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Course outline. Introduction. What is self-organisation?. System with discrete components Spontaneously ordered properties Global Order from Local, random interactions. Living systems. Self-organized catalytic set of molecules Origin of life RNA world Driving force is G - PowerPoint PPT Presentation

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Page 1: Course outline
Page 2: Course outline

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

Page 3: Course outline

Introduction

Page 4: Course outline

What is self-organisation?

System with discrete components

Spontaneously ordered properties

Global Order from Local, random

interactions

Page 5: Course outline

Self-organized catalytic set of molecules

Origin of life

RNA world

Driving force is G

Goal is self-replication

Living systems

Page 6: Course outline

Self-Reproducing (cellular) Automata

Artificial Neural Networks

Boolean Networks

Artificial Life Systems

Evolutionary Systems

DNA Systems

Artificial self-organisation systems

Page 7: Course outline

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

Page 8: Course outline

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

Page 9: Course outline

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

Page 10: Course outline

Construction with smart brick

Page 11: Course outline

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

Page 12: Course outline

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.

Page 13: Course outline

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.

Page 14: Course outline

Magnetic meso-scale self-assembly

Wisconsin material sciences group

Page 15: Course outline

Magnetic meso-scale self-assembly

Wisconsin material sciences group

Page 16: Course outline

Programming 2-d DNA lattices

for the construction of molecular

scale structures

for rendering patterns at the

molecular level

Page 17: Course outline

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

Page 18: Course outline

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

Page 19: Course outline

Programming 2-d DNA lattices

Page 20: Course outline

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

Page 21: Course outline

DX molecules

DNA crossover molecules self-assembled from

artificially synthesized single stranded DNA.

Page 22: Course outline

DX molecules

Page 23: Course outline

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

Page 24: Course outline

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

Page 25: Course outline

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.

Page 26: Course outline

TX tiles

[LaBean et al, J. Am. Chem. Soc., 2000]

Page 27: Course outline

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

Page 28: Course outline

TX tiles

Page 29: Course outline

Another way

Page 30: Course outline

Still another way

Page 31: Course outline

Or another way

Page 32: Course outline

A tiling is an arrangement of tiles

(shapes) that covers a plane

Tiles fit based on matching rules

(complementary shapes)

Self assembly and computation

Page 33: Course outline

XOR tile

Self assembly and computation

Page 34: Course outline

Wang Tile

Self assembly and computation

Page 35: Course outline

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

Page 36: Course outline

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)

Page 37: Course outline

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

Page 38: Course outline

Sticky ended cohesion-ligation

DNA as building material

Page 39: Course outline

DNA as building material

Assembly of branched junctions into a 2-d lattice

Page 40: Course outline

DNA as building material

Holiday junction

Page 41: Course outline

DNA as building material

Flexibility of DNA branched junctions

Page 42: Course outline

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

Page 43: Course outline

Constructing DNA objects

Page 44: Course outline

Constructing DNA objects

Borromean Rings Truncated Octaheadron

Page 45: Course outline

Design & Synthesize Oligonucleotides

Formation of H-bonded Complex

Purification using Gel Elecrophoresis to

eliminate the linear strands

Phosphorylation and Ligation

Construction of tiles

Page 46: Course outline

Construction of tiles

Page 47: Course outline

Single molecule gaps

Crossover molecules

Page 48: Course outline

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

Page 49: Course outline

Ned Seeman

DNA topological structures

Page 50: Course outline

DNA topological structures

Ned Seeman

Page 51: Course outline

DNA topological structures

Ned Seeman

Page 52: Course outline

Imaging

Page 53: Course outline

TX tiles

Page 54: Course outline

Metallic nanoparticles.

Triangles or multi-triangle tiles.

Biotin-streptavidin (with or without

nanogold).

Multi-tile subassemblies.

New tile topologies.

Stem-loops

Imaging

Page 55: Course outline

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

Page 56: Course outline

Modified DNA tiles

Page 57: Course outline

Modified DNA tiles

Facilitates visualization by imaging devices such as AFM.

Page 58: Course outline

Modified DNA tiles

Page 59: Course outline

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

Page 60: Course outline

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

Page 61: Course outline

TEM image of TAO AB* lattice

Page 62: Course outline

Applications

Page 63: Course outline

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

Page 64: Course outline

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

Page 65: Course outline

Start keysInputs (x = 0, 1)

Outputs: yi = f(xi,yi-1)

Tiles XOR

Page 66: Course outline

Assembled XOR arrays

yi = yi-1 XOR xi

Page 67: Course outline

Assembled XOR arrays

Page 68: Course outline

X1 tilesY1 tiles

Y2 tiles

C tiles

X2 tiles

Sticky ends binds

Reporter strand

Ligation

PCR with primers for Reporter Strand

Algorithmic assembly

Page 69: Course outline

Reporter strand

EcoR(1) cut PvuII(0) cut

EcoR: GATATC

PvuII: CAGCTG

Extraction of results

Page 70: Course outline

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

Page 71: Course outline

Barcode Lattice for Readout

Input Strand

1 0 1 1 0 0 0 1 0 1 1 1

Directed nucleation assembly

Page 72: Course outline

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

Page 73: Course outline

Directed nucleation assembly

Page 74: Course outline

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).

Page 75: Course outline

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

Page 76: Course outline

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

Page 77: Course outline

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

Page 78: Course outline

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

Page 79: Course outline

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