc is constitutively expressed in
the plasmid under the control of IPTG. When induced by IPTG, we perform luminescence measurement with the
Nano-Glo® Live Cell Assay System from Promega. We successfully characterize the signal-time curve, gaining
essential information about signal recession and other features. Moreover, we build models upon generated data,
thus gaining a more thorough comprehension of the signaling process and how we characterize it.

## Characterization of Luminescence (RLU)

After being induced by IPTG for 4h, we followed the Nano-Glo® Live Cell Assay System standard protocol for
measuring luminescence, continuously recording for 2h.

We acquired the following data:

![Nanoluc_Final](https://static.igem.wiki/teams/4619/wiki/wetlab/lbwnb/oct-10-11/nanoluc-final.png)

The result of the luminescence-time span plot

Compared with the negative control group, the group with furimazine added demonstrates a significant rise in
luminescence level, which can be captured by our hardware undoubtedly. We further mix the substrate with E. coli
that does not express nanoluc to ensure the positivity of former results.

Moreover, the decay of the signal follows a relatively predictable pattern, which is beneficial for modeling and
overall characterization. More information regarding the model, please click [here](https://2023.igem.wiki/ucas-china/model).

# Kill Switch

## Results of the Toxin-Antitoxin System

To examine the effects of our toxin-antitoxin system, we constructed a plasmid containing both the antitoxin gene
(phD) induced by IPTG and the frequently expressed toxin gene (doc). We plan to culture engineered bacteria
carrying suicide switch plasmids on two solid media, one without IPTG and the other containing 0.1M IPTG,
representing the experimental and positive control groups, respectively. Since the survival of the bacterial
strain needs to be ensured during plasmid transformation, the use of a liquid medium containing IPTG is
inevitable. Therefore, to make the experimental results more rigorous, we performed multiple rounds of washing
with deionized water on a portion of the experimental group of engineered bacteria. Thus, the experimental group
was divided into two subgroups: one with trace amounts of IPTG residue (→0) and one completely free of IPTG (0).
As shown in the figure below, it can be seen that the engineered bacteria can survive when there is a certain
concentration of IPTG in the culture environment. However, without IPTG, the engineered bacteria have a
significantly lower survival rate. Comparing the group with inducer residue concentration approaching 0 and the
group equal to 0, the survival status of the engineered bacteria also conforms to the experimental expectation.

There are some problems with these experimental results: The engineered bacteria that still survive in the
environment without IPTG, the reason should be that the lac promoter used in the gene circuit has a certain
leakage expression problem. Also, the number of engineered bacteria on the solid medium containing the inducer is
not very large. The reason for this should be that the J23119 promoter controlling the expression of the toxin
gene on the vector is too strong compared to the lac promoter upstream of the antitoxin. The above problems can be
better balanced by replacing the promoter pairs with different initiation and leakage strengths and using
toxin-antitoxin pairs with different antagonistic strengths.

![Pic](https://static.igem.wiki/teams/4619/wiki/wetlab/lbwnb/suicide-result.png)

The Verification of the Toxin-Antitoxin Kill Switch

# Rational Design

According to the structural database provided by [UniProt](https://www.uniprot.org/uniprotkb/P12746/entry#structure) and results from [Alphafold](https://alphafold.ebi.ac.uk/entry/P12746), we first collected the structures of LuxR and its
homologs in other species, including SdiA from *E. coli* and LuxR from *Yersinia enterocolitica*.
Then, we perform molecular docking on the interaction between VAI and the wildtype LuxR from *Vibrio
fischeri*. We aim to explore the binding pattern between VAI and LuxR, therefore providing insights into
further engineering the binding process to be more specific and efficient.

![image-20231213160026789](https://static.igem.wiki/teams/4619/wiki/wetlab/lbwnb/pic1.png)

The Result of the Alignment

By aligning the architecture of three structures of LuxR, we distinguished the similar binding pocket of
LuxR-VAI, and some amino acid residues nearby play important roles. Moreover, the position of VAI in LuxR remains
similar, indicating core polar interactions.

![Summary](https://static.igem.wiki/teams/4619/wiki/wetlab/lbwnb/rd.jpg)

The docking results between VAI and two LuxR homologs and the target LuxR(last docking position)

Hydrogen bonds are formed between the nitrogen from amide group and hydroxyl group from Serine or between
structured water and the hydroxyl group from Serine.

Compared with the predicted structure, the original serine is replaced by leucine, which eliminated the hydrogen
bond. Moreover, the orginal valine is replaced by arginine, which partially compensate for the polar interaction.
We then concluded the possible rational design to be two mutations based on understanding the interaction between
AHL and the protein, including **Leu 42 to Ser and Arg 67 to Val.**

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