iGEM 2020 — Team OhioState

[![](https://static.igem.org/mediawiki/2020/8/8b/HQ_page_logo.jpg)](https://2020.igem.org)

# Team:OhioState/Notebook

[Team](https://2020.igem.org/Team%3AOhioState/Team)
[Attributions](https://2020.igem.org/Team%3AOhioState/Attributions)
[Collaborations](https://2020.igem.org/Team%3AOhioState/Collaborations)
[Inclusion](https://2020.igem.org/Team%3AOhioState/Inclusion)

Team

[Contribution](https://2020.igem.org/Team%3AOhioState/Contribution)
[Description](https://2020.igem.org/Team%3AOhioState/Description)
[Engineering Success](https://2020.igem.org/Team%3AOhioState/Engineering)
[Implementation](https://2020.igem.org/Team%3AOhioState/Implementation)
[Notebook](https://2020.igem.org/Team%3AOhioState/Notebook)
[Proof of Concept](https://2020.igem.org/Team%3AOhioState/Proof_Of_Concept)
[Experiments](https://2020.igem.org/Team%3AOhioState/Experiments)
[Database](https://2020.igem.org/Team%3AOhioState/Database)
[Modeling](https://2020.igem.org/Team%3AOhioState/Model)

Project

[Human Practices](https://2020.igem.org/Team%3AOhioState/Human_Practices)
[Education and Engagement](https://2020.igem.org/Team%3AOhioState/Education)

Human Practices

[Safety](https://2020.igem.org/Team%3AOhioState/Safety)

# March

* 3/18 Dry Lab- Jacob started making a full list of kill switches to include in a database. Megan, Annie, Lizzie, and Lindsey all contributed to this document.

# May

* Project topic finalized
* 5/12- Dry Lab. Members: Jacob, Annie, Megan, Lindsey. Started brainstorming ideas to create a web crawler to search for kill switch literature.
* 5/12- Dry Lab.: Have set more specific deadlines (mySQL/database setup -  5/19, populating database - 5/23) and divided the dry lab sub-team into smaller subgroups. We have also drafted an email to send to the iGEM measurement committee to discuss the current iGEM database next week.
* 5/13- Dry Lab-modeling. Members: Annie, Lizzie, Lindsey Nate. Started brainstorming.
* 5/15- Human Practices. Members: Lizzie, Lindsey, Megan, Peter. Discussed more ideas specifically and what we could do with them. We decided that it was best to wait until after attending the iGEM opening sessions this week and spending some time looking at previous iGEM Human Practice ideas to decide what we were going to do, so we can be efficient with our time. We also appointed Lizzie as our administrator for Human Practices.
* 5/18- Dry Lab. Brainstormed ideal attributes we would like our database to have. We decided that we would want it to be user friendly, easy to understand, long lasting tool for years to come, remove the repeated and useless biocontainment parts, include the qualities of the promoter, and also, we considered the option of a “build your own kill switch”
* 5/18- Branding. Made a style guide. Jacob and Annie brainstormed colors/fonts/other branding.
* 5/19-Wet Lab. Members: Satvik, Ankit, Nate, Peter, Jacob, Megan, Lizzie.
* 5/21- Dry Lab- meeting with the iGEM measurement committee. The registry that is seen on the iGEM registry uses out-dated technology and anybody can edit it. However, the out-dated technology is kept for consistency on searching for various iGEM projects. iGEM has a complementary registry under SynBioHub. This is a database we could use to gather the “data” on biocontainment strategies to reorganize to our liking. Dr. Myers suggested we create a “good part” and “bad part” collection and comb through the kill switches and place them in those two categories. We can then go and find more research on the “bad parts” to make them ready for the good parts collection. Some positive features of SynBioHub is that once something is published, it can’t be changed and one can add “plug-ins”. Dr. Myers seemed particularly interested in our incorporation of our modeling data to provide users an experimental prediction of a possible kill switch they would implement. Dr. Myers suggested we get in touch with his graduate student (Jet Mante), the safety committee and possibly the iGEM president. His graduate student is familiar with iGEM registry’s strengths and weaknesses and works on plug-ins for SynBioHub.
* 5/21- general team meeting.
* 5/22- Human Practices. Brainstormed a plan of action and all of the corresponding ideas we had for our project. Our ideas for our project include: legislation regarding GMOs, search for and reach out to biotechnology companies that need intrinsic biocontainment, understand what type of biocontainment system other igem teams need, reach out to Sir Richard Roberts and Dr. Pam Silver, start to brainstorm ideas for videos, start engaging the public through social media, continue to engage with the Infectious Disease SCOPE through the Battelle center on campus. Lizzie drafted emails for Purdue, Sir Richard Roberts, and Dr. Pam Silver.
* 5/22- Branding meeting
* 5/22- Team bonding!
* 5/26-Wet Lab meeting with Dr. Sara Short, an Ohio State University assistant professor and principal investigator studying entomology. Dr. Short’s knowledge on mosquitoes was invaluable in our attempt to understand the applications of gene drives, the potential hazards of this technology, and the place of biocontainment and other kill switches in order to make this process safe.
* 5/28- Dry Lab- modeling. Lindsey and Lizzie finalized what impacts the proposed models.
* 5/28- Dry Lab- modeling meeting
* 5/21- general team meeting
* 5/29- meeting with Dr. Mandell. He liked both of the kill switch ideas, but reiterated the point of protecting against mutagenic escape, environmental supplementation, and horizontal gene transfer, as he had told us previously. He suggests that we start simple with designing our kill switch, and also mentioned that there are many ways to improve current biocontainment. Dr. Mandell was very fond of the idea of making guidelines to explain GMO/synthetic biology regulations, and he suggested that we first send out surveys to groups of people in order to understand the current public perception on GMOs and what needs added to current guidelines. Dr. Mandell emphasized the need for written guidelines for community purpose, thus prompting the idea of specifying the target population for such work. Mathematical predictive modeling may be difficult because there are many implicit assumptions that go into this, whereas we might need a more explicit model.
* 5/29 meeting with Dr. Pamela Silver. Dr. Silver recognizes the importance of biocontainment mechanisms, she believes that it is the key part to the promotion of the synthetic biology field. People who are in chronic pain or are suffering from fatal conditions are more open to solutions even if they involve GMOs (Insulin for example). This knowledge also helps understand why 3rd world countries are more accepting of GMO food to feed themselves whereas countries like America, who have enough land to grow “natural” food for now, have the choice to be against GMOs. It will likely be harder to change opinions now that politics are so involved with GMOs, but the Impossible Burger is a success. People know it is a GMO yet Burger King sells it and people are actively choosing to buy and consume it: people are okay with this GMO. People also might be more open-minded when a bio-economy offers jobs to all levels of education/background. Silver also mentioned that GMO food provides the opportunity to know exactly what is in the food whereas nature is kind of a gamble.
* 5/29 Wet Lab meeting.

