Team:Manchester/Model/DoE
Design of Experiments
Achievements:
1. Expression optimisation of a new part
2. Robust characterisation of expression
3.
4.
Introduction
Design of Experiments (DoE) is a statistical method that allowed us to design the most efficient experiments to determine the factors that influence the expression of our PPK enzyme and the expression of our Eut (microcompartment) proteins. By using DoE, we can efficiently explore a very large experimental space in a small number of experiments, allowing us to test multiple hypotheses at once in a rapid and robust manner. Performing our measurements using the statistical tools of DoE allowed us to develop an improved understanding of the experimental factors affecting protein expression in the Phosphostore system, within the limited time frame available for an iGEM project.
Method - PduD(1-20)_mCherry_cgPPK Expression Optimization
In order to optimise the efficiency of our engineered phosphate-accumulating organism, we wanted to find the ideal expression conditions for the PduD(1-20)_mCherry_cgPPK under a T7 promoter in BL21 (DE3) E. coli cells. We used JMP software by SAS to design our experiments. We decided to focus our analysis on continuous factors as more information can be extracted from a small number of experiments. With this in mind, we chose to investigate the following factors:
- OD at induction
- IPTG concentration in inducer: 0.1 - 1.0mM
- Post induction temperature: 20ºC and 37ºC
- post induction time: 4 and 24 hours
Round 1 of experiments yielded the following data:
Background
Round 2 of DoE
With the results from the first round, it was clear that a higher OD at induction yielded more protein. Because of this we decided to fix the induction OD at 0.8. This removed one of the factors, allowing us to create higher resolution data with the same number of runs. With our remaining factors we used the interaction profiler to identify the ranges for our second round of experiments.
Some nice graphs as those already in the presentation. More if possible. Prove that the only few iterations needed to get high optimisation Conclusion That this is a technique that works and should be used
