iGEM 2025 — Team japan-scinet

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{% block title %}Notebook{% endblock %}
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{% block lead %}This serves as a chronological record of your team's progress throughout the season. It documents your daily activities, experiments, discussions, and decisions.{% endblock %}
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![Experiments Header](https://static.igem.wiki/teams/5702/img/common/headerimg/head-wet.webp)
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* [Notebook](#notebook)
  + [Gifu Notebook\_August1](#pdf-aug1)
  + [Gifu Notebook\_August2](#pdf-aug2)
  + [Gifu Notebook\_September1](#pdf-sep1)
  + [Gifu Notebook\_September2](#pdf-sep2)
  + [Gifu Notebook\_Octorber1](#pdf-oct1)

## Notebook

---

### Gifu Notebook\_August1

### Gifu Notebook\_August2

### Gifu Notebook\_September1

### Gifu Notebook\_September2

### Gifu Notebook\_Octorber1

[Back to Top](#note-top)

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{% extends "layout.html" %}
{% block title %}Engineering Success{% endblock %}
{% block top %}En-top{% endblock %}
{% block lead %}Demonstrate engineering success in a technical aspect of your project by going through at least one iteration of the engineering design cycle.{% endblock %}
{% block header\_image %}
![Experiments Header](https://static.igem.wiki/teams/5702/img/common/headerimg/head-pro.webp)
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MathJax Example

* [Overview](#overview0)
  + [Cre](#cre)
  + [loxP](#loxp)
  + [Tom](#tom)

Overview
Cre
loxP
Tom

## Overview

Our project, PreserVEG, aims to reduce food waste by improving produce safety and enabling the visualization of deterioration. To accomplish this aim, we used Cre/loxP-based three-in-one system. The experiments to realize this system can be divided into three main elements. The first project involved the introduction and functional verification of the Cre plasmid, the second focused on the construction of the loxP plasmid and functional validation of nisin, and the third examined the expression and functional simulation of TOM.
These three projects are interconnected as follows:
Co-transformation of the Cre and loxP plasmids
Co-culture simulation of E. coli expressing TOM with E. coli expressing EtnR1 and EtnR2
Based on these two relationships, the three projects proceeded in parallel, through repeated cycles of experimentation and simulation, to improve the overall performance of the system.

![](https://static.igem.wiki/teams/5702/img/overview/1000014044.avif)

* [Cycle1: Plasmid Construction](#crecycle1)
  + [1-1](#cre1-1)
  + [1-2](#cre1-2)
* [Cycle2: Functional Analysis of EtnR1R2 and Petn](#crecycle2)
  + [2-1](#cre2-1)
  + [2-2](#cre2-2)
  + [2-3](#cre2-3)
  + [2-4](#cre2-4)
* [Cycle3: Analysis of the EtnR1R2\_Cre Plasmid](#crecycle3)
  + [3-1](#cre3-1)
  + [3-2](#cre3-2)
* [Reference](#reference-cre)

Overview
Cre
loxP
Tom

## Cycle1: Plasmid Construction

To induce Cre recombinase expression in response to ethylene, we decided to utilize the ethylene metabolic control system from *mycobacterium chubuence NBB4*.
Specifically, we applied the transcription factors EtnR1 and EtnR2, which are activated by epoxyethane, an ethylene-derived metabolite.
We aimed to construct a base plasmid for protein expression using epoxyethane as an inducer by introducing Petn, which binds to these transcription factors. [(\*1)](#cre-ref1)

### 1-1: Construction of a Plasmid Expressing the Transcription Factor EtnR1R2

#### Abstract

We performed GoldenGate Assembly to construct a regulatory plasmid expressing the transcription factor EtnR1R2, which is involved in ethylene metabolism.
Whole plasmid sequencing revealed a single nucleotide variation compared to the expected sequence, but this did not affect the insert (EtnR1R2) or plasmid replication.

Thus, we successfully constructed a plasmid containing EtnR1R2.

Design

We constructed a plasmid equipped with a complete regulatory system that expresses the transcription factors EtnR1R2, activated by the ethylene metabolite epoxyethane, and can subsequently be connected to the Petn promoter control system.

Build

Using the replication origin [(BBa\_J435300)](https://registry.igem.org/parts/bba-j435300) and lac promoter [(BBa\_J435350)](https://parts.igem.org/Part%3ABBa_J435350) included in the iGEM 2025 Distribution Kit as a base, the region containing the BsaI recognition sequence was amplified by PCR.
Additionally, fragments of the transcription factor EtnR1R2, essential for ethylene sensing, were synthesized by IDT. These three fragments were inserted using the Golden Gate Assembly (using BsaI restriction).

Test

Plasmid was extracted from colonies obtained via transformation and designated as the LacP\_EtnR1R2\_GoldenGate plasmid. Since all sequences used in this assembly were amplified by PCR, full-length sequencing analysis was carried out to confirm the absence of mutations.

Alignment with the expected sequence revealed a single-base mutation at the origin of replication.

Learn

Although the constructed plasmid contained a single-base mutation compared to the expected sequence, the transformants proliferated normally in liquid medium under ampicillin selection. This suggests the mutation does not significantly affect *E. coli* growth function.
Therefore, we concluded that we had successfully constructed the plasmid containing EtnR1R2, which forms the basis for ethylene metabolite sensing, and proceeded to the next step.

### 1-2: Construction of an Ethylene Metabolite Sensing Plasmid Using EtnR1R2-Petn

#### Abstract

Using the plasmid constructed in Cycle1-1 as the backbone, Gibson Assembly was performed with Petn\_fuGFP as the insert.
Whole plasmid sequencing confirmed the constructed plasmid perfectly matched the intended sequence, successfully establishing a plasmid based on EtnR1R2 and Petn.

Design

We constructed a plasmid equipped with a complete set of regulators to enable protein expression using epoxyethane as an inducer, incorporating Petn activated by EtnR1R2.
Furthermore, to enable subsequent functional analysis of EtnR1R2 and Petn, a simple detectable GFP was introduced downstream of Petn.

Build

Using the LacP\_EtnR1R2\_GoldenGate plasmid constructed in Cycle1-1 as the backbone, Petn\_fuGFP was introduced via Gibson Assembly.

Test

Plasmid was extracted from colonies obtained via transformation, resulting in the EtnR1R2\_Petn\_fuGFP\_Gibson plasmid. Since all sequences used in this assembly were amplified by PCR, full-length sequencing was performed to confirm the absence of mutations.

The results confirmed that the constructed plasmid possesses the expected nucleotide sequence.

Learn

We successfully constructed a plasmid containing Petn, which is regulated by transcription factors EtnR1 and EtnR2, along with GFP necessary for functional analysis of these factors.

## Cycle2: Functional Analysis of EtnR1R2 and Petn

Here, we aimed to construct a circuit that activates EtnR1/EtnR2 using epoxyethane, an ethylene monoxide, to induce GFP expression. However, fluorescence could not be detected even after optimizing the concentration conditions and induction timing of inducers such as IPTG and epoxyethane (hereafter EtO).
SDS-PAGE results revealed that EtnR1 was found in the soluble fraction, while EtnR2 was present in the insoluble fraction. Therefore, it was suggested that the reason why the induction circuit by epoxyethane did not work was due to the folding failure of EtnR2. It became clear that improvements such as codon optimization are necessary in the future.

### 2-1: Functional Verification of EtnR1R2 Using GFP①

#### Abstract

After inducing EtnR1/EtnR2 expression with IPTG, we aimed to activate epoxyethane and induce GFP expression. GFP fluorescence was monitored by adding epoxyethane at concentrations ranging from 0 to 10 µM. However, GFP fluorescence was not detected under any of these conditions. Since bacterial growth was unaffected, the absence of GFP fluorescence was attributed to insufficient epoxyethane for induction, rather than toxicity.

Design

EtnR1 and EtnR2 are transcription factors that bind to the Petn promoter region in the presence of epoxyethane and induce transcription of downstream genes. Therefore, we thought that placing GFP downstream of Petn and confirming its expression would allow simultaneous verification of EtnR1/R2 expression and function, as well as the effectiveness of Petn as a promoter.

Build

Epoxyethane (500 µg/mL in DMSO) was added to the culture medium at concentrations of 0/1/5/10 μM, and IPTG was added to achieve a concentration of 0.4 mM. The culture was incubated overnight at 25°C. Samples were then collected, and GFP fluorescence was confirmed under black light illumination. Note that epoxyethane may exhibit cytotoxicity at high concentrations [(\*2)](#cre-ref2), so concentrations were set considering its potential impact on E. coli growth inhibition.

Test

GFP fluorescence was not detected at any concentration condition.
Furthermore, no difference in E. coli growth was observed after protein expression induction by IPTG and epoxyethane.

Learn

Although epoxyethane is a highly toxic substance raising concerns about cell growth inhibition, no correlation was observed between epoxyethane concentration and OD600 values after induction. Therefore, it was confirmed that E. coli growth is not inhibited within the concentration range used in this experiment.
This led us to consider the possibility that the epoxyethane concentration had not reached the threshold for EtnR1R2 activation.
Consequently, we decided to attempt expression induction under conditions with a higher concentration of epoxyethane.

### 2-2: Functional Verification of EtnR1R2 Using GFP②

#### Abstract

To activate EtnR1/EtnR2 and induce GFP expression using epoxyethane, we conducted verification using higher concentrations of epoxyethane (0-50 µM) than in the previous cycle. After adding 0.4 µM IPTG and culturing overnight, fluorescence was checked, but no GFP fluorescence was observed under any conditions.

Design

In Cycle 2-1, epoxyethane was added at final concentrations of 0-10 µM, but GFP fluorescence was not detected. Therefore, we decided to set the epoxyethane concentration even higher and re-verify whether the EtnR1/EtnR2 system responds.

Build

Previous studies reported that in the EtnR1R2 and Petn expression regulation system, fluorescence values peaked (\*1) when 50 mM epoxyethane was added. Therefore, in this cycle, epoxyethane was added to the culture medium to achieve final concentrations of 0/1/5/10/25/50 µM.
Additionally, IPTG was added to achieve a concentration of 0.4 mM, and the culture was incubated overnight at 25°C. After incubation, samples were collected, cells were harvested, and GFP fluorescence was observed.

Test

Under black light illumination, no GFP fluorescence was detected at any concentration condition. Sample numbers 0 through 6 correspond to epoxyethane final concentrations of 0/1/5/10/25/50 µM, respectively.

![fig1](https://static.igem.wiki/teams/5702/img/engineering/cre/012345.avif)

Fig.1

Learn

The failure to detect GFP expression even at high epoxyethane concentrations suggests that insufficient epoxyethane concentration alone may not be the sole cause of the lack of GFP expression.
Previous studies have reported that pre-induction of EtnR1/R2 by IPTG enhances fluorescence intensity [(\*1)](#cre-ref1). This led us to consider that differences in the expression state of transcription factors might influence activation efficiency.

### 2-3: Confirmation of EtnR1R2 Function in Pre-Induction

#### Abstract

After induction of the transcription factors EtnR1 and EtnR2, epoxyethane was added to examine whether activation of these transcription factors would lead to a GFP fluorescence response. After culturing for 8 h or 16 h with 0.2 or 0.4 mM IPTG added, epoxyethane was added. However, GFP fluorescence was not detected under either condition.
Based on these results, concerns arise that the induction response to EtO is not established, or that there may be issues with the expression of EtnR1 and EtnR2 itself. Therefore, in the next cycle, we decided to first examine the expression of EtnR1 and EtnR2.

Design

Previous reports indicate that pre-inducing EtnR1/R2 before adding epoxyethane enhances the GFP fluorescence response [(\*1)](#cre-ref1).
Furthermore, epoxyethane is highly reactive with water, raising the possibility that it decomposes before IPTG-induced EtnR1/R2 expression is complete, thereby losing its function as an inducer. Therefore, in this cycle, we attempted to improve the fluorescence response by adding epoxyethane after pre-inducing the transcription factors with IPTG.

