Mastering the complexity of DNA nanostructures

Mastering the complexity of DNAnanostructuresMarco Brucale1, Giampaolo Zuccheri1,2,3 and Bruno Samorı1,2

1Department of Biochemistry “G. Moruzzi” University of Bologna, Via Irnerio, 48; Bologna, Italy- 401262National Center on nanoStructures and bioSystems at Surfaces (S3) of INFM-CNR, Via G. Campi, 2 –Modena I-411003National Consortium of Materials Science and Technology (INSTM)

The self-assembly of oligodeoxynucleotides is a versatile

and powerful tool for the construction of objects in the

nanoscale. The strictly information-drivenpairingofDNA

fragments can be used to rationally design and build

nanostructureswithplanned topologies andgeometries.

Taking advantage of the steadily expanding library of

well-characterized DNA motifs, several examples of

structureswith different dimensionalities have appeared

in the literature in the past few years, laying the

foundations for a promising DNA-mediated, bottom-up

approach to nanotechnology. This article focuses on

recent developments in this area of research and

proposes a classification of DNA nanostructures based

on topological considerations in addition to describing

strategies for tackling the inherent complexities of such

an endeavor.

Introduction

Objects shorter than the characteristic lengths associatedwith particular physical phenomena often display newproperties, including conductivity, reactivity and thermo-dynamic andmechanical behaviors. For this reason, at theatomic, molecular and macromolecular scales, propertiesare exhibited that differ significantly from those at alarger scale. Thus, the precisely controlled assembly ofmatter with nanometer resolution has the potential ofprompting dramatic future technological advances and iscurrently a foremost goal in several fields, includingmaterials science, electronic engineering and biosensordevelopment. Several methods have been developed forobtaining nano-patterned or nano-structured materials ofvarious chemical natures [1]; among these, the methodsbased onDNA offer possibilities that cannot bematched byother molecules. In the context of nanotechnology, DNAcan be regarded as the supramolecular building block withthe highest informational content. The Watson and Crickcomplementarity code can be exploited to organize theintra- or inter-molecular self-assembly of an arbitrarynumber of natural or synthetic DNA molecules.Nanoscience can use this, and other specific codesembedded in the DNA sequence, to plan and implementefficient and complex self-assembly and self-directingprocesses [2]. Moreover, DNA can be easily modified

Corresponding authors: Samorı, B. ([email protected]); Zuccheri, G.([email protected]).

Available online 15 March 2006

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with extreme precision and versatility by syntheticchemistry or by taking advantage of the extensive toolboxprovided by natural enzymes. A DNA molecule can bedecorated with different species, such as metal nanopar-ticles, proteins, carbon nanotubes or organic dyes [3–11],and still retain its self-assembly abilities, thus providing astraightforward method for organizing an ample library ofthese nano-sized objects into well-defined structures.

Structural DNA nanotechnology was commenced in1982. Inspired by the branched intermediates of nucleicacids during recombination, Ned Seeman started toinvestigate the possibility of obtaining topologically andgeometrically defined DNA branched nanostructures [12].In particular, he used the immobile Holliday junction [13](Figure 1), and other junctions with between three and sixdouble-helical arms [14], to introduce stable branchingpoints in DNA, making it possible, in principle, to obtainarbitrarily complex nanostructures of virtually any shape.An exhaustive review of all the most important motifsused so far in DNA nanotechnology has been writtenrecently by Seeman and Lukeman [15].

Another possibility offered by branched DNA is todesign networked structures in which several DNA chainsare mechanically coupled through multiple junctions.Here, the mechanical stresses exerted on a small portionof the structure must distort the whole network to have aneffect. The result is that the entire structure has a rigiditysurpassing that of an isolated double-stranded chain,which is a rather rigid polymer itself [16].

The supramolecular interactions giving rise tocomplex DNA-based nanostructures are intrinsicallyencoded in the sequences of the constituent strands.Being strictly information-regulated, the self-assemblingprocess that leads from a collection of DNA strands tothe complete nanostructure can be viewed as a form ofprogrammable nanofabrication in which the program isdefined by the set of the involved sequences [12].Once the desired set of strands is appropriately designed(Box 1) and synthesized, the assembly of the completestructure can be as simple as mixing all the componentsat high temperature and then letting them cool downover periods of time up to a few days, in a near-equilibrium regime [17,18].

Most of the ongoing development of DNA-basednanostructures aims to expand their complexity over

Review TRENDS in Biotechnology Vol.24 No.5 May 2006

. doi:10.1016/j.tibtech.2006.02.009

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(a)

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Figure 1. Schematic representation of some of the main assembly features used in

DNA nanoarchitectures. (a) Cohesion of two double-helical fragments by means of

‘sticky-ends’. A sticky end is a single-stranded overhang protruding from a double-

helical segment. Two such overhangs with complementary sequences can bind,

giving rise to an aggregate that assumes the geometrical characteristics of a

continuous double-helix with two nicks. If desired, such paired structures can be

further stabilized by chemical or enzymatic ligation to make the phosphodiester

backbones continuous. (b) Schematic illustration of a Holliday Junction. If a set of

oligonucleotides is synthesized so that they form a branched junction in which the

sequences that flank the center do not have any symmetry, the branching point

cannot migrate as it does in the naturally occurring symmetric junction, and the

junction is, thus, labeled ‘immobile’. The angles and lengths in the scheme do not

correspond to the actual structure. (c) Sticky-end-mediated cohesion of branched

structures. A four-arm junction with four self-complementary sticky-ends forms a

superstructure with the shape of a quadrilateral by binding to three other similar

junctions. This shape is often called ‘DNA parallelogram’ or ‘DNA rhombus motif’.

