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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


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.

Fig. 1. Visual representation of the usage of the CIDosis patch and the engineering and scientific approach. 1: The patch collecting sweat from the skin. 2: The layers in the patch. 3: The scientific receptor engineering. 4: The patch after it has changed color. 5: The image-analyzing app.
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.

Minimal Biosensor Design
The initial, minimal, biosensor design builds on the split-ubiquitin based Membrane Yeast Two-Hybrid method (MYTH) [1], 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 [2]). 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.
Fig. 2. Minimal biosensor design. Complementation of the C- and N-terminal halves of Ubiquitin results in their recognition by deubiquitinating enzymes, leading to cleavage and release of the bound LexA-VP16 transcription factor.
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 [3]. 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.
Fig. 3. Intermediate biosensor design. Split TEV protease complementation leading to cleavage of the linker tethering the transcription factor LexA-VP16 to the membrane.
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 [4].

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.
Fig. 4. Advanced biosensor design. Split TEV protease complementation leading to cleavage of a TEV protease cut site in GPA1, thereby initiating gene expression through the yeast pheromone pathway.
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. 5).

Fig. 5. Comparison of the dynamic ranges of our designs. Plotting reporter signal strength against interleukin concentration in uM reveals a significant difference in sensitivity between the three designs.

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. 6). This tool has the potential to improve our troubleshooting in the future.

Fig. 6. The effect of reporter toxicity on the reporter concentration. The amount of noise applied to all variables increases with reporter concentration, which leads to highly variable reporter concentrations (illustrative)

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, as they gained affinity to the beta subunit instead of losing affinity for it. Based on these findings, we articulated a refined framework for engineering signal transduction in our biosensor.

Fig. 7. Structural model of a GPA1 mutant variant with a TEV cleavage site inserted. The red region marks the modified ENLYFQG cleavage sequence. It is located close to the N-terminal α-helix that mediates a significant amount of the binding affinity towards the β-γ complex.
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.

Fig. 16. Structure of the CIDosis patch.

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.
Fig. 17. Longer spaced testing gives an incomplete picture of the disease

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.

Fig. 18. Mock-up of the CIDosis app.
The general scientific workflow followed the diagram seen on figure 8, with many iterations of ordering synthetic DNA, transformations in both E. coli and yeast, and performing colony PCRs.

Fig. 8. General scientific workflow.

USER Cloning

All plasmids used in this work were constructed using USER cloning - a ligase independent cloning technique for seamless fusion of several PCR products and a vector. The method utilizes a Uracil Specific Excision Reagent (USER) enzyme mix to cut out uracils from PCR products and create 8-10 bp 3’ overhangs on PCR products [5]. The uracils are introduced with the primers in the PCR reaction with a proofreading polymerase that has been engineered to allow uracils called X7 [6]. The products can subsequently anneal to vectors containing a “USER cassette”, meaning that the vectors contain cut-sites that can yield overhangs upon digestion. These overhangs are complementary to the overhangs on the PCR products of interest. The USER reaction products are ligated by endogenous ligation mechanisms upon E. coli transformation.

Yeast Genomic Integration

Yeast strains were created through stable integration by homologous recombination using a 5-assembler system (unpublished). The yeast is transformed with five vectors that are integrated into site 3 in chromosome X of Saccharomyces cerevisiae in a directional manner. Before transformation the vectors are linearized so that flanking 3’ and 5’ regions in each vector can be recombined with the other vectors and the integration site in the yeast genome. The 3’ region of each vector is identical to the 5’ region of the next vector in the system or an upstream region of the integration site. The 5’ region of each vector is identical to the 3’ region of the previous vector in the system or a downstream region of the integration site. See figure 9.

Fig. 9. The 5-assembler system. The biosensor is assembled by co-transforming five linearized module plasmids that contain a promoter and a coding sequence, with both being flanked by homologous recombination regions.

Luciferase Assays

To evaluate the functionality of our biosensors we used luciferase assays. The biosensor strains were incubated with a dilution series of the interleukin of interest. To measure the amount of signalling from our biosensors, nanoLuc luciferase [7] was used as a reporter. After incubation with the interleukin, the amount of luminesce was measured using a plate reader as a measure of the amount of reporter produced by the biosensors.
To construct our modular biosensors, we performed 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. We used integrative plasmids, so as to establish yeast strains with stable genomic integration of our genes. To this end, our different modules we targeted for genomic integration into chromosome X site 3 using the homologous recombination based 5-plasmid assembly system (unpublished) available in our supervisor’s lab.

