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<h4>Acetaminophen <img class="acetaminophen" src="https://upload.wikimedia.org/wikipedia/commons/thumb/2/29/Paracetamol-skeletal.svg/1200px-Paracetamol-skeletal.svg.png" style="width:168px;height=128px"> </h4> | <h4>Acetaminophen <img class="acetaminophen" src="https://upload.wikimedia.org/wikipedia/commons/thumb/2/29/Paracetamol-skeletal.svg/1200px-Paracetamol-skeletal.svg.png" style="width:168px;height=128px"> </h4> | ||
− | <div class=text- | + | <div class=text-container> |
To predict theoretical acetaminophen production, we calculated the amount of its precursor, chorismate, by quantifying its main products, the aromatic amino acids phenylalanine, tyrosine, and tryptophan. | To predict theoretical acetaminophen production, we calculated the amount of its precursor, chorismate, by quantifying its main products, the aromatic amino acids phenylalanine, tyrosine, and tryptophan. | ||
− | Since no amino acid composition data was available for Synechococcus, we started by using literature data for the similar cyanobacteria species Spirulina found that between 11 and 13.6 percent of amino acids were aromatics by mass, or between 6.5 and 7.7 molar percent of total protein. | + | Since no amino acid composition data was available for Synechococcus, we started by using literature data for the similar cyanobacteria species Spirulina found that between 11 and 13.6 percent of amino acids were aromatics by mass, or between 6.5 and 7.7 molar percent of total protein. Even using the lower aromatic percentages and assuming a third of precursor goes to our pathway, we predict 22.6mg acetaminophen per gram biomass. |
− | + | ||
</br> | </br> | ||
</div> | </div> | ||
− | + | $$ | |
− | + | \frac{0.449\ mmol\ FWY}{1g\ biomass}\approx \frac{0.449\ mmol\ chor.}{1g\ biomass}\rightarrow\frac{1\ mol\ acet.}{3\ mol\ chor.}=\frac{0.15\ mmoles\ acet}{1\ g\ biomass}\times\frac{151.163g\ acet.}{1\ mol\ acet.}=\frac{22.62mg\ acet.}{1g\ biomass}$$ | |
+ | <div class=text-cuntainer> | ||
+ | An estimate for acetaminophen production using the amino acid composition for Spirulina and assuming one third of the precursor goes to our enzyme, 4ABH. | ||
+ | </div> | ||
</br> | </br> | ||
− | <div class=text- | + | <div class=text-container> |
− | Using our sequence | + | To further verify our organism's amount of acetaminophen precursor, we ran both the genome and ribosomal protein sequences through a custom Python program converting codons to amino acids and calculating aromatic amino acid molar percentages which resulted in 9.3% and 5.14% respectively. Using our sequence analysis based value of 9.3% and the assumption that our enzymes would take a third of the acetaminophen precursor, we estimate an acetaminophen concentration would be around 18mg per gram dried biomass. |
− | + | ||
</br> | </br> | ||
</div> | </div> | ||
− | $$\frac{0. | + | $$\frac{0.093\ g\ FYW}{1\ g\ protein}\times\frac{0.6g protein}{1\ biomass}=\frac{0.056\ g\ FYW}{1g\ biomass}\rightarrow\frac{0.37\ mmol\ chor}{1\ g\ biomass}\times\frac{1\ mol\ acet}{3\ mol\ chor}\times\frac{151.163g\ acet}{1\ mol\ acet.}=\frac{18.61mg\ acet.}{1g\ biomass}$$ |
− | + | <div class=text-cuntainer> | |
+ | This equation is based on moles of aromatic amino acids calculated by translating the organism's 3MB genome and assuming a third of precursor goes to our pathway. | ||
+ | </div> | ||
+ | </br> | ||
+ | <div class=text-container> | ||
+ | These numbers show that there is likely enough precursor and that acetaminophen production should be within a userful, measurable range of up to 23mg acetaminophen per gram biomass. | ||
+ | </div> | ||
</div> | </div> | ||
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+ | .text-cuntainer { | ||
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Revision as of 01:03, 21 September 2017
Modeling
Predict and optimize yield.
Acetaminophen
To predict theoretical acetaminophen production, we calculated the amount of its precursor, chorismate, by quantifying its main products, the aromatic amino acids phenylalanine, tyrosine, and tryptophan.
Since no amino acid composition data was available for Synechococcus, we started by using literature data for the similar cyanobacteria species Spirulina found that between 11 and 13.6 percent of amino acids were aromatics by mass, or between 6.5 and 7.7 molar percent of total protein. Even using the lower aromatic percentages and assuming a third of precursor goes to our pathway, we predict 22.6mg acetaminophen per gram biomass.
$$
\frac{0.449\ mmol\ FWY}{1g\ biomass}\approx \frac{0.449\ mmol\ chor.}{1g\ biomass}\rightarrow\frac{1\ mol\ acet.}{3\ mol\ chor.}=\frac{0.15\ mmoles\ acet}{1\ g\ biomass}\times\frac{151.163g\ acet.}{1\ mol\ acet.}=\frac{22.62mg\ acet.}{1g\ biomass}$$
An estimate for acetaminophen production using the amino acid composition for Spirulina and assuming one third of the precursor goes to our enzyme, 4ABH.
To further verify our organism's amount of acetaminophen precursor, we ran both the genome and ribosomal protein sequences through a custom Python program converting codons to amino acids and calculating aromatic amino acid molar percentages which resulted in 9.3% and 5.14% respectively. Using our sequence analysis based value of 9.3% and the assumption that our enzymes would take a third of the acetaminophen precursor, we estimate an acetaminophen concentration would be around 18mg per gram dried biomass.
$$\frac{0.093\ g\ FYW}{1\ g\ protein}\times\frac{0.6g protein}{1\ biomass}=\frac{0.056\ g\ FYW}{1g\ biomass}\rightarrow\frac{0.37\ mmol\ chor}{1\ g\ biomass}\times\frac{1\ mol\ acet}{3\ mol\ chor}\times\frac{151.163g\ acet}{1\ mol\ acet.}=\frac{18.61mg\ acet.}{1g\ biomass}$$
This equation is based on moles of aromatic amino acids calculated by translating the organism's 3MB genome and assuming a third of precursor goes to our pathway.
These numbers show that there is likely enough precursor and that acetaminophen production should be within a userful, measurable range of up to 23mg acetaminophen per gram biomass.
Biomass ![](https://static.igem.org/mediawiki/2017/5/5c/Spirulina_powder.png)
To understand the production capacity of our organism, we aggregated growth data from published papers and all of our lab’s growth data. Using limited logistic growth curves and linear algebra to fit our equation, we modelled dried biomass and cell count per time, with the additional dependent variables of temperature, light intensity, and starter culture density.
Timescale:
days
Light Intensity:
μE m-2 s-1
Temperature:
℃
Starting Density:
g biomass/ L