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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   <p class="notbookmaintitle" align=center>Demonstration of Genetic Softcoding</p>
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       <th width="638" height="916" scope="col"><p class="mn"><a href="https://2011.igem.org/Team:Peking_R/Project/Application/AG"> AND gate</a></p>
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<p ><a href="https://2011.igem.org/Team:Peking_R/Project/Application/BS">Bistable switch</a></p>
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        <p><a href="https://2011.igem.org/Team:Peking_R/Project/Application/VIO">Violacein synthetic pathway</a></p>
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        <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>
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<p 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. </p>
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        <p class="mainbody"><span class="picturemark">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 genetic rheostat 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, <a href="https://2011.igem.org/Team:Peking_R/Project/Application/AG">AND gate</a> and<a href="https://2011.igem.org/Team:Peking_R/Project/Application/BS"> bistable switch</a>.</span></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 an AND gate with improved performance.</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>
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         <p class="mainbody">We further applied this platform to  optimize a segment of <a href="https://2011.igem.org/Team:Peking_R/Project/Application/VIO">violacein biosynthetic pathway</a>, and achieved producing purer desired products. </p>
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  <p class="mainbody"><strong>Background of softcoding</strong><br />
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    There are basically two design principles  in computer programming: hardcoding and softcoding. Hardcoding1  refers to the practice of embedding parameters and functions into the source  code of a program, whereas softcoding2 obtains values and functions  from external source. Hardcoding would be convenient when no dynamic parameters  are required in the program, but the source code should be rewritten anytime  the input data or functions change. On the contrary, softcoding enables users  to customize the software to their needs by altering external input, without  having to edit the program&rsquo;s source code time after time. </p>
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  <p class="mainbody">In the exciting field of synthetic biology,  various genetic programs have been developed to perform certain functions in  living organismswhich are similar to computer programs. For instance, a genetic  toggle switch <em>in vivo</em> was developed  that could be switched between two states by chemical or thermal induction.Another  example is that an oscillatory network was constructed in which the synthesis  of green fluorescent protein was periodically induced.Yet  genetic programs need optimization to achieve ideal performance, especially  when several genetic modules are coupled. Similarly, optimization of metabolic  pathways is also a key issue in the field of metabolic engineering. </p>
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  <p>Traditional methods to optimize genetic  programs or metabolic pathways generally involve construction of libraries that  contain large amounts of mutants, and multi-round screening is usually  required. Apart from the obvious drawback that the constructing and screening  procedures are laborious and time-consuming, these methods could only generate  mutants with a fixed configuration, and to fine-tune their performance would  require another round of mutagenesis and selection, which resembles &ldquo;hardcoding&rdquo;.  Therefore, a platform for &ldquo;softcoding&rdquo; of genetic programs is urgently needed. </p>
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  <p>&nbsp;</p>
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  <p class="mainbody"><strong>Softcoding Approach</strong><br />
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  Based on the principle of softcoding, this  year our team established an extensible and versatile platform for softcoding  of genetic program, which is composed of anRNA toolkit and a methodology-- The RNA  toolkit consists of interoperable and truly modular ligand-responsive  riboswitches/ribozymes, while the methodology is automated design of synthetic  ribosomal binding sites (RBS) with customized translation rate. When combining  them together, a quantitative correlation between the concentration of specific  ligand and synthetic RBS&rsquo; translation strength can be established. Therefore,  when tuning genetic program, customized RBS&rsquo; translation strength at multiple  sites can be high-throughputly achieved without having to conduct laborious  mutagenesis and characterization, followed by easily determining the  configuration of RBS(s)&rsquo;translation strength. Then RBS sequences that meet this  configuration will be automatically designed via computer  algorithms. </p>
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    <em>RNA toolkit</em><a href="https://2011.igem.org/Team:Peking_R/Project/RNAToolkit">(Learn more...)</a><br />
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    Recently, RNA devices have emerged as powerful  tools to regulate gene expression <em>in vivo</em>,  and particularly, ligand-responsive riboswitches/ribozymes enable us to  manipulate translation strength of specific genes upon different concentrations  of ligands.<a href="#_edn3" name="_ednref3" title="" id="_ednref3"> </a>Ligand-responsive  riboswitches/ribozymes regulate the translation rate of downstream gene by changing  conformations, cleaving or splicing upon external addition of ligand. Compared  with transcriptional and post-translational regulation, riboswitches/ribozymes  function through allostery of RNA structure, which requires little or no  assistance from proteins, so the regulation mechanism is relatively simpler and  their functions are more decoupled from native biological activities.</p>
