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<h4><a href="#header">MetabolicModeling</a></h4> | <h4><a href="#header">MetabolicModeling</a></h4> | ||
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<section id="Intro"> | <section id="Intro"> | ||
<h1>Metabolic Modeling</h1> | <h1>Metabolic Modeling</h1> | ||
− | <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 | + | <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 <a class="tooltip">chassis<span class="tooltiptext">The chassis is the base organism that is modified</span></a> 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></section> |
<section id="FBA"> | <section id="FBA"> | ||
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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.<br> | 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.<br> | ||
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.<br> | 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.<br> | ||
− | Given the published version of the model, 3.15 mmol* | + | Given the published version of the model, 3.15 mmol*gram Dry Weight^-1*hour^-1 was the parsimonious response when maximizing for biomass production whilst minimizing all other functions.<br> |
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.<br> | 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.<br> | ||
"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.<br> | "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.<br> | ||
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<br><section id="results"> | <br><section id="results"> | ||
<h1><b>Key Results</b></h1> | <h1><b>Key Results</b></h1> | ||
− | <p>The relationship between max ATP available for survival and water efflux is shown in Figure 1, it demonstrates that there is a linear relation. This implies that if no water is available for ATP used for maintenance outside cell growth, the cell will die. When the model is run without any modification, ie in an environment where it is in the exponential growth phase an ATP Maintenance flux of 3.15 | + | <p>The relationship between max ATP available for survival and water efflux is shown in Figure 1, it demonstrates that there is a linear relation. This implies that if no water is available for ATP used for maintenance outside cell growth, the cell will die. When the model is run without any modification, ie in an environment where it is in the exponential growth phase an ATP Maintenance flux of 3.15 mmol*gram Dry Weight^-1*hour^-1 is given as output by the model.</p><p> |
We do not know the amount needed in sugar water conditions, but because of these results we can start looking at the relationship between survival time and water efflux.</p><p> | We do not know the amount needed in sugar water conditions, but because of these results we can start looking at the relationship between survival time and water efflux.</p><p> | ||
In Figure 2 we can see not only the relationship of survival time against max ATP available for survival, but also how different thresholds of minimal cell-water tolerance would affect this relationship. The minimal cell-water tolerance threshold gives the value at which percentage of the remaining cell-water the point of no return for the cell had been reached. Which has a drastic effect on survival time, changing 20 minutes of maximum survival time to a mere ~90 seconds in the worst case scenario. | In Figure 2 we can see not only the relationship of survival time against max ATP available for survival, but also how different thresholds of minimal cell-water tolerance would affect this relationship. The minimal cell-water tolerance threshold gives the value at which percentage of the remaining cell-water the point of no return for the cell had been reached. Which has a drastic effect on survival time, changing 20 minutes of maximum survival time to a mere ~90 seconds in the worst case scenario. |
Revision as of 11:08, 4 October 2016
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 chassisThe 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. The relationship between max ATP available for survival and water efflux is shown in Figure 1, it demonstrates that there is a linear relation. This implies that if no water is available for ATP used for maintenance outside cell growth, the cell will die. When the model is run without any modification, ie in an environment where it is in the exponential growth phase an ATP Maintenance flux of 3.15 mmol*gram Dry Weight^-1*hour^-1 is given as output by the model.
We do not know the amount needed in sugar water conditions, but because of these results we can start looking at the relationship between survival time and water efflux.
In Figure 2 we can see not only the relationship of survival time against max ATP available for survival, but also how different thresholds of minimal cell-water tolerance would affect this relationship. The minimal cell-water tolerance threshold gives the value at which percentage of the remaining cell-water the point of no return for the cell had been reached. Which has a drastic effect on survival time, changing 20 minutes of maximum survival time to a mere ~90 seconds in the worst case scenario.
Figure 1 shows us that osmotic pressure alone can indeed have an effect on cell regulation and cell death and from Figure 2 it appears that the minimal water allowance threshold has a high impact on range of possible times. We also must accept that the range outside of 90 seconds to 90 minutes is completely undocumented territory as we can only say something about non-infinite values. Because we don't exactly know how much mmol*gDW-1*hour-1 is needed for proper maintenance under harsh conditions, we can not say anything about where on the scale that would be.
What we can say is that if the cells can survive for longer outside of this period, then they must have enough ATP available for basic maintenance, and that if cell death occurs then, that other processes than pure water-efflux must be the cause of that. Perhaps combinations of lack of nutrients and water-efflux, or over production of osmolytes to keep the balance.
Metabolic Modeling
What is Flux Balanace Analysis
Key Results
Conclusion