Richard A. Muscat

DNA nanotechnology from the test tube to the cell

The programmability of Watson-Crick base pairing, combined with a decrease in the cost of synthesis, has made DNA a widely used material for the assembly of molecular structures and dynamic molecular devices. Working in cell-free settings, researchers in DNA nanotechnology have been able to scale up system complexity and quantitatively characterize reaction mechanisms to an extent that is infeasible for engineered gene circuits or other cell-based technologies. However, the most intriguing applications of DNA nanotechnology - applications that best take advantage of the small size, biocompatibility and programmability of DNA-based systems - lie at the interface with biology. Here, we review recent progress in the transition of DNA nanotechnology from the test tube to the cell. We highlight key successes in the development of DNA-based imaging probes, prototypes of smart therapeutics and drug delivery systems, and explore the future challenges and opportunities for cellular DNA nanotechnology.

A Programmable Molecular Robot

We have developed a programmable and auton-omous molecular robot whose motion is fueled by DNA hybridization. Instructions determining the path to be followed are programmed into the fuel molecules, allowing precise control of cargo motion on a branched track.

An autonomous molecular assembler for programmable chemical synthesis

Molecular machines that assemble polymers in a programmed sequence are fundamental to life. They are also an achievable goal of nanotechnology. Here, we report synthetic molecular machinery made from DNA that controls and records the formation of covalent bonds. We show that an autonomous cascade of DNA hybridization reactions can create oligomers, from building blocks linked by olefin or peptide bonds, with a sequence defined by a reconfigurable molecular program. The system can also be programmed to achieve combinatorial assembly. The sequence of assembly reactions and thus the structure of each oligomer synthesized is recorded in a DNA molecule, which enables this information to be recovered by PCR amplification followed by DNA sequencing.

A spatially localized architecture for fast and modular DNA computing

Cells use spatial constraints to control and accelerate the flow of information in enzyme cascades and signalling networks. Synthetic silicon-based circuitry similarly relies on spatial constraints to process information. Here, we show that spatial organization can be a similarly powerful design principle for overcoming limitations of speed and modularity in engineered molecular circuits. We create logic gates and signal transmission lines by spatially arranging reactive DNA hairpins on a DNA origami. Signal propagation is demonstrated across transmission lines of different lengths and orientations and logic gates are modularly combined into circuits that establish the universality of our approach. Because reactions preferentially occur between neighbours, identical DNA hairpins can be reused across circuits. Co-localization of circuit elements decreases computation time from hours to minutes compared to circuits with diffusible components. Detailed computational models enable predictive circuit design. We anticipate our approach will motivate using spatial constraints for future molecular control circuit designs.

Single-cell profiling of the developing mouse brain and spinal cord with split-pool barcoding

Identifying single-cell types in the mouse brain The recent development of single-cell genomic techniques allows us to profile gene expression at the single-cell level easily, although many of these methods have limited throughput. Rosenberg et al. describe a strategy called split-pool ligation-based transcriptome sequencing, or SPLiT-seq, which uses combinatorial barcoding to profile single-cell transcriptomes without requiring the physical isolation of each cell. The authors used their method to profile >100,000 single-cell transcriptomes from mouse brains and spinal cords at 2 and 11 days after birth. Comparisons with in situ hybridization data on RNA expression from Allen Institute atlases linked these transcriptomes with spatial mapping, from which developmental lineages could be identified. Science, this issue p. 176 Single-cell analyses with SPLiT-seq (split-pool ligation-based transcriptome sequencing) elucidate development of the mouse nervous system. To facilitate scalable profiling of single cells, we developed split-pool ligation-based transcriptome sequencing (SPLiT-seq), a single-cell RNA-seq (scRNA-seq) method that labels the cellular origin of RNA through combinatorial barcoding. SPLiT-seq is compatible with fixed cells or nuclei, allows efficient sample multiplexing, and requires no customized equipment. We used SPLiT-seq to analyze 156,049 single-nucleus transcriptomes from postnatal day 2 and 11 mouse brains and spinal cords. More than 100 cell types were identified, with gene expression patterns corresponding to cellular function, regional specificity, and stage of differentiation. Pseudotime analysis revealed transcriptional programs driving four developmental lineages, providing a snapshot of early postnatal development in the murine central nervous system. SPLiT-seq provides a path toward comprehensive single-cell transcriptomic analysis of other similarly complex multicellular systems.

