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DNA is a highly programmable biomolecule and has been used to construct biological circuits for different purposes. An important development of DNA circuits is to process the information on receptors on cell membranes. In this Communication, we introduce an architecture to program localized DNA-based biomolecular reaction networks on cancer cell membranes. Based on our architecture, various types of reaction networks have been experimentally demonstrated, from simple linear cascades to reaction networks of complex structures. These localized DNA-based reaction networks can be used for medical applications such as cancer cell detection. Compared to prior work on DNA circuits for evaluating cell membrane receptors, the DNA circuits made by our architecture have several major advantages including simpler design, lower leak, lower cost, and higher signal-to-background ratio.

DNA is a reliable biomolecule with which to build molecular computation systems. In particular, DNA logic circuits (diffusion-based) have shown good performance regarding scalability and correctness of computation. However, previous architectures of DNA logic circuits have two limitations. First, the speed of computation is slow, often requiring hours to compute a simple function. Second, the circuits are of high complexity regarding the number of DNA strands. Here, we introduce an architecture of DNA logic circuits based on single-stranded logic gates using strand-displacing DNA polymerase. The logic gates consist of only single DNA strands, which largely reduces leakage reactions and signal restoration steps such that the circuits are improved in regard to both speed of computation and the number of DNA strands needed. Large-scale logic circuits can be constructed from the gates by simple cascading strategies. In particular, we have demonstrated a fast and compact logic circuit that computes the square-root function of four-bit input numbers. A new DNA logic circuits architecture based on single-stranded logic gates and strand-displacing DNA polymerase requires less computation time and fewer DNA strands.

DNA outperforms most conventional storage media in terms of information retention time, physical density, and volumetric coding capacity. Advances in synthesis and sequencing technologies have enabled implementations of large synthetic DNA databases with impressive storage capacity and reliable data recovery. Several robust DNA storage architectures featuring random access, error correction, and content rewritability have been constructed with the potential for scalability and cost reduction. We survey these recent achievements and discuss alternative routes for overcoming the hurdles of engineering practical DNA storage systems. We also review recent exciting work on in vivo DNA memory including intracellular recorders constructed by programmable genome editing tools. Besides information storage, DNA could serve as a versatile molecular computing substrate. We highlight several state-of-the-art DNA computing techniques such as strand displacement, localized hybridization chain reactions, and enzymatic reaction networks. We summarize how these simple primitives have facilitated rational designs and implementations of in vitro DNA reaction networks that emulate digital/analog circuits, artificial neural networks, or nonlinear dynamic systems. We envision these modular primitives could be strategically adapted for sophisticated database operations and massively parallel computations on DNA databases. We also highlight in vivo DNA computing modules such as CRISPR logic gates for building scalable genetic circuits in living cells. To conclude, we discuss various implications and challenges of DNA-based storage and computing, and we particularly encourage innovative work on bridging these two areas of research to further explore molecular parallelism and near-data processing. Such integrated molecular systems could lead to far-reaching applications in biocomputing, security, and medicine.

Many biochemical events of importance are complex and dynamic. Fluorescence microscopy offers a versatile solution to study the dynamics of biology at the mesoscale. An important challenge in the field is the simultaneous study of several objects of interest, referred to as optical multiplexing. For improved multiplexing, some prior techniques used repeated reporter washing or the geometry of nanostructures; however, these techniques require complex nanostructure assembly, multiple reporters, or advanced multistep drift correction. Here we propose a time-based approach, for improved optical multiplexing, that uses readily available inexpensive reporters and requires minimal preparation efforts. We program short DNA strands, referred hereby as DNA devices, such that they undergo unique conformation changes in the presence of the dye-labeled reporters. The universal fluorescent reporter transiently binds with the devices to report their activity. Since each device is programmed to exhibit different hybridization kinetics, their fluorescent time trace, referred to as the temporal barcode, will be unique. We model our devices using continuous-time Markov chains and use stochastic simulation algorithm to generate their temporal patterns. We first ran simulation experiments with a small number of DNA devices, demonstrating several distinct temporal barcodes, all of which use a single dye color. Later, using nanostructure-based devices, we designed a much larger pool of temporal barcodes and used machine learning for classification of these barcodes. Our simulation experiments and design principles can aid in the experimental demonstration of the DNA devices.

Developing intelligent molecular systems for the desired functions is a significant current research topic in the field of nanoscience. Several materials have been explored to construct interesting systems, such as molecular motors, molecular walkers, and Boolean logic circuits. Deoxyribonucleic acid (DNA) is one of the most widely used materials as the Watson–Crick base pairing makes it a versatile substrate. A significant achievement in DNA nanoscience has been the construction of large-scale logic circuits. However, most of the prior works have focused on developing the single-use DNA logic circuits. These single-use circuits can perform robust computations. However, the computing material, such as gate strands, cannot be reused to achieve the same (or a different) computation again. Such reusable behavior is essential for applications, such as feedback and sequential logic computation. In this paper, we propose a novel design strategy for building renewable DNA logic circuits. First, we propose a renewable DNA hairpin-based motif and, then, use this motif to implement a Boolean logic gate. Such renewable circuits make the overall sample preparation convenient and straightforward. We believe that our work will serve as a seed for the development of renewable intelligent molecular systems.

Access to fast and reliable nucleic acid testing continues to play a key role in controlling the COVID-19 pandemic, especially in the context of increased vaccine break-through risks due to new variants. We report a rapid, low-cost (~ 2 USD), simple-to-use nucleic acid test kit for self-administered at-home testing without lab instrumentation. The entire sample-to-answer workflow takes