Other junctions can bind to the quadrilateral and form a continuous lattice. (d)

Scheme of a DNA double crossover (DX) motif. The depicted motif can be viewed as

two linked four-way junctions. Several possible DX conformational isomers exist in

addition to that depicted here.

Box 1. Designing the sequences

The key step in the construction of these DNA architectures is the

design of the sequences of the constituent oligonucleotides. The

success or failure of the self-assembly is intrinsically determined by

the interplay between the affinity and specificity of those sequences

[69]. Additional characteristics that could be required are the

inclusion or exclusion of sub-sequences of biological or biochemical

relevance (e.g. promoters, restriction sites and deoxyribozymes)

[70]. The design problems of these sequences are not exclusive to

structural DNA nanotechnology but also arise in other fields such as

probe selection for DNA microarrays or primer design for PCR.

However, the complexity of the self-assembly required to form even

the most simple DNA architectures is usually much higher than that

required by other such applications. The design of more than just a

handful of sequences meeting the desired criteria makes the use of

computer programs indispensable [71].

The pipeline for the design of a DNA nanostructure begins with the

definition of the number, length and mutual connections of all the

component oligonucleotides, keeping the intended topology of the

assembly clear in mind. Then the base sequences are chosen,

obeying a set of criteria most commonly based on the minimization

of sequence symmetry [12] and energy [13]. Sometimes, however,

sequence symmetry can be intentionally included and exploited

advantageously [72]. The ongoing development also tries to take

into account the kinetic features of the energy landscape of the

assembly in order to avoid trapping the assembling structures into

unwanted stable by-products that would be alternative to the target

structure [73]. We foresee the need for design tools that could also

implement the concepts of hierarchical assembly and permit the

organization of different stability regions for different hierarchy

levels within one superstructure.


spatial and temporal dimensions through hierarchicalintegrations of elementary structural and functional units.

Topological and geometrical dimensions of the

assembly

DNA nanoarchitectures are characterized by theirgeometrical and topological properties. Although thegeometrical dimensionality of an object is identifiedsimply, the topological dimensionality of a structure isrecognized less easily: in general terms, topology is thestudy of those properties of a structure that are preservedthrough its deformation. As a coarse but useful definition,the topological dimensionality of an object is the number ofcoordinates needed to univocally specify a point of theobject. The characteristic way in which the points of anobject are connected among themselves does not changewith deformation and defines its topological attributes. Asan example, a line is topologically one-dimensional, even ifit is warped into a sinusoid or a helix and has ageometrical dimensionality higher than one. A flatsurface, a curved surface or a tube are all two-dimensionalobjects topologically, regardless of their geometricaldimensionalities. These topological concepts are usefulfor describing and classifying DNA nanostructureswithout ambiguity.

The most common approach is to base the description ofstructures on the way the branching points included inthem are connected. This permits discussion of motifs andstructures without the complication of considering theirmechanical flexibility and, thus, the geometrical

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deformations to which they might be subjected. As anexample, it is possible to discuss the design of DNAnanostructures having the connectivity of polyhedra [14],even if the exact geometry of such objects varies duringtime because of thermal conformational fluctuations.

An alternative approach is to consider any structure asan array and take into account, exclusively, how the sub-units (tiles) constituting the array are connected amongthemselves regardless of their shape. For example, anyarray in which each tile is connected to exactly two othertiles is a topologically linear, one-dimensional array, evenif the geometrical shape of the array has more than onedimension. An individual object not connected to any otheris considered a zero-dimensional array.

Herein, we attempt to rationalize the different types ofDNA nanostructures reported so far by using thisalternative classification. One of the advantages is thatthe geometrical shapes of the reported DNA nanoarchi-tectures are extremely varied, whereas there are only alimited number of different topological dimensionalitiesavailable to build DNA arrays. Moreover, the topologicaldimension of the array has an undeniably fundamentalrole in the design and implementation of DNA nanoarchi-tectures. This type of categorization is implied innumerous descriptions of DNA nanoarchitectures, evenif it is seldom exploited as a means of classification.

Topologically zero-dimensional arrays: discrete DNA

constructs

The earliest achievements of structural DNA nanotech-nology were the construction of discrete objects such as aDNA cube, a DNA truncated octahedron or DNABorromean rings (three interlinked rings, whereby the


Review TRENDS in Biotechnology Vol.24 No.5 May 2006 237

linkage between any pair of rings disappears in theabsence of the third) [14]. These were not designed tointeract with other molecules and form superstructures,thus they were topologically zero-dimensional, asdescribed above. The mainstay for this type of designwas the DNA multiple-branched junction [19], whichensured complete sequence-dependent topological controlbut lacked the geometrical rigidity required to formobjects with a reliably programmable shape. Recently,however, Mao and co-workers proposed the possibility ofimplementing the concept of tensile integrity (tensegrity)in DNA nanostructures [20]. Tensegrity is a property ofobjects, conferred by components that balance opposedtension and compression loads in a combination thatyields a high mechanical resilience. By implementing thisconcept in the design of DNA nanoarchitectures a rigidzero-dimensional structure can be obtained, even fromnon-rigid components.

Other reported examples of discrete DNA nanostruc-tures include a DNA tetrahedron [21], and an octahedronremarkably formed by a 1.7 kilobase single-stranded DNAthat folds into the programmed shape [22] with the aid offive shorter oligonucleotides (Figure 2a). Most of the DNA-based nanomotors reported so far are zero-dimensionalobjects, which are not designed to oligomerize or interact,although there are examples of motor elements introducedinto higher-dimensional assemblies [23].

