Introducing...
A new superpower we have given the gut microbiota member E. coli Nissle 1917 to dampen inflammation in the gastrointestinal tract of IBD patients. A true hero for real probiotic gut force!
Inflammatory Bowel Disease (IBD) is an umbrella term that comprises conditions such as Crohn’s disease (CD) and ulcerative colitis (UC). Patients suffer from chronic inflammation in the gastrointestinal tract that leads to symptoms like bloody stools, diarrhea, abdominal pain and fatigue. As of today, the cause of IBD is still unknown and there is no cure available. Current therapies are systemic and can lead to severe side effects. Furthermore, the therapies’ costs are causing a significant economic burden on the national health care system. We, the 2022 iGEM team from the University of Zurich, want to tackle the lack of targeted treatment options by harnessing the power of the gut microbiome to help IBD patients and increase their daily quality of life. On our mission, we have divided ourselves into three groups to build the fundamental pillars of our project.
1 in 250 people in Switzerland suffer from IBD
7.8 x higher costs on Swiss health care system than non IBD-patients
4 drug classes used only to manage symptoms
The IBD NanoBiotics Wet Lab team has been dedicated to designing and testing our engineered E. coli Nissle 1917. Equipped with new genetic circuits to sense nitric oxide, produce and secrete anti-TNF-α nanobodies, our chassis has started its mission to dampen inflammation.
ResultsThe IBD NanoBiotics Human Practices team had the aim to connect our vision for a new therapy to the world and connect the world to our project. We have focused on integrating patients and experts to develop a solution targeted to their needs. Educating the next generation of researchers has been an additional point of focus for the team.
Human practicesThe IBD NanoBiotics Dry Lab team has developed an exploratory model to simulate the interaction between artificial infection sites in the gastrointestinal tract and the diffusion of the secreted nanobodies based on a 2D grid. The model aims to estimate essential parameters for the best therapeutic efficacy.
Modelling