# June

* 6/1- Dry Lab- Database. Outlined final goals that we wanted to accomplish. We decided to focus on two main aspects: collection and display of information, both igem related, biocontainment parts, and academic literature related information. The second aspect we decided to focus on was the display of information in the form of a flowchart. We decided to use SynBioHub to curate the igem biocontainment parts through the usage of a plugin.
* 6/1- Lecture. Satvik gave us a lecture on lab techniques
* 6/1- Meeting with Sir Richard Roberts. Sir Richard Roberts emphasized the importance of GMOs in this world considering the ominous impact of global warming. The almost nonexistent negative impacts of GMOs are completely outweighed by the great benefits of drought resistant and flood resistant crops. Pest resistant crops/GMO crops are vital in order to feed those in developing countries. To quell GMO fears, one must emphasize the benefits, and express the naivety of an antiGMO mindset. In addition, it was expressed that the outreach with the greatest impact may be through the school system. Treating children like adults, having thorough discussions, and outreaching to populations in libraries have had the greatest impact in Sir Richard Robert’s own personal experience.
* 6/2 Branding.
* 6/2 Human Practices. Wrote down takeaways from previous 3 meetings with professionals. Brainstormed key points from those meetings that we will include in our project. Went over how to refine our ideas with youtube videos, guidelines, social media and more people to network with. We also discussed collaborations with MSU and Costa Rica.
* 6/2 Wiki. Started collecting content.
* 6/3-Dry Lab-Database meeting with Jet Mante. She's starting work on a plugin interface that we could write code for and she would use it. This code would curate parts from SynBioHub that fit certain criteria. She doesn't expect the interface to be usable for a couple months, but she will let us know when it is and would love our feedback/input for it. She went over some of the technical details of SynBioHubs plugin functions as well as how she's making it, but we didn't understand everything.
* 6/3- Dry Lab-modeling. Lindsey took the lead of finding existing models related to Wet Lab procedures.
* 6/4 Branding. Finalized logo.
* 6/4- Collab meeting with MSU. Gave our advice on their potential kill switch.
* 6/4- General team meeting.
* 6/5-Dry Lab-database. Megan went through various logics for academic literature searches and took note of the most relevant papers and pulled out beneficial keywords to input for a kill switch academic literature web scraper.
* 6/5 Human Practices. We spoke about potential survey questions to send out to the global igem slack. We brainstormed more people to reach out to such as religious leaders, farmers, and other companies. We also established due dates for each of our project intentions.
* 6/5- Wet Lab meeting.
* 6/5-Team bonding
* 6/8- Human Practices. Lindsey finished writing analogies for education regarding GMOs.
* 6/8- Wet Lab lecture.
* 6/9-Dry Lab-database. Made a finalized plan of action outlife for the rest of June. Had a first thought to tailor the web scraper to be more broad and to include scraping for igem videos for easy synthesis of info in past videos rather than redundant videos.
* 6/9- meeting with Professor Patti Zettler. Suggested focusing on a situation that is blocked by regulation or specific regulation that we have an issue with, and she taught us a lot about how the agencies carry out their business and how they interact with the public.
* 6/11- Human Practices. Megan finished researching anti-GMO viewpoints and explained research for a better holistic understanding of public understanding.
* 6/11- Dry Lab. modeling.
* 6/11 - general team meeting
* 6/12- Human Practices. We discussed anti-GMO viewpoints we came across onto the internet. We established biotechnology companies to reach out with as well as world and religious leaders. Based on prior conversations, Lindsey decided to make analogies for optimal education. Furthermore, we decided to pursue human practice related mathematical modeling based on a conversation we had with Sir Richard Roberts.
* 6/12- Wet Lab meeting
* 6/15- Meeting with Dr. Rovner. She noted that our regulations would be great if implemented as they would allow for greater public transparency. As well, she said that there would be a market for biocontainment with people who do not receive EPA or FDA approval. Dr. Rovner also said that there has not been much done environmentally in regards to biocontainment, so this would more than likely be able to have a big impact if we focused on something more environmental. She said that we can call her with any questions we have or if we need guidance on anything. Dr. Rovner also said that the FDA is not as concerned with biocontainment as the EPA, so focusing on FDA guidelines and making ways for less chances of moratorium for projects gone wrong would be a good path.
* 6/15- Wet Lab lecture.
* 6/16- collab with SBU. Talked about kill switches.
* 6/17- Wet Lab meeting
* 6/17- collab with Costa Rica iGEM team.
* 6/18- modeling meeting.
* 6/18- team meeting
* 6/19- Human Practices. As a group we went over medal criteria and narrowed our ideas to specific medal criteria.
* 6/19- Human Practices. Tele Surveyed BITS Goa\_India. Gained great insight.
* 6/19- collab. Gave BITS Goa-India insight on their kill switch.
* 6/19- Wet Lab need summary
* 6/19- team bonding
* 6/21- Dry Lab- database. After a meeting with Jet Mante, Megan decided to look into SBKS SynBioHub and took notes on it.
* 6/22- Dry Lab- database. Outlines how our database work fits in with the 2020 medal criteria.
* 6/22- Human Practices. Wrote out all ideas for Human Practices in order to narrow down exactly what we want to pursue.
* 6/24- Wet Lab- Satvik completed safety form
* 6/25- Dry Lab modeling
* 6/26-Dry Lab another meeting with jet. Jet Mante walked us through the plugin development process by walking us the SynBioHub documentation (https://SynBioHub.github.io/api-docs/#what-is-SynBioHub) and an example plugin on the SynBioHub github. Using the visualization plugin, she explained how it worked by three endpoints (status, evaluate, and run) to request and get the information about a SynBioHub part. An html page (Test.html, in this case, that is the final output) is then read into the program and key information can be filled in based on the part information. Finally, Jet Mante showed us different options for testing our code. The visualization plugin is easier, as you can read the Test.html file to see if it contains the desired output, but she also suggested either installing a local version of SynBioHub to perform tests on, or Postman. This meeting increased our familiarity with plugin development and set us up so that we can now make a list of standards to identify if a part is a biocontainment part, then we will alter a visualization plugin and test it.
* 6/26- Human Practices. Tele-surveyed Manipal Biomachines in india. Consulted them regarding their kill switch.
* 6/26- Wet Lab meeting
* 6/26-Dry Lab meeting
* 6/29-Dry Lab. Database group meeting. Debriefed meeting with Jet. Made a plan for plugin/SynBioHub development as well as events to help propel the project forward such as lectures, etc.. Also finalized ideas for kill switch datatable.
* 6/29- Human Practices. We decided to tailor our survey to a telephone conversation to get more in depth input regarding our project plan from other iGEM team viewpoints. We also decided which videos to pursue for the Synthetic biology behind the science video collaboration.
* 6/30- Human Practices.SBU video collaboration. Lindsey finished writing the biocontainment mechanisms section of the SBU video collab transcript.
* 6/30- collab with IISER.
* 6/30 meeting with Sam Malloy
* 6/30- collaboration regulations meeting.

