Team:Austin UTexas/Proof Of Concept


Proof of Concept

For our assay to function properly as a sensor for E. coli in water samples, it must be able to lyse a cell faster than its wildtype counterpart while maintaining a thorough output of signaling proteins. This design ensures that a single cell can optimize the output of signaling proteins while also amplifying the effect as progeny infect neighboring cells to repeat the same process. Ultimately, this creates an additive signal that is easily visible and recognizable by the user, as more signaling molecules accumulate within the water sample. To show our assay's potential effectiveness, we model the output of Green Fluorescent Protein (GFP), lysis time, and burst size (progeny output) of our finalized engineered T7 phage, which included a GFP and Holin Protein inserted before Gene 10 of its genome (Fig. 1). We then compared these values to that of the wildtype strain and alternative designs.


Figure 1. Final T7 Bacteriophage Design. The final design for our Mutant T7 Bacteriophage contains a GFP gene and Holin gene between genes 9 and 10 of the wildtype T7 Bacteriophage genome. The Holin gene was derived from the T7 Bacteriophage itself, notated as Gene 17.5 based on its original location. The parts of the genome that were not altered are slightly faded in order to highlight the team's alterations. Figure made by team member Harsh Madaik.


GFP Production:

To measure and display our assay's ability to effectively produce signaling molecule post-cell infection, we designed several models of T7 bacteriophage, each including a GFP gene, as a proof of concept, within a different region of its genome. We then used PineTree, a stochastic gene expression simulator, to simulate the mutated T7 bacteriophage's infection cycle and measured the average GFP proteins it produced. When stimulated, our final T7 bacteriophage design expressed an average of 12509.333 GFP proteins over 96 total simulations. (Fig. 1) This was roughly a 2238% increase from the lowest GFP expressing mutant, which included a GFP gene replacing the nonessential Gene 1.4. This output of GFP proteins shown by the simulations not only affirms our success in engineering the phage, but its sheer large output also affirms the potential to produce a strong signal in a sample. This statement is further supported when considering that the engineered bacteriophages will be infecting multiple cells to have an additive effect.


Figure 2. The average GFP output of varying T7 bacteriophage mutants derived from a set of 96 infection cycle simulations. Mutants either contain a GFP gene replacing a wildtype gene (gene replacement) or an insert of a GFP gene and Holin (Hol) genes around the T7 Bacteriophage Gene 10.


Lysis Time:

The incorporation of a faster lysis time within our final design allows the exponential build-up of a signal, as progeny are released faster from a host cell to repeat the infection process. To analyze our designed T7 bacteriophage's ability to lyse a host cell faster than its wildtype counterpart, we created a lysis time calculator to determine and compare the lysis time of varying T7 bacteriophages. Using this calculator, we analyzed the lysis time of a total of 96 simulations involving our final T7 mutant bacteriophage and compared it to the lysis time of a wildtype T7 bacteriophage. Over these simulations, final design had a median lysis time of 804 seconds or approximately 13 minutes. This time is roughly a 39% decrase from the median lysis time of a wildtype T7 bacteriophage, being roughly 1292 seconds or 22 minutes. While we found other mutants to have faster lysis time, our final design incorporated the largest production of GFP proteins with a large decrease in lysis time (Fig. 2). This combination ensured the largest possible GFP production in a short timeframe, which would then be amplified faster as progeny are released quicker to infect more cells and repeat the process.


Figure 3. The median lysis time and GFP production for different T7 Bacteriophage Mutants compared to the Wildtype variant. The data for the variants, including the wildtype, was determined over 96 infection cycle simulations.


Burst Size:

While testing our designs, we were faced with a trade-off majorly between lysis time and the burst size (progeny release) of our Mutant T7 Bacteriophages. That is, as lysis time decreases burst size naturally decreases as less time is present to manufacture progeny. However, maintaining a high burst size within a single infection cycle further increases the accumulation of a signal as more E. coli cells are infected within a sample. To ensure our final design produces the largest amount of progeny, we created a burst size calculator to analyze and compare the amount of progeny released by different mutants. Using this calculator, we determined our final product's median burst size to be 27 progeny out of 96 infection cycle simulations. This burst size was the highest progeny output by any of our designed mutants found to have both a high GFP output and a short lysis time, with the smallest value being roughly 11 progeny per cell infection (Fig 3). As described earlier, maximizing the burst size, as our final product does, allows for the exponential accumulation of the signaling molecule as more of our designed T7 Bacteriophage are released to repeat the cycle.



Figure 4. Median Burst Size of T7 Bacteriophage Mutants Over a Set of 96 Infection Cycle Simulations.


An Optimized T7 Bacteriophage Mutant

By simulating the infection cycle of our designed T7 Bacteriophage on an E. coli cell, we show that we have optimized the GFP production, lysis time, and burst size of our device to yield the best results in a real-world application. As the accumulation of these three factors provides for the rapid and high accumulation of GFP proteins within a contaminated water source, and thus a strong signal. Since these simulations directly reflect the infection cycle of a T7 Bacteriophage on an E. coli cell, we can rely on these results to be representative models of its real-world function and potential.