Team:KU Leuven/Project/DataPage
From 2013.igem.org
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Secondly we aimed to <b><a href="https://2013.igem.org/Team:KU_Leuven/Project/Glucosemodel/MeS/Modelling" target="_blank">predict the exact amounts produced</a> and find the rate limiting steps</b>. Here we fed wet-lab data into our algorithms. The outcome will define/defined our choice of promoters, plasmid copy number, additive requirements etc.. </br></br> | Secondly we aimed to <b><a href="https://2013.igem.org/Team:KU_Leuven/Project/Glucosemodel/MeS/Modelling" target="_blank">predict the exact amounts produced</a> and find the rate limiting steps</b>. Here we fed wet-lab data into our algorithms. The outcome will define/defined our choice of promoters, plasmid copy number, additive requirements etc.. </br></br> | ||
Third, we must know the <b>effect of our pheromones on the ecosystem</b>. We performed a series of modelling steps which you can find in our <a href="https://2013.igem.org/Team:KU_Leuven/Project/Ecological/Modelling" target="_blank">ecological model page</a>. This information is essential on various levels :</br> | Third, we must know the <b>effect of our pheromones on the ecosystem</b>. We performed a series of modelling steps which you can find in our <a href="https://2013.igem.org/Team:KU_Leuven/Project/Ecological/Modelling" target="_blank">ecological model page</a>. This information is essential on various levels :</br> | ||
- | 	<ul><li>It will define the choice of pheromone production rate, which we can regulate through eg. promoter ranges</br></li> | + | 	<ul><li>It will define the choice of pheromone production rate, which we can regulate through eg. promoter ranges</br></li> |
- | 	<li>Dispersion data will indicate the optimal spacing of the BanAphid stickers, key information for the end-user</br></li></ul></br> | + | 	<li>Dispersion data will indicate the optimal spacing of the BanAphid stickers, key information for the end-user</br></li></ul></br> |
Finally, we designed an <a href="https://2013.igem.org/Team:KU_Leuven/Project/Oscillator/Modelling" target="_blank">oscillating transcription factor network</a> to <b>regulate pheromone production for the "sticker enclosed" BanAphids</b>. This oscillator network allows communication between cells, enforcing a synchronized but oscillating production rhythm onto the whole colony. This will optimise the impact of our BanAphids on aphids and ladybugs even though a direct contact cue between aphids and BanAphids is prevented. We designed this model to answer the concerns of our private end-users regarding the spray (or glucose) model.<br/><br/> | Finally, we designed an <a href="https://2013.igem.org/Team:KU_Leuven/Project/Oscillator/Modelling" target="_blank">oscillating transcription factor network</a> to <b>regulate pheromone production for the "sticker enclosed" BanAphids</b>. This oscillator network allows communication between cells, enforcing a synchronized but oscillating production rhythm onto the whole colony. This will optimise the impact of our BanAphids on aphids and ladybugs even though a direct contact cue between aphids and BanAphids is prevented. We designed this model to answer the concerns of our private end-users regarding the spray (or glucose) model.<br/><br/> | ||
Summarised, <b>these algorithms allow us to model our system from the cellular metabolism throughout to the environmental impact</b>. Based on our models, we continuously adapted the actual building of the system towards the most effective circuit. This will reduce costs and save time when our <i>E. coligy</i> are ready for field tests, and later for actual use. | Summarised, <b>these algorithms allow us to model our system from the cellular metabolism throughout to the environmental impact</b>. Based on our models, we continuously adapted the actual building of the system towards the most effective circuit. This will reduce costs and save time when our <i>E. coligy</i> are ready for field tests, and later for actual use. |
Revision as of 16:52, 27 October 2013
Secret garden
Congratulations! You've found our secret garden! Follow the instructions below and win a great prize at the World jamboree!
- A video shows that two of our team members are having great fun at our favourite company. Do you know the name of the second member that appears in the video?
- For one of our models we had to do very extensive computations. To prevent our own computers from overheating and to keep the temperature in our iGEM room at a normal level, we used a supercomputer. Which centre maintains this supercomputer? (Dutch abbreviation)
- We organised a symposium with a debate, some seminars and 2 iGEM project presentations. An iGEM team came all the way from the Netherlands to present their project. What is the name of their city?
Now put all of these in this URL:https://2013.igem.org/Team:KU_Leuven/(firstname)(abbreviation)(city), (loose the brackets and put everything in lowercase) and follow the very last instruction to get your special jamboree prize!
![tree](https://static.igem.org/mediawiki/2013/a/ac/Tree.png)
![ladybugcartoon](https://static.igem.org/mediawiki/2013/6/64/Ladybugcartoon.png)
Data Page
Welcome to our data page! Here we will summarize everything we achieved this summer. Of course, if you want a more extensive explanation, please check out corresponding wiki page.
