Team:Wageningen UR/overview/results

From 2014.igem.org

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                             <h1 id="Key_results">Key Results</h1>
<p>In this section we will discuss the key results of fungal <a class="soft_link" href="https://2014.igem.org/Team:Wageningen_UR/project/fungal_sensing">sensing</a>, fungal <a class="soft_link" href="https://2014.igem.org/Team:Wageningen_UR/project/fungal_inhibition">inhbition</a>, <a class="soft_link" href="https://2014.igem.org/Team:Wageningen_UR/project/fungal_kill-switch">kill-switch</a>.</p>
<p>In this section we will discuss the key results of fungal <a class="soft_link" href="https://2014.igem.org/Team:Wageningen_UR/project/fungal_sensing">sensing</a>, fungal <a class="soft_link" href="https://2014.igem.org/Team:Wageningen_UR/project/fungal_inhibition">inhbition</a>, <a class="soft_link" href="https://2014.igem.org/Team:Wageningen_UR/project/fungal_kill-switch">kill-switch</a>.</p>
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<h2>Sensing</h2>
<h2>Sensing</h2>
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<p>In literature it was never sure if there is really a fusaric acid dependent promoter. In this project we proved that there is such a promoter. A fusaric acid dependent promoter (isolated from <i>Pseudomonas putida</i> KT2440) was cloned in front of GFP <a class="soft_link" href="http://parts.igem.org/Part:BBa_E0040">(BBa_E0040)</a>, transformed in <i>Pseudomonas putida</i> KT2440 (<i>P.putida</i>). And flouresence were measured in different fusaric acid concentration. We were able to validate and characterize a novel fusaric acid dependent promoter <a class="soft_link" href="http://parts.igem.org/Part:BBa_K1493000">(Bba_K1493000)</a>.
+
<p>In literature it was never sure if there is really a fusaric acid dependent promoter. In this project we proved that there is such a promoter. A fusaric acid dependent promoter (isolated from <i>Pseudomonas putida</i> KT2440) was cloned in front of GFP<a class="soft_link" href="http://parts.igem.org/Part:BBa_E0040">(BBa_E0040)</a>, transformed in <i>Pseudomonas putida</i> KT2440 (<i>P.putida</i>). And flouresence were measured in different fusaric acid concentration. We were able to validate and characterize a novel fusaric acid dependent promoter <a class="soft_link" href="http://parts.igem.org/Part:BBa_K1493000">(Bba_K1493000)</a>.
<figure>
<figure>
<img src="https://static.igem.org/mediawiki/2014/3/37/Wageningen_UR_sensing_Faip14.jpg"><figcaption>Figure 6. <br>*Significantly different from WT.<br>**Significantly different from WT, grouped together<br>The measurement is based on GFP fluorescence in <i>P. putida</i> at increased concentrations of fusaric acid to prove and characterize the activity of the fusaric acid induced promoter, <a class="soft_link" href="http://parts.igem.org/Part:BBa_K1493000">BBa_K1493000</a>. For comparison, the well characterized pLac promoter (<a class="soft_link" href="http://parts.igem.org/Part:BBa_K741002">BBa_K741002</a>, uninduced by IPTG) was used to quantify the activity of this promoter at different concentrations of fusaric acid. Our fusaric acid inducible promoter does not respond to low concentrations up to 170µM. From 255µM and up, the activity increases. The maximum measured activity of the promoter is 0.21 RPU at 425µM. </figcaption></figure>
<img src="https://static.igem.org/mediawiki/2014/3/37/Wageningen_UR_sensing_Faip14.jpg"><figcaption>Figure 6. <br>*Significantly different from WT.<br>**Significantly different from WT, grouped together<br>The measurement is based on GFP fluorescence in <i>P. putida</i> at increased concentrations of fusaric acid to prove and characterize the activity of the fusaric acid induced promoter, <a class="soft_link" href="http://parts.igem.org/Part:BBa_K1493000">BBa_K1493000</a>. For comparison, the well characterized pLac promoter (<a class="soft_link" href="http://parts.igem.org/Part:BBa_K741002">BBa_K741002</a>, uninduced by IPTG) was used to quantify the activity of this promoter at different concentrations of fusaric acid. Our fusaric acid inducible promoter does not respond to low concentrations up to 170µM. From 255µM and up, the activity increases. The maximum measured activity of the promoter is 0.21 RPU at 425µM. </figcaption></figure>
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<p><p>In general,  it was hard to distinguish the increase inhibition effect of the anti-fungal producing transformants against <i>F. oxysporum</i>. This is because the <i>P. putida</i> chassis we have chosen is already very good at inhibiting <i>F. oxysporum</i> naturally, which probably makes it hard to see a distinguish increased growth inhibition by our synthetic, anti-fungal producing <i>P. putida</i> strains. However, with the Methionine-γ-lyase(MgL) strain, we have a clear indication that there is an increase of growth inhibition of <i>F. oxysporum</i> (figure 3) and with others, producing 2,4-DAPG, chitinase or pyoverdine, we can say that there is an indication of a slight increase of growth inhibition (figure 8, 12 and 13) on top of the natural inhibition. For more information, read <a class="soft_link" href="https://2014.igem.org/Team:Wageningen_UR/project/fungal_inhibition">fungal inhibiton</a>.</p>
