Back

Integrated antigenic and nucleic acid detection in single virions and virion-infected host-derived extracellular vesicles

Nguyen, K. T.; Rima, X. Y.; Nguyen, L. T. H.; Wang, X.; Kwak, K. J.; Yoon, M. J.; Li, H.; Chiang, C.-L.; Doon-Ralls, J.; Scherler, K.; Fallen, S.; Godfrey, S. L.; Wallick, J. A.; Magana, S. M.; Palmer, A. F.; Lee, I.; Nunn, C. C.; Reeves, K. M.; Kaplan, H. G.; Goldman, J.; Heath, J. R.; Wang, K.; Pancholi, P.; Lee, L. J.; Reategui, E.

2023-09-02 infectious diseases
10.1101/2023.08.31.23292825 medRxiv
Show abstract

Virion-mediated outbreaks are imminent and despite rapid responses, they continue to cause adverse symptoms and death. Therefore, tunable, sensitive, high-throughput assays are needed to control future virion-mediated outbreaks. Herein, we developed a tunable in situ assay to selectively sort virions and infected host-derived extracellular vesicles (IHD-EVs) and simultaneously detect antigens and nucleic acids at a single-particle resolution. The Biochip Antigen and RNA Assay (BARA) enhanced sensitivities, enabling the detection of virions in asymptomatic patients, genetic mutations in single virions, and the continued long-term expression of virion-RNA in the IHD-EVs of post-acute sequelae of COVID-19 patients. The BARA revealed highly accurate diagnoses by simultaneously detecting the spike glycoprotein and nucleocapsid-encoding RNA on single SARS-CoV-2 virions in saliva and nasopharyngeal swab samples. Altogether, the single-particle detection of antigens and virion-RNA provides a tunable framework for the diagnosis, monitoring, and mutation screening of current and future outbreaks. TeaserThe BARA enables antigenic and nucleic acid testing in single virions for unprecedented perspectives on viral diseases

Matching journals

The top 9 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.