In total, the 53 different module-specific constructs enabled us to create 21 yeast strains relevant for our biosensor designs, allowing us to test the feasibility of the different biosensor variants for key aspects in interleukin sensing.
Fig. 10. Yeast colony PCR. A band at 1500 bp meant no insertion into the locus, while a band at 1000 bp implied successful insertion of the five vectors. Arrow a and b denote positive and negative bands respectively.

Testing Receptor Localization

Through our extensive subcellular localization assays for all the three designs, we found that localization issues of the interleukin receptor proteins and accessory proteins were prominent for several of the proteins.

Fig. 11. Example of subcellular localization assay result. sIL-10R1-Cub is shown to primarily localize to the plasma membrane, in the endoplasmic reticulum, and in small inclusion bodies near the membrane.

Cleavage of membrane-bound transcription factor

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.

Fig. 12. Luminescence assay based on cleavage of a membrane-bound transcription factor. Cells were expressed without (glucose media) and with (galactose+raffinose media) induction of the TEV protease. A 1300-fold increase in luminescence was seen upon induction of the TEV protease. The data shown is the average of three biological replicates.

GPA1 Switch Functionality

The different GPA1 mutants were tested in the context of an adenosine biosensor employing the human adenosine GPCR receptor A2A(R199A) (unpublished) in S. cerevisiae, previously developed in the Kampranis lab. By comparing our engineered GPA1 proteins to the wildtype, we observed that the amount of luminescence produced by the biosensor was higher when cells were incubated in galactose + raffinose media (and the TEV protease was induced) for all versions of GPA1, including the wildtype. This infers that the rise in luminescence with the change of media might be caused by another mechanism than cleavage of GPA1. Thus, it was not possible to determine whether cleavage of our modified GPA1 variants by the TEV protease was the reason for reporter gene expression in our induction assays.

Fig. 13. Characterization of modified GPA1 proteins in adenosine biosensor. The biosensors were grown in either glucose media or galactose + raffinose media which repressed or activated expression of a TEV protease. The biosensors were further grown with a dilution series of adenosine.

Complete Minimal Biosensor Interleukin Assay

No correlation between interleukin concentration and luminescence was observed for the minimal IL-6 and IL-10 biosensor strains at any incubation time.

Fig. 14. Luciferase assay of the minimal interleukin-6 biosensor. The amount of luminescence observed after incubation with a dilution series of interleukin-6 for 1, 3, 14 and 22 hours.


Several experiments were identified for optimization of the biosensors. 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 practices were instrumental in both developing the science behind the CIDosis patch, and placing/establishing it in the larger context of healthcare. Both in the initial phases of the project and all throughout the project period, we have engaged with stakeholders and experts that could guide our decisions.

Conceptualizing CIDosis

From the conception of the project, our choice to dedicate the patch to measure general inflammation rather than for diagnostic purposes was guided by expert advice from doctors and researchers within the field. Through conversing with specialists in this initial phase of the biosensor design, we decided to make the following wet lab modifications:
  • Choosing interleukins for biomarkers, as they are abundant in general inflammation.
  • Making a modular design to accommodate the vast number of interleukins that experts deemed could be of clinical interest.

Designing the CIDosis Patch

In total, we engaged with 10 experts ranging from researchers at the University of Copenhagen to doctors in the United States, and received input from 86 CID patients across four interviews and two surveys. While the first survey was aimed at CID patients in general, our second survey specifically targeted Crohn’s and Colitis patients.
The results confirmed the wish for more frequent and accessible testing for inflammation (fig. 15) and provided us many ideas for central design features of the patch, including:

  • Patch colour - we were made aware of the counterintuitivity of providing CID patients, who do not wish to be defined by their illness, with a very noticeable patch. Concerns about skin color differences were also brought up, leading us to make the patch see-through. This, in turn, would also make any patch color change much more visible.
  • Clear instructions - we made a clear user guide for the patch detailing how to use the patch correctly and record/interpret the received results, due to reported concerns regarding accidental misuse and unclear instructions.
  • Wear time - our modeling results showed that the biosensor in the patch is best able to distinguish between high and low inflammation around the five hour mark, which fits perfectly within the time period users said they would be willing to wear the patch for.

