iGEM 2023 — Team gifu

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

---

* Chronological notes of what your team is doing.
* Brief descriptions of daily important events.
* Pictures of your progress.
* Mention who participated in what task.

## Inspirations

---

* [2018 Munich](http://2018.igem.org/Team%3AMunich/Notebook)
* [2019 Georgia State](https://2019.igem.org/Team%3AGeorgia_State/Notebook)
* [2019 Newcastle](https://2019.igem.org/Team%3ANewcastle/Notebook)
* [2020 IISER Pune India](https://2020.igem.org/Team%3AIISER-Pune-India/Notebook)
* [2020 Lund](https://2020.igem.org/Team%3ALund/Notebook)
* [2020 NOVA LxPortugal](https://2020.igem.org/Team%3ANOVA_LxPortugal/Notebook)
* [2020 RDFZ China](https://2020.igem.org/Team%3ARDFZ-China/NoteBook)

{% endblock %}

# Engineering

## **Introduction**

Our goal in this project is to establish a strategy to respond to a pandemic caused by drug-resistant bacteria. To achieve this goal, we focused on gRNA construction by using a tool called CRISPR Multi Targeter. In engineering, we have summarized our activities from project planning to the achievement of our goals in four cycles.

## Cycle1: Project Planning

## **Design**

Today, antibiotics are used as a countermeasure against drug-resistant bacteria, but the production of one mutant after another in response to these drugs has become a problem. Therefore, we considered the development of phage drugs with Cas9 to approach the problem at the gene level. The use of phage drugs can prevent horizontal transmission of drug resistance genes at the same time that they lyse.

## **Build**

It was unclear whether the development of phage drugs was feasible in Japan, so we decided to hear professional stories from people working in phage medicine. In addition, we interviewed physician's familiar with infectious diseases to better understand the reality of the drug-resistant bacteria problem.

## **Test**

To resolve this issue, we interviewed experts.

[Here is the link for human practice](https://2023.igem.wiki/gifu/human-practices)

As a result, we learned the following.

The emergence of antibiotic resistant bacteria and the development of antibiotics is a constant battle.

The use of antibiotics causes the growth of antibiotic resistant bacteria species and mutants. Therefore, we learned that we need means that can respond immediately to mutants.

## **Learn**

From this interview, we have found that phage therapy is not an appropriate response to antibiotic resistant bacteria. Thus, we decided to aim for a means to respond immediately to new mutants.

## Cycle2: Application of CRISPR Multi Targeter ~Development of PAM ConAligner~

## **Design**

Through Cycle1, we have learned that we should develop tools to deal with a wide range of mutants and quickly. In the search for new ways to use Cas9, we discovered a tool called CRISPR Multi Targeter, which is possible to find common arrays from multiple arrays. Therefore, we attempted to design gRNAs that recognize multiple genes by using this tool.

## **Build**

Multi Targeter only works if all input sequences have a common sequence. In other words, when you input 7 sequences, what Multi Targeter checks is whether all 7 sequences have a common sequence or not. For example, even if it is possible to design a gRNA that can cut 5 out of 7 gRNAs, the Multi Targeter will not output the gRNA sequence.So, we developed a new software that solves these problem.(See Figure2-1 in Solution)

## **Test**

We have evolved the Multi Targeter that recognizes sequences common to all sequences and presents gRNA, developed a software called PAM ConAligner. This software can design gRNAs that cut some common sequences from the whole sequences.

![Figure2-1. Differences between Multi Targeter and PAM ConAligner ](https://static.igem.wiki/teams/4715/wiki/wet-engineering/engineering-cycle2.png)

Figure2-1. Differences between Multi Targeter and PAM ConAligner

![Figure2-2. testing with PAM ConAligner ](https://static.igem.wiki/teams/4715/wiki/wet-engineering/testing-with-pamcon.png)

Figure2-2. testing with PAM ConAligner

[Here is the link for PAM ConAligner test](https://static.igem.wiki/teams/4715/wiki/wet-engineering/pam-conaligner.pdf)

## **Learn**

When you want to know the gRNA that can cleave some sequences from the input sequence, Multi Targeter is too inefficient as it can only design gRNAs when all input sequeces have a common sequence.

However, the development of PAM ConAligner has made it possible to efficiently design gRNAs in such cases. This software is expected to make it easier and faster to design effective gRNAs for a wide range of mutants.

