Team:CSU CHINA/Collaborations

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• CPU
• SYSU
• NUDT
• UESTC
• UESTC-Software

CPU_CHINA & Nanjing_NFLS

We received the hTERT promoter!

In early period of our project, we considered to find a promoter with different promoting efficiency between normal cells and breast cancer cells to mediate the apoptosis of breast cancer cells. Thanks to CPU-CHINA, a team we communicated with during the last year CCiC meeting, we manage to find one qualified promoter-hTERT-from their program last year.

However, as the chart above shows, the difference in expression of this promoter is not as efficient as we need, leading to a possibility that our loop may kill normal cells by accident. In order to reduce this side effects, we decided to use other synthetic promoter and to add binding site technic in our loop.

This precious collaboration with CPU-CHINA allow us to reconsider the safety of our gene therapy loop and give us a chance to raise the question of how to find a better to deduce the side affect-killing normal cells, which promotes the targeting ability of breast cancer cells.

SYSU-CHINA

Abstract

This summer, we are working with team SYSU-CHINA to create a mixed antagonistic/synergistic miRNA repression model which enables accurate predictions of multi-input miRNA sensor activity. The communication between us begins in CCiC this year. Since the subjects of both two teams are equally interested in the treatment of cancer, it is helpful for us to exchange our design opinions and methods of our program indeed. They introduce to us the mixed antagonistic/synergistic miRNA repression model[1] which help us come up to the idea of using binding sites in our loop.

Attributions

What we have done:

√ Construction of the LsBr5&3-miR-target plasmid using the Golden Gate method.

√ Detect the efficiency of miR-target by flow cytometry.(19.10.21 finished!)

What SYSU_CHINA have done:

√ Provide the LsBr5&3 vector.

√ Analyse the results of flow cytometry.

Collaboration pattern

Working on literature

SYSU-Figure1:The literature we refer to.

supplementary information

Reference

This article find that miRNA target site sets within the same untranslated region exhibit combined miRNA activity described by an antagonistic relationship while those in separate untranslated regions show synergy. The resulting antagonistic/synergistic computational model enables the high-fidelity prediction of miRNA sensor activity for sensors containing many miRNA targets.

So we explore the detailed method of detecting the efficiency of miR-BS, which shows that four targets in the structure has the most expected results. [1] (SYSU-Figure2)

Finding common switch-miR

In our project, we designed a miRNA-BS as a part of AND-Gate making the system more specific in triple negative breast cancer than normal cells, while SYSU_CHINA aims to using the miRNA switches to control the system. As miRNA is widely used for tumor classification and prognosis, they now put forward an engineered adenovirus which can conditionally kill tumor cells by targeting unique miRNA profiles in specific cell. They assume to verify this system in colon cancer, so they developed a R package screening for specific recognition and found out miR-663b, miR-885-5p and miR-592 in COAD . Then they constructed corresponding miRNA sensors and used adenovirus early gene E1A and E1B55K to determine viral replication and tumor lysis.

Mailing the vector-LsBr5&3

Firstly, after comminication, we chose LsBr5&3 (SYSU_CHINA 2019 part BBa_K3179107) as the vector (Figure3: LsBr5&3), which was mailed by team SYSU_CHINA.

Construction of miR sensor

We firstly design the primer with BbsI restriction site (Table1)