One-dimensional topologies: linear arrays

To obtain a superstructure with a geometrically definedshape propagating in just one topological dimension, rigidconstituent elements are required. The DNA rhombus [24]and the DNA double crossover (DX) [25,26] (Figures 1b–d)were the first suitably rigid DNA motifs developed. Thesimplest possible assembly of multiple sub-units is a one-dimensional periodic arrangement in which each unitbinds to the successive by means of cohesive sticky-ends(Figure 1a), leading to the formation of a long linearsuperstructure; this was achieved for the first time usingthe aforementioned structural motifs [24,27,28]. Once thisproof-of-concept was obtained, the research focusgradually shifted to the construction of arrays generatedby DNA motifs capable of conferring specific features.Recently, a new type of DNA motif, the helical bundle,enabled the construction of one-dimensional, linearlyarranged arrays reaching contour lengths of severalmicrometers [29]. Linear arrays do not need to begeometrically one-dimensional, as exemplified by theassemblies described in Box 2 and Figure 2b.

The simple option of having just one self-complemen-tary constituent unit is not the only one suitable forbuilding one-dimensional linear arrays. It is also possibleto design a set of two or more sub-units with differentcomplementarities, whereby the order of the successivecomponents in the array is a consequence of the set ofinstructions represented by the complementary sub-units.This also permits us to go beyond the limits of a periodicsuccession of components and obtain a completelyaperiodic, algorithmic self-assembly. The algorithmicself-assembly of DNA can be used not only for a molecularfabrication task but also as a physical model of


computations [30–33]. This approach led to the rapidconvergence of DNA computing [34] with structural DNAnanotechnology: both fields aim for full control over theassembly of individual units over disparate length scalesin an attempt to create structures that can be pro-grammed, bottom-up, from individual molecules.

Two-dimensional topologies

The structural units (e.g. branched junctions and stickyends) and the self-assembly mechanisms we described forone-dimensional structures are the same as those used tobuild two-dimensional arrays. A large variety of motifswere obtained from those structural units and used todesign DNA tiles that are capable of self-assembling intotwo-dimensional periodic lattices, including the double-(Figure 1d) and triple-crossover (TX) [17,25,35], theparallelogram or rhombus motif (Figure 1c) [24], thefour-by-four structure (Figure 2c) [7], the three- and six-helix bundles [29,36,37] and the DX triangle [38].Comparing the lists of motifs used to obtain one- andtwo-dimensional arrays, readers will notice that a fewmotifs are present in both, for example the DNA bundlesand the DNA parallelogram. This is because the overallshape and properties of the assembled array is notdictated solely by the constituent motif but, moreimportantly, by the way each element binds to theneighboring ones. Thus, the shape of the array isultimately dependent on the exact position, orientationand length of the cohesive sticky ends on the tiles.

Once the hurdle of designing the set of DNA tiles isovercome (Box 1), two-dimensional lattices are usuallybetter behaved than one-dimensional linear structures.One reason for this is that each tile in a regular two-dimensional lattice is linked to at least three otheradjoining tiles instead of only two, as in linear arrays:this implies that the persistence of the whole structuredoes not depend, crucially, on the simultaneous stability ofeach tile–tile interaction. In linear arrays, the rupture ofeven one interaction between two adjacent tiles results inthe breakdown of the whole structure into smaller parts.Conversely, in two-dimensional lattices, the rupture of onetile–tile bond is not sufficient to impair the overallstructural integrity, and the removal of an internal tileis unlikely because it entails the simultaneous rupture ofall the interactions with the neighboring tiles.

Two-dimensional lattices of DNA, in which the tilesinclude chemically modified oligonucleotides [3–11,39],can be used to obtain programmable nanosized patterns offunctional chemical moieties on surfaces. Through suchchemical functionalizations these information-containingscaffolds can then direct the localization of furtherfunctional moieties on the nanoscale [2,4]. For this reason,two-dimensional DNA arrays have several potentialapplications in molecular electronics, sensors andsmart materials.

The increase of topological dimensionality from one- totwo-dimensional arrays implies an increase in thecomplexity of the constituent network of tiles. Thismeans that it is possible to code more complex algorithmsinto the self-assembly of two-dimensional lattices thaninto their one-dimensional counterparts. It has been


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Figure 2. Examples of DNA nanoarchitectures with different topological dimensionalities. (a) A zero-dimensional array (i.e. an individual DNA octahedral object) [22]. Adapted

with permission from Macmillan Publishers Ltd. (a1) The ‘unfolded’ structure of the octahedron. It consists of one long (1.7 kilobases) and five short strands. Five of the edges

of the octahedron are double crossover (DX) motifs, formed by specific regions of the long strand and the five shorter-strands, here colored in blue. The remaining edges are

subsequently formed by the paranemic cohesion of appropriately designed domains. The pairs of complementary domains are labeled with the same colors. Edges are

joined by four-arm junctions (labeled with roman numbers). (a2) Representation of the structure resulting from the cohesion of all the domains. The vertexes of the

octahedron are the four-arm junctions and have the same numeration as in panel (a1). (a3) Cryo-electron microscopy imaging of the octahedron. The first- and the third-row

panels are the raw images of individual particles, and the second and fourth are the result of projecting the experimental data onto a three-dimensional model of the folded

octahedron, obtained by single-particle reconstruction techniques. (b) One-dimensional DNA arrays made of triangular tiles. Adapted with permission [20]. (b1) Schematic

representation of a DNA triangle comprising three duplex domains (shown as rods of different colors). Vertexes are four-way junctions, where the blue domain is equipped

with a pair of complementary sticky ends on opposed termini. Each domain is exactly seven-helical-turns long. (b2) One-dimensional array generated by the sticky-end

cohesion of the triangular tile shown in panel (b1). Because the sticky ends are separated by an integer number of helical turns, each triangular tile is oriented in the same

direction. (b3) An atomic force microscope (AFM) image of the array depicted in panel (b2). Size bar is 100 nm. (b4) Triangular tile similar to that represented in panel (b1) but

with a 7.5-turn-long blue domain. (b5) One-dimensional array generated by the sticky-end cohesion of the triangular tile shown in panel (b4). Because the periodicity

comprises an odd number of half-helical turns, tiles point alternately in opposite directions. (b6) An AFM image of the array depicted in panel (b5). Size bar is 100 nm. (c) Two-

dimensional DNA array comprising two alternating tiles. Adapted with permission [39]. (c1) Strand structure of one of the two tiles comprising the array. The tile is a DNA

