Evaluation of Commercial RNA Extraction Protocols for Avian Influenza Virus Using Nanopore Metagenomic Sequencing.


Journal

Viruses
ISSN: 1999-4915
Titre abrégé: Viruses
Pays: Switzerland
ID NLM: 101509722

Informations de publication

Date de publication:
07 Sep 2024
Historique:
received: 24 07 2024
revised: 21 08 2024
accepted: 04 09 2024
medline: 29 9 2024
pubmed: 28 9 2024
entrez: 28 9 2024
Statut: epublish

Résumé

Avian influenza virus (AIV) is a significant threat to the poultry industry, necessitating rapid and accurate diagnosis. The current AIV diagnostic process relies on virus identification via real-time reverse transcription-polymerase chain reaction (rRT-PCR). Subsequently, the virus is further characterized using genome sequencing. This two-step diagnostic process takes days to weeks, but it can be expedited by using novel sequencing technologies. We aim to optimize and validate nucleic acid extraction as the first step to establishing Oxford Nanopore Technologies (ONT) as a rapid diagnostic tool for identifying and characterizing AIV from clinical samples. This study compared four commercially available RNA extraction protocols using AIV-known-positive clinical samples. The extracted RNA was evaluated using total RNA concentration, viral copies as measured by rRT-PCR, and purity as measured by a 260/280 absorbance ratio. After NGS testing, the number of total and influenza-specific reads and quality scores of the generated sequences were assessed. The results showed that no protocol outperformed the others on all parameters measured; however, the magnetic particle-based method was the most consistent regarding C

Identifiants

pubmed: 39339905
pii: v16091429
doi: 10.3390/v16091429
pii:
doi:

Substances chimiques

RNA, Viral 0

Types de publication

Journal Article Evaluation Study

Langues

eng

Sous-ensembles de citation

IM

Subventions

Organisme : United States Department of Agriculture
ID : AP22VSD&B000C010

Auteurs

Maria Chaves (M)

Department of Veterinary Diagnostic and Production Animal Medicine, College of Veterinary Medicine, Iowa State University, Ames, IA 50011, USA.

Amro Hashish (A)

Department of Veterinary Diagnostic and Production Animal Medicine, College of Veterinary Medicine, Iowa State University, Ames, IA 50011, USA.
National Laboratory for Veterinary Quality Control on Poultry Production, Giza 12618, Egypt.

Onyekachukwu Osemeke (O)

Department of Veterinary Diagnostic and Production Animal Medicine, College of Veterinary Medicine, Iowa State University, Ames, IA 50011, USA.

Yuko Sato (Y)

Department of Veterinary Diagnostic and Production Animal Medicine, College of Veterinary Medicine, Iowa State University, Ames, IA 50011, USA.

David L Suarez (DL)

US National Poultry Research Center, Agricultural Research Service, US Department of Agriculture, Athens, GA 30605, USA.

Mohamed El-Gazzar (M)

Department of Veterinary Diagnostic and Production Animal Medicine, College of Veterinary Medicine, Iowa State University, Ames, IA 50011, USA.

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Classifications MeSH