Team:MIT/Motivation

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iGEM 2012

Bacterial

  • Annealing Oligos
  • BP Reaction
  • Capped Transcription Reaction Assembly
  • Cell Stock
  • Gel Extraction - QIAGEN
  • Gel Preparation
  • Golden Gate Reaction
  • Inoculation - Midiprep
  • Inoculation - Miniprep
  • LR Reaction
  • Midiprep QIAGEN
  • Miniprep QIAGEN
  • Nanodrop
  • PCR - Using PFX
  • Pouring LB Agar Plates
  • Restriction Mapping
  • Sequencing
  • Transformation

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:

  • Much smaller nucleotide footprint.
    RNA parts require much fewer bases than the mRNAs coding for protein parts.
  • Smaller metabolic load.
    Nucleic acid parts are fully functional and do not need to be translated into proteins.
  • Large combinatorial space.
    We can generate and iterate unlimited parts and filter for constraints, such as percentage of Cs or Gs, instead of being constrained to searching for existing proteins.
  • 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.

In recognizing the valuable contributions that the DNA strand displacement method offered to synthetic biological circuits, our team chose to further investigate the idea of nucleic-acid based molecular computation by using RNA as the species performing complex digital logic in circuitry. We envisioned several advantages of using RNA rather than DNA.

A primary goal of ours was to transition from in vitro to in vivo studies by implementing the technology in mammalian cells; since RNA predominantly exists naturally as a single stranded species, open toehold regions in input strands can Watson-Crick pair with complementary toehold domains in gate-output complexes to yield strand displacement.

Furthermore, we recognized the ability of RNA to directly interface with other cellular nucleic acids, such as endogenous messenger RNA and micro RNA. This interface would allow for an individual cellular mRNA expression profile to serve as an input into a logical circuit to successfully assess and classify the cell state. Additionally, it would allow for tight circuit regulation through endogenous mammalian RNA interference pathways.

Application Space

Using RNA strand displacement as a mechanism to process genetic information in vivo has tremendous applications for analyzing complex cell states. RNA-based logic gates can sense expression levels of endogenous cellular biomarkers, process these abstract inputs, and conditionally actuate any desired outputs within the cell.

An example of a potential application of our system is to facilitate the detection of a cancerous state in mammalian cells. Previously, such a circuit had been designed by Xie et. al (Science 2011)2 to exclusively distinguish a HeLa cancerous cell from any other cell type using traditional, promoter-based synthetic biology logic. The state-of-the-art circuit sensed high and low concentrations of five endogenous mRNA concentrations, processed these inputs into a single logical signal, and ultimately used this signal to conditionally induce apoptosis if the mRNA expression profile matched that of a HeLa cell.

We compared traditional promoter-based synthetic biology logic with the novel strand displacement computational method to examine how our method of information processing could improve such an engineered cell classifier circuit.

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
Ultimately, using nucleic-acid based strand displacement as a method of logical computation provides valuable advantages for mammalian cell circuitry, including minimizing nucleotide footprints, increasing combinatorial space, and decreasing overall circuit size. We envision that these significant improvements to genetic circuitry through the mechanism of RNA Strand Displacement can revolutionize our ability to diagnose complex cell states and engineer cells to conditionally perform desirable functions, thus providing a powerful advance within the field of synthetic biology.