1 Programmable Self-Assembled DNA-Based Autonomous Molecular Devices John Reif Duke University DNA Nanostructure Group John H Reif & Thomas H. LaBean Graduate

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Programmable Self-Assembled DNA-Based Autonomous Molecular Devices

John ReifDuke University

DNA Nanostructure GroupJohn H Reif & Thomas H. LaBean

QuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.Graduate Students: Harish Chandran and Nikhil Gopalkrishnan

Recent Graduated Phds: Urmi Majumder, Sudheer Sahu, & Peng Yin

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Self-Assembly in NatureSpontaneous organization of components into stable superstructures due to local

interactions

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Key to DNA Self-Assembly

T T G T T T A A C C T

A A C A A A T T G G A5’ 3’

5’3’

Hybridization

T T G T T T A A C C T

A A C A A A T T G G A5’ 3’

5’3’

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Hybridization for superstructures

(Mao et al: Nature00)NYU&Duke Univ(Park, et al 05) Duke Univ

(Yan et al Nature03) Duke Univ(He et al 05)

2D Periodic Grid Lattices

3D Cube

(Chen and Seeman, 91)

(Rothemund et al 04)

1D Algorithmic Assembly

(Rothemund 06)Origami - 2D Addressable Lattices

cool

Base Pairing

cool

sticky end

QuickTime™ and aTIFF (Uncompressed) decompressorare needed to see this picture.

(Yan et al: PNAS 03) Duke Univ

Barcode

Barcode patterning

2D Algorithmic Assembly2D Hierarchal Assembled Lattices(Park et al: Angewandte Chemie06) Duke Univ

(Lui et al PNAS 04) Duke(Yin et al Science 08)

Duke&Caltech

Tube Lattices

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Compact, Complex, Robust, Flexible,

Scalable, Easily CharacterizedComputing Device

Activatable Tiles (Compact, Robust)

Error MinimizationRedundant Tile Design

Binary Counter(Compact, Robust)

Part I

Stochastic ModelYield & Convergence

Rates(Easily Characterized)

DNA WalkersWalking on 1D & 2D

Lattices(Programmable)

Double-decker tiles Tiling in 3D

(Scalable)

ApplicationsReaction CatalyzationDNAzyme DNADoctor

Isothermal DNA or RNA Detection

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Double-decker tiles: Route to Assembly in 3D

• No tile rigid enough to create 3D periodic lattices

• Difficult to characterize

Challenges

Design a motif that can tile in 2D as well as 3D

Goal

Protein Crystallization: original goal of DNA nanotechnology

Molecular sieve, 3D computing, host guest molecules

Motivation


Urmi Majumder, Abhijit Rangnekar, Thomas H.

LaBean and John H. Reifin preparation

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Cross tiles: Grid Assembly in 2DCross Tile

Symmetric Tile

Figures adopted from He et al, 2005

Branched Junction

Corrugation creates enormous lattices

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4 identical arms

sticky ends

2 cross tiles held together by branched junctions

Branched Junction

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Corrugation cancels curvature of lattice=> creates enormous lattices

2D Corrugation

2D Pad Programming of Double-Decker Tiles

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Double-decker tiles: Route to Assembly in 3D2D Lattices

Yeilds:Extremely

Large, Regular2D Grids

with Predominant Unidirectional

Banding10 um

2D ProgrammedDouble-Decker

Tiles

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3D Programming ofDouble-Decker

Tiles

3D Generalized Corrugation cancels curvature of lattice in all 3 dimensions !

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Summary of Results

Double-decker tiles: Route to Assembly in 3DDNA Design of new motif (Double-decker tile)

Flexible sticky end programming

Sticky Ends can be programmed to form 2D lattices

Sticky Ends can be programmed to form 3D lattices

Agarose gel verification of tile formation

Programming of sticky ends for 2D Lattices with corrugation

AFM verification of formation of big, rigid lattices (10s of um)

Fluorescence verification of formation of enormous lattices (100s of um)

Analyze unidirectional banding in 2D lattices

Reprogramming of sticky ends for 2D lattices without corrugation

Fluorescence verification of formation of enormous lattices (100s of um)


Urmi Majumder, Abhijit Rangnekar, Thomas H.

