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Biochemical circuits made of rationally designed DNA molecules are proofs of concept for embedding control within complex molecular environments. They hold promise for transforming the current technologies in chemistry, biology, medicine and material science by introducing programmable and responsive behaviour to diverse molecular systems. As the transformative power of a technology depends on its accessibility, two main challenges are an automated design process and simple experimental procedures. Here we demonstrate the use of circuit design software, combined with the use of unpurified strands and simplified experimental procedures, for creating a complex DNA strand displacement circuit that consists of 78 distinct species. We develop a systematic procedure for overcoming the challenges involved in using unpurified DNA strands. We also develop a model that takes synthesis errors into consideration and semi-quantitatively reproduces the experimental data. Our methods now enable even novice researchers to successfully design and construct complex DNA strand displacement circuits., DNA circuits hold promise for advancing information-based molecular technologies, yet it is challenging to design and construct them in practice. Thubagere et al. build DNA strand displacement circuits using unpurified strands whose sequences are automatically generated from a user-friendly compiler.

INTRODUCTION Since the 1980s, the design and synthesis of molecular machines has been identified as a grand challenge for molecular engineering. Robots are an important type of molecular machine that automatically carry out complex nanomechanical tasks. DNA molecules are excellent materials for building molecular robots, because their geometric, thermodynamic, and kinetic properties are well understood and highly programmable. So far, the development of DNA robots has been limited to simple functions. Most DNA robots were designed to perform a single function: walking in a controlled direction. A few demonstrations included a second function combined with walking (for example, picking up nanoparticles or choosing a path at a junction). However, these relatively more complex functions were also more difficult to control, and the complexity of the tasks was limited to what the robot can perform within 3 to 12 steps. In addition, each robot design was tailored for a specific task, complicating efforts to develop new robots that perform new tasks by combining functions and mechanisms. RATIONALE The design and synthesis of molecular robots presents two critical challenges, those of modularity and algorithm simplicity, which have been transformative in other areas of molecular engineering. For example, simple and modular building blocks have been used for scaling up molecular information processing with DNA circuits. As in DNA circuits, simple building blocks for DNA robots could enable more complex nanomechanical tasks, whereas modularity could allow diverse new functions performed by robots using the same set of building blocks. RESULTS We demonstrate a DNA robot that performs a nanomechanical task substantially more sophisticated than previous work. We developed a simple algorithm and three modular building blocks for a DNA robot that performs autonomous cargo sorting. The robot explores a two-dimensional testing ground on the surface of DNA origami, picks up multiple cargos of two types that are initially at unordered locations, and delivers each type to a specified destination until all cargo molecules are sorted into two distinct piles. The robot is designed to perform a random walk without any energy supply. Exploiting this feature, a single robot can repeatedly sort multiple cargos. Localization on DNA origami allows for distinct cargo-sorting tasks to take place simultaneously in one test tube or for multiple robots to collectively perform the same task. On average, our robot performed approximately 300 steps while sorting the cargos. The number of steps is one to two magnitudes larger than the previously demonstrated DNA robots performing additional tasks while walking. Using exactly the same robot design, the system could be generalized to multiple types of cargos with arbitrary initial distributions, and to many instances of distinct tasks in parallel, whereas each task can be assigned a distinct number of robots depending on the difficulty of the task. CONCLUSION Using aptamers, antibodies, or direct conjugation, small chemicals, metal nanoparticles, and proteins could be transported as cargo molecules so that the cargo-sorting DNA robots could have potential applications in autonomous chemical synthesis, in manufacturing responsive molecular devices, and in programmable therapeutics. The building blocks developed in this work could also be used for diverse functions other than cargo sorting. For example, inspired by ant foraging, adding a new building block for leaving pheromone-like signals on a path, DNA robots could be programmed to find the shortest path and efficiently transport cargo molecules. With simple communication between the robots, they could perform even more sophisticated tasks. With more effort in developing modular and collective molecular robots, and with simple and systematic approaches, molecular robots could eventually be easily programmed like macroscopic robots, but working in microscopic environments.

The ability to assess the risks of human exposure to engineered nanomaterials requires fundamental understanding of the fate and potential cytotoxicity of nonbiodegradable nanoparticles, for instance, after oral uptake. In this study, we quantify the impact of nanoparticles with low chemical toxicity on the intestinal membrane in a human intestinal in vitro model. Differentiated human colorectal adenocarcinoma cells, Caco-2, were cultured on a permeable support where they form an epithelial monolayer separating an apical and basal compartment. This model system allows a systematic characterization of the effect of nanoparticles on the cell viability as a function of size, surface chemistry, concentration, and incubation time. We used polystyrene (PS) nanoparticles (20 and 40 nm diameter) with two different surface chemistries (carboxylic acid and amines). The experiments performed show a strong decrease in cell viability as a response to nanoparticle exposure. Incubation times ofor=4 h are sufficient to induce dramatic losses in cell viability after an additional induction period of 4-12 h. Mapping the temporospatial distribution of dead cells in the Caco-2 cell monolayer using optical microscopy reveals that the nanoparticles induce apoptosis in individual cells, which then propagate across the cell monolayer through a "bystander killing effect". Addition of catalase, which selectively decomposes hydrogen peroxide, leads to a significant decrease in apoptosis levels, indicating that hydrogen peroxide causes the spread of apoptosis across the monolayer. Our findings confirm that ingested nonbiodegradable nanoparticles represent a potential health risk due to their detrimental impact on the intestinal membrane by destroying their barrier protection capability over time.

Defined nanoparticle cluster arrays (NCAs) with total lateral dimensions of up to 25.4 microm x 25.4 microm have been fabricated on top of a 10 nm thin gold film using template-guided self-assembly. This approach provides precise control of the structural parameters in the arrays, allowing a systematic variation of the average number of nanoparticles in the clusters (n) and the edge-to-edge separation (Lambda) between 1 < n < 20 and 50 nm < or = Lambda < or = 1000 nm, respectively. Investigations of the Rayleigh scattering spectra and surface-enhanced Raman scattering (SERS) signal intensities as a function of n and Lambda reveal direct near-field coupling between the particles within individual clusters, whose strength increases with the cluster size (n) until it saturates at around n = 4. Our analysis shows that strong near-field interactions between individual clusters significantly affect the SERS signal enhancement for edge-to-edge separations Lambda < 200 nm. The observed dependencies of the Raman signals on n and Lambda indicate that NCAs support a multiscale signal enhancement which originates from simultaneous inter- and intracluster coupling and |E|-field enhancement. The NCAs provide strong and reproducible SERS signals not only from small molecules but also from whole bacterial cells, which enabled a rapid spectral discrimination between three tested bacteria species: Escherichia coli, Bacillus cereus, and Staphylococcus aureus.