Difference between revisions of "Team:Wageningen UR/testpage"

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  <a href="#Bees">Saving the Bees</a>
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  <a href="#Bees">Introduction</a>
 
 
 
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  <a href="#something">Something</a>
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  <a href="#something">What is FBA</a>
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<section id="Bees">
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<h1>Fungal resistance journal</h1>
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<h1>Metabolic Modeling</h1>
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<p>All transformations were done in <i>E. coli</i>. Preparation of the backbones was done in DH5alfa, while for transformations with the clusters JM109 was used.</p>
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<p>In order to assess the real world viability of the BeeT we evaluated the proposed system of
 +
application by making a model of the entire system. To do this we used Flux Balance
 +
Analysis (FBA) to make model the base chassis. The chassis [tooltip: Chassis is the base organism that is modified] of BeeT is a variant of
 +
<i>​ Escherichia coli
 +
</i>, for which it is known that it does not grow in sugar water, mainly due
 +
to high osmotic pressure <sup> <a href="#fn1" id="ref1">1</a></sup> <!­­-- REFERENCE: The Effect of Sucrose­induced Osmotic Stress on
 +
the Intracellular level of cAMP in Escherichia coli using Lac Operon as an Indicator, Yu Ling
 +
Cheng, Jiyoung Hwang, and Lantai Liu --­­>. The question remained: Does it survive there,
 +
and if so, for how long? </p>
 
                              
 
                              
 
                              
 
                              
  
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<h2 class="timelineMajorMarker"><span>May</span></h2>
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<a class="timelineMajor"><span>Flux balance analysis (FBA) is a mathematical method for simulating metabolism in genome-scale reconstructions of metabolic networks.</span></a>
 
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<dt id="02w1"><a>Growth experiments</a></dt>
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<dt id="02w1"><a>In-depth explanation</a></dt>
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<p>Growth experiments were conducted with fusaric acid concentrations ranging from 0 to 250 ug/ml were performed on <i>Eschericia coli (Strains DH5alfa, BL21 and JM109), Bacillus subtilis</i> and <i>Pseudomonas putida</i>. After 18 hours of incubation at 37 degress celcius, OD 600 measurements were taken.</p>
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<p> The main components of FBA are reactions and metabolites, which are derived from knowledge about genes and the enzymes they produce to facilitate the reactions between metabolites.
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Reactions are represented as rows in a matrix of numbers showing a positive number for production and a negative number for consumption, the numbers representing stoichiometrically balanced chemical equations.</p><p>
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                                                        <figure>
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Fluxes are represented as a vector of numbers representing the speed and direction of each reaction. The optimize function will find a parsimonious solution, given a certain objective or multiple objective reaction fluxes to maximize, or minimize if that is the case.</p><p>
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                                                        <img src="https://static.igem.org/mediawiki/2014/1/13/Wageningen_UR_journal_resistance_resistance_assay.png" width="800px">
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When using FBA the objective is usually the "Biomass reaction", which is a kind of resource sink that consumes all kinds of metabolites to represent growth and cell division, which makes sense given that most cells in the exponential phase will allocate as many resources as possible to cell division.
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                                                        <figcaption>
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An important set of reactions is the exchange reactions which represent whether the growth medium itself is either losing or gaining certain metabolites at a certain rate. This represents compounds accumulating in or getting taken up from the medium.</p><p>
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                                                        Figure 1. Both <i>B. subtilis</i> and all of the <i>E. coli</i> strains show a strong response to increasing doses of fusaric acid in the medium. <i>P. putida</i>, however, does not show any decrease in growth for the concentrations used. Therefore another experiment was done with higher concentrations for <i>P. putida</i>.
+
There is also an ATP Maintenance reaction, another resource sink, which represents all ATP required to maintain gene-regulation and regular functioning of a non-growing cell.
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                                                        </figcaption>
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Given the published version of the model, 3.15 mmol*gDW^-1*h^-1 was the parsimonious response when maximizing for biomass production whilst minimizing all other functions.</p><p>
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                                                        </figure>
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Every flux has certain bounds based on the medium the cell is in and what is known to be biologically possible for a specific organism to take up. These bounds have to be either experimentally determined, but in other cases are put at -1000 for the lower, and +1000 for the upper. The entire range of objective solutions can also be looked for, for every flux, this is known as Flux Variance Analysis, but in general a solution is preferred such that all other fluxes are as low as possible. </p><p>
−
                                                       
