nanorobots and devlivery of pharmaceutics

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Jinglin Fu and Hao Yan are in the Department

of Chemistry and Biochemistry and the

Biodesign Institute at Arizona State University,

Tempe, Arizona, USA.e-mail: [email protected]

to bind to cell-surface receptors and inhibit the

growth of the target cells. Similarly, an increasein T cell activation was induced by a nanobot

loaded with Fab fragments specific for humanCD3 and flagellin. Additional measurements

that quantify the AND gates sensitivity to theinputs, the rate of erroneous nanobot activation

and the correlation between the number of acti-vated nanobots with successfully modified cell

signaling pathways would be required to fullyevaluate nanobot performance.

The aim of smart drug-delivery systems isto administer smaller drug doses to patients

while offering improved therapeutic efficiencyand fewer side effects compared with conven-

tional drug delivery methods. Notable recent

developments have included systems based onliposomes, polymersomes, micelles, nanopar-

ticles and antibodies9. Yet these approaches donot provide the wide range of design modular-

ity and structural programmability that DNAnanotechnology affords.

Much work remains before the approach ofDouglas et al.1 could be used for drug delivery

in vivo. For example, nanobots might not bestable in the presence of nucleases and other

enzymes in the blood. Increased resistance todegradation may be achievable by methods

such as chemical cross-linking of selected DNAstrands or the use of peptide nucleic acids or

locked nucleic acids. Similarly, aptamer-encoded locks may lose specificity and effi-

ciency in protein-rich serum.In addition, delivery into cells is required for

broad application of a drug-delivery system

consists of two halves connected by a switchable

hinge (Fig. 1). Two distinct DNA aptamers areused to close and lock the DNA barrel. Because

each of the aptamers specifically binds differentprotein antigens, they form an AND logic gate

that requires the presence of two protein targetsto be activated. When both aptamers bind their

targets, a conformational change in the barrelreleases the cargo. Thus, the aptamer-encoded

lock functions as a sense-compute-actuatemechanism that could in principle be deployed

to trigger a specific therapeutic response.In a first set of experiments, Douglas et al.1

used their aptamer-gated DNA nanobots todetect selected biomarkers (such as platelet-derived growth factor or protein tyrosine

kinase 7) expressed on the surface of leukemiacells. Several combinations of three aptamers

that recognize different surface antigens wereincorporated into the nanobot. To character-

ize the system, the authors used fluorescentlylabeled Fab antibody fragments as the payload;

the nanobots showed highly specific binding tothe cells that displayed the correct combination

of surface antigens, even in mixed populationsof whole-blood leukocytes.

Next, the nanobots were used to activatesignaling pathways in target cells. The authors

loaded the nanobots with Fab antibody frag-ments known to bind human CD33 and human

CDw328 and induce growth arrest in leukemiccells. Upon recognition of the surface antigen

PDGF on cells from a patient with aggressivelymphocytic NK-type leukemia, the barrel

structure opened, allowing the antibody payload

In the 1966 film Fantastic Voyage, a shrunken

submarine is injected into a mans circu-latory system to find and destroy a life-

threatening blood clot in his brain. Scientistshave embraced this science-fictional concept

in the form of research on targeted or smartdrug delivery: nano- or microscale systems

that can discriminate between healthy anddiseased cells and selectively deliver medici-

nal payloads. In a recent paper in Science,Douglas et al.1 describe a nanoscale DNA cagethat releases Fab antibody fragments in the pre-

sence of target cells in vitro. Although the util-

ity of this approach for targeted drug deliveryin vivo remains unclear, the study shows howDNA nanostructures can be combined with

rudimentary robotic functions to induce cellsignaling pathways.

The work of Douglas et al.1 builds onadvances in DNA nanotechnology that

allowed the construction of sophisticatedmultidimensional structures2 and of devices

capable of robot-like functions such asmolecular sensing3, logical computation4 and

activation5. The authors produced their nano-structures using DNA origami, an approach

for creating two- or three-dimensionalnanoscale shapes by folding a long single-

stranded DNA molecule along a predeter-mined path using oligonucleotide staples6.

