Team:Peking R/Project/Application

From 2011.igem.org

Revision as of 00:07, 6 October 2011 by KeyboardKen (Talk | contribs)

Template:Https://2011.igem.org/Team:Peking R/bannerhidden Template:Https://2011.igem.org/Team:Peking R/back2 Template:Https://2011.igem.org/Team:Peking R/Projectbackground 无标题文档

Softcoding of Genetic Program


During the first wave of synthetic biology, many functional genetic devices were constructed based on engineering principles, including logic gates, switches, oscillators and sensors. However, most cases do not exhaust the understanding accumulated by previous biological research. Previous design and construction of genetic devices mostly rely on concepts borrowed from electronic engineering, rather than design principles or methods developed specially for synthetic biology itself.

The topology of devices leads to parameter sensitivity, thus screening for well performing devices requires laborious, time-consuming refinement cycles. Additionally, lack of well-characterized parts and devices, complicated but not-so reliable models, and fluctuation caused by intrinsic noise of biological system also contribute to the limitation. Similar problems exist in the field of metabolic engineering. When constructing more complex genetic program to perform more complicated functions, such obstacles become more obvious and need to be solved urgently.

This year our team developed a platform for soft-coding of genetic circuits aiming at making screening fast, affordable and more predictable. The platform is composed of a RNA controller toolkit and an RBS calculator as illustrated previously in our project. To demonstrate the versatility and validity of the platform, we utilized the platform to improve performance of two modular genetic devices, AND gate and bistable switch.

Figure 1. AND gate performance regulated by different concentration of thiamine pyrophosphate (TPP). The on/off ratio of AND gate increases with ligand concentration, while the single induction of arabinose is diminished, resulting in an AND gate with improved performance.

Figure 2.  Fluorescence images of E.coli DH5α strain populations with different plasmids from bistable switch mutant library. Each plasmid contains different ribosome binding sites (RBSs) which control the expression of cI434 gene, demonstrating that the ratiometric of green cells to red cells is correlated with translation strength.

We further applied this platform to optimize a segment of violacein biosynthetic pathway, and achieved producing purer desired products.

 

Figure 3. E. coli producing pigments. When induced by arabinose, the engineered E. coli produced dark-green pigments. Upon addition of different concentration of thiamine pyrophosphate (TPP), the color of the bacteria gradually shifted from dark-green to dark-brown.


Reference:

 

 

 

 

[TOP]