# July

* 7/1- Human Practices. Tele-Surveyed Lund Sweden.
* 7/1- Wet Lab meeting
* 7/1- video collab meeting
* 7/2-Dry Lab modeling meeting
* 7/2- team meeting
* 7/3- Human Practices. We had a short meeting to discuss our progress on our videos. We also are preparing for a presentation with the infectious disease scope through the Battelle Center at Ohio State.
* 7/4 Dry Lab- kill switch table/flow chart. Lindsey and Jacob started working on the table. To make it easier for igem/public to understand applications of a kill switch.
* 7/6- undergrad meeting.
* 7/6- Human Practices meeting with Rob Warden-Rothman
* 7/6- meeting with SBU.
* 7/7 Dry Lab- database. Decided that our kill switch table will be more like a flowchart/phylogenetic tree. Outlined goals for july.
* 7/7 Dry Lab-database. We had a SynBioHub plugin, github overview, Python programming logic lecture given by Annie
* 7/9-Dry Lab modeling
* 7/9 team meeting
* 7/10- Human Practices. During this meeting we covered our video plans with the SBU collaboration as well as theBreaking Down Synthetic Biology collaboration. We also spoke about our upcoming meeting with Dr. George Church, as well as the iGEM biocontainment registry telephone survey which we are planning to conduct with other teams.
* 7/10. Meeting with BITSPilani-Goa.
* 7/10- video collab. Had an animation/visual meeting.
* 7/13- Human Practices. Tele-Surveyed FCB-UNAL mexico.
* 7/13- Dr. George Church meeting
* 7/14- Human Practices. tele-Surveyed Michigan State University
* 7/14 Dry Lab- database. Reviewed the kill switch tree and updated on our personal work regarding both our work on the plugin and the web scraper.
* 7/14 wiki: Jacob upload code for style etc for the wiki
* 7/15- Meeting with Prof. Zettler. She said that our idea to rewrite the Coordinated Updated Framework in an easier to understand way is very good, and she likes the idea of linking to resources outside of the document to make things easier for people to understand. She said that she thinks it would be interesting for us to take one part of a law and to say “this is what this prevents,” so that we can narrow our focus in a little bit. She also suggests that for our flowchart, we link in more outside resources and to just make it a sort of overview. In regards to leveling the playing field for international regulations, she said it would be very cool to see this done, and that we should look into the current global harmonization efforts to see how we can follow what they are doing.
* 7/15- Wet Lab. Genius plasmid design tutorial by Satvik, Brian and Anice.
* 7/15- video collaboration meeting.
* 7/15- Human Practices. Jacob finished writing the history of synthetic biology transcript.
* 7/16- Meeting with Dr. George Church. He said that biocontainment is actually quite often seen as a bad thing by people because it may require debugging and can cause the opposite effect of what the goal is. Additionally, he reiterated Dr. Silver’s point that those who are against GMOs are often those who are not in need. In regards to helping iGEM teams through the regulations, he said that it could be impactful if we set up a system where iGEM teams could talk with people from federal agencies to be walked through the process in an easy to understand way.
* 7/16- team meeting
* 7/17 Human Practices meeting. Big updates include brainstorming about iGEM jamboree deliverable videos. As well as, looking into new specific names for toxins so that the public does not get alarmed by such a strong name.
* 7/17- matlab lecture for modeling by Annie and Lindsey
* 7/20 Dry Lab- Database: Started work on cleaning up iGEM biosafety registry, Megan took notes/documented the current status of the biosafety iGEM parts registry for a basis before we started working on it.
* 7/20- Dry Lab- Database. Annie developed logic for the web scraper. As a group, we decided that we will make an all inclusive web scraper that pulls out all sorts of info, but emphasizing the importance of scraping out info that past igem teams included on their wiki related to biocontainment.
* 7/20- SBU meeting,
* 7/21- Human Practices. Finished researching current videos that are present related to the topics we are considering making videos for. This is so we avoid redundancy,
* 7/22-collab with Waterloo iGEM team.
* 7/22- meeting with BITSPilani-Goa and FCB-UNAL
* 7/22- Human Practices. Tele-Surveyed Waterloo iGEM team.
* 7/23- Human Practices. Tele-Surveyed UNILausanne.
* 7/23- Collab. UNILausanne.
* 7/23 Dry Lab modeling.
* 7/23 team meeting.
* 7/24- Human practice. During this meeting we spoke about the video collaboration in regards to policy. Also, the major additional update consists of the fact that we made progress and the story boarded our visualization of the SBU collab video.
* 7/24- Human Practices. Lizzie finished writing the GMO guideline transcript.
* 7/27- Dry Lab- database. Reviewed major achievements of the week. We decided during this meeting that we will manually groom the biosafety parts list by adding and removing parts for the most convenient iGEM hosted resource.
* 7/27- Dry Lab- database. Megan went through various igem team projects that included a kill switch section on their wiki in order to pull out relevant key terms to use as an input in a biocontainment web scraper.
* 7/27- Human Practices. Tele-Surveyed Thessaly Greece.
* 7/29- video collab.
* 7/30- team meeting.
* 7/31- Human Practices meeting.Reviewed our progress with the SBU video collab and the SYNBIO behind the science collab videos. GMO analysis of modeling will be completed in the next week.
* 7/31- video collab. animation/visual meeting.

