Development and Validation of a Quantitative Polymerase Chain Reaction Assay for the Detection of Red Sea Bream Iridovirusopen access
- Authors
- Kim, Kyung-Ho; Choi, Kwang-Min; Kang, Gyoungsik; Woo, Won-Sik; Sohn, Min-Young; Son, Ha-Jeong; Yun, Dongbin; Kim, Do-Hyung; Park, Chan-Il
- Issue Date
- Oct-2022
- Publisher
- MDPI AG
- Keywords
- red sea bream iridovirus; diagnostic performance; TaqMan-based real-time PCR; Megalocytivirus; sensitivity; specificity
- Citation
- Fishes, v.7, no.5
- Indexed
- SCIE
SCOPUS
- Journal Title
- Fishes
- Volume
- 7
- Number
- 5
- URI
- https://scholarworks.gnu.ac.kr/handle/sw.gnu/29460
- DOI
- 10.3390/fishes7050236
- ISSN
- 2410-3888
- Abstract
- The analytical and diagnostic performances of methods for detecting red sea bream iridovirus (RSIV), which infects marine fish, have not been evaluated. As disease management and transmission control depend on early and reliable pathogen detection, rapid virus detection techniques are crucial. Herein, we evaluated the diagnostic performance of a TaqMan-based real-time polymerase chain reaction (PCR) assay that detects RSIV rapidly and accurately. The assay amplified the RSIV, infectious spleen and kidney necrosis virus, and turbot reddish body iridovirus genotypes of Megalocytivirus and the detection limit was 10.96 copies/reaction. The assay's performance remained uncompromised even in the presence of nine potential PCR inhibitors, including compounds commonly used in aquaculture. The variation of the cycle threshold values between assays performed by three technicians was evaluated using a plasmid DNA containing the major capsid protein gene sequence. The variation between replicates was low. The diagnostic sensitivity and specificity of the developed assay were evaluated using fish samples (n = 510) and were found to be 100% and 99.60%, respectively. Two technicians evaluated the reproducibility of the assay using fish samples (n = 90), finding a high correlation of 0.998 (p < 0.0001). Therefore, the newly developed real-time PCR assay detects RSIV both accurately and rapidly.
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Collections - 자연과학계열 > 해양생명과학과 > Journal Articles
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