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We stated the role of each team member as well as credited everyone who has helped us along the way.

Project description

We have described what motivated us to choose this project and why it is important.


We used the antifreeze protein FfIBP for the first time in the iGEM competition, thus bringing a new thoroughly characterised basic part: BBa_K3782000
In our work on antifreeze proteins, we also created several composite parts to express RiAFP, DcAFP and FfIBP:

We built a hardware to characterise AFPs and provide the 3D model of it as well as a step by step protocol to build it and a software to use it.
We were the first iGEM team to work on and characterise tailocins, thus providing a protocol new to the iGEM community to purify them.



Engineering Success

We showed that we could apply the “design, build, test, learn” cycle in every part of our project.


  • with Chalmers-Gothenburg iGEM team, we collaborated on our blog: The transcriptome
  • with EPFL iGEM team, we collaborated on our podcast: Les OGMs en Suisse

Human Practices

In order to determine the impact our product could have on the world if it was to be really used on apricot crops, we interviewed an agricultural engineer.

Proposed Implementation

We were able to implement future scenarios for two of our treatments according to the law.



Integrated Human practices

We interviewed several experts and it had an impact on the design of our project.


We have modelled the antifreeze proteins activity as a function of their concentration and Pseudomonas population dynamics when exposed to tailocins.

Proof of Concept

We purified the antifreeze proteins FfIBP and RiAFP and confirmed their activity on water freezing. We showed that these proteins reduce frost damage on Arabidopsis. We confirmed the killing activity of our tailocins on Pseudomonas syringae pv. syringae B301D and showed that this treatment reduces this bacteria’s ice nucleation activity.

Education & Communication

  • with Chalmers-Gothenburg iGEM team, we collaborated on our blog: The transcriptome
  • with EPFL iGEM team, we collaborated on our podcast: Les OGMs en Suisse
  • with the Eprouvette, our University’s Science and Society Lab, we organised a week-end course in the lab for high school students

Special prizes


Best Education

By basing our educational event on our own iGEM research, we were able to teach a subject we thoroughly studied and skills we honed all summer, maximizing the quality of education provided to our high-school-level students. To make our event as impactful as possible, we poured over pedagogy literature to ensure the highest quality of learning for our students. After studying the question at length, we decided to teach each concept in conjunction with a hands-on experiment. We chose to host only a small group of motivated students in order to nurture their connection to science one-on-one, encouraging questions and opinions on their part. The weekend was a resounding success – our students emerged with a working understanding of synthetic biology and microbiology in general, and all expressed enthusiasm at the idea of pursuing this kind of research as a career.

Best Hardware

Nominated 🦾

Our project requires a precise control of temperature under a microscope. We created: FROZONE, a precise cooling device that fits under a microscope, it acts like a Nanoliter Osmometer. This machine was inspired by the "MicroIce LTD" . According to them "A Nanoliter osmometer is a cooling stage mounted on an upright optical microscope. Cooling of the stage is achieved with the use of Peltier devices driven with a precision temperature controller."
Our Nanoliter osmometer, Frozone, was designed and created by ourselves. Cooling is achieved with a thermoelectric cooler controlled by a custom Python software. We also designed a vacuum chamber to minimize ambient humidity from crystallizing on our samples (using a vacuum pump or a desicant).
Put simply, we created a machine that controls the temperature of a copper plate in order to measure the Thermal hysteresis of our different sample solutions.

Best Measurement

Nominated 💪

We performed many assays to measure parameters of the solutions we produced. Our device, FROZONE, allowed us to freeze drops of AFP solutions to measure their thermal hysteresis values at various concentrations. We performed another assay to compare the damage on Arabidopsis thaliana after an overnight incubation in our AFP solution or in a simple buffer. We then measured the damage area on the plant with our own algorithm, VISION, and proved our AFPs successfully reduce frost damage.
We also performed an assay using FROZONE to measure the time it takes for a drop of solution containing Pseudomonas syringae to freeze at -15 °C, then compare that to a negative control, proving that our pathogen accelerates freezing. Similarly, we measured the time necessary for a solution of P. syringae previously incubated with our tailocins to freeze at -15 °C. These measures allowed us to prove that our tailocins are functional.

Best Model

To reduce frost damage in crops due to late spring freeze, we developed a treatment consisting of purified antifreeze proteins (AFP). To determine the optimal concentration that is needed for our protein to function on plants, we used the kinetic pinning model to simulate the TH at increasing concentrations.
Our strategy consists of using tailocins to kill the pathogen bacteria P. syringae on plant leaves. We decided to simulate the effect our tailocins would have on a population of our target bacteria, P. syringae, to determine how often tailocins should be applied in the field. The model is based on the Lotka-Volterra model.

Best New Basic Part

Nominated 💪

We submit the following part: BBa_K3782000

Best New Composite Part

Nominated 💪

We submit the following part: BBa_K3782022

Safety and security award

In designing our project, we took special care to think about possible consequences and adverse effects our product could pose to the environment and took care to minimize them as much as possible. When thinking of possible implementations, we made sure no GMOs would have to be directly released in the environment in our final product. We therefore decided to produce AFPs and tailocins, which being proteins cannot spread or persist long term in the environment. AFPs are naturally occurring proteins produced by various organisms and have no known toxic effects. Tailocins can kill bacteria, but their narrow killing range makes them unlikely to target beneficial bacteria species or have adverse effects on microbial communities, compared to broad spectrum antibiotics for example. As they do not replicate, they also raise less safety concerns as the release of engineered phages. The third approach of our projects involves modifying bacteria in the environment, which is currently banned by Swiss regulations. Nevertheless, we aimed at minimizing the risks of uncontrolled spreading of GMOs by using a phagemid, unable to replicate autonomously, instead of a phage as a modifying agent.

Best Software tool

In our project, we developed two different assays for different purposes.
The first assay called “I said freeze (ISF) assay” is used to characterize AFPs, and test AFP by their ability to lower the freezing temperatures of water. For this assay, we developed a hardware called “FROZONE” that is able to freeze or heat up water drops treated with AFPs placed on the surface of the device to a certain setpoint. This allows us to measure the thermal hysteresis, the difference between freezing point and melting point of a solution and track the freezing points between two water drops (treated with AFPs and untreated).
To be able to control the temperatures to a certain setpoint, we designed a software called “EDNA” and based on a proportional–integral–derivative (PID) controller for our device “FROZONE”.
In our second assay called “Frost Damage Treatment (FDT) assay” we assess the damage of plant leaves visible through Trypan Blue staining caused by freezing. For this assay, we developed our image processing software “VISION” based on color thresholding to identify the areas of interest of our samples.

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