Thank you for visiting Nature.com. The version of browser you are using has limited CSS support. For best results, we recommend that you use a newer version of your browser (or disable Compatibility Mode in Internet Explorer). In the meantime, to ensure ongoing support, we are displaying the site without styling or JavaScript.
Over the past few decades, we have witnessed the evolution of electronic and photonic integrated circuits from application-specific to programmable1,2. Although liquid-phase DNA circuits have the potential for massive parallelism in coding and algorithm execution,3,4 the development of general-purpose DNA integrated circuits (DICs) remains to be explored. Here, we demonstrate a DIC system by integrating a multilayer DNA field programmable gate array (DPGA). We found that using a universal single-stranded oligonucleotide as a unified transmission signal allows for robust integration of large-scale DIC with minimal leakage and high accuracy suitable for general-purpose computing. A single DPGA with 24 addressable dual-rail gates can be reconfigured using wiring instructions to implement over 100 billion different circuits. Additionally, to control the inherently random collisions of molecules, we designed DNA origami registers to provide directionality for the asynchronous execution of cascaded DPGAs. We demonstrate this by solving a quadratic equation for a DIC assembled from three layers of cascaded DPGAs containing 30 logic gates and approximately 500 strands of DNA. We also show that integration of DPGAs with analog-to-digital converters can classify disease-associated miRNAs. The ability to integrate large-scale DPGA networks without significant signal degradation marks an important step towards general-purpose DNA computing.
Data supporting the results of this study can be found in the manuscript or in the supporting information. Source data is provided for this article. All other data is available upon request.
The source code (Visual DSD, MATLAB, Python) used in this study is available on GitHub (https://github.com/FeiWANG-SJTU/DPGA). All other code is available from the corresponding author on reasonable request.
Burks, A. W., A History of Twentieth Century Computing (ed. Metropolis, N.) 311–344 (Elsevier, 1980).
Chen X. and Ellington A.D. Formation of nucleic acid calculations. current. Opinion. Biotechnology. 21, 392–400 (2010).
Li, J., Green, A. A., Yang, H., and Fan, Q. Engineered nucleic acid structures for programmable molecular circuits and intracellular biocomputers. Nat. Chemical. 9, 1056–1067 (2017).
Benenson Y. et al. Programmable autonomous computers made from biomolecules. Nature 414, 430–434 (2001).
Qian, L. and Winfrey, E. Extending digital circuit computation using DNA strand bias cascades. Science 332, 1196–1201 (2011).
Seelig G., Soloveitchik D., Zhang D.Yu. and Winfrey E. Logic circuits of nucleic acids without enzymes. Science 314, 1585–1588 (2006).
Wang, F. et al. Enable digital computing with DNA-based switching circuits. Nat. communicate. 11, 121 (2020).
Cherry K.M. and Qian L.L. Extending molecular pattern recognition using winner-take-all DNA neural networks. Nature 559, 370–376 (2018).
Kishi, J. Y., Schaus, T. E., Gopalkrishnan, N., Xuan, F., and Yin, P. Programmable autonomous synthesis of single-stranded DNA. Nat. Chemical. 10, 155–164 (2018).
Zhang Y. et al. Selective transitions between nanoparticle superlattices are achieved through reprogramming of DNA-mediated interactions. Nat. Matt. 14, 840–847 (2015).
Douglas, S.M., Bachelet, I. and Church, G.M. Logic-controlled nanorobots for targeted transport of molecular payloads. Science 335, 831–834 (2012).
Lopez R, Wang R and Seelig G. Molecular multigene classifiers for disease diagnosis. Nat. Chemical. 10, 746–754 (2018).
Zhang S. et al. Cancer diagnosis using DNA molecular computing. Nat. nanotechnology. 15, 709–715 (2020).
Hills, G. et al. Modern microprocessors are built on the basis of complementary transistors made of carbon nanotubes. Nature 572, 595–602 (2019).
Debnath S. et al. Demonstration of a small programmable quantum computer with atomic qubits. Nature 536, 63–66 (2016).
Athanas, P.M. and Silverman, H.F. Processor reconfiguration via instruction set morphing. Computers 26, 11–18 (1993).
Ruiz-Rocero, J., Ramirez-Gonzalez, G., and Hanna, R. Application of field programmable gate arrays—a scientometric review. Computing 7, 63 (2019).
Benenson, Y. Biomolecular computing systems: principles, advances and potential. Nat. Pastor Ginette. 13, 455–468 (2012).
Pei, R., Matamoros, E., Liu, M., Stefanovic, D., and Stojanovic, M.N. Training molecular automata to play. Nat. nanotechnology. 5, 773–777 (2010).
Woods D. et al. Diverse and powerful molecular algorithms using reprogrammable DNA self-assembly. Nature 567, 366–372 (2019).
Wang, N.H. et al. Large-scale integration of artificial atoms into hybrid photonic circuits. Nature 583, 226–231 (2020).
