1introduction 2theoretical background biochemistry/molecular biology 3theoretical background...
TRANSCRIPT
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1 Introduction
2 Theoretical background Biochemistry/molecular biology
3 Theoretical background computer science
4 History of the field
5 Splicing systems
6 P systems
7 Hairpins
8 Detection techniques
9 Micro technology introduction
10 Microchips and fluidics
11 Self assembly
12 Regulatory networks
13 Molecular motors
14 DNA nanowires
15 Protein computers
16 DNA computing - summery
17 Presentation of essay and discussion
Course outline
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Introduction
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What is self-organisation?
System with discrete components
Spontaneously ordered properties
Global Order from Local, random
interactions
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Self-organized catalytic set of molecules
Origin of life
RNA world
Driving force is G
Goal is self-replication
Living systems
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Self-Reproducing (cellular) Automata
Artificial Neural Networks
Boolean Networks
Artificial Life Systems
Evolutionary Systems
DNA Systems
Artificial self-organisation systems
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Seeman-Winfree
Construction of Specific Geometrical
and Topological Targets from DNA
Construction Process => Computation
Cellular Automata and Tilings
Basic Building Block is Stiff DNA
Double-Crossover Molecule (DX)
Self-organisation DNA systems
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A process involving the spontaneous self-
ordering of substructures into
superstructures.
Is a Bottom-up Process rather than a Top-
Down process used in most manufacturing or
lithography processes
Self-assembly
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Cells perform a multiplicity
of self-assemblies:
Cell walls (via lipids),
Microtubules
Cellular Superstructures
and Transport Structures
Utilize the specificity of
ligand affinities to direct
the self-assembly
Cellular self-assembly
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Construction with smart brick
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Molecular affinity
hydrogen bonding of complementary DNA or RNA bases
Magnetic attraction (U. of Wisconsin materials science group)
pads with magnetic orientations constructed by curing
polymer/ferrite composites in the presence of strong magnet
fields, or
pads with patterned strips of magnetic orientations [Reif].
Capillary force [Whitesides], [Rothmemund, 1999]
using hydrophobic/hydrophilic (capillary) effects at surface
boundaries that generate lateral forces.
Shape complementarity [Whitesides]
using the conformational shape affinity of the tile sides to
hold them together.
Tiles binding mechanisms
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Scale of tiling assembly
Meso-scale tiling assemblies
have tiles of size a few
millimeters up to a few
centimeters.
Molecular-scale tiling assemblies
have tiles of size up to a few
hundred Angstroms.
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Magnetic meso-scale self-assembly
Wisconsin material sciences group
Self assembly on Water/Air Interface.
Pads with magnetic orientations constructed by curing
polymer/ferrite composites in the presence of strong magnet
fields.
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Magnetic meso-scale self-assembly
Wisconsin material sciences group
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Magnetic meso-scale self-assembly
Wisconsin material sciences group
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Programming 2-d DNA lattices
for the construction of molecular
scale structures
for rendering patterns at the
molecular level
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A 2D DNA lattice is constructed by a self-assembly process
Begins with the assembly of DNA tile nanostructures
DNA tiles of size 14 x 7 nanometers
Composed of short DNA strands with Holliday junctions
These DNA tiles self-assemble to form a 2D lattice:
The assembly is programmable
Tiles have sticky ends that provide programming for the
patterns to be formed.
Alternatively, tiles self-assemble around segments of a
DNA strand encoding a 2D pattern.
Programming 2-d DNA lattices
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Programming 2-d DNA lattices
Patterning
Each of these tiles has a surface perturbation
depending on the pixel intensity.
pixel distances 7 to 14 nanometers
Key Applications
Assembly of molecular electronic components and
circuits
molecular robotic components
image rendering
cryptography
mutation detection
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Programming 2-d DNA lattices
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DX is double crossover
Antiparallel strands
4-arm junctions
Full turn in B-form of DNA (10.5 bp)
Even or Odd number of half turns
DAE, DAO
DX molecules
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DX molecules
DNA crossover molecules self-assembled from
artificially synthesized single stranded DNA.
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DX molecules
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Double-crossover (DX) Tiles [Winfree,
Seeman]:
consist of two double-helices fused by
crossover strands.
DAE contains an Even number of helical
half-turns between crossover points.
DAO contains an Odd number.
Anti-parallel crossovers:
cause a reversal in direction of strand
propagation through the tile following
exchange of strand to a new helix.
DAO and DAE are double-crossover DX tiles
with two anti-parallel crossovers.
DNA tiles
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Pads:
Tiles have sticky ends that preferentially
match the sticky ends of certain other DNA
tiles.
The sticky ends facilitate the further
assembly into tiling lattices.
Total of 4 Pads of single stranded DNA at
ends.
DNA tiles
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TX tiles
[LaBean et al, J. Am. Chem. Soc., 2000]
Triple-crossover (TX) Tiles consist of three
double-helices fused by crossover strands.
TAE contains an even number of helical half-
turns between crossover points.
TAO contains an odd number.