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<p><p>In general,  it was hard to distinguish the increase inhibition effect of the anti-fungal producing transformants against <i>F. oxysporum</i>. This is because the <i>P. putida</i> chassis we have chosen is already very good at inhibiting <i>F. oxysporum</i> naturally, which probably makes it hard to distinguish increased growth inhibition by our synthetic, growth inhibitor producing <i>P. putida</i> strains. However, with the Methionine-γ-lyase(MgL) strain, we have a clear indication that there is an increase of growth inhibition of <i>F. oxysporum</i> (figure 3) and with others, producing 2,4-DAPG, chitinase or pyoverdine, we can say that there is an indication of a slight increase of growth inhibition (figure 8, 12 and 13) on top of the natural inhibition. For more information, read <a class="soft_link" href="https://2014.igem.org/Team:Wageningen_UR/project/fungal_inhibition">fungal inhibiton</a>.</p>
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<h2>Kill-Switch<h2>
<h2>Kill-Switch<h2>
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<p>Once fungal growth inhibitors are produced and <i>F. oxysporum</i> is no longer in the soil BananaGuard has done it's job and is no longer needed in the soil. Therefore we have implemented a Kill-Switch into our system, it works like a toggle-switch that knows when fusaric acid was around and once it's gone, toxins will be produced that eliminates GananaGuard itself. With the kill switch regulatory system in figure 4.  
+
<p>Once fungal growth inhibitors are produced and <i>F. oxysporum</i> is no longer in the soil BananaGuard has done it's job and is no longer needed in the soil. Therefore we have implemented a Kill-switch into our system, which works like a toggle switch that senses when fusaric acid is around, and when it has dissipated toxins will be produced that eliminate BananaGuard. Toxins will be produced that eliminate BananaGuard itself, with the kill switch regulatory system in figure 4.
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<p>LambdaCI (induced by rhamnose) has shown to suppress pcIλ/Tet promoter and pcIλ/lac promoter by showing no GFP produced when induced with rhamnose (figure 5 and figurexx respectively). LacI was also shown to suppress pcIλ/lac by showing no GFP produced when induced with rhamnose(figure xx). The toggle-switch was constructed (<a class="soft_link" href="http://parts.igem.org/Part:BBa_K1493702"> Bba_K1493702</a>, <a class="soft_link" href="http://parts.igem.org/Part:BBa_K1493703"> Bba_K1493703</a>) containing pCI/lac promoter + TetR together with ptet + LacI + GFP. After testing, it was concluded that the toggle switch can be in its resting state. Because it was to have low GFP fluorescence when induced by IPTG. In addition, the toggle switch can also be activated and be in its actives state because of high fluorescence when induced by aTc.</p>
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<p>CIλ (induced by rhamnose) has shown to suppress the pcIλ/Tet and pcIλ/lac promoters by inhibiting GFP production when induced with rhamnose (figure 5 and figurexx respectively). LacI was also shown to suppress pcIλ/lac by Inhibiting GFP expression when induced with rhamnose(figure xx). The toggle-switch was constructed (<a class="soft_link" href="http://parts.igem.org/Part:BBa_K1493702"> Bba_K1493702</a>, <a class="soft_link" href="http://parts.igem.org/Part:BBa_K1493703"> Bba_K1493703</a>) containing pCI/lac promoter + TetR together with ptet + LacI + GFP. After establishing that induction by IPTG leads to adequately low GFP expression (the off-state), whereas induction by aTc results in high GFP expression (the on-state), we concluded that the toggle switch mechanism suits our intended application purpose (figure xx).</p>
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<h3>Promoter design model</h3>
<h3>Promoter design model</h3>
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<p>With the kill-switch being designed, it was never quiet sure it would work as it is a pretty complicated circuit. So we looked at a statistical mechanics model has led to the experimentalists decision to opt for a new set of designed promoters and build two kill-switches in parallel. The model has predicted the newly designed promoters to have a higher stability. For more information, read <a class="soft_link" href="https://2014.igem.org/Team:Wageningen_UR/project/model#cost1">kill-swtich promoter design</a>. </p>
+
<p>The kill-switch design is relatively intricate and therefore requires in silico analysis in order to test and improve its architecture. In order to accommodate this aim, we exploited statistical mechanics to derive a model of the system. Not unexpectedly, the new insight obtained strongly favored some adaptations to the current design, which included reallocation of promoters as well as parallel placement of an additional kill-switch, which according to the predictions would yield a more stable system. For more information, read <a class="soft_link" href="https://2014.igem.org/Team:Wageningen_UR/project/model#cost1">kill-swtich promoter design</a>. </p>
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<h2>System model</h2>
<h2>System model</h2>
<h3>Cost</h3>
<h3>Cost</h3>