LaBean and John H. Reifin preparation

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Part II






(Scalable)

ApplicationsReaction CatalyzationDNAzyme DNA Doctor


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Stochastic Analysis of Reversible Assembly

Every chemical reaction is reversible

Reversible Assembly close to reality

Information about time complexity, assembly yields

Motivation

Existing abstract model: irreversible and assumes error-free growth

Kinetic tiling assembly modeled errors for DNA

No framework for studying convergence rates

General model for reversible assembly in 2D: hard

whether infinite tiles form in the percolation problem not known in general case

Challenges GoalMake simplifying assumptions

Study existence of equilibrium in 2D and 3D assembly

Characterize equilibrium

Calculate time to equilibrium

Stochastic Assembly of Self-Assembly ProcessesUrmi Majumder, Sudheer Sahu and John

H. ReifComp. & Theo. Nano., 5,7 1289-1305, 2008

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Tiling AssemblyN

W T E

SInput1

Inp

ut

2

Outp

ut

2

Output 1

Encode computation as tiles Temperature = 2

Tiling Assembly is Turing Universal

Assembly Rule: Glue type as well as glue strength have to match for assemblyA tile can attach to an assembly iff the combined strength of the “matchings glues” is greater than or equal to the temperature.

x

y

yx

Counter Encoding

⋀

⊕ yx

1 100

Computational Tilesstrength =1

seed y input x input

strength = 2

1

2

3

4

5

6

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Tiling AssemblyKinetic Model for Errors

rf

rb,2

rf

rb,2rf

rb,1

1

2

7

8

9

Error due to pad mismatch!

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Stochastic Analysis of Reversible AssemblySolve important subclass of 2D assemblies

Allow only monomer addition (No super-tile assemblies allowed)

Pre-assembled boundary

Same on/off rate for each binding or dissociation event for all tile types

Binding Rule: A tile can bind to a site where it has at least two neighbors

Dissociation Rule: A tile can only dissociate from a growth site where it has at most two neighbors

Binding or dissociation event on one pad of a tile is independent of what’s happening on the remaining three pads

Model Assumptions

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Stochastic Analysis of Reversible Assembly

Equilibrium Characterization n x n completely addressable square

Let aij denote the fraction of a tile Tij when it is free at top /right

Assume σ = on probability and τ = off probabilityDropping subscripts, let a’ be the next time step value of a. Then

At steady stateOff event On event

Time Convergence:

Multiplicative (<1) decrease in

each time step

Δ(t), distance from equilibrium decays exponentially in t

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Stochastic Analysis of Reversible AssemblySummary of Results

General characterization of equilibrium for 2D assembly

Yields & Polytime Convergence to Equilibrium

Completely addressable square in 2D and 3D

Periodic Assembles

Algorithmic Assemblies (Distribution of error at near-equilibrium)

Assemblies with Partial Mismatches

Correlation between Rapidly Mixing Markov Chains and Self-Assembly

Stochastic Assembly of Self-Assembly ProcessesUrmi Majumder, Sudheer Sahu and John H. Reif

Comp. & Theo. Nano., 5,7 1289-1305, 2008

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Part III








(Scalable)

ApplicationsReaction Catalyzation

Enzyme Free DNADoctorIsothermal DNA or RNA Detection

Computational tiles

Frame tiles

Seed tile

Error!

