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<h3 style="font-family: Bavro; font-size: 2.75em; color: #F3557E; text-align: center; padding: 1.5%;">Welcome to the UCopenhagen Poster Page!</h3>
 
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<p style="font-family: Avenir, Arial; font-size: 16px; margin-top: 1.5%;">This page looks a little different from the others, as here you'll find the poster we're going to be using at the Jamboree! We hope you like our blahblah for an interactive poster that almost doesn't suck</p>
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<li>Split ubiquitin, the assembly of which leads to the release of a transcription factor (TF).</li>
 
<li>Split ubiquitin, the assembly of which leads to the release of a transcription factor (TF).</li>
 
<li>A split TEV protease, that cuts a membrane-bound TF loose upon reconstitution.</li>
 
<li>A split TEV protease, that cuts a membrane-bound TF loose upon reconstitution.</li>
 
<li>Another split TEV protease, which will cut an engineered G-alpha (GPA1) protein into smaller fragments, allowing for beta-/gamma dissociation and subsequent signaling.</li>
 
<li>Another split TEV protease, which will cut an engineered G-alpha (GPA1) protein into smaller fragments, allowing for beta-/gamma dissociation and subsequent signaling.</li>
 
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Click through to read about the different biosensor designs in detail.
 
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Revision as of 16:00, 10 November 2020

Description Design Implementation Poster
Engineering Success Modeling/Simulation Parts Overview Results Protocols Notebook Safety
Integrated Human Practices Entrepreneurship Education
Collaborations Partnership Our Contribution
Judging Form Medals
Team Members Attributions Sponsors


Welcome to the UCopenhagen Poster Page!

This page looks a little different from the others, as here you'll find the poster we're going to be using at the Jamboree! We hope you like our blahblah for an interactive poster that almost doesn't suck

CIDosis - A Monitoring Tool for Chronic Inflammatory Diseases
Presented by Team UCopenhagen 2020

Authors: Aje Al-Awssi, David Nørgaard Essenbæk, Emil Funk Vangsgaard, Endre Lindhardt Garberg, Ignacio Pardo Casado, Jan Weicher, Shivani Pradeep Karnik, Victoria Thusgaard Ruhoff & Vit Zemanek

Abstract
Chronic Inflammatory Diseases (CIDs) are debilitating diseases affecting millions of people worldwide. Optimal treatment requires constant monitoring, but current testing methods are invasive, time-consuming, and costly. CIDosis strives to change this with a non-invasive patch for self-monitoring. Backed by extensive computer modeling, we are developing a biosensor that continuously collects sweat from the skin, and produces a color reflecting the level of inflammation. The biosensor in our patch is based on Saccharomyces cerevisiae cells equipped with interleukin-specific receptors that will associate in the presence of interleukins, resulting in the intracellular complementation of a split protein. A transduction pathway is then triggered, leading to the production of a color, whose intensity is logged by an app and shared with a medical professional. By integrating the wishes of patients living with CIDs, as well as experts within these fields, CIDosis brings a next generation tool to improve patient quality of life.

Three Tiers of Biosensor Design
We've developed three interleukin biosensors of varying complexity. Our overall biosensor design is based on the expression of interleukin receptors on the surface of yeast cells. Upon binding interleukins, two receptor constructs associate, leading to the activation of an intracellular signaling cascade. The receptor constructs consist of the extracellular part of an interleukin receptor fused to a generic transmembrane domain (TMD) (Wsc1, [1]) and to an intracellular, split actuator protein. For the three designs, these split proteins are;

  • Split ubiquitin, the assembly of which leads to the release of a transcription factor (TF).
  • A split TEV protease, that cuts a membrane-bound TF loose upon reconstitution.
  • Another split TEV protease, which will cut an engineered G-alpha (GPA1) protein into smaller fragments, allowing for beta-/gamma dissociation and subsequent signaling.