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<p>Having all the whole system in <i>P.putida</i> is great but to keep in mind is that there is always metabolic stress in everything that we want <i>P. putida</i> to produce. So a model was developed that would predict the cost of the whole system. In the model it is indicated that metabolic stress is not a bottleneck for the production of fungal growth inhibitors in the activated system. For more information read <a class="soft_link" href="https://2014.igem.org/Team:Wageningen_UR/project/model#cost1">system cost</a> </p>
+
<p>Having the whole system in <i>P. putida</i> is great however there is always metabolic stress in everything that we want <i>P. putida</i> to produce. Therefore another model was developed to predict the cost of the whole system. The model indicates that the metabolic stress introduced by fungal growth inhibitors production should not pose a bottleneck. For more information read <a class="soft_link" href="https://2014.igem.org/Team:Wageningen_UR/project/model#cost1">system cost</a> </p>
<figure>
<figure>
<img src="https://static.igem.org/mediawiki/2014/4/4a/Wageningen_UR_modeling_Combined_growth_rates.png" width="80%">
<img src="https://static.igem.org/mediawiki/2014/4/4a/Wageningen_UR_modeling_Combined_growth_rates.png" width="80%">
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<h3>Performance</h3>
<h3>Performance</h3>
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<p>Knowing that <i>P. putida</i> is able to handle the production of the whole system. But what about the performance of the system itself, will kill switch be able to switch or will <i>P. putida</i> die before anything can even happen due to toxin imbalance in the system. So we sought out a stochastic model that takes the whole system into account, the metabolic stress, the leakiness of each promoter and the toxins to see if this whole system is in anyway possible to live up to it's expectation. The following results can be seen in figure 4. For more information read <a class="soft_link" href="https://2014.igem.org/Team:Wageningen_UR/project/model#performance1">model performance</a>  </p>
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<p>Knowing that <i>P. putida</i> is able to cope with the whole system, the next objective is to assess the performance of the system; will the kill-switch function according to our expectations? Will the kill-switch kill <i>P. putida</i> in advance of performing its intended role as a fungicide due to imbalance of the toxin anti-toxin system?In order to answer these questions we created a stochastic whole system model, incorporating metabolic stress, leakiness of each individual promoter and the toxin anti-toxin syswtem. The results of this analysis are depicted in figure 4. For more information read <a class="soft_link" href="https://2014.igem.org/Team:Wageningen_UR/project/model#performance1">model performance</a>  </p>
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<figure>
                             <img src="https://static.igem.org/mediawiki/2014/b/b2/Wageningen_UR_model_bobwalter_Overviewpicture.png" width="100%">
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<p>The stochastic model (figure 11) has shown that different basal production levels of CIλ can have different effects on population dynamics, cell growth and the stability of the kill-switch, a point of attention for final construct of the system. Finally, the kill-switch will perform with 98% efficiency given the slow growth rate in the soil predicted by the metabolic model.</p>
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     </section>     
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<section id="greenhouse">
<section id="greenhouse">
<h2>Green house</h2>
<h2>Green house</h2>
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<p>Currently we have banana plants in the green house (figure 12) that have been inoculate with our engineered <i>P. putida</i> and also infected with <i>F. oxysporum</i>. However plants grow at a much slower rate when compared to bacteria. So results were not possible to obtain before the wiki-freeze (see  <a class="soft_link" href="https://2014.igem.org/Team:Wageningen_UR/project/greenhouse">green house </a>). </p>
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<p>We were able to establish a collaboration with the plant research international group of Wageningen, which gave us the unique opportunity to test the system, not only against <i>F. oxysrporum</i>, but in a setting that mimics the situation outside the lab as closely as possible with banana plants.
 +
At present we have banana plants in the green house (figure 12) that have been inoculate with our engineered <i>P. putida</i> and which were also infected with <i>F. oxysporum</i>. However, plants grow at a much slower pace than bacteria. So results were not possible to obtain before the wiki-freeze
 +
(see  <a class="soft_link" href="https://2014.igem.org/Team:Wageningen_UR/project/greenhouse">green house </a>). </p>
<figure>
<figure>
<img src="https://static.igem.org/mediawiki/2014/0/08/Wageningen_UR_greenhouse_banana_plants.JPG"width="80%"/> <figcaption style="font-size:11px;font-weight:bold">Figure 12. Banana plants in greenhouse
<img src="https://static.igem.org/mediawiki/2014/0/08/Wageningen_UR_greenhouse_banana_plants.JPG"width="80%"/> <figcaption style="font-size:11px;font-weight:bold">Figure 12. Banana plants in greenhouse

