Shanghai Jiaotong University reports on universal DNA computing circuits

On September 13, 2023, Beijing time, Academician Chunhai Fan, School of Chemistry and Chemical Engineering/Center for Transformative Molecular Frontier Science, Shanghai Jiao Tong University, and the team of Associate Professor Wang Fei published a research result entitled “DNA-based programmable gate arrays for general-purpose DNA computing” in the journal Nature.

This achievement reports a DNA-based programmable gate array (DPGA) that supports universal digital computing, which can develop universal digital DNA computing by molecular instruction programming, and realize the construction of large-scale liquid phase molecular circuits without attenuation.

The corresponding authors of the paper are Wang Fei and Fan Chunhai; The first author is Lv Hui.

Liquid-phase biocomputing using biomolecular interactions has great potential for highly parallel computing. Using DNA molecular reaction networks, researchers have successfully realized cellular automata, logic circuits, decision-making machines, neural networks and other functions. However, existing DNA computing systems can only be hardware customized for specific functions. In the field of electronic computers, general-purpose integrated circuits (such as FPGAs) can perform various computing functions through software programming, without the need to design and manufacture hardware from scratch, which provides a high-level platform for the development of computing machines. Similar to the evolution from specific applications of electronic integrated circuits to general applications, the development of universal programmable DNA integrated circuits is very promising for applications in a variety of scenarios. However, in DNA integrated circuits, biomolecular components diffuse and mix in solution, making the inherent random collisions between molecules difficult to control, hindering the development of scalable and programmable DNA computing devices, and making the practical implementation of universal DNA computing challenging.

In this work, Academician Fan Chunhai’s team developed a DPGA that supports universal digital computing and supports multi-DPGA integration at the device level, realizing programmability within the device and integration between devices. Using the programmability and high integration of DPGA, this study breaks through the bottleneck of DNA molecular computing in circuit scale and circuit depth, and for the first time experimentally demonstrates the circuit scale of up to 30 logic elements, 500 DNA strands, and 30 layers of DNA strands to replace the reaction. Due to the scalability of DPGA, any practical problem in theory can be connected to the DPGA circuit after analog-to-digital conversion. This study conceptually demonstrates the nonlinear classification of disease-relevant molecular targets using DPGA as the information processing core in molecular diagnostics.

Figure 1: Workflow for DPGA programming.

Figure 2: Consistent two-track arithmetic element with gated global DNA signaling (DNA-UTS) transmission.

Figure 3: Signal transmission within and between DPGA via wired instructions.

Figure 4: Multifunctional reprogramming of the DPGA.

Figure 5: Multi-DPGA computing network.

Figure 6: DPGA-based nonlinear classifier.

DPGA’s ability to integrate and operate large-scale reaction networks marks a key step towards universal DNA computing, which is expected to be more widely used in mathematical operations and disease diagnosis. (Source: Science Network)

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