Here are the significant results of our Project!
The relative fluorescence measurements of the Anderson Promoter Series was measured across 3 different microorganisms: Bath, E. coli, and OB3b. These values were obtained by measuring the fluorescence using a fluorimeter and dividing that value by the OD (optical density) to ensure that our data values could be accurately compared. Our data reflected that the promoter strength was strongest in E. coli, followed by Bath, and then OB3b. Specific to promoters, our expectation was for p100 to have the strongest fluorescence, given that it was strongest in the original Anderson Series measurements. However, for our experiment, p104 demonstrated the strongest fluorescence. This was excluding p119, the control promoter that all our promoters were based off of, understandably having the greatest fluorescence. We further compared the correlation of relative fluorescence activity between E. coli and Bath, and E. coli and OB3b in separate graphs. In our graphs, each promoter was displayed to have little variation in fluorescence activity across all microorganisms. This was seen through our lines of best fit having R2 values of 0.854 and 0.742 in graphs comparing OB3b and E. coli and Bath and E. coli, respectively. However, a gap was clearly present in our fluorescence activity between our strongest promoter (p104) and the control (p119). When scaled, our fluorescence activity between the two promoters was too large for our purposes. We were missing activity in the same ranges that would have allowed for successful expression of synthetic products without being high enough to restrict cellular growth. Our solution involved the creation of a novel mutagenesis promoter library. Twenty five colonies were eventually selected within our desired range of fluorescence. Our data indicated that we had a consistent range of activity in a similar scaled pattern as in previous graphs and sectioned off in ranges from low, medium, to high. This data was precisely what was able to ‘fill the gap’ that we had been challenged with. Further sequencing of these promoters displayed that many of these promoters had similar mutations, and thus five unique promoters were further selected with strengths that were relevant for our interests. When comparing the strengths of our mutated promoters to the original scale that the Anderson Series was measured on, a scale normalized to p100, we saw that the mutated promoters generally had much greater activity, both in E. coli and Bath. The comparison of relative strengths between Bath and E. coli further demonstrated the mutated promoters greater levels of fluorescence in Bath as well. Overall, our results indicate that these mutagenized promoters allow for a full dynamic range of expression without inhibiting cellular growth in both E. coli and Bath. For our purposes, this meant that these promoters would serve as more diverse, flexible, and effective genetic tools, with broad implications on the environment and industrial fields.
Our future plans for the project involve the application of our products to produce viable products. The mutagenized promoters have the ability to convert methane into methanol, serving as a foundation for further conversions into other useful products. Furthermore, these promoters can be further tested in other organisms, and observed to determine whether their efficacy remains the same or if any significant differences occur. OB3b remained out of our mutagenized data due to time constraints and the nature of its slow growth. Further work can be done to see whether OB3b provides similar data as in E. coli and Bath. Regarding the replication of our experiment, our data has already been repeated in numerous trials to result in the averaged values that are seen in our data. Measures, such as the evaluation of fluorescence in both liquid and cell cultures, as well as in biological and technical replicates, have ensured that our results are precise and accurate and take into account various scenarios. Furthermore, outliers in the general data set have been included in our data to maintain full transparency and indicate that despite those differences, our data as a whole remains reliable.