Build

IPTG was added at concentrations of 0.2 or 0.4 mM, and after incubation for 8 or 16 hours, epoxyethane was added. The simultaneous addition of IPTG and epoxyethane—that is, the concurrent induction of the transcription factors and GFP under the Petn promoter—was used as a control for comparison.

In Cycle 2-2, it was confirmed that the addition of epoxyethane at a final concentration of 50 mM did not inhibit the growth of E. coli. Therefore, the same concentration was adopted in this experiment.After incubation at 25 °C, samples were collected, cells were harvested, and GFP fluorescence was observed.

Table.1
![table1](https://static.igem.wiki/teams/5702/img/engineering/cre/crecycle2-3.avif)

Test

Under black light illumination, GFP fluorescence was not detected at any concentration condition. Refer to the Build table for sample numbers.

![fig2-gfp](https://static.igem.wiki/teams/5702/img/engineering/cre/crecycle2-3test.avif)

Fig.2

Learn

We examined multiple conditions, including pre-induction with IPTG and simultaneous induction, but GFP fluorescence was not observed in any case. This suggests that either the induction response to epoxyethane is not occurring at all, or EtnR1/EtnR2 itself is not being expressed. Therefore, we decided to seek advice from experts and perform troubleshooting.

### 2-4: Confirmation of EtnR1R2 Expression by SDS

#### Abstract

A meeting with Prof. Yokogawa suggested that EtnR1/EtnR2 were not expressing correctly, indicating the Petn expression system might not be functioning. Originally, the Gifu team's wet lab lacked the necessary reagents and equipment to perform SDS, but thanks to Prof. Yokogawa's generosity, SDS-PAGE was conducted.

SDS analysis confirmed the presence of an EtnR1 band in the soluble fraction, while an EtnR2 band was observed in the insoluble fraction. Based on these results and the fact that the sequence has not been codon optimized, it is possible that the induction circuit by epoxyethane did not function due to faulty folding of EtnR2.

Design

We consulted Professor Yokogawa to determine why GFP fluorescence was not observed in our prior evaluations and to refine the experimental setup. As a result, it was pointed out that the transcription factors EtnR1 and EtnR2, derived from different microorganisms, might not be expressing properly.
Therefore, with the professor's cooperation, we decided to use SDS-PAGE to confirm whether the EtnR1/EtnR2 proteins were expressing in E. coli.

cre detail about Human Practices, click [here](https://2025.igem.wiki/japan-scinet/human-practices)

Build

The Gifu team's wet lab lacked the necessary reagents and equipment, making SDS-PAGE difficult to perform. However, thanks to Professor Yokogawa's generosity, we were able to conduct the experiment using his original protocol. For detailed experimental methods, please see Experiment.

Test

E. coli cells induced only with IPTG (0.4 mM) were lysed, and both soluble and insoluble fractions were applied. Previous studies have reported bands for EtnR1 around 50-75 kDa and for EtnR2 around 25 kDa [(\*3)](#cre-ref3). In the present results, a band for EtnR1 was detected in the soluble fraction at around 66 kDa, whereas a strong band for EtnR2 was observed in the insoluble fraction at around 25 kDa.
These results suggest that although EtnR2 is expressed, it may not be functioning properly due to misfolding.

![fig3-gel](https://static.igem.wiki/teams/5702/img/engineering/cre/crecycle2-4.avif)

Fig.3

Learn

SDS-PAGE results confirmed the expression of EtnR1 and EtnR2. However, EtnR2 was present in the insoluble fraction and was likely nonfunctional due to folding defects. This suggested that interaction between the two transcription factors was not established, and the epoxyethane-induced expression system may not have functioned.

Furthermore, since the EtnR1/EtnR2 sequences were not codon optimized for E. coli, there was concern that this might cause reduced translation efficiency and folding defects.

However, due to time constraints, it was difficult to synthesize new codon-optimized genes and redo all the assays. Therefore, we decided to try to improve the expression status using the Rosetta2 strain, which possesses tRNA corresponding to rare codons.

###### ◎We are sharing the experiments as a joint team between Gifu University and Nagahama Institute of Bio-Science and Technology, with the Nagahama team responsible for analysis at the protein level. Since the Nagahama team can confirm expression by SDS-PAGE, they will be able to directly evaluate the expression and function of EtnR1/EtnR2 without relying on GFP fluorescence. Therefore, the previously used EtnR1R2\_Petn\_fuGFP\_Gibson plasmid was deemed unnecessary, and we decided to proceed with constructing the final plasmid designed to express Cre in response to ethylene metabolites, aligning with the original goal of the project.

## Cycle3: Analysis of the EtnR1R2\_Cre Plasmid

In this cycle, we constructed a Cre expression plasmid with the goal of “detecting ethylene metabolites to express Cre and activate the Cre/LoxP system.” First, we replaced the GFP sequence in the EtnR1R2\_Petn\_fuGFP\_Gibson plasmid used in Cycle 2 with Cre, creating the EtnR1R2\_Petn\_Cre\_Gibson plasmid.

This plasmid was transferred to the Nagahama team. To confirm that EtnR1 and EtnR2 were expressed and transferred to the soluble fraction, the host strain was changed to Rosetta2 and protein expression analysis was performed. SDS-PAGE results showed no bands corresponding to EtnR1 and EtnR2, indicating that further investigation of expression levels and folding conditions is necessary.

### 3-1: Co transformation & GFP detection

#### Abstract

A plasmid containing Cre downstream of EtnR1/EtnR2 and Petn was constructed to induce Cre expression using epoxyethane as an inducer. DNA sequencing of the newly introduced Cre confirmed perfect match with the expected sequence. Thus, successful construction of the plasmid containing EtnR1R2 was achieved.

Design

We aimed to construct a plasmid in which Cre expression is induced by ethylene metabolites.
The functionality of the newly introduced Cre [(BBa\_25Q0IEK8)](https://registry.igem.org/parts/bba-25q0iek8) via Golden Gate Assembly was characterized in LoxP Cycle 3.
This Cre recombinase recognizes loxP sites and mediates excision of the loxP-flanked sequence.

Build

The EtnR1R2\_Petn\_fuGFP\_Gibson plasmid constructed in Cycle 1-2 contained BsaI sites flanking the GFP cassette.
We synthesized a Cre DNA fragment bearing compatible BsaI sites and, via Golden Gate Assembly, replaced the GFP cassette with the Cre sequence.

Test

Following transformation, plasmid DNA was extracted from resulting colonies and designated the EtnR1R2\_Petn\_Cre\_GoldenGate plasmid.
Partial sequencing across the Cre insert confirmed that the fragment matched the intended sequence.

Learn

Thus, we successfully constructed a plasmid encoding EtnR1 and EtnR2, the Petn promoter they regulate, and Cre recombinase under Petn control.
The completed plasmid was transferred to the Nagahama wet lab.

### 3-2: Verification of Transcription Factor Expression in the EtnR1R2\_Petn\_Cre Plasmid

#### Abstract

Building on Cycle 2, where EtnR2 appeared insoluble in BL21, we switched to the Rosetta2 strain to supplement rare-codon tRNAs and reassess expression.
Rosetta2 cells transformed with the EtnR1R2\_Petn\_Cre\_GoldenGate plasmid were processed, and protein samples were concentrated using centrifugal filter units: 12,000 rpm for 30 min, then the filter insert was inverted and spun at 3,500 rpm for 2 min to recover the retentate.

Taking into account the Cycle 2 results and the lack of codon optimization, we attempted to improve EtnR1/EtnR2 expression by using the Rosetta2 strain, which supplies tRNAs for rare codons.
Rosetta2 was transformed with the EtnR1R2\_Petn\_Cre\_GoldenGate plasmid constructed in Cycle 3-1.
We then performed SDS-PAGE on IPTG-induced samples; however, no bands corresponding to either transcription factor were detected.

Design

Building on Cycle 2, where EtnR2 appeared insoluble in BL21, we switched to the Rosetta2 strain to supplement rare-codon tRNAs and reassess expression.
Rosetta2 cells transformed with the EtnR1R2\_Petn\_Cre\_GoldenGate plasmid were processed, and protein samples were concentrated using centrifugal filter units: 12,000 rpm for 30 min, then the filter insert was inverted and spun at 3,500 rpm for 2 min to recover the retentate.

Build

The concentrated samples were separated into supernatant (soluble) and pellet (insoluble) fractions and analyzed by SDS–PAGE under both IPTG-induced and non-induced conditions.

Test

E. coli subjected only to IPTG induction (0.1 mM) was lysed, and both soluble and insoluble fractions were applied. Previous studies have identified bands for EtnR1 around 50–75 kDa and for EtnR2 around 25 kDa (\*3). In this study, no bands for EtnR1 or EtnR2 were detected.

![](https://static.igem.wiki/teams/5702/img/engineering/cre/crecycle3-2.avif)

Fig.4

Learn

The reason EtnR1R2 expression was confirmed at Gifu University but not at Nagahama Institute of Bio-Science and Technology may be due to differences in culture conditions. At Gifu University, the culture was incubated at 37°C for 3 hours during this experiment, whereas at Nagahama Institute of Bio-Science and Technology, incubation was performed at 37°C for approximately 22 hours. As a result, the protein may have denatured, preventing the detection of bands at the intended positions.

## Reference

1. Claudia F. Moratti, Sui Nin Nicholas Yang, Colin Scott, Nicholas V. Coleman, Development of a whole-cell biosensor for ethylene oxide and ethylene, Microbial Biotechnology,vol 17(6),(2024)
   [↑](#cre-cite1 "戻る")
2. G. T. Michael, C. R. Stumbo, Ethylene oxide sterilization of Salmonella senftenberg and Escherichia coli: death kinetics and mode of action, Journal of Food Science, vol. 35(5), pp. 631–634 (1970).
   [↑](#cre-cite2 "戻る")
3. https://2016.igem.org/Team:Sydney\_Australia/Sense
   [↑](#cre-cite3 "戻る")

* [Cycle1: Plasmid Construction](#loxcycle1)
* [Cycle2: In Vitro Cre Recombination Assay](#loxcycle2)
  + [2-1](#lox2-1)
  + [2-2](#lox2-2)
  + [2-3](#lox2-3)
* [Cycle3: In Vivo Cre Recombination Assay](#loxcycle3)
  + [3-1](#lox3-1)
    - [3-1-1](#lox3-1-1)
    - [3-1-2](#lox3-1-2)
  + [3-2](#lox3-2)
  + [3-3](#lox3-3)
* [Cycle4: NisinQ Expression and Functional Analysis](#loxcycle4)
  + [4-1](#lox4-1)
  + [4-2](#lox4-2)
* [Cycle5: Co-transformation w/EtnR1R2\_Cre](#loxcycle5)
  + [5-2](#lox5-1)
  + [5-1](#lox5-2)
  + [5-1](#lox5-3)
  + [5-4](#lox5-4)
* [Reference](#reference-lox)

Overview
Cre
loxP
Tom

## Cycle1: Plasmid Construction

We created a loxP plasmid susceptible to Cre recombinase. In this project, we designed the loxP sequences to be oriented in the same direction, enabling the gene between the loxP sites to be knocked out via deletion.
By placing the antimicrobial peptide Nisin and a terminator between the loxP sites and introducing GFP downstream of the loxP, we aimed to construct a plasmid capable of two-step gene expression in a Cre-dependent manner.

#### Abstract

We designed and constructed a plasmid to enable the sequential expression of the antibacterial peptide NisinQ and the fluorescent protein GFP using the Cre/loxP system. The plasmid, constructed via Gibson Assembly, was confirmed by sequence analysis, and we successfully built a vector containing NisinQ between loxP sites.

Design

To achieve both antibacterial and visualization functions within a single metabolic pathway, it was necessary to design a plasmid enabling sequential expression of the antibacterial peptide NisinQ and the fluorescent protein GFP.

To accomplish this, we applied the Cre/loxP system, combining conditional knockout with Cre expression-dependent gene regulation.

Build

The sequences for loxP, terminator, and GFP were quoted from a paper based on an *E. coli* assay where the terminator was inserted between loxP sites to halt expression, allowing downstream GFP expression after recombination [(\*1)](#lox-ref1).
Furthermore, considering molecular weight and solubility in E. coli, the composite part [(BBa\_K4437002)](https://parts.igem.org/Part%3ABBa_K4437002) designed for iGEM Calgary 2022 [(\*2)](#lox-ref2) combining NisinQ with nusA was adopted.

