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 1. Relative mCherry fluorescence from raw liquid culture expressing the PduD(1-20)_mCherry_cgPPK (BBa_K2213005) construct under different conditions.

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 2. 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 (BBa_K2213005) are above 20°C, a post-induction growth period above 24 hours and an IPTG concentration above 1mM.

With this information we chose the following ranges of factors

IPTG concentration in inducer: 1 - 10mM
Post induction temperature: 16ºC, 20ºC and 24ºC
post induction time: 24 and 48 hours

These choices in ranges proved to be significantly closer to the optimum as evident from figure 3:

Figure3. mCherry fluorescence measurements from the 24 hour time points from round 2 of optimisation (Pink) plotted alongside the mCherry fluorescence measurements from the round one experiments, which used the same gain setting. The readings from the second round have saturated the detector which is why all of the peaks are the same.

as you can see from the graph above,

Conclusion

From these 2 rounds of DoE we saw a huge increase in the yield of the protein. We found the optimal conditions to be:

OD of 0.8
IPTG concentration of 1mM
Post induction temperature of 24ºC
post induction time of 48 hours

This is just one example where we have used DoE in our project but the scope for its application is huge. We used DoE to optimise the synthesis of EutM protein; the results of which can be seen at BBa_k2213001 <--LINK THIS TO THIS http://parts.igem.org/Part:BBa_K2213001. In conclusion we found DoE to be an incredibly useful tool and would recommend it to any other teams with projects where optimisation is key.