iGEM 2021 — Team Tongji_Software

[![](https://static.igem.org/mediawiki/2021/8/8b/HQ_page_logo.jpg)](https://2021.igem.org)

# Team:Tongji Software/Notebook

[

](https://static.igem.org/mediawiki/2021/b/b7/T--Tongji_Software--Rocket-hover.mp4)
[

](https://static.igem.org/mediawiki/2021/e/e1/T--Tongji_Software--Rocket-click.mp4)

![](https://static.igem.org/mediawiki/2021/3/3a/T--Tongji_Software--zyp_logo.svg)

* [Home](https://2021.igem.org/Team%3ATongji_Software)
* [Medal](https://2021.igem.org/Team%3ATongji_Software/Medal)
* [Human Practices](https://2021.igem.org/Team%3ATongji_Software/Human_Practices)
* [Communication](https://2021.igem.org/Team%3ATongji_Software/Communication)

Our Project

[Description](https://2021.igem.org/Team%3ATongji_Software/Description)

[Design](https://2021.igem.org/Team%3ATongji_Software/Design)

[Model](https://2021.igem.org/Team%3ATongji_Software/Model)

[Engineering](https://2021.igem.org/Team%3ATongji_Software/Engineering)

[Implementation](https://2021.igem.org/Team%3ATongji_Software/Implementation)

[Proof of Concept](https://2021.igem.org/Team%3ATongji_Software/Proof_Of_Concept)

[Contribution](https://2021.igem.org/Team%3ATongji_Software/Contribution)

Team

[Member](https://2021.igem.org/Team%3ATongji_Software/Member)

[Attributions](https://2021.igem.org/Team%3ATongji_Software/Attributions)

[Collaborations](https://2021.igem.org/Team%3ATongji_Software/Collaborations)

[Partnership](https://2021.igem.org/Team%3ATongji_Software/Partnership)

[Notebook](https://2021.igem.org/Team%3ATongji_Software/Notebook)

[Safety](https://2021.igem.org/Team%3ATongji_Software/Safety)

![](https://static.igem.org/mediawiki/2021/c/ca/T--Tongji_Software--Slide1.png)
![](https://static.igem.org/mediawiki/2021/d/dd/T--Tongji_Software--Slide2.png)
![](https://static.igem.org/mediawiki/2021/7/78/T--Tongji_Software--Slide3.png)

* 2020.12
* 2021.1-4
* 2021.5
* 2021.6
* 2021.7
* 2021.8
* 2021.9
* 2021.10

# NOTEBOOK

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This page demonstrates notebook of our team activitied.

## ★2020.12

(1) Set up our team, Tongji\_Software 2021

## ★2021.1-4

(1) Investigate former projects of software track to learn background and related inspirations

(2) Learn knowledge about synthetic biology

(3) Literature research

(4) Communicate with Prof.Liu for the first time

(5) Register team

(6) Get in touch with SJTU-Software

## ★2021.5

(1) Determine our research direction of phagotherapy

(2) Recruit new team members for 2 times

(3) Phage & Superbug related literature research

(4) Team leader communication between Tongji\_Software and SJTU-Software

(5) Give out questionnaire and receive results

## ★2021.6

(1) Design team logo

(2) Make preparation for Mini Game and Presentation Video

(3) Do research for CRISPR/Cas++ database

(4) Communicate with SJTU-Software

(5)Get in touch with XJTLU-China

## ★2021.7

(1) Complete presentation video

(2) Collect raw data, design preliminary project process and get basic result

(3) Construct the basic database framework

(4) Online meeting with XJTLU-China for 2 times

(5) Communicate with SJTU-Software

(6) Attend 4th Summit Forum on superbacterial infection and Phage

(7) Attend Seeding Program

## ★2021.8

(1) Complete popular science webpage

(2) Get help from SJTU-Software

(3) Exchange idea with Prof. Du and Prof. Guo

(4) Communicate with clinical workers

(5) Modify project design for 3 times, improve our pipeline and validate our result

(6) Attend CCiC

(7) Confirm three modules: Bacteriophage Bay (database), Phage Finder and Interactive MAP

(8) Prepare for database website Phage-MAP

(9) Complete Mini Game

(10) Introduce Game to public in our university to inspire their interests of synthetic biology

## ★2021.9

(1) Complete database construction

(2) Accomplish webpage's front-end and back-end configuration

(3) Attend CRISPR Conference

(4) Conduct propaganda of our project and iGEM to Innovation Club of the Academy of Life Science and Technology, Tongji University

(5) Begin Wiki construction

## ★2021.10

(1) Get validation from XJTLU-China's experiment results

(2) Visit and communicate with Delonix Bioworks

(3) Prepare for Giant Jamboree

Contacts
If you have any question, please contact us.

