iGEM 2022 — Team lzu-china

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{% block title %}Notebook{% endblock %}
{% block lead %}Notebook{% endblock %}
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# Notebook

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The next PDF file shows the records of our experiments in chronological order, which helps us to do them in a more organized way.

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{% block title %}Engineering{% 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 %}
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Engineering

[Cycle 1: Initial Testing of pH Promoter](#l1)
[Cycle 2: Make It More Stable](#l2)
[Cycle 3: Lysis!](#l3)
[Cycle 4: Which is the Best Chassis?](#l4)

# Overview

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Synthetic biology is principally concerned with the rational design and engineering of biologically based parts, devices, or systems. As in any other engineering field, synthetic biologists follow iterations of the **Design-Build-Test** to successfully develop innovative biological systems (figure 1).

![](https://static.igem.wiki/teams/4156/wiki/engineering/fig1.jpg)

figure 1. developments in the tools and methodologies of synthetic biology (Richard et al.2014)

In the framework of our project, we first **designed** what parts we used, then **assembled** them into chassis, finally **tested** its effective. We through many times of iterations in order to construct a targeted therapy engineered microbe. Here we only describe in detail the process of multiple iterations of the pH promoter pCadC, about which the entire successful results of our successful construction of the engineered strain can visit [proof of concept](https://2022.igem.wiki/lzu-china/proof-of-concept).

# Cycle 1: Initial Testing of pH Promoter

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## Design

According to the literature, the pH-sensitive promoter pCadC, regulated by membrane-tethered activator protein (CadC), exhibits higher activity in acidic media than in neutral pH media (figure 2). So we chose this part to response to the low pH microenvironment around the colorectal tumor. The part is [BBa\_K4156076](http://parts.igem.org/Part%3ABBa_K4156076).

![](https://static.igem.wiki/teams/4156/wiki/engineering/fig2.png)

figure 2. mechanism of the three operons, picture from Enhancing the tropism of bacteria via genetically programmed biosensors, Nature biomedical engineering.

## Build

So we added mRFP after the promoter and wanted to initially test the response of this promoter to low pH based on the fluorescence intensity. We use *E.coli* Nissle 1917 as chassis.

## Test

We continuously measured the response of this promoter at different pH over 132 hours, characterized by normalized fluorescence intensity (figure 3). The results show a progressive enhancement of its response profile as the pH decreases. These could indicate that the pH promoter is effective.

![](https://static.igem.wiki/teams/4156/wiki/engineering/fig3.png)

figure 3. low pH induce the promoter test

## Learn

But in the early stage, i.e. before 23 hours, we found that this promoter was very unstable in response to the signal, so we decided to add the amplification genetic switch. As for how to find this part, more details can be found by visiting [integrated human practice](https://2022.igem.wiki/lzu-china/human-practices).

# Cycle 2: Make It More Stable

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## Design

In order to enable living cells to perform complex signal processing operations, amplifying genetic switches and Boolean logic gates based on serine integrase (Bxb1, TP901) are used in the design of biosensor systems [1]. These genetic devices enable bacteria to perform reliable detection, multiplex logic and data storage of clinical biomarkers in human clinical samples [2，3] to meet the requirements of medical testing.

To be specific, amplifying genetic logic gates use the asymmetric transcription terminator as the reversible switch to control the RNA Pol flow between gate input and output (figure 4). However, only when serine recombinase catalyze the unidirectional reversion of DNA in the corresponding recognition site can the status of signal output be changed.

![](https://static.igem.wiki/teams/4156/wiki/engineering/fig4.png)

figure 4. picture of amplifying genetic switches and Boolean logic gates, picture from Detection of pathological biomarkers in human clinical samples via amplifying genetic switches and logic gates, Sci Transl Med.

## Build

We added switch, which is TP901 and XOR gate, then followed with mRFP to characterize (figure 5). We also used *E.coli* Nissle 1917 as chassis organism.

![](https://static.igem.wiki/teams/4156/wiki/engineering/fig5.jpg)

figure 5. genetic circuit design

## Test

We continuously measured the response of this promoter, namely pH reporter, at different pH over 132 hours, characterized by normalized fluorescence intensity (figure 6). The fluorescence intensity of the pH reporter after adding switch appeared more stable over time at pH 7.3 and was higher than that of the reporter at pH 5.8, 6.3, and 7.3, which achieved the effect we wanted.

![](https://static.igem.wiki/teams/4156/wiki/engineering/fig6.png)

![](https://static.igem.wiki/teams/4156/wiki/engineering/fig7.png)

figure 6. before and after adding switch the pH reporter's response

## Learn

We initially achieved what we wanted - a biosensor that can steadily respond to low pH signals. Not only is this a solid foundation for our next iteration, but it shows that amplified genetic switch can indeed stabilize pH biosensors.

# Cycle 3: Lysis!

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## Design

Because we have therapeutic proteins that cannot be exocytosed, it is not enough to simply stabilize the response signal, and we intend to add bacteriophage lysis gene phiX174E parts that will enable bacteria lysis.

## Build

We added phiX174E to the above genetic parts (figure 7). We also used *E.coli* Nissle 1917 as chassis organism.

![](https://static.igem.wiki/teams/4156/wiki/engineering/fig8.png)

figure 7. genetic circuit design

## Test

We continuously measured the OD600 values of the engineered strains in the above four pH over 132 hours (figure 8). The lower $OD\_{600}$ values indicate better lysis of the bacteria. The results showed that as the pH decreased, so did the $OD\_{600}$, indicating that indeed the pH induced lysis of the strain and that phiX174E was effective.

