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Programmable pH-Triggered DNA Nanoswitches
Open accessAbstract
We have designed programmable DNA-based nanoswitches whose closing/opening can be triggered over specific different pH windows. These nanoswitches form an intramolecular triplex DNA structure through pH-sensitive parallel Hoogsteen interactions. We demonstrate that by simply changing the relative content of TAT/CGC triplets in the switches, we can rationally tune their pH dependence over more than 5 pH units. The ability to design DNA-based switches with tunable pH dependence provides the opportunity to engineer pH nanosensors with unprecedented wide sensitivity to pH changes. For example, by mixing in the same solution three switches with different pH sensitivity, we developed a pH nanosensor that can precisely monitor pH variations over 5.5 units of pH. With their fast response time (<200 ms) and high reversibility, these pH-triggered nanoswitches appear particularly suitable for applications ranging from the real-time monitoring of pH changes in vivo to the development of pH sensitive smart nanomaterials.
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Seeman, N. C. (2010) · Annual Review of Biochemistry · doi:10.1146/annurev-biochem-060308-102244 · Cited by 992
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Zhao, J., Gao, J., Xue, W., Di, Z., Xing, H., Lu, Y., & Li, L. (2018) · Journal of the American Chemical Society · doi:10.1021/jacs.7b11161 · Cited by 361
Triplex DNA Nanostructures: From Basic Properties to Applications
Hu, Y., Cecconello, A., Idili, A., Ricci, F., & Willner, I. (2017) · Angewandte Chemie International Edition · doi:10.1002/anie.201701868 · Cited by 336
Self-citationZhou, Z., Vázquez-González, M., & Willner, I. (2021) · Chemical Society Reviews · doi:10.1039/d0cs01030h · Cited by 308
Metadata
- Authors
- Idili, A., Vallée-Bélisle, A., & Ricci, F.
- Venue
- Journal of the American Chemical Society
- Publisher
- American Chemical Society (ACS)
- Published
- 2014-04-09
- Volume
- 136
- Issue
- 16
- Pages
- 5836-5839
- ISSN
- 0002-7863 (ISSN-L)
- 1520-5126
- OpenAlex
- W2327048176
- Cited by
- 356
- References
- 1
- FWCI
- 10.34
- Type
- journal article
- Language
- en
- Open access
- green
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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).
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