Since our establishment in 2007, iGEM Toronto has proudly represented the University of Toronto at the undergraduate level of this research competition. The outstanding commitment and dedication of members from previous years has led to the awards of 2 Gold Medals, 3 Silver Medals, and 4 Bronze Medals for our projects.
This year, iGEM Toronto is designing a cell-free detection system to detect oak wilt, a fungal disease caused by Bretziella fagacearum.
2020
iGEM Toronto built upon the work of our gold medal winning 2019 project and further expanded our efforts in optimizing the catalytic activity and thermostability of the PET hydrolases PETase, MHETase and LCC. We further expanded our machine learning model by introducing transformer architecture and vastly increasing our training sequences. We also improved our rational design by including new tools that improved the stability of regions outside the active site and enhanced the active site’s proximity and interactions with the Polyethylene terephthalate (PET) ligand. We believe that this work has brought us closer to developing a low cost microbial solution to the recycling of plastic textiles.
2019
iGEM Toronto used machine learning and rational design to optimize the catalytic activity and thermostability of the Polyethylene terephthlate hydrolyzing enzyme PETase. Further, we used a p-nitrophenol butyrate in vitro assay to confirm that our PETase variants improved upon the wildtype PETase variant. With further optimization, we believe PETase may offer an eco-friendly and cost-effective solution to industrial plastic recycling efforts.
2018
iGEM Toronto designed a system for the flotation of Escherichia coli using gas vesicle proteins (GvPs) as a novel cellular separation technique for bioremediation processes. Shapiro et al., (2018) engineered a GvP-producing plasmid using arg1 from Aphanizomenon flos-aquae and Bacillus megaterium to synthesize these echogenic structures and observed that high expression enabled E. coli to float. Our goal is to replicate and improve their flotation results by modifying arg1 to achieve consistent flotation using a specific induction protocol. Upon sorption or uptake of pollutants or valuable materials, this technique could allow for simpler extraction of pollutant-harboring or heavy metal-bound bacteria.
2017
iGEM Toronto characterized in detail a novel light-activated gene regulation system that combines the DNA-binding region of LacI with the light inducible LOV (Light Oxygen Voltage) domain.We then computationally modelled the structure of our protein and identified key mutations to optimize its activity. We designed and modelled a light activated switch to control CRISPR-Cas9 activity by putting guide RNAs and anti-CRISPR proteins under LacILOV-regulated promoters. We further designed and prototyped hardware to pave the way for our system to be used in stem cell cultures.
2016
iGEM Toronto used machine learning and rational design to optimize the catalytic activity and thermostability of the Polyethylene terephthlate hydrolyzing enzyme PETase. Further, we used a p-nitrophenol butyrate in vitro assay to confirm that our PETase variants improved upon the wildtype PETase variant. With further optimization, we believe PETase may offer an eco-friendly and cost-effective solution to industrial plastic recycling efforts.
2015
iGEM Toronto proposed to develop a new cost-effective bioremediation technology to reduce the accumulation of toxins from oil sands tailings and increase the rate of tailings ponds’ reclamation activities. We created a genetically modified Escherichia coli bacterium that will metabolize toluene toxins, develop a pro-gram simulator to show the potential of its use in tailing ponds, and formulate a policy framework for the industrial use of this technology.
2014
iGEM Toronto proposed to use a “self-deleting” CRISPR/Cas9 plasmid as an alternative approach for genetic safeguard system.
2013
iGEM Toronto characterized in detail the decision-making machinery in E. coli that decides between a stationary, low growth state and a mobile, high growth state. We developed a semi-high throughput procedure to measure several biochemical parameters in parallel in a microtiter plate format and characterized wild type and knockout strains, as well as strains that overproduced relevant factors through expression plasmids we had constructed, in a multitude of stimuli conditions.
2012
iGEM Toronto designed two constructs for the purpose of engineering Arabidopsis thaliana as proof of concept for further studies of feasibility in crops. The first construct would allow for extracellular secretion of Aspergillus phytase from Arabidopsis roots – allowing the plants to utilize the accumulated forms of soil organic phosphorus (primarily, phytate), which otherwise would not be available to the plant. The second construct, building on Yale’s 2011 project, aimed to increase the range of tolerance to low temperature stress in A.thaliana by incorporating a Rhagium inquisitor antifreeze protein and ensuring it is constitutively expressed in the plant.
2011
iGEM Toronto proposed a magnetite synthesis pathway in E.coli that could be used to develop a novel gene expression system utilizing magnetic fields. For these purposes, the Mms6 gene from Magnetospirillium Magneticum AMB-1 would be fused to ToxR from Vibrio cholerae.
2010
iGEM Toronto aimed to increase the efficiency of polyaromatic hydrocarbon (PAH) degradation through the synthetic construction of several variations of the P.putida catechol degradation pathway in E.coli. Ultimately, channeling of different pairs of enzymes can be introduced to target pathways in endogenous tailings ponds species (e.g. P. Putida) for the application oil sand tailing pond bioremediation.
2009
iGEM TorontoMaRSDiscovery has taken an interdisciplinary approach to systematically investigate how nature implements metabolic channeling and how this knowledge may be exploited for biotechnological applications, such as the production therapeutic molecules and biofuels and the degradation of toxic wastes.
2007
iGEM BlueGenes developed a simple two-input-one-output light directed feedforward neural network using E. coli cells, with the ultimate goal of being trained to function as different types of digital logic gates.
2005
The joint team between University of Toronto and Waterloo designed a temperature tunable LacI sensor that produces a colorimetric shift from green fluorescence to red fluorescence as temperature increases and LacI repression decreases. Additionally, a Bacterial Etch-A-Sketch was designed where a LacI/TetR GFP system could be induced and repressed by the exogenous addition of lactose and tetracycline, respectively.