Team:MIT/Motivation

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<h1>Motivation</h1>
<h1>Motivation</h1>
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<h2>RNA-based Molecular Computation</h2>
<p>Our project aims to combine the <b>modular parts</b> of synthetic biology with the exponential growth in <b>logic circuit complexity</b> of nucleic-acid based molecular computation to create <b>RNA circuits in mammalian cells</b>.</p>
<p>Our project aims to combine the <b>modular parts</b> of synthetic biology with the exponential growth in <b>logic circuit complexity</b> of nucleic-acid based molecular computation to create <b>RNA circuits in mammalian cells</b>.</p>
<p>Nucleic-acid based circuitry has several advantages over traditional transcription-based topologies:</p>
<p>Nucleic-acid based circuitry has several advantages over traditional transcription-based topologies:</p>

Revision as of 19:48, 3 October 2012

iGEM 2012

Motivation

RNA-based Molecular Computation

Our project aims to combine the modular parts of synthetic biology with the exponential growth in logic circuit complexity of nucleic-acid based molecular computation to create RNA circuits in mammalian cells.

Nucleic-acid based circuitry has several advantages over traditional transcription-based topologies:

  • No need for specialized parts.
    We can design circuit parts from the ground up instead of searching for suitable orthogonal proteins.
  • Large combinatorial space.
    We can generate and iterate unlimited parts and filter for constraints, such as percentage of Cs or Gs.
  • Minimal metabolic load.
    Nucleic acid parts are fully functional and do not need to be translated into proteins.
  • Much smaller nucleotide footprint.
    RNA parts require much fewer bases than the mRNAs coding for protein parts.
  • Direct interfacing with mRNA, miRNA, etc.
    The use of mammalian cells provides us with access to various levels of regulation, such as the RNA-interference pathway.

One potential synthetic biology application of our system is detection of cancer state in mammalian cells.

The first step, sensing the cancer state, can be achieved using an engineered 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 step involves processing information from these five separate inputs, including inversion of signals, into a single signal that tells the cell to upregulate fluorescent protein production. This requires another set of promoters for each sensed mRNA and a repression system to produce the correct logic.

The last step is induction of expression of the signal protein, which requires yet another unique promoter/protein pairing.

We compared traditional, promoter-based synbio logic with a novel strategy from the field of DNA computing: strand displacement.

Parts required (see below for explanation):

  • 5 input sensor modules
  • 5 processor modules (one for each input)
  • 1 actuation module

Promoter-based logic

Maximum number of promoters found in published synbio circuits, over time.
Purnick and Weiss. The second wave of synthetic biology: from modules to systems. Nature Reviews Molecular Cell Biology 10, 410-422 (June 2009) 		Strand displacement-based logic

Maximum number of gates found in published strand displacement-like systems from the Winfree group, over time.
Promoter-protein pairs required: 11 (one for each module)
Max achieved in literature: 6 		Strands of nucleic acid required: 80
Size of each promoter-protein pair: ~1,600 bp Length of each strand: ~40 bp
Total size of circuit: ~17,600 bp Total size of circuit: ~3,200 bp

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