Gibson Assembly was performed using the downstream loxP sequence and the sequence containing GFP as the vector, and the upstream loxP sequence, NusA\_NisinQ, and the terminator sequence as the insert.

![The result of electrophoresis](https://static.igem.wiki/teams/5702/img/engineering/horoto/cycle1.avif)

Fig.1

Test

Plasmid was extracted using colonies obtained through transformation and designated as the loxP\_NisinQ\_sfGFP\_Vector\_Assembled plasmid. Since all sequences used in this assembly were amplified by PCR, full-length sequence analysis was performed to confirm the absence of mutations.

As a result, it was confirmed that the plasmid contained the designed sequence.

Learn

We successfully constructed a plasmid containing the antibacterial peptide NisinQ between loxP sites.

In the next step, we will verify whether the loxP sites are actually knocked out by Cre recombinase.

## Cycle2: In Vitro Cre Recombination Assay

Site-specific cleavage using the Cre/loxP system is an essential process for advancing this project. Therefore, we conducted an in vitro recombination assay using purified Cre recombinase.

First, Cre recombinase and the loxP plasmid were reacted under NEB-recommended conditions. Subsequently, the loxP plasmid was linearized using restriction enzymes to investigate the relationship between plasmid form and enzyme reaction.
Furthermore, conditions for enzyme reaction time and enzyme concentration were optimized. The results of these verifications were evaluated by confirming the band of the loxP-deleted plasmid via electrophoresis.

### 2-1: Verification of Cleavage Using the NEB Standard Protocol

#### Abstract

Based on the NEB recommended protocol, an in vitro recombination assay of loxP plasmids using purified Cre recombinase was performed. The positive control loxP 2+ yielded the recombinant fragment. In contrast, no new bands resulting from recombination were detected in the plasmid constructed in Cycle 1.
These results suggest that constraints arising from the three-dimensional structure due to supercoiling, or sequences surrounding the loxP site, may be inhibiting Cre access.

Design

To verify whether the constructed loxP plasmid is cleaved by Cre recombinase, we decided to use purified Cre recombinase (NEB#M0298). First, Cre and the loxP plasmid were reacted under NEB's recommended conditions [(\*3)](#lox-ref3).
Subsequently, reaction conditions would be optimized as necessary. The success criteria for the assay were detecting the predicted fragment lengths [3006 kb, 1922 kb] by electrophoresis and no new bands detected in the negative control.

Build

Using the loxP plasmid purified by mini-prep in Cycle 1 as a sample, we set up a reaction system employing purified Cre recombinase and analyzed the plasmid strand length in the post-treatment sample via agarose gel electrophoresis.
To ensure verification reliability, we also assayed a LoxP2+ Cre+ sample (positive control) and a loxP plasmid Cre- sample (negative control) under identical conditions.

![The result of electrophoresis](https://static.igem.wiki/teams/5702/img/engineering/horoto/cycle2.avif)

Fig.2

Test

Following the NEB protocol, a recombination assay was performed using purified Cre recombinase, and the strand lengths of the treated plasmids were confirmed by electrophoresis.

![The result of electrophoresis](https://static.igem.wiki/teams/5702/img/engineering/loxp/cycle2-1.avif)

Fig.3

From the official NEB website[(\*3)](#lox-ref3), pLox2+ is known to be a circular plasmid of 2787 bp (appears to be around 1.7 kbp) and a fragment of 838 bp after recombination.
In this experiment, no band was observed for the positive control fragment. However, a band likely representing a circular plasmid was detected around 1.7 kbp, indicating that the positive control recombination was successful.
On the other hand, the plasmid we constructed did not change the band pattern with or without Cre, suggesting that recombination failed.

Learn

Under these conditions, recombination succeeded in the positive control, but no recombination was observed in the constructed loxP plasmid. This result suggests that the supercoiled structure may restrict Cre recombinase access to the loxP site.
In the next cycle, it will be necessary to investigate differences in recombination efficiency due to plasmid topology.

### 2-2: Confirmation of Cleavage by Plasmid Linearization

#### Abstract

To evaluate the DNA structure-dependent reactivity of the loxP plasmid, the plasmid was linearized with SpeI to enhance the accessibility of purified Cre recombinase near the loxP site, followed by verification.
Electrophoresis results showed no new bands from cleavage in the circular (supercoiled) form, while recombinant products were detected in the linearized plasmid. This suggests that the DNA's three-dimensional structure affects the reaction efficiency of Cre recombinase.

Design

Based on Human Practice with Prof. Yokogawa and literature review, we hypothesized that in circular plasmids, the supercoiled structure may reduce Cre recombinase access to loxP sites, potentially lowering recombination efficiency. Furthermore, based on the random collision model hypothesis [(\*4)](#lox-ref4),
we considered the possibility that two rings generated by Cre cleavage could become entangled, preventing detection of the recombinant plasmid at the correct size.

Therefore, we designed the plasmid to be processed with the restriction enzyme SpeI to linearize it and expose the region near loxP, enabling Cre recombinase to act efficiently.

For more detail about Human Practices, click [here](https://2025.igem.wiki/japan-scinet/human-practices)

Build

After mini prep, the loxP plasmid (4928 bp) was digested with SpeI to prepare linearized plasmid.

After the reaction, the enzyme was inactivated, and the product was purified using a gel extraction kit. The linearized plasmid obtained from purification was used in the reaction with Cre recombinase. The same experiment was performed with a SpeI-untreated sample. This allowed comparison of recombination efficiency based on topological differences.

SpeI does not cleave the loxP sequence or the reporter region; therefore, it was determined that it does not affect the DNA strand length resulting after recombination.

Test

Analysis of reaction products by electrophoresis revealed that no bands indicative of Cre-mediated recombination was detected in the circular loxP plasmid, just as in Cycle2-1. In contrast, the linearized loxP plasmid showed bands indicating Cre-mediated recombination, confirming the deletion between the loxp plasmids.

![](https://static.igem.wiki/teams/5702/img/engineering/loxp/cycle2-2-1.avif)

Fig.4
![](https://static.igem.wiki/teams/5702/img/engineering/loxp/cycle2-2-2.avif)

Fig.5

When recombination occurs in the constructed plasmid, a 1922 bp sequence is deleted between loxP sites, resulting in a 3006 bp plasmid. The band observed around 3000 bp in the linear Cre+ sample in Fig. is considered to be the recombinant plasmid. Furthermore, the band observed slightly above the arrow in the linear Cre- sample is thought to be either a recircularized plasmid or a restriction enzyme processing remnant.

Learn

It was revealed that linearizing the plasmid with restriction enzymes and resolving its supercoiled structure enables recombination at loxP sites by purified Cre recombinase. This supports the possibility that access to loxP is restricted in the supercoiled state due to steric hindrance. Furthermore, these results confirmed that the constructed plasmid functions as a recognition site for Cre recombinase.

However, Cre recombination in *E. coli* occurs with the plasmid in its circular form. Therefore, we have decided to investigate conditions further to achieve successful recombination in the circular plasmid.

### 2-3: Examination of Reaction Time and Enzyme Concentration Conditions

#### Abstract

To evaluate cleavage efficiency in circular (supercoiled) plasmids, we performed in vitro verification under all 20 conditions combining Cre recombinase enzyme amount and reaction time. Electrophoresis results revealed a novel fragment generated by loxP deletion under the high-concentration, short-incubation-time condition of 4 units of Cre recombinase and 5 and 15 minutes of reaction time. This confirmed that loxP site cleavage occurs even in the supercoiled state.

Design

In the Cre/loxP system, increasing enzyme concentration and reaction time may improve recombination efficiency [(\*5)](#lox-ref5). Therefore, to confirm Cre recombinase cleavage in circular plasmids, we set multiple conditions for Cre recombinase concentration and incubation time and verified the results.

Build

Cre-recombined concentrations were set at four conditions: 1 unit, 2 units, 3 units, and 4 units. Each Cre concentration was incubated for 5 min, 15 min, 30 min, 1 h, and 2 h, resulting in a total of 20 conditions examined. Plasmid DNA was extracted from each condition using mini-prep and analyzed by electrophoresis.

Test

Electrophoresis results showed bands likely representing recombinant plasmids when incubated for short periods.

Bands were particularly clearly visible in samples incubated for 5 minutes and 15 minutes after adding 4 units of Cre.

![](https://static.igem.wiki/teams/5702/img/engineering/loxp/2025-10-09-090647.avif)

Fig.6
![](https://static.igem.wiki/teams/5702/img/engineering/loxp-cycle2-3-test.avif)

Fig.7

Learn

Increasing the Cre recombinase concentration and shortening the incubation time revealed that recombination by Cre recombinase occurs even in the supercoiled state.

Then, we decided to examine the Cre recombination assay within *E. coli* itself.

## Cycle3: In Vivo Cre Recombination Assay

Based on discussions with Prof. Yokogawa and literature review, it was suggested that recombination mediated by Cre recombinase may occur more readily in vivo than in vitro [(\*6)](#lox-ref6).
Therefore, in this cycle, we performed in vivo validation of the Cre/loxP system using a Cre-expressing plasmid and the loxP plasmid constructed in Cycle 1. The cell culture after protein expression induction was used to examine whether recombination occurred at the DNA level. In addition, we quantified the GFP fluorescence intensity observed during bacterial harvesting to verify the progression of GFP protein expression after recombination.
Furthermore, we aimed to comprehensively evaluate the effects of promoter leak expression and IPTG concentration on GFP expression levels by setting multiple induction conditions.

For more detail about Human Practices, click [here](https://2025.igem.wiki/japan-scinet/human-practices)

### 3-1: Co transformation & GFP detection

#### Abstract

The BL21 strain was co-transformed with a plasmid that expresses Cre recombinase[(BBa\_25Q0IEK8)](https://registry.igem.org/parts/bba-25q0iek8) and the loxP plasmid. After transformation, colonies were obtained and cultured by shaking, successfully generating the bacterial strains required for the in vivo assay. To confirm successful recombination, IPTG induction was performed, and GFP expression was visually examined. However, no fluorescence was observed in any of the samples, suggesting that Cre-mediated cleavage at the loxP sites may not have occurred.
Therefore, as the next step, we decided to perform DNA-level analysis to investigate the recombination event more precisely.

### 3-1-1: Co-transformation

#### Abstract

BL21 cells were co-transformed using a plasmid expressing Cre [(BBa\_25Q0IEK8)](https://registry.igem.org/parts/bba-25q0iek8) and a loxP plasmid. After transformation, colonies were obtained and the strains required for the in vivo assay were successfully generated. To confirm recombination success, IPTG induction was performed to visually detect GFP expression; however, no fluorescence was observed in any sample. Therefore, considering the possibility that Cre recombinase did not cleave the loxP site, we decided to proceed with DNA-level analysis as the next step.

Design

To verify recombination by Cre/loxP system in E. coli, Cre plasmid and loxP plasmid were co-transformed into E. coli BL21(DE3). Using this strain, it is possible to verify recombination at the DNA level and to examine protein expression from the loxP plasmid after recombination.

Build

Co-transformation (details in experiment) was performed [(\*7)](#lox-ref7). To prevent incompatibility, Cre and loxP plasmids were selected with different replication origins. The former carries an ampicillin resistance gene, while the latter carries a chloramphenicol resistance gene. Culturing on medium containing both ampicillin and chloramphenicol enabled reliable screening of colonies successful in co-transformation.

Test

Transformation succeeded, and colonies were obtained. A glycerol stock was prepared.

Learn

We successfully created E. coli strains harboring the recombinase expression plasmid and a plasmid containing the loxP sequence, which is the recognition site for the enzyme, both necessary for verifying the Cre/loxP system. We decided to use this strain to perform an in vivo Cre recombination assay.

