Team:MIT/Motivation

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<h1>Motivation</h1>
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<p>Synthetic biology has grown as a field over the past few decades to feature increasingly complex circuit topology, modular parts, and a myriad of application spaces. However, the increase in complexity is limited by the number of specialized parts available to the community. The proteins used for cellular processing must be orthogonal to one another and cannot place too high a metabolic load on the host cell. </p>
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<p>At the same time, a field of similar origins, nucleic-acid based molecular computation, has seen an exponential growth in the ability to make more and more complex structures and logic circuits. In particular, recent publications feature square-root calculators and neural network implementations using strands of DNA and their natural thermodynamic reactions to process information and make calculations. </p>
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<p><b>We are motivated by the advances made in both synthetic biology and molecular computation and aim to bring the best of both together into one project.</b></p>
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<p>Nucleic-acid based circuitry has several advantages over traditional transcription-based topologies:</p>
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<ul>
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<li type=circle>a much smaller nucleotide footprint
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<li type=circle>no need for specialized parts
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<li type=circle>a huge combinatorial space which is easily parametrized
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<li type=circle>minimal metabolic load; DNA parts don’t need to be translated into proteins
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<li type=circle>direct interface with mRNA, miRNA, etc.
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</ul><p>By using mammalian cells, we have access various levels of regulation, for example being able to use the RNA-interference (RNAi) pathway.</p>
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<p>Let's look at a potential synthetic biology application: <b>detecting cancer state in mammalian cells</b>. What would this require?  </p>
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<p>You can imagine the first step, a cancer cell sensor, can be achieved by creating an mRNA sensor. The state of the art circuit with this function, (1 Multi-Input RNAi-Based Logic Circuit for Identification of Specific Cancer Cells. Xie et al. Science 2011)  requires at least five composite parts for sensing high and low mRNA concentrations. The next part would need to process information from these five separate inputs, invert some of it, and send a signal to up regulate fluorescent protein production. This would require another set of promoters for each sensed mRNA and a repression system to produce the correct logic. The last step would be the induced expression of the signal protein; another unique promoter and protein pairing.</p><p>We'll compare traditional, promoter-based synbio logic with a novel strategy from the field of DNA computing: strand displacement.
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Parts required (see below for explanation):
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<li>5 input sensor modules
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<li>5 processor modules (one for each input)
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<li>1 actuation module
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<h1>Background and Motivation</h1>
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<b style="font-size:18px">Promoter-based logic</b>
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<img src="https://static.igem.org/mediawiki/2012/c/ce/Promotergraph.png" height=220/>
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<i>Maximum number of promoters found in published synbio circuits, over time.</i>
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<h4>In the near future, biological circuits will be much more <b>modular</b> and <b>sophisticated</b> than they are now, with a ten-fold <b>smaller nucleotide footprint</b>. </h4>
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<b style="font-size:18px">Strand displacement-based logic</b>  
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<img src="https://static.igem.org/mediawiki/2012/4/4f/Gategraph.png" height=220/>
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<i>Maximum number of gates found in published strand displacement-like systems, over time.</i>
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<h3>The Enabling Technology: Toehold-Mediated Strand Displacement</h3>
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Promoter-protein pairs required: 11 (one for each module)
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<b>Max achieved in literature: 6</b>
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Strands of nucleic acid required: 80
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<center><br/><img src="https://static.igem.org/mediawiki/2012/e/ef/MIT_Strand_Displacement_Cartoon.png"/><br/><br/></center>
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A <b>gate strand</b> and <b>output strand</b> exist as a complex that is <b>partially bound</b> through complementary Watson-Crick base-pairing within the S2 binding domain. The gate strand also contains an <b>open, unbound domain</b> called a <b>toehold</b> region, T*. An input signal strand with a free complementary toehold region, T, can bind to the toehold region on the gate strand, and subsequently displace the output strand to yield an input-gate complex and a free output signal strand. This is called a <b>toehold-mediated strand displacement reaction</b>. The output signal strand can be used as an input signal for a downstream gate-output complex, enabling sophisticated interactions which yield full logic circuits.
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Size of each promoter-protein pair: ~1,600 bp
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Length of each strand: ~40 bp
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<h3>Background</h3>
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<b>Total size of circuit: ~17,600 bp</b>
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<b>Total size of circuit: ~3,200 bp</b>
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<a href="http://www.sciencemag.org/content/332/6034/1196.abstract">Qian and Winfree (<i>Science</i> 2011)</a> utilized DNA computation to create AND and OR logic gates <i>in vitro</i>. They constructed a sophisticated binary square root circuit using these gates:
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<img src="https://static.igem.org/mediawiki/2012/4/4a/MIT_Curly_strands_square_root_circuit.png" width=570/>
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<div style="text-align: right; margin-right: 8em;"><em>Image courtesy of Lulu Qian.</em></div>
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This hypothetical circuit requires at least eleven unique promoters and proteins to function. At 1600 nucelotides per composite part, that means inserting 17,600 new bases into the cellular DNA. As shown in the graph above, the current maximum number of promoters in a cellular circuit is six. </p>
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</br>Each of these:
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</br><img src="https://static.igem.org/mediawiki/2012/6/6c/MIT_Curly_strand_1.png" height=30> <img src="https://static.igem.org/mediawiki/2012/3/36/MIT_Curly_strand_2.png" height=15>
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</br>undergoes the same <b>toehold-mediated strand displacement reaction</b>. These reactions are fully modular and can be scaled to circuits of any degree of sophistication.
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<h3 id="s2">Motivation for Bringing Strand Displacement to Mammalian Synthetic Biology</h3>
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<ul>
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<li><b>More sophisticated circuits with smaller nucleotide footprint</b>
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<center><img src="https://static.igem.org/mediawiki/2012/b/bc/MIT_Transcription_versus_strand_displacement_circuits.png" width=350></center>
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</br> Sophistication of traditional transcription-translational circuits has grown linearly over the past 10 years, while sophistication of strand-displacement circuits has grown nearly exponentially.
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<li><b>Simple combinatorial design space</b>
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</br>With 4 nucleotides, we can create a nearly infinite number of orthogonal sequences leading to orthogonal parts.
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<li><b>Ease of composition</b>
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</br>The input motif matches the output motif allowing for modular cascading reactions.
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<li><b>Tunability</b>
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</br>We can set arbitrary digital signal thresholds by varying the concentration of circuit species. We can also achieve signal amplification by including a fuel molecule.
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<h4>RNA versus DNA</h4>
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Clearly, a novel method of information processing is needed if we want to create complex circuits in vivo. For inspiration, we turned to "Scaling up digital circuit computation with DNA strand displacement cascades." Qian, L., Winfree, E. Science 2011. That research shows that it is possible to use the method of DNA strand displacement for complex circuits in vitro. The team built a circuit which calculated square roots with inputs of different short DNA strands representing binary numbers. The same hypothetical cancer sensing and highlighting circuit, designed using the strand displacement motif, requires only 3200 nucleotides of coding, creating over eighty strands which are roughly 40 bases in length.
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<img src="https://static.igem.org/mediawiki/2012/d/db/Calc.png"/>
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An information processing system is of limited use without dynamic production. RNA is a good medium because it can be continually produced from a few initial DNA parts. As in nature, DNA acts as the information-storage medium, and RNA acts as the information-processing medium. We can transfect DNA parts into mammalian cells to co-opt existing cellular machinery to produce our RNA parts.
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</br>Our RNA parts can then interact with the cell through <a href="https://2012.igem.org/Team:MIT/Sensing">sensing</a> and <a href="https://2012.igem.org/Team:MIT/Actuation">actuation</a>. Endogenous cellular RNAs can act as inputs, and we can actuate by knocking down endogenous cellular RNAs.
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Integrating this into a ceullar system is non-trivial, but possible.
 
