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Application of phylogeography to reconstruct Equine influenza virus migration on a global and a US scale

Lee Kyuyoung1*, Nicola Pusterla1, Samantha M. Barnum1 and Beatriz Martínez-López1*
  • 1 Department of Medicine & Epidemiology, School of Veterinary Medicine, University of California, Davis, United States

Equine influenza virus (EIV) is a significant infectious pathogen causing upper respiratory signs in equids. EIV has globally spread through direct contacts with infectious horses by international movements and resulted in persistent financial losses for the global equine industry.[1] Since 1980s, H3N8 subtype has been recognizant as the only subtype and recently diverged into two dominant clades[2], Florida sub-lineage clade 1 (FC1) and clade 2 (FC2)[3–5]. Phylogenetic analysis based on genome-informed diagnosis of pathogen has been applied to evaluate genetic closeness between identifed pathogen and identify a potential source of transmission. Phylodynamics expands the capacity of phylogenetic analysis to recontruct the spread of pathogen by the estimation of the divergence time and ancestral character of pathogen based on epidemiological data[6–8]. Current phylogenetic studies of EIV H3N8 on a global scale explored the genetic closeness of EIV H3N8 strains identified until 2011[4,9]. Our research updated current understanding of global EIV H3N8 phylogeny based on HA gene sequence identified until 2017. Furthermore, we reconstructed EIV H3N8 spread on a global and a US scale by Bayesian phylogeography. Our present research will inform EIV circulation patterns on a global and a US scale and provide meaningful insights to establish risk-based preventive and control strategies of EIV spread within and out of the US. Our study reviewed 241 EIV H3N8 positive submissions in the US from 2012 to 2017 diagnosed in the school of veterinary medicine at the University of California, Davis. A total of 70 EIV positive cases were randomly selected from strata of year and state and HA genes of these samples was sequenced by ABI 3730 capillary electrophoresis genetic analyzers. A total 12 of EIV samples failed to identify HA gene sequences and remaining 58 EIV HA gene sequences were involved in our research. A total of 276 HA gene sequences and their information about states (or country) and time of isolation of globally identified EIV H3N8 from 1963 to 2017 were collected from two global influenza genetic information repositories, the Global Initiative on Sharing All Influenza Data (GISAID) and the Influenza Research Database (IRD). HA gene sequences collected from the same state (or country) within a week and showing high similarity in nucleotide sequences were grouped and only one representative sequence was selected within each group. Finally, A total of 240 EIV representatives (58 US field HA sequences + 182 published HA sequences) were finally selected in our phylogenetic analysis. A total 67 EIV strains of 5 regions (Asia, Europe, Africa, North America and South America) on a global scale and 44 EIV strains of 4 US regions (Northwest, Midwest, South and West regions) on a US scale were re-sampled for the phylogeography on a global and a US scale, based on the number of horses in each region. MUtiple Sequence Comparison by Log-Expectation on the Molecular Evolutionary Genetic Analysis were used to align HA sequences on a global and a US scale. Finally, two alignments with 1692 base-pair were estimated in our study. The best-fit phylogenetic model of alignments was selected by Bayes factor and the marginal likelihoods of candidate models were estimated by the stepping stone simulation[10] on RevBayes [V1.1.11][11]. The final model for molecular clock model in both alignment was Hasegawa-Kishino-Yano (HKY) with among-site gamma-distributed rate variation (+Γ, 8 categories) in codon position partition model (1st & 2nd + 3rd partition) with the uncorrelated lognormal relaxed-clock model (UCLN) and coalescent node prior model. The asymmetrical Q-matrix model was selected as the best-fit model of ancestral state estimation for phylogeography. Bayesian Markov chain Monte Carlo (MCMC) Metropolis-Hastings Algorithm was used for the estimation of phylogenies of the molecular clock model and phylogeography on RevBayes. The convergence and mixing of MCMC chains evaluated the reliability of MCMC by Effective sample size (ESS) and tracer plot for every parameter on Tracer [V1.7][12]. Phylogenetic diffusion analysis for temporary phylogeography will use the maximum clade credibility (MCC) tree of molecular clock model to estimate the posterior probability of 5 regions on a global scale and 4 regions on a US scale as an ancestral character and the results will be visualized on SPREAD [v1.0.7][13]. Phylogenetic analysis showed that most EIV H3N8 strains identified in the US were classified into FC 1. EIV H3N8 FC 2 mostly circulated in European countries and spread to China, Mongolia and India. The only one US EIV H3N8 strain classified into FC 2 was isolated from a horse imported from Germany and quarantined at an US import facility[14]. Our result of phylogeography indicates that EIV H3N8 FC1 mostly circulated in the US would have spread four times to Asia (Dubai/2012, Malaysia/2015 and Yokohama/2011 and 2017), once to Europe (Sweden/2011) and once to South America in 2012. Our research illustrates the value of the application of phylodynamics including field data, and global repositories containing both genetic and epidemiological information and provides meaningful insights to establish rapid and effective preventive measures against international and US EIV spreads.

Acknowledgements

This study was supported by the 2017-18 research grant from the Center for Equine Health and fellowship of the graduate student support program at UC Davis.

References

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Keywords: Equine influenza virus (EIV), phylogentic, Bayesian Phylodynamics, Molecular Epidemiology, Molecular clock analysis, Phylogeograpy, RevBayes

Conference: GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data, Davis, United States, 8 Oct - 10 Oct, 2019.

Presentation Type: Regular oral presentation

Topic: Spatio-temporal phylogenetic approaches, phylogeography and phylodynamics

Citation: Kyuyoung L, Pusterla N, Barnum SM and Martínez-López B (2019). Application of phylogeography to reconstruct Equine influenza virus migration on a global and a US scale. Front. Vet. Sci. Conference Abstract: GeoVet 2019. Novel spatio-temporal approaches in the era of Big Data. doi: 10.3389/conf.fvets.2019.05.00029

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Received: 11 Jun 2019; Published Online: 27 Sep 2019.

* Correspondence:
DVM. Lee Kyuyoung, Department of Medicine & Epidemiology, School of Veterinary Medicine, University of California, Davis, Davis, CA 95616, United States, pvmlee@ucdavis.edu
DVM, PhD. Beatriz Martínez-López, Department of Medicine & Epidemiology, School of Veterinary Medicine, University of California, Davis, Davis, CA 95616, United States, beamartinezlopez@ucdavis.edu