DNA computing uses a set of designed oligonucleotides as the medium for computation. These oligonucleotides are programmed with sequences to dynamically assemble according to user-specified logic and respond to specific nucleic-acid inputs. In proof-of-concept studies, the output of the computation typically consists of a set of fluorescently labelled oligonucleotides that can be detected via gel electrophoresis or fluorescence plate readers. Over the past 30 years, increasingly complex DNA computational circuitries have been demonstrated, such as various digital logic cascades, chemical reaction networks, and neural networks1,2,3. To assist with the preparation of these DNA circuits, mathematical models have been used to predict the functionality of synthetic gene circuits4,5, and computational tools have been developed for orthogonal DNA sequence design6,7,8,9,10. Compared to silicon-based computers, the advantages of DNA computers include their ability to interface directly with biomolecules, operate in solution in the absence of a power supply, as well as their overall compactness and stability. With the advent of next-generation sequencing, the cost of synthesizing DNA computers has been decreasing for the past two decades at a rate faster than Moore's Law11. Applications of such DNA-based computers are now beginning to emerge, such as for disease diagnosis12,13, for powering molecular biophysics14, and as data storage platforms15.

Figure 1: Mechanism of toehold-mediated DNA strand displacement. The toehold, δ, is a free, unbound sequence on a partial duplex. When a complementary domain (δ*) is introduced on a second strand, the free δ domain serves as a toehold for hybridization, allowing for the rest of the strand (ɑ*) to slowly displace its competitor through a zipping/unzipping reversible reaction known as strand migration. As the length of δ increases, the ΔG for the forward reaction decreases, and displacement happens more readily. Please click here to view a larger version of this figure.
To-date, the majority of DNA computers utilize a well-established motif in the field of dynamic DNA nanotechnology known as toehold-mediated DNA strand displacement (TMDSD, Figure 1)16. This motif consists of a partially double-stranded DNA (dsDNA) duplex displaying short "toehold" overhangs (i.e., 7- to 10 nucleotides (nt)). Nucleic acid "input" strands can interact with the partial duplexes through the toehold. This leads to the displacement of one of the strands from the partial duplex, and this liberated strand can then serve as input for downstream partial duplexes. Thus, TMDSD enables signal cascading and information processing. In principle, orthogonal TMDSD motifs can operate independently in solution, enabling parallel information processing. There have been a number of variations on the TMDSD reaction, such as toehold-mediated DNA strand exchange (TMDSE)17, "leakless" toeholds with double-long domains18, sequence-mismatched toeholds19, and "handhold"-mediated strand displacement20. These innovative design principles allow more finely tuned TMDSD energetics and dynamics for improving DNA computing performance.
Synthetic gene circuits, such as transcriptional gene circuits, are also capable of computation21,22,23. These circuits are regulated by protein transcription factors, which activate or repress transcription of a gene by binding to specific regulatory DNA elements. Compared to DNA-based circuits, transcriptional circuits have several advantages. First, enzymatic transcription has a much higher turnover rate than existing catalytic DNA circuits, thus generating more copies of output per single copy of input and providing a more efficient means of signal amplification. In addition, transcriptional circuits can produce different functional molecules, such as aptamers or messenger RNA (mRNA) encoding for therapeutic proteins, as computation outputs, which can be exploited for different applications. However, a major limitation of current transcriptional circuits is their lack of scalability. This is because there is a very limited set of orthogonal protein-based transcription factors, and de novo design of new protein transcription factors remains technically challenging and time-consuming.

Figure 2: Abstraction and mechanism of "tether" and "cage" polymerase complex. (A and B) An oligonucleotide tether is enzymatically labelled to a T7 polymerase through the SNAP-tag reaction. A cage consisting of a "faux" T7 promoter with a tether-complement overhang allows it to hybridize to the tether and block transcriptional activity. (C) When the operator (a*b*) is present, it binds to the toehold on the oligonucleotide tether (ab) and displaces the b* region of the cage, allowing transcription to occur. This figure has been modified from Chou and Shih27. Abbreviations: RNAP = RNA polymerase. Please click here to view a larger version of this figure.
This paper introduces a novel building block for molecular computing that combines the functionalities of transcriptional circuits with the scalability of DNA-based circuits. This building block is a T7 RNAP covalently attached with a single-stranded DNA tether (Figure 2A). To synthesize this DNA-tethered T7 RNAP, the polymerase was fused to an N-terminal SNAP-tag24 and recombinantly expressed in Escherichia coli. The SNAP-tag was then reacted with an oligonucleotide functionalized with the BG substrate. The oligonucleotide tether allows the positioning of molecular guests in close proximity to the polymerase via DNA hybridization. One such guest was a competitive transcriptional blocker referred to as a "cage", which consists of a "faux" T7 promoter DNA duplex with no gene downstream (Figure 2B). When bound to the RNAP via its oligonucleotide tether, the cage stalls polymerase activity by outcompeting other DNA templates for RNAP binding, rendering the RNAP in an "OFF" state (Figure 2C).
To activate the polymerase to an "ON" state, T7 DNA templates with single-stranded "operator" domains upstream of the T7 promoter of the gene were designed. The operator domain (i.e., domain a*b* Figure 2C) can be designed to displace the cage from the RNAP via TMDSD and position the RNAP proximal to the T7 promoter of the gene, thus initiating transcription. Alternatively, DNA templates were also designed where the operator sequence was complementary to auxiliary nucleic-acid strands that are referred to as "artificial transcription factors" (i.e., TFA and TFB strands in Figure 3A). When both strands are introduced into the reaction, they will assemble at the operator site, creating a new pseudo-contiguous domain a*b*. This domain can then displace the cage via TMDSD to initiate transcription (Figure 3B). These strands can be supplied either exogenously or produced.

Figure 3: Selective programming of polymerase activity through a three-component switch activator. (A) When the transcription factors (TFA and TFB) are present, they bind to the operator domain upstream of the promoter, forming a pseudo single-stranded sequence (a*b*) capable of displacing the cage through toehold mediated DNA displacement. (B) This a*b* domain can displace the cage via TMDSD to initiate transcription. This figure has been modified from Chou and Shih27. Abbreviations: TF = transcription factor; RNAP = RNA polymerase; TMDSD = toehold-mediated DNA strand displacement. Please click here to view a larger version of this figure.
The use of nucleic acid-based transcription factors for in vitro transcriptional regulation allows the scalable implementation of sophisticated circuit behaviors such as digital logic, feedback, and signal cascading. For example, one can build logic gate cascades by designing nucleic acid sequences such that the transcripts from an upstream gene activate a downstream gene. One application that exploits the cascading and multiplexing made capable by this proposed technology is the development of more sophisticated molecular computing circuitries for portable diagnostics and molecular data processing. In addition, integrating the molecular computing and de novo RNA synthesis capabilities can enable new applications. For example, a molecular circuit can be designed to detect one or a combination of user-defined RNAs as inputs and output therapeutic RNAs or mRNAs encoding functional peptides or proteins for point-of-care medical applications.