An open-source, automated, and cost-effective platform for COVID-19 diagnosis and rapid portable genomic surveillance using nanopore sequencing.
Journal
Scientific reports
ISSN: 2045-2322
Titre abrégé: Sci Rep
Pays: England
ID NLM: 101563288
Informations de publication
Date de publication:
21 Nov 2023
21 Nov 2023
Historique:
received:
09
05
2023
accepted:
10
11
2023
medline:
23
11
2023
pubmed:
22
11
2023
entrez:
22
11
2023
Statut:
epublish
Résumé
The COVID-19 pandemic, caused by SARS-CoV-2, has emphasized the necessity for scalable diagnostic workflows using locally produced reagents and basic laboratory equipment with minimal dependence on global supply chains. We introduce an open-source automated platform for high-throughput RNA extraction and pathogen diagnosis, which uses reagents almost entirely produced in-house. This platform integrates our methods for self-manufacturing magnetic nanoparticles and qRT-PCR reagents-both of which have received regulatory approval for clinical use-with an in-house, open-source robotic extraction protocol. It also incorporates our "Nanopore Sequencing of Isothermal Rapid Viral Amplification for Near Real-time Analysis" (NIRVANA) technology, designed for tracking SARS-CoV-2 mutations and variants. The platform exhibits high reproducibility and consistency without cross-contamination, and its limit of detection, sensitivity, and specificity are comparable to commercial assays. Automated NIRVANA effectively identifies circulating SARS-CoV-2 variants. Our in-house, cost-effective reagents, automated diagnostic workflows, and portable genomic surveillance strategies provide a scalable and rapid solution for COVID-19 diagnosis and variant tracking, essential for current and future pandemic responses.
Identifiants
pubmed: 37990068
doi: 10.1038/s41598-023-47190-w
pii: 10.1038/s41598-023-47190-w
pmc: PMC10663496
doi:
Substances chimiques
RNA, Viral
0
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
20349Subventions
Organisme : King Abdullah University of Science and Technology
ID : BAS/1/1080-01
Organisme : King Abdullah University of Science and Technology
ID : BAS/1/1080-01
Organisme : King Abdullah University of Science and Technology
ID : URF/1/1976-36
Organisme : King Abdullah University of Science and Technology
ID : BAS/1/1080-01
Organisme : King Abdullah University of Science and Technology
ID : BAS/1/1080-01
Organisme : King Abdullah University of Science and Technology
ID : URF/1/1976-36
Organisme : King Abdullah University of Science and Technology
ID : BAS/1/1080-01
Organisme : King Abdullah University of Science and Technology
ID : URF/1/1976-36
Informations de copyright
© 2023. The Author(s).
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