Computational Errors (Winfree)

Error Resilience: Previous Approaches ➡ Optimizing physical conditions

‣ Decrease concentration and increase binding strength [Winfree 98]

‣ Shortcoming: Reduces speed

➡ Biochemistry Techniques‣ Strand invasion [Chen et al 04]

‣ Shortcoming: Increase in tile set size

➡ Coding Theory Methods‣ Proofreading Tiles, Snake Tiles, Zig-zag Tiles [Winfree et al,

2003, Chen et al 2004, Schulman et al 2005]

‣ Shortcoming: Increase in tile set size

‣ Compact Redundancy techniques [Reif et al 2004, Sahu et al 2006]

‣ Shortcoming: Ignores nucleation errors

Compact Error Correction of Computational Lattices (Reif, et al 2004)

Initial Computational Tiles:

Error Resilient DNA Tiles:

Self-Propagation of Error Detection

Makes Erroronious Assembly Unstable

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Error Minimization in Tiling Assembly: in vitroMotivatio

nNatural DNA self-assembly has powerful physical mechanisms for error correction & repair

Artificial self-assembly needs similar mechanisms

Very difficult to build large structures w/o these capabilities

ChallengeMinimize errors

at the same scale as original assembly

w/o modifying tile structure

GoalControl Physical parameters to reduce errors

Annealing Temperature

Relative Stoichiometry of tiles

Perform self-assembly w/o a scaffold

Error Minimization through Optimization of Physical Parameters: Assembly of a Binary Counting Lattice using DNA Cross-Tiles, Thomas H. LaBean, Sung Ha Park,

Urmi Majumder, Masahito Yamamoto, and John H. Reif, in submission (2009).

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Characteristics of the experiment

No nucleating structure used

Result comparable to previous demonstration of Binary Counter (Barish et al, 2005)

Error Minimization

Second step annealing temperature tuned based on melting data of tiles forming grids and ribbons

Relative stoichiometry of tiles tuned based on a fixed size binary counting pattern

Use of a pre-assembled nucleating structure

Minimize spontaneous nucleation

Information about which lattices to analyze under AFM

Summary of Results

Error Minimization in Tiling Assembly: in vitro

Error Minimization through Optimization of Physical Parameters: Assembly of a Binary Counting Lattice using DNA Cross-Tiles

Thomas H. LaBean, Sung Ha Park, Urmi Majumder, Masahito Yamamoto, and John H. Reif

Manuscript

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Error Minimization in Tiling Assembly: in vitroTemperature Control

After: Counting!

Before:Single tile association

BC2 BC3

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Error Minimization in Tiling Assembly: in vitroStoichiometry Control

Before

After: 70% reduction in Error

Tile # RatioBC1 20 10

BC2 40 20

BC3 22 11

BC4 18 9

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Error Minimization in Tiling Assembly: in vitroUse of pre-assembled nucleating structure

Minimize spontaneous nucleation

Information about which lattices to analyze under AFM

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Part IV






(Scalable)





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Error Minimization in Tiling Assembly: in silico Types of Error

Mismatch ErrorModel assumes directional growth (i/p to o/p)

Model assumes T=2 rule (at least two correct binding required)

Also known as error by insufficient attachment

Spontaneous Nucleation ErrorAssembly in absence of seed

Challenge Minimize errors

At the same scale as original assembly

Use already existing DNA nanostructures with minimal modifications

Handle all kinds of errors (related to the tile assembly model)

Goals

Enforce model assumptions at the same scale as original assembly

Activatable Tiles: Basic Idea

➡ Tiles are initially inactive ‣ o/p pads protected and not available

for hybridization➡ Tiles transition to active state and

o/p pads are exposed only when the correct neighbors bind to its input pads

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Error Minimization in Tiling Assembly: in silico

Error by insufficient attachment (T=2)

Activatable Tiles: Working Principle

➡Tiles are initially inactive ‣o/p pads protected and not available for hybridization

➡Tiles transition to active state and o/p pads are exposed only when the correct neighbors bind to its input pads

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Activatable Tile Correct Growth

Error Minimization in Tiling Assembly: in silicoOne correct i/p match induces

the other i/p deprotection

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Activatable Tile prevents errors by

insufficient attachment

Second i/p is not deprotected


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Error Minimization in Tiling Assembly: in silicoSmall probability of error from the tiles

that leave a growth site after being completely deprotected.