### 3-1-2: Confirmation of GFP Expression

Design

To confirm recombination occurs in E. coli via the Cre/loxP system, we used the strain created in Cycle3-1-1. We aimed to induce Cre expression in this bacterial culture and delete the sequence between the loxP sites.
As in Cycle 1, the Cre-sensitive plasmid contains a terminator between the loxP sites and a GFP-coding sequence downstream of the loxP sites. Therefore, confirmation of GFP expression following the deletion of the sequence between the loxP sites allows verification of whether Cre recombination was successful.

Build

E. coli harboring Cre and loxP plasmids were cultured overnight at 25°C with IPTG added at three concentrations: 0, 0.2, and 0.4 mM. After incubation, GFP expression was confirmed under each condition.

Test

Under any conditions, GFP fluorescence could not be detected in liquid medium. This may be due to the Cre recombinase failing to cleave the loxP site. Therefore, we decided to verify whether the loxP site was cleaved in the next cycle.

Learn

A possible reason for the lack of GFP fluorescence is that Cre recombinase did not cleave at the loxP sites.
Therefore, in the next cycle, we will verify whether cleavage at the loxP sites has occurred.

### 3-2: Confirmation of Cre recombination at the DNA level

#### Abstract

To verify whether site-specific cleavage by the Cre/loxP system functions in E. coli, experiments were conducted using E. coli prepared with Cycle3-1. Plasmids were extracted from samples after IPTG induction and subjected to electrophoresis to confirm the activity of Cre recombinase in vivo.
The results showed recombination was confirmed under all conditions, including samples without IPTG addition.

Design

Using E. coli containing the Cre plasmid and loxP plasmid created in Cycle 3-1, verify recombination at the DNA level. The cause of the lack of GFP fluorescence expression is thought to be one of the following three possibilities.

Cause 1 → Recombination by Cre did not occur, and the polymerase did not reach the GFP gene.

Cause 2 → Recombination by Cre occurred, but the protein was not expressed.

Cause 3 → Recombination by Cre occurred, and the GFP protein was expressed, but it lacks activity.

The goal was to narrow down the cause(s) preventing fluorescence observation to one, or two or three possibilities, by confirming the deletion at the DNA level.

Build

E. coli harboring Cre and loxP plasmids were cultured overnight at 25°C with IPTG added at four concentrations: 0, 0.1, 0.2, and 0.4 mM. Plasmids were recovered from post-induction samples via mini prep.
These extracted plasmids were subjected to electrophoresis. Recombination was verified by confirming the presence of bands corresponding to plasmids with the loxP region deleted.

Test

We unexpectedly observed GFP fluorescence when recovering the bacterial cells during the initial stage of miniprep.

![gggfffppp](https://static.igem.wiki/teams/5702/img/engineering/loxp/2025-10-08-232450.avif)

Fig.8

Furthermore, we confirmed the band of loxP plasmid after recombination in all samples. The position of this band was consistent with the results of the in vitro assay.
This result indicates the success of the in vivo Cre recombination assay.
The detection of bands in the IPTG (-) samples suggests that Cre leakage expression occurred.

![](https://static.igem.wiki/teams/5702/img/engineering/loxp/2025-10-08-232611.avif)

Fig.9

\*loxP plasmid = 4928 bp(mini prep), Cre colonal plasmid = 3353 bp (synthetic nucleic acid) We applied each sample to the wells in equal amounts of DNA.

Learn

As GFP fluorescence was confirmed during bacterial cell recovery, all causes indicated in the Design phase could be rejected.

And the electrophoresis results demonstrated that the Cre/LoxP system functions in co-transformed E. coli. Even in IPTG (-) samples, bands following recombination were clearly visible. Therefore, even in the absence of IPTG, Cre can express in sufficient quantities due to leakage from the T7 promoter.

However, in the IPTG (-) sample in Fig., we didn't observe fluorescence visually, which suggests that the T7 promoter in the loxP plasmid can highly regulate protein expression.

In the next step, it is necessary to quantify the GFP fluorescence and compare the fluorescence intensity for each IPTG concentration.

### 3-3: Measurement of fluorescence intensity

#### Abstract

GFP fluorescence intensity was measured under each induction condition (IPTG 0/0.1/0.2/0.4 mM), and the relative values were compared. Based on these results, the effects of Cre leak expression and IPTG concentration on GFP expression levels were examined. After protein expression induction, the culture medium OD600 was adjusted to 0.5, and fluorescence values were measured. The results showed maximum fluorescence at 0.1 mM IPTG, with fluorescence decreasing at higher concentrations.
While the confirmation of recombination at the DNA level suggested the influence of Cre leak expression, a significant difference was confirmed between the fluorescence values of samples without IPTG addition and those with IPTG addition.

Design

Confirmation of GFP expression suggests the success of the Cre recombination and the proper progression of the gene circuit in the loxP plasmid after recombination.

We aim to compare GFP fluorescence intensity with and without IPTG and confirm that fluorescence values are significantly higher in the presence of IPTG. Additionally, we will investigate the extent to which Cre leak expression and the resulting recombination affect gene expression from the loxP plasmid.

Build

E. coli harboring Cre and loxP plasmids were cultured overnight at 25°C with IPTG added at four concentrations: 0/0.1/0.2/0.4 mM (n=3). After protein induction, 1 mL of culture was taken, and the cells were harvested. The cells were then diluted in PBS to achieve an OD600 of 0.5.
This sample was applied to a 96-well plate, and we measured fluorescence at 535 nm using excitation light at 485 nm using a microplate reader.

Test

The results of the measurements are as shown in the table below.

| IPTG (mM) | 0 | 0.1 | 0.2 | 0.4 | PBS |
| --- | --- | --- | --- | --- | --- |
| RFU | 14761 | 30610 | 21519 | 24216 | 32 |
| RFU | 14854 | 28107 | 27298 | 23010 | 32 |
| RFU | 15319 | 31434 | 25030 | 22886 | 32 |

We performed Tukey's multiple comparison test to examine the fluorescence values.

![gfp graf](https://static.igem.wiki/teams/5702/img/engineering/loxp/2025-10-08-232706.avif)

Fig.10

Fluorescence intensity significantly increased upon IPTG induction compared to 0 mM (p < 0.05). The maximum expression was observed at 0.1 mM IPTG, while higher concentrations (0.2 mM and 0.4 mM) showed decreased fluorescence.

Learn

Fluorescence intensity measurements revealed the strongest fluorescence under conditions where 0.1 mM IPTG was added. Furthermore, GFP expression was confirmed even under conditions without IPTG addition (IPTG (-)), due to recombination occurring from Cre leak expression.
However, the fluorescence intensity under these conditions was significantly lower compared to the IPTG-added condition. This indicates that the terminator designed between the loxP sites is functioning.

These results confirm that the loxP\_NisinQ\_sfGFP\_Vector\_Assembled plasmid constructed in Cycle 1 undergoes deletion of the sequence between loxP sites in vivo upon Cre recombinase action.
Furthermore, it was shown that following recombination, IPTG induces expression of the downstream GFP.

## Cycle4: NisinQ Expression and Functional Analysis

By Cycle 3, we demonstrated that the constructed loxP plasmid undergoes recombination by Cre recombinase. Furthermore, by measuring fluorescence after deletion of the loxP-flanked region, we verified Cre-dependent protein expression and its functionality.
In Cycle 4, we analyzed NisinQ—the segment positioned between the loxP sites that is deleted in a Cre-dependent manner. Notably, for NisinQ we adopted the NusA–NisinQ fusion part (BBa\_K4437002) designed by iGEM Calgary 2022, considering molecular weight and solubility in \*E. coli\* (\*2\*).

For more detail about Human Practices, click [here](https://2025.igem.wiki/japan-scinet/human-practices)

### 4-1: Confirmation of NisinQ Expression

Design

We aim to confirm the expression of Nisin Q from the loxP plasmid using SDS-PAGE. We will also examine the difference in expression levels with and without IPTG induction.

Build

After preculturing the loxP plasmid at 37°C, the cells were transferred to a main culture at 37°C. When the OD reached approximately 0.6, IPTG was added to a final concentration of 0.1 mM. Following incubation, 1 mL of the culture was collected. After centrifugation and resuspension, 500 μL of the cell extract was purified using affinity chromatography with a spin column, and then analyzed by SDS-PAGE.

Test

As a result of the SDS-PAGE analysis of the loxP plasmid, a faint band was observed around 65 kDa, which corresponds to the expected molecular weight of the NusA–NisinQ fusion protein.
Although very faint bands were also detected in the flow-through and wash fractions 1 and 2, the strongest band appeared in the elution fraction.
Furthermore, since no other bands were observed in the elution fraction besides the one near 65 kDa, it is highly likely that this band represents the target fusion protein composed of NusA and NisinQ.

![](https://static.igem.wiki/teams/5702/img/engineering/loxp/nisin-iptg-1.avif)

Fig.11
![](https://static.igem.wiki/teams/5702/img/engineering/loxp/nisin-iptg-1-2.avif)

Fig.12

Learn

Although a band likely corresponding to the target protein was observed in the SDS-PAGE results, it was faint, and thus we could not conclusively confirm that it represents the NusA–NisinQ fusion protein.
Unfortunately, due to time constraints, we were unable to perform additional experiments. However, increasing the amount of cell lysate applied to the column could enhance the detection of the target band, making it easier to evaluate both the expression level and the difference between IPTG-induced and non-induced conditions.
To verify whether the observed band truly corresponds to the target fusion protein, further affinity purification using a larger amount of cells should be performed, followed by testing the isolated protein for antimicrobial activity in Wet lab experiments.

### 4-2: Nisin Functional Analysis

#### Abstract

To prevent foodborne illnesses caused by bacteria on fresh produce, we evaluated the antimicrobial functionality of the natural peptide nisin, which cannot be handled in the laboratory, through simulation. Targeting Listeria monocytogenes, a pathogen capable of proliferating under refrigeration, we analyzed the effects of concentration, pH, and temperature by combining the Weibull model and the Hill function.

Design

One of the concepts of this biosensor project is to prevent foodborne illness caused by bacteria attached to fresh produce. Therefore, we decided to evaluate the functionality of nisin, which serves to protect produce from bacterial contamination. Among Gram-positive bacteria that cause spoilage and food poisoning, we focused on Listeria monocytogenes. This pathogen can grow even under refrigerated conditions, posing a risk of reaching infectious levels in stored produce, and has been responsible for numerous outbreaks. However, since Listeria requires BSL-2 facilities and cannot be handled in our laboratory, we conducted a dry functional evaluation instead.

Build

We aimed to quantitatively clarify how the bactericidal effect of the natural antimicrobial peptide nisin varies with three factors—concentration, pH, and temperature—by constructing a predictive model that integrates multiple mathematical models. Specifically, we used the Weibull model to describe the nonlinear decrease in bacterial count over time and applied the Hill function to reproduce the steep, switch-like response to changes in nisin concentration.

$$\boxed{\;\delta(C, \mathrm{pH}, T) \;=\exp (\;
b\_0 \;+\; b\_{\mathrm{Hill}}\,H(C) \;+\; b\_{\mathrm{pH2}}\,( \mathrm{pH}-\mathrm{pH}\_{\mathrm{opt}} )^2 \;+\; b\_T\,(T-T\_{\mathrm{ref}})
\;)}$$

![fig3-1](https://static.igem.wiki/teams/5702/img/dry/project3/fig3-1.webp)

Fig.13

Test

We defined parameters for concentration, pH, and temperature and estimated their optimal values. Parameter estimation was performed using the least squares method to minimize the residuals between observed and modeled values. The results showed that nisin is most effective under acidic conditions (pH ≈ 5.0) and at low temperatures, but requires relatively high concentrations to achieve sufficient antibacterial activity.

Interpreting these results in the context of our project, nisin works more effectively on produce that tends to be slightly acidic. Although Listeria monocytogenes can proliferate even in refrigerated environments, nisin can help prevent such foodborne risks during cold storage. Furthermore, the study demonstrated that effective sterilization requires high concentrations of nisin (10²–10³ µg/mL) over extended periods. Through the process of building this multivariate model, we realized that the model’s accuracy strongly depends on the quality and diversity of input data, reaffirming the importance of robust data collection in biosensor development.