---

[![](https://static.igem.org/mediawiki/2021/8/8b/HQ_page_logo.jpg)](https://2021.igem.org)

# Team:Tongji Software/Engineering

[

](https://static.igem.org/mediawiki/2021/b/b7/T--Tongji_Software--Rocket-hover.mp4)
[

](https://static.igem.org/mediawiki/2021/e/e1/T--Tongji_Software--Rocket-click.mp4)

![](https://static.igem.org/mediawiki/2021/3/3a/T--Tongji_Software--zyp_logo.svg)

* [Home](https://2021.igem.org/Team%3ATongji_Software)
* [Medal](https://2021.igem.org/Team%3ATongji_Software/Medal)
* [Human Practices](https://2021.igem.org/Team%3ATongji_Software/Human_Practices)
* [Communication](https://2021.igem.org/Team%3ATongji_Software/Communication)

Our Project

[Description](https://2021.igem.org/Team%3ATongji_Software/Description)

[Design](https://2021.igem.org/Team%3ATongji_Software/Design)

[Model](https://2021.igem.org/Team%3ATongji_Software/Model)

[Engineering](https://2021.igem.org/Team%3ATongji_Software/Engineering)

[Implementation](https://2021.igem.org/Team%3ATongji_Software/Implementation)

[Proof of Concept](https://2021.igem.org/Team%3ATongji_Software/Proof_Of_Concept)

[Contribution](https://2021.igem.org/Team%3ATongji_Software/Contribution)

Team

[Member](https://2021.igem.org/Team%3ATongji_Software/Member)

[Attributions](https://2021.igem.org/Team%3ATongji_Software/Attributions)

[Collaborations](https://2021.igem.org/Team%3ATongji_Software/Collaborations)

[Partnership](https://2021.igem.org/Team%3ATongji_Software/Partnership)

[Notebook](https://2021.igem.org/Team%3ATongji_Software/Notebook)

[Safety](https://2021.igem.org/Team%3ATongji_Software/Safety)

![](https://static.igem.org/mediawiki/2021/c/ca/T--Tongji_Software--Slide1.png)
![](https://static.igem.org/mediawiki/2021/d/dd/T--Tongji_Software--Slide2.png)
![](https://static.igem.org/mediawiki/2021/7/78/T--Tongji_Software--Slide3.png)

* Born
* Preliminary Design
* Build
* Grow
* Complete Design
* Test and Validation
* Improvement

# ENGINEERING SUCCESS

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This year, we achieved engineering success by following the engineering design cycle: Born → Design → Build → Test → Learn → Design...

## ★Born

Drug-resistant bacteria are becoming a worldwide problem. In the early stage of our project, we saw phage therapy emerging as a promising new treatment for superbugs. At the same time, we found that **how to select the specific phage/phages is a challenge**, and scientists often spend a lot of time finding it from the vast amount of literature and to conduct preliminary experiments. Compared with wet experiments, computational methods of identifying phage-bacteria interactions are much more efficient, saving time with lower cost meanwhile. By [**human practices**](https://2021.igem.org/Team%3ATongji_Software/Human_Practices), we think this is a meaningful research direction. So, we started.

## ★Preliminary Design

In the preliminary stage, we chosed CRISPR system as the basis for the design of the project. **CRISPR** (Clustered Regularly Interspaced Short Palindromic Repeats) is the immune system of bacteria. When phages invade, bacteria will intercept the phage genome fragment and insert it into their own genome. We call this fragment **Spacer**. Numerous spacers and directed repeat(DR) sequences are arranged at regular intervals, making up a CRISPR array. The purpose of the bacteria to use CRISPR is to form an immune memory of the phage so that they can react quickly and fight against the next phage's invasion.

![](https://static.igem.org/mediawiki/2021/6/65/T--Tongji_Software--crispr-demo.png)

#### Figure: the CRISPR immune system of bacteria

So, based on the principle of the CRISPR system, we designed our basic analysis method. First, find spacers in genome of bacteria; Then, aligned spacers to the genome of phages; Finally, the intensity of interaction between the phages and the bacteria was calculated by the number and score of alignment result.

## ★Build

Our initial details of build as follows:

① Use the CRISPRDetect tool to obtain the spacer sequence with high probability in bacteria;

② Align the analyzed short spacer sequence to the phage genome through the BLAST tool;

③ Analyze and integrate BLAST scoring that reach a certain e-value threshold into a 2D table;

④ Perform normalization analysis on the corresponding bit-score to get a score Scorespacer\_Blast.

Through dataset verification, we found that the results obtained from the preliminary design are not satisfactory. No matter how small we adjust the threshold, the detection rate is still so low that we had to improve it.

