North Atlantic Migratory Bird Flyways Provide Routes for Intercontinental Movement of Avian Influenza Viruses

<div><p>Avian influenza virus (AIV) in wild birds has been of increasing interest over the last decade due to the emergence of AIVs that cause significant disease and mortality in both poultry and humans. While research clearly demonstrates that AIVs can move across the Pacific or Atlantic Ocean, there has been no data to support the mechanism of how this occurs. In spring and autumn of 2010 and autumn of 2011 we obtained cloacal swab samples from 1078 waterfowl, gulls, and shorebirds of various species in southwest and west Iceland and tested them for AIV. From these, we isolated and fully sequenced the genomes of 29 AIVs from wild caught gulls (Charadriiformes) and waterfowl (Anseriformes) in Iceland. We detected viruses that were entirely (8 of 8 genomic segments) of American lineage, viruses that were entirely of Eurasian lineage, and viruses with mixed American-Eurasian lineage. Prior to this work only 2 AIVs had been reported from wild birds in Iceland and only the sequence from one segment was available in GenBank. This is the first report of finding AIVs of entirely American lineage and Eurasian lineage, as well as reassortant viruses, together in the same geographic location. Our study demonstrates the importance of the North Atlantic as a corridor for the movement of AIVs between Europe and North America.</p></div

Figure 2

<p>A. Map showing position of Iceland relative to the East Atlantic Flyway (red arrows) and the North American Atlantic Flyway (yellow arrows). Flyways represent generalized migration movements of birds with most using only portions of the flyways. Actual regions of flyways used by migratory birds are dependent on species and breeding population. B. Map of Iceland depicting bird sampling locations (red dots) used in this study and Reykjavik (red star) is provided for reference. Breiðafjörður and Selfoss sampling locations are generalized as samples provided by hunters and fisherman were obtained over a larger area within these marked regions.</p

Viruses recovered from Iceland wild birds in 2010–2011 with segment lineage detail.

<p>EU denotes the segment is most similar to Eurasian lineage viruses, AM denotes the segment is most similar to American lineage viruses. Within each segment column, segments that have the same color indicate a ≥99% nucleotide sequence similarity among that segment. * indicates a ≥99% similarity to only one other virus segment of the same color denoted by †. Bold text indicates novel virus assemblages.</p

Patterns of viral migration jointly estimated across the 5 internal protein gene segments.

<p>Lines connecting discrete regions indicate statistically supported ancestral state changes and are thickened according to statistical support. There are five categories of support. The thinnest lines indicate 6≤BF&lt;10 (supported); 10≤BF&lt;30 (strong support); 30≤BF&lt;100 (very strong support) and the thickest lines with BF≤100 (decisive support). Dashed lines indicate statistical supports between 3≤BF&lt;6 but with posterior probabilities &lt;0.5.</p

A) H3-HA phylogenetic tree for isolates from Alberta.

<p><b>B) H3-HA phylogenetic tree for isolates from Delaware Bay.</b> C) H3-HA phylogenetic tree for isolates from Alaska. D) Multidimensional scaling of tree-to-tree TMRCA estimates from Alberta. For reference, the space occupied by human H3N2 viruses from similar analysis is centered (grey circle). E) Multidimensional scaling of tree-to-tree patristic distance from Delaware Bay. F) Multidimensional scaling of tree-to-tree patristic distance from Alaska.</p

Bayesian relaxed clock HA gene phylogenetic tree from all H3 wild bird isolates in North America.

<p>The two co-circulating North American lineages (I and II) are annotated to the right of the tree. Branches are colored according to ancestral state location estimated from geographical tip-state observations for all observed localities.</p

A) Mean migration rate per MCMC step within flyway migration rates vs Mean between flyway migration jointly estimated from all publically available PA, PB1, PB2, NP and M gene segments.

<p>B) Density distribution of mean within flyway and mean between flyway rates.</p

Statistically supported state transitions indicating migratory events.

ψ<p>State Transition between the “Other” and Texas was supported once in our analysis (BF = 64, I = 88) likely due to the broad taxonomic sampling included in the “Other” state and phylogenetic uncertainty in estimating migration.</p>†<p>The indicator is the posterior probability of observing non-zero migration rates in the Bayesian sampled trees.</p>*<p>Bayes factor greater than 6 with indicator value greater than 0.50 was the minimum criteria for significance; 6≤BF&lt;10 statistically significant; 10≤BF&lt;30 strong statistical support; 30≤BF&lt;100 very strongly supported; BF≥100 decisive.</p

Standardized Metadata for Human Pathogen/Vector Genomic Sequences

<div><p>High throughput sequencing has accelerated the determination of genome sequences for thousands of human infectious disease pathogens and dozens of their vectors. The scale and scope of these data are enabling genotype-phenotype association studies to identify genetic determinants of pathogen virulence and drug/insecticide resistance, and phylogenetic studies to track the origin and spread of disease outbreaks. To maximize the utility of genomic sequences for these purposes, it is essential that metadata about the pathogen/vector isolate characteristics be collected and made available in organized, clear, and consistent formats. Here we report the development of the GSCID/BRC Project and Sample Application Standard, developed by representatives of the Genome Sequencing Centers for Infectious Diseases (GSCIDs), the Bioinformatics Resource Centers (BRCs) for Infectious Diseases, and the U.S. National Institute of Allergy and Infectious Diseases (NIAID), part of the National Institutes of Health (NIH), informed by interactions with numerous collaborating scientists. It includes mapping to terms from other data standards initiatives, including the Genomic Standards Consortium’s minimal information (MIxS) and NCBI’s BioSample/BioProjects checklists and the Ontology for Biomedical Investigations (OBI). The standard includes data fields about characteristics of the organism or environmental source of the specimen, spatial-temporal information about the specimen isolation event, phenotypic characteristics of the pathogen/vector isolated, and project leadership and support. By modeling metadata fields into an ontology-based semantic framework and reusing existing ontologies and minimum information checklists, the application standard can be extended to support additional project-specific data fields and integrated with other data represented with comparable standards. The use of this metadata standard by all ongoing and future GSCID sequencing projects will provide a consistent representation of these data in the BRC resources and other repositories that leverage these data, allowing investigators to identify relevant genomic sequences and perform comparative genomics analyses that are both statistically meaningful and biologically relevant.</p></div

Core Sample Attributes.

<p>*Mandatory NCBI BioSample attributes in the “Pathogen: clinical or host-associated” version 1.0 package.</p