## Cycle3: Application of CRISPR Multi Targeter ~Considering whether sequences are evolutionarily conserved~

## **Design**

In Cycle 2, we developed PAM ConAligner. Next, we designed gRNA by using PAM ConAligner to connect this software to social implementation.

## **Build**

In the initial version of PAM ConAligner, we tried to construct a phylogenetic tree using aligned sequences and assess the evolutionary conservation of the sequences utilized for gRNA design.
In general, creating a gRNA by searching for a common sequence across multiple sequences in the same genus means identifying an evolutionarily conserved region within the genus.
However, we wanted to clarify that reveal evolutionarily conserved regions and select the best gRNAs by another method as well.

## **Test**

Thus we introduced the Distance Matrix to reveal that it is more evolutionarily conserved. We focused on the evolutionary distance, which is calculated by the Unweighted Pair Group Method using arithmetic Average; (UPGMA). By using this as an indicator, we measured whether a group of sequences recognized by the gRNAs were derived from a common sequence.

![Figure3-1. Differences between Multi Targeter and PAM ConAligner ](https://static.igem.wiki/teams/4715/wiki/software/12.png)

Figure3-1. distance matrix

distance matrix is a measure of sequence differences.
It is an array of evolved distances that correspond to sequence pairs as shown in Figure 3-1.
The calculation was done using Build gather\_subs\_local\_homology\_module.py.

![Figure3-2. Compare average of distance matrix](https://static.igem.wiki/teams/4715/wiki/software/distance-matrix.png)

Figure3-2. Compare average of distance matrix

## **Learn**

When you want to know the gRNA that can cleave some sequences from the input sequence, Multi Targeter is too inefficient as it can only design gRNAs when all input sequences have a common sequence.
However, the development of PAM ConAligner has made it possible to efficiently design gRNAs in such cases. In addition, PAM ConAligner can reveal evolutionarily conserved regions by two means, providing a more suitable gRNA design.
This software is expected to make it easier and faster to design effective gRNAs for a wide range of mutants.

## Cycle4: Building a system that makes effective use of Multi Targeter

## **Design**

To make the use of Multi Targeter closer to social implementation, we attempted to construct a system for actual use of gRNAs designed in Cycle 2.

## **Build**

If one Cas9 plasmid is designed with the gRNA corresponding to the mutation, Cas9 must be redesigned each time the gRNA sequence changes. This method takes a long time to respond to mutations. Therefore, we designed the compatible Cas9 plasmid to allow easy introduction of various gRNAs.

## **Test**

First, we designed a Cas9 plasmid that can easily insert various gRNA. In this plasmid, nine DNA fragments were introduced by Gibson Assembly into the backbone Cas9 plasmid. In addition, all DNA fragments and backbone Cas9 plasmid were prepared from plasmids from the iGEM Kit plate. \*Figure4-1
Next, gRNA was introduced by Golden Gate assembly using Bbs1 and T4 ligase. \*Figure4-2

![grna-is-introduced](https://static.igem.wiki/teams/4715/wiki/wet-engineering/figure4.png)

[Here is the link for experiments](https://2023.igem.wiki/gifu/experiment)

## **Learn**

This trial allowed us to build systems for effective utilization of gRNA designed with the Multi Targeter. A series of systems were constructed by creating compatible Cas9 plasmids, determining model genes, designing gRNAs, enzymatic processing, and completing Cas9 with gRNA.

![grna-is-introduced](https://static.igem.wiki/teams/4715/wiki/wet-engineering/engineering-success.png)

Figure4-3. Engineering success

## Future work

To establish a more plausible system, we need to confirm the expression and activity of the Cas9 protein in the gRNACasPlasmid that we constructed in addition to our test. For this purpose, we will perform tests to confirm whether the AmpR fragment can be cleaved in vitro, and trials to confirm protein expression by SDS-PAGE. Once it is confirmed that the Cas9 plasmid constructed by these trials is normally expressed and works normally, we will confirm the action of the Cas9 plasmid in vivo. We believe that this trial can proceed with the following trials.

Using BBa\_J435300 and the Cas9 plasmid, we perform a transformation. We culture the Escherichia coli in media with IPTG added and media without IPTG added, comparing the colony numbers. (Both media were supplemented with Amp and Cm.) If Cas9 is functioning properly, it can be expected that the colony count in the medium with IPTG added will be less than in the medium without IPTG added. Therefore, if the colony count in the IPTG-added medium decreases compared to the colony count in the medium without IPTG, it can be concluded that the Cas9 has effectively cleaved the AmpR gene (drug resistance gene) in E. coli, and the experiment is successful.

