DNA origami is a powerful method for fabricating precise nanoscale objects by programming the self-assembly of DNA molecules. Here, we describe how DNA origami can be utilized to design a robotic robot capable of sensing biological cues and responding by shape shifting, subsequently relayed to a desired effect.
Nucleic acids are astonishingly versatile. In addition to their natural role as storage medium for biological information1, they can be utilized in parallel computing2,3 , recognize and bind molecular or cellular targets4,5 , catalyze chemical reactions6,7 , and generate calculated responses in a biological system8,9. Importantly, nucleic acids can be programmed to self-assemble into 2D and 3D structures10-12, enabling the integration of all these remarkable features in a single robot linking the sensing of biological cues to a preset response in order to exert a desired effect.
Creating shapes from nucleic acids was first proposed by Seeman13, and several variations on this theme have since been realized using various techniques11,12,14,15 . However, the most significant is perhaps the one proposed by Rothemund, termed scaffolded DNA origami16. In this technique, the folding of a long (>7,000 bases) single-stranded DNA ‘scaffold’ is directed to a desired shape by hundreds of short complementary strands termed ‘staples’. Folding is carried out by temperature annealing ramp. This technique was successfully demonstrated in the creation of a diverse array of 2D shapes with remarkable precision and robustness. DNA origami was later extended to 3D as well17,18 .
The current paper will focus on the caDNAno 2.0 software19 developed by Douglas and colleagues. caDNAno is a robust, user-friendly CAD tool enabling the design of 2D and 3D DNA origami shapes with versatile features. The design process relies on a systematic and accurate abstraction scheme for DNA structures, making it relatively straightforward and efficient.
In this paper we demonstrate the design of a DNA origami nanorobot that has been recently described20. This robot is ‘robotic’ in the sense that it links sensing to actuation, in order to perform a task. We explain how various sensing schemes can be integrated into the structure, and how this can be relayed to a desired effect. Finally we use Cando21 to simulate the mechanical properties of the designed shape. The concept we discuss can be adapted to multiple tasks and settings.
The robot we will design in this paper responds to a protein P by making a cargo C available to bind to receptors on the surface of a chosen target cell. The robot is shown in Figure 1. C may be a receptor-blocking drug; a growth factor etc., and a way to chemically link it to a DNA oligonucleotide must be available that does not destroy its function. The robot has two states. When inactive, DNA gates on the two external ‘lips’ are hybridized, making sure the robot remains closed such that any cargo loaded within it is securely sequestered. In the presence of protein P, the gates open by either one of several mechanisms (discussed below) allowing the robot to open and expose the cargo. When designing the structure, consider that the robot has to be flexible enough to close onto itself in the closed state, and spring to the open state when the gates enable it to do so. Modeling the behavior of a DNA structure integrating thermodynamic and mechanical components is difficult, and the actual object might require some iterative improvement. Nevertheless, here we focus on the design process using a general working model, which can be built upon.
Note:
For a more comprehensive understanding of the process of DNA origami design and folding, we highly recommend reading the original caDNAno paper by Douglas and colleagues19 which explains the abstract representation of DNA in the design interface and how it relates to the actual molecular structure of a 3D DNA shape. This paper is accompanied by two video tutorials describing the caDNAno representation and interface in a very clear way. Additionally, we recommend reading the more recent paper by Dietz and colleagues describing many important aspects and detailed protocols of the folding process, including the Cando analysis tool21.
1. Download and Install caDNAno 2.0 and Autodesk Maya 2012
Note: Autodesk software is free for students and academic use. The instructions below include setting up an academic account at Autodesk.
2. Outline the Desired Shape and Scaffold Strand Path
3. Define Opening Mechanism Axes
The described robot opens in response to a defined biological input to expose its payload. Opening takes place in a shell-like manner, with two halves (helices 0-29 make up one half, helices 30-61 make up the second half) revolving around two axes. The axes are formed by crossovers between helices 29-30 and 61-0, which are the only crossovers between those halves and are positioned only in or close to the left edge of the grid. The right edge will contain the gate strands (discussed below).
4. Define Payload Attachment Sites
After we finish plotting the scaffold strand path, we need to define the payload attachment (loading) sites. Loading sites are in fact staple strands that extend out of their helices as single stranded ‘branches’. It is therefore important to define very precisely where along the helix this branching occurs, to make sure it extends to the desired direction. If we define staple extensions arbitrarily, loading sites might occur on the external side of the robot instead of the internal side.
To make sure a staple extends to a specific direction only, we plot an additional helix, which serves as guides for the directional branching of the staple from the main body. After extending the desired loading site staple, the guide helix is removed.
