Contribution

Overview

Driven by the mission to pursue a project with impact in the field of synthetic biology, particularly in therapeutics, our team underwent extensive research and brainstorming. Guided by our supervisors’ advice and indications, we discovered that the issue of worldwide low medication adherence is a striking point of concern. Therefore, we explored the ways we could potentially help in combatting it, integrating both our members’ and supervisors’ expertise. This way, GutFeeling came to existence!

Specifically for Utrecht, we compiled a detailed handbook and documentation package so that the next generation can build on our work. In the lab, we developed a protocol for quantifying L-DOPA and established the use of zebrafish as a living model system, accompanied by a full set of protocols and a user manual. These resources make zebrafish more accessible as a general model for future iGEM projects. Through our Human Practices work, we looked at the multilevel perspectives (MLP) of HP, drafted policy and regulation suggestions for live-bacteriotherapy, and shared our perspectives in the Vector Journal, ensuring our ideas reach both scientific and policy audiences. On the educational side, we created innovative materials to engage diverse audiences: a plasmid-design card game, age-specific lesson plans for schools, and a Dungeons & Dragons inspired campaign that teaches synthetic biology concepts through storytelling and play. Our modeling team contributed two key frameworks: a Flux Balance Analysis (FBA) model to predict L-DOPA production, and a growth model to study plasmid interactions and population dynamics. Together, these contributions reflect our commitment to leaving a lasting impact both by moving the field of microbial therapeutics forward and by equipping future iGEM teams and the wider community with tools, knowledge, and inspiration.

Lab

L-DOPA quantification protocol

For our project, we wanted to measure the amount of L-DOPA produced by our genetically engineered bacterium, however we struggled to find a complete protocol that fit our needs. Because of this, we finetuned our own L-DOPA quantification protocol that can be found on the experiments page.

In addition to the protocols established by the 2024 iGEM team CSMU-NCHU-Taiwan, which quantified and extracted L-DOPA from plants, this now offers future iGEM teams the protocols for quantification of polar molecules in three different biological matrices; FBS, LB, and plant leaves (Nicotina benthamiana).

The Zebrafish Guide; Swimming for all!

Utrecht iGEM 2025 team is the of the rare teams to use zebrafish larvae in the competition, it has been a long learning process that involved a lot of tedious research. From our experience we came to a conclusion that a handbook with basic information about this model is needed, since there haven't been many projects like this in iGEM previously and it is a lot more difficult to find information about zebrafish larvae as opposed to adult fish.

To help any future teams wanting to use zebrafish as a model organism, we have gathered all of this information in a single guidebook available on our Resources page. Next to this information, the document includes protocols, as well as tips for designing a project based on zebrafish models and how to navigate the use of zebrafish in your iGEM deliverables.

Our aim with this guidebook was to take any aspect of zebrafish work we struggled with or spent a significant amount of time researching on, and to hopefully spare future teams working with zebrafish the same time and trouble.

Human Practices

Vector Journal and the use of Innovation Science for HP

In our submission to the Vector Journal (see Resources), we provide an overview of theoretical frameworks from Innovation Science and argue for their use in iGEM. Furthermore, we analyzed how past teams have engaged with theoretical frameworks from Innovation Science, and how effective that approach ended up being. It became evident that few iGEM teams from previous years utilised theoretical frameworks from Innovation Science for HP. We also showed that teams whose work aligns more closely with the aspects of a framework had a tendency to perform better in their HP, highlighting the potential benefits of their use.

Based on this, we made a recommendation to use either Multi-Level Perspective (MLP) or Strategic Niche Management (SNM) as theoretical frameworks to guide their HP. We hope to have motivated teams to strategically plan their HP work using a theory-driven design, and provided a starting point for them to explore theoretical frameworks for this purpose.

On top of the recommendation to use MLP or SNM as theoretical frameworks for iGEM teams to base their HP on, our own HP page can serve as an example on how a MLP-based HP approach might look. Our HP page, despite being a long read, provides a structure that other teams could follow or use as an example for MLP-based HP, and provides inspiration for the stakeholders and dimensions to investigate.

Policy Regulation that a GMO Living-Biopharmaceutical Should Meet

As a part of our human practices, we have really dove into the industry and regulatory standards, and we expectedly confirmed that a lot of work and research goes into the development of therapeutics. However, we also found that it can be particularly difficult to navigate in this area of human practices.