Klosin A. et al. Phase separation provides a mechanism for reducing cellular noise. Science 367, 464–468 (2020).
Chatterjee, G., Dalchau, N., Muscat, R. A., Phillips, A., and Seelig, G. A spatially localized architecture for fast and modular DNA computing. Nat. nanotechnology. 12, 920–927 (2017).
Bian, Q., Zhang, Z., Xiong, Q., De Camilli, P., and Lin, Q. A programmable DNA origami platform for studying lipid transfer between bilayers. Nat. Chemical. biology. 15, 830–837 (2019).
Josar A. et al. Synthetic DNA-based communication in primitive cell populations. Nat. nanotechnology. 14, 369–378 (2019).
Zhang D.Yu. and Winfrey E. Controlling DNA strand displacement dynamics by support replacement. J. Am. Bitch. 131, 17303–17314 (2009).
Li, W., Zhang, F., Yang, H., and Liu, Y. DNA-based arithmetic functions: A half-adder based on DNA strand offsets. Nanoscale 8, 3775–3784 (2016).
Song, T. et al. Fast and compact DNA logic circuitry based on single-stranded gates using strand displacement polymerase. Nat. nanotechnology. 14, 1075–1081 (2019).
Ke, Y. G., Lindsay, S., Chang, Y., Liu, Y., and Yang, H. Self-assembled water-soluble nucleic acid probe panels for label-free RNA hybridization assays. Science 319, 180–183 (2008).
Lauback, S. et al. Real-time magnetic actuation of DNA nanodevices via modular integration with rigid micro-levers. Nat. communicate. 9, 1446 (2018).
Janotte, A.J. et al. High-resolution mapping of bifurcations in nonlinear biochemical chains. Nat. Chemical. 8, 760–767 (2016).
Rothemund, PWK folds DNA to create nanoscale shapes and patterns. Nature 440, 297–302 (2006).
Oldridge T.E., Louis A.A. and Doy J.P.K. Structural, mechanical and thermodynamic properties of raw DNA models. J.Chemistry. physics. 134, 085101 (2011).
Snowdin, BEK et al. Incorporating improved structural properties and salt dependence into coarse-grained DNA models. J.Chemistry. physics. 142, 234901 (2015).
Summa, A. et al. TacoxDNA: a user-friendly web server for modeling complex DNA structures, from single strands to origami. J. Computer. Chemical. 40, 2586–2595 (2019).
Dow, J.P. et al. The coarse-grained oxDNA model serves as a tool for DNA origami modeling. numerator of the method. biology. 2639, 93–112 (2023).
Poppleton E. et al. Design, optimize and analyze large DNA and RNA nanostructures using interactive visualization, editing and molecular modeling. Nucleic acid research. 48, e72 (2020).
We thank L. Qian (Caltech) and Y. Huang (Peking University) for helpful discussions. This work was supported by the National Key Research and Development Program (Grant Number: 2021YFF1200300), the National Natural Science Foundation of China (Grant Numbers: T2188102, 21991134, 21904060, 22025404 and 22104088), Shanghai Research Institute Support Committee. Technology Fund (grant numbers 20dz1101000 and 21TQ1400222) and the New Cornerstone Investigator program. Molecular dynamics simulations were carried out on the π2.0 cluster with support from the High Performance Computing Center of Shanghai Jiao Tong University.
Department of Chemistry and Chemical Engineering, Shanghai Jiao Tong University, New Cornerstone Science Laboratory, Science Center for Translational Molecular Research, National Center for Translational Medicine, Shanghai Jiao Tong University
Hui Lv, Nuli Xie, Mingqiang Li, Chengyun Sun, Qian Zhang, Lei Zhao, Xiaolei Zuo, Fei Wang and Chunhai Fan
Shanghai Advanced Research Institute, Chinese Academy of Sciences, Shanghai Interdisciplinary Research Center for Synchrotron Radiation Facility, Shanghai, China
Institute of Materials Biology, Department of Chemistry, School of Science, Shanghai University, Shanghai, China
Institute of Molecular Medicine, Renji Hospital, Affiliated School of Medicine, Shanghai Jiao Tong University, Shanghai Key Laboratory of Nucleic Acid Chemistry and Nanomedicine, Shanghai, China
CF and FW conceived the study. FW designed the circuit and wrote the sequence generation and compilation routines. HL performed most of the experiments. NX performed the AFM experiments. CS and QZ performed magnetic field experiments. ML and FW performed the simulations. LZ trained the nonlinear classification model. FW, CF, and HL analyzed the data and wrote the manuscript. MD, JL, and HC contributed to data analysis and discussion. CF, HC, JL, NX, MD, and XZ reviewed and edited the manuscript.
Nature thanks the anonymous reviewers for their contributions to the review of this work. Review reports are available.
Publisher’s Note Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.
Post time: Nov-04-2024