Information processing using an integrated DNA reaction network
Source abstract
Abstract
Living organisms use interconnected chemical reaction networks (CRNs) to exchange information with the surrounding environment and respond to diverse external stimuli. Inspired by nature, numerous artificial CRNs with a complex information processing function have been recently introduced, with DNA as one of the most attractive engineering materials. Although much progress has been made in DNA-based CRNs in terms of controllable reaction dynamics and molecular computation, the effective integration of signal translation with information processing in a single CRN remains to be difficult. In this work, we introduced a stimuli-responsive DNA reaction network capable of integrated information translation and processing in a stepwise manner. This network is designed to integrate sensing, translation, and decision-making operations by independent modules, in which various logic units capable of performing different functions were realized, including information identification (YES and OR gates), integration (AND and AND-AND gates), integration-filtration (AND-AND-NOT gate), comparison (Comparator), and map-to-map analysis (Feynman gate). Benefitting from the modular and programmable design, continuous and parallel processing operations are also possible. With the innovative functions, we show that the DNA network is a highly useful addition to the current DNA-based CRNs by offering a bottom-up strategy to design devices capable of cascaded information processing with high efficiency.
Source: openalex_inverted_index · Quality: candidate unverified · Source record ↗
Research context
OpenAlex topics: Advanced biosensing and bioanalysis techniques · DNA and Biological Computing · DNA and Nucleic Acid Chemistry
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Key Laboratory of Green Chemistry & Technology of Ministry of Education
College of Chemistry
Sichuan University
Chengdu
China
Key Laboratory of Drug-Targeting and Drug Delivery System of the Education Ministry
Sichuan Engineering Laboratory for Plant-Sourced Drug and Sichuan Research Centre for Drug Precision Industrial Technology
West China School of Pharmacy
Funding
National Natural Science Foundation of China
References (40)
Show source-provided references
1. Chen · Nat. Nanotechnol. · 2013 · 8 · 75510.1038/nnano.2013.189 ↗
2. Werner · Nature · 2007 · 446 · 49310.1038/446493a ↗
3. Bhalla · Science · 1999 · 283 · 38110.1126/science.283.5400.381 ↗
4. Han · Nat. Chem. · 2015 · 7 · 83510.1038/nchem.2325 ↗
5. van Roekel · Chem. Soc. Rev. · 2015 · 44 · 746510.1039/C5CS00361J ↗
6. Wang · Chem. Rev. · 2019 · 119 · 637010.1021/acs.chemrev.8b00625 ↗
7. He · J. Am. Chem. Soc. · 2020 · 142 · 1423410.1021/jacs.0c05453 ↗
8. Xia · Angew. Chem., Int. Ed. · 2009 · 48 · 6010.1002/anie.200802248 ↗
9. Rycenga · Chem. Rev. · 2011 · 111 · 366910.1021/cr100275d ↗
10. Chirieleison · Nat. Chem. · 2013 · 5 · 100010.1038/nchem.1764 ↗
11. Zadorin · Nat. Chem. · 2017 · 9 · 99010.1038/nchem.2770 ↗
12. Lin · Chem. Sci. · 2020 · 11 · 961710.1039/D0SC03392H ↗
13. Pogodaev · J. Am. Chem. Soc. · 2017 · 139 · 1529610.1021/jacs.7b08109 ↗
14. Tamate · Adv. Mater. · 2015 · 27 · 83710.1002/adma.201404757 ↗
15. Tamate · Angew. Chem., Int. Ed. · 2016 · 55 · 517910.1002/anie.201511871 ↗
16. Che · J. Am. Chem. Soc. · 2018 · 140 · 535610.1021/jacs.8b02387 ↗
17. Litschel · Angew. Chem., Int. Ed. · 2018 · 57 · 1628610.1002/anie.201808750 ↗
18. Liu · J. Am. Chem. Soc. · 2019 · 141 · 645810.1021/jacs.8b13816 ↗
19. Guo · Sci. Rep. · 2014 · 4 · 731510.1038/srep07315 ↗
20. Bader · Chem. – Eur. J. · 2018 · 24 · 482010.1002/chem.201800756 ↗
21. Jiao · J. Am. Chem. Soc. · 2020 · 142 · 1073910.1021/jacs.0c01962 ↗
22. Lebar · Nat. Commun. · 2014 · 5 · 500710.1038/ncomms6007 ↗
23. Kim · Mol. Syst. Biol. · 2006 · 2 · 6810.1038/msb4100099 ↗
24. Padirac · Proc. Natl. Acad. Sci. U. S. A. · 2012 · 109 · E321210.1073/pnas.1212069109 ↗
25. Qian · Nature · 2011 · 475 · 36810.1038/nature10262 ↗
26. Stojanovic · Nat. Biotechnol. · 2003 · 21 · 106910.1038/nbt862 ↗
27. Macdonald · Nano Lett. · 2006 · 6 · 259810.1021/nl0620684 ↗
28. Gao · Chem. Sci. · 2016 · 7 · 185310.1039/C5SC03570H ↗
29. Gao · Chem. Sci. · 2017 · 8 · 421110.1039/C7SC00361G ↗
30. Joesaar · Nat. Nanotechnol. · 2019 · 14 · 36910.1038/s41565-019-0399-9 ↗
31. Huang · Chem. – Eur. J. · 2019 · 25 · 699610.1002/chem.201900734 ↗
32. Huang · Nanoscale · 2019 · 11 · 1624110.1039/C9NR05270D ↗
33. Yang · NPG Asia Mater. · 2018 · 10 · 49710.1038/s41427-018-0051-4 ↗
34. Zhong · Chem. Commun. · 2018 · 54 · 131110.1039/C7CC07733E ↗
35. Su · Nat. Commun. · 2019 · 10 · 539010.1038/s41467-019-13310-2 ↗
36. Fan · Nanoscale · 2016 · 8 · 383410.1039/C6NR00032K ↗
37. Zhang · Nanoscale · 2016 · 8 · 1568110.1039/C6NR04762A ↗
38. Zhang · Chem. Commun. · 2018 · 54 · 311010.1039/C8CC00178B ↗
39. Huang · J. Cell Physiol. · 2016 · 231 · 32810.1002/jcp.25135 ↗
40. Catto · Cancer Res. · 2009 · 69 · 847210.1158/0008-5472.CAN-09-0744 ↗