![](https://static.igem.wiki/teams/4156/wiki/engineering/fig9.png)

![](https://static.igem.wiki/teams/4156/wiki/engineering/fig10.png)

figure 8. the $OD\_{600}$ value of adding phiX174E and control group

## Learn

After three iterations we have constructed a genetically engineered circuit that meets our expectations, and the next step is to select the appropriate chassis organism.

# Cycle 4: Which is the Best Chassis?

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## Design

Based on the above validation, we can assume that strains were constructed that can stably respond to low pH. Since the chassis organism must be *E.coli*, but we started to think in which strain this gene circuit is responding better. So we wanted to compare it in *E.coli* Nissle 1917 and *E.coli* DH 5-alpha.

## Build

The data were recorded at 2-hour intervals over 48 hours of induction at the same four pH values as before, and finally plotted as the normalized fluorescence intensity (figure 9). It can be observed that the circuit responds with higher intensity in *E.coli* Nissle 1917 than in *E.coli* DH5-alpha, so *E.coli* Nissle 1917 is a better chassis organism.

## Test

The data were recorded at 2-hour intervals over 48 hours of induction at the same four pH values as before, and finally plotted as the normalized fluorescence intensity (figure 9). It can be observed that the circuit responds with higher intensity in *E.coli* Nissle 1917 than in *E.coli* DH5-alpha, so *E.coli* Nissle 1917 is a better chassis organism.

![](https://static.igem.wiki/teams/4156/wiki/engineering/fig11.jpg)

figure 9. result in different chassis

## Learn

Since *E.coli* Nissle 1917 responded better as the chassis organism, we chose it as the chassis organism to construct our engineered bacteria in our subsequent experiments.

# Conclusion

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Through four iterations of the pCadC promoter, we have obtained a biosensor that can respond stably to low pH and can lyse the parent strain, which laid a solid foundation of our subsequent work.

## Reference:

[1] Courbet A, Endy D, Renard E, Molina F, Bonnet J. Detection of pathological biomarkers in human clinical samples via amplifying genetic switches and logic gates. Sci Transl Med. May 27 2015;7(289):289ra83. doi:10.1126/scitranslmed.aaa3601
[2] Benenson Y. Biomolecular computing systems: principles, progress and potential. Nat Rev Genet. Jun 12 2012;13(7):455-68. doi:10.1038/nrg3197
[3] Bonnet J, Yin P, Ortiz ME, Subsoontorn P, Endy D. Amplifying genetic logic gates. Science. May 3 2013;340(6132):599-603. doi:10.1126/science.1232758

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{% block title %}Experiments{% endblock %}
{% block lead %}Describe the research, experiments, and protocols you used in your iGEM project.{% endblock %}
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## What should this page contain?

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Describe the research, experiments, and protocols you used in your iGEM project. These should be detailed enough for another team to repeat your experiments.

If you made Parts this year, please remember to put all information, characterization, and measurement data on the Part's Main Page on the [Registry](http://parts.igem.org/Main_Page).

## Inspirations

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* [2019 Nantes](https://2019.igem.org/Team%3ANantes/Experiments)
* [2019 TU Eindhoven](https://2019.igem.org/Team%3ATU_Eindhoven/Experiments)
* [2019 Mingdao](https://2019.igem.org/Team%3AMingdao/Demonstrate)
* [2020 Amsterdam](https://2020.igem.org/Team%3AAmsterdam/Experiments)
* [2020 NCTU Formosa](https://2020.igem.org/Team%3ANCTU_Formosa/Experiments)
* [2020 USAFA](https://2020.igem.org/Team%3AUSAFA/Experiments)

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{% block title %}Results{% endblock %}
{% block lead %}You can describe the results of your project and your future plans here.{% endblock %}
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## What should this page contain?

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* Clearly and objectively describe the results of your work.
* Future plans for the project.
* Considerations for replicating the experiments.

## Describe what your results mean

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* Interpretation of the results obtained during your project. Don't just show a plot/figure/graph/other, tell us what you think the data means. This is an important part of your project that the judges will look for.
* Show data, but remember **all measurement and characterization data must also be on the Part's Main Page on the [Registry](http://parts.igem.org/Main_Page).** Otherwise these data will not be in consideration for any medals or part awards!
* Consider including an analysis summary section to discuss what your results mean. Judges like to read what you think your data means, beyond all the data you have acquired during your project.

## Project Achievements

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You can also include a list of bullet points (and links) of the successes and failures you have had over your summer. It is a quick reference page for the judges to see what you achieved during your summer.

* A list of linked bullet points of the successful results during your project
* A list of linked bullet points of the unsuccessful results during your project. This is about being scientifically honest. If you worked on an area for a long time with no success, tell us so we know where you put your effort.

## Inspirations

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* [2019 Newcastle](https://2019.igem.org/Team%3ANewcastle/Results)
* [2019 Munich](https://2019.igem.org/Team%3AMunich/Results)
* [2019 Tec Chihuahua](https://2019.igem.org/Team%3ATec-Chihuahua/Results)
* [2020 Aalto Helsinki](https://2020.igem.org/Team%3AAalto-Helsinki/Results)
* [2020 GreatBay SCIE](https://2020.igem.org/Team%3AGreatBay_SCIE/Results)
* [2020 Queens Canada](https://2020.igem.org/Team%3AQueens_Canada/Results)

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