Improved detection of influenza A virus from blue-winged teals by sequencing directly from swab material.

Guatemala Illumina blue‐winged teal influenza A virus next‐generation sequencing wild bird

Journal

Ecology and evolution
ISSN: 2045-7758
Titre abrégé: Ecol Evol
Pays: England
ID NLM: 101566408

Informations de publication

Date de publication:
Jun 2019
Historique:
received: 29 12 2018
revised: 10 04 2019
accepted: 12 04 2019
entrez: 26 6 2019
pubmed: 27 6 2019
medline: 27 6 2019
Statut: epublish

Résumé

The greatest diversity of influenza A virus (IAV) is found in wild aquatic birds of the orders Anseriformes and Charadriiformes. In these birds, IAV replication occurs mostly in the intestinal tract. Fecal, cloacal, and/or tracheal swabs are typically collected and tested by real-time RT-PCR (rRT-PCR) and/or by virus isolation in embryonated chicken eggs in order to determine the presence of IAV. Virus isolation may impose bottlenecks that select variant populations that are different from those circulating in nature, and such bottlenecks may result in artifactual representation of subtype diversity and/or underrepresented mixed infections. The advent of next-generation sequencing (NGS) technologies provides an opportunity to explore to what extent IAV subtype diversity is affected by virus isolation in eggs. In the present work, we evaluated the advantage of sequencing by NGS directly from swab material of IAV rRT-PCR-positive swabs collected during the 2013-14 surveillance season in Guatemala and compared to results from NGS after virus isolation. The results highlight the benefit of sequencing IAV genomes directly from swabs to better understand subtype diversity and detection of alternative amino acid motifs that could otherwise escape detection using traditional methods of virus isolation. In addition, NGS sequencing data from swabs revealed reduced presence of defective interfering particles compared to virus isolates. We propose an alternative workflow in which original swab samples positive for IAV by rRT-PCR are first subjected to NGS before attempting viral isolation. This approach should speed the processing of samples and better capture natural IAV diversity. This article has earned an Open Data Badge for making publicly available the digitally-shareable data necessary to reproduce the reported results. The data is available at https://doi.org/10.5061/dryad.3h2n106.

Identifiants

pubmed: 31236242
doi: 10.1002/ece3.5232
pii: ECE35232
pmc: PMC6580304
doi:

Banques de données

Dryad
['10.5061/dryad.3h2n106']

Types de publication

Journal Article

Langues

eng

Pagination

6534-6546

Subventions

Organisme : NIAID NIH HHS
ID : HHSN272201400006C
Pays : United States
Organisme : NIAID NIH HHS
ID : HHSN272201400008C
Pays : United States

Déclaration de conflit d'intérêts

None declared.

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Auteurs

Lucas M Ferreri (LM)

Poultry Diagnostic and Research Center, Department of Population Health, College of Veterinary Medicine University of Georgia Athens Georgia.

Lucia Ortiz (L)

Poultry Diagnostic and Research Center, Department of Population Health, College of Veterinary Medicine University of Georgia Athens Georgia.
Centro de Estudios en Salud Universidad del Valle de Guatemala Guatemala City Guatemala.

Ginger Geiger (G)

Poultry Diagnostic and Research Center, Department of Population Health, College of Veterinary Medicine University of Georgia Athens Georgia.

Gonzalo P Barriga (GP)

Laboratory of Emerging Viruses, Virology Program Institute of Biomedical Sciences, Faculty of Medicine Universidad de Chile Santiago Chile.

Rebecca Poulson (R)

Southeastern Cooperative Wildlife Disease Study, Department of Population Health, College of Veterinary Medicine University of Georgia Athens Georgia.

Ana Silvia Gonzalez-Reiche (AS)

Department of Genetics and Genomic Sciences Icahn School of Medicine at Mount Sinai New York New York.

Jo Anne Crum (JA)

Southeastern Cooperative Wildlife Disease Study, Department of Population Health, College of Veterinary Medicine University of Georgia Athens Georgia.

David Stallknecht (D)

Southeastern Cooperative Wildlife Disease Study, Department of Population Health, College of Veterinary Medicine University of Georgia Athens Georgia.

David Moran (D)

Centro de Estudios en Salud Universidad del Valle de Guatemala Guatemala City Guatemala.

Celia Cordon-Rosales (C)

Centro de Estudios en Salud Universidad del Valle de Guatemala Guatemala City Guatemala.

Daniela Rajao (D)

Poultry Diagnostic and Research Center, Department of Population Health, College of Veterinary Medicine University of Georgia Athens Georgia.

Daniel R Perez (DR)

Poultry Diagnostic and Research Center, Department of Population Health, College of Veterinary Medicine University of Georgia Athens Georgia.

Classifications MeSH