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An information-bearing seed for nucleating algorithmic self-assembly

An information-bearing seed for nucleating algorithmic self-assembly. Robert D. Barish1, Rebecca Schulman1, Paul W. K. Rothemund , and Erik Winfree2. Presented by : Venkata Chaitanya Goli 651366318. Outline. Overview Preparation Experiments Techniques used and Results

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An information-bearing seed for nucleating algorithmic self-assembly

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  1. An information-bearing seed for nucleating algorithmic self-assembly RobertD.Barish1,RebeccaSchulman1,PaulW.K.Rothemund,andErikWinfree2 Presented by : Venkata Chaitanya Goli 651366318

  2. Outline Overview Preparation Experiments Techniques used and Results Principles for Success Future research topics

  3. OverviewExplaining the Title Information – bearing Seed Information in a seed molecule can determine which form is grown as well as where and when. Self- assembly Self-assembly creates natural mineral, chemical, and biological structures of great complexity. This phenomena can be exploited to program the growth of complex structures, as demonstrated by the algorithmic self-assembly of DNA tiles.

  4. Overview Controlled growth using Nucleation Barrier Mineral and chemical compounds  Simplest form seeded growth Multicellular development, where genomic information in the zygote directs the algorithmic construction of the entire organism What is a seed ?

  5. Preparation Key features to be present for a seed : • Sufficiently well-formed • Capable of being synthesized with arbitrary information • Straightforward to implement experimentally. Problems incorporating significant amounts of specific information into such seeds remains prohibitive high error rates, high spontaneous nucleation rates and low yields of well-formed structures. Single-stranded DNA Problems Finite-sized tileassemblies Self-assembled ribbon-like crystals

  6. Preparation Each DNA tile consists of multiple strands folded into a rigid unit typically displaying 4 single-stranded ‘‘sticky ends’’ that direct the tile’s binding interactions with other tiles. Sticky ends DNA Tile

  7. Preparation Origami DNA seed Tile Adapters Consists Scaffold strand 192 Staple strands 32 Adapter strands

  8. Preparation Tiling theory A tile is a geometrical shape, such as a jigsaw puzzle piece, that may be assembled with other tiles based on local matching rules. Problems : • Go beyond familiar fixed size • random arrangements like fractals, binary trees, cellular automata That’s where I come in

  9. Preparation The self-assembly process begins with an initial seed tile to which additional tiles can attach if they make sufficiently many ‘matching contacts’ So to summarize in simple terms Program - The starting materials, i.e. a set of available tiles. . Input - The seed Output - The structure produced by self-assembly is the output.

  10. Experiments Experiment 1 (Temperature-dependent ): To test the growth Steps : All strands for the seed and for the tile set are mixed together in buffer Heated to 90 °C Annealed slowly to room temperature. The process of self assembly is observed

  11. Experiments At temperature 90 °C - 60 °C • At these temperatures, the DNA double helix is unstable and dissociates into its single- stranded form • All the stick ends are inert and don’t show any binding properties.

  12. Experiments At temperature 60 °C - 40 °C • At these temperatures, the seed and individual tiles become stable because of extensive contacts between strands • Tiles do not attach to the seed nor to each other because the two additional sticky-end contacts formed by each tile attachment are not thermodynamically favorable at these temperatures and concentrations.

  13. Experiments At temperature 40 °C - 20 °C • At slightly lower temperatures, below the crystal melting temperature, slightly supersaturated conditions are achieved. • The attachment of a tile by two matching sticky ends becomes favorable, but attachment by a single matching sticky end remains unfavorable • Consequently, tiles now attach to the origami seed and then attach to each other to grow a crystal

  14. Experiments Experiment 2 (Width - Dependent ): • Used a DNA tile set

  15. Experiments Experiment 2 (Width - Dependent ): • This tile set is added a nucleation barrier under some controlled conditions

  16. Experiments Experiment 2 (Width - Dependent ): • This tile set is added a nucleation barrier under some controlled conditions • A sample Zig-Zag pair

  17. Experiments Experiment 2 (Width - Dependent ): The sequence formed from the tile formation

  18. Experiments Experiment 2 (Width - Dependent ): A copy tile Set is created to maintain the bonding in a desired manner.

  19. Experiments Experiment 2 (Width - Dependent ): 4 1 5* 1* 4 1 • Additional tiles for the Copy tile set. Inset shows how correct copying of information at bit boundaries depends on preferred attachment of tiles matching two sticky ends over tiles matching just one. 5* 1*

  20. Experiments Experiment 2 (Width - Dependent ): Binary counter Tile sets

  21. Experiments Experiment 2 (Width - Dependent ): • ‘‘Carry Bit 1-Block’’ and ‘‘Carry Bit 0-Block’’ are added to the Copy tile set • The gray double tile is replaced by the beige one, whose sticky end provides the initial carry bit for each new COUNT layer. 1 1* 2* 1* Gray Tile Replacement

  22. Observations from the experiment: • The rate of spontaneous nucleation decreases dramatically with width, and so, when the tiles are annealed without a seed, we expect the majority of crystals to be just 4 tiles wide. • when annealed in the presence of seeds whose adapter tiles specify a particular width ribbon, we expect crystals of the specified width will grow off the seed— even before 4-wide ribbons nucleate spontaneously.

  23. Experiments Experiment 3 (Origami seed size): Magnified image of at the ribbon Observations with 8 width Origami:

  24. Experiments Experiment 3 (Origami seed size): Magnified image of at the ribbon Observations with 10 width Origami:

  25. Experiments Experiment 3 (Origami seed size): Magnified image of at the ribbon Observations with 12 width Origami:

  26. Observations from the experiment: • Within ribbons, information was copied with an error rate of 0.13% per tile. • The most significant errors were those that changed the width of the ribbon, either by an internal lattice defect or by a double tile attaching too early, causing a premature reversal of the zig-zag path. • Examination of errors on the first layer of the ribbon, where tiles attach directly to tile adapters, revealed that nucleation is not perfect • The copying error rate increased to 8% per tile and width-changing errors increased to 6% per layer.

  27. Observations from the experiment: • ‘‘0-Block’’ tiles appear gray • ‘‘1-Block’’ tiles appear white

  28. Observations from the experiment: • Fig F shows that the 1 block tiles are stopped

  29. Observations from the experiment: • The yellow part shows the error

  30. Principles behind the success: • Each tile set was capable of generating an infinite variety of distinct structures, a precondition for programmability • A designed nucleation barrier prevented the spontaneous assembly of tiles in slightly supersaturated conditions, clearing the way for high-yield seeded growth with low error rates. • Information contained in the seed was propagated, and sometimes processed, during crystal growth, enacting a simple developmental program.

  31. The problems observed • The rate of copying errors that changed 1 to 0 was 5–10 times higher than errors changing 0 to 1 • Premature reversal errors and spurious nucleation errors could be reduced by adding an independent nucleation barrier on the other edge of the ribbon • Implementing improved proofreading techniques (39) should further reduce logical error rates and larger block sizes may reduce internal lattice defects. • Aggregation of crystals must be reduced.

  32. The Future Research topics • The More efficient algorithm whose error rate is minimum that can compute the algorithmic complex structure of the seeded growth. • More efficient tiles like origami rectangles which can be used to develop the structure or of even more complex organism. • Getting the knowledge of combining the nanoparticles with the DNA can further help in developing new products in the field of nanotechnology

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