  • Fig. 15. Snippet of survey results. Survey results showing the frequency of CID testing and desired frequency of wearing the CIDosis patch.

    Ethical Considerations

    Due to the nature of our project, ethical concerns surrounding working with patients with CIDs and developing a “device” such as ours quickly surfaced. Our considerations spanned from our patch potentially causing mental distress to the patients, to ensuring the safety surrounding GMO usage. Patient interviews, literature findings, and discussions with our fellow Nordic iGEM teams were invaluable in resolving these issues.
More of Our Work
Apart from the work directly related to developing the CIDosis patch, a lot of our iGEM journey was dedicated to interacting with the iGEM community, as well as different local communities to spread the word of science, help each other learn and grow, and develop new and exciting skills ourselves. Under here you’ll find a handful of the things you can read more about on our wiki!

Our Ethics Guide

Since ethical considerations surrounding working with chronically ill people was such a big part of our project this year, we decided to develop an ethics guide as our contribution to the iGEM community. The guide was developed in collaboration with SynthEthics, and serves as a six step guide for future iGEM teams to analyze and reduce moral ambiguities in their iGEM projects and ideas. We used CIDosis and the iGEM Lund 2020 team’s project, Protecto, as example cases for easy understanding and interpretation. Do give it a read!

Children’s Book

To inculcate passion for science and synthetic biology among children from an early age, we made the first installment of what we envision to be a series of children’s books. The first book, “My Sister Can Talk with Bacteria”, explains the concept of bacterial transformation, while future books will explain other synbio techniques, such as PCRs or protein fusions, or cellular processes such as cell division. With this, 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!

Partnership with iGEM Team Aalto-Helsinki

We partnered with iGEM Team Aalto-Helsinki for the most part of our iGEM journey. 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 models and organized an ethics workshop for various Nordic teams.


As part of iGEM Team MSP-Maastricht’s initiative to produce a peer-reviewed journal, we wrote an article explaining the science behind our project and were 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 also approached by the iGEM Taiwan teams for their “I’ve Gotta PhD” initiative for which we contributed an article on the mental health effects of devices such as our patch on patients with CIDs.


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.
Supervisors: Sotirios Kampranis, Nanna Heinz, Karel Miettinen, Jon Fugl, Nattawat Leelahakorn, Cecilie Cetti Hansen, Iben Egebæk Nikolajsen & Jonas Hansen.

Thank you to our sponsors!

Scientific References

[1] - Snider, J., Kittanakom, S., Curak, J., & Stagljar, I. (2010). Split-ubiquitin based membrane yeast two-hybrid (MYTH) system: A powerful tool for identifying protein-protein interactions. Journal of Visualized Experiments.
[2] - Dossani, Zain & Apel, Amanda & Szmidt‐Middleton, Heather & Hillson, Nathan & Deutch, Samuel & Keasling, Jay & Mukhopadhyay, Aindrila. (2017). A combinatorial approach to Synthetic Transcription Factor-Promoter combinations for yeast strain engineering. Yeast. 35. 10.1002/yea.3292.
[3] - Wehr, M. C., Laage, R., Bolz, U., Fischer, T. M., Grünewald, S., Scheek, S., Bach, A., Nave, K. A., & Rossner, M. J. (2006). Monitoring regulated protein-protein interactions using split TEV. Nature Methods.
[4] - Bardwell L. A walk-through of the yeast mating pheromone response pathway. Peptides. 2005;26(2):339-350. doi:10.1016/j.peptides.2004.10.002
[5] - Geu-Flores F, Nour-Eldin HH, Nielsen MT, Halkier BA. USER fusion: a rapid and efficient method for simultaneous fusion and cloning of multiple PCR products. Nucleic Acids Res. 2007;35(7):e55. doi: 10.1093/nar/gkm106. Epub 2007 Mar 27. PMID: 17389646; PMCID: PMC1874642.
[6] - Nørholm, Morten. (2010). A mutant Pfu DNA polymerase designed for advanced uracil-excision DNA engineering. BMC biotechnology. 10. 21. 10.1186/1472-6750-10-21.
[7] - England CG, Ehlerding EB, Cai W. NanoLuc: A Small Luciferase Is Brightening Up the Field of Bioluminescence. Bioconjug Chem. 2016;27(5):1175-1187. doi:10.1021/acs.bioconjchem.6b00112

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