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<p class="mainbody">We characterized some existing  riboswitches/ribozymes, namely thiamine pyrophosphate (TPP)-responsive hammerhead  ribozymes and theophylline riboswitches. By altering the upstream promoter and  downstream coding sequence of the RNA controllers, we demonstrated that their  performance was independent from sequence context, which proved the modularity  of these RNA devices.</p>
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  <p class="mainbody">To further extend the range of application  of our RNA toolkit, we created a ribozyme that functions with a different  mechanism, which has an extreme low level of backgrounds. We substituted the  aptamer domain of c-di-GMP group Intron to theophylline-responsive aptamer, thus  invented a group I intron that senses theophylline to perform splicing function.  Moreover, we introduced a general method to evolve hammerhead ribozyme that  senses a new ligand. By coupling an adenine aptamer with hammerhead ribozyme  and randomizing nucleotides in the linker domain, we evolved new hammerhead  ribozymes through dual selection, whose self-cleavage could be regulated by  adenine. Our project provided a new design principle for rational or  semi-rational design of riboswitches/ribozymes. </p>
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  <p class="mainbody"><em>RBS automated design</em><a href="https://2011.igem.org/Team:Peking_R/Project/RBSAutomatedDesign">(Learn more...)</a><br />
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  In bacteria, ribosomal binding site (RBS) sequence  is one of the most important determinants of translational initiation/translation  strength. Therefore manipulating RBS sequence would significantly affect the  translation strength of downstream gene. Salis <em>et.al</em>. used Gibbs energy (∆G) of the &ldquo;docked&rdquo; state of the mRNA-30S ribosomal subunit complex to  predict the translation strength of RBS sequence. Based on their pioneering  work, we developed a methodology that correlated the performance of the RNA  controllers under certain concentration of ligand to translation strength met  by corresponding RBS sequence. Combining this methodology with our RNA toolkit,  we can generate an RBS sequence through automated design once we achieved an  ideal configuration of genetic programs through RNA controllers.</p>
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  <p class="mainbody"><strong>Application</strong><br />
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  we utilized the  platform to improve performance of two modular genetic devices,<a href="https://2011.igem.org/Team:Peking_R/Project/Application/AG"> <u>AND gate</u></a> and<u> <a href="https://2011.igem.org/Team:Peking_R/Project/Application/BS">bistable switch</a></u><a href="https://2011.igem.org/Team:Peking_R/Project/Application/">.</a></p>
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  <p class="mainbody">&nbsp;</p>
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  <p class="mainbody"><a href="https://2011.igem.org/Team:Peking_R/Project/Application/AG">AND gate</a></p>
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      <td><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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  <p><a href="https://2011.igem.org/Team:Peking_R/Project/Application/BS">Bistable switch</a></p>
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      <td><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 class="mainbody"> <u><a href="https://2011.igem.org/Team:Peking_R/Project/Application/VIO">violacein biosynthetic pathway</a></u></p>
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  <p class="mainbody">We further applied this platform to  optimize a segment of<u><a href="https://2011.igem.org/Team:Peking_R/Project/Application/VIO">violacein biosynthetic pathway</a></u>, and achieved producing purer desired products. </p>
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      <td><p>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></td>
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   <p class="picturemark"><strong>Figure 3. <strong> <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="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>[1]  <a href="http://en.wikipedia.org/wiki/Hard_coding">http://en.wikipedia.org/wiki/Hard_coding</a><br />
 
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  [2] <a href="http://en.wikipedia.org/wiki/Softcoding">http://en.wikipedia.org/wiki/Softcoding</a></p>
 
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<p><span class="mainbody">[3].Gardner, Timothy S. <em>et. al.</em> (2000). Construction of a genetic toggleswitch in <em>Escherichia coli</em>. Nature 403, 339-342</span> [4].Elowitz, Michael B. and  Leibler, Stanislas (2000). A synthetic oscillatory network of transcriptional  regulators. Nature 403, 335-338  [5].Breaker, Ronald R (2004).Natural and engineered nucleicacids as  tools to explore biology. Nature 432, 838-845<br />
 
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  [6].Salis, Howard M <em>et.al.</em> (2009). Automated design of synthetic ribosome binding sitesto control protein  expression. Nat. Biotech. 27, 946-950</p>
 
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Latest revision as of 15:50, 28 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/Projectbackground8 无标题文档 无标题文档

Demonstration of Genetic Softcoding

AND gate

Bistable switch

Violacein synthetic pathway

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 genetic rheostat 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.

 

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