Team:KUAS Korea/DryLab/Conclusion
Modeling Results & Conclusion |
Modeling results
- We coded python for our mathematical mode. We can change the parameter values.
[Fig 1] Python code
We plotted graph by this python code, and these are results. We changed glucose capture efficiency value for each graph. In graph orange shows cheater's growth rate, and blue graph shows the cooperator's growth rate.
[Fig 2] curve of epsilon is 0.002
[Fig 3] Curve of epsilon = 0.2
[Fig 4] Curve of epsilon = 0.8
[Fig 5] code which plot the rainbow curve
If epsilon is 0, shows the blue cheater graph. And if epsilon is 1, shows the red cheater graph.
Conclusion
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1. Calculation of the flux of glucose into a cooperator cell
• Measurement of displayed β-glucosidase per cell using whole-cell activity
- Vmax = 2.49 x 10^7 glucose·s-1 per cell
- The specific growth rate = 0.61 h-1 in 0.004% (w/v) glucose (5.16 x 10^5 cells·μL-1)
- Glucose creation rate = 2.40 x 10^7 glucose·s-1 per cell
- Glucose consumption = 2.59 x 10^8 glucose per cell
• The resulting flux of glucose into a single cell
= the growth rate x the number of glucose molecules per cell = 4.39 x 10^4 glucose ·s-1 per cell
[Fig 5] glucose capture efficiency
And we esitmated the efficency of glucose capture with dividing glucose flux by glucose creation rate. We assumed that the glucose molecules produced by β-glucosidase directly diffuse into media because it is located in the outer membrane of E.coli. And this will cause temporary increase of glucose concentration by a local cloud of glucose at the surface. And this will benefit to influx rate of the glucose into the cell.
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