Revision as of 10:36, 17 October 2014

Wageningen UR iGEM 2014

Key Results

In this section we will discuss the key results of fungal sensing, fungal inhbition, kill-switch.


Sensing

In literature it was never sure if there is really a fusaric acid dependent promoter. In this project we proved that there is such a promoter. A fusaric acid dependent promoter (isolated from Pseudomonas putida KT2440) was cloned in front of GFP(BBa_E0040), transformed in Pseudomonas putida KT2440 (P.putida). And flouresence were measured in different fusaric acid concentration. We were able to validate and characterize a novel fusaric acid dependent promoter (Bba_K1493000).

Figure 6.
*Significantly different from WT.
**Significantly different from WT, grouped together
The measurement is based on GFP fluorescence in P. putida at increased concentrations of fusaric acid to prove and characterize the activity of the fusaric acid induced promoter, BBa_K1493000. For comparison, the well characterized pLac promoter (BBa_K741002, uninduced by IPTG) was used to quantify the activity of this promoter at different concentrations of fusaric acid. Our fusaric acid inducible promoter does not respond to low concentrations up to 170µM. From 255µM and up, the activity increases. The maximum measured activity of the promoter is 0.21 RPU at 425µM.

For more information, read fungal sensing.


Inhibition

Upon sensing fusaric acid, three genes and a gene cluster will be activated that will lead to production production of certain antifungal. Those genes and their function being:

  1. phlABCDE gene cluster, able to produce 2,4-Diacetylphloroglucinol(2,4-DAPG)
  2. Methionine-γ-lyase, Dimethyldisulfide (DMDS) and dimethyltrisulfide (DMTS)
  3. Pfri, produce pyoverdine in pressence of iron
  4. Chitinase, overexpresses chitinase activity

Methionine-γ-lyase and Pfri were bopth made into biobricks, Bba_K1493300 and Bba_K1493200 respectively. With both biobricks validated, and for Pfri characterized. Pfri has shown to give a four fold increase of pyoverdine production in the pressence of iron in the medium.

