Location: Virus and Prion Research
Title: Mitigating pandemic risk with influenza A virus field surveillance: mia (mobile influenza analysis)Author
BARNES, JOHN - Centers For Disease Control And Prevention (CDC) - United States | |
RAMBO-MARTIN, BENJAMIN - Batelle Natick | |
KELLER, MATTHEW - Oak Ridge Institute For Science And Education (ORISE) | |
WILSON, MALANIA - Centers For Disease Control And Prevention (CDC) - United States | |
NOLTING, JACQUELINE - The Ohio State University | |
Anderson, Tavis | |
BAGAL, UJWAL - Batelle Natick | |
JANG, YUNHO - Centers For Disease Control And Prevention (CDC) - United States | |
DAVIS, C - Centers For Disease Control And Prevention (CDC) - United States | |
BOWMAN, ANDREW - The Ohio State University | |
WENTWORTH, DAVID - Centers For Disease Control And Prevention (CDC) - United States | |
Baker, Amy |
Submitted to: Meeting Abstract
Publication Type: Abstract Only Publication Acceptance Date: 6/1/2019 Publication Date: 9/1/2019 Citation: Barnes, J.R., Rambo-Martin, B.L., Keller, M.W., Wilson, M.M., Nolting, J.M., Anderson, T.K., Bagal, U., Jang, Y., Davis, C.T., Bowman, A.A., Wentworth, D.E., Vincent, A.L. 2019. Mitigating pandemic risk with influenza A virus field surveillance: mia (mobile influenza analysis) [abstract]. Options for the Control of Influenza Conference. Abstract No. 10960. Interpretive Summary: Technical Abstract: Introduction: The unique portability of nanopore sequencing has created new possibilities in the investigation of viral outbreaks by allowing on-site and real-time collection of critical genomic information during an outbreak. However, the necessity to run complex analyses offsite with higher computational power limits the utility of on-site genomic data. We designed a Mobile influenza analysis (Mia) platform to provide genomic information from an outbreak while providing actionable analyses at the site of an influenza outbreak. Methods: We designed the Mia platform to provide genomic information from an outbreak while providing actionable analyses at the site of an influenza outbreak. Working at a large swine exhibition, we collected nasal wipes from 24 swine, purified RNA, amplified the genomes, nanopore-sequenced, and analyzed sequences to obtain genomic data on 13 viruses within 18 hours. Results: Mia successfully sequenced and identified 13 full genomes: 1 H1N1, 1 H3N2, and 11 H1N2-d2 swine lineage viruses. On-site analysis of the H1N2-d2 revealed more than 30 aa differences from the nearest human vaccine candidate. Consensus sequences were sent to CDC for synthetic candidate vaccine virus development. Analysis of other specimens from the show confirm that Mia identified much of the overall influenza diversity seen at the swine exhibition. Further, similar viruses to the H1N2-d2 outbreak detected at the swine exhibition, spread to other swine shows and caused 12 known human infections. Conclusion: We have successfully created Mia, an inexpensive and portable integrated molecular and bioinformatic system for the analysis of influenza A virus outbreaks, and demonstrated its utility in the field. The broad utility of Mia extends beyond field surveillance for pandemic preparedness. Mia may also help in areas where natural disasters have crippled public health infrastructure. Moreover, the affordability and scalability are well suited to initiating public health infrastructure in small or developing countries. |