# August

* 8/2 math with Waterloo.
* 8/5- Dry Lab database meeting
* 8/5- video collab
* 8/6- Dry Lab modeling meeting.
* 8/6- team meeting
* 8/7- Human Practices. For the videos, we planned a date for the filming of our project video and decided to do a still photo animation for the SBU video collab. FOr the country policy collaboration, we uploaded our summarized coordinated framework to the wiki. Also, finished the GMO analysis models today.
* 8/7 UNILausanne meeting
* 8/9- project video. Finished writing 2 minute video project.
* 8/10- Dry Lab. Database meeting summary
* 8/10- Human Practices. Country policy collab. Met with FCB-UNAL, BITSPilani-Goa, and Denmark iGEM. Discussed our progress and future deadlines regarding the policy comparison. FCB-UNAL presented a great organizing chart that we will use.
* 8/10- Human Practices. SBU video collab. Made great progress today regarding video production plans. We have a finalized plan for graphics and distant filming. We allocated roles for graphic designers, actors, and editors.
* 8/12- video collab meeting. At this meeting, the youtube channel was set up. The first video in the series was released.

# September

* Continue to have weekly team meetings
* Draft wiki pages
* Create project promotion video

# October

* Revise wiki pages
* Wrap up project sections
* Create project presentation video

## Contact Us

Email: [igem.osu@gmail.com](igem.osu%40gmail.com)

Instagram: [@igem.osu](https://www.instagram.com/igem.osu/)

## Our Sponsors

The Ohio State University College of Medicine

The Ohio State University Infectious Diseases Institute

[![](https://static.igem.org/mediawiki/2020/8/8b/HQ_page_logo.jpg)](https://2020.igem.org)

# Team:OhioState/Engineering

[Team](https://2020.igem.org/Team%3AOhioState/Team)
[Attributions](https://2020.igem.org/Team%3AOhioState/Attributions)
[Collaborations](https://2020.igem.org/Team%3AOhioState/Collaborations)
[Inclusion](https://2020.igem.org/Team%3AOhioState/Inclusion)

Team

[Contribution](https://2020.igem.org/Team%3AOhioState/Contribution)
[Description](https://2020.igem.org/Team%3AOhioState/Description)
[Engineering Success](https://2020.igem.org/Team%3AOhioState/Engineering)
[Implementation](https://2020.igem.org/Team%3AOhioState/Implementation)
[Notebook](https://2020.igem.org/Team%3AOhioState/Notebook)
[Proof of Concept](https://2020.igem.org/Team%3AOhioState/Proof_Of_Concept)
[Experiments](https://2020.igem.org/Team%3AOhioState/Experiments)
[Database](https://2020.igem.org/Team%3AOhioState/Database)
[Modeling](https://2020.igem.org/Team%3AOhioState/Model)

Project

[Human Practices](https://2020.igem.org/Team%3AOhioState/Human_Practices)
[Education and Engagement](https://2020.igem.org/Team%3AOhioState/Education)

Human Practices

[Safety](https://2020.igem.org/Team%3AOhioState/Safety)

# **Integrated Human Practices and the Database**

The iterative engineering process is the core method used by any iGEM team to create a final product. While we had no traditional design to iterate over and no product to test against the intended implementation conditions, we found ourselves using engineering concepts in our Integrated Human Practices.