Learn

Interpreting these results in the context of our project, nisin works more effectively on produce that tends to be slightly acidic. Although Listeria monocytogenes can proliferate even in refrigerated environments, nisin can help prevent such foodborne risks during cold storage. Furthermore, the study demonstrated that effective sterilization requires high concentrations of nisin (10²–10³ µg/mL) over extended periods. Through the process of building this multivariate model, we realized that the model’s accuracy strongly depends on the quality and diversity of input data, reaffirming the importance of robust data collection in biosensor development.

## Cycle5: Co-transformation w/EtnR1R2\_Cre

#### Abstract

Through Cycle 2-4, we successfully verified the functionality of the constructed loxP plasmids.
In previous in vivo analyses, a plasmid constitutively expressing Cre recombinase was used.
However, to achieve the goals of Protection, Sensing, and Visualization in this project, it is necessary to employ a Cre expression plasmid that responds to ethylene.
Therefore, we used the EtnR1R2\_Petn\_Cre\_GoldenGate plasmid constructed in Cre Cycle 3 to co-transform BL21 cells, thereby generating the Sense strain for this system.

Design

The EtnR1R2\_Petn\_Cre\_GoldenGate plasmid encodes EtnR1 and EtnR2, transcription factors that are activated by ethylene metabolites, as well as their corresponding binding promoter, Petn.
Theoretically, this plasmid enables Cre expression induced by epoxyethane, a metabolite of ethylene.
For this purpose, the Cre plasmid and the loxP plasmid were co-transformed into E. coli BL21(DE3).

Build

Cotransformation was performed using the EtnR1R2\_Cre plasmid and the loxP plasmid.
To prevent plasmid incompatibility, the two plasmids were designed with different origins of replication.
The former carries an ampicillin resistance gene, while the latter carries a chloramphenicol resistance gene.
Therefore, by culturing on medium containing both ampicillin and chloramphenicol, colonies that successfully underwent cotransformation were reliably screened and selected.
To convert ethylene into epoxyethane, which can activate EtnR1R2, a monooxygenase-expressing strain was employed.
Accordingly, a coculture simulation was conducted using the constructed strain together with the monooxygenase-expressing strain.

Test

Transformation was successful, and colonies were obtained.
These colonies were preserved as glycerol stocks, designated as the Sense strain.
The results of the coculture simulation conducted with the Sense strain and the monooxygenase-expressing strain are presented below.

For more detail about Dry project 1, click [here](https://2025.igem.wiki/japan-scinet/model)

Learn

At this stage, the functional analysis of EtnR1R2\_Cre has not yet been completed; therefore, the experiment will not be conducted.
However, it will be possible to perform an in vivo Cre recombination assay following the Cycle 3 protocol, as well as to use this strain for coculture simulations with monooxygenase-expressing E. coli that oxidizes ethylene.

#### Future Work

We have not yet demonstrated the expression and function of EtnR1R2, and resolving this is a priority.
Once completed, we will perform validations analogous to Cycle 3 to determine whether environment-responsive Cre, induced via the EtnR1R2–Petn module, mediates recombination at the loxP sites in vivo.

### Reference

1. Nathan Tague, Virgile Andreani, Yunfan Fan, Winston Timp, Mary J. Dunlop, Comprehensive screening of a light-inducible split Cre recombinase with domain insertion profiling, ACS Synthetic Biology, vol 12,Issue 10 (2023)
   [↑](#lox-cite1 "戻る")
2. https://2022.igem.wiki/calgary/preservation-nisin
   [↑](#lox-cite2 "戻る")
3. https://www.neb.com/ja-jp/products/m0298-cre-recombinase?srsltid=AfmBOop3g-84v-WZAYt7JwDgK8DkVBqJI63Hyed8PiX4b7ObbTSVsiHG
   [↑](#lox-cite3 "戻る")
4. Abremski K, Hoess R, Sternberg N. Studies on the properties of P1 site-specific recombination: evidence for topologically unlinked products following recombination. Cell. 1983 Apr;32(4):1301-11. doi: 10.1016/0092-8674(83)90311-2. PMID: 6220808.
   [↑](#lox-cite4 "戻る")
5. S.W. Santoro, P.G. Schultz, Directed evolution of the site specificity of Cre recombinase, Proc. Natl. Acad. Sci. U.S.A. 99 (7) 4185-4190 (2002)
   [↑](#lox-cite5 "戻る")
6. Enghiad, B., Huang, C., Guo, F. et al. Cas12a-assisted precise targeted cloning using in vivo Cre-lox recombination. Nat Commun 12, 1171 (2021)
   [↑](#lox-cite6 "戻る")
7. Tomoiaga, D., Bubnell, J., Herndon, L. et al. High rates of plasmid cotransformation in E. coli overturn the clonality myth and reveal colony development. Sci Rep 12, 11515 (2022)
   [↑](#lox-cite7 "戻る")

* [Cycle1: Plasmid Construction](#tomcycle1)
  + [1-1](#tomcycle1-1)
  + [1-2](#tomcycle1-2)
* [Cycle2: Tom Expression Confirmation\_Wet](#tomcycle2)
* [Cycle3: Tom Expression Simulation\_Dry](#tomcycle3)
* [Cycle4: Simulation of TOM Functionality](#tomcycle4)
* [Cycle5: Co-culture Simulation of Sense Strains and Monooxygenase Strains](#tomcycle5)
* [Reference](#reference-tom)

Overview
Cre
loxP
Tom

## Cycle1: Plasmid Construction

With the design goal of developing a module that enables the Tom protein (monooxygenase) to function as an ethylene reactor—converting ethylene into epoxyethane detectable by the sensor strain—we aim to establish an integrated DBTL cycle combining wet experiments and dry modeling.

Specifically, we will first determine the DNA sequence of Tom derived from Burkholderia cepacia G4 and redesign it for expression in E. coli. Based on this optimized sequence, we will conduct plasmid construction as part of the design phase.
Next, we will attempt wet-lab experiments to verify Tom expression; however, if expression is difficult to confirm experimentally, we will employ computational modeling to predict Tom expression levels and evaluate expected enzyme activity through in silico simulations.

Subsequently, we will integrate the Tom-expressing strain into a co-culture model with the epoxyethane sensor strain, allowing us to simulate both ethylene oxide (Eto) accumulation and sensor response following ethylene addition.
Through this iterative process, we will validate and optimize the Tom expression module, ultimately establishing a robust engineering cycle that integrates the module into the ethylene-responsive biosensor system.

### 1-1: Tom Sequence Determination

#### Abstract

In this project, the V106F and A113F mutants of toluene/o-xylene monooxygenase (Tom) were selected as target enzymes functioning as ethylene monooxygenases. However, since sequence information for both mutants was unavailable, the related gene cluster was investigated, and the mutation sites were identified based on literature data.
Mutations were then introduced into the wild-type sequence accordingly. Subsequently, codon optimization was performed based on the codon usage bias of the host organism, and the desired mutant sequences were constructed.

Design

In this project, the V106F and A113F mutants of toluene/o-xylene monooxygenase derived from Burkholderia cepacia G4 were selected to function effectively as ethylene monooxygenases. However, since the sequence information of these mutant enzymes was not available in existing databases, the gene cluster sequence of Burkholderia cepacia G4 Tom (TomA0-TomA5) was first investigated using GenBank [(\*1)](#tom-ref1).
Subsequently, to determine which subunit corresponded to the V106F and A113F mutations, a comparative analysis was conducted, revealing that only TomA3 contained valine at position 106 and alanine at position 113 (Figure 1).

![Figure 1](https://static.igem.wiki/teams/5702/img/engineering/tom1-1-toma1.avif)
![Figure 2](https://static.igem.wiki/teams/5702/img/engineering/tom1-1-toma3.avif)
![Figure 3](https://static.igem.wiki/teams/5702/img/engineering/tom1-1-toma4.avif)

Figure 1-1-1: Comparison of the amino acid sequences of TomA1, TomA3, and TomA4 at residues 106 and 113

Build

Therefore, nucleotide sequences of the enzyme genes obtained from GenBank were modified to introduce either the V106F or A113F mutation. These sequences were then optimized using VectorBuilder (2) according to the codon usage bias of Escherichia coli (strain K-12, substr. MG1655), while ensuring that no restriction enzyme sites were included.

Test

Through sequence optimization using VectorBuilder, the Codon Adaptation Index (CAI) and GC content were obtained as shown in Table 1. This optimized sequence was used for the prediction of expression levels by machine learning.

Table 1-1-1. Evaluation of CAI and GC content after optimization.

Table 1-1-1. Evaluation of CAI and GC content after optimization.

| Gene | GC Content (%) | CAI |
| --- | --- | --- |
| TomA0 | 54.22 | 0.98 |
| TomA1 | 59.04 | 0.94 |
| TomA2 | 48.52 | 0.97 |
| TomA3 of V106F | 50.32 | 0.95 |
| TomA3 of A113F | 50.26 | 0.95 |
| TomA4 | 59.10 | 0.96 |
| TomA5 | 55.68 | 0.94 |

![図１](https://static.igem.wiki/teams/5702/img/engineering/tom-fig1.avif)

Figure1-1-2. the whole sequence of Tom A113F Mutant

![図2](https://static.igem.wiki/teams/5702/img/engineering/tom-fig2.avif)

Figure1-1-3. the whole sequence of Tom V106F Mutant

Learn

In the sequence determination process of this study, the gene cluster of Tom derived from strain G4 was found to contain six coding regions, designated TomA0 to TomA5. According to previous studies, the functional enzyme consists of three subunits—TomA1, TomA3, and TomA4—which assemble into an (αβγ)₂ structure to exhibit enzymatic activity.
Based on this information, it was assumed that the mutations occurred in TomA3. In fact, similar mutations have been reported in TomA3 in earlier studies, supporting the validity of this assumption (※3, 4).

### 1-2: Tom Plasmid Construction

#### Abstract

EtnR1/EtnR2 are transcription factors that do not respond to ethylene itself but react to its monoxide, epoxyethane. Therefore, an enzyme is required to oxidize ethylene released from fruits and vegetables into epoxyethane. In this study, we created the plasmid TOM\_A113F\_GoldenGate by codon-optimizing the ethylene monooxygenase Tom and introducing the A113F mutation.
TOM\_TomA0124\_Vector and TOM\_A113F\_Tom34\_BsaI were ligated via Golden Gate Assembly. Electrophoresis analysis confirmed a shifted-up band compared to the vector, demonstrating successful construction of the TOM\_A113F\_GoldenGate plasmid.

Design

EtnR1/EtnR2 are transcription factors that do not respond to ethylene itself but react to its monoxide, epoxyethane. Therefore, an enzyme is required to oxidize ethylene released from fruits and vegetables into epoxyethane.
In this study, we created the plasmid TOM\_A113F\_GoldenGate by codon-optimizing the ethylene monooxygenase Tom and introducing the A113F mutation. TOM\_TomA0124\_Vector and TOM\_A113F\_Tom34\_BsaI were ligated via Golden Gate Assembly. Electrophoresis analysis confirmed a shifted-up band compared to the vector, demonstrating successful construction of the TOM\_A113F\_GoldenGate plasmid.

Build

Recombination was performed using the TOM\_TomA0124\_Vector plasmid and the TOM\_A113F\_Tom34\_BsaI plasmid via Golden Gate Assembly. To confirm the success of the recombination, agarose gel electrophoresis was performed, and it was determined that the band would shift upward compared to the vector (TOM\_TomA0124\_Vector plasmid).

\*TOM\_TomA0124\_Vector plasmid = 6015 bp, TOM\_A113F\_GoldenGate plasmid = 7194 bp

Test

The electrophoresis results showed that the TOM\_A113F\_GoldenGate band was positioned above the TOM\_TomA0124\_Vector plasmid band, confirming the expected shift-up.

![](https://static.igem.wiki/teams/5702/img/engineering/2025-10-09-104859.avif)

Figure1-2-1

Learn

Based on the electrophoresis results, we determined that the TOM\_A113F\_GoldenGate plasmid was successfully constructed.