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"Parsimonious Flux Balance Analysis” was born from the argument that less flux through a certain reaction means less effort the cell has to expend on the production of a certain protein and thereby will be more evolutionarily beneficial in the long term. It is to me the most sensible way to pick a specific solution from the allowed solution space created from a certain Metabolic Linear Programming Problem.</p><p>
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                                                        <p><i><b>NOTE: After ordering new fusaric acid later in the project, it was found out that the fusaric acid used in this experiment was not the same strength, with the old one most likely being (partially) degraded. Therefore data from this experiment is not used.</b></i></p>
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On the BIGG database we found a pre-existing well characterized metabolic model, named iJO1366 from the paper: “A comprehensive genome-scale reconstruction of Escherichia coli metabolism”. Orth JD1, Conrad TM, Na J, Lerman JA, Nam H, Feist AM and Palsson BØ.
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                                                        </p>
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In order to work with the model in smbl format the python package CobraPy was downloaded to facilitate the manipulation and perturbation of the “in silico organism“. [ COBRApy: COnstraints-Based Reconstruction and Analysis for Python ]</p><p>
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The previously mentioned exchange reactions were modified by reading in the reaction ids and their upper and lower bounds. [Link to small page about file.]</p><p>
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Then we changed the objective from Biomass to ATP maintenance in order to represent the ‘starvation mode’ which we assume the cell to be in.
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And finally we loop through a range of water efflux rates from the cell and produce a value for the objective, given minimal other fluxes.  
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<h2 class="timelineMajorMarker"><span>June</span></h2>
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<dt id="02w2"><a>HPLC</a></dt>
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<p>Since some soil bacteria are known to be able to degrade fusaric acid (FA), a HPLC experiment was started to test <i>P. putida</i>(PP) for fusaric acid degradation and carbon utilization. M9 media was used with glucose/fusaric acid(250ug/ml) or both as a carbon source.  </p>
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                                                        <p>For the HPLC the following settings were used.  </p>
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                                                        <li>Column: Polaris C18A</li>
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                                                        <li>Eluent: Acetonitril</li>
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                                                        <li>Temperature: 35 degrees Celsius</li>
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                                                        <li>Detection: UV (260 - 280nm)</li>
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                                                        <figcaption>
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                                                        Figure 2. Left: The HPLC method used delivered a good calibration curve, but peak resolvance was not optimal, with the FA peak having overlap with several smaller peaks in the samples with <i>P. putida</i>. Therefore it was decided to repeat the experiment to improve the HPLC method. </br>
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                                                        Right: Initial results on fusaric acid breakdown showed signs of breakdown, but because peak resolvance was not optimal and the measurements were not done in duplo more data was needed to draw conclusions.                                                     
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                                                        </figcaption>
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                                                        </figure>
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                                                        <p>Based on the initial results a more elaborate experiment was started in duplo. Six samples would be grown in duplo:</p>
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                                                        <li>A. Negative control for growth on M9 without carbon source. (PP+, Glucose-, FA-)</li>
+
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                                                        <li>B. Positive control for growth on M9 with carbon source (glucose).(PP+, Glucose+, FA-)</li>
+
−
                                                        <li>C. Positive control for growth on M9 with carbon source and fusaric acid. (PP+, Glucose+, FA-)</li>
+
−
                                                        <li>D. Test for PP growth on FA as carbon source.(PP+, Glucose-, FA+)</li>
+
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                                                        <li>E. E. Negative control for contamination and FA stability. (PP+, Glucose-, FA-)</li>
+
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                                                        <li>F. Negative control for contamination. (PP-, Glucose+, FA-)</li>
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<h1><b>Saving the Bees</b></h1>
 
<h1><b>Saving the Bees</b></h1>
 
<p> Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.  
 