‘four-by-four’ motif, consisting of four four-way junctions flanking a central cavity. Each external double-helical domain ends with a sticky-end, labeled with a different

number. This tile incorporates a biotin group, represented here as a red dot, which does not impair the assembling ability of the tile. (c2) Strand structure of the second tile

participating in the array, similar to that depicted in panel (c1) but without the biotin. Sticky ends labeled N 0 are complementary to those labeled N in panel (c1). (c3)Schematic

of the array resulting from the assembly of the tiles depicted in panels (c1) and (c2). The sticky ends in both tiles are cleverly arranged so that the array has a corrugation

scheme that minimizes distortions out of the plane [36]. (c4) An AFM image of the array schematized in panel (c3). Size bar is 300 nm in the main figure and 100 nm in the

inset. (c5) An AFM image of the same array after functionalization with streptavidin (STV). STV molecules bind to the biotin present on one of the tiles and appear as white

dots localized at alternated junctions, as expected from the model shown in panel (c3). Size bar is 300 nm in the main figure and 100 nm in the inset.




Box 3. Strategies to decrease errors in the assemblies

The degree of perfection of self-assembled DNA nanostructures

depends on the emergence of defects or mismatches during the

assembly, possibly impairing structure and function of the construct.

DNA computing is particularly sensitive to any imperfection in the

assembly and devising countermeasures to this inconvenience is an

active field of research [74].

One approach for the minimization of growth errors is the

optimization of the physical conditions under which the growth

occurs. Mismatches occur when a DNA tile binds to the growing

array in an energetically sub-optimal configuration. Under equili-

brium regime, the energy landscape is thoroughly sampled over the

course of time, and specific interactions are preferred on the basis of

their thermodynamic stabilities: this process is controlled by

association and dissociation rates. Arbitrarily low error-rates can

be achieved by appropriate control of these contrasting rates,

although this necessarily occurs at the cost of a significant slow

down: decreasing error rates by a factor of 10 entails slowing down

the self-assembly process by a factor of 100 [75].

Erik Winfree and co-workers have proposed two main strategies to

decrease the error rate in the formation of two-dimensional

assemblies without slowing down the process. The first relies

upon the concept of ‘proofreading tile sets’ [75]. These sets are

designed so that if a mismatched tile is incorporated into the

assembly there is no way to continue growth without making an

additional error. The result is that, when a mismatch error occurs, the

assembly process effectively stalls, giving time to the mismatched

tile to detach from the assembly and be replaced by a correct tile.

The second strategy is aimed at the correction of spurious

nucleation errors [76]. This can be achieved if assembly originating

from a seed tile (seeded growth) proceeds quickly, whereas those

originating from a non-seed tile (unseeded growth) stops because

their propagation is highly improbable. The main concept behind

such a tile set is a predetermined sequence in which the tiles bind to

the assembly during seeded growth. The tiles bind in this sequence

because the correct growth continually provides the most favored

binding site for the next tile, whereas out-of-sequence growth must

continuously advance through energetically unfavorable structures.

Box 2. Building three-dimensional objects with one-dimen-

sional topologies

Topologically one-dimensional arrays can result in a variety of

geometries. For example, if we represent each tile as a single point,

these can be arranged on a straight line or on a curve such as a three-

dimensional-helix.

One way of making a three-dimensional helix out of topologically

linearly arranged, flat and rigid rhomboidal DNA tiles (see Figure 3b

for an example of strand structure of a typical rhomboidal tile) is to

equip each tile with two sticky ends pointing in different directions.

In addition, the joining of the two sticky ends must connect

subsequent tiles at a dihedral angle so that they are not coplanar:

With rhomboidal tiles, this can be achieved by having a non-integer

number of half-helical turns between branching points belonging to

adjacent tiles in the assembled array (Figure I). The overall

architecture of such a super-helix is thus determined by the

geometrical features of the tiles and their connections. These objects

have a considerable bending and torsional flexibility because

successive tiles are only connected through a single sticky-end;

nonetheless, they oscillate around an average helical shape. The

figure reports an example of a model for a super-helical structure

built out of flat parallelogram tiles and AFM images showing such

chains once adsorbed on a flat surface (Giro, A., et al., unpublished

data).

20 nm

60 nm

4 tu

rns

(a) (b)

(c) (d)

Figure I. (a) Model of a DNA parallelogram with four full helical turns between

branching points. The strand structure is not depicted here but it is similar to the

rhombuses in Figure 3. (b) High-resolution AFM image of a single parallelo-

gram tile adsorbed on mica, showing the cavity between the four double-helical

domains. (c) Model of a topologically one-dimensional helical polymer made of

the flat parallelogram tiles described in panel A and linked by sticky-ends

cohesion. Each connection sets an angle between the planes of successive tiles.