5. Add and Edit Staples
6. Create Loading Sites and Gates
7. Designing Gate Strands
The gate strands are the only strands, except for the axes, linking helices 29-30 and 61-0. In contrast to the axes, the gate strands are not crossovers. Rather, they hybridize to form a double stranded segment that serves as the sensor for the biological input of choice. Once the gate duplexes are displaced, the entire robot can entropically revolve around the axes and open.
8. Choose Scaffold Sequence
For example, if the scaffold strand needed to fold a small shape is ~1,600 bases long, which is significantly shorter than the preset sources in the dialog box, a custom sequence can be used as scaffold. Several sources can be considered. For example, the M13mp18 can be digested with a specific restriction enzyme that produces a fragment of the desired length. Designing such a source can be done at NebCutter (http://tools.neb.com/NEBcutter2/) by pasting the M13mp18 sequence (http://www.neb.com/nebecomm/tech_reference/restriction_enzymes/dna_sequences_maps.asp?#.UAygyzFWomR) in the NebCutter input window, and mapping restriction sites. Another option is to use pre-digested ssDNA, such as the phiX174 virion ssDNA HaeIII digest, available from New England Biolabs.
9. Export Staple Sequence as a Spreadsheet
10. Assign Gate and Loading Sequences
11. Simulate Results in CANDO
12. Order DNA and Fold the Robot
Once the design process is complete and CANDO analysis shows satisfactory prediction of the product, the staple strand list generated in sections 9-10 can be ordered. Typically, staple strands do not require particular purification; however, it is recommended that special purpose strands such as gates or loading sites be purified by HPLC.
The steps following DNA order, namely folding, purification and evaluation of product, including visualization of the folded structure by either atomic force microscopy (AFM) or transmission electron microscopy (TEM) are outside the scope of this paper, and can be found in previous reports17,18,20,21 . A TEM image of the robot designed here is brought as an example (Figure 27). Sample preparation and staining was carried out exactly as described elsewhere21.
Figures 1-25 are screenshots of the caDNAno 2.0 interface showing the design process step-by-step. The cross-section of the shape was first outlined (Figure 3), followed by automatic addition of scaffold strand fragments and completion of the entire scaffold path (Figure 7). Staple strands are automatically added (Figure 12), broken according to user-defined parameters (Figure 14), and manually edited to adapt the staples to the desired function of the device (Figures 15-18). Figures 23-24 describe how loading site and gate strands are added and edited. Finally, Figure 27 shows a TEM image of the model designed here.
Figure 1. A 3D model of the finished robot, designed by caDNAno 2.0 and generated by Autodesk Maya 2012.
Figure 2. A view of the caDNAno 2.0/Autodesk Maya 2012 design interface. Top panel: lattice panel for outlining the initial shape. Bottom panel: editing panel. Right panel: 3D model generator (see section 2.1). Click here to view larger figure.
Figure 3. Drawing the section of the shape on the top panel (see section 2.3).
Figure 4. The bottom (editing) panel of caDNAno 2.0. The orange vertical bar determines where along the grid editing actions will occur. The grey arrows on the top right corner are used to extend the grid to either side (see section 2.4).
Figure 5. A draft of the scaffold strand after the initial outline in the top panel (see section 2.5). Click here to view larger figure.
Figure 6. Selecting all the scaffold strand path edges and extending the path to the desired length (see section 2.7).
Figure 7. A general view of the bottom and right panels demonstrating how the 3D model changes in real time along with editing actions. Click here to view larger figure.
Figure 8. The blue bridge icons between helices denote the positions where scaffold crossovers are allowed (red icons refer to staple crossovers and are not yet shown, see section 2.9).
Figure 9. Creating new scaffold crossovers by clicking the bridge icons of choice (see section 2.10).
Figure 10. Creating an axis (a crossover a close as possible to the left side of the grid) between helices 29 and 30 (see section 3.2).
Figure 11. Adding helices that guide the branching of loading sites (see section 4.1).
Figure 12. The blueprint after the “AutoStaple” action. The staple colors in the bottom panel and the right panel are consistent (see section 5.1). Click here to view larger figure.
Figure 13. The “AutoBreak” dialogue box in which the user can define AutoBreak parameters (see section 5.2).
Figure 14. The blueprint after the “AutoBreak” action (see section 5.2). Click here to view larger figure.
Figure 15. Manual editing of staples I: locating staples that cross over from helix 29 and 30 and should be deleted.
Figure 16. Manual editing of staples II: deleting the bridges between the located staples.
Figure 17. Manual editing of staples III: seaming the nicks along fragmented staples (see section 5.5).
Figure 18. The entire gap between helices 29-30 showing no crossovers link the two (see section 5.5). Click here to view larger figure.
Figure 19. Manual editing of staples drawn in thick line (denoting they are either too short, too long or circular, see section 5.6).
Figure 20. Adding guide helices for loading site branching (see section 6.1). Click here to view larger figure.
Figure 21. Manual addition of staple strands to the guide helices, so branching points can be located (see section 6.2). Click here to view larger figure.
