Journal article icon

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

Actions

Access Document

Publisher copy:
10.1038/s41565-022-01287-x

Authors

More by this author
Role:
Author
ORCID:
0000-0001-7663-2408
More by this author
Role:
Author
ORCID:
0000-0003-4935-825X
More by this author
Role:
Author
ORCID:
0000-0003-0331-9538
More by this author
Role:
Author
ORCID:
0000-0003-3537-1074
More by this author
Role:
Author
ORCID:
0000-0003-3170-0336


More from this funder
Funder identifier:
https://ror.org/0472cxd90
Grant:
899538
More from this funder
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


Views and Downloads






If you are the owner of this record, you can report an update to it here: Report update to this record

TO TOP