Project Overview

The Problem

Enterohemorrhagic E. coli (EHEC) causes sickness in over a quarter of a million people each year, costing billions of dollars worldwide. This bacteria lives peacefully in the gut of some cattle, but if the levels of this bacteria are high in meat that is consumed by humans, we become ill. Interestingly, 95% of the EHEC bacteria in cattle are found in just 5% of the cows. These high bacterial load cows are known as "super shedders", and are a large concern to the beef industry. If the super shedders could be identified before they enter the processing plants, the contamination of the meat and the tools used in the plant could be avoided.

That was exactly the goal of our project: to design and build a biological system capable of detecting these supershedding cows.

The Solution

Before embarking on a project like this we began discussions with industry that we kept going throughout our project. We believe that research aiming to solve a problem should have input from all involved parties at all times. This core belief of our team has led us to design a system that can achieve the technical requirements we asked of it as well as being in line with what the industry wants in terms of a sensor. More on our user-focused approach to human practices can be found here.

To detect the EHEC bacteria in a sample we have developed a unique detection strategy that borrows from previous iGEM projects and commercially successful testing platforms. We have designed DNA binding proteins that allow us to capture sequences only found in the pathogenic E. coli coupled with a chemically modified protein nanoparticle that acts as a rapid catalyst to create a readable colour change in a matter of seconds. To aid in tuning our system we created a mathematical model to predict the amount of protein needed for varying levels of sensitivity, as well as animating two qualitative models to show how our system works. Finally, we designed a physical prototype of our system and were able to obtain some preliminary data as to its functionality. More on the scientific details of our project can be found here.

As well as focusing solely on our project, we felt the need to give back to the iGEM community as a whole. Early in the planning stages of our project our team was looking into past projects and found a staggering number of biosensors. By joining forces with Paris-Bettencourt's iGEM team we have created the first database of sensors created by iGEM teams, SensiGEM. This tool will aid in streamlining the design process for future teams, as well as giving information to the general public about the awesome projects iGEM teams worldwide have been involved in. More on our collaboration can be found here.