Journal article
Simultaneous identification of viruses and viral variants with programmable DNA nanobait
- Abstract:
- Respiratory infections are the major cause of death from infectious disease worldwide. Multiplexed diagnostic approaches are essential as many respiratory viruses have indistinguishable symptoms. We created self-assembled DNA nanobait that can simultaneously identify multiple short RNA targets. The nanobait approach relies on specific target selection via toehold-mediated strand displacement and rapid readout via nanopore sensing. Here we show that this platform can concurrently identify several common respiratory viruses, detecting a panel of short targets of viral nucleic acids from multiple viruses. Our nanobait can be easily reprogrammed to discriminate viral variants with single-nucleotide resolution, as we demonstrated for several key SARS-CoV-2 variants. Last, we show that the nanobait discriminates between samples extracted from oropharyngeal swabs from negative- and positive-SARS-CoV-2 patients without preamplification. Our system allows for the multiplexed identification of native RNA molecules, providing a new scalable approach for the diagnostics of multiple respiratory viruses in a single assay.
- Publication status:
- Published
- Peer review status:
- Peer reviewed
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(Preview, Version of record, pdf, 5.8MB, Terms of use)
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- Publisher copy:
- 10.1038/s41565-022-01287-x
Authors
+ European Research Council
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- Funder identifier:
- https://ror.org/0472cxd90
- Grant:
- 899538
+ Biotechnology and Biological Sciences Research Council
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- Funder identifier:
- https://ror.org/00cwqg982
- Grant:
- BB/I006303/1
- Publisher:
- Springer Nature
- Journal:
- Nature Nanotechnology More from this journal
- Volume:
- 18
- Issue:
- 3
- Pages:
- 290-298
- Place of publication:
- England
- Publication date:
- 2023-01-16
- Acceptance date:
- 2022-11-07
- DOI:
- EISSN:
-
1748-3395
- ISSN:
-
1748-3387
- Pmid:
-
36646828
- Language:
-
English
- Pubs id:
-
1322213
- Local pid:
-
pubs:1322213
- Deposit date:
-
2025-01-14
- ARK identifier:
Terms of use
- Copyright holder:
- Bošković et al
- Copyright date:
- 2023
- Rights statement:
- ©2023 The Authors. This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder.
- Licence:
- CC Attribution (CC BY)
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