Total of 6 Pads of single stranded DNA at
ends.
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TX tiles
[LaBean et al, J. Am. Chem. Soc., 2000]
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Unique Sticky Ends on DNA tiles.
Input layers can be assembled via unique
sticky-ends at each tile joint thereby
requiring one tile type for each position in
the input layer.
Tiling self-assembly
proceeds by the selective annealing of the
pads of distinct tiles, which allows tiles to
compose together to form a
controlled tiling lattice.
TX tiles
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TX tiles
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Another way
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Still another way
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Or another way
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A tiling is an arrangement of tiles
(shapes) that covers a plane
Tiles fit based on matching rules
(complementary shapes)
Self assembly and computation
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XOR tile
Self assembly and computation
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Wang Tile
Self assembly and computation
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Given a Turing machine, tiles and matching
rules can be designed so that the tilings
formed correspond to a simulation of the
Turing Machine.
Computation by tiling is hence Universal i.e.
all SA structures can be viewed as
computation.
Self assembly and computation
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C-tile, P-tile and XOR tile
Error rate 0.2%, 2.2%, 14.7% for C, P and XOR tiles; % error= mismatches/(mismatches+bonds)
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The powerful molecular recognition system of base
pairing can be used in
Nanotechnology to direct the assembly of highly
structured materials with specific nanoscale
features
DNA computation to process complex information.
Appealing features include
Minuscule size, with a diameter of about 2
nanometres
Short structural repeat (helical pitch) of about
3.4–3.6 nm,
’Stiffness', with a persistence length (a measure
of stiffness) of around 50 nm.
DNA
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Sticky ended cohesion-ligation
DNA as building material
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DNA as building material
Assembly of branched junctions into a 2-d lattice
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DNA as building material
Holiday junction
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DNA as building material
Flexibility of DNA branched junctions
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DNA drawn as a series of right angle turns
Each edge of square contain 2 turns of helix in a
but only 1.5 turns in b
DNA as building material
ba
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Constructing DNA objects
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Constructing DNA objects
Borromean Rings Truncated Octaheadron
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Design & Synthesize Oligonucleotides
Formation of H-bonded Complex
Purification using Gel Elecrophoresis to
eliminate the linear strands
Phosphorylation and Ligation
Construction of tiles
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Construction of tiles
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Single molecule gaps
Crossover molecules
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Fault tolerance: Result is probabilistic, e.g. 2-5% error in XOR computation Only open one set of sticky ends at a time to prevent
incorrect binding (correct competes with partially correct) Performance highly sensitive to process (melting) conditions
Differences from periodic tiling Correct tiles compete with partially correct tiles, thus
amplifying error
Efficiency (for small problems): Many serial chemistry steps for preparation, ligation, and
analysis, e.g. a few days for XOR computation
Scalability Reporter strand technique limited to 20-30 ligated crossovers Then can we layout 3D materials, e.g. circuit patterns?
Limitations
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Ned Seeman
DNA topological structures
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DNA topological structures
Ned Seeman
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DNA topological structures
Ned Seeman
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Imaging
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TX tiles
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Metallic nanoparticles.
Triangles or multi-triangle tiles.
Biotin-streptavidin (with or without
nanogold).
Multi-tile subassemblies.
New tile topologies.
Stem-loops
Imaging
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DNA Stem-loops:
DNA tiles with additional stem-loops of 8 to 16 basepairs,
directed out of the plane of the tile helix axes, are used
in DX and TX lattices to evaluate successful assembly of
periodic arrays.
Stem-loops can also be directed orthogonal to the tile
helix axes within the tile plane in single layer
assemblies.
These loops are used mark binary values on the tiles where
the presence of a loop indicates a 1 and the absence
indicates 0.
Modification of protruding stems or stem-loops with gold
or biotin-streptavidin increases their visibility
Imaging
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Modified DNA tiles
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Modified DNA tiles
Facilitates visualization by imaging devices such as AFM.
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Modified DNA tiles
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A1 2
3 4
B1’2’
3’4’B
A
BA
BA
BA
BA
BA
BA
BA
BA
BA
BA
BA
BA
BA
BA
BA
BA
BA
BA
BA
Cartoon of DNA lattice composed of two types of TAO tile:
B with (dark) and A without (light) stem-loops directed
out of the lattice plane.
TEM image of TAO AB* lattice
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Platinum rotary-shadow TEM image of DNA lattice
assembled by stoichiometric annealing of 8 oligos
designed to form two tile types (A and B):
A tiles (lighter) only associate with B tiles
(darker) and vice versa.
B tiles appear darker due to increased platinum
deposition on an extra loop of DNA directed out of
the lattice plane.
Stripes of dark B tiles have approximately 28 nm
periodicity, as designed.
TEM image of TAO AB* lattice
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TEM image of TAO AB* lattice
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Applications
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A method for assembly of complex patterns Use artificially synthesized DNA strands that
specify the pattern and around which 2D DNA
tiles assemble into the specified pattern. The permanent features of the 2D pattern are
generated uniquely for each case.
