Our FerriTALE

The Problem

Enterohemorrhagic E. coli (EHEC) causes severe illness in over a quarter of a million people each year in the United States (Centers for Disease Control and Prevention, 2011), costing us billions of dollars worldwide in food recalls and treatment (Russo and Johnson, 2003). From the developing world to North America and Europe, we frequently experience EHEC outbreaks in our water (Okeke, 2009), food (Mermin and Griffin, 1999), and beef (Cross, 2012), causing deaths, hospitalizations, massive economic losses and an overall loss of consumer confidence in food safety. These bacteria normally live peacefully in the gut of cattle, but when they are present in the water, vegetables or meat that we eat, they can result in illness and even death (Centers for Disease Control and Prevention, 2011). Because of these dangers, water treatment stations and slaughter houses regularly test for EHEC. Standard industry tests use cell culture and PCR as gold standard techniques but these take between 18 to 40 hours to give a result (Junillon et al., 2012). On top of being time-consuming, current detection only provides data for EHEC levels in samples of meat well after the cattle has been processed. Pre-screening techniques could act earlier and be a promising in preventing the distribution of contaminated meat and reducing the spread of EHEC into water and food supplies.

In the cattle population less than 10% of animals produce more than 95% of the EHEC produced by the all cattle (Chase-Topping et al., 2008). These cattle with such high bacterial loads are known as "super-shedders" as they contain anywhere from 100 to 100,000 times as many colony forming units of these bacteria (Chase-Topping et al., 2008). Super-shedders are kept in holding pens with normal cattle. By excreting high amount of EHEC, they can lead to contamination of ground water, vegetables and surrounding cattle. In the case of other cattle, a contaminated hide of an animal increases the risk of spreading the contaminant to the meat where it could causing illnesses to consumers. If super-sheddering cattle could be detected in feedlots and prior to their entry the processing plants, a significant risk for the contamination of water, vegetables, and meat could be eliminated.

Our Goal: to design and build a synthetic biology system capable of detecting EHEC, detecting super-shedding cattle, and preventing contamination.

The Solution

Before embarking on our project, we asked ourselves “how does the industry view this problem?”. Therefore we began discussions with the industry that continued throughout the development of our project. This information was then used to inform the design of our project. We believe developing a product-based project should involve both the industry’s and end-user’s input at all steps of development. Their input could then be incorporated into the design of the overall project, addressing their concerns and needs. This core belief has led us to build a system for the needs of the industry. To read more about our user-focused, informed design approach to human practices, click here.

To detect EHEC bacteria in a sample we developed a unique detection strategy combining tools available in iGEM as well as the literature. We 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 DNA binding proteins needed for varying levels of sensitivity, alongside two spatial models to demonstrating 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.

In addition to the EHEC biosensor we have been working on, we felt the need to give back to the iGEM community as well. Early in the planning stages of our project our team looked into past projects and found a staggering number of biosensors. By joining forces with Paris-Bettencourt's iGEM team we created the first biosensor database, created exclusively by iGEM teams, named SensiGEM. This tool will aid in streamlining the design process for future teams doing projects with the theme of a biosensor. To learn more about our collaboration click here.

A summary of our approach to designing our biosensor is shown below, highlighting our reliance on modeling to predict our experiments and our collaborations with industry to inform us of what they needed in a final product, as well as how our individual components work together.