Click through to read about the different biosensor designs in detail.
Minimal Biosensor Design
The initial, minimal, biosensor design builds on the split-ubiquitin based Membrane Yeast Two-Hybrid method (MYTH) [2], where two proteins of interest are fused to either half of a modified ubiquitin molecule, that are by themselves unable to reconstitute a functional protein. However, whenever the proteins of interest associate, the attached halves of split ubiquitin come into proximity of each other, facilitating reconstitution. In addition, one of the halves of split ubiquitin is further fused to a synthetic transcription factor (LexA-VP16 [3]). Upon reconstitution, the ubiquitin can be cleaved by deubiquitinating enzymes resulting in the release of the transcription factor and ultimately the activation of a reporter gene resulting in a biosensor signal.
Intermediate Biosensor Design
In order to add one amplification step to our biosensors signaling pathway we devised another biosensor design. Our intermediate design utilizes a similar receptor-system to the ubiquitin-based design. Here, our intracellular split-protein is the split TEV-protease. This is another method to monitor protein-protein interactions, described by Wehr, M. C. et al in 2006. Here, we again have two engineered inactive halves of the TEV-protease, that only regain activity when coexpressed as fusion constructs with interacting proteins [4]. Therefore, we again utilize the receptor/TMD from the previous design, but now each of our receptors will be fused to one half of the TEV-protease instead with a flexible linker.

In parallel, we also express the Wsc1 TMD, which is fused with the same transcription factor from the previous design, and use the recognition sequence for the TEV-protease as the linker between the two. Thus, upon reconstitution,The TEV protease will be able to cleave the transcription factor that can now freely translocate to the nucleus and activate a reporter gene. In theory, the TEV-protease will be able to cut many transcription factors loose, meaning that one interleukin (by extension of the association of our two receptors) will result in the cleavage of multiple transcription factors and thus an amplification of the biosensor signal.
Advanced Biosensor Design
To further improve the potential sensing properties of our biosensor we decided to exploit signal processing capabilities of the yeast pheromone sensing pathway by integrating parts of it into our biosensor design. This was anticipated to result in higher biosensor sensitivity.

Yeast has a G-protein-coupled receptor (GPCR) specific to yeast mating pheromones. When a pheromone binds to the receptor, the receptor occupancy stimulates the G-alpha subunit of the G-protein to exchange GDP for GTP, and release the beta and gamma subunits. The released beta and gamma subunits can then recruit the Ste5 scaffold protein to the membrane, starting a phosphorylation cascade eventually leading to the phosphorylation and activation of the transcription factor Ste12 and expression of pheromone response genes [5].

Since the dissociation of G-alpha from the beta and gamma subunits is what drives the pheromone cascade, we decided to design our own switch for this step in the pathway. Building onto the previous TEV protease design, we designed a mutant G-alpha with cleavage sites from the TEV protease inserted at multiple points, as described on our engineering success page. This meant that the presence of an interleukin, and ultimately the reconstitution of the TEV protease, would result in the cleavage of G-alpha into multiple fragments. These fragments would then, in theory, dissociate from the beta/gamma subunit, freeing it in a similar fashion to the normal signal transduction pathway. The free beta/gamma subunit would then be able to trigger the pheromone pathway and activate a downstream reporter gene. In order to maintain orthogonality, we used the same promoter as previously, and the transcription factor LexA-Ste12 - a synthetic transcription factor that can be activated by phosphorylation in the last step of the phosphorylation cascade in the pheromone pathway.
Modeling
To guide the development of a yeast strain with the ability to sense inflammation biomarkers we included modeling of different biosensor designs. In the dry lab, we focused on comparing the three designs in terms of their contribution to biosensor sensitivity and behavior. This resulted in identifying the most applicable design for our biosensor. Furthermore, special effort was spent on modeling and evaluating different versions of the modified GPA1 protein (advanced design), by employing computational methods for protein engineering.

Sensitivity Comparison
We compared the three designs of engineered signaling pathways in S. cerevisiae in terms of sensitivity through modeling with ordinary differential equations (ODEs). The models revealed the additional benefits of employing the yeast pheromone cascade in signal amplification (~7 orders of magnitude), thus rendering one of the designs as a clear candidate for the application in the biosensor (fig. 4).

