Difference between revisions of "Team:Pumas Mexico/Model"

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<p style="font-size:18px">It includes 843 out of 7,100 annotated genes (around 12%), delineating 1,770 metabolites and 2,294 reactions, being the amino acid and lipid metabolisms the most accurately reconstructed <sup>2</sup>. Importantly the authors of this model report that the uptake rates were experimentally verified experimentally.</p>
 
<p style="font-size:18px">It includes 843 out of 7,100 annotated genes (around 12%), delineating 1,770 metabolites and 2,294 reactions, being the amino acid and lipid metabolisms the most accurately reconstructed <sup>2</sup>. Importantly the authors of this model report that the uptake rates were experimentally verified experimentally.</p>
  
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<p style="font-size:18px">First, we analyzed which light wavelength was the best for the overall growth of the algae according to the metabolic model. When comparing different type of lights in the metabolic model, we couldn't find a notorious difference between the different light sources, while in the literature it is reported that the best light for growing <i>Chlorella</i> on long periods is the blue one (wavelength of 475 nm)
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<p style="font-size:18px">First, we analyzed which light wavelength was the best for the overall growth of the algae according to the metabolic model. When comparing different type of lights in the metabolic model, we couldn't find a notorious difference between the different light sources. It's important to emphasize that this only happens if we find and apply the optimal value in each of the conditions.
 
</p>
 
</p>
  
 
<p style="font-size:18px">
 
<p style="font-size:18px">
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With this, we can see that if you optimize the light conditions in a rank; you can obtain the same biomass production values, independently from your initial light source.
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Spectral decomposition of solar light measured from outer space is the first studied condition. In this case we find the solution that optimized best our model, more specifically the one that increases the overall production.
 
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<div style="text-align:center"><p><center>Solar Light<center></p><img src="https://static.igem.org/mediawiki/2016/d/d0/T--Pumas_Mexico--_wt_opt_solarlight.png" ></div>
 
  
 
<div style="text-align:center"><p><center>Solar Light (Optimized)<center></p><img src="https://static.igem.org/mediawiki/2016/7/7c/T--Pumas_Mexico--optimized_solarlight.png" ></div>
 
<div style="text-align:center"><p><center>Solar Light (Optimized)<center></p><img src="https://static.igem.org/mediawiki/2016/7/7c/T--Pumas_Mexico--optimized_solarlight.png" ></div>
  
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<div style="text-align:center"><p><center>Growthroom light comparison wt-optimized<center></p><img src="https://static.igem.org/mediawiki/2016/4/4d/T--Pumas_Mexico--wt_opt_growthroom.png" ></div>
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<p style="font-size:18px">
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Spectral decomposition of growth room is the second studied condition. We repeated the previously described analysis.
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</p>
  
 
<div style="text-align:center"><p><center>With Growth room light search optimal intensity<center></p><img src="https://static.igem.org/mediawiki/2016/b/ba/T--Pumas_Mexico--optimized_growthroom.png" ></div>
 
<div style="text-align:center"><p><center>With Growth room light search optimal intensity<center></p><img src="https://static.igem.org/mediawiki/2016/b/ba/T--Pumas_Mexico--optimized_growthroom.png" ></div>
  
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<div style="text-align:center"><p><center>Solar vs Growthroom lights<center></p><img src="https://static.igem.org/mediawiki/2016/8/89/T--Pumas_Mexico--solar_growthroom.png" ></div>
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<p style="font-size:18px">
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Dynamics of the possible optimal values in each of the conditions.
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</p>
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<div style="text-align:center"><p><center>With Growth room light search optimal intensity<center></p><img src="https://2016.igem.org/File:T--Pumas_Mexico--solar_growthroom.png" ></div>
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<p style="font-size:18px">
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With this, we can see that if you optimize the light conditions in a rank; you can obtain the same biomass production values, independently from your initial light source.
 +
</p>
  
 
<p style="font-size:18px">Then, we analyzed the resources and nutrients for the culture. We simulated more water and carbon sources in the medium. Also we tried the effect of oxygen, given that it is present in small quantities, because we were not able to get a sealed biorreactor. For the water and oxygen simulations, we used the photoautotroph model, while for the carbon source (acetate) we used the heterotroph one. The plots of these experiments are below.
 
<p style="font-size:18px">Then, we analyzed the resources and nutrients for the culture. We simulated more water and carbon sources in the medium. Also we tried the effect of oxygen, given that it is present in small quantities, because we were not able to get a sealed biorreactor. For the water and oxygen simulations, we used the photoautotroph model, while for the carbon source (acetate) we used the heterotroph one. The plots of these experiments are below.

Revision as of 05:08, 19 October 2016

Pumas_Mexico



Modeling

Chlorella vulgaris modelling by means of Flux Balance Analysis

To model the growth and lipid production of Chlorella vulgaris we used the Constraint-Based Modelling, being our principal tool the kit the COBRApy library offers 1. The metabolic reconstruction we used was that of Chlorella vulgaris UTEX 395, published on July of this year 2. This reconstruction is based on Chlamydomonas reinhardii, with experimental and bioinformatic data on the literature.

It includes 843 out of 7,100 annotated genes (around 12%), delineating 1,770 metabolites and 2,294 reactions, being the amino acid and lipid metabolisms the most accurately reconstructed 2. Importantly the authors of this model report that the uptake rates were experimentally verified experimentally.

First, we analyzed which light wavelength was the best for the overall growth of the algae according to the metabolic model. When comparing different type of lights in the metabolic model, we couldn't find a notorious difference between the different light sources. It's important to emphasize that this only happens if we find and apply the optimal value in each of the conditions.

Spectral decomposition of solar light measured from outer space is the first studied condition. In this case we find the solution that optimized best our model, more specifically the one that increases the overall production.

Solar Light (Optimized)

Spectral decomposition of growth room is the second studied condition. We repeated the previously described analysis.

With Growth room light search optimal intensity

Dynamics of the possible optimal values in each of the conditions.

With Growth room light search optimal intensity

With this, we can see that if you optimize the light conditions in a rank; you can obtain the same biomass production values, independently from your initial light source.

Then, we analyzed the resources and nutrients for the culture. We simulated more water and carbon sources in the medium. Also we tried the effect of oxygen, given that it is present in small quantities, because we were not able to get a sealed biorreactor. For the water and oxygen simulations, we used the photoautotroph model, while for the carbon source (acetate) we used the heterotroph one. The plots of these experiments are below.

Referencias:

1. Ebrahim, A., Lerman, J. A., Palsson, B. O., & Hyduke, D. R. (2013). COBRApy: constraints-based reconstruction and analysis for python. BMC systems biology, 7(1), 74.

2. Zuñiga, C., Li, C. T., Huelsman, T., Levering, J., Zielinski, D. C., McConnell, B. O., ... & Betenbaugh, M. J. (2016). Genome-scale metabolic model for the green alga Chlorella vulgaris UTEX 395 accurately predicts phenotypes under autotrophic, heterotrophic, and mixotrophic growth conditions. Plant Physiology, pp-00593.

3. Blair, M. F., Kokabian, B., & Gude, V. G. (2014). Light and growth medium effect on Chlorella vulgaris biomass production. Journal of environmental chemical engineering, 2(1), 665-674.