Input deprotection reversibleOutput deprotection irreversible

Source of Error

DNA Implementation

➡ Strand Displacement for Input Deprotection

➡ DNA polymerization for Output Deprotection

‣ Particularly Effective over long distances (e.g. tile cores)

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Strand DisplacementDNA

Polymerization

Strand displacing DNA Polymerization

DNA Strand Displacement

Using Polymerase Phi 29 for Strand Displacement: - Replicative polymerase from bacteriophage Phi29 - Phi29 polymerase can travel at the rate of 2000 nucleotides per minute at room temperature

- This polymerase has exceptional strand displacement and processive synthesis properties

Activatable Tiles: Basic Idea in 1D

DNA Design of 1D Activatable Tile

A Reaction PathwayStage 0

S2 S1A S1B H

S1A’ S1B’P’M

S2’5’

3’

3’5’

Tile Core

ETile 1(Protected)

5’3’

Tile 2(Unprotected)H’S1A’ S1B’

S3

Stage 2

Hybridization of sticky ends by displacement of the protection strand

S2 S1A S1B H

S1A’ S1B’P’

MS2’5’

3’

3’ Tile Core

E

3’

H’

S1A’ S1B’

S3

Stage 1

S2 S1A S1B

HS1A’ S1B’P’M

S2’5’

3’

3’ Tile Core

E

H’

S1A’

S1B’

3’

S3

Toehold hybridization

5’

Polymerase

Stage 5

S2 S1A S1B H

S1A’

S1B’

P’MS2’

5’3’

3’ Tile Core

E

5’3’

H’S1A’ S1B’ S3

Complete polymerization of the primer and dehybridization of protection strand from the output

sticky endS1AM’

Exposed output sticky end

5’

P5’

3’

S2 S1A S1B H

S1A’

S1B’

P’MS2’5’

3’

3’ Tile Core

E

5’3’

H’S1A’ S1B’ S3

Primer polymerization and gradual de-protection of output sticky end due to the stripping of the template strand

S1AM’

Stage 4

5’

3’

P

P

S2 S1A S1BH

S1A’ S1B’

P’MS2’5’

3’

3’ Tile Core

E

5’

3’H’S1A’ S1B’ S3

Primer binding to now available template (protection strand)Stage 3

5’

5’3’ PPrimer

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GSOriginal∝ E2

GS: Growth SpeedE: Error Rate

GS2x2∝ E

GSActivatable GSOriginal

>e-∊Gse

EActivatable EOriginal

= e-ɣGse

0<ɣ<<∊<1

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New kind of tile : Activatable tile

Tile set size same as before

Basic nanostructure: existing tile types

Errors handled

Minimizes error due to insufficient attachment (proof)

Minimizes nucleation error

Allows self-healing (proof)

Summary of Results


Protection / deprotetcion mechanism

through strand displacement + polymerization

DNA Design of 1D/2D activatable tile system

Applications beyond computing

Concentration System

Reaction CatalyzationActivatable Tiles for Compact, Robust Programmable Assembly and other Applications

Urmi Majumder, Thomas H. LaBean, and John H. Reif

DNA 13, LNCS 4848, 15-25, 2007

Summary➡ Activatable tiles reduce error in

assembly by virtue of physical design of the tiles (use of DNA strand displacement and DNA polymerization)

➡ Other Potential Applications:‣ A Chemical Concentration Probing System‣ Chemical Reaction Catalytic System

➡ Current Work: ‣ Test a 1D Deprotection System

➡ Open Question: ‣ Overlay Redundancy Technique+ Activatable

Tiles

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Part VI






in silico




(Scalable)



DNA Walker Devices: Formulation & First Designs [Reif, 2002]Designs for the first autonomous DNA nanomechanical devices that execute cycles of motion without external environmental changes. Walking DNA device Rolling DNA deviceUse ATP consumption Use hybridization energy

These DNA devices translate across a circular strand of ssDNA and rotate simultaneously. Generate random bidirectional movements that acquire after n steps an

expected translational deviation of O(n1/2).

Bidirectional Translational& Rotational Movement

dsDNAWalker:

ssDNARoad:

Walking DNADevice

Bidirectional RandomTranslational& RotationalMovement

ssDNARoller:ssDNA

Road:

Rolling DNADevice

First Autonomous DNA Walker 2004: Peng Yin, Hao Yan, Xiaoju G. Daniel, Andrew J. Turberfield, John H. Reif, A Unidirectional DNA Walker Moving Autonomously Along a Linear Track, Angewandte Chemie Volume 43, Number 37, Sept. 20, 2004, pp 4906-4911.