Primer	Primer sequence	Base count
F1-miR592BS-BbsI	GTGGAAGACAACAGAACATCATCGCATATTGAC	33
R1-miR592BS-BbsI	CCTGAAGACAAACCTGTGGCACCTGAAGAGAA	32
F2-miR592BS-BbsI	GAGAAGACAAGCTTACATCATCGCATATTGAC	32
R2-miR592BS-BbsI	AATGAAGACAAGTTGGTGGCACCTGAAGAGAA	32
F1-miR663bBS-BbsI	GTGGAAGACAACAGACCTCAGGCACGGCCGG	31
R1-miR663bBS-BbsI	CCTGAAGACAAACCTGGTGGCACCTGAAGAGA	32
F2-miR663bBS-BbsI	GAGAAGACAAGCTTCCTCAGGCACGGCCGG	30
R2-miR663bBS-BbsI	AATGAAGACAAGTTGGGTGGCACCTGAAGAGA	32
F1-miR885-5pBS-BbsI	GTGGAAGACAACAGAAGAGGCAGGGTAGTGTA	32
R1-miR885-5pBS-BbsI	CCTGAAGACAAACCTCACCTGAAGAGAAACCTG	33
F2-miR885-5pBS-BbsI	GAGAAGACAAGCTTAGAGGCAGGGTAGTGTA	31
R2-miR885-5pBS-BbsI	AATGAAGACAAGTTGCACCTGAAGAGAAACCTG	33
F1-miR141BS-BbsI	GTGGAAGACAACAGAATTGTGACTAGACCATTT	33
R1-miR141BS-BbsI	CCTGAAGACAAACCTTTGCCATTAGAAATGGTC	33
F2-miR141BS-BbsI	GAGAAGACAAGCTTATTGTGACTAGACCATTT	32
R2-miR141BS-BbsI	AATGAAGACAAGTTGTTGCCATTAGAAATGGTC	33
F1-miR148bBS-BbsI	GTGGAAGACAACAGAACAAAGTTCTGTGATGCA	33
R1-miR148bBS-BbsI	CCTGAAGACAAACCTTTGCCATTCAGTGCATCA	33
F2-miR148bBS-BbsI	GAGAAGACAAGCTTACAAAGTTCTGTGATGCA	32
R2-miR148bBS-BbsI	AATGAAGACAAGTTGTTGCCATTCAGTGCATCA	33

The miRNA-BD we designed: miR141-BD(BBa_K2908333), miR148b-BD(BBa_K2908444), miR101-BD(BBa_K2908668);

The miRNA-BD SYSU_CHINA designed: miR663b-target(BBa_K3179000), miR885-5p-target(BBa_K3179002), miR592-target(BBa_K3179003).

Long DNA oligonucleotides encoding miRNA target site repeats were synthesized as ultramers by the company, annealed and restriction-ligated via BbsI-mediated Golden Gate. White/blue screening enabled selection of mostly correct clones which were further verified by Sanger sequencing.The following figure shows the previous structure and our target structure.

Previous Structure

Target Structure

Detection of fluorescence reflecting the efficiency of miR sensor

Forward transfected cells in 24-well plate format were analyzed in tube format with >50,000 events collected per sample. mKate2 was detected using a 561 nm laser with 610/20 filter and 235 PMT voltage, EBFP2 was detected using a 405 nm laser with 450/50 nm filter and 240 PMT voltage.

Analysis using FlowJo

We analyzed the results of Flow Cytometry using the software FlowJo, the classification of experiment groups and control are listed as follows.

PC (Positive Control): Only transfected with LsBr5&3;

NC (Negative Control): Transfected with LsBr5&3-target and NC fragment;

miRNA-mimics/inhibitors: Transfected with LsBr5&3-target and miRNA-mimics (miR141, miR148b, miR592(SYSU_CHINA)) or inhibitors (miR663b-inhibitor(SYSU_CHINA), miR885-3p(SYSU_CHINA) )

The results are as follows:

Figure5. The efficiency of our part miR141-BD and miR148b-BD can reach to 30% when the laser of mKate is 488nm (the best excited wavelength is 588nm)and the part SYSU_CHINA used this year have 14%-16% efficiency.

Significance of this collaboration

This collaboration aims to construct a standard method to detect the miRNA in the cell and reflect the actual expression, namely the truly quantity of miRNA who can play a role in regulating the expression of downstream gene. This method has a super advance than simply extracted the total RNA in the sample and detect the level using qPCR. This collaboration actually helped us to verify the functional expression of the miRNA we have used in our project and so as the SYSU_CHINA did. As the construction of this method need a plenty of data and it is not a short-time work, so we will continue our cooperation after the Giant Jamboree.

References:

[1] Jeremy J. Gam, Jonathan Babb & Ron Weiss, NATURE COMMUNICATIONS | (2018) 9:2430, A mixed antagonistic/synergistic miRNA repression model enables accurate predictions of multi-input miRNA sensor activity.

NUDT_CHINA

In our project, transferrin-lipoplexes are used to carry the designed loop into the breast cancer cells. Transferrin is the major protein that regulates and distributes circulating iron and contains iron needed for various biological processes, including DNA synthesis, cell metabolism and proliferation[BM JA]. The main mechanism of transferrin - mediated iron uptake is clathrin - mediated endocytosis, which is useful in transferring our loop into specific cancer cells.

This summer, we shared this idea with team NUDT_CHINA whose project with adenovirus use liver cells where the transferrin receptors are most commonly distribute.