The two biggest regulatory bodies, European Medicines Agency (EMA) and Food and Drug Administration (FDA), set the tone for a very big part of the industry, as they are the deciding factors that determine whether or not a product meets all the safety and efficacy requirements to be on the market. For small drug molecules these requirements are clear, they are easy to find and most of the time the approval process is straightforward. However, it is not the case for Living Biopharmaceuticals and GMOs.

When we were looking for specific guidelines, trying to establish what safety and efficacy requirements our bacteria based delivery system should be, we found out that the guidance is a lot more ambiguous and not so straightforward. Thus, we made this guide where we have gathered safety and efficacy criteria from these two agencies that would

Education

The Plasmid Game; The greatest hit since canned tuna

The plasmid game is an activity that we made during the early stages of our project. We wanted the game to be engaging and interactive, adjustable to all age levels, inspiring critical thinking, and for it to be openly available for public use.

We have used this game with adults, kids of all ages and backgrounds, and it has been a constant hit. It is a fun activity that can be easily adjusted in detail and complexity to meet participants' interests and achieve the learning goals. It was one of the most simple ideas we had, but somehow it ended up being one of the most exciting.

For example, instead of straightforward prompts used in schools, in university we changed them to real-world scenarios. Additionally, we have some blank plasmid building blocks that players can customize to their problem and thus enhance the complexity of the game. Everything you need to start playing the plasmid game can be found under the Resources page. We would love to see this game develop and grow within the iGEM community. With new projects and ideas it will be exciting to see how the plasmid game will branch out, perhaps we will even get multiple editions…

Pseudomonas' Palace: iGEM meets DnD

Since several people on our iGEM team were big fans of the tabletop roleplaying game Dungeons and Dragons and some even had experience with making and running their own adventures in the game, we set out to create an educational one-shot that teaches its players the basic concepts of synthetic biology through a series of in-game challenges.

We have created this adventure to be playable with the free to play rules of 5th edition Dungeons and Dragons, so that anyone who would want to could run the game with the resources we have provided on the resources page.

Modelling

Software tool that allows comparison of three different growth models based on plate reader data

We wanted a model to extract valuable information about bacterial growth, comparing growth rates and max capacity primarily. The reason for this is that Stirling et al. (2017) indicated that kill switches always have a low level expression of the toxin, even when they are not induced. This impacts growth and means that kill switches are stable for only a finite amount of generations. Modeling these parameters can provide insight into how stable our constructs are, and if they might be outcompeted by other bacteria they would encounter in the gut.

Therefore we built a Matlab code that compared the accuracy of 3 different but widely used growth models, the exponential, logistic and Gompertz model. These models have 1, 2 and 3 free parameters, respectively. Comparing models with different numbers of free parameters is bad practice, so we made the model calculate and compare performance based on the Akaike information criterion.

After fitting it to self-obtained growth data from both Escherichia coli and Pseudomonas alcaligenes we concluded that the Gompertz model performed the best. To further improve on our efforts we looked in literature to use the Gompertz model even better. After additional literature study we found a very recent paper that detailed a parameter estimation method for the Gompertz model that was better than previous methods. We tried to incorporate this into our model, but unfortunately could not get it to work in time for the wiki freeze.

However, we still believe our growth model can contribute to future teams. It has the capacity to analyze a 96-well plate reader experiment with many repeated measurements. Based on the conditions it will group measurements together if they and compare different conditions amongst themselves with ANOVA. It will exclude wells from rows or columns that are marked as 'Empty'.

We also wanted to help other iGEM teams understand how to interpret growth models like the ones we used. So we decided to make an educational tool that allows users to change the growth rate, max capacity or lag time and visually see the effect on simulated graphs for the three models. On the wiki page Dry lab - Growth models we have posted a video where we demonstrate the tool, which we recommend checking out. This educational tool is available as a free resource.

Flux Based Analysis for Pseudomonas species extended with gene product reactions

Flux Based Analysis (FBA) is a type of modeling that maps the metabolic network and fluxes in that network. It is a constraints based model that assumes steady state. For our project we added the reactions needed for L-DOPA synthesis.

Additionally, in our project we ran into an issue that the toxin of our kill switch degrades mRNA. However, the FBA we used did not have gene product reactions (GPRs), which allow different gene expression and gene-metabolic interactions. We could therefore also not perform knock-in screening of genes that would increase or decrease yield. So we decided to add GPRs to the model.

This massively expands the capacity of the model. It can now be used to study the effects of knock-ins, differential gene expression and gene-interactions and networks. This can not only be used for L-DOPA synthesis, but for any other metabolic study of Pseudomonas species. We think this is a valuable contribution to future teams. We will provide the code as a resource.