Team:DTU Denmark/results

From 2009.igem.org

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As expected, both strains showed different profiles of growth accordingly to the substrate. For Glucose and Galactose, the growth curve showed two exponential phases, the first one corresponding to the growth on Glucose and the second corresponding to the growth on Galactose.  Although the initial OD was similar in both cases, the growth on Galactose showed an even longer lag phase than the glucose. Finally, as expected, the substrate reporting less growth was ethanol. For the Redoxilator, the growth solely on Glucose showed a longer lag phase compared to the mixed substrate, probably due to a lower initial OD.<br><br>
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<p align="justify">As expected, both strains showed different profiles of growth accordingly to the substrate. For Glucose and Galactose, the growth curve showed two exponential phases, the first one corresponding to the growth on Glucose and the second corresponding to the growth on Galactose.  Although the initial OD was similar in both cases, the growth on Galactose showed an even longer lag phase than the glucose. Finally, as expected, the substrate reporting less growth was ethanol. For the Redoxilator, the growth solely on Glucose showed a longer lag phase compared to the mixed substrate, probably due to a lower initial OD.</p><br><br>
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Regarding the GFP signal, all substrates showed different profiles. Nevertheless, the fermentative substrates, Glucose and Galactose, showed higher values of GFP than the respirative substrate, Ethanol.<br><br>
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<p align="justify">Regarding the GFP signal, all substrates showed different profiles. Nevertheless, the fermentative substrates, Glucose and Galactose, showed higher values of GFP than the respirative substrate, Ethanol.</p><br><br>
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Although these results are accordingly to what was expected, it is important to mention that these cultures didn’t have comparable growths, so, in order to subtract this variability of the growth, one should normalize the GFP expression with OD. Additionally, to the GFP values, the residual values for each case were subtracted.<br><br>
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<p align="justify">Although these results are accordingly to what was expected, it is important to mention that these cultures didn’t have comparable growths, so, in order to subtract this variability of the growth, one should normalize the GFP expression with OD. Additionally, to the GFP values, the residual values for each case were subtracted.</p><br><br>
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Revision as of 18:19, 21 October 2009

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The project

Home The Team The Project Parts submitted Modelling Notebook

The redoxilator

 - Genetic design
- Applications and perspectives
- Results
- Safety considerations
The USER assembly standard

 - USER fusion of biobricks
USER fusion primer design software

 - Abstract
- Instructions
- Output format
The project


 Results

Two strains were grown under diferent substrates, Glucose, Galactose, Glucose and Galactose and Ethanol. These two strains that we denominate Redoxilator and Leaky correspond to the redoxilator with a constitutive promoter and a minimal promoter repectivelly.

Growth rates (h-1) obtained for the two strains on diferent carbon sources

Carbon Source

Leaky

Redoxilator

Glucose

0,114 ± 0,006

0,112 ± 0,003

Galactose

0,084 ± 0,010

0,076 ± 0,003

Ethanol

E0,013 ± 0,005

0,007 ± 0,001


As expected, both strains showed different profiles of growth accordingly to the substrate. For Glucose and Galactose, the growth curve showed two exponential phases, the first one corresponding to the growth on Glucose and the second corresponding to the growth on Galactose. Although the initial OD was similar in both cases, the growth on Galactose showed an even longer lag phase than the glucose. Finally, as expected, the substrate reporting less growth was ethanol. For the Redoxilator, the growth solely on Glucose showed a longer lag phase compared to the mixed substrate, probably due to a lower initial OD.



Growth profile (OD) of the Redoxilator for the different carbon sources


Growth profile (OD) of the Leaky for the different carbon sources


Regarding the GFP signal, all substrates showed different profiles. Nevertheless, the fermentative substrates, Glucose and Galactose, showed higher values of GFP than the respirative substrate, Ethanol.



GFP signal of the Redoxilator for the different carbon sources


GFP signal of the Leaky for the different carbon sources



Although these results are accordingly to what was expected, it is important to mention that these cultures didn’t have comparable growths, so, in order to subtract this variability of the growth, one should normalize the GFP expression with OD. Additionally, to the GFP values, the residual values for each case were subtracted.



GFP signal corrected from the residual signal, normalized with growth of the Redoxilator for the different carbon sources


GFP signal corrected from the residual signal, normalized with growth of the Leaky for the different carbon sources



One other aspect that is worth instigating is the variation of the GFP signal with growth. In other words, if growth is correlated with GFP signal.

Variation of the corrected GFP signal with growth of the Redoxilator for the different carbon sources


Variation of the corrected GFP signal with growth of the Redoxilator for the different carbon sources

Achievements

Redox sensing device
Two novel genes have been designed and synthesized each comprised of 5 genetic elements. Together they function as a device termed the Redoxilator that can sense the internal redox state of a yeast cell, and output a reporter signal.

Biobricks
DNA of several new biobricks have been designed and submitted including a yeast optimized GFP reporter protein, a protein degradation sequence and a fast degradable yeast GFP. (Bronze medal)

We have demonstrated that our USER fusion biobrick works as expected and documented it (silver medal)

USER fusion Assembly standard
A new biobrick assembly standard that allows the rapid construction of multi-part devices have been developed and documented. The assembly standard offers many benefits: All restriction sites are allowed, multiple biobricks can be joined in one step, the result is scar-free making it ideal for protein fusions and more. (Gold medal)

USER-fusion primer design software
A novel and very useful software tool have been developed that can automatically design the optimal primers for USER fusion assembly of 2-9 biobricks, taking several parameters into account.

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