In the brainstorm phase, we knew we wanted to make the implementation of genetic biocontainment easier. Our initial thought was to simply test the biosafety parts in the iGEM parts registry and record how well each part functioned. Upon further inspection into the registry, we found that the majority of the parts tagged with ‘biosafety’ were incapable of being a biocontainment system on their own. In fact, many of them were simply promoters or toxins that other teams had used to create functioning systems, and those systems were quite rudimentary. At this point, we realized that our solution needed to be more than just characterization.

Therefore, we expanded our scope to include the rest of the registry and we adjusted our plan to include time for sorting through the larger pool of parts. But this wasn’t our final revision: we brought this concept and the beginnings of our database to our sponsor, the Ohio State University’s Infectious Disease Institute. They helped us expand this plan even further. We added organizational tags and we included non-iGEM biocontainment systems as well. We also had a new feature to implement: Automation.

It seemed entirely possible to create a program to crawl across the internet in search of new biocontainment systems to add to the database, and we knew that this would be an indispensable tool. However, after we started working on this concept, we found it to be beyond the scope of our technical knowledge. In fact, this kind of program is on the bleeding edge of computer science, so we decided to cut it out of our plan. Instead, we focused on making sure our selection was thorough and high-quality. The engineering process

Our integrated human practices became a shining example of the iterative engineering process, starting as a distant idea and becoming a polished product over numerous revisions and ‘backward’ steps. And yet, there is still more that can be done in the realm of genetic biocontainment. It’s our goal that future projects will pick up where we left off in this cycle of improvement.

# **Experiments for Modeling Data**

One of our initial ideas was to develop mathematical models that could predict properties of biocontainment systems based on data from the constituent genes. In order to determine the feasibility and relevance of this, we talked to several experts in the field. All agreed that it was both possible and would be a useful, new tool.

For our design, we picked a set of 12 promoters and 10 death mechanisms, selecting both commonly used genes and those that are used in more niche circumstances, such as temperature and nitrate based promoters.

|  |  |  |  |
| --- | --- | --- | --- |
| Promoter | | Death Mechanism | |
| Description | Gene | Description | Gene |
| Nitrate based promoter | amilCP | Death Pathway | mazF |
| Rhamnose inducible, glucose repressible promoter (pRha) | pRha | Suicide Mechanism | t |
| Tightly-regulated lactose-inducible promoter | *PlacIQ* | Holes in the membrane | hokD |
| acid induced promoter | asr | Inhibits DNA replication | parE |
| ethanol/stress induced | YJL052W | Puts holes into the membrane | ghoT |
| mercury inducible | MerRT | Degrades both RNA and DNA | 1BRS |
| cI repressor and cI regulated promoter. The repressor protein denatures at 42 C | lambda PR | Holes in the membrane | nucD |
| Interrupts DNA gyrase and kills the cell | ccdB |

## Plasmid Diagrams

![plasmid](https://static.igem.org/mediawiki/2020/e/eb/T--OhioState--lambda_pR.jpg)

![plasmid](https://static.igem.org/mediawiki/2020/8/8e/T--OhioState--pMerT.jpg)

![plasmid](https://static.igem.org/mediawiki/2020/1/1a/T--OhioState--pLacQ.jpg)

![plasmid](https://static.igem.org/mediawiki/2020/4/46/T--OhioState--pAsr.jpg)

![plasmid](https://static.igem.org/mediawiki/2020/4/45/T--OhioState--ccdB.jpg)

![plasmid](https://static.igem.org/mediawiki/2020/b/be/T--OhioState--nucD.jpg)

![plasmid](https://static.igem.org/mediawiki/2020/0/0f/T--OhioState--pRha.jpg)

![plasmid](https://static.igem.org/mediawiki/2020/c/cf/T--OhioState--pYeaR.jpg)

![plasmid](https://static.igem.org/mediawiki/2020/5/5e/T--OhioState--pYJI052W.jpg)

![plasmid](https://static.igem.org/mediawiki/2020/8/8d/T--OhioState--ghoT.jpg)

![plasmid](https://static.igem.org/mediawiki/2020/a/af/T--OhioState--hokD.jpg)

![](https://static.igem.org/mediawiki/2020/e/e5/T--OhioState--mazF.jpg)

![plasmid](https://static.igem.org/mediawiki/2020/f/f4/T--OhioState--parE.jpg)

![plasmid](https://static.igem.org/mediawiki/2020/7/76/T--OhioState--T4Holin.jpg)

![plasmid](https://static.igem.org/mediawiki/2020/4/49/T--OhioState--1BRS.jpg)

We would then pass this on to our modeling team who would predict kill switch escape rates for several combinations of one promoter and one cell-death gene. After, we will combine the previously characterized promoter and toxin to create a kill switch. Then the killswitched would be characterized for escape frequency This would be done multiple times with different combinations of promoter and toxin..This would provide us data with which we could compare our modeling predictions and refine the models used to predict kill switches.

If the model is successful we would expand the experiments to cover many more uncommon or niche promoters and toxins and use those results to further refine the model.

# **Human Practices Modeling**

To exemplify the potential value of genetically modified organisms in solving real world issues, our team decided to tackle an important issue in developing countries: malnutrition. Specifically, we took population data and calculated the vitamin A supply necessary to satisfy the recommended daily intake of the Zimbabwean people. Then, we showed how genetically modified maize, which is a staple of the Zimbabwean diet, could be used to satisfy the vitamin A requirements in Zimbabwe, which is a country where approximately ¼ of the population has a vitamin A deficiency.

