Team:Manchester/Model/DoE

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:

Figure 6. Relative mCherry fluorescence from raw liquid culture expressing the PduD(1-20)_mCherry_cgPPK construct under different conditions.

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 inbuilt interaction profiler to decide on the ranges of our factors for round 2.

Figure 9. The interaction profile of the input factors, maximised for yield. OD600 at induction consistently correlated with higher yields. The profiler also suggests that optimal conditions for expression of PduD(1-20)_mCherry_cgPPK lie close to 20°C and a post-induction growth period of 24 hours or more.

With this information we chose the following ranges fo factors

0.1-1
IPTG concentration in inducer
Post induction temperature
post induction time

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