Figure 2.Pyoverdine absorbance at 400nm with error bars,OD corrected.


All transformants were co-inoculated with Fusarium oxysporum cubense TR4 on agar plates in order to test its inhibition ability. Controls used were wild type P.putida KT2440 with F.oxysporum and just F.oxysporum.

Figure 3.In vivo assay, P.putida co-inoculated with F.oxysporum. Red circle indicates area occupated by F.oxysporumgrowth. Foc control=Fusarium oxysporum cubense TR4, WT=wild type P.putida KT2440, DAPG=P.putida containing phlABCDE gene cluster, MgL=P.putida containing methionine-γ-lyase, chitinase=P.putida overexpressing chitinase, pfri= P.putida overexpressing pfri and mix(all 4)=all 4 tranformants mixed.

In general, it was hard to distinguish the increase inhibition effect of the anti-fungal producing transformants against F. oxysporum. This is because the P. putida chassis we have chosen is already very good at inhibiting F. oxysporum naturally, which probably makes it hard to distinguish increased growth inhibition by our synthetic, growth inhibitor producing P. putida strains. However, with the Methionine-γ-lyase(MgL) strain, we have a clear indication that there is an increase of growth inhibition of F. oxysporum (figure 3) and with others, producing 2,4-DAPG, chitinase or pyoverdine, we can say that there is an indication of a slight increase of growth inhibition (figure 8, 12 and 13) on top of the natural inhibition. For more information, read fungal inhibiton.


Kill-Switch

Once fungal growth inhibitors are produced and F. oxysporum is no longer in the soil BananaGuard has done it's job and is no longer needed in the soil. Therefore we have implemented a Kill-switch into our system, which works like a toggle switch that senses when fusaric acid is around, and when it has dissipated toxins will be produced that eliminate BananaGuard. Toxins will be produced that eliminate BananaGuard itself, with the kill switch regulatory system in figure 4.

Figure 4: the overview of the kill switch regulatory system showing al possible repressions. To simplify things in wetlab rhamnose input (white dots) is used instead of fusaric acid and GFP output (green dots) is used instead of toxins.


CIλ (induced by rhamnose) has shown to suppress the pcIλ/Tet and pcIλ/lac promoters by inhibiting GFP production when induced with rhamnose (figure 5 and figurexx respectively). LacI was also shown to suppress pcIλ/lac by Inhibiting GFP expression when induced with rhamnose(figure xx). The toggle-switch was constructed ( Bba_K1493702, Bba_K1493703) containing pCI/lac promoter + TetR together with ptet + LacI + GFP. After establishing that induction by IPTG leads to adequately low GFP expression (the off-state), whereas induction by aTc results in high GFP expression (the on-state), we concluded that the toggle switch mechanism suits our intended application purpose (figure xx).


Figure 5. LambdaCI induced by rhamnose suppressing pcIλ/Tet promoter expressing GFP (input output plasmid. Plates were done in duplo.Top plates are plates without rhamnose and the bottom plates are plates with rhamnose.

Figure 8. The relative fluorescence unit of each toggle switch state. Fluorescence is measured in duplo of cell cultures carrying the pSB3K3 plasmid with the toggle switch construct (BBa_K1493702, BBa_K1493703) grown in M9 medium containing 500 ng/ml aTc (green), 2 mM IPTG (red) and with no inducer added to the medium (blue).

Promoter design model

The kill-switch design is relatively intricate and therefore requires in silico analysis in order to test and improve its architecture. In order to accommodate this aim, we exploited statistical mechanics to derive a model of the system. Not unexpectedly, the new insight obtained strongly favored some adaptations to the current design, which included reallocation of promoters as well as parallel placement of an additional kill-switch, which according to the predictions would yield a more stable system. For more information, read kill-swtich promoter design.