## Cycle2: Tom Expression Confirmation\_Wet

#### Abstract

Using the plasmid constructed in Cycle 1, we attempted to confirm the expression of TomA0-A5. However, since the protein was not tagged or otherwise labeled, we were unable to detect a clear band. Therefore, we decided to proceed to expression simulation in Dry.

Design

The Tom complex consists of six subunits (TomA0-A5). Therefore, with the cooperation of Prof. Yokogawa, SDS-PAGE was performed to confirm protein expression from the plasmid created in Cycle 1-2.

Build

E. coli cells induced with IPTG (A: 0.2 mM or B: 0.4 mM) were disrupted, and the soluble and insoluble fractions were applied separately. Since the molecular weights of TomA0-A5 are widely distributed, gels prepared as follows were used.

![](https://static.igem.wiki/teams/5702/img/engineering/2025-10-09-105348.avif)

Figure2-1.

Test

We've identified several bands, but we are not entirely sure which Tom they correspond to.There are too many bands to see clearly. We should have tagged each protein.

![](https://static.igem.wiki/teams/5702/img/engineering/2025-10-09-105410.avif)

Figure2-2.

TomA0 = 8.3 kDa

TomA1 = 37.5 kDa

TomA2 = 10 kDa

TomA3 = 61.0 kDa

TomA4 = 13.1 kDa

TomA5 = 39.2 kDa

Learn

We attempted to confirm TOM expression using the constructed plasmid, but were unable to detect expression of any of the six TOMs. Based on this result and the professor's advice that it is difficult to perfectly confirm the expression of the six untagged proteins, we decided to proceed with in vitro expression simulation.

## Cycle3: Tom Expression Simulation\_Dry

The biosensor proteins EtnR1 and EtnR2 used in this project respond specifically to ethylene oxide and are therefore unable to directly detect ethylene. Consequently, to achieve ethylene sensing, it is necessary to introduce and express an enzyme that converts ethylene into ethylene oxide in a separate Escherichia coli strain from the one expressing EtnR1 and EtnR2. The enzyme employed in this study is a mutant of toluene/o-xylene monooxygenase derived from Burkholderia cepacia G4. Since few previous studies have investigated this mutant, and its expression level in E. coli remains unknown, a Python-based prediction program was developed to estimate its expression level.

#### Abstract

In this study cycle, it was confirmed that the V106F and A113F mutants of toluene/o-xylene monooxygenase (Tom) function effectively as ethylene monooxygenases (※3-1). Therefore, the nucleotide sequences of both mutants were constructed using information from literature and databases, and a Python-based program was developed to predict their expression levels. As training data, protein expression levels and the corresponding DNA sequences of Escherichia coli were obtained from PaxDb (※3-2) and UniProt (※3-3).

Design

As mentioned above, in developing the prediction program, the approach was designed based on information derived from nucleotide sequences that encode the target proteins. However, since the information obtainable from nucleotide sequences (e.g., the secondary structure of mRNA, free energy and diversity in the thermodynamic ensemble, and mountain plots, etc.) is highly diverse, only a selected subset of these features was used for the prediction process.

Build

To obtain nucleotide sequence-derived information from the input DNA sequences, the ViennaRNA package was implemented in the Python code to calculate the “minimum free energy (MFE)” and “minimum free energy structure (SS)” of the DNA sequences obtained from the database(※3-2, 3-3). In addition, the Longformer model was employed to extract features from the RNA sequences. These extracted data were then combined with the corresponding “expression levels” into a single DataFrame, which was prepared as the training dataset.

Test

The dataset was divided into features (X) and the target variable (y: expression level), and then split into training and test sets. A random forest regression model was trained, and the predictive performance on the test data was evaluated using the mean squared error (MSE). Subsequently, RNA sequences were generated from unknown DNA sequences, and the expression levels were predicted through the same procedure as for sequences with known expression levels. As a result, when predictions were performed in two stages using 40 and 95 training data points, respectively, the MSE was smaller with 95 data points, and the gap between the “observed” and “predicted” values was reduced.

Learn

Initially, when obtaining protein expression levels of E. coli and their corresponding DNA sequences from the database, the data were entered in descending order of expression levels. As a result, when the training dataset contained 40 samples, a clear tendency of Predicted > Observed (Actual) was observed in the scatter plot. Therefore, to improve the prediction accuracy and enable comparison, 57 additional pairs of DNA sequences and expression data were added, and the two sequences with the highest expression levels were removed as outliers before re-performing the prediction. As a result, a decrease in MSE was observed, and the scatter plot showed that the relationship between expression levels became closer to Predicted ≒ Observed (Actual). These findings suggest that, in addition to increasing the number of data points and removing outliers, randomly including DNA sequences with significantly different expression levels is also important for improving prediction accuracy. Furthermore, since the enzyme showed a consistent level of expression in all predictions, the next step was to proceed to the functional evaluation of this enzyme.

## Cycle4: Simulation of TOM Functionality

#### Abstract

Building upon the results of Cycle 3, we formulated the rate equation describing the change in concentration (formation rate) of ethylene oxide, the product of the enzymatic reaction catalyzed by TOM. This equation was implemented in Python to simulate the concentration dynamics, and the functionality of the enzyme was evaluated primarily based on the behavior of these concentration changes.

Design

From the results of Cycle 3, we confirmed the expression of TOM in E. coli. Based on this outcome, we conducted a simulation to evaluate the functionality of the expressed TOM enzyme and to determine whether it could serve as a practically useful biocatalyst in our project.

Build

Further literature research was conducted; however, we were unable to find a detailed enzymatic reaction equation describing the catalytic process inside TOM. Therefore, we assumed that the enzymatic reaction occurring within TOM proceeds through a mechanism similar to that of alkene monooxygenases (11), and constructed a corresponding reaction model.

Based on this assumption, we derived rate equations describing the concentration changes of the product ethylene oxide (C₂H₄O) and the substrate ethylene (C₂H₄).

To verify the validity of this assumption, we consulted Professor Atsuhiro Shimada at Gifu University as part of our Human Practices activities.

Test

A Python simulation was developed based on the constructed rate equations and fitted to experimental data reported in the literature (※3-1). The simulation was executed, and the results can be viewed on the Dry Lab’s Model 1 page via the link below.

Example of simulation results:

![fig3-1](https://static.igem.wiki/teams/5702/img/dry/project1/project1-14.webp)

Figure4-1.Expressed enzyme: A113F

![fig3-1](https://static.igem.wiki/teams/5702/img/dry/project1/project1-16.webp)

Figure4-2.Expressed enzyme: V106F

Learn

The obtained simulation results demonstrated that both TOM variants, A113F and V106F, exhibited time-dependent concentration changes consistent with a typical first-order enzymatic reaction. However, the reaction time for A113F was approximately 250 minutes, whereas V106F required around 8,000 minutes—roughly 32 times longer.

These findings suggest that, within the experimental framework of our project, the A113F variant—with its significantly shorter reaction time—is the more suitable enzyme for practical application.

## Cycle5: Co-culture Simulation of Sense Strains and Monooxygenase Strains

#### Abstract

In this project, we developed and analyzed a mathematical model describing the behavior of a co-culture system composed of Escherichia coli engineered to express monooxygenase, which converts ethylene into ethylene oxide, and sensor E. coli responsive to ethylene oxide. First, using single-strain cultivation data, we estimated fundamental parameters such as the maximum specific growth rate and the substrate half-saturation constant.
Next, enzyme expression levels and catalytic turnover numbers were estimated, and the epoxidation reaction was described using the Michaelis-Menten framework. Furthermore, growth inhibition by the product, ethylene oxide, was incorporated into the model. Substrate consumption, product accumulation, and sensor response under co-culture conditions were then represented as a system of ordinary differential equations (ODEs).
Through this model, we simulated the dynamics under different initial biomass and substrate concentrations and identified conditions that maximize the sensor response.

Design

This study aimed to model the dynamics of a co-culture system consisting of a monooxygenase-expressing strain that oxidizes ethylene to ethylene oxide and a sensor strain that responds to the produced ethylene oxide. First, single-strain cultivation experiments were designed to obtain data for estimating key Monod parameters, including the maximum specific growth rate (μₘₐₓ), the substrate half-saturation constant (Kₛ), and the yield coefficient (Yₓ/ₛ).

Based on these values, we constructed an integrated system of ordinary differential equations (ODEs) describing the growth of both strains, substrate consumption, the ethylene oxidation reaction (modeled by the Michaelis–Menten equation), and the growth-inhibitory effects of the product.
The resulting unified model was designed to predict the time-course fluorescence output of the sensor strain (SensorOutput). Furthermore, the model can be applied to exploring optimal conditions for maximizing sensor response and to parameter sensitivity analyses.

Build

The model was implemented in Python, employing SciPy’s solve\_ivp function for numerical integration and scipy.optimize.curve\_fit for parameter estimation. First, Monod parameters were fitted using single-strain cultivation data as input, and the resulting parameters were incorporated into the co-culture model.

For the enzymatic reaction, values of Vₘₐₓ and Kₘ were derived from literature data, which were then used to calculate kₐₜ and the corresponding enzyme concentration. These parameters were integrated into the model as part of the reaction rate expression. To account for inhibitory effects and product accumulation, a function was introduced in which the growth rate μ is suppressed as a function of the ethylene oxide concentration (P).

The entire model was modularly structured, allowing independent validation of each process—biomass growth, substrate consumption, product formation, and sensor output—thus enabling flexible testing and refinement of individual system components.

![fig3-1](https://static.igem.wiki/teams/5702/img/dry/result/fig1-oed.webp)

Figure.5-1 Ordinary Differential Equation (ODE) system representing the co-culture dynamics after ethylene addition

Test

Using the constructed model, simulations were performed under both single-culture and co-culture conditions, and the resulting biomass dynamics, substrate consumption, product concentration, and sensor responses were analyzed.

Furthermore, optimization of the initial conditions (S\_0, X\_{0,1}, X\_{0,2}) was conducted, with the maximum sensor output y′\_max defined as the objective function. An initial grid search was employed to capture the overall trend, followed by Bayesian optimization using Optuna to improve search precision.

As a result, it was confirmed that variations in the initial substrate concentration and cell ratio significantly affected the sensor response, enabling the quantitative identification of conditions that maximize response intensity.

![](https://static.igem.wiki/teams/5702/img/dry/project2/project2-17.webp)

Figure.5-2 Comparison of Sensor Outputs

Learn

Simulation results revealed that enzyme expression level, initial cell ratio, and substrate concentration strongly influence the sensor response. Furthermore, the difference in growth rates between the TOM-expressing strain and the sensor strain was suggested to contribute to product accumulation and response delay.

However, several simplifications remain in the current model. In particular, the model does not account for induction delay of enzyme expression, metabolic burden of protein synthesis, gas–liquid equilibrium and diffusion losses of ethylene and ethylene oxide, or intracellular localization effects. In addition, the sensor response was approximated using a Hill equation, which does not capture the nonlinear dynamics or stochastic noise inherent in transcription factor behavior.

Future work will involve extending the model to incorporate these factors and validating parameters through experimental comparison. This refinement is expected to enable quantitative design of biosensors suitable for real-world applications such as fruit ripening detection and other environmental ethylene-sensing systems.

