Team:Harvard/Results
Results
Purpose
In order to show that optimizing the stoichiometry of the curli pathway can affect curli production, we attempt to demonstrate that variations in the RBS strength of csgG can impact levels of curli production. This would give a proof-of-concept foundation for the idea that curli production can be optimized by regulating expression strengths of the pathway proteins.
Generating RBS Variation
We employed a simple screening process in order to identify and select RBSs of varying expression strengths. Using the Salis Lab RBS generator, we identified a degenerate RBS sequence with a wide range of expression strengths based on whether each degenerate base crystallized to adenine, guanine, cytosine, or thymine. We sent that degenerate sequence out for synthesis and got back our library of interest.
Then, we used Gibson Assembly to position the RBSs in front of the csgG gene within the pBbB8K-CsgBACEFG plasmid used by the Joshi Lab, which was originally the consolidated curli operons with the wild-type RBSs for each protein under an arabinose promoter. The Gibson Assembly produced a library of plasmids which were identical except for the csgG modified RBS.
Detecting RBS Variation
The assembled plasmids were transformed into competent PQN4 E. coli cells and grown on plates with arabinose and Congo Red. The arabinose induced curli production while the Congo Red was there to indicate how much curli was being produced per colony.
Generally, Congo Red has been shown to bind to amyloid proteins like curli, thereby making the substance red, and can therefore act as an indicator of curli presence. However, it binds non-specifically to curli, meaning that it can also bind other extracellular components of E. coli cells such as pili. This is why we chose to transform into the PQN4 strain, which has knock-outs of most other extracellular features. Furthermore, adding just a tiny amount of Congo Red to the agar plates made them also turn red, so it was not possible to visually identify which colonies were producing curli and which weren’t.
To make such a distinction, it was necessary to take fluorescent images of the plates. After that, a MATLAB script was used to compare the average pixelation brightness between colonies, and we made a preliminary conclusion that the brightest colonies had the most curli production.