Figure 9. Color maps indicating functioning and non-functioning systems. Each letter represents different repressor binding site configurations. Each small square within the colour maps represents a score for a simulation of the system with a unique set of parameters. The colours correspond to the previously given description

2: The system performs to design, after a rhamnose input the toggle switch changes state and GFP is produced when CIλ leaves the system

1: The system performs less efficiently, though the toggle switch changes state, the GFP promoter is leaky


0: The system does not work, the toggle switch is out of balance and does not function, the system favors either LacI or TetR


Back to the lab

With new output from the promoter model, new promoters were made with different inhibitor binding sites with the BioBrick standard in mind. These promoters were then coupled in front of GFP and all 5 out of the 6 promoters we have designed have shown to work (Bba_K1493801, Bba_K1493802, Bba_K1493804, Bba_K1493805 and Bba_K1493806) . By showing GFP expression (see figure xx).

System model

Cost

Having the whole system in P. putida is great however there is always metabolic stress in everything that we want P. putida to produce. Therefore another model was developed to predict the cost of the whole system. The model indicates that the metabolic stress introduced by fungal growth inhibitors production should not pose a bottleneck. For more information read system cost

Figure 10: The relative growth rate compared to the wild type P. putida for different carbon uptake rates. The optimal solution is with glucose as carbon source, the realistic solution is with the banana exudates as carbon source. The expected carbon uptake rate of P. putida in the rhizosphere is indicated with transparent red.

Performance

Knowing that P. putida is able to cope with the whole system, the next objective is to assess the performance of the system; will the kill-switch function according to our expectations? Will the kill-switch kill P. putida in advance of performing its intended role as a fungicide due to imbalance of the toxin anti-toxin system?In order to answer these questions we created a stochastic whole system model, incorporating metabolic stress, leakiness of each individual promoter and the toxin anti-toxin syswtem. The results of this analysis are depicted in figure 4. For more information read model performance

Figure 11. Two histrograms showing the effect of leaky promoters on the system and the performance of the system upon induction by fusaric acid.
(A) For a Maximum growth rate of 180 minutes the stability of the kill-switch a basal CIλ production of 50 nM/min or higher destabilizes the kill-switch. The population dynamics are affected. Low protein dilution due to slow growth causes the Kill-switch to leak toxin. Higher basal production rates compensate, increasing the average growth rate but also the instability. A total of 5000 simulation were run.
(B) For a maximum growth rate of 180 minutes 98% of the kill-switches activate, longer division times activate the cells more effectively. A total of 20000 simulations were run

The stochastic model (figure 11) has shown that different basal production levels of CIλ can have different effects on population dynamics, cell growth and the stability of the kill-switch, a point of attention for final construct of the system. Finally, the kill-switch will perform with 98% efficiency given the slow growth rate in the soil predicted by the metabolic model.

Green house

We were able to establish a collaboration with the plant research international group of Wageningen, which gave us the unique opportunity to test the system, not only against F. oxysrporum, but in a setting that mimics the situation outside the lab as closely as possible with banana plants. At present we have banana plants in the green house (figure 12) that have been inoculate with our engineered P. putida and which were also infected with F. oxysporum. However, plants grow at a much slower pace than bacteria. So results were not possible to obtain before the wiki-freeze (see green house ).

Figure 12. Banana plants in greenhouse

In short

We as an iGEM team have achieved quiet a lot during these couple of months. Here is a short list of what we have achieved:

  • Validated and characterized a novel working fusaric acid dependent promoter
  • Proved that pyoverdine can be produce in an iron rich environment
  • Improve inhibiton of P. putida towards F. oxysporum
  • Show the proof of concept of the Kill-Switch using input output plasmid
  • Did an extensive characterization of the rhamnose promoter
  • Have a stable toggle switch that can be activated
  • Feedback loop with model and wetlab by promoter design
  • Have new promoters made and validated for future iGem team to use!
  • Have a model that predicts the metabolic cost of our whole system BananaGuard
  • Have a model that shows the performance of our whole system BananaGuard

Apart from all things in the lab, we have also been waiting patiently to see the results of the greenhouse. How will our engineered P.putida behave in the its final application against F. oxysporum! Is it good enough in the soil? is it enough to help the banana plants? Sadly, the results were not here before the wiki-freeze however we will present them at the jamboree! So stay tuned and come to our presentation!