Team:Bielefeld-CeBiTec/Medal Criteria

Achievements

We were able to achieve a gold medal and a Top 10 ranking.










Nominations

We got nominated for Best New Application and Best New Basic Part.










Special Prices

We applied for the following special prices:

Best Education

Synthetic biology is a very complex topic and difficult to understand for young children and even adults. Therefore, we created an educational podcast ‘Ask Nici’, which answers questions asked by children. Our goal is to introduce a broader audience to synthetic biology, independent of age and prior knowledge, and show them the exciting world of science to engage with. To accomplish that, our main focus are biological questions of children’s everyday life, especially in times of the pandemic. We explain the basic concepts to give everyone the opportunity to understand the background of synthetic biology in everyone’s life. Thereby, we give examples how it can be used to help humanity in a sustainable and efficient way. We shared ‘Ask Nici’ on several platforms and integrated it in an educational program of the largest German biotechnology student association btS to engage with schools. To reach people all over the world, we created a handbook which was translated into 15 languages.

Best Model

In our project, we created a plant-based detection system for chemical weapon degradation products, for which a functional and specific receptor is crucial. Therefore, we computationally designed a receptor based on a ribose binding protein to bind a given chemical. For this we utilized Rosetta and combined it with EvoDock, a Python script that adds an evolutionary approach, and increased the efficiency of the design process. We experimentally showed the binding of the chemical by the computationally engineered receptor and thereby proved our modeling success. This was performed in two approaches, in vitro binding analysis and in vivo by the activation of a signaling cascade resulting in the induced expression of GFP upon specific ligand binding in bacteria. Our engineering pipeline can be re-applied to engineer receptors for countless applications. Following our detailed workflow descriptions, future iGEM teams are able to design their own specific receptors and binding proteins.

Best Plant Synthetic Biology

In our project, we created a plant-based biosensor in Nicotiana benthamiana to detect remaining chemical weapon degradation products of past wars. For the detection of our chemicals of interest, we engineered specific receptors using computational protein design. We created a signaling cascade in combination with a receptor, to activate expression of a reporter upon chemical detection. Therefore, we contributed the novel reporter system RUBY and were able to show that its change in leaf color is easily visible, stable over time and its expression can be induced. We proved the functionality of the signaling cascade and the specificity of the receptor in bacteria. As a crucial factor, we were able to prove that N. benthamiana took up several chemicals of interest in a hydroculture experiment. Altogether we were able to show that our plant-based biosensor can be realized for the detection of chemical weapons degradation products.

Competition Deliverables

We completed the following Competition Deliverables by creating a wiki, submitting a presentation video and filling out the judging form.

Attribution

On our Attribution page we showed who did what in the project and who we want to thank for helping us.

Project Description

We have a page describing our project and our inspiration.

Contribution

We created a handbook with important information about working with phototrophs. This handbook can be extended by future iGEM teams. Click here to learn more.

Engineering Success

We demonstrated engineering success by optimizing the signal cascade in bacteria and implementing our designed receptors.

Collaboration

We organized and participated in several collaborations.

Human Practices

In order to develop our project idea and achieve the goal to design a plant-based detection system in the best possible way, we have talked to many different experts during the year in order to further develop our project. Read more on our Human Practice page.

Proposed Implementation

We envisioned how our product would be implemented in the real world, which we documented on our Implementation Page.

Integrated Human Practices

We discussed our project with several experts and incorporated their advice.

Improvement of an Existing Part

During our project we improved the red fluorescent protein mRuby3 (BBa_M50009) to have an enhanced stability in low pH environments (BBa_K3900021).

Project Modeling

We computationally designed a receptor based on a ribose binding protein to bind a given chemical. For this we utilized Rosetta and combined it with EvoDock, a Python script that adds an evolutionary approach, and increased the efficiency of the design process.

Proof of Concept

We successfully transfected RUBY into N. benthamiana as an inducible reporter. Furthermore, our computationally designed receptor is activated by benzenetricarboxylic acid, which can activate the signaling cascade in E. coli.

Partnership

Together with the iGEM Team Marburg we built up a strong partnership and created a phototroph community platform for all the iGEM teams working with phototrophs.

Education & Communication

We created a podcast called ‘Ask Nici’. It is a format in which questions that children have asked us about biology are answered in a way that no previous knowlegde about biology is required. More detailed information can be found here.

Excellence in Another Area

We examined the regulations of releasing a GMO, the laws that should be considered, the problems that will occur and further topics. By releasing a GMO several views should be taken into consideration. An important aspect are regulations and laws. For further information read our GMO page.