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Viral infections are a major global health issue, but no current method allows rapid, direct, and ultrasensitive quantification of intact viruses with the ability to inform infectivity, causing misdiagnoses and spread of the viruses. Here, we report a method for direct detection and differentiation of infectious from noninfectious human adenovirus and SARS-CoV-2, as well as from other virus types, without any sample pretreatment. DNA aptamers are selected from a DNA library to bind intact infectious, but not noninfectious, virus and then incorporated into a solid-state nanopore, which allows strong confinement of the virus to enhance sensitivity down to 1 pfu/ml for human adenovirus and 1 × 10 4 copies/ml for SARS-CoV-2. Applications of the aptamer-nanopore sensors in different types of water samples, saliva, and serum are demonstrated for both enveloped and nonenveloped viruses, making the sensor generally applicable for detecting these and other emerging viruses of environmental and public health concern.
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This content will become publicly available on December 11, 2025
Matrix-Insensitive Sensor Arrays via Peptide-Coated Nanoparticles: Rapid Saliva Screening for Pathogens in Oral and Respiratory Diseases
Plasmonic nanoparticle-based biosensors often report a colorimetric signal through the aggregation or clustering of the nanoparticles (NPs), but these mechanisms typically struggle to function in complex biofluids. Here, we report a matrixinsensitive sensor array approach to detect bacteria, fungi, and viruses whose signal is based on the dissociation of the peptideaggregated NPs by thiolated polyethylene glycol (HS-PEG) polymers. We show that the HS-PEGs of differing sizes have varying capabilities to dissociate citrate-capped gold nanoparticle (AuNP) and silver nanoparticle (AgNP) assemblies. The dissociative abilities of the HS-PEGs were used in this sensor array to discriminate at the 90% confidence level the microorganisms Porphyromonas gingivalis, Fusobacterium nucleatum, and Candida albicans in water and saliva using linear discriminant analysis (LDA). We further demonstrate the versatility of the sensor array by detecting various subtypes of the viruses SARS-CoV-2 (beta, delta, and omicron) and influenza (H3N2) spiked in saliva samples using LDA. In the final demonstration, the sensor array design stratified healthy saliva samples from patient samples diagnosed with periodontitis as well as COVID-19.
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- Award ID(s):
- 2011924
- PAR ID:
- 10589228
- Publisher / Repository:
- ACS
- Date Published:
- Journal Name:
- ACS Applied Materials & Interfaces
- Volume:
- 16
- Issue:
- 49
- ISSN:
- 1944-8244
- Page Range / eLocation ID:
- 67362 to 67372
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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