Nanostructures made by DNA origami can bedesigned to present addressable surface fea-

tures at which other particles or moleculescan be precisely positioned2. This capabilityhas been used to generate simple two-

dimensional structures that direct the motionof robots constructed from DNAzymes7.

Several years ago, a report describing athree-dimensional DNA box with a lid that

can be opened by a DNA key showed that

DNA-origami structures are capable of actingas dynamic containers8.

Douglas et al.1 extended this line of research

by designing a box that releases its cargo in thepresence of a specific configuration of target

molecules. The barrel-shaped device, whichthe authors call a nanorobot or nanobot,

Controlled drug release by a nanorobot

Jinglin Fu & Hao Yan

A tiny, locked box made of DNA opens up to release drug molecules in the presence of target cells.

Figure 1 DNA nanobot for targeted drug delery. To fabrcate the nanobot by DNA orgam, a long

sngle-stranded DNA scaffold s folded nto the shape of a hexagonal barrel by short olgonucleotde

staple strands. The assembled nanobot conssts of to aptamer-encoded locks, a barrel-shaped body

and a bound molecular cargo. The use of to dfferent aptamers that unlock hen exposed to to

antgens results n an AND logc gate, meanng that the nanobot opens n the presence of the correct

combnaton of antgen keys. The molecular payload s then released to bnd to target cells and actate

sgnalng pathays.

Aptamerlock

Hexagonalbarrel

Single-strandedbacteriophage DNA

Origamiself-assembly

Short staplestrands

DNAnanorobot

Antigens unlockaptamers

Exposed payloadtriggers signalingresponses in cells

Payload

K a t i e v i c a r i

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given the many potential intracellular targets,

and large DNA nanostructures are believed tohave difficulty penetrating biological mem-

branes. The display of amphiphilic moleculesor cell-penetrating peptides on the surface of

nanobots might facilitate tissue penetration andcellular uptake.

Another concern is that DNA-origami con-tainers, which can require nearly 200 unique

oligonucleotides, are structurally more com-plicated than liposomes and many other drug

carriers. For large-scale production, it may benecessary to minimize the number of constitu-

ent strands and reduce the complexity of thedesign, perhaps to even a single DNA strand10.

Despite these challenges, it is conceivable

that DNA nanobots could one day be used toinfluence the gene expression or meta-

bolic pathways of target cells11. As with anydrug-delivery strategy, improved understanding

of systems biology in health and disease

will be crucial for the ultimate success ofthis approach.

COMPETING FINANCIAL INTERESTS

The authors declare no competing financial interests.

1. Douglas, S.M., Bachelet, i. & Church, G.M. Science

335, 831834 (2012).

2. Pnhero, A.v., Han, D., Shh, w.M. & Yan, H. Nat.Nanotechnol. 6, 763772 (2011).

3. Cho, E.J., Lee, J.w. & Ellngton, A.D. Annu. Rev. Anal.

Chem.2, 241264 (2009).

4. Qan, L. & wnfree, E. Science 332, 11961201

(2011).

5. Benenson, Y., Gl, B., Ben-Dor, U., Adar, R. & Shapro, E.

Nature429, 423429 (2004).

6. Rothemund, P.w.K. Nature440, 297302 (2006).

7. Lund, K. et al.Nature465, 206210 (2010).

8. Andersen, E.S. et al.Nature459, 7376 (2009).

9. Lammers, T., Ame, S., Hennnk, w.E., Storm, S. &

Kesslng, F. Acc. Chem. Res.44, 10291038 (2011).

10. Shh, w.M., Quspe, J.D. & Joyce, G.F. Nature427,

618621 (2004).

11. Delebecque, C.J., Lndner, A.B., Sler, P.A. & Aldaye, F.A.

Science333, 470474 (2011).

Carlos Caldas is in the Department of Oncology

at the University of Cambridge and at Cancer

Research UK, Cambridge Research Institute,

Cambridge, UK.

e-mail: [email protected]

isolated the cells using an inverted micro-

scope and microcapillary pipetting followedby whole-genome amplification (WGA)

based on multiple-displacement amplifica-tion with the 29 enzyme, which allowed

linear amplification of the complete genome.WGA DNA was then analyzed by mas-

sively parallel sequencing with Illuminainstruments. The authors developed and vali-

dated the method with two single cells froma lymphoblastoid cell line isolated from the

individual whose DNA was used for the firstAsian diploid genome sequenced.This workshowed that whole-genome sequencing of

WGA DNA has acceptable error rates, and itprovided a baseline for subsequent studies of

single cells from cancer samples using onlyexome sequencing.

