Algorithmic Self-Assembly of DNA Sierpinski Triangles
By Paul Wilhelm Karl Rothemund, Nick Papadakis, Erik Winfree. PLoS Biology, 2004
852 citations recorded by the source corpus.
Algorithms and information, fundamental to technological and biological organization, are also an essential aspect of many elementary physical phenomena, such as molecular self-assembly. Here we report the molecular realization, using two-dimensional self-assembly of DNA tiles, of a cellular automaton whose update rule computes the binary function XOR and thus fabricates a fractal pattern—a Sierpinski triangle—as it grows. To achieve this, abstract tiles were translated into DNA tiles based on double-crossover motifs. Serving as input for the computation, long single-stranded DNA molecules were used to nucleate growth of tiles into algorithmic crystals. For both of two independent molecular realizations, atomic force microscopy revealed recognizable Sierpinski triangles containing 100–200 correct tiles. Error rates during assembly appear to range from 1% to 10%. Although imperfect, the growth of Sierpinski triangles demonstrates all the necessary mechanisms for the molecular implementation of arbitrary cellular automata. This shows that engineered DNA self-assembly can be treated as a Turing-universal biomolecular system, capable of implementing any desired algorithm for computation or construction tasks.
Subfields: Mechanical Engineering, Molecular Biology
View Paper: https://www.semanticscholar.org/paper/67b2918c1804a76552002aa2ea6f35e0722d3b8f
How researchers see this paper
The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.
In Mechanical Engineering
In Molecular Biology
- Georg Seelig
- Erik Winfree
- David Soloveichik
- Nadrian C. Seeman
- Peng Yin
- Niles A. Pierce
- Jehoshua Bruck
- Jan Gardell
Citations in the corpus
- DNA as a universal substrate for chemical kinetics (2009, methodology): “We hope that the methods presented here provide a framework for successfully generalizing and unifying the existing experimental achievements in this direction (36, 37, 51).”
- The Emerging Field of RNA Nanotechnology (2010, neutral): “and algorithmic self-assembled Sierpinski triangles (aperiodic arrays of fractal patterns”
- DNA rendering of polyhedral meshes at the nanoscale (2015, background): “For fine-tuning of the design (optional step (4)), the smaller gaps within the imported relaxedmodel can be filled with unpaired nucleotides, which will provide flexibility and correct strand misalignments during assembly.”
- Programming biomolecular self-assembly pathways (2008, background): “Additional control experiments (Supplementary Information 6.9) show that this difference in time-scales cannot be explained by the relative rates with which freely diffusing bipedal and monopedal walkers land on the track.”
- Nanomaterials Based on DNA (2010, background): “Winfree and his colleagues have built Sierpinski triangles (60), most successfully when using an approach that “chaperones” the area of the aperiodic array (61).”
- Computation with finite stochastic chemical reaction networks (2008, methodology): “Computation has also been suggested via a Turing machine (TM) simulation on a polymer [5, 6], via cellular automaton simulation in self-assembly [7], or via compartmentalization of molecules into membrane compartments [8, 9].”
- Dynamic DNA nanotechnology using strand-displacement reactions. (2011, neutral): “[78] Rothemund, P.”