Directed Nucleation Self Assembly Steps an input DNA strand is synthesized that encodes
the required pattern then specified tiles assemble around blocks of
this input DNA strand, forming the required 1D
or 2D pattern of tiles.
Directed nucleation assembly
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Cumulative XOR
Inputs = xi
Outputs = yi
1 Choose x1, then set y1 = x1
2 Then for i > 1 yi = yi-1XORxi
XOR
x y XOR
0 0 0
0 1 1
1 0 1
1 1 0
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Start keysInputs (x = 0, 1)
Outputs: yi = f(xi,yi-1)
Tiles XOR
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Assembled XOR arrays
yi = yi-1 XOR xi
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Assembled XOR arrays
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X1 tilesY1 tiles
Y2 tiles
C tiles
X2 tiles
Sticky ends binds
Reporter strand
Ligation
PCR with primers for Reporter Strand
Algorithmic assembly
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Reporter strand
EcoR(1) cut PvuII(0) cut
EcoR: GATATC
PvuII: CAGCTG
Extraction of results
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Barcode lattice displays banding patterns dictated by
the sequence of bit values programmed on the input
layer.
Extends 2D arrays into simple aperiodic patterning:
The pattern of 1s and 0s is propagated up the
growing tile array.
The 1-tiles are decorated with a DNA stem-loop
pointing out of the tile plane (black rectangle) and
0-tiles are not.
Columns of loop-tiles and loopless-tiles can be
distinguished by AFM as demonstrated with periodic
AB* lattice.
Directed nucleation assembly
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Barcode Lattice for Readout
Input Strand
1 0 1 1 0 0 0 1 0 1 1 1
Directed nucleation assembly
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Applications
Molecular Scale Patterning of Molecular
Electronics and Molecular Motors.
Image Storage: a region 100km x 100km
imaged by a satellite to 1 cm resolution
resulting image is of size 1,000,000 x
1,000,000, containing 1012 pixels requires
a DNA lattice of size 2 millimeters on a
side.
Directed nucleation assembly
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Directed nucleation assembly
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Computation by self-assembly
Tiling Self-assembly can
Provide arbitrarily complex assemblies using
only a small number of component tiles.
Execute computation, using tiles that specify
individual steps of the computation.
Computation by DNA tiling lattices
First Proposed by [Winfree, 98].
First Experimentally demonstrated by [Mao, et
al 2000] Mao, C., T.H. LaBean, J. H. Reif, and
N.C. Seeman, An Algorithmic Self-Assembly,
Nature, Sept 28, p 493-495 (2000).
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Pads complementary base sequences determining neighbour relations of tiles in final assembly
Large-Scale Computational Tilings formed during assembly encode valid mappings of input to output. local tile association rules insure only valid computational lattices form regardless of temporal ordering of binding events.
Key Advantageof DNA Self-Assembly for DNA Computing Use a sequence of only 4 laboratory procedures: mixing the input oligonucleotides to form the DNA tiles, allowing the tiles to self-assemble into superstructures, ligating strands that have been co-localized, and performing a single separation to identify the correct output.
Computation by self-assembly
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A tiling assembly using `Smart Bricks' to sort 8 keys.
A B
B A
A B
A B
2 33 2
1 44 1
0 33 0
0 44 0
77
5 77 5
5 66 5
2 62 6
1 21 2
2 44 2
3 53 5
0 10
6 76 7
3 44 3
5 65 6
77
111
00
Computation with smart bricks
Sorting
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Defined by Wang [Wang61]
Input
a finite set of unit size square tiles,
Tile pads: each of whose sides are labeled with
symbols over a finite alphabet.
initial placement of a subset of certain tiles,
dimensions of the region where tiles must be placed.
Domino Tiling Problem
assuming arbitrarily large supply of each tile
place the tiles to completely fill the given region
each pair of abutting tiles must have identical
symbols on their contacting sides.
Domino tiling problem
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Speed of DNA self-assembly reactions
Between a few seconds to many minutes.
Far slower per assembly than silicon
technology.
Concurrent DNA self-assembly
Concurrent assemblies execute
computations independently.
Executes massively parallel computation
at molecular scale.
Degree of parallelism from 1015 to 1018.
Rates of self-assembly
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Mao, et al. “Logical computation using algorithmic self-
assembly of DNA triple-crossover molecules”, Nature
407:493, 2000.
Winfree, E. “Algorithmic self-assembly of DNA: Theoretical
motivations and 2D assembly experiments”, J. Biomolecular
Structure and Dynamics, 11:263, 2000.
LaBean, et al. “Construction, analysis, ligation, and
self-assembly of DNA triple crossover complexes”, JACS,
122:1848, 2000.
Rothemund, et al. “Using Capillary forces to compute by
self-assembly”, PNAS, 97: 984-989 , 2000
Seeman, et al. “Nucleic acid nanostructures and topolgy”,
Angew. Chem. Int. Edn. Engl. 37, 3220-3238 , 1998
References