(d) AFM image of poly-parallelograms after spreading on the mica surface.


theorized [31] that a two-dimensional self-assembly ofDNA tiles can physically model a set of abstract Wang tiles[40]. Two-dimensional Wang tiles can be defined as equal-sized squares with a color on each of its four sides. Whenlaid down to tile a plane, each square must be placed sothat adjoining sides have the same color; thus, eachdifferent tile set has its peculiar way of tiling the plane. Allmathematical algorithms can be translated into a set ofWang tiles. A single Wang tile binding to neighboring tilesaccording to its color coding can be represented by a DNAtile spontaneously binding to other tiles as a result of thecomplementarity of its sticky ends. Accordingly, all


algorithms can be encoded in a set of DNA Wang tiles.The result of the algorithm is the assembly of the tile setinto a two-dimensional DNA ‘algorithmic crystal’ [27,41].However, any defect or mismatch occurring during theassembly impairs the output result; therefore, a consider-able effort has been directed to design error-proof, self-assembling sets of tiles that minimize the occurrence oferrors (Box 3). Although two-dimensional algorithmic self-assembly offers new capabilities for both computation andnanoconstruction compared with its one-dimensionalcounterpart, the design is more challenging [42] and wasonly successfully implemented, experimentally,recently [41].

If a periodic array is based on a tile that is not perfectlyplanar, or if the tiles are connected so that they are notcoplanar, the deformations in the propagating structurewill accumulate to an extent that might ultimately becomea limiting factor in determining the extension of thelattice. Many published atomic-force microscopy images oftwo-dimensional lattices show ribbon-like structuresrather than indefinitely wide periodic arrays. It has beenproposed [43] that this is because of the tendency of suchlattices to form curved surfaces that eventually reach atube-like shape, inhibiting further growth of the lattice.The ribbons seen in the images could be the result ofdiscrete tubes forming in solution and then unrollingthemselves during deposition on a flat surface, like that of



mica. Recently, this feature has been rationalized andintentionally included in the design of sets of tiles thatself-assemble in DNA hollow nanotubes [29,36,37,43–45].

Three-dimensional topologies

The original goal for building DNA nanoscale arrays camefrom Seeman: his original idea was to use a regular DNAthree-dimensional lattice as a guide to facilitate macro-molecular crystallization [12]. Unfortunately, the con-struction of such a lattice by means of the conceptsdeveloped for one- and two-dimensional structures provedto be an elusive task for decades. Recently, however,Seeman and co-workers reported the structure of acontinuous DNA three-dimensional lattice held togetherby non-Watson–Crick interactions [46]. The same designcould be used to generate structures with varying latticedimensions and, thus, in the future serve as the prototypeof a DNA molecular sieve or scaffold for the orderedinclusion of a variety of ‘guest’ molecules.

Time dimensionality

As summarized above, an ongoing effort is devoted toextending the control exerted over the self-assemblyprocess of DNA structures to as many dimensions aspossible; in some instances this includes time as one of thedimensions. Thus, the objective is to achieve controlledmotion of matter on the molecular scale, where the resultcan be a change in the shape or size of the construct.

Many nanosized DNA constructs that are capable of atriggered change in their shape have been reported[47,48]. A variety of different principles are used to obtainmovement in these constructs, including DNA confor-mational transitions [49–52], strand-displacement equili-bria [18,23,53–58] and protein binding [59]. Motion of theconstruct is obtained either in direct response to a specific,externally provided stimulus or is autonomous [56,60–62].

The main advantage of DNA-based devices over thoseobtained with different chemical compounds is that thehigh sequence-specificity of the various types of DNAhybridization permits the design of information-depen-dent mechanisms for the actuation of the device, thusenabling simultaneous control of different devices in thesame environment or control of different functionalities ofthe same device [47].

Given that objects that can modify their shape inresponse to a specific external stimulus are, in principle,capable of functional use, it has been proposed that DNAmolecular constructs can be employed as devices [48].Proposed applications of DNA molecular devices includesuch diverse fields as materials science, nanoelectronics,biosensors, chemical synthesis [63] and moleculartherapy. For instance, the ability to not only control thenanoscale assembly of matter but also to dynamically alterits structure could lead to the development of smartmaterials, capable of modifying their characteristics inresponse to specific stimuli. It is possible to envision datastorage and processing technologies in which the infor-mation bits are defined by the state of single nanoparticlesor molecules, and DNA nanodevices used in this contextwould have the advantage of being individually addres-sable thanks to their intrinsic informational content.


In addition to changes in shape, changes in the sizes ofDNA nanoconstructs can also be implemented. Forexample, the so called ‘hybridization chain-reaction’ [64]can be exploited to obtain a triggered self-assembly ofDNA nanostructures. Briefly, it is possible to storepotential energy in locked conformations, such as loopsthat are kinetically stable at room temperature, over along time scale, and then unlock them using a chainreaction of successive hybridizations, initiated by acatalyst strand of nucleic acid. In the reaction, all theloops are opened one at a time and incorporated into agrowing nanostructure by hybridization.

A matter of hierarchy

Nature can form large and complex functional aggregatesfrom elementary building blocks that are often orders ofmagnitude smaller. However, the huge gap between thebasic components and the complete assembly is seldomcrossed in just one leap. Subunits combine into higher-order constructs that will, in turn, serve as the basiccomponents of a next higher-order assembly until the finallevel of architecture and functionality is reached. In thecell, for example, nucleic acids are synthesized and laterorganized into progressively higher-order structures up tothe chromatin and chromosome level. Such organization ismade possible by several different hierarchical inter-actions among DNA and several classes of proteins.

It is easy to recognize the levels of hierarchy inherentlypresent in the design of most of the DNA nano-assembliesdescribed above. The lowest level is represented by themost basic components – the synthetic oligonucleotidesfundamental to the formation of the desired structure. Thenext, and in some cases the last, hierarchical level is thatof an individual supra-molecular object. These objectsusually constitute oligonucleotides kept together by thepairing of relatively long stretches of bases (typically O10nucleotides long). A further level of hierarchy, if present, isthe combination of the objects into a larger super-structure. Typically, the constituent sub-structures arereciprocally bound by shorter cohesive sticky ends, in therange of 4–7 nucleotides-long [65], or other types ofreversible interactions. These interactions do not disruptthe lower, pre-existing, levels; on the contrary, they needthis structural integrity to be able to settle. Successivehierarchical levels are reached when discrete aggregates,formed at the previous level, merge into a new structure orwhen the obtained structures are decorated withfunctional elements of a different chemical nature.