Our project aims to reduce aphid infestations and thus improve crop yields for the industrial end-user and the private customer. With an environmental project like ours, the importance of the computer and the feedback from our future end-users cannot be underestimated. We adapted our project according to survey information and modelling results. Ultimately, we hope to reduce the real costs of field tests via our in silico work.
First, we must figure out the impact of E-β-farnesene and methyl salicylate production on E. coli. Thus, we performed a Flux Balance Analysis. Results were compared with wetlab data such as growth curves, survival tests etc.
Secondly we aimed to predict the exact amounts produced and find the rate limiting steps. Here we fed wet-lab data into our algorithms. The outcome will define/defined our choice of promoters, plasmid copy number, additive requirements etc..
Third, we must know the effect of our pheromones on the ecosystem. We performed a series of modelling steps which you can find in our ecological model page. This information is essential on various levels :
- It will define the choice of pheromone production rate, which we can regulate through eg. promoter ranges
- Dispersion data will indicate the optimal spacing of the BanAphid stickers, key information for the end-user
Summarised, these algorithms allow us to model our system from the cellular metabolism throughout to the environmental impact. Based on our models, we continuously adapted the actual building of the system towards the most effective circuit. This will reduce costs and save time when our E. coligy are ready for field tests, and later for actual use.
Wetlab
Our wetlab work consists of 3 experimental parts :
(1) the production and testing of the methyl salicylate bricks
(2) the production and testing of the E-beta farnesene bricks
(3) ecological work, testing pheromone impact on the ecosystem (i.e. plants, ladybugs, ...). Here, we found industrial partners in the companies Biobest and pcfruit.
Methyl Salicylate Experiments
Throughout the summer, we made 4 different BioBricks involved in the production of methyl salicylate.
After finding out that the MIT 2006 brick (BBa_J45700) only produced weak amounts of the wintergreen scent (MeS), we dove into the literature and discovered a possible lack of chorismate present in the bacteria. We tried to overcome this problem by overexpressing aroG in E. coli. In the literature, we found two mutations that could make DAHP synthase insensitive to allosteric inhibition. We succeeded in biobricking the normal aroG gene, which gives future teams the opportunity to introduce mutations themselves to overcome the chorismate problem. We characterized our bricks with a renewed smell test and an SDS-PAGE analysis.
(E)-β-farnesene Experiments
After the whole summer's work, we finally made 5 BioBricks for this section.
Our favorites are:
1. BBa_K1060002 contains an open reading frame that codes for (E)-β-farnesene synthase from Artemisia annua. The enzyme converts farnesyl diphosphate into E-β-farnesene. It was a milestone in our project work. We succeeded to remove an EcoRI site in the gene (AY835398.1). This gave us one of the basic parts we needed to create our system.
2. BBa_K1060009 is a construct that constitutively expresses β-farnesene synthase. This was the final device used for our Aphid experiments.
3. BBa_K1060011 is similar to BBa_K1060009. However, in this biobrick we added a lac operator in front of the βfarnesene synthase. This makes it possible to switch of (E)- β-farnesene production by using biosensors expressing LacI.
Our pilot studies with these biobricks and the aphids are promising. Apart from this in vivo characterization, we also initiated an SDS-PAGE analysis. This indicated that the EBF synthase was most likely produced. We can possibly measure the amounts of EBF and MeS produced by our bacteria and use these concentrations to characterize the impact of our synthetic compounds further.
Ecosystem Experiments
Two companies (Biobest and pc fruit) specialised in biological pest management, were very interested in our project and invited us to perform experiments at their facilities. These experiments proved to be challenging given the fact that there are quite a few variables when working with plants and insects. Nonetheless, we were able to demonstrate the effect of MeS in inducing plant defence mechanisms and that this has an effect on the aphid population.
Human Practices
As a result of our unique collaboration between philosophers and scientists within our team, we formulated a new approach, which is bottom-up structured and central is the dialogue between scientists, philosophers and the general public. Therefore, all team members and their supervisors were interviewed about their ethical beliefs. We also explained why we should inform the general public using the ideas of philosopher Hannah Arendt and we examined the responsability of synthetic biologists using the ideas of philosopher Hans Jonas. This is not only a first time in the iGEM competition that these well-known philosophers are read to provide a strong foundation, but has also never been done in the scientific literature!
We consider this bottom-up collaboration between students a new starting point for approaching human practices within the iGEM competition.
To make sure that we have a product that is worth to be launched, we asked Biobest & pcfruit why they were so interested in the BanAphids. Furthermore, we also asked the end users (farmers) whether they would use our BanAphids and the results were definitely positive!
Outreach
We organized a symposium for the general public for which we also invited the other BeNeLux teams to present their project. We hope that one day this will become a yearly tradition in the iGEM competition.
We also went to schools to teach them about synthetic biology. For this we made our very own Plexiglas "biobricks" which the students can use to work on excercises and we made a 3D-bacterial model, which gives the students an idea of what a bacterium looks like.