## Contact Us

Email: [igem.osu@gmail.com](igem.osu%40gmail.com)

Instagram: [@igem.osu](https://www.instagram.com/igem.osu/)

## Our Sponsors

The Ohio State University College of Medicine

The Ohio State University Infectious Diseases Institute

[![](https://static.igem.org/mediawiki/2020/8/8b/HQ_page_logo.jpg)](https://2020.igem.org)

# Team:OhioState/Experiments

[Team](https://2020.igem.org/Team%3AOhioState/Team)
[Attributions](https://2020.igem.org/Team%3AOhioState/Attributions)
[Collaborations](https://2020.igem.org/Team%3AOhioState/Collaborations)
[Inclusion](https://2020.igem.org/Team%3AOhioState/Inclusion)

Team

[Contribution](https://2020.igem.org/Team%3AOhioState/Contribution)
[Description](https://2020.igem.org/Team%3AOhioState/Description)
[Engineering Success](https://2020.igem.org/Team%3AOhioState/Engineering)
[Implementation](https://2020.igem.org/Team%3AOhioState/Implementation)
[Notebook](https://2020.igem.org/Team%3AOhioState/Notebook)
[Proof of Concept](https://2020.igem.org/Team%3AOhioState/Proof_Of_Concept)
[Experiments](https://2020.igem.org/Team%3AOhioState/Experiments)
[Database](https://2020.igem.org/Team%3AOhioState/Database)
[Modeling](https://2020.igem.org/Team%3AOhioState/Model)

Project

[Human Practices](https://2020.igem.org/Team%3AOhioState/Human_Practices)
[Education and Engagement](https://2020.igem.org/Team%3AOhioState/Education)

Human Practices

[Safety](https://2020.igem.org/Team%3AOhioState/Safety)

# Promoters

*E.coli* strain MG1655 with the plasmid construct containing the promoter regions and regulatory proteins fused to a gfp will be used to inoculate 5 mL of M9 glucose medium containing tetracycline (20 *μ*g/mL) to select for the plasmid. Cultures will be grown in 18 mm x 150 mm tubes. They will then be grown for 20 hours at  37℃ while being spun at 70 RPM for aeration. The cultures will be diluted 1:100 in 5 mL of pre-warmed media at the previous conditions for approximately 4 hours. Then the optical density at 600 nm (OD600) of a 500 μL sample from each culture will be determined. Using the OD600, each sample will be diluted to 0.07 OD and grown for 1 hour at the same conditions as above.

Six 200 μL samples of transformed culture, three with inducer and three without, and one 200 μL sample of untransformed cells will be pipetted into wells. There will also be one 200 μL sample of M9 medium added to the wells as a control. These wells were then placed into the SpectraMax plate reader with the settings as stated in Table 2.

#

|  |  |  |  |
| --- | --- | --- | --- |
| Promoters and Their Inducers   (Table 1) | | | |
| Insert | Promoter | Regulating Molecule | Inducer |
| NsrR pYeaR--GFP | pYeaR | NsrR | 10 mM NaNO3 |
| rhaR rhaS pRha--GFP | pRha | RhaR | 3 mM Rhamnose |
| pAsr--GFP | pAsr | Acid Shock RNA | Decrease pH to 5 |
| pLacIQ -- LacI -- PL8-UV5 -- GFP | PL8-UV5 | LacI | 5 mM IPTG |
| lambda cITS lambda pR---GFP | lambda pR | lambda cITS repressor | Increase temperature above 47°C |
| MerR pMerT--GFP | pMerT | MerR | 0.3 μM Hg(II) ion |
| pYJL052W--GFP | pYJL052W | Ethanol | 1.5 M EtOH |

|  |  |
| --- | --- |
| SpectraMax Settings   (Table 2) | |
| Emission Spectra | 525 nm |
| Absorption Spectra | 485 nm |
| Time interval | 0.1 sec |

Kelly, Jason R., et al. "Measuring the activity of BioBrick promoters using an in vivo reference standard." Journal of biological engineering 3.1 (2009): 1-13

#

# Toxins

*E.coli* strain MG1655 with the plasmid construct containing the toxin regions controlled by a *lac* operon will be used to inoculate 5mL of M9 medium containing kanamycin (50 *μ*g/mL) to select for the plasmid. Cultures will be grown in 18 mm x 150 mm tubes. They will be grown for 20 hours at  37℃ while being spun at 70 RPM for aeration.  The cultures would be diluted 1:100 in 5mL of pre-warmed media at the previous conditions for approximately 4 hours. Then the optical density at 600 nm (OD600) of a 500μL sample from each culture will be determined. Using the OD600, each sample will be diluted to 0.07 OD and grown for 1 hour at the same conditions as above.

Three plates containing LB agar and 200 μM IPTG will be streaked with the strain containing the plasmid construct. One plate containing LB agar and 20 mM lactose will be streaked with MG1655 without the toxin containing plasmid. Another three plates containing LB agar with no lactose will be streaked with the toxin containing strain. After 24 hours, the number of colony forming units on each plate will be counted.

#

# NEB 2-Step PCR

1. Denature at 98℃ for 30 seconds.
2. 25-35 cycles of 98℃ for 10 seconds followed 10 seconds at the annealing temperature according to the Gibson Table
3. Final extension at annealing temperature for 2 minutes.