The role of hierarchy during the self-assembly

The preparation of even the most complex DNA structurescan, in principle, be performed in a single step. This can bedone by mixing all the constituent oligonucleotides at hightemperature and then slowly cooling the mix in a near-equilibrium regime to maximize the number of inter-actions, thus converging through spontaneous self-assembly into the planned structure. However, it isprobable that there might be an inherent complexitythreshold in the successful self-assembly of a ‘one-pot’ mixof many oligonucleotides. The ruggedness of the energylandscape governing such assembly increases with the


(a)

(b)

(c)

Figure 3. A scheme for the possible stepwise assembly of DNA parallelograms

arrays. Three hierarchical levels are depicted here: (a) single-stranded constituent

oligonucleotides; (b) individual parallelograms; and (c) parallelogram-based

superstructure. The colored stripes represent sequences, whereby stripes of

matching color on different oligonucleotides are complementary sequences.

Rounded rectangles represent physically separated vessels, in which the

components are assembled during each step. Notice how the one-pot mixing of

the oligonucleotides would not have resulted exclusively in the desired assembly.

More generally, a system could be constituted by N different structural hierarchic

levels (named L(1),.,L(N)). The structures in a given level L(n) are completely stable

(i.e. functionally acting as indivisible ‘monomers’) in a temperature range that is

higher than that of the structures of level L(nC1) and not overlapping it: L(n)

structures are effectively polymers, comprising several L(nK1) monomeric struc-

tures. The assembly of the final L(N) structure is obtained by the mixing of the L(n)

monomers, individually synthesized in separate vessels, and the successive

decrease in temperature to the L(nC1) stability region until the final hierarchic

level is assembled.


number of oligonucleotides involved. Because the numberof possible interactions increases exponentially with thenumber of oligonucleotides, so the time required for ablueprint-perfect assembly should increase accordingly.During this time, as the temperature decreases, thesystem has to sample all the possible interactions insearch of the most stable ones at each temperature; soon,this becomes an impractically long time. Consequently,during the assembly of a large number of oligonucleotides,kinetic trapping events will occur that will inevitablydrive the formation of a collection of unwanted structuresif the assembly is conducted in a manageable time span.

To reach a level of complexity unattainable by simpleone-pot methods, a stepwise procedure can be adopted.This strategy must be based on the design of structureswith different, non-overlapping ranges of thermal stabilitycorresponding to different hierarchic levels. Each sub-structure within the same level is assembled in separatevessels then brought into contact with the others and


finally cooled to a temperature that stabilizes the higher-level assembly (Figure 3).

During each step, only the sequences actually directingthe assembly at that level (e.g. the appropriate stickyends) are relevant to the process, whereas the sequencesalready included in the lower level (higher stability)structures are not disassembled. The result is thatstructures of the same hierarchic level can have almostidentical sequences (with the exception of the sticky ends)because they are assembled separately and then neverdisassembled. A few examples of this multi-pot strategyhave been already implemented [66,67].

The practical limit of this approach has not beenassessed but it could reasonably be reached when thelevel of structures gets big enough not to diffuse efficientlyand find partner constructs belonging to the samehierarchy level, or when the number of levels is so highthat it is almost impossible to obtain perfect segregation ofthermal stability ranges between contiguoushierarchic levels.

Conclusion and perspectives

DNA architectures are an extremely versatile method oforganizing matter on the nanoscale. The information-driven self-assembly of oligonucleotides can be used todesign and build nanostructures of almost any desiredshape and complexity.

Two parallel trends of development are currently activein this field. One trend constantly tries to expand thelibrary of DNA motifs and nanoarchitectures, ultimatelyaiming at the continuous control of nano-sized objects inboth space and time. For this to occur, architectures with afully programmable three-dimensional geometricaldimensionality, and retaining all the features so farimplemented with only one- and two-dimensional struc-tures, must be achieved. Concurrently, an ongoing effort isdevoted to obtaining functional capabilities using theexisting DNA structures. Given that the functionalcharacteristics often are conferred by molecular speciesdifferent than DNA, a stepwise, hierarchic type ofassembly is necessary to obtain plausible structures witha high degree of complexity. Some of the applicationsforeseen for DNA nanostructures will require theirimmobilization on a solid substrate, whereby the specificinteraction properties between DNA and the substratecould be used as an additional tool towards the design ofcomplex structures. As an example, base-sequence-specific interactions could orient nanostructures onsurfaces so that they expose only some of their parts tothe environment, as we have evidenced, recently, forcurved DNA [68].

The progress achieved in the field of DNA nanoarchi-tectures in the past ten years is amazing but even greaterchallenges await the scientific community in the nextfew years.

Acknowledgements

The authors wish to acknowledge support from EUROCORES-SONSprogram BIONICS through funds from the Italian National ResearchCouncil (CNR), FISR D.M. 16/10/20–1999, EU FP6-STREP programNMP4-CT-2004–013775 NUCAN, Progetto Pluriennale 2004



Dipartimento di Biochimica, Universita di Bologna and FIRB ProgettoRBLA03ER38_001 (Lab. Naz Nanotech. per Genomica and Post-Gen).

References

1 Hoffmann, H. (2002) Nanostructured Materials, Springer2 Samorı, B. and Zuccheri, G. (2004) DNA codes for nanoscience. Angew.

