Team:Peking R/Project/Application

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  <p class="notbookmaintitle" align=center>Softcoding of Genetic Program<a name="start" id="start"></a></p>
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    <th width="638" height="108" scope="col"><p class="mainbody">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. </p></th>
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    <td height="318"><p align="center"><img src="project Application final_clip_image002.jpg" alt="" width="466" height="251" /></p>
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<p class="picturemark">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 a well performed AND gate.</p></td>
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    <td height="178"><p><span class="mainbody">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. </span></p></td>
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    <td height="241"><p align="center"><img src="project Application final_clip_image002_0000.jpg" alt="" width="587" height="147" /></p>
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<p class="picturemark">Figure 2<strong>.</strong>  Fluorescence images of <em>E.coli</em> DH5α strain  populations with different plasmids from bistable switch mutant library. Each  plasmid contains different ribosome binding sites (RBSs) which control the  expression of <em>cI434 </em>gene, demonstrating  that the ratiometric of green cells to red cells is correlated with translation  strength.</p></td>
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  <p align="center"><img src="project Application final_clip_image002_0001.jpg" alt="" width="606" height="172" /></p>
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  <p class="picturemark">Figure 3.  <em>E. coli</em> producing pigments. When induced by  arabinose, the engineered <em>E. coli </em>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.</p>
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  <p class="picturemark">&nbsp;</p>
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<p>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. <a name="OLE_LINK2" id="OLE_LINK2"></a><a name="OLE_LINK1" id="OLE_LINK1">To demonstrate the  versatility and validity of the platform,</a> we utilized the  platform to improve performance of two modular genetic devices, <u>AND gate</u> and<u> bistable switch</u>. </p>
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<p class="mainbody"><span class="Reference">Reference:</span><a name="r101" id="r101"></a><a name="r102" id="r102"></a><a name="r103" id="r103"></a><a name="r201" id="r201"></a><a name="r202" id="r202"></a><a name="r203" id="r203"></a><a name="r204" id="r204"></a><a name="r301" id="r301"></a><a name="r302" id="r302"></a><a name="r303" id="r303"></a><a name="r304" id="r304"></a></p>
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<p class="mainbody">&nbsp;        </p>
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<p class="mainbody"><span class="exist"><a href="#start">[TOP]</a></span></p>
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<p class="mainbody">&nbsp;</p>
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<p class="mainbody">&nbsp;</p>
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<p class="mainbody">&nbsp;</p>
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Revision as of 22:44, 5 October 2011

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.

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 a well performed AND gate.

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.

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.

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.

 

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.

 

 

 

 

 

 

Reference:

 

 

 

 

[TOP]

 

 

 

 

 

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