Team:Calgary/Project/OurSensor/Modelling/SpatialModelling

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Spatial Modelling

Spatial modelling

In order to get a sense for how to optimally assemble our reporter and detector molecules for integration with the prototype, we used Autodesk Maya to build and analyze potential capture protein fusions in silico. In contemplating the prototype design of capture TALE detectors in the nitrocellulose lateral flow strip prototype, the wetlab team conceived the following protein fusion designs:

Figure 1. Possible versions of capture TALE protein genes fusions which could be integrated into the prototype. Figure 1A shows the TALE in isolation whereas Figure 1B shows the protein scaffolded from ferritin.

We were concerned about how the interaction of TALE detectors with the nitrocellulose substrate might reduce their sensitivity. The wetlab asked the modelling team who proposed simulating the capture proteins and nitrocellulose in Maya to answer this question. In order to determine potential for steric hinderance issues with DNA binding, we needed to know how DNA and TALEs bind together. The steps in this interaction have not been previously documented, so we animated a putative interaction in Maya. See Figure 2 below.

Figure 2. Shows a putative mechanism for TALE-DNA binding which we built using Maya.Contortions and shifting of the TALE are require for it to envelop the DNA.

The interaction between the TALE and DNA appears to require intricate contortions of the TALE and space around the periphery of the protein. The next step was to use Maya to show how the interaction of DNA with the TALE is influenced by association of the TALE with a surface such as nitrocellulose. See Figure 3 below.

Figure 3. The scaffolding of capture TALEs with a linker to surface representative of nitrocellulose alleviates geometric constraints to potentially improve TALE-DNA interactions. This image influenced the selection of proteins to be integrated into the capture component of the strip prototype.

In Figure 3A, the TALE is associated directly with a surface representing nitrocellulose, whereas in 3B, it is separated by linker sequence separating the TALE from the surface. Given the geometric constraints of the TALE-DNA interaction shown in Figure 2, the modelling team concluded that capture TALEs in the system should be bound to a protein to separate detector from nitrocellulose. From this data, the wetlab will be focussing prototype development where capture TALEs are fused to ferritin to separate them from nitrocellulose (see Figure 1B and 3B).

Animation of complete system

From the basic protein components imported into Maya from spatial modelling, we repurposed these elements to create a compelling animation to explain our completed system in the iGEM presentation. We wanted to show the complete system in a cohesive video to efficiently explain how the molecular interactions of the FerriTALE output a signal on the final prototype. Please see the video below:

Although our video is only a few seconds long, we invested a great deal of time learning how to effectively use the animation tools in Maya. Since physics of the FerriTALE biological interactions have not previously been defined, we could not use the Maya physics engine to drive the motion of the molecules. To overcome this, we used a technique called 'key-framing' where we combined a series of still frames into a fluid video.

3D Printing:

Through our collaboration with Cesar Rodriguez, a Senior Research Scientist in the Bio/Nano/Programmable Matter group at Autodesk, we have been able to expand our spatial modelling beyond the computer screen. He and his team have offered us access to the 3D printing services at Autodesk to make a tangible model of our molecules based off our Maya simulations. This has allowed our team to get a feel for the shape of our proteins, aiding the the design of our prototype, linkers, and the system as a whole.

Figure 4. (Left) The Maya animation and 3D printed model of one of our TALEs bound to DNA. (Right) A closeup of one of our 3D printed TALEs, showcasing the space-filling model we based our model on.