B C D A

Track

AnchorageA

Walker*

LigasePflM I

BstAP I

Restriction enzymes

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Autonomous Motion of the Walker

• autonomous, • programmable, and further require • no protein enzymes. ________________________The basic principle involved is inspired by a simple but

ingenious molecular device due to Mao et al

– Mao used DNAzyme to traverse on a DNA nanostructure, but was not programmable (it did not executed computations).

Programmable Autonomous DNA Nanorobotic Devices Using DNAzymes John H. Reif and Sudheer Sahu

Our DNAzyme based designs1.DNAzyme calculator : a limited ability computational

device

2.DNAzyme FSA: a finite state automata device, that executes finite state transitions using DNAzymes• extensions to probabilistic automata and non-deterministic automata,

3.DNAzyme router: for programmable routing of nanostructures on a 2D DNA addressable lattice

4.DNAzyme porter: for loading and unloading of transported nano-particles

5.DNAzyme doctor : a medical-related application to provide transduction of nucleic acid expression. 1. can be programmed to respond to the under-expression or over-expression

of various strands of RNA, with a response by release of an RNA

2. operates without use of any protein enzymes.

DNAzyme FSA (inputs, transitions)

DNAzyme Crawler

DNAzyme Calculator

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A “Molecular-Racecar” on Circular Track Used Power of Strand-displacing Polymerase

Used Polymerase Phi 29 to push wheel W on circular track T

-Protector BQ prevents W from moving on its own-Powerful strand displacement capability of Phi 29 during polymerization dislodges BQ from track=> much faster & forceful movement than other DNA Walkers

Sudheer Sahu, Thom H. LaBean, John H. Reif, A DNA Nanotransport Device Powered by Polymerase Phi29 , Nanoletters, 2008

Polymerase Phi 29Replicative polymerase from bacteriophage Phi29 Phi29 polymerase can travel at the rate of 2000 nucleotides per minute at room temperatureThis polymerase has exceptional strand displacement and processive synthesis properties

-Experimental Demonstrations via FRET and Gel data

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Summary







(Scalable)





Other Applications of Activatable TilesMolecular Sensing and Concentration System

Other Applications of Activatable TilesReaction Catalyzation

Other Applications of Activatable TilesReaction Catalyzation

DNAzyme Doctor (state diagram)

DNAzyme Doctor(RNA expression)

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Application of DNA Nanotechnology: Isothermal DNA and RNA Detection

Isothermal detection protocols: exquisitely sensitive detection of specific DNA or RNA sequences. Report target DNA detection via nanoparticle colorimetric detection.Two Isothermal Detection Techniques Demonstrated: (1) Superlinear Hybridization Chain Reaction (HCR)- Based on linear hybridization chain reactionof (Dirks04).-triggered by target DNA or RNA- New DNA detection protocol using a superlinear hybridization cascade reaction - No use of Enzymes- Superlinear Detection Response- nanoparticle-based colorimetric readout.

(2) Cross-Catalytic Deoxyribozymogen Reaction (DRZ) - No use of Protein Enzymes- Based on cross-catalytic DNAzyme-based reaction of (Levy03)-triggered by target DNA or RNA- Exponential Detection Response- nanoparticle-based colorimetric readout.

Diagnostic Applications:Detectiion of Disease Sequences (DETECTIONChlamydia & HIV)

The modification of the HCR and DRZ methods to detect target sequences in Chlamydia trachomatis bacterial DNA & HIV viral RNA/DNA sequences.

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Summary






ApplicationsReaction Catalyzation

Enzyme Free DNADoctorIsothermal DNA or RNA Detection


(Scalable)



Documents

1 Programmable Self-Assembled DNA-Based Autonomous Molecular Devices John Reif Duke University DNA Nanostructure Group John H Reif & Thomas H. LaBean Graduate