Results

Wet Lab

Initially, the wet lab wanted to test the OhioState 2021 team's constructs from last year in phage for phage therapy (Phighter Phage) and test a new set of promoters to find the best turnaround times for a phage reporter (Phinder Phage). However, because of not finding lab space until late June, we decided to focus solely on the testing and design of the Phinder Phage. Furthermore, restrictions on phage cloning until August were put in place because of worries about contamination with an existing project in the lab space. This meant we decided to pivot and focus on just testing the best promoter for our Phinder Phage. We were successfully able to isolate pET28 backbone via gel extraction and isolate our four promoter constructs fused to mCherry as seen in the gel below.

However, when we went to ligate and transform, no colonies were growing on our plates. We decided to swap out ligases but this proved ineffective. Then, we decided to re-streak the origin for our backbone and attempt ligation with that new backbone. Again, this proved ineffective. Further attempts were made by changing buffers and re-making plates. In the end, they also proved unsuccessful and because of time constraints, work in the wet lab had to stop. While investigating the cause of these ligation failures after our final attempt, other graduate students who just started ligations told us they also noticed issues with plating ligation transformation. This leads us to believe the problem may be because of temperature control issues on our incubator and dry heat baths.

In the future we hope to actually clone our reporter fusion into E. coli and then pick the strongest one for further work and study. Then, we would clone this reporter construct into various phages and test the time it takes for detection to occur.

Successes:

• Isolation of backbone (pET28a)
• PCR and digestion of four fusion with mCherry
• Selection of hybrid promoters to test from literature
• Ligations of backbone and insert

Failures:

• Not able to clone into bacteria
• Not able to clone into phage

Human Practices

The human practices committee was able to educate and create materials to inform people about sepsis and synthetic biology. Talking with doctors and other professionals helped the team highlight which important effects and causes of sepsis were largely unknown by the population. These highlighted areas led the team to research ICU psychosis from sepsis patients, post sepsis syndrome, and other detrimental impacts of sepsis. Understanding some of the most important effects of sepsis allowed the team to inform listeners. Our visitation of two Ohio science museums gave us an opportunity to enlighten others to learn about synthetic biology. The museums also allowed us to teach listeners specifically about our project and why it is so important to combat sepsis.

Although our team had great successes with outreach, we had hoped to speak with a greater number of doctors who deal with sepsis on a daily basis. It is important to learn how doctors are adjusting to new technologies as well as how they are combating increasing sepsis cases. A lack of responses from professionals restricted our ability to analyze sepsis stories. Also, because of struggles with acquiring a lab space and other lab difficulties, we were unable to update our Instagram followers on the progress of our experiment. Despite not being able to skillfully use Instagram to teach about sepsis from our lab updates, we were still able to post an at home synthetic biological protocol as well as sepsis facts.

Successes:

• Created sepsis awareness fliers to place in hospitals
• Traveled to COSI and Boonshoft science museums to teach listeners about sepsis and synthetic biology
• Spoke with doctors and patients who helped us narrow down the most important effects of sepsis
• Posted sepsis facts as well as the Strawberry DNA experiment protocol to allow viewers to repeat the experiment at home

Failures:

• A small sample of doctors were spoken to because of a lack of responses
• The team had hoped to highlight progress from lab work on Instagram, but difficulties from acquiring a lab space and other complications shifted the content of the posts

Dry Lab

Dry lab completed three models for our project: the phage-bacteria population model, the cellular automata, and the bioreactor model. The population model was able to build on OhioState 2021’s population model. The previous year’s model assumed that the interactions occurred at steady state, which would not be applicable to all situations. This year, the model was created using the Runge-Kutta method and was able to account for unsteady state interactions. The cellular automata displayed that phage cocktails were more effective than using a single phage at eliminating bacteria. For the bioreactor model, we were able to create a dynamic model for the concentrations of phage and E. coli leaving the bioreactor.

In the future, we would like to expand on our current models. Currently, the bioreactor model only includes a dynamic model for concentration; however, there are a number of other parameters that will need to be modeled to create a control system for the bioreactor. For example, temperature would need to be modeled to ensure the contents within the bioreactors are maintained at the temperature that leads to the most phage growth. Using the dynamic models, the team would be able to make the control systems by converting the dynamic models into transfer functions. With the control system created, our goal would be to build the bioreactor and test how well our control system works. The population model would need to be tested versus experimental trials to understand how accurate it is. With the experimental data, we could learn ways to improve the population model. Similarly, we would want to run experiments to display that our findings with the cellular automata are valid and work to eliminate as many assumptions as possible.

Successes:

• Cellular Automata displayed that phage cocktails were more effective at eliminating bacteria compared to just using a single phage
• An unsteady state phage-bacteria population model was successfully made utilizing the Runge-Kutta method
• A dynamic model for phage and E. coli concentration leaving the bioreactor was created
• Successfully designed and printed the 2D phage puzzles
• Expanded the phage database to include 4 more sepsis-causing-bacteria

Failures:

• Our team attempted to create a sepsis detection device. The device would analyze a blood sample and determine how much the blood fluoresces when phage is added. We were planning on quantifying how much the sample fluoresces to determine how much bacteria is in the sample. However, we did not have enough time to create a presentable model for the device.
• Initially, our goal was to build the bioreactor. However, our team lacked the resources or manpower to do so. Also, many of the researchers and professionals we reached out to were unresponsive which limited our progress at points during the summer. Therefore, towards the end of the summer we scrapped that idea and focused on creating a dynamic model of the concentration leaving the bioreactor.