## Reference:

1. GenBank: AF349675.1,
   <https://www.ncbi.nlm.nih.gov/nuccore/AF349675.1>
   [↑](#tom-cite1 "戻る")
2. Vector Builder,
   <https://www.vectorbuilder.jp/tool/codon-optimization.html>
   [↑](#tom-cite2 "戻る")
3. Rui L, Kwon Y.M., Fishman A., Reardon K.F., Wood T.K. (2004).
   Saturation Mutagenesis of Toluene ortho-Monooxygenase of *Burkholderia cepacia* G4 for Enhanced 1-Naphthol Synthesis and Chloroform Degradation.
   *Applied and Environmental Microbiology*, 70(6), 3246–3252.
   <https://doi.org/10.1128/AEM.70.6.3246-3252.2004>
   [↑](#tom-cite3 "戻る")
4. Rui L., Reardon K.F., & Wood T.K. (2005).
   Protein engineering of toluene ortho-monooxygenase of *Burkholderia cepacia* G4 for regiospecific hydroxylation of indole to form various indigoid compounds.
   *Applied Microbiology and Biotechnology*, 66, 422–429.
   <https://doi.org/10.1007/s00253-004-1698-z>
   [↑](#tom-cite4 "戻る")
5. D.A. Carlin, S.J. Bertolani, & J.B. Siegel (2015).
   Biocatalytic conversion of ethylene to ethylene oxide using an engineered toluene monooxygenase.
   *Chemical Communications (ChemComm)*, 51(12), 2283–2285.
   <https://doi.org/10.1039/C4CC08802F>
   [↑](#tom-cite5 "戻る")
6. PaxDb: Protein Abundance Database,
   <https://www.pax-db.org/>
   [↑](#tom-cite6 "戻る")
7. UniProt,
   <https://www.uniprot.org/>
   [↑](#tom-cite7 "戻る")
8. Shimada, H. (1998).
   Mechanism of Oxygen Activation by Cytochrome P450: Diversity and Unity.
   *Kagaku to Seibutsu (Chemistry and Biology)*, 36(7), 465–469.
   <https://doi.org/10.1271/kagakutoseibutsu1962.36.465>
   [↑](#tom-cite8 "戻る")

[Back to Top](#En-top)

{% endblock %}

{% extends "layout.html" %}
{% block title %}Experiments{% endblock %}
{% block top %}Ex-top{% 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 %}
{% block header\_image %}
![Experiments Header](https://static.igem.wiki/teams/5702/img/common/headerimg/head-wet.webp)
{% endblock %}
{% block page\_content %}

* [**Construction**](#Plasmid Construction) ▸

  + [Plasmid Design](#Plasmid Design)
  + [Plasmid and Material Procurement](#Plasmid and Material Procurement)
  + [PCR for cloning](#PCR for cloning)
  + [Gel Preparation](#Gel Preparation)
  + [Electrophoresis](#Electrophoresis)
  + [Gel Extraction](#Gel Extraction)
  + [DNA Assembly](#DNA Assembly)
  + [Transformation into E. coli](#Transformation into E. coli)
  + [Prepare LB Agar Plate](#Prepare LB Agar Plate)
  + [Colony PCR](#Colony PCR)
  + [mini culture](#mini culture)
  + [Mini Prep](#Mini Prep)
  + [Sequencing](#Sequencing)
* [**Expression**](#Protein Expression)▸

  + [pre culture](#pre culture)
  + [main culture](#main culture)
  + [SDS-PAGE](#SDS-PAGE)
  + [Co-transformation](#Co-transformation)
  + [Cre recombination Assay](#Cre recombination in vitro assay)
  + [Affinity Chromatography for NisinQ-NusA Fusion Protein](#Affinity Chromatography for NisinQ-NusA Fusion Protein)

## Plasmid Constuction

Plasmid Design

The plasmids related to this project were constructed using Snap Gene, a software for everyday molecular biology.

Plasmid and Material Procurement

The plasmid parts we designed were manufactured by Twist bioscience and Integrated DNA technology(IDT).

PCR for cloning

PCR for cloning: We amplified the parts (backbone, fragment) required for plasmid construction using PCR. Primers varied depending on what we amped.
![Miyu Makimura](https://static.igem.wiki/teams/5702/img/experiment/pcr.webp)

Prepare Premix as above in PCR tube

- 1.Add MQ to 25μl
- 2.Add optional DNA
- 3.The DNA was amplified using the following thermal cycling conditions:
- [ ・98℃ 30 sec
- ・98℃ 10 sec
- ・66℃ 20 sec
- ・72℃ vary depending on template DNA ] 35 cycle
- 72℃ 2 min
- 4℃ ∞

Gel Preparation

Gels were created for electrophoresis as follows:

1.Dissolve agarose S in 1x TAE buffer at a rate of 1% and heat the mixture until agarose dissolves.

2.Pour the mixture into a conical tube.

3.Add EtBr at a 1:10000 ratio to the gel, and gently mix and tumble ten times to ensure even distribution.

4.Pour the gel into a tray and make it solidify at room temperature.

※ 1x TAE buffer is prepared by diluting 50x TAE buffer which has 2M tris-acetate and 0.05M EDTA. 10 mg/mL EtBr was purchased from Fujifilm.

Electrophoresis

This procedure was conducted to assess the length of DNA fragments which are amplified through techniques such as PCR.

1.Place the gel in the electrophoresis chamber without removing it from the tray.
2.Pour 1x TAE buffer into the chamber until the gel is fully immersed.
3.Add an appropriate size marker to the first lane.
4.Apply the samples (the quantity depends on each reagent) sequentially in the lanes, starting from the second lane.
5.Turn on the chamber and run electrophoresis at 100 V for 20 min.
6.Remove the gel carefully from the tray.
7.Visualize the bands using a trans illuminator.

Use two types of markers depending on the target DNA strand length, and dye the migrated DNA with 6x loading dye.

Gel Extraction

Isolate the desired fragments of undamaged DNA from the agarose gel after gel electrophoresis.

DNA Assembly

**Gibson Assembly** …

This is a technique for assembling DNA seamlessly and in the correct order based on exonucleases.

1.Set up the following reaction on ice:

![Miyu Makimura](https://static.igem.wiki/teams/5702/img/experiment/gibson-assembly.webp)

2.Incubate samples in a thermal cycler at 50℃for 15 minutes when 2 or 3 fragments are being assembled.

Gibson Assembly Master Mix (Q5 High-Fidelity 2X Master Mix) contains dNTPs, Mg++, and a dedicated buffer. Simply add primers and DNA templates to enable robust amplification regardless of GC content

**Goldengate Assembly** …

Goldengate Assembly can be used for directed assembly of multiple inserts/modules and single insert/library generation cloning with single insert(s) using the Golden Gate approach.

1.Set up assembly reactions as follows:

![Miyu Makimura](https://static.igem.wiki/teams/5702/img/experiment/goldengate-assembly.webp)

2.For 2-10 inserts, (37°C, 1 min → 16°C, 1 min) x 30 → 60°C, 5 min

Transformation into E. coli

We introduced the plasmid into E. coli following this protocol. We used two strains of E. coli: **DH5α** (the strain commonly used for routine transformation) and **NEB5α** (the strain recommended by NEB).

- **DH5α**
- 1. Mix 2μl of plasmid and 50μl of E. coli + pipetting or flicking
- 2. Leave the mixture on ice for 10 min
- 3. Place the mixture in a heat block at 42℃ for 45 sec
- 4. Leave it on ice for 2 min
- 5. Drip 50μl of the mixture on an optional plate
- 6. Incubate the plate at 37℃ for 11h~15h
- 7. After checking the colony grows, store at 4℃
- If recovery culture was required (in a case we use Cm as an antibacterial substance), after step 4, we added 950μl of SOC into the mixture. After that, we shake it vigorously at 37℃.
- **NEB5α**
- 1. Thaw a competent E. coli
- 2. Add 2μl of the chilled DNA to the cell mixture
- 3. Pipetting or flicking 4-5 times to mix cells and DNA
- 4. Place it on ice for 30 min
- 5. Place the mixture in a heat block at 42℃ for exactly 30 sec
- 6. Leave it on ice for 2 min
- 7. Mix the cells thoroughly by flicking the tube and inverting
- 8. Drip 50 ~100μl of each dilution on a selection plate
- 9. Incubate the plate at 37℃ for 11h~15h
- 10. After checking the colony grows, store at 4℃
- If recovery culture is required (in a case we use Cm as an antibacterial substance), after step 6, we added 950μl of SOC into the mixture. After that, we shake it vigorously at 37℃.

Prepare LB Agar Plate

We used LB Broth, Miller (The composition of the LB Broth MILLER per liter is 5g yeast extract, 10g peptone from casein, and 10g sodium chloride.)

- 1.A mixture is prepared as follows:
![Miyu Makimura](https://static.igem.wiki/teams/5702/img/experiment/lb.webp)- 2.Heat in the microwave until transparent.
- 3.Once cooled, add optional antibacterial agents and pour onto a plate to solidify.

Colony PCR

- 1. A single, relatively isolated colony was picked using a pipette tip, and the tip was dipped into the liquid which is prepared as follows:
- 2. Dispense 100µL of LB medium (no antibiotics) to 1.5 mL tube. Incubate at 37℃ for 1 h
- Prepare premix and dispense 9.75 µl each into PCR tubes
- Add the template (culture) 1 µL
- The DNA was amplified using the following thermal cycling conditions:
- [・98℃ 30 sec
- ・98℃ 10 sec
- ・66℃ 20 sec
- ・72℃ 1min 52sec ] 35 cycle
- 72℃ 2 min
- 4℃ ∞

mini culture

- 1.Add 3 ml of LB and the optional antimicrobial agent to a 15 ml tube.
- 2. Take a small amount of glycerol stock and suspend it.
- 3.Incubate at 37℃ O/N (12h～)

Mini Prep

We take this process to extract the plasmid, using Fast Gene Plasmid mini kit.

- 1.Harvest of bacteria: c.f.g. 10,000 rpm; 1 min → remove the sup
- 2.Lysis: add 200μL of mp1 → voltexing, add 200μL of mp2: invert the tube → stay 2min at RM, add 300μL of mp3: invert the tube
- 3.Lysate: clarification: c.f.g.13,000 rpm; 2 min
- 4.Sample loading: Load the sup to the column → c.f.g 13,000 rpm; 2 min
- 5.Membrane washing and membrane drying: add 150μL of mp4 and 300μL of mp5 → 13,000 rpm; 3 min
- 6.Elation: 50μL of mp6 → stay 2 min at RM→ 13,000 rpm; 2 min

Sequencing

We conducted sequence analysis using sequencing provided by Azenta Life Science and sequencing provided by Gifu University Institute for Advanced Studies Center for Scientific Research Infrastructure. All functional regions of the plasmid used in this project were subjected to sequence analysis to verify their sequences.

## Protein Expression

pre culture

- 1.Add 3 ml of LB, 60μl of 25% glucose and the optional antimicrobial agent to a 15 ml tube.
- 2.Pick a single isolated colony and dip it into the liquid.
- 3.Shake culture 145rpm, 37℃, O/N

main culture

- 1. Dispense 20ml of LB and add Amp 20μl and glucose 400μL
- 2.Shake it at 37℃ 3h

SDS-PAGE

We conducted this experiment with the assistance of Professor Takashi Yokogawa.

- 1. Prepare the separation gel solution and concentrated gel as follows:
![Miyu Makimura](https://static.igem.wiki/teams/5702/img/experiment/sds-page2.webp)- 2.add 40µl of 40% APS, 5µl of TEMED → pour into the gel plate and layer EtOH
- 3.After the separating gel solidifies → add 20µl of 40% APS, 2.5µl of TEMED to concentrated gel
- 4.pour into the gel plate → insert a comb
- 5.Apply marker and optional samples

Co-transformation

- 1.Dilute each optional plasmid 5-fold with MiliQ
- 2.Mix plasmids- 3.Mix plasmids and E. coli as follows:
    ![Miyu Makimura](https://static.igem.wiki/teams/5702/img/experiment/co-transformation.webp)- → pipetting or flicking- 4.on ice for 5 min- 5.heat shock 42℃ for 30 sec- 6.Add 80μl of room temperature SOC into the mixture.- 7.Place at 37℃ for 60 min → shake vigorously (250rpm) or rotate- 8.plate on LB plate- 9.Incubate at 37℃ for 11h～15h

Cre recombination Assay

- 1.37℃ 10min incubate
- 2.70℃ 10 min heat
![Miyu Makimura](https://static.igem.wiki/teams/5702/img/experiment/creassay.avif)

Affinity Chromatography for NisinQ-NusA Fusion Protein

Reagents:

- ・Cell extract (supernatant suspended in binding/wash buffer)
- ・Binding/Wash buffer: 50 mM potassium phosphate (NaPi) buffer [pH 7.4], 300 mM

NaCl, 20 mM imidazole

- ・Elution buffer: 250 mM and 500 mM imidazole
- ・Ni-NTA agarose

Procedure:

- ↓mAdded 100 mL of RO water to a tube containing 100 mL of resin.
- ↓Resuspended the resin and aliquoted.
- ↓Added 500 µL of cell extract (IPTG-induced and non-induced).
- ↓Kept on ice.
- ↓Gently inverted every 2-3 min for 10 min.
- ↓Transferred the entire mixture to a spin column.
- ↓Centrifuged using a benchtop centrifuge for 2-3 sec.
- ↓Collected the flow-through (Fl).
- ↓Added 0.6 mL of 20 mM His buffer onto the resin in the spin column.
- ↓Mixed gently by slow pipetting.
- ↓Centrifuged for 2-3 sec using a benchtop centrifuge.
- ↓Collected the wash fraction (Wa1).
- ↓Repeated steps 9-12 to obtain the second wash fraction (Wa2).
- ↓Added 200 µL of 250 mM imidazole, kept on ice for 2 min, and pipetted several
  times.
- ↓Centrifuged for 2-3 sec and collected the eluate (El1).
- ↓Added 500 mM imidazole (two additions of 200 µL 250 mM imidazole), kept on ice for 2 min and pipetted several times.
- ↓Centrifuged for 2-3 sec and collected the eluate (El2).
- ↓Confirmed the collected samples by SDS-PAGE.

