Results

This page displays our all our successes and failures. We managed to successfully create several new functional PhytoBricks, and add experimental data to already existing ones. Some of the PhytoBricks, namely GUS, mCherry, and RTBV promoter, could prove to be very valuable parts in the registry. Fortunately, for these parts, we have extensive data. Unfortunately (or fortunately if you're an aphid), we didn't manage to detect the presence of siRNAs in our transgenic plants, though we suspect this is because our detection system was sub-optimal, rather than them not being produced. We also did not manage to test the toxicity of these siRNAs on the aphids themselves, due to the final constructs only being produced in the last week of our lab time, and the toxicity protocol taking several weeks. Thus, our future steps would of course involve using a more specialised detection protocol for siRNAs, or perhaps a northern blot, and perform the toxicity assay on our aphids to provide a definite toxicity range of our RNAs.

Abundant aphids and sad scientists

As mentioned above, we did not manage to conclusively detect the presence of the siRNAs in the infiltrated plants. However, below shows some of the final gels that were run, as no results are still results. The protocol we were using for this was not specifically designed for siRNAs, as specialised protocols had too many reagents for our budget. In the future, we would use an optimised protocol, such as this one. Of course, we also did not manage to perform a toxicity assay on the aphids themselves, but our laboratory model shows some possibly scenarios, assuming a specific toxicity value for our siRNA constructs. In the future, we would perform this toxicity assay, in an experiment analogous to this one.

A colourful display

Despite our siRNA side falling short, we had great success with the PhytoBrick-focused side of our project. We managed to successfully create a new PhytoBrick reporter gene, beta-glucuronidase (or GUS), which is widely used in plant biology, but was not in the registry previously. Using GUS, we made several composite parts, seen on our composite parts page. We managed to get high quality experimental data for GUS itself, and for the 35S and RTBV promoters, and Nos, G7, and 35S terminators, characterising these parts in the process, further strengthening the PhytoBrick registry. These results can be seen below, and are on each respective part's page. The left GUS assay shows experiments testing the 35S and RTBV promoters. Clearly expression is constitutive for both, though RTBV has been extensively reported in the literature to be vascular specific. The right two GUS assays show tests of the three terminators. We concluded from these that the G7 terminator produced strong expression consistently, and the nopaline synthase terminator, used as standard in all our constructs, has the most inconsistent expression. Ideally we would perform more assays on these with GUS, mCherry and eGFP, but from these results we would suggest that future teams using plants should use the G7 terminator.



Initially, we were visualising eGFP in plants, but quickly found that expression levels were very close to background levels, possibly because chlorophyll does not absorb green light, which is reflected. We knew that GFP functions as a dimer, meaning it requires more protein copies to fluoresce effectively. For these reasons, we soon created codon-optimised mCherry, which we had excellent results with. The only construct we managed to get even tentative eGFP results with was RTBV-OTMV-eGFP-NosT. These are shown below. The expression pattern of RTBV using eGFP as a reporter does not match the expression pattern when using GUS and mCherry, creating uncertainty in this result. In addition, the experiment performed with this construct was before we used heat-shocked plants, which could explain the difference. Looking at the GFP experiments to identify differences between the terminators, there is no significant difference in fluorescence between the 3 samples (35S-OTMV enhancer-eGFP-NosT/G7/35ST) and the negative control.



Finally, we had excellent success with our improved mCherry, which we made compatible with GoldenGate and codon-optimised it for Nicotiana benthamiana. Here it is important to note that chlorophyll autofluoresces in the red region of light (around 680nm), which could explain the very low levels of expression in negative control leaves. Using this reporter, we only had time to perform a single experiment, with mCherry under control of either the 35S or RTBV promoter, where we heat shocked plants 1 DPI and tested them 3 DPI. This means that the protocol was shortened by one day which may effect the results. Due to the original mCherry sequence not being GoldenGate compatible, we couldn't create level 1 constructs with it to test. In addition, to show our part still functions in bacteria, we created a part containing a bacterial promoter, RBS, our mCherry, and a bacterial terminator. Both the plant and bacterial experiments had extremely promising results, as shown below. Of course, we would improve this characterisation further with more experimental time.



Thus, we are happy with our contribution to the PhytoBrick registry, and believe that we have massively improved the opportunities for plant teams, especially those that use GoldenGate cloning. We suspect that our parts, especially GUS, mCherry, and the RTBV promoter, will be used commonly in the future. Because the reporter constructs worked with high efficiency, we think that the siRNAs were likely present, but we could not detect them with our methods. Even though the RTBV promoter was meant to have vascular-specific expression, its weak constitutive expression in our tobacco plants suggests that it could still make a useful tool. However, to minimise the amount of siRNA eaten by non-target insects, we would need to find an alternative, truly vascular specific promoter.

The dry stuff

It wasn't only in the lab that we made progress. We managed to create a piece of hardware that proved to be very useful for human practices, especially in helping children to understand about plant GM. This side of our project gave us new leads, and allowed us to chat to a wide variety of stakeholders, who voiced their opinions and concerns about GMOs, GM food, and our project. We, with the help of our supervisor, Dr. Daniel Pass, managed to bioinformatically analyse the potential ecological effects if our siRNAs were deployed, and weighed this up to other strategies. In addition, we modelled several scenarios which could occur when aphids fed on the transgenic plants, in a laboratory or field setting. We communicated with several teams for collaborations, and ended up testing a regulatory sequence of DNA in our plants, and 3D printed a model detection chamber for WashU, giving detailed feedback. Finally, we completed the InterLab study and provided iGEM with a highly valued +1 to their sample size.