Chem. Int. Ed. Engl. 44, 1166–11813 Mirkin, C.A. et al. (1996) A DNA-based method for rationally

assembling nanoparticles into macroscopic materials. Nature 382,607–609

4 Niemeyer, C.M. (2000) Self-assembled nanostructures based on DNA:towards the development of nanobiotechnology. Curr. Opin. Chem.Biol. 4, 609–618

5 Park, S.J. et al. (2001) Directed assembly of periodic materials fromprotein and oligonucleotide-modified nanoparticle building blocks.Angew. Chem. Int. Ed. Engl. 40, 2909–2912

6 Williams, K.A. et al. (2002) Nanotechnology: carbon nanotubes withDNA recognition. Nature 420, 761

7 Yan, H. et al. (2003) DNA-templated self-assembly of protein arraysand highly conductive nanowires. Science 301, 1882–1884

8 Katz, E. and Willner, I. (2004) Integrated nanoparticle-biomoleculehybrid systems. Angew. Chem. Int. Ed. Engl. 43, 6042–6108

9 Niemeyer, C.M. (2004) Semi-synthetic DNA–protein conjugates: noveltools in analytics andnanobiotechnology.Biochem.Soc.Trans. 32, 51–53

10 Singh, R. et al. (2005) Binding and condensation of plasmid DNA ontofunctionalized carbon nanotubes: toward the construction of nano-tube-based gene delivery vectors. J. Am. Chem. Soc. 127, 4388–4396

11 Zuccheri, G. et al. (2005) The tube or the helix? this is the question:towards the fully controlled DNA-directed assembly of carbonnanotubes. Small 1, 590–592

12 Seeman, N.C. (1982) Nucleic acid junctions and lattices. J. Theor. Biol.99, 237–247

13 Kallenbach, N.R. et al. (1983) An immobile nucleic acid junctionconstructed from oligonucleotides. Nature 305, 829–831

14 Seeman, N.C. (1998) DNA nanotechnology: novel DNA constructions.Annu. Rev. Biophys. Biomol. Struct. 27, 225–248

15 Seeman, N.C. and Lukeman, P.S. (2005) Nucleic acids nanostructures:bottom-up control of geometry on the nanoscale. Rep. Prog. Phys. 68,237–270

16 Bustamante, C. et al. (1994) Entropic elasticity of lambda-phage DNA.Science 265, 1599–1600

17 LaBean, T.H. et al. (2000) Construction, analysis, ligation, and self-assembly of DNA triple crossover complexes. J. Am. Chem. Soc. 122,1848–1860

18 Sherman, W.B. and Seeman, N.C. (2004) A precisely controlled DNAbiped walking device. Nano Lett. 4, 1203–1207

19 Seeman, N.C. (1991) Construction of three-dimensional stick figuresfrom branched DNA. DNA Cell Biol. 10, 475–486

20 Liu, D. et al. (2004) Tensegrity: construction of rigid DNA triangleswith flexible four-arm DNA junctions. J. Am. Chem. Soc. 126,2324–2325

21 Goodman, R.P. et al. (2004) The single-step synthesis of a DNAtetrahedron. Chem. Commun. 12, 1372–1373

22 Shih, W.M. et al. (2004) A 1.7-kilobase single-stranded DNA that foldsinto a nanoscale octahedron. Nature 427, 618–621

23 Feng, L. et al. (2003) A two-state DNA lattice switched by DNAnanoactuator. Angew. Chem. Int. Ed. Engl. 42, 4342–4346

24 Mao, C. et al. (1999) Designed two-dimensional DNA junction arraysvisualized by atomic force microscopy. J. Am. Chem. Soc. 121,5437–5443

25 Fu, T.J. and Seeman, N.C. (1993) DNA double-crossover molecules.Biochemistry 32, 3211–3220

26 Li, X. et al. (1996) Antiparallel DNA double crossover molecules ascomponents for nanoconstruction. J. Am. Chem. Soc. 118, 6131–6140

27 Seeman, N.C. (2003) DNA in a material world. Nature 421, 427–43128 Seeman, N.C. (2003) Biochemistry and structural DNA nanotechnol-

ogy: an evolving symbiotic relationship. Biochemistry 42, 7259–726929 Mathieu, F. et al. (2005) Six-helix bundles designed from DNA. Nano

Lett. 5, 661–66530 Adleman, L.M. (1994) Molecular computation of solutions to combi-

natorial problems. Science 266, 1021–102431 Winfree, E. (1996) On the computational power of DNA self-assembly

and ligation. In DNA Based Computers: DIMACS Workshop


(Lipton, R.J. and Baum, E.B., eds), pp. 199–221, American Math-ematical Society

32 Roweis, S. et al. (1998) A sticker-based model for DNA computation.J. Comput. Biol. 5, 615–629

33 Mao, C. et al. (2000) Logical computation using algorithmic self-assembly of DNA triple-crossover molecules. Nature 407, 493–496

34 Gibbons, A. et al. (1997) DNA computing. Curr. Opin. Biotechnol. 8,103–106

35 Winfree, E. et al. (1998) Design and self-assembly of two-dimensionalDNA crystals. Nature 394, 539–544

36 Park, S.H. et al. (2005) Three-helix bundle DNA tiles self-assembleinto 2D lattice or 1D templates for silver nanowires. Nano Lett. 5,693–696

37 Wei, B. and Mi, Y. (2005) A new triple crossover triangle (TXT) motiffor DNA self-assembly. Biomacromolecules 6, 2528–2532

38 Ding, B. et al. (2004) Pseudohexagonal 2D DNA crystals from doublecrossover cohesion. J. Am. Chem. Soc. 126, 10230–10231