[Back to Top](#Ex-top)

{% endblock %}

{% extends "layout.html" %}
{% block title %}Results{% endblock %}
{% block top %}Re1-top{% endblock %}
{% block lead %}Describe how and why you chose your iGEM project.{% endblock %}
{% block header\_image %}
![Wet Results Header](https://static.igem.wiki/teams/5702/img/common/headerimg/head-pro.webp)
{% endblock %}
{% block page\_content %}

* [Model1-1. Prediction of unknown-enzyme-expression](#model1-1)
* [Model1-2. Functional evaluation of te TOM complex](#model1-2)
* [Model2. Co-culture Simulation](#model2)
* [Model3. Evaluation of the Antimicrobial Activity of Nisin](#model3)

## Model1-1: Prediction of unknown-enzyme-expression

▼ Show

### 1 Prediction of Tom-expression overview

The biosensor used in this project responds to ethylene oxide but not to ethylene itself. Therefore, it was necessary to introduce an additional enzyme to enable the conversion of ethylene into ethylene oxide. Since the expression level of the enzyme in E. coli was unknown, it was computationally predicted using Python.

### 2 Introduction

In this project, a literature review suggested that specific enzyme modifications could potentially introduce new functional properties. Based on this finding, assuming difficulties in experimental verification, sequence data were constructed from publicly available information, and machine learning was applied to predict their expression characteristics.
.

### 3 The way the datasets were collected

To develop the expression-level prediction program in Python, gene sequences with known expression levels in E. coli were used as training data. These datasets were constructed based on protein expression information and corresponding DNA sequences obtained from public databases.

### 4 Explanation of Python code for expression-prediction

To extract structural and sequence-based information from the input DNA data, computational analysis was conducted to generate feature representations, which were then integrated with expression data for model training. A machine learning regression model was employed to predict expression levels, followed by evaluation using both known and unknown sequences to assess model performance.

### 5 Results of the prediction

For comparison of model performance, simulations were conducted in two stages, using 40 and 95 training samples, respectively. The results are summarized in Tables 1–4. Furthermore, graphs of feature importance and predicted vs. observed values, which served as evaluation indicators of model performance, are presented in Graphs 1–4. From these results, it was suggested that, at both stages of prediction, the target nucleotide sequences could achieve a certain level of protein expression in E. coli.

Table 1 (Machine Learning Data: 40 Samples)

| Gene (Unknown Expression in *E. coli*) | Predicted Expression (ppm) |
| --- | --- |
| TomA0 | 9056.29 |
| TomA1 | 5873.83 |
| TomA2 | 7447.67 |
| TomA3 (V106F) | 7194.09 |
| TomA3 (A113F) | 7194.94 |
| TomA4 | 10205.76 |
| TomA5 | 7149.04 |

**Test MSE:** 13,987,415.769112501

Table 2 (Machine Learning Data: 95 Samples)

| Gene (Unknown Expression in *E. coli*) | Predicted Expression (ppm) |
| --- | --- |
| TomA0 | 3988.56 |
| TomA1 | 2793.93 |
| TomA2 | 3686.44 |
| TomA3 (V106F) | 2486.01 |
| TomA3 (A113F) | 2487.43 |
| TomA4 | 3965.34 |
| TomA5 | 2437.71 |

**Test MSE:** 2,875,357.8509500003

Table 3 (Machine Learning Data: 40 Samples)

| Gene (Known Expression in *E. coli*) | Observed Expression (ppm) | Predicted Expression (ppm) |
| --- | --- | --- |
| rplF | 4110 | 5201.77 |
| rpsP | 4070 | 5991.55 |

**Test MSE:** 13,987,415.769112501

Table 4 (Machine Learning Data: 95 Samples)

| Gene (Known Expression in *E. coli*) | Observed Expression (ppm) | Predicted Expression (ppm) |
| --- | --- | --- |
| rplF | 4110 | 3354.16 |
| rpsP | 4070 | 4071.46 |

**Test MSE:** 2,875,357.8509500003

#### Graph 1: Feature importance (40-sample dataset)

Graph 1: Bar graph of feature importance

![Project figure](https://static.igem.wiki/teams/5702/img/dry/project1/project-17.webp)

## Model1-2: Functional evaluation of te TOM complex

▼ Show

From the results of section 1-1, it was confirmed that the TOM mutants A113F and V106F were expressed in E. coli. Based on these results, the concentration changes of the substrates C₂H₄ (ethylene) and C₂H₄O (ethylene oxide), which are involved in the enzyme reaction of TOM, were plotted as graphs to evaluate their functionality.

The equations used for the simulation and the list of parameters that compose those equations are shown below.

Table Parameters Used in the Enzyme Kinetic Model

| Parameter | Description |
| --- | --- |
| $$V\_{max}$$ | Maximum velocity of the reaction (mM/min) |
| $$K\_{ia}$$ | Constant for NADH (mM) |
| $$K\_b$$ | Constant for O2 (mM) |
| $$K\_c$$ | Constant for C2H4 (mM) |
| $$K\_{bc}$$ | Cross-term of O2 and C2H4 (mM) |
| $$V\_{\max}^{\ast}$$ | Maximum velocity in the approximated first-order reaction equation (mM/min) |
| $$K\_{m}^{\ast}$$ | Reaction rate constant in the approximated first-order reaction equation |

equation
$$
\frac{d[\mathrm{C\_2H\_4O}]}{dt}
= v([C])
= \frac{V\_{\max}^\ast [C]}{K\_m^\ast + [C]}
\
$$

For a detailed explanation, please refer to the page of “mode1” conducted by the Dry team.

Graph1. Changes in the concentrations of C₂H₄ and C₂H₄O when A113F was expressed.

![Project figure](https://static.igem.wiki/teams/5702/img/dry/project1/project1-14.webp)

The data used for plotting Graph 1 are shown in the following table.

Table 8. Parameters Used for A113F Mutation

| Parameter | Initial value |
| --- | --- |
| \( V\_{\max}^{\ast} \) | 0.019 (mM/min) |
| \( K\_{m}^{\ast} \) | 0.5 (mM) |
| \( [\mathrm{C\_2H\_4}] \) | 0.7 (mM) |
| \( [\mathrm{C\_2H\_4O}] \) | 0.0 (mM) |

Graph2. Changes in the concentrations of C₂H₄ and C₂H₄O when V106F was expressed.

![Project figure](https://static.igem.wiki/teams/5702/img/dry/project1/project1-15.webp)

The data used for plotting Graph 2 are shown in the following table.

Table 9. Parameters Used for V106F Mutation

| Parameter | Initial value |
| --- | --- |
| \( V\_{\max}^{\ast} \) | 0.0007 (mM/min) |
| \( K\_{m}^{\ast} \) | 0.5 (mM) |
| \( [\mathrm{C\_2H\_4}] \) | 0.7 (mM) |
| \( [\mathrm{C\_2H\_4O}] \) | 0.0 (mM) |

From these two results, it can be observed that the graph of A113F follows the curve based on the first-order enzyme reaction equation, while that of V106F shows a linear pattern. We assumed that this is due to the reaction rate of V106F being much slower than that of A113F, and therefore extended the reaction time only for V106F to 10,000 minutes and replotted the graph. The result of this replotting is shown in Graph3 below.

Graph3. Changes in the concentrations of C₂H₄ and C₂H₄O when V106F was expressed (reaction time extended to 10,000 minutes).

![Project figure](https://static.igem.wiki/teams/5702/img/dry/project1/project1-16.webp)

From Graph 3, it can be seen that the reaction graph of V106F also follows the curve based on the first-order enzyme reaction equation when the simulation time is extended. Considering the total time required for the enzyme reaction to complete, it is suggested that introducing the gene expressing A113F into E. coli would be more appropriate for carrying out the project.

Ethylene can be oxidized to ethylene oxide using an engineered toluene monooxygenase
The mechanism of oxygen activation by P450 enzymes also provides useful insights

---

## Model2: Co-culture Simulation

▼ Show

In the dry simulation of the Tom monooxygenase system, the main Monod parameters were first estimated from single-culture data, yielding a maximum specific growth rate of　\(\mu\_{max} = 0.795\,\mathrm{h^{-1}}\), a half-saturation constant of \(K\_S = 0.0404\,\mathrm{g\,L^{-1}}\) and a biomass yield of \(Y\_{X/S} = 1.72\times10^9\,\mathrm{cells\,mL^{-1}(g\,L^{-1})^{-1}}\).
Based on these parameters, a co-culture model of the monooxygenase-expressing strain and the sensor strain was constructed to analyze the time evolution of ethylene oxide concentration and sensor output \(y′\) following ethylene addition.

For initial condition optimization, the substrate concentration was varied within \(S\_0 = 0.5\text{–}10.0\,\mathrm{g\,L^{-1}}\), and the initial cell densities of the producer (\(X\_{0,1}\)) and sensor strain (\(X\_{0,2}\)) were explored within \(8.0\times10^8\text{–}1.6\times10^{10}\,\mathrm{cells\,mL^{-1}}\).
Bayesian optimization was performed with the maximum \(y′\) value as the objective function. The results indicated that \(y′\) was maximized when the sensor strain had a slightly higher density than the producer strain (approximately a 2:1 ratio) and when the substrate concentration was moderate (\(S\_0 \approx 4.0\,\mathrm{g\,L^{-1}}\)).

Furthermore, increasing the Tom-producing strain density accelerated ethylene oxide production but caused stronger growth inhibition in the sensor strain, delaying the response peak. Conversely, when the producer strain density was lower, the production rate decreased and the sensor output weakened, though the system exhibited more stable behavior.

These findings demonstrated that the ratio between the two strains governs both the amplitude and timing of the sensor response.

This analysis quantitatively showed that tuning the balance of cell ratios enables control over the response strength, providing a rational design guideline for optimizing ethylene-detecting biosensors.

![Project figure](https://static.igem.wiki/teams/5702/img/dry/project2/project2-17.webp)

## Model3: Evaluation of the Antimicrobial Activity of Nisin

▼ Show

We evaluated nisin’s antimicrobial performance under varying concentration, pH, and temperature conditions using a multivariate model fitted by least-squares minimization. The analysis identified the optimal conditions for nisin’s activity within our biosensor framework.

Results show that nisin is most potent in acidic environments (around pH 5), performs better under refrigeration (~7 °C), and requires relatively high concentrations (\(10^2–10^3\) µg/mL) for strong bacterial inactivation. These findings suggest that nisin-based biosensors are well-suited for protecting acidic fruits during cold storage, offering practical guidance for reducing foodborne risks such as Listeria monocytogenes contamination.

![Project figure](https://static.igem.wiki/teams/5702/img/dry/project3/pred-timekill.webp)
![Project figure](https://static.igem.wiki/teams/5702/img/dry/project3/fig3-pred-timekill-by-ph.webp)
![Project figure](https://static.igem.wiki/teams/5702/img/dry/project3/fig4-pred-timekill-by-t.webp)

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