Small Molecule Signals that Direct the Route of a Molecular Cargo

The route taken by a DNA cargo on a branched track can be controlled by the small molecule adenosine using a pair of aptamers that reciprocally block and unblock branches of the track in response to adenosine binding.

MicroRNA-Based Single-Gene Circuits Buffer Protein Synthesis Rates against Perturbations

Achieving precise control of mammalian transgene expression has remained a long-standing, and increasingly urgent, challenge in biomedical science. Despite much work, single-cell methods have consistently revealed that mammalian gene expression levels remain susceptible to fluctuations (noise) and external perturbations. Here, we show that precise control of protein synthesis can be realized using a single-gene microRNA (miRNA)-based feed-forward loop (sgFFL). This minimal autoregulatory gene circuit consists of an intronic miRNA that targets its own transcript. In response to a step-like increase in transcription rate, the network generated a transient protein expression pulse before returning to a lower steady state level, thus exhibiting adaptation. Critically, the steady state protein levels were independent of the size of the stimulus, demonstrating that this simple network architecture effectively buffered protein production against changes in transcription. The single-gene network architecture was also effective in buffering against transcriptional noise, leading to reduced cell-to-cell variability in protein synthesis. Noise was up to 5-fold lower for a sgFFL than for an unregulated control gene with equal mean protein levels. The noise buffering capability varied predictably with the strength of the miRNA-target interaction. Together, these results suggest that the sgFFL single-gene motif provides a general and broadly applicable platform for robust gene expression in synthetic and natural gene circuits.

Scaling single cell transcriptomics through split pool barcoding

Constructing an atlas of cell types in complex organisms will require a collective effort to characterize billions of individual cells. Single cell RNA sequencing (scRNA-seq) has emerged as the main tool for characterizing cellular diversity, but current methods use custom microfluidics or microwells to compartmentalize single cells, limiting scalability and widespread adoption. Here we present Split Pool Ligation-based Transcriptome sequencing (SPLiT-seq), a scRNA-seq method that labels the cellular origin of RNA through combinatorial indexing. SPLiT-seq is compatible with fixed cells, scales exponentially, uses only basic laboratory equipment, and costs one cent per cell. We used this approach to analyze 109,069 single cell transcriptomes from an entire postnatal day 5 mouse brain, providing the first global snapshot at this stage of development. We identified 13 main populations comprising different types of neurons, glia, immune cells, endothelia, as well as types in the blood-brain-barrier. Moreover, we resolve substructure within these clusters corresponding to cells at different stages of development. As sequencing capacity increases, SPLiT-seq will enable profiling of billions of cells in a single experiment.

A Spatially Localized Architecture for Fast and Modular Computation at the Molecular Scale

Cells use spatial constraints to control and accelerate the flow of information in enzyme cascades and signaling networks. Here we show that spatial organization can be a similarly powerful design principle for overcoming limitations of speed and modularity in engineered molecular circuits. We create logic gates and signal transmission lines by spatially arranging reactive DNA hairpins on a DNA origami. Signal propagation is demonstrated across transmission lines of different lengths and orientations, and logic gates are modularly combined into circuits that establish the universality of our approach. Because reactions preferentially occur between neighbors, identical DNA hairpins can be reused across circuits. Colocalization of circuit elements decreases computation time from hours to minutes compared to circuits with diffusible components. Detailed computational models enable predictive circuit design. We anticipate that our approach will motivate the use of spatial constraints in molecular engineering more broadly, bringing embedded molecular control circuits closer to applications.