Difference between revisions of "Team:Valencia UPV/Modeling/Conclusions"

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<p>After modeling AladDNA, these are the most important features that characterize our genetically engineered machine:</p>
 
<p>After modeling AladDNA, these are the most important features that characterize our genetically engineered machine:</p>
<p>-   It is controlled by two consecutive inputs, each of both can be blue or red light, and their combination results in different outputs.</p>
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<p>When both inputs are of the same color, it is better to consider them as a single long input, avoiding pauses in the induction and dark intermediate periods.</p>
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<p>When first and second input differ in color, recombinases action is the key element in order to activate the second input. The efficiency of the whole process is affected by the time required by these enzymes to inactivate the production of the second level that was not activated.</p>
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<li>It is controlled by two consecutive inputs, each of both can be blue or red light, and their combination results in different outputs.</li>
<p>Massive amounts of gene copies result in high levels of basal expression which are enough to produce both recombinases, that cut alternatives of the second level.</p>
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<li>When both inputs are of the same color, it is better to consider them as a single long input, avoiding pauses in the induction and dark intermediate periods.</li>
<p>Multiple production pathways are possible with simultaneous inputs and sequences with more than two input elements.  
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<li>When first and second input differ in color, recombinases action is the key element in order to activate the second input. The efficiency of the whole process is affected by the time required by these enzymes to inactivate the production of the second level that was not activated.</li>
<p>Input sequences that achieve maximum results for the production of each output are:</p>
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<li>Massive amounts of gene copies result in high levels of basal expression which are enough to produce both recombinases, that cut alternatives of the second level.</li>
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<li>Multiple production pathways are possible with simultaneous inputs and sequences with more than two input elements.</li>
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Input sequences that achieve maximum results for the production of each output are:
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<div style="text-align:center;"><h5><b>Alpha input sequence.</b></h5></div>
 
<div style="text-align:center;"><h5><b>Alpha input sequence.</b></h5></div>

Revision as of 18:50, 14 November 2015

Valencia UPV iGEM 2015

After modeling AladDNA, these are the most important features that characterize our genetically engineered machine:

  • It is controlled by two consecutive inputs, each of both can be blue or red light, and their combination results in different outputs.
  • When both inputs are of the same color, it is better to consider them as a single long input, avoiding pauses in the induction and dark intermediate periods.
  • When first and second input differ in color, recombinases action is the key element in order to activate the second input. The efficiency of the whole process is affected by the time required by these enzymes to inactivate the production of the second level that was not activated.
  • Massive amounts of gene copies result in high levels of basal expression which are enough to produce both recombinases, that cut alternatives of the second level.
  • Multiple production pathways are possible with simultaneous inputs and sequences with more than two input elements.
Input sequences that achieve maximum results for the production of each output are:
Alpha input sequence.

Beta input sequence.

Gamma input sequence.

Omega input sequence.

References

1. MÜLLER, K. et al. (2014). A red light-controlled synthetic gene expression switch for plant systems. Royal Society of chemistry.

2. MÜLLER, K. ZURBRIGGEN, M & WEBER, W (2014). Control of gene expression using a red- and far-red light-responsive bi-stable toggle switch. University of Freiburg, Germany. Nature America.

3. VIGNONI, A. BOADA, Y. REYNOSO-MEZA, G & PICÓ, J. (2015). Obtaining model based guidelines for the design of synthetic devices with robust performance. An adaptive network case. Universitat Politècnica de València UPV. Frontiers in Bioengineering.

4. PICÓ, J et al. (2015). Modelado de sistemas bioquímicos: de la Ley de Acción de Masas a la Aproximación Lineal del Ruido. Valencia, España. ELSEVIER.

5. ZHOU, X et al. (2012). Optical control of protein activity by fluorescent protein domains. Stanford, CA, USA. Science.

6. :BONNET, J. SUBSOONTORN, P & ENDY, D. (2012). Rewritable digital data storage in live cells via engineered control of recombination directionality. Stanford, CA, USA. PNAS.

7. BONNET, J. SUBSOONTORN, P & ENDY, D. (2012). Supporting Information: Rewritable digital data storage in live cells via engineered control of recombination directionality. Stanford, CA, USA. PNAS.

8. QUIJANO RUBIO, A. (2015). Construcción de un Nuevo interruptor genético basado en recombinación específica de sitio para Biología Sintética de Plantas. TFG. Valencia, Universitat Politècnica de València Editorial.

9. PICO, VIGNONI,MUÑOZ (2015).Chapter 2 of Syntethic biology Wet&Dry lab PICO, VIGNONI,MUÑOZ (2015). John Wiley&Sons Publication.

10. PICO, VIGNONI, PICO-MARCO, BOADA. (2015) Modelado de sistemas bioquímicos:de la Ley de Accion de Masas a la Aproximaci ón Lineal del Ruido . Science direct.