Erik Benson

DNA nanotechnology offers precise, biocompatible structures with strong potential for targeted drug delivery, yet current discovery approaches rely on testing individual designs, limiting exploration of structural diversity. In this study, we introduce an iterative selection strategy that screens large libraries of DNA nanostructures, each folded from a single‑stranded “structure genome” compatible with amplification and sequencing. Cellular internalization is used as the selection pressure: libraries are incubated with mammalian cells, internalized structures are recovered from lysates, and the process is iterated across multiple rounds in HEK293T and RAW264.7 cells. High‑throughput sequencing of recovered structure genomes reveals cell‑type‐specific enrichment patterns, enabling the identification of individual nanostructures with preferential uptake. Selected candidates were synthesized and evaluated as purified structures, confirming differential internalization by quantitative flow cytometry and microscopy. Turning DNA nanostructure discovery into a selection‑based process could enable high‐throughput exploration of structural diversity and provide an alternative route to identify nanostructures with cell‑specific uptake properties for biomedical applications.

Of the three classes of lymphocytes that constitute the adaptive immune system, γδT cells are the only class for which the principles of antigen recognition remain enigmatic. Although endogenous γδT cell antigen receptor (γδTCR) ligands are thought to regulate γδT cell development, their identities are largely elusive. Here, we identified the interleukin 17 receptor A chain (IL17RA) as a γδTCR ligand that drove the differentiation of Vδ7 ⁺ γδT cells with a T helper 1 (T _H 1)–like effector program in mice. IL17RA promoted this differentiation through an interaction involving germline-encoded regions of the Vδ7 chain, enabling the selection of cells with a diverse CDR3 repertoire and thus acting as a nonclonotypic γδTCR ligand. Together with the nonclonotypic mode of γδTCR engagement by butyrophilins, these results suggest that such interactions represent a general biological mechanism shaping the γδT cell compartment.

DNA nanotechnology offers precise, biocompatible structures with strong potential for targeted drug delivery, yet current discovery approaches rely on testing individual designs, limiting exploration of structural diversity. Here, we introduce an evolutionary selection strategy that screens large libraries of DNA nanostructures, each folded from a single-stranded ‘structure genome’ compatible with amplification and sequencing. Cellular internalization is used as the selection pressure: libraries are incubated with mammalian cells, internalized structures are recovered from lysates, and the process is iterated across multiple rounds in HEK293T and RAW264.7 cells. High-throughput sequencing of recovered structure genomes reveals cell-type-specific enrichment patterns, enabling the identification of individual nanostructures with preferential uptake. Selected candidates were synthesized and evaluated as purified structures, confirming differential internalization by quantitative flow cytometry and microscopy. Turning DNA nanostructure discovery into a selection-based process, could enable high-throughput exploration of structural diversity and provide an alternative route to identify nanostructures with cell-specific uptake properties for biomedical applications.

Synthetic combinatorial DNA libraries are widely used to produce protein variants, optimize binders, and for high-throughput studies of protein-DNA interactions. The libraries can be made by researchers or vendors, and high-throughput sequencing is used for both quality control and to study the outcome of selection experiments. Oxford nanopore sequencing (ONT) is well suited to this as it allows for long read lengths and can be done rapidly with low-cost instrumentation. However, it suffers from a lower overall read accuracy and an uneven error profile. No current bioinformatics tools are well-suited to the challenge of deducing the composition and order of constituent members of combinatorial libraries from ONT reads. We introduce cONcat, an algorithm to identify the makeup of concatenated DNA fragments in a set of ONT sequencing reads from a pool of known fragments. cONcat uses an edit distance-based recursive covering algorithm for finding the best possible matchings between the fragments and the reads. In our experiments on simulated and experimental data, cONcat accurately detects the correct fragment coverings given the short fragment sizes (< 20 bp) and the sequencing errors present in ONT reads. However, we find that the high error rates in the start of ONT reads make it challenging to get confident coverage there, inferring a need for experimental strategies to avoid key sequence information in the start of reads.

Synthetic combinatorial DNA libraries are widely used to produce protein variants, optimize binders, and for high throughput studies of protein - DNA interactions. The libraries can be made by researchers or vendors and high-throughput sequencing is used for both quality control and to study the outcome of selection experiments. Oxford nanopore sequencing (ONT) is well suited to this as it allows for long read lengths and can be done rapidly with low-cost instrumentation. However, it suffers from a lower overall read accuracy and an uneven error profile. No current bioinformatics tools are well suited to the challenge of deducing the composition and order of constituent members of combinatorial libraries from ONT reads. We introduce cONcat, an algorithm to identify the makeup of concatenated DNA fragments in a set of ONT sequencing reads from a pool of known fragments. cONcat uses the edit distance-based recursive covering algorithm for finding the best possible matchings between the fragments and the reads. In our experiments on simulated and experimental data, cONcat could accurately detect the correct fragment coverings given the short fragment sizes (< 20bp) and the sequencing errors present in ONT reads. However, we find that the high error rates in the start of ONT reads make it challenging to get confident coverage there, inferring a need for experimental strategies to avoid key sequence information in the start of reads.

The successful translation of therapeutic nucleic acids (NAs) for the treatment of neurological disorders depends on their safe and efficient delivery to neural cells, in particular neurons. DNA nanostructures can be a promising NAs delivery vehicle. Nonetheless, the potential of DNA nanostructures for neuronal cell delivery of therapeutic NAs is unexplored. Here, tetrahedral DNA nanostructures (TDN) as siRNA delivery scaffolds to neuronal cells, exploring the influence of functionalization with two different reported neuronal targeting ligands: C4‐3 RNA aptamer and Tet1 peptide are investigated. Nanostructures are characterized in vitro, as well as in silico using molecular dynamic simulations to better understand the overall TDN structural stability. Enhancement of neuronal cell uptake of TDN functionalized with the C4‐3 Aptamer (TDN‐Apt), not only in neuronal cell lines but also in primary neuronal cell cultures is demonstrated. Additionally, TDN and TDN‐Apt nanostructures carrying siRNA are shown to promote silencing in a process aided by chloroquine‐induced endosomal disruption. This work presents a thorough workflow for the structural and functional characterization of the proposed TDN as a nano‐scaffold for neuronal delivery of therapeutic NAs and for targeting ligands evaluation, contributing to the future development of new neuronal drug delivery systems based on DNA nanostructures.

Modular reconfigurable systems can be achieved with DNA origami, demonstrating the potential to generate molecular robots.

Nanoscale manipulation and patterning usually require costly and sensitive top-down techniques such as those used in scanning probe microscopies or in semiconductor lithography. DNA nanotechnology enables exploration of bottom-up fabrication and has previously been used to design self-assembling components capable of linear and rotary motion. In this work, we combine three independently controllable DNA origami linear actuators to create a nanoscale robotic printer. The two-axis positioning mechanism comprises a moveable gantry, running on parallel rails, threading a mobile sleeve. We show that the device is capable of reversibly positioning a write head over a canvas through the addition of signaling oligonucleotides. We demonstrate “write” functionality by using the head to catalyze a local DNA strand–exchange reaction, selectively modifying pixels on a canvas. This work demonstrates the power of DNA nanotechnology for creating nanoscale robotic components and could find application in surface manufacturing, biophysical studies, and templated chemistry.