Subsequently, we conducted additional experiments to verify the impact of Cas protein expression on colony formation. We compared the colony numbers of those where Cas protein acting on BBa\_J435300 was expressed and those where Cas protein not acting was expressed. The Cas used in the previous experiment is the same as the one used. The non-acting Cas uses a plasmid with the mCherry region unchanged.
We performed a transformation using each Cas plasmid and BBa\_J435300, and cultured them in media supplemented with Amp, Cm, and IPTG. This allows Cas protein to be expressed under both conditions. If Cas protein expression does not affect colony formation, it can be expected that colonies will form equally in both media. Therefore, if the number of colonies in the medium with the Cas protein acting on BBa\_J435300 decreases compared to the medium with the non-acting Cas protein, it can be concluded that Cas protein expression does not impact colony formation, and the reduction in colony count is due to the action of Cas.

{% extends "layout.html" %}
{% block title %}Team{% endblock %}
{% block lead %}On this page you can introduce your team project.{% endblock %}
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#

##

![](https://2021.igem.org/wiki/images/f/f4/T--Gifu--home1.png)

## We all live with **fatigue**.

Fatigue cannot be judged visually, and it may not be recognized correctly by others or even by ourselves...

## Thus, many people tend to neglect the excessive fatigue that can cause **depression** and other problems

![](https://2021.igem.org/wiki/images/7/76/T--Gifu--home2.png)

![](https://2021.igem.org/wiki/images/a/a4/T--Gifu--Home3.png)

## **Quantifying fatigue** and expressing it as an objective indicator can be the first step to a deeper understanding of ourselves.

[![Project](https://2021.igem.org/wiki/images/c/c7/T--Gifu--home-project.png)](https://2021.igem.org/Team%3AGifu/Description)

[![Result](https://2021.igem.org/wiki/images/f/f5/T--Gifu--home-result.png)](https://2021.igem.org/Team%3AGifu/Result)

[![Human Practices](https://2021.igem.org/wiki/images/a/a1/T--Gifu--home-humanpractice.png)](https://2021.igem.org/Team%3AGifu/Human_Practices)

[![Parts](https://2021.igem.org/wiki/images/6/66/T--Gifu--home-parts.png)](https://2021.igem.org/Team%3AGifu/Parts)

{% endblock %}

# Result

## Plasmid construction and transfection

We conduct experiments to building a system using gRNA designed by PAMConAligner.
As a model for antibiotic-resistant bacteria, we use a plasmid carrying the AmpR gene. This time, we selected and used BBa\_J435300 from the iGEM 2023 kit plate. We determined the gRNA sequence targeting the AmpR gene in BBa\_J43530 at PAMConAligner and constructed the gRNA.We also construct a Cas9 plasmid with a gRNA transfected part. This part can be cut with restriction enzyme Bbs I. First, we constructed a Cas9 plasmid with mCherry inserted in this part. This Cas9 plasmid has CmR and it is designed to be expressed only in the presence of IPTG.
（From here, we will refer to the plasmid with mCherry inserted as 'mCherryCas Plasmid' and the plasmid with gRNA inserted as 'gRNACas Plasmid'.）

We introduced gRNA targeting BBa\_J435300 into the mCherry part of the constructed Cas9 plasmid by Golden Gate assembly, and we constructed a functional Cas9 plasmid. We performed transformation with the assembly product to obtain E. coli that had acquired the gRNACas plasmid. However, most of the red colonies expressed mCherry. From this, we considered that the efficiency of gRNA introduction into the Cas plasmid was low and that the mCherryCas plasmid remained unchanged. Therefore, we increased the amount of gRNA used in the Golden Gate method and extended the time for digestion and ligation. As a result, the percentage of mCherry-expressing colonies decreased more than before. From this plate, white E. coli colonies that had acquired the gRNA Cas plasmid were selected to create a competent cell with the gRNACas plasmid. The CaCl2 method was used to create this competent cell. Transformation of BBa\_J435300 was performed in this competent cell by the heat shock method and cultured on plates supplemented with Amp, Cm, and IPTG. As a result, colonies could be confirmed, and E. coli that acquired both gRNACas plasmid and BBa\_J435300 plasmid were obtained.

![](https://static.igem.wiki/teams/4715/wiki/result/result-plasmids.png)

Figure1. general view of result