Team:Washington/Results

From 2014.igem.org

UW Homepage Official iGEM website

Results

Protein stability analysis using Circular Dichroism

Our system was verified using Circular Dichroism (CD) analysis. CD works by sending a circularly polarized beam of light through a protein. Particular folding patterns, such as alpha-helices and beta-sheets, provide recognizable patterns in a CD signal. While CD does not indicate how a protein is folded, it does show the level of folding in a protein by recording an initial signal and comparing it to the signal of the denatured protein. In our project, a scan of the protein in a PBS solution was done across a variety of wavelengths to find the signal minima that would best indicate the state of folding. An equivalent concentration of protein in concentrated guanidinium chloride (GdmCl), a powerful chaotropic agent, was then prepared to be mixed into our sample. This solution was then added to the sample in small increments, allowing us to measure the CD signal at increasing concentrations of GdmCl while maintaining a constant concentration of the protein being tested. The concentration of GdmCl at which the CD signal was half of its initial value was recorded. A protein has higher stability if a higher concentration of GdmCl is required to half-denature the protein sample.

CD data
Fig. 1. Our CD data from the Guanidine melt is consistent with the literature in that BbpD04.3 is the most stable with Bindi slightly less stable. BbpD04 is very unstable.

Protein stability analysis using Degron Constructs and Flow Cytometry

The results for the no-protein of interest degron constructs matched expected results in which Deg0 had the highest expected stability which correlated to the highest fluorescence output. These expectations were validated by our experimental results in which cells with Deg0 exhibited the highest fluorescent levels. Our second expectations were that Deg2 and Deg3 would exhibit middle levels of fluorescence, lower than Deg0 but higher than Deg1 or Deg4. Once again, these expectations were validated by our experimental results. The results for the no protein of interest degron constructs are as follow, cells containing our Deg0 protein construct exhibited the highest fluorescent followed by Deg2 and Deg3 and finally by Deg1 and Deg4 both of which exhibited baseline levels (no protein, no degron construct PYE1 cells) of fluorescence.

In order, to validate the system as a whole we must analyze the degron constructs with a specific well studied protein to analyze that protein's stability with our system compared to the protein stability measurements from current existing techniques. There were three variants of a protein each with varying stabilities that were quantified using circular dichroism and guanidinium hydrogen chloride melts. The protein BINDI had the highest stability followed by BbpD04.3 and then BbpD04. If our system is accurate, cells containing the BINID-Degron construct would exhibit the highest fluorescence output followed by BbpD04.3 and BbpD04 would show the lowest fluorescence output. Since there are 5 possible degron constructs for each of our 3 proteins of interest, all 15 data points would have to match our expectations. We expect that BINDI Deg0 would have the highest fluorescence of the all protein of interest Deg0 constructs followed by BbpD04.3 Deg0 and BbpD04 Deg0. Next, BINDI Deg2/3 would have middle levels of fluorescence followed by BbpD04.3 Deg2/3 and BbpD04 Deg2/3. Finally, BINDI Deg1/4, BbpD04.3 Deg1/4 and BbpD04 Deg1/4 would have the lowest levels of fluorescence if not baseline levels. The experimental results accquired through flow cytometry show a rough correlation to these expections as Deg0 shows higher GFP output than Deg2/3 and Deg2/3 show higher GFP output compared to Deg1/4.


High-Throughput Testing of Protein Variants by Fluorescence-Activated Cell Sorting

The random mutagenesis library of BbpD04 was analyzed for GFP fluorescence by a Fluorescence-Activated Cell Sorting machine. Cells were first measured for their forward scatter and side scatter to select only for single cells. Then these single cells were measured for GFP fluorescence and we set a gate for the top 1.00% of fluorescing cells to be sorted. We sorted ten-fold the library size. After sorting, the recovered cells were grown up and then sorted again. This was repeated such that the library was sorted three times. We compared this to a clone of BbpD04 which was not mutagenized to see how our random mutagenesis library compared.


Fig4. Subsequent sorts lead to improved GFP output for the random mutagenesis library.

Serial sorts of our mutagenized library showed increasing mean GFP fluorescence (Fig. 4) when compared to BbpD04 clone. This shows we successfully selected for the top GFP producers in the population. Our hypothesis is that these contain variants of our protein that are more stable. We are currently in the process of cloning and expressing these variants and characterizing their stability by chemical denaturation.