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A rapid and label-free platform for virus capture and identification from clinical samples.

Abstract：

:Emerging and reemerging viruses are responsible for a number of recent epidemic outbreaks. A crucial step in predicting and controlling outbreaks is the timely and accurate characterization of emerging virus strains. We present a portable microfluidic platform containing carbon nanotube arrays with differential filtration porosity for the rapid enrichment and optical identification of viruses. Different emerging strains (or unknown viruses) can be enriched and identified in real time through a multivirus capture component in conjunction with surface-enhanced Raman spectroscopy. More importantly, after viral capture and detection on a chip, viruses remain viable and get purified in a microdevice that permits subsequent in-depth characterizations by various conventional methods. We validated this platform using different subtypes of avian influenza A viruses and human samples with respiratory infections. This technology successfully enriched rhinovirus, influenza virus, and parainfluenza viruses, and maintained the stoichiometric viral proportions when the samples contained more than one type of virus, thus emulating coinfection. Viral capture and detection took only a few minutes with a 70-fold enrichment enhancement; detection could be achieved with as little as 102 EID50/mL (50% egg infective dose per microliter), with a virus specificity of 90%. After enrichment using the device, we demonstrated by sequencing that the abundance of viral-specific reads significantly increased from 4.1 to 31.8% for parainfluenza and from 0.08 to 0.44% for influenza virus. This enrichment method coupled to Raman virus identification constitutes an innovative system that could be used to quickly track and monitor viral outbreaks in real time.

journal_name

Proc Natl Acad Sci U S A

journal_title

Proceedings of the National Academy of Sciences of the United States of America

authors

Yeh YT,Gulino K,Zhang Y,Sabestien A,Chou TW,Zhou B,Lin Z,Albert I,Lu H,Swaminathan V,Ghedin E,Terrones M

doi

10.1073/pnas.1910113117

subject

Has Abstract

pub_date

2020-01-14 00:00:00

pages

895-901

issue

eissn

0027-8424

issn

1091-6490

pii

1910113117

journal_volume

117

pub_type

杂志文章

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A rapid and label-free platform for virus capture and identification from clinical samples.