## ★Grow

Later, by communicating with [**SJTU-Software**](https://2021.igem.org/Team%3ATongji_Software/Partnership#SJTU-Software), we further improved our analysis methods. Based on the sequence alignment-based analysis in the early stage, we added alignment-free methods to analyze sequence relation from other perspectives, such as k-mer frequency and Markov model. By using these models, we can get Scorekmer\_freq and ScoreMarkov. More detail can be found in [**Model**](https://2021.igem.org/Team%3ATongji_Software/Model).

Finally, we can get the three characteristic scores, **Scorespacer\_Blast, Scorekmer\_freq and ScoreMarkov**. Then, we applied the TOPSIS method to obtain a composite index **Score**, so as to comprehensively evaluate phagotherapy treatment, and then visualize them in [**our webpage**](http://tjigem2021.com/).

## ★Complete Design

In addition, We also did some extra processing on the superbug dataset.

By communication with Prof. Guo, we noticed existence of lysogenic phages in nature. Considering the universality of this phenomenon and its destabilizing effect on our prediction results, we decided to take this mechanism into consideration. By using the prediction software PHASTER based on the BLAST and DBSCAN algorithms, we selected prophage-bacteria pairs, in which *phage* consist with high-score prophage in *bacteria*, and directly deleted them form superbug-phages dataset.

In real life, for severe bacterial infections, medical professionals will use several specific bacteriophages to attack and kill virus bacteria. This method of using multiple phage reagents to treat diseases is called phage cocktail therapy, which is also the most common form of phage therapy. In this project, we also took this into consideration on the advice of the doctor at Dongfang' Hospital. According to genome similarity, we clustered the remaining phages in superbug dataset and obtained different phage clusters. In this way, users can choose phages from different clusters to make up a "specific phages cocktail".

## ★Test and Validation

**One thing the software team must do is constantly validate the results of the software and improve it based on the results.** The test result of our preliminary design didn't turn out well, we then improved our model based on these failures, and the test result of our complete design finally pleased us. The more details as follows. Click [**Proof\_of\_Concept**](https://2021.igem.org/Team%3ATongji_Software/Proof_Of_Concept#Test%20and%20Validation) to learn more details about validation.

![](https://static.igem.org/mediawiki/2021/5/51/T--Tongji_Software--test-and-validation.png)

#### Fig: Summary diagram of the test and validation section

In a word, we verified the excellent performance of Phage-MAP from 3 aspects: dataset validation, literature validation and wet-experiment validation. Based on these evidence, we could defintely confirm out Phage-MAP is a reliable tool to find accurate interaction between phages and bacteria to assist phagotherapy.

## ★Improvement

In addition, through the project discussion and literature research, we also put forward some further improvement schemes for some existing shortcomings. And they can be applied to the update of Phage-MAP.

The first one is about the further expansion and improvement of characteristic scores. We can further investigate various analysis tools, summarize and integrate their analysis models with performance results. Then we could adopt more effective models (such as convolutional neural networks) and develop new tools to analysis correlations between bacteria and phages.

The other one is the improvement of multi-score evaluation method. We can further apply other evaluation models, such as gray evaluation models. Also, if we can obtain more characteristic analysis scores in the future, we can apply feature engineering analysis to them by means of machine learning methods, so as to construct and tune a neural network to achieve a better comprehensive evaluation result.

### Reference:

[1] Alkhnbashi OS, Meier T, Mitrofanov A, Backofen R, Voß B. CRISPR-Cas bioinformatics. Methods. 2020 Feb 1;172:3-11. doi: 10.1016/j.ymeth.2019.07.013. Epub 2019 Jul 19. PMID: 31326596.

[2] Tan X, Chen H, Zhang M, Zhao Y, Jiang Y, Liu X, Huang W, Ma Y. Clinical Experience of Personalized Phage Therapy Against Carbapenem-Resistant Acinetobacter baumannii Lung Infection in a Patient With Chronic Obstructive Pulmonary Disease. Front Cell Infect Microbiol. 2021 Feb 26;11:631585. doi: 10.3389/fcimb.2021.631585. PMID: 33718279; PMCID: PMC7952606.

Contacts
If you have any question, please contact us.

---

[![](https://static.igem.org/mediawiki/2021/8/8b/HQ_page_logo.jpg)](https://2021.igem.org)

# Team:Tongji Software/Experiments

Template loop detected: [Template:Tongji Software](/Template%3ATongji_Software "Template:Tongji Software")

# Experiments

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

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

### What should this page contain?

* Protocols
* Experiments

### Inspiration

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

[![](https://static.igem.org/mediawiki/2021/8/8b/HQ_page_logo.jpg)](https://2021.igem.org)

# Team:Tongji Software/Results

Template loop detected: [Template:Tongji Software](/Template%3ATongji_Software "Template:Tongji Software")

# Results

You can describe the results of your project and your future plans here.

### What should this page contain?

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

### Describe what your results mean

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

### Project Achievements

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

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

### Inspiration

See how other teams presented their results.

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