<p> Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.  
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<b>iGEM team Wageningen 2016</b> has designed and created BeeT, a genetic system in <i>Escherichia coli</i> that detects the presence of <i>Varroa. destructor</i> in the bee hive and produces a combination of chitinases and Cry/Cyt/Mtx toxins to remove them! If you want to read more about the system and our work during the last six months, the <b>iGEM team Wageningen 2016</b> invites you to continue surfing around our Wiki.<sup> <a href="#fn1" id="ref1">1</a></sup></p>
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<b>iGEM team Wageningen 2016</b> has designed and created BeeT, a genetic system in <i>Escherichia coli</i> that detects the presence of <i>Varroa. destructor</i> in the bee hive and produces a combination of chitinases and Cry/Cyt/Mtx toxins to remove them! If you want to read more about the system and our work during the last six months, the <b>iGEM team Wageningen 2016</b> invites you to continue surfing around our Wiki.
 
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<h2>References</h2>
 
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<a id="fn1" href=http://www.sciencedirect.com/science/article/pii/S0966842X11001752>1.</a> Evans, J. D., & Schwarz, R. S. (2011). Bees brought to their knees: microbes affecting honey bee health. Trends in microbiology, 19(12), 614-620 <a href="#ref1" title="Jump back to footnote 1 in the text.">↩</a>
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<a id="fn1" href=https://www.microbiology.ubc.ca/sites/default/files/roles/drupal_ungrad/JEMI/15/JEMI15_15-21.pdf>1.</a> Cheng, Y. L., Hwang, J., & Liu, L. (2011). The Effect of Sucrose-induced Osmotic Stress on the Intracellular Level of cAMP in Escherichia coli using Lac Operon as an Indicator. Journal of Experimental Microbiology and Immunology (JEMI) Vol, 15, 15-21. <a href="#ref1" title="Jump back to footnote 1 in the text.">↩</a>
 
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Revision as of 15:43, 3 October 2016

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Wageningen UR iGEM 2016

 

Metabolic Modeling

In order to assess the real world viability of the BeeT we evaluated the proposed system of application by making a model of the entire system. To do this we used Flux Balance Analysis (FBA) to make model the base chassis. The chassis [tooltip: Chassis is the base organism that is modified] of BeeT is a variant of ​ Escherichia coli , for which it is known that it does not grow in sugar water, mainly due to high osmotic pressure 1 . The question remained: Does it survive there, and if so, for how long?


Flux balance analysis (FBA) is a mathematical method for simulating metabolism in genome-scale reconstructions of metabolic networks.
In-depth explanation




Saving the Bees

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum. iGEM team Wageningen 2016 has designed and created BeeT, a genetic system in Escherichia coli that detects the presence of Varroa. destructor in the bee hive and produces a combination of chitinases and Cry/Cyt/Mtx toxins to remove them! If you want to read more about the system and our work during the last six months, the iGEM team Wageningen 2016 invites you to continue surfing around our Wiki.

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Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

Tiny Bee

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

Tiny Bee

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

Lorem ipsum dolor sit amet, consectetur adipiscing elit, sed do eiusmod tempor incididunt ut labore et dolore magna aliqua. Ut enim ad minim veniam, quis nostrud exercitation ullamco laboris nisi ut aliquip ex ea commodo consequat. Duis aute irure dolor in reprehenderit in voluptate velit esse cillum dolore eu fugiat nulla pariatur. Excepteur sint occaecat cupidatat non proident, sunt in culpa qui officia deserunt mollit anim id est laborum.

References

    1. Cheng, Y. L., Hwang, J., & Liu, L. (2011). The Effect of Sucrose-induced Osmotic Stress on the Intracellular Level of cAMP in Escherichia coli using Lac Operon as an Indicator. Journal of Experimental Microbiology and Immunology (JEMI) Vol, 15, 15-21. ↩