Impact of Adverse Effects
We modeled the effects of hypothetical cellular scenarios (e.g. reporter toxicity) on the pathways within the framework of stochastic differential equations (SDEs). There, we explored various expected and unexpected behaviors in the models, which suggested that specific failures of pathway components may lead to characteristic statistics of reporter concentrations (fig. 5). This tool has the potential to improve our troubleshooting in the future.

Protein Modeling
As the most applicable design required utilization of the yeast pheromone cascade, we had to engineer a novel GPA1 protein that would allow for signal transduction from our designed receptor system. Guided by several iterations of simulations with Rosetta Software Suite, we identified multiple regions suitable for inserting cleavage sites.
However, the predictions suggested that the post-cleavage protein fragments did not exhibit the properties we expected (fig. 6). Based on these findings, we articulated a refined framework for engineering signal transduction in our biosensor.
Design of the Patch
Our solution is a sweat-collecting patch that the patient can wear on the go. It consists of three layers.
  1. Porous nanofilm - A porous nanofilm will allow interleukins to diffuse into the patch and prevent the yeast cells from escaping the patch. This film provides safety for the users and bio-containment.
  2. Genetically modified yeast-based biosensor - Our yeast biosensor in dry-yeast form, ready to be activated upon contact with sweat.
  3. Adhesive patch - Common transparent plastic or woven fabric (such as nylon) used by bandage manufacturers.
General inflammation can greatly fluctuate, and infrequent testing can give a misleading picture of a patient's inflammation status, due to the snapshot nature of these tests. For example, rheumatoid arthritis patients can experience big inflammation changes between current testing, leading to irrevocable damage. We want to avoid this by giving patients easy access to weekly stress-free monitoring. The CIDosis patch can be used in the patient’s daily life and help guide treatment by providing more data to the healthcare professionals. We envision the use of an app that would enable the users to read the inflammation results in a precise manner. This app will track the inflammation results over time. In this way, inflammation levels can be saved and used for disease progression analysis. Here you see a representation of our app with a color slider that allows the user to save the patch color to their calendar and follow their inflammation.
Methods
Plasmids with desired constructs were made through USER cloning- and ligation in E. coli. Stable transformation of the yeast with purified plasmids from the USER step happened via use of a 5-assembly system, which allows for controllable expression of our gene of interest. Confirmation of positive yeast transformations was done through colony PCR. The biosensor designs were tested in interleukin induction assays, measured in luminescent units, as luciferase is expressed upon interleukin binding. GPA1 mutants were tested in the context of an adenosine biosensor employing the human adenosine GPCR receptor A2A(R199A). Subcellular localization assays of proteins of interest coupled to superfolding GFP were made with confocal laser scanning microscopy.
Results
To construct our modular biosensors, the simple, intermediate and advanced designs, we performed countless amounts of USER ligation- and cloning in E.coli cells to create the plasmids encoding our modified G-alpha variants and interleukin receptors. For these steps to work, we digested all our gene fragments of interest with USER enzyme to create custom sticky ends, thereby allowing for stable transformation into competent E. coli cells.

Following verifications of positive transformations and selection of the positive colonies through gel electrophoresis, for which we managed to clone 53 constructs, the plasmids were purified and transformed into Saccharomyces cerevisiae cells.

The strains used were constructed genomic integration of the different modules into chromosome X site 3 using the homologous recombination based 5-plasmid assembly system (unpublished) available at the host lab.

In total, 21 yeast strains relevant for our biosensor designs were created using this system, allowing us to test the feasibility of the different biosensor variants for key aspects in interleukin sensing.

Through our extensive testing with luciferase assays and subcellular localization assays for both the minimal, intermediate and advanced design, we found that localization issues of the interleukin receptor proteins and accessory proteins were prominent for several of the proteins.

Induction of the TEV protease was shown to effectively cleave our membrane-bound transcription factor containing a TEV recognition site in a flexible linker, thereby inducing the expression of our reporter gene of interest. However, other results were not conclusive to verify the effectiveness of our biosensor designs.

Results were inconclusive regarding the advanced design, as, while seemingly plausible due to the increase in reporter gene expression, it was not possible to determine whether cleavage of our modified GPA-1 variants by a TEV protease was the reason for reporter gene expression in our induction assays.