Biolabs, N. (n.d.). PCR Optimization (E0555). Retrieved October 27, 2020, from <https://www.neb.com/protocols/2013/01/11/pcr-optimization-e0555>

#

# Gibson Table Data is gathered from Geneious Gibson Reports.

|  |  |  |  |  |  |
| --- | --- | --- | --- | --- | --- |
| **Promoter  Constructs** | Forward Primer | Tm [℃]  (Forward) | Reverse  Primer | Tm [℃]  (Reverse) | Digestion Enzyme Used |
| lambda cITS lambda pR---GFP | TGCGGGCCCGGTACCAGGTTTATGGCTAGCTCAGTCCTAGG | 59.1 | TCTCTCTCTATCTATCTAGGGCAACCATTATCACCGCCAG | 59.6 | StuI |
| MerR pMerT--GFP | CTTGCTTCTGCTTGTTAGCCTAGATAGATAGAGAGAGAGAGAGACT | 42.9 | GAAAGCCTGGTCAAAGAGCCTGGTACCGGGCCCG | 61.6 | StuI |
| pAsr--GFP | CAAATTGAGGGTATGACACCTAGATAGATAGAGAGAGAGAGAGACT | 59.2 | GCTGAATAAATTACAGCGCCTGGTACCGGGCCCG | 61.6 | StuI |
| pLacIQ -- LacI -- PL8-UV5 -- GFP | TGCGGGCCCGGTACCAGGCGTTGACACCATCGAATGGTG | 59.9 | TCTCTCTCTATCTATCTAGGAATTGTTATCCGCTCACAATTTCAC | 58.9 | StuI |
| NsrR pYeaR--GFP | GGTACCAGGTTCCCATCTATAATCCTCCCTGA | 57.6 | CTATCTAGGCGCCTGATAATTTGCATTTT | 53.2 | StuI |
| pYJL052W--GFP | TAAATTTACACACAAAACAAACCTAGATAGATAGAGAGAGAGAGAGACT | 59.2 | GTCGCATATCCTATTCCCCTGGTACCGGGCCCG | 61.6 | StuI |
| rhaR rhaS pRha--GFP | GGTACCAGGCGGCGAAATAGTAATCACGAGG | 59.3 | CTATCTAGGTACGACCAGTCTAAAAAGCGC | 57.3 | StuI |
| **Toxin Constructs** |  | | | | |
| T4 Holin | TTAAAGAGGAGAAAGGTACATGGCAGCACCTAGAATATCA | 56.6 | CACCTTTAGACATGGTACTTATTTAGCCCTTCCTAATATTCTGGC | 59.1 | KpnI |
| hokD | TTAAAGAGGAGAAAGGTACATGAAGCAGCAAAAGGCGATG | 60.1 | CACCTTTAGACATGGTACTTACTCCTCAGGTTCGTAAGCTG | 59.8 | KpnI |
| parE | TTAAAGAGGAGAAAGGTACATGACGCGCAGGCTGC | 60.9 | CACCTTTAGACATGGTACATTACTCGAAGGTGCGGCC | 60.2 | KpnI |
| ghoT | GAAAGGTACATGGCCTTGTTCAGCAAAATCT | 59.1 | ACATGGTACTCAGAACAAGCTGAACAACAAGG | 59.6 | KpnI |
| Barnase | ACCTTTACAAAAATCAGATAAGTACCATGTCTAAAGGTGAAGA | 55.2 | GATAACCTGTGCTGCCATGTACCTTTCTCCTCTTTAATGAATTCGG | 60.2 | KpnI |
| NucD | TTAAAGAGGAGAAAGGTACATGCGACATCGCGGAGGAAA | 62.6 | CACCTTTAGACATGGTACTCATGAGGCAATGCCCTGC | 55.0 | KpnI |
| ccdB | TTAAAGAGGAGAAAGGTACATGCAGTTTAAGGTTTACACCT | 55.9 | CACCTTTAGACATGGTACTTATATTCCCCAGAACATCAGGT | 56.7 | KpnI |
| mazF | TTAAAGAGGAGAAAGGTACATGGTGAGCCGCTATGTGC | 60.5 | CACCTTTAGACATGGTACTTAGCCAATCAGCACGTTAA | 55.4 | KpnI |

#

# Gibson Procedure

Use the fragment assembly protocol from the HiFi DNA Assembly table. Each insert must be at least twice the vector. For this reaction – Vector = 0.05 pmol and each Insert = 0.1 pmol. Allowing the total reaction to be under 0.5 pmol. Reagent Volume (µl) pSB1C3 backbone: 2.35 BBa\_K2797002: 5.74 Master Mix: 8.09 Add the fragments and vector to a PCR tube with the master mix and water if required. Incubate samples on a heat block 60 minutes at 50 °C.

Biolabs, N. (n.d.). NEBuilder® HiFi DNA Assembly. Retrieved October 27, 2020, from <https://www.neb.com/applications/cloning-and-synthetic-biology/dna-assembly-and-cloning/nebuilder-hifi-dna-assembly>

