Team:MIT/Motivation

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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.

RNA Strand Displacement

Our system of RNA circuitry in mammalian cells utilizes the mechanism of RNA strand displacement, a novel nucleic-acid based molecular computation tool that can be used to process genetic information.

Qian and Winfree (Science 2011) demonstrated the viability of DNA strand displacement as a scalable mechanism for performing complex digital logic in vitro. They constructed complex AND and OR logic gates by utilizing elementary DNA strand displacement reactions known as seesawing, thresholding, and reporting.

The basic technique of DNA strand displacement involves three single stranded DNA molecules, as shown in the diagram below. 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 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. The output strand could hypothetically be used as an input for a downstream gate-output complex.

Application Space

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):

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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