Considering that there were many similarities between the two teams' projects, we asked them to help us test transferrin delivery efficiency and safety in primary hepatocytes and hepatocellular carcinoma cell line HepG2 compared with common liposomes and adenoviruses.

Through this cooperation, we manage to find the best way among several ways of transferring. By comparing these methods, it is believed to be benefit for cancer treatment in the future, since it can reduce the possibility of targeting treatments killing normal cells around mistakenly. According to current results, transferrin-Lipofectamine™2000 is not able to promote transfection efficiency of Lipofectamine™2000 into mouse primary hepatocytes. Currently for mouse primary hepatocytes, virus like adenovirus is probably still the most efficient way for gene delivery. Maybe we need some modification on the liposome to raise the efficiency and the safety as well.

UESTC

University of electronic science and technology in data processing of the questionnaire survey after encountered more problems, in after E-mail to contact with us, decided to adopt the way of video discussion, remote face-to-face way to deal with problems, first of all about, questionnaire survey method, electronic science and technology university struggling to find suitable processing method, we suggest they adopt SPSS system to deal with the data, rather than only by use of excel data processing, because as a statistical software of SPSS, on the information processing of the data is more rigorous and more convenience, at the same time, we will communicate the specific details are:If suggest they adopt multifactor analysis method.In addition, we discuss the problem of public education, public education in the elderly of our group, carried on the thorough exchange, electronic science and technology university students suggested that we should further based on the current community for further research work, in the aspect of news propaganda and education, we share our previous experience, advised them to further expand the influence, not confined to the existing scope, adopt multi-channel media way.

UESTC-Software

http://www.biomaster-uestc.com

We test the software and give our improving advice, and the team UESTC-Software polished their product including our suggestion.

Advice from CSU-CHINA

Comment:

Biomaster2.0 is useful and it helps users to improve their working efficiency when they’re searching for biobricks.

UESTC-Software developed a method to broaden annotations in IGEM-Registry by using BLAST tools according to the original sequences. Ambiguous annotations created in the past are corrected now! For whom has never learnt about bioinformatics, acquiring a large amount of information in the same website is cheerful.

‘Search’ module permits users typing more search fields. It can also help someone who cannot afford a VPN account to get access to a ’mirror’ of IGEM-Search.

Personally speaking, I like ‘Synbiohub’ most. Considering that traditional plasmid graphics software, such as SnapGene and SimVector, do not allow to design or display two or more plasmids in one file, we need a brand-new software to satisfy the desired. Moreover, I have noticed that you designed a ‘Comment’ module on the page of the search result. It reminds me that Biomaster has the potential to be a public forum which provides with a platform for IGEMers to discuss about the details of particular system. If you put ‘Comment’ and ‘Synbiohub’ together, we can create a interactive platform of academic exchange like Researchgate.net. In conclusion, Synbiohub makes us design or understand artificial genetic loop faster and better.

Advice:

• If it shows ‘0 hit’, there is no alert when I click the ‘Download’ button and all files are FASTA, no matter which button I have clicked.
• I recommend you to change filename extension from ‘.txt’ to ‘.gb’ when users click ‘Download as genebank’ button. It’s easy to open the file.
• Hyperlinks are needed in the ‘Cross reference’ and ‘Team wiki’ module.
• The software could not identify space character when I tried to blast the sequences put by myself. Sometimes when I input particular uniport ID in Search module, it claims an error like the figure 1.

Feedback from UESTC-software

First of all, thank you very much for your sincere and friendly evaluation, which is a very high degree of recognition of our project, thank you very much!

Secondly, your suggestions are also very valuable. After careful consideration of your Suggestions, we have modified BioMaster, which makes our project more perfect.

Here are some improvements to your suggestions:

• Some files cannot be downloaded when "0 hit" is shown in the part mentioned above, but it is not clearly indicated to the user. We have added a prompt, when the part is not part of the download file, click the button will appear text prompt.

• The downloaded file format has been increased to.gb.
• We have added a hyperlink in the Team Wiki search results to facilitate users to view the project information of previous teams more quickly.

• The reason for the above error message is that there are too many parts corresponding to the searched UniProt ID. The longest sequence in UniProt can correspond to about 3000 parts, but it is obviously difficult for users to find the one they want out of the 3000, so we set only 1000 parts to be displayed.

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