We assisted Melbourne with their model, and they helped us to distribute our survey in Australia in return.

As part of our collaboration with the Melbourne iGEM team, we implemented an earlier version of the outer model on MATLAB, with the architecture to include their own interaction processes. The Melbourne iGEM team aims to increase the reaction kinetics of the mevalonate pathway using their star peptide.

After the completion of our combined model, the Melbourne team realized that the products from one enzyme reaction on one star peptide node do not show a clear flow towards the node of the other enzyme reaction, where they will be consumed. Otherwise, the contour lines would trace a pattern that contains both nodes (the contour lines surrounding each node will be joined). This flow was an assumption that the Melbourne team made in the formulation of their project. More simulations are needed to verify the accuracy of that assumption.

In exchange for our assistance with the diffusion dynamics of their system, the Melbourne team assisted us with validating the diffusion solver of the RIOT Model’s inner model component. We provided a test case where lactate was released from the center of the bacteria, with an impermeable bacteria membrane. The Melbourne team showed that the concentration field within the bacteria homogenized within 200 milliseconds (see Figure below), which is what one would expect. This validated the diffusion component of our inner model.

Figure: Plot of lactate concentration field in the bacteria in cylindrical coordinates, with respect to time (plotted by Melbourne team using MATLAB).

With the help of our collaborators from the Melbourne iGEM team, our survey was distributed in Australia via an online link.

The raw data obtained from the Australian survey are as follows:

The survey results from Australia illustrated in the above table shows that 32.8% of participants were very receptive to the RIOT System (rating it a ‘5’), despite many of them believing that it is not completely safe - only 6% rated safety with a ‘5’. For more details on the analysis of these results, please refer to the Human Practices (International Outreach).

We assisted Hong_Kong_HKUST with their model, and they helped us to validate our RIOT Sensor in return.

The Hong_Kong_HKUST team worked on the tri-stable switch, which required the full treatment of the RIOT Model system. Their intra-bacterial tri-stable switch responds to inducer concentrations in the bacterial environment. As such, the diffusion of the inducers in the environment were modelled in the outer model, and the inducers enter the bacteria at each outer point via free diffusion through the bacterial membrane.

Upon implementation, the RIOT Model was sent to the Hong_Kong_HKUST team to experiment with.

The Hong_Kong_HKUST team kindly helped us to measure the sfGFP expression under the control of different lactate sensors over a range of lactate concentrations. However, the bacteria were unable to grow and the blank media had very high readings. Therefore, we could not use these results to compare with ours.

Hong_Kong_HKU helped us to distribute our survey in Hong Kong.

With the help of our collaborators from the Hong_Kong_HKU iGEM team, our survey was distributed in Hong Kong. They distributed our survey in their university, the University of Hong Kong, and to the general public. To cater to language barriers, they also did a Chinese translation of our survey to ensure that the survey participants understood the terminologies used in our survey.

The raw data obtained from the Hong Kong survey are as follows:

The survey results from Hong Kong shown in the table above illustrate that 12.5% of surveyees were very receptive to the system (rating with a ‘5’), and 16.7% of them rated safety with a ‘5’. For more details on the analysis of these results, please refer to the Human Practices (International Outreach).