39 Park, S.H. et al. (2005) Programmable DNA self-assemblies fornanoscale organization of ligands and proteins. Nano Lett. 5, 729–733

40 Wang, H. (1961) Proving theorems by pattern recognition II. BellSystem Technical Journal 40, 1–42

41 Rothemund, P.W. et al. (2004) Algorithmic self-assembly of DNASierpinski triangles. PLoS Biol. 2, e424

42 Winfree, E. Self-healing tile sets. Nanotechnology: Science andComputation (in press)

43 Rothemund, P.W. et al. (2004) Design and characterization ofprogrammable DNA nanotubes. J. Am. Chem. Soc. 126, 16344–16352

44 Mitchell, J.C. et al. (2004) Self-assembly of chiral DNA nanotubes.J. Am. Chem. Soc. 126, 16342–16343

45 Ekani-Nkodo, A. et al. (2004) Joining and scission in the self-assemblyof nanotubes from DNA tiles. Phys. Rev. Lett. 93, 268301

46 Paukstelis, P.J. et al. (2004) Crystal structure of a continuous three-dimensional DNA lattice. Chem. Biol. 11, 1119–1126

47 Seeman, N.C. (2005) From genes to machines: DNA nanomechanicaldevices. Trends Biochem. Sci. 30, 119–125

48 Niemeyer, C.M. and Adler, M. (2002) Nanomechanical devices basedon DNA. Angew. Chem. Int. Ed. Engl. 41, 3779–3783

49 Brucale, M. et al. (2005) The dynamic properties of an intramoleculartransition from DNA duplex to cytosine–thymine motif triplex. Org.Biomol. Chem. 3, 575–577

50 Chen, Y. et al. (2004) A DNA nanomachine based on a duplex–triplextransition. Angew. Chem. Int. Ed. Engl. 43, 5335–5338

51 Mao, C. et al. (1999) A nanomechanical device based on the B–Ztransition of DNA. Nature 397, 144–146

52 Yang, X. et al. (1998) Torsional control of double-stranded DNA branchmigration. Biopolymers 45, 69–83

53 Yurke, B. et al. (2000) A DNA-fuelled molecular machine made ofDNA. Nature 406, 605–608

54 Li, J.J. and Tan, W. (2002) A single DNA molecule nanomotor. NanoLett. 2, 315–318

55 Yan, H. et al. (2002) A robust DNA mechanical device controlled byhybridization topology. Nature 415, 62–65

56 Turberfield, A.J. et al. (2003) DNA fuel for free-running nanoma-chines. Phys. Rev. Lett. 90, 118102

57 Shin, J.S. and Pierce, N.A. (2004) A synthetic DNA walker formolecular transport. J. Am. Chem. Soc. 126, 10834–10835

58 Tian, Y. and Mao, C. (2004) Molecular gears: a pair of DNA circlescontinuously rolls against each other. J. Am. Chem. Soc. 126,11410–11411

59 Shen, W. et al. (2004) A protein-driven DNA device that measures theexcess binding energy of proteins that distort DNA. Angew. Chem. Int.Ed. Engl. 43, 4750–4752

60 Yin, P. et al. (2004) A unidirectional DNA walker that movesautonomously along a track. Angew. Chem. Int. Ed. Engl. 43,4906–4911

61 Chen, Y. et al. (2004) An autonomous DNA nanomotor powered by aDNA enzyme. Angew. Chem. Int. Ed. Engl. 43, 3554–3557

62 Chen, Y. and Mao, C. (2004) Putting a brake on an autonomous DNAnanomotor. J. Am. Chem. Soc. 126, 8626–8627

63 Chen, Y. and Mao, C. (2004) Reprogramming DNA-directed reactionson the basis of a DNA conformational change. J. Am. Chem. Soc. 126,13240–13241



64 Dirks, R.M. and Pierce, N.A. (2004) Triggered amplification byhybridization chain reaction. Proc. Natl. Acad. Sci. U. S. A. 101,15275–15278

65 Qiu, H. et al. (1997) A DNA decamer with a sticky end: the crystalstructure of d-CGACGATCGT. J. Mol. Biol. 267, 881–898

66 Chworos, A. et al. (2004) Building programmable jigsaw puzzles withRNA. Science 306, 2068–2072

67 Liu, Y. et al. Self-assembly of symmetric finite-size DNA nanoarrays.J. Am. Chem. Soc. 127, 17140–17141

68 Sampaolese, B. et al. (2002) Recognition of the DNA sequence by aninorganic crystal surface. Proc. Natl. Acad. Sci. U. S. A. 99,13566–13570

69 Demidov, V.V. and Frank-Kamenetskii, M.D. (2004) Two sides of thecoin: affinity and specificity of nucleic acid interactions. TrendsBiochem. Sci. 29, 62–71

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70 Feldkamp, U. et al. (2003) Software tools for DNA sequence design.Genetic Programming and Evolvable Machines 4, 153–171

71 Brenneman, A. and Condon, A. (2002) Strand design for biomolecularcomputation. Theor. Comput. Sci. 287, 39–58

72 He, Y. et al. (2005) Sequence symmetry as a tool for designing DNAnanostructures. Angewandte Chemie 44, 6694–6696

73 Dirks, R.M. et al. (2004) Paradigms for computational nucleic aciddesign. Nucleic Acids Res. 32, 1392–1403

74 Roweis, S. and Winfree, E. (1999) On the reduction of errors in DNAcomputation. J. Comput. Biol. 6, 65–75

75 Winfree, E. and Bekbolatov, R. (2003) Proofreading tile sets: logicalerror correction for algorithmic self-assembly. In DNA BasedComputers 9 (Chen, J. and Reif, J., eds), pp. 126–144, Springer–Verlag

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