Next, Hou et al.2 sequenced the exomes of58 single cancer cells from an individual with

essential thrombocythemia, a myeloprolifera-

tive neoplasm, to a mean depth of 30. Usingmutation-calling algorithms, which wereexperimentally validated both by comparing

all single-cell somatic variants to those identi-fied in whole essential-thrombocythemia tissue

sequencing and by PCR-Sanger sequencing of30 randomly selected mutations, the authors

identified 712 somatic variants, of which171 coding variants were further assessed.

Seventy-eight of these 171 coding somaticmutations (in a total of 71 genes) were non-

synonymous. A population-genetics analysis ofthese data revealed the monoclonal origin of

essential-thrombocythemia cells in this patient.Furthermore, a driver-gene prediction model

identified eight genes as the ones with thehighest likelihood of being involved in the

neoplastic initiation and/or progression ofessential thrombocythemia.

In a second study from the same labora-tory, Xu et al.3 applied the single-cell sequenc-ing method to analyze the exomes of 25 single

cells from a renal cell carcinoma20 from thetumor and 5 from adjacent normal tissue.

The sequencing data revealed 260 codingsomatic mutations. Principal component

analysis showed that three of the single cancer

cells clustered tightly with the five normal singlecells, which the authors took to indicate thatthese were actually healthy cells admixed within

the tumor. The remaining 17 single cancercells had 229 somatic mutations, and these

mutations were used to determine the allelicfrequency at the 229 nucleotide positions. This

analysis revealed two distinct peaks, one with afrequency range of 05% and the other with a

frequency range of 1520%. Thus, not only wasthere significant intratumoral heterogeneity, but

alsonotablythere were no dominant clonesidentified in the cancer tissue. In other words,

In previous work, single-cell analysis hasbeen used to define the clonal architecture

of acute lymphoblastic leukemia5 by multi-plex fluorescence in situ hybridization and to

define the tumor evolution of breast cancers6

using next-generation sequencing to quantifygenomic copy number within individual nuclei.

In both cases, the common progenitor clone ofthe diverse subclones was marked and iden-

tified by genome aberrations (chromosomaltranslocations and/or copy-number altera-

tions). The outstanding question was whethersomatic variants would reveal a similar clonal

pattern at the sequence level. Understanding

this issue in detail will have profound clinicalimplications. There are now several targetedtherapies directed against cancer genes that are

mutated (such as BRAFand EGFR) or ampli-fied (such as HER2), which some have called

actionable mutations. Tumor heterogeneityposes a considerable challenge to such thera-

pies. For example, how will clinicians decidewhether a targeted therapy is indicated if the

mutation is present in only a minor proportionof cancer cells?

Hou et al.2 developed a novel method forgenome sequencing of single cells. First, they

In 1976, Peter Nowell proposed a model ofcancer as an evolutionary process in which a

population of cells descended from a single cellof origin, or clone, acquires successive somatic

mutations that allow sequential selection offitter subclonesan evolution that underlies

tumor progression, metastasis and resistanceto therapy1 (Fig. 1). Nearly 36 years later,this model has been analyzed at the single-

nucleotide level in studies published in Cell2,3and in the New England Journal of Medicine4.

Hou et al.2 and Xu et al.3 carried out exomesequencing on single cells from an essential

thrombocythemia tumor and a kidney tumor,

respectively, whereas Gerlinger et al.4 analyzedexome-sequencing data, in combination withchromosome-aberration and ploidy data, from

multiple samples of renal carcinomas andassociated metastases4. The three studies have

confirmed the clonal heterogeneity of primarytumors and metastases at the sequence level.

Cancer sequencing unravels clonalevolution

Carlos Caldas

Characterization of tumor heterogeneity at the sequence level presents

new challenges and opportunities for targeted therapies.

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