Figure 22. Introducing a loading site crossover to the robot chassis scaffold in a convenient location (one that requires minimal editing of chassis staples, see section 6.5).
Figure 23. View of the loading site staples as seen in the bottom panel after removing the guide helices, which are no longer necessary (see section 6.9).
Figure 24. Extending two staples, which are going to be used as gate strands, from helices 29 and 30. Note that the two strands face opposite directions, which is mandatory for the formation of the gate duplex (see section 7.4). Click here to view larger figure.
Figure 25. The scaffold sequence addition (“Seq” tool) dialogue box, allowing to choose either one of pre-defined scaffolds, or to insert a custom sequence (see section 8.1).
Figure 26. Results of CANDO analysis of the design described here. The simulation generates a .zip archive containing the various files that provide the requested information. Here the RMSF (root mean square fluctuation) files (.png) are depicted, showing a model of the design from 3 view angles, colored according to the key detailed in the accompanying file named “HeatMap4RMSF.txt”. In this case, minimum RMSF (bluest) is 1.03 nm, and 95% RMSF (redest) is 3.19 nm. The gradient of color across the model derives from the polarity of the robot (gates in ‘front’, axis in ‘back’) and the fact that there are no connecting staples along helices 29-30 and 61-0, causing the ‘front’ side to fluctuate more than the ‘back’ side.
Figure 27. TEM image of the robot designed in this article. Sample preparation and staining was carried out exactly as described elsewhere21.
DNA origami enables us to fabricate accurately defined objects with arbitrary features at the nanoscale. An important next step would be the integration of function into these designs. While many applications and challenges could be addressed with this technology, there is a particular interest in fabricating therapeutic and scientific robots from DNA origami, as these represent a natural milieu of DNA. DNA already interfaces with molecular machinery in cells as a genetic information storage medium. Interestingly, the folded DNA in a nanorobot or another machine can still serve as genetic information in addition to being a construction material, which can be relayed to the expression of a desired protein after the nanorobot disintegrates, as parts of a sequence of outputs.
In the example discussed in this paper, we use a restriction enzyme to operate the robot. However, additional mechanisms by which DNA robots can respond to inputs include the following.
Molecular recognition: we recently demonstrated aptamer-based gates for DNA robots that recognize protein molecules on the surface on target cells20. Aptamers can be selected in-vitro using methods such as SELEX23, outsourced from companies, or used from the aptamer database (http://aptamer.icmb.utexas.edu/). When aptamers are employed, it is important to consider that the strand complementary to the aptamer, which together forms the gate, can be designed to include mismatches, which will facilitate binding of the aptamer’s ligand and displacement of the complementary strand. While the mechanism allowing this is unknown, the sensitivity and specificity of an aptamer-based gate can be tuned by increasing or decreasing the % of mismatch between the two strands, to get either a very stringent but inefficient gate, or a fast but leaky one.
Enzymatic cleavage: for this, the gates should be designed such that they contain the substrate of that enzyme. For example, a small peptide substrate of a protease can be tethered from both sides to the gate, which will keep the robot closed in the absence of the enzyme.
Remote control: a potential approach that has not been applied to DNA machines is using a gold nanocrystal antenna in a high-frequency electromagnetic field to induce dsDNA melting24. This may provide a user-operated switch in addition to bio-responsive ones. Although DNA origami robots are relatively straightforward to design and make, they pose several technical challenges as a therapeutic platform. DNA is not an ideal material for drug delivery as it is highly vulnerable to cleavage by nucleases. Moreover, it might precipitate an immune response. A thorough study of the behavior of DNA origami objects in an organism is needed to define their fate and make sure they do not aggregate in tissues or integrate into the host genome.
In summary, we presented the use of caDNAno, a straightforward, robust CAD tool to designing DNA origami shapes. We hope to start seeing application-driven research in DNA origami, in areas such as therapeutics, energy, metamaterials, and education. In all these places, caDNAno is expected to have a significant impact on realizing the solutions. In the future, it might become an industrial and design standard, which can be replaced (or parts of which can) by any user because they are all compatible.
The authors have nothing to disclose.
The authors wish to thank S. Douglas for extremely valuable discussions and advice, and all the members of the Bachelet lab for helpful discussions and work. This work is supported by grants from the Faculty of Life Sciences and Institute of Nanotechnology & Advanced Materials at Bar-Ilan University.
Name of Reagent/Material | Company | Catalog Number | Comments |
Autodesk Maya 2012 | Autodesk | A student/academic account needs to be created first (see platform-specific instructions in http://cadnano.org) | |
caDNAno 2.0 (software) | (Open source) | Software for the design of DNA origami structures http://cadnano.org | |
Cando (webpage) | (Open source) | Webpage running a simulator of DNA origami shapes http://cando-dna-origami.org |