#

# Mach1 OneShot Chemical Transformation Protocol

Pellet 1–5 ml bacterial overnight culture by centrifugation at >8000 rpm (6800 x g) for 3 min at room temperature (15–25°C). Resuspend pelleted bacterial cells in 250 μl Buffer P1 and transfer to a microcentrifuge tube. Add 250 μl Buffer P2 and mix thoroughly by inverting the tube 4–6 times until the solution becomes clear. Do not allow the lysis reaction to proceed for more than 5 min. If using LyseBlue reagent, the solution will turn blue. Add 350 μl Buffer N3 and mix immediately and thoroughly by inverting the tube 4–6 times. If using LyseBlue reagent, the solution will turn colorless. Centrifuge for 10 min at 13,000 rpm (~17,900 x g) in a table-top microcentrifuge. Apply 800 μl supernatant from step 5 to the QIAprep 2.0 spin column by pipetting. For centrifuge processing, follow the instructions marked with a triangle. For vacuum manifold processing, follow the instructions marked with a circle . Centrifuge for 30–60 s and discard the flow-through, or apply vacuum to the manifold to draw the solution through the QIAprep 2.0 spin column and switch off the vacuum source. Recommended: Wash the QIAprep 2.0 spin column by adding 0.5 ml Buffer PB. Centrifuge for 30–60 s and discard the flow-through, or apply vacuum to the manifold to draw the solution through the QIAprep 2.0 spin column and switch off the vacuum source. Note: This step is only required when using endA+ strains or other bacteria strains with high nuclease activity or carbohydrate content. Wash the QIAprep 2.0 spin column by adding 0.75 ml Buffer PE. Centrifuge for 30–60 s and discard the flow-through, or apply vacuum to the manifold to draw the solution through the QIAprep 2.0 spin column and switch off the vacuum source. Transfer the QIAprep 2.0 spin column to the collection tube. Centrifuge for 1 min to remove residual wash buffer. 10.Place the QIAprep 2.0 column in a clean 1.5 ml microcentrifuge tube. To elute DNA, add 50 μl Buffer EB (10 mM TrisCl, pH 8.5) or water to the center of the QIAprep 2.0 spin column, let stand for 1 min, and centrifuge for 1 min.

Mach1 Competent Cells: Thermo Fisher Scientific - US. (n.d.). Retrieved October 27, 2020, from <https://www.thermofisher.com/us/en/home/life-science/cloning/competent-cells-for-transformation/competent-cells-strains/mach1-competent-cells.html>

#

# Agarose Gel Electrophoresis

Measure 1 g of agarose. Double to obtain 2% agarose gel Add agarose to 100 mL 1x TAE buffer in a microwavable flask. TBE can substitute for TAE. Microwave 1-3 minutes until completely dissolved. Take it out and swirl every 30-45 seconds. Beware surprise boiling. Stop microwaving as soon as boiling occurs; excessive evaporation will change the agarose percentage. Don't let it boil over. Cool to about 50 °C (about when it is comfortable to keep your hand on the flask), about 5 minutes. Add ethidium bromide (EtBr) to a final concentration of xxx (usually about 10 μl of lab stock solution per 100 mL gel). EtBr binds to the DNA and allows you to visualize the DNA under ultraviolet (UV) light. Pour slowly into a gel tray with the well comb in place. Pour slowly to avoid bubbles which will disrupt the gel. Any bubbles can be pushed away from the well comb or towards the sides/edges of the gel with a pipette tip. Place newly poured gel at 4 °C for 10-15 mins OR let sit at room temperature for 20-30 mins, until it has completely solidified. Add a loading buffer to each of your DNA samples. Loading buffer serves two purposes:

 one, it provides a visible dye that helps with gel loading and allows you to gauge how far the DNA has migrated, two it contains a high percentage of glycerol that increases the density of your DNA sample causing it to settle to the bottom of the gel well, instead of diffusing in the buffer. Once solidified, place the agarose gel into the gel box (electrophoresis unit). Fill the gel box with 1xTAE (or TBE) until the gel is covered. Carefully load a molecular weight ladder into the first lane of the gel. Carefully load your samples into the additional wells of the gel. Run the gel at 80-150 V until the dye line is approximately 75-80% of the way down the gel. A typical run time is about 1-1.5 hours, depending on the gel concentration and voltage. Turn OFF power, disconnect the electrodes from the power source, and then carefully remove the gel from the gel box. Using any device that has UV light, visualize your DNA fragments. The fragments of DNA are usually referred to as ‘bands’ due to their appearance on the gel.

Agarose Gel Electrophoresis. (n.d.). Retrieved October 27, 2020, from <https://www.addgene.org/protocols/gel-electrophoresis/>

#

## Contact Us

Email: [igem.osu@gmail.com](igem.osu%40gmail.com)

Instagram: [@igem.osu](https://www.instagram.com/igem.osu/)

## Our Sponsors

The Ohio State University College of Medicine

The Ohio State University Infectious Diseases Institute

[![](https://static.igem.org/mediawiki/2020/8/8b/HQ_page_logo.jpg)](https://2020.igem.org)

# Team:OhioState/Results

[Team](https://2020.igem.org/Team%3AOhioState/Team)
[Attributions](https://2020.igem.org/Team%3AOhioState/Attributions)
[Collaborations](https://2020.igem.org/Team%3AOhioState/Collaborations)
[Inclusion](https://2020.igem.org/Team%3AOhioState/Inclusion)

Team

[Contribution](https://2020.igem.org/Team%3AOhioState/Contribution)
[Description](https://2020.igem.org/Team%3AOhioState/Description)
[Engineering Success](https://2020.igem.org/Team%3AOhioState/Engineering)
[Implementation](https://2020.igem.org/Team%3AOhioState/Implementation)
[Notebook](https://2020.igem.org/Team%3AOhioState/Notebook)
[Proof of Concept](https://2020.igem.org/Team%3AOhioState/Proof_Of_Concept)
[Experiments](https://2020.igem.org/Team%3AOhioState/Experiments)
[Database](https://2020.igem.org/Team%3AOhioState/Database)
[Modeling](https://2020.igem.org/Team%3AOhioState/Model)

Project

[Human Practices](https://2020.igem.org/Team%3AOhioState/Human_Practices)
[Education and Engagement](https://2020.igem.org/Team%3AOhioState/Education)

Human Practices

[Safety](https://2020.igem.org/Team%3AOhioState/Safety)

# 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.

* [2014 TU Darmstadt](https://2014.igem.org/Team%3ATU_Darmstadt/Results/Pathway)
* [2014 Imperial](https://2014.igem.org/Team%3AImperial/Results)
* [2014 Paris Bettencourt](https://2014.igem.org/Team%3AParis_Bettencourt/Results)