Automated Quantification and Description of the Evolutionary Patterns of Influenza Viruses in U.S. Swine

Transcription

1 Automated Quantification and Description of the Evolutionary Patterns of Influenza Viruses in U.S. Swine Spatial dissemination of a novel H3 influenza A Swine influenza A epidemic peaks

2 Influenza A virus in swine Negative-sense, single-stranded RNA virus Subtype name derived from HA and NA number Swine H1N1, H1N2, and H3N2 HA is target of neutralizing antibodies Antigenic drift Co-infection and reassortment Antigenic shift

3 Consequence of infection Increased mortality Reduced feed efficiency Susceptibility to secondary infection Public health: economic loss associated with perception of swine-origin IAV e.g., swine-origin 2009 pandemic resulted in ~200,000 deaths and ~$1.6 billion cost to swine industry What can we do to minimize the IAV problem?

4 Classify and determine components for vaccines Vincent, Lager, & Anderson (2014)

5 Goal of USDA swine IAV surveillance 1. Develop a baseline for monitoring the evolution, emergence, and spread of new genetic and antigenic subtypes 2. Use evidence of known swine IAV diversity for vaccine strain selection and diagnostics USDA-ARS-NADC (Dr. Amy Vincent and Vincent lab) USDA-APHIS, National Animal Health Laboratory Network (NAHLN), swine producers and veterinarians All data and analyses available in open-access publications or on the USDA-APHIS Swine Health Monitoring Surveillance webpage

6 USDA Surveillance System Structure Implemented in November 2009 ~40 participating labs Passive surveillance HA and NA sequenced: major vaccine components

7 Rapid adoption 1200 Swine IAV HA sequences pre * Anderson et al. (2013) IRV Anderson et al. (2015) Virus Res.

8 and good spatial coverage Anderson et al. (2013) IRV

9 What can we do with these data? Determine when we should vaccinate: Time series and seasonality Determine what we should vaccinate with: subtypes: H1N1, H1N2, and H3N2 genetic diversity and vaccine strains variation from region to region

10 Are there patterns in the genetic diversity observed in North American swine IAV?

11 Phylogenetic relationships of H1 swine influenza viruses Phylogenetic clade H1α H1β H1γ H1γ-2 H1N1pdm09 H1δ1 H1δ2 ~3000 HA genes

12 Phylogenetic relationships of H3 swine influenza viruses Phylogenetic clade HumanLike H3 Cluster I Cluster III Cluster IV Cluster IV-A Cluster IV-B Cluster IV-C Cluster IV-D Cluster IV-E Cluster IV-F ~2000 HA genes

13 USA HA and NA diversity 4 major genetic clades = potentially feasible vaccine Walia et al. (in review)

14 Are there spatial patterns in the genetic diversity observed in North American swine IAV?

15 Spatial patterns in genetic diversity Region 4 Region 2 Region 5 Region 3 Region 1

16 US does not equal regional diversity Region 4 Region 5 Region 2 Region 1 Region 3 Walia et al. (in review)

17 and new variants are constantly emerging Anderson et al. (2015) Virus Res.

18 Summary Surveillance system provides critical data on genetic diversity of circulating swine IAV. 4 major HA/NA pairings Data suggest tailored regional intervention solutions are necessary New variants appear to constantly emerge

19 Can we automate our classification process and describe endemic diversity AND identify novel viruses of concern?

20 Feature identification and classification + + Evolutionary history + genetic distance within and between clade + amino acids

21 Phylogenetic relationships of global H1 swine influenza viruses Anderson et al. (2016) msphere

22 Classification using a phylogenetic scaffold ~35,000 sequences down to ~ % accuracy Available on Anderson et al. (2016) msphere

23 Phylogenetic baseball and classification rules vs 99.4% accuracy Available on Anderson et al. (2016) msphere

24 Search by: state, host, time, genetic clade or classify your unknown data Influenza Research Database Catherine Macken (Auckland) Richard Scheuermann (JCVI) Yun Zhang (JCVI)

25 Integration with the front line: Iowa State University VDL Phillip Gauger (ISU VDL) Michael Zeller (ISU VDL) ISU Presidential Initiative in Data Driven Science ISU Veterinary Diagnostic Laboratory Zeller et al. (in prep)

26 Impact: successfully identifying an unknown Swine influenza A virus lineage Other Hu-like swine H3 Cluster I swine H3 Cluster II swine H3 Cluster IV swine H3 Human seasonal H3 Human seasonal H3 vaccine Hu-like swine H

27 Impact: determining the transmission routes January 2013

28 Impact: determining the transmission routes January 2014

29 Impact: determining the transmission routes May 2015

30 Impact: determining the transmission routes August 2015

31 Impact: determining the transmission routes January 2016

32 Impact: determining the transmission routes August 2016

33 Impact: making a recommendation to update vaccines Generation PB2 PB1 PA HA NP NA M NS H1N1 pandemic TRIG Human seasonal N2 Classical swine N swine N2 Human seasonal H3

34 Impact: making a recommendation to update vaccines

35 Impact: making a recommendation to update vaccines

36 Conclusion Surveillance system provides critical data on genetic diversity of circulating swine IAV. These data (temporal and spatial) allow us to make informed decisions on: vaccine strain selection; and animal and public health management. Automated classification tool on Influenza Research Database Interactive near real-time trends available at ISU VDL FLUture All data and analyses available in open-access publications or on the USDA-APHIS Swine Health Monitoring Surveillance webpage

37 Acknowledgements USDA-ARS-NADC: Amy Vincent and the Vincent lab, Rasna Walia, Daniela Rajao, Eugenio Abente IRD: Catherine Macken (University of Auckland), Richard Scheuermann and Yun Zhang (JCVI) Cambridge: Nicola Lewis; Iowa State University: Phillip Gauger, Michael Zeller USDA-APHIS-NVSL: Ellen Kasari, John Korslund, John Schiltz, Sabrina Swenson, Bev Schmitt, Alicia Janas-Martindale, Mary Lea Killian The National Animal Health Laboratory Network Swine Producers and Veterinarians Funding: USDA-ARS Research Participation Program (ORISE), USDA-ARS, USDA-APHIS, NIH CEIRS

38 Cocirculating swine IAV subtypes

39 Swine IAV subtype time series

40 Part of a global swine IAV initiative Network of expertise on animal influenza 9 countries, 14 institutions The classification and identification initiative led by USDA-ARS Amy Vincent, Catherine Macken, Nicola Lewis, Richard Scheuermann, Kristien Van Reeth, Ian Brown, Sabrina Swenson, Gaëlle Simon, Takehiko Saito, Yohannes Berhane, Janice Ciacci-Zanella, Ariel Pereda, C. Todd Davis, Ruben Donis, Richard Webby.

41 But diversity constantly increases with interspecies transmission Vincent, Lager, & Anderson (2014)