Several experiments were identified for optimization of the biosensors, however. Our future work must focus on improving the subcellular localization of the interleukin receptors to allow efficient detection of interleukins in sweat for color production through expression of our reporter gene of interest.
Human Practices
Human practice was instrumental in developing CIDosis. We talked with 10 experts and got 86 patient inputs from interviews and surveys. This not only affected the formulation of our, but also directed our lab efforts towards developing a modular design that can be used by other scientists. Furthermore, patient surveys helped us design the patch. Patient feedback gave us some indication of what the patch should look like, and it made clear the need for proper instructions for the user. This culminated in a user-guide that specifies how to use the patch, and how patients can log and use the results they receive.

Patient surveys also influenced our dry lab work. Feedback suggested that most CIDosis users would be willing to wear the patch for up to 24 hours. Since time does not seem to be an issue for most patients, we could model the optimal time period for wearing the patch. Our results show that after being worn for 5 hours, the patch is best able to distinguish between high and low inflammation.

Finally, Throughout the project we worked on the ethical aspects CIDosis. These considerations spanned from potentially causing mental distress to patients, to the dangers of GMO products. Expert input was invaluable in resolving these issues, but we also collaborated with other iGEM teams who faced similar issues. The experience gained from working on ethical issues culminated in an ethics guide designed to make the process easier for future iGEM teams.
More of Our Work
1. Ethics Guide: The road to ethics in science looked daunting and confusing. As a contribution for future iGEM teams, and in collaboration with SynthEthics, we created an ethics guide. It is a six-step guide for how we can analyze and reduce moral ambiguities in our iGEM projects and ideas. We used CIDosis and the iGEM Lund 2020 team’s project, Protecto, as cases-in-point for easy understanding and interpretation. Do give it a read!

2. Children’s Book: Our team is not short of artists! To inculcate passion for science and synthetic biology among children from an early age, we made the first edition of what we believe would be a series of children’s books. Named “My Sister Can Talk with Bacteria”, we hope to sensitize and educate young minds on genetic engineering, while emphasizing the importance of women in science. Other iGEM teams also helped us in translating the book to Arabic, Dutch and Japanese!

3. Partnership with iGEM 2020 Team from Aalto: We partnered with the iGEM Team from Aalto-Helsinki for the most part of our iGEM journey – initially, we met in the spring for a coffee hour and the professional relationship strengthened through the summer and fall as we partnered on troubleshooting each other’s dry lab and organized an ethics workshop for various Nordic teams. Thanks to this partnership, we decided to include Rosetta in our dry lab modelling.

4. Publications: The iGEM team from Maastricht organized a peer-reviewed journal in the summer. We were ecstatic to know that our article got voted to be published in the journal. We are thankful to the MSP team for allowing us this opportunity and helping us hone our academic writing skills through peer review. We were approached by the iGEM Taiwan teams for a “I’ve Gotta PhD” initiative for which we contributed an article on the mental health effects of having a chronic inflammatory disease among patients.

5. Entrepreneurship: The University of Copenhagen has at least three different innovation and incubator hubs that guide students, employees, and others on the fundamentals of planning and launching a start-up through various workshops spread throughout the year. For CIDosis, we approached the hub at the Faculty of Health and Medical Sciences, called SUND Hub, to mentor our team. We joined the annual SUND Hub Incubator Program where we were enlightened on a wide range of topics from engagement with stakeholders and customer segmentation to regulatory pathways for medical devices. We also made a business canvas for our project.

6. Other education initiatives: Based on our survey among medical students, we discovered that 22% students did not know what synthetic biology was, and most thought it had little application in healthcare. We set out to educate other students on the importance and growing applications of synthetic biology, first targeting the high school students at a public school in Copenhagen and another high school talent program called Academy for Talented Youth (ATU). We also arranged a workshop at the Biotech Academy, Copenhagen and will be organizing a second one with personalized kits in late November.
Attributions
If not already cited in other sections of your poster, what literature sources did you reference on this poster? Who helped or advised you?