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Latest revision as of 03:55, 27 October 2012

iGEM 2012

Background and Motivation

In the near future, biological circuits will be much more modular and sophisticated than they are now, with a ten-fold smaller nucleotide footprint.

The Enabling Technology: Toehold-Mediated Strand Displacement




A gate strand and output strand exist as a complex that is partially bound through complementary Watson-Crick base-pairing within the S2 binding domain. The gate strand also contains an open, unbound domain called a toehold region, T*. An input signal strand with a free complementary toehold region, T, can bind to the toehold region on the gate strand, and subsequently displace the output strand to yield an input-gate complex and a free output signal strand. This is called a toehold-mediated strand displacement reaction. The output signal strand can be used as an input signal for a downstream gate-output complex, enabling sophisticated interactions which yield full logic circuits.

Background

Qian and Winfree (Science 2011) utilized DNA computation to create AND and OR logic gates in vitro. They constructed a sophisticated binary square root circuit using these gates:
Image courtesy of Lulu Qian.


Each of these:

undergoes the same toehold-mediated strand displacement reaction. These reactions are fully modular and can be scaled to circuits of any degree of sophistication.

Motivation for Bringing Strand Displacement to Mammalian Synthetic Biology

  • More sophisticated circuits with smaller nucleotide footprint

    Sophistication of traditional transcription-translational circuits has grown linearly over the past 10 years, while sophistication of strand-displacement circuits has grown nearly exponentially.
  • Simple combinatorial design space
    With 4 nucleotides, we can create a nearly infinite number of orthogonal sequences leading to orthogonal parts.
  • Ease of composition
    The input motif matches the output motif allowing for modular cascading reactions.
  • Tunability
    We can set arbitrary digital signal thresholds by varying the concentration of circuit species. We can also achieve signal amplification by including a fuel molecule.

RNA versus DNA

An information processing system is of limited use without dynamic production. RNA is a good medium because it can be continually produced from a few initial DNA parts. As in nature, DNA acts as the information-storage medium, and RNA acts as the information-processing medium. We can transfect DNA parts into mammalian cells to co-opt existing cellular machinery to produce our RNA parts.

Our RNA parts can then interact with the cell through sensing and actuation. Endogenous cellular RNAs can act as inputs, and we can actuate by knocking down endogenous cellular RNAs.

Retrieved from "http://2012.igem.org/Team:MIT/Motivation"