JOURNAL ARTICLE

Comparison of droplet digital PCR and real‐time quantitative PCR for quantitative detection of the parasitic ciliate Ichthyophthirius multifiliis in the water environment.

  • Published In: Journal of Fish Diseases, 2023, v. 46, n. 4. P. 357 1 of 3

  • Database: Academic Search Ultimate 2 of 3

  • Authored By: Hu, Guangran; Huang, Ke; Zhou, Weitian; Wang, Runqiu; Zhao, Weishan; Zou, Hong; Li, Wenxiang; Wu, Shangong; Li, Ming; Wang, Guitang 3 of 3

Abstract

Ichthyophthiriasis, caused by the parasitic ciliate Ichthyophthirius multifiliis (Ich), is considered one of the most harmful diseases affecting freshwater fish globally. It can cause mass mortalities of fish in intensive farming systems. In such systems, it is thus necessary to detect and quantify the number of Ich in the water so that control measures can be implemented before Ichthyophthiriasis breaks out. In recent years, molecular diagnostic methods have become increasingly important in aquaculture. Real‐time quantitative polymerase chain reaction (qPCR) and droplet digital polymerase chain reaction (ddPCR) have become robust assays for detecting pathogens. In this study, a set of specific primers and a TaqMan‐minor groove binder probe targeting the small‐subunit rDNA (SSU rDNA) of Ich were developed. They were used in qPCR and ddPCR assays to compare the performance of these two different methods in quantitatively detecting Ich. After optimizing the reaction conditions, both qPCR and ddPCR assays were found to have high linearity and quantitative correlations for standard plasmid DNA. When used for the detection of Ich eDNA in water samples, the qPCR assay had a wider detection range, making it a suitable method to screen for the prevalence of Ichthyophthiriasis. However, the ddPCR approach had higher sensitivity, which would help provide advance notice of the disease in complex water environmental samples. [ABSTRACT FROM AUTHOR]

Additional Information

  • Source:Journal of Fish Diseases. 2023/04, Vol. 46, Issue 4, p357
  • Document Type:Article
  • Subject Area:Science
  • Publication Date:2023
  • ISSN:0140-7775
  • DOI:10.1111/jfd.13749
  • Accession Number:162295627
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