Skip to main content
Advertisement
Browse Subject Areas
?

Click through the PLOS taxonomy to find articles in your field.

For more information about PLOS Subject Areas, click here.

  • Loading metrics

Partial validation of a TaqMan quantitative polymerase chain reaction for the detection of the three genotypes of Infectious spleen and kidney necrosis virus

  • Samantha A. Koda,

    Roles Data curation, Investigation, Methodology, Validation, Visualization, Writing – original draft

    Affiliations Department of Infectious Diseases and Immunology, College of Veterinary Medicine, University of Florida, Gainesville, Florida, United States of America, Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America

  • Kuttichantran Subramaniam,

    Roles Conceptualization, Data curation, Investigation, Methodology, Supervision, Validation, Writing – review & editing

    Affiliations Department of Infectious Diseases and Immunology, College of Veterinary Medicine, University of Florida, Gainesville, Florida, United States of America, Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America

  • Paul M. Hick,

    Roles Conceptualization, Data curation, Methodology, Resources, Supervision, Validation, Writing – review & editing

    Current address: The Virology Laboratory, Elizabeth Macarthur Agricultural Institute, NSW Department of Primary Industries, Menangle, NSW, Australia

    Affiliation Sydney School of Veterinary Science, The University of Sydney, Camden, New South Wales, Australia

  • Evelyn Hall,

    Roles Formal analysis, Writing – review & editing

    Affiliation Sydney School of Veterinary Science, The University of Sydney, Camden, New South Wales, Australia

  • Thomas B. Waltzek ,

    Roles Data curation, Funding acquisition, Methodology, Project administration, Resources, Supervision, Validation, Writing – review & editing

    joy.becker@sydney.edu.au (JAB); tbwaltzek@ufl.edu (TBW)

    Current address: Animal and Plant Health Inspection Services, U.S. Department of Agriculture, Gainesville, Florida, United States of America

    Affiliations Department of Infectious Diseases and Immunology, College of Veterinary Medicine, University of Florida, Gainesville, Florida, United States of America, Emerging Pathogens Institute, University of Florida, Gainesville, Florida, United States of America

  • Joy A. Becker

    Roles Conceptualization, Data curation, Funding acquisition, Methodology, Project administration, Resources, Supervision, Validation, Writing – review & editing

    joy.becker@sydney.edu.au (JAB); tbwaltzek@ufl.edu (TBW)

    Affiliation School of Life and Environmental Sciences, The University of Sydney, Camden, New South Wales, Australia

Abstract

Megalocytiviruses (MCVs) are double-stranded DNA viruses known to infect important freshwater and marine fish species in the aquaculture, food, and ornamental fish industries worldwide. Infectious spleen and kidney necrosis virus (ISKNV) is the type species within the genus Megalocytivirus that causes red seabream iridoviral disease (RSIVD) which is a reportable disease to the World Animal Health Organization (WOAH). To better control the transboundary spread of this virus and support WOAH reporting requirements, we developed and partially validated a TaqMan real-time qPCR assay (ISKNV104R) to detect all three genotypes of ISKNV, including the two genotypes that cause RSIVD. Parameters averaged across 48 experiments used a 10-fold dilution series of linearized plasmid DNA (107–101 copies), carrying a fragment of the three-spot gourami iridovirus (TSGIV) hypothetical protein revealed that the assay was linear over 7 orders of magnitude (107–101), a mean efficiency of 99.97 ± 2.92%, a mean correlation coefficient of 1.000 ± 0.001, and a limit of detection (analytical sensitivity) of ≤10 copies of TSGIV DNA. The diagnostic sensitivity and specificity for the ISKNV104R qPCR assay was evaluated and compared to other published assays using a panel of 397 samples from 21 source populations with different prevalence of ISKNV infection (0–100%). The diagnostic sensitivity and specificity for the ISKNV104R qPCR assay was 91.99% (87.28–95.6; 95% CI) and 89.8% (83.53–94.84). The latent class analysis showed that the ISKNV104R qPCR assay had similar diagnostic sensitivities and specificities with overlapping confidence limits compared to a second TaqMan qPCR assay and a SYBR green assay. This newly developed TaqMan assay represents a partially validated qPCR assay for the detection of the three genotypes of the species ISKNV. The ISKNV104R qPCR assay once fully validated, will serve as an improved diagnostic tool that can be used for ISKNV surveillance efforts and diagnosis in subclinical fish to prevent further spread of MCVs throughout the aquaculture and ornamental fish industries.

Introduction

Aquaculture continues to be one of the fastest growing sectors of agriculture and reached a record high of an estimated $263 billion in 2018 [1]. Finfish production including inland, coastal, and marine production has dominated the aquaculture sector accounting for an estimated $140 billion annually [1]. With increasing economic importance and as a major global food source, the pressure on finfish production has also led to more frequent outbreaks of disease [2]. There has been an increasing concern that the exportation and importation of aquacultured fish are contributing to the spread of pathogens globally [3, 4]. The topic of transboundary movement of pathogens has not only been restricted to aquaculture and food fish but also to the global ornamental fish trade [59]. A key pathogen of global concern is the infectious spleen and kidney necrosis virus (ISKNV), as it is known to cause epidemics in numerous wild and farmed food and ornamental fish species.

ISKNV is known to cause disease in at least 165 different fish species across 53 fish families with the number of susceptible species continuing to increase in recent years [7, 1022]. ISKNV has been detected across a wide range of countries (22) and continents (6) with a majority of the reports from Asia [8, 2326]. In clinical cases of ISKNV infections, mortality can reach up to 100%, but most cases range from 20–60% mortality [6, 11, 2738]. Clinical signs of disease are non-specific and include lethargy, gill pallor, skin discoloration, inappetence, and abnormal swimming. These gross clinical signs in addition to subclinical infections make surveillance efforts extremely important to control the spread of this virus.

The emergence of ISKNV infections in new host species and regions has led to a plethora of virus names to be given to isolates of the same virus species (e.g., see [39]) leading to inconsistent viral nomenclature. ISKNV is one of two classified species within the genus Megalocytivirus (MCV) [40]. Within the species ISKNV, there are three genotypes: RSIV (Genotype II), ISKNV (Genotype I), and turbot reddish body iridovirus (TRBIV) (Genotype III) [8]. These three genotypes can each be further subdivided into clades 1 and 2, for a total of six clades within the species ISKNV [8, 25, 41]. Henceforth, the term ISKNV will refer to the taxonomic level of species unless otherwise stated (e.g., ISKNV genotype). The three genotypes of ISKNV have overlapping host and geographic ranges. Noting its international importance, red seabream iridoviral disease (RSIVD), caused by infections with ISKNV and RSIV genotypes, is listed as one of 12 WOAH reportable fish diseases [42]. At the time of this publication, infection with TRBIV is not included in the definition of RSIVD, although this is being reviewed by WOAH Aquatic Animal Health Standards Commission (meeting held 14–21 September 2022). Scale drop disease virus is the second officially recognized species within the genus Megalocytivirus according to the International Committee on Taxonomy of Viruses (ICTV) [40]. SDDV first emerged as a pathogen of barramundi [36] and has recently caused epidemics in farmed Yellowfin Seabream (Acanthopagrus latus) [43]. In addition to SDDV, European chub iridovirus (ECIV) and three-spined stickleback (TSIV) are unclassified MCVs that have been proposed as species within the genus [44, 45].

To support global animal disease control, appropriate diagnostic tools that are fit for purpose and validated must be developed for WOAH reportable diseases like RSIVD. At present, several diagnostic tools have been developed for the detection of ISKNV including: conventional PCR [8, 46, 47], real-time PCR (qPCR; [4852]), immunofluorescent antibody tests (IFAT) using a monoclonal antibody [5355], virus isolation [5661], DNA microarrays [62, 63], and loop-mediated isothermal amplification [6466]. Out of all these diagnostic assays, there are only three recommended assays for RSIVD detection 1) a stamp smear showing megalocytic cell inclusions confirmed by an IFAT, 2) virus isolation with MCV-like characterized cytopathic effects (CPE) confirmed with an IFAT, and 3) a conventional PCR [67]. Of these, only the conventional PCR can differentiate between RSIV and ISKNV [67]. There is currently no validated assay to detect all three genotypes of ISKNV and this is a pressing need to develop a real-time quantitative polymerase chain reaction (qPCR) assay.

The development and validation of a highly sensitive and specific qPCR assay would be beneficial for the detection of ISKNV infections, especially with low viral loads as sometimes encountered during recent or resolving infections, and in subclinical carriers [68, 69]. The objective of this study was to develop and partially validate a TaqMan qPCR assay that detects all three ISKNV genotypes and here on out is referred to as the ISKNV104R qPCR assay. As part of the partial validation efforts, analytical and diagnostic sensitivity and specificity were evaluated for the ISKNV104R qPCR. Latent class analysis was performed to compare the diagnostic performance of the new assay with two previously published assays with different gene targets and/or assay chemistry [49, 70]. The intent of this work was to generate a qPCR assay useful in diagnostic laboratories with sufficient validation data for future inclusion as a WOAH acceptable test for surveillance and diagnosis of diseases caused by infections with ISKNV.

Material and methods

In silico TaqMan qPCR primer and probe design

Development and analytical performance of the ISKNV104R TaqMan qPCR were carried out at the University of Florida’s Wildlife and Aquatic Animal Veterinary Diagnostic Laboratory (WAVDL) in Gainesville, Florida, USA. An initial review of all published MCV genomes revealed that some MCVs (e.g., ECIV and SDDV) were too divergent from ISKNV strains (<75% amino acid identity), to be included in the scope of a single qPCR assay. Thus, ECIV and SDDV were not included in the sequence alignments used to generate the primers and TaqMan probe. Twelve fully sequenced genomes (S1 Table), representing all three ISKNV genotypes (ISKNV, RSIV, TRBIV), were downloaded from the National Center for Biotechnology Information (NCBI) GenBank database. A full genome alignment was performed using Mauve 2.4.0 with default settings [71]. From the output alignment, the locally collinear blocks (LCBs) were visually inspected for conserved sequence segments to be used to design the qPCR primers and probe. Once the LCBs were identified, the 100% consensus sequence for each segment was imported into Primer Express Software Version 3.0 (Applied Biosystems) to design an ISKNV species-specific primers and a [6FAM]-minor groove binder/non fluorescent quencher-labeled TaqMan hydrolysis probe using default settings. After the selection of suitable primers and a probe, an additional 11 fully sequenced MCVs were downloaded from GenBank to determine the in silico primer and probe specificity (S1 Table). All 23 genomes were aligned using MAFFT [72] and visualized in Bioedit v7.2.5 to inspect the specificity of the primers and probe [73].

Generation of megalocytivirus DNA standards to assess assay performance

To test the efficiency of the new primers and probe, standard curves were evaluated from amplification of a linearized plasmid DNA standard that was generated through TOPO TA cloning. Additional primers were developed outside of the sequence to be amplified by the qPCR assay to generate an amplicon for cloning. A three spot gourami iridovirus sample (TSGIV; [8]) was used as the nucleic acid template for generating the target to be cloned. TSGIV was previously identified to belong to clade 2 of the TRBIV genotype (III) [8].

The volumes for the conventional PCR reactions were 30 μl and consisted of 0.15 μl of Platinum Taq DNA Polymerase (Invitrogen), 3.0 μl of 10× PCR Buffer, 1.2 μl of 50 mM MgCl2, 0.6 μl of 10 mM dNTPs, 1.5 μl of 20 μM of forward and reverse primers, 17.55 μl of molecular grade water, and 4.5 μl of DNA template. The reaction was carried out using a SimpliAmp thermal cycler (Applied Biosystems) using the following conditions: 94°C for 5 m, followed by 30 cycles at 94°C for 30 s, 56°C for 30 s, 72°C for 30 s, and final elongation at 72°C for 10 m. The presence of amplified products was confirmed by analyzing the PCR products on a 1% agarose gel stained with ethidium bromide. The expected band was purified using a QIAquick PCR Purification Kit (Qiagen). The concentration of the purified band was quantified using a Qubit® 3.0 Fluorometer and the dsDNA BR Assay Kit (Life Technologies). Once quantified, the purified DNA target was cloned into a vector (Invitrogen) and transformed into E. coli using the TOPO® TA Cloning® Kit (Invitrogen) following the manufacturer’s instructions. Transformed bacterial colonies were screened by conventional PCR using the M13 forward and reverse primers and the target was confirmed via Sanger sequencing. The colonies with the correct insert were grown in the LB broth overnight (16–20 hours) in an Incu-Shaker mini (Benchmark Scientific) at 37°C and 200 rpm. The following day, the tubes were centrifuged at 3000 x g for 10 minutes at 15°C before following the manufacturer’s protocol for plasmid purification using a QIAprep Spin Miniprep Kit (Qiagen).

The recombinant plasmid was linearized using the NotI enzyme (New England Biolabs) following the manufacturer’s instructions and analyzed on a 1% agarose gel stained with ethidium bromide. The correct size band containing the qPCR target was purified using a QIAquick PCR Purification Kit (Qiagen) and the DNA concentration was quantified as described above. The linearized plasmid was then diluted to 107 copies/μl in TE buffer using the formula described by Krieg (1990) and aliquoted into 30 μl volumes and stored at -80°C until used. For each qPCR plate (termed experiment), an aliquot of 107 copies of linear plasmid was thawed and serially diluted 10-fold with nuclease-free water using the QIAgility (Qiagen). Each standard dilution (107–101 copies) was run in triplicate (4 μl reaction well-1) to create the standard curve for each qPCR plate.

Detection of the ISKNV DNA standard using the ISKNV104R qPCR assay

All qPCR plates were set up in a MicroAmp™ Fast Optical 96-Well Reaction Plate, 0.1 mL (Applied Biosystems) using the QIAgility (Qiagen). Each reaction contained 0.9 μM of each primer, 0.25 μM of probe, 4 μl of nucleic acid template (maximum of 50 ng of total DNA per reaction), 10 μl of universal qPCR mix (TaqMan® Fast Universal PCR Master Mix 2X, Applied Biosystems), and 3 μl of molecular grade water for a total volume of 20 μl. Once the plate was set up, it was sealed with a MicroAmp™ Optical Adhesive Film (Applied Biosystems), mixed on a 96 well plate shaker, and spun down before being evaluated by qPCR. The samples were run on a QuantStudio 5 Real-Time PCR System (Applied Biosystems) using the following fast qPCR protocol thermocycling conditions: 95°C for 20 s followed by 40 cycles at 95°C for 3 s and 60°C for 30 s. A threshold cycle (Ct) value was automatically calculated by the QuantStudioTM Design & Analysis Software v1.4.1 and interpreted as a positive result if the calculated Ct value as the proportional cycle number when the 6-carboxy-X-rhodamine (ROX)-normalized 6-carboxyfluorescein (FAM) signal exceeds the threshold assigned by the Applied Biosystems software. A sample was considered positive if 2/3 or 3/3 wells generated a Ct value ≤ 40.

Each plate included quality control samples including a negative extraction control, a no template control (molecular grade water), a standard curve (107–101), and a VetMAX™ Xeno™ Internal Positive Control (IPC) VIC Assay (Applied Biosystems). All the aforementioned samples and controls were run in triplicate wells with the ISKNV species-specific primers and probe except the VetMAX™ Xeno™ Internal Positive Control (IPC) which was added into the fourth well for each sample. The IPC reactions contained 0.8 μl of VetMAX™ Xeno™ Internal Positive Control–VIC™ Assay (Applied Biosystem), 1 μl of VetMAX™ Xeno™ Internal Positive Control DNA (Applied Biosystem) diluted 1:10, 4 μl of nucleic acid template, 10 μl of TaqMan™ Fast Universal PCR Master Mix (2X), and 4.2 μl of molecular grade water. IPC wells were deemed positive if the well generated a Ct value ≤ 35; indicating there was little to no PCR inhibition.

Estimation of qPCR assay analytical sensitivity and specificity

Triplicate 10-fold dilutions of the TSGIV standard (107−101 copies) were used in each of 48 plates to estimate the correlation coefficient (R2), y-intercept, slope, efficiency, dynamic range, analytical sensitivity, repeatability, and reproducibility of the qPCR assay as previously described [74, 75]. Efficiency was calculated as 10-1/slope– 1 [76]. The qPCR assay limit of detection (LOD or analytical sensitivity) was defined as the lowest dilution at which 50% of positive samples (wells) were detected by a positive result. The coefficient of variation was used to assess intra-assay variability (repeatability) and inter-assay variability (reproducibility) for the 48 plates according to the formula CV% = [SD/mean] × 100. To estimate the qPCR analytical sensitivity further, infected tissues or isolates representing all three genotypes within the species ISKNV were used to determine the inclusivity of the assay for the three ISKNV genotypes (Table 1). Samples representing five of the six ISKNV clades (except clade 1 of the TRBIV genotype) were used to test the inclusivity of the ISKNV TaqMan qPCR. The ISKNV Clade 1, RSIV Clade 1, and TRBIV Clade 2 samples have been previously described by Koda et al. [77], Koda et al. [78], and Koda et al. [8], respectively. The genotype ISKNV clade 2 infected tissue DNA was extracted from the spleen and kidney from a Banggai cardinalfish Pterapogon kauderni that was confirmed by full genome sequencing (GenBank acc. no. MN432490). The genotype RSIV clade 2 infected tissue DNA was extracted from the liver of a diseased Florida pompano Trachinotus carolinus and was confirmed by PCR and Sanger sequencing using two MCV-specific primer sets [8].

thumbnail
Table 1. Summary of samples used in determining the analytical specificity and inclusivity of the ISKNV104R TaqMan qPCR assay.

https://doi.org/10.1371/journal.pone.0281292.t001

To estimate the qPCR analytical specificity, the assay was tested against DNA from an isolate of a divergent, unclassified MCV, European chub iridovirus (ECIV; [45], as well as other previously described tissues infected with iridoviruses of the closely related genera, Lymphocysitivirus [79] and Ranavirus [80]. Other double-stranded DNA viruses including cypriniviruses (Cyprinid herpesvirus 13, CyHV1-3) [81] and carp edema virus (CEV) [82] were also tested against the ISKNV TaqMan qPCR assay (Table 1).

Estimation of qPCR assay diagnostic sensitivity and specificity for 3 assays

The diagnostic performance of the ISKNV104R TaqMan qPCR assay was evaluated at The University of Sydney, Camden, NSW, Australia. The fish tissues samples used were approved by The University of Sydney Animal Ethics Committee (2014/720; 2016/979). A panel of 397 samples of pooled liver, kidney, and spleen tissue homogenates was acquired from a cross sectional surveillance survey and challenge studies that were performed at The University of Sydney (Table 2). In total, the 397 samples represented 21 different fish populations to test the diagnostic performance. Apparent prevalence in these populations was estimated by prior testing (using [49]) and populations were categorized according to low (<10%), medium (10–70%), and high prevalence (>70%). For the low prevalence populations, we selected all the positive samples in the low prevalence populations and then randomly selected negatives from the same population. For the medium and high prevalence populations, we randomly selected positives and purposively selected negatives. Diagnostic sensitivity was assessed based on all 21 populations, while three populations that were free from infection and represented true negative samples (Populations 15–17; 36 samples) were used to assess diagnostic specificity. The panel of validation samples from surveillance in Australia included a range of samples (Table 2) from those with low viral load (< 100 viral genome copies mg-1 tissue) and low prevalence (<10% of the population) to samples with high viral load (8.6 x 109 viral genome copies mg-1 tissue) and 100% population prevalence. All sample populations were determined to be the genotype ISKNV by testing using the SYBR green assay [49] and genotyping via three conventional PCRs followed by Sanger sequencing [83, 84].

thumbnail
Table 2. Summary of fish population samples used to determine the diagnostic sensitivity and specificity for comparison of the ISKNV104R, RSIV RT, and C1073/C1074 qPCR assays.

https://doi.org/10.1371/journal.pone.0281292.t002

The diagnostic performance of the newly developed ISKNV104R qPCR assay was performed at the University of Sydney and was assessed by testing the samples in duplicate 25 μl reactions prepared with TaqMan™ Universal Master Mix (ThermoFisher). Reactions were prepared with 12.5 μl mastermix with 0.6 μM of each primer, 0.25 μM of probe, 2 μl of nucleic acid template, and nuclease free water. The reaction mixtures were loaded in a 96-well plate sealed with optically clear strip caps (Agilent). Each plate included duplicate no-template controls (nuclease free water), negative extraction control, and a PCR positive ISKNV genomic.

DNA sample, all tested in duplicate. Reactions were carried out on a Mx3000P qPCR system (Stratagene) using the following thermal cycling conditions: 95°C for 10 m, followed by 45 cycles at 95°C for 15 s and 60°C for 60 s. The sample was interpreted as a positive result if the ROX-normalized FAM signal exceeded the threshold assigned by the MxPro software (Stratagene) in at least one of the duplicate reaction wells.

Partial validation of the newly developed ISKNV104R qPCR assay was conducted with the operator blinded to the sample status to test the panel. A second TaqMan qPCR assay (RSIV RT) using the primers RSIV RT F/R and RSIV probe [70] was conducted consistent with the Australian and New Zealand Standard Diagnostic Procedure [85] and a SYBR green qPCR assay (C1073/C1074) using the C1073 and C1074 primers [49]. Each assay used aliquots of the nucleic acids at the same number of freeze thaw cycles as the ISKNV104R TaqMan qPCR assay. Similarly, all reactions (including no template controls) were run in duplicate in 96-well 0.2 ml qPCR plates sealed with optically clear strip caps (Agilent) on a Mx3000P qPCR system (Stratagene). The qPCR assay reactions for the RSIV RT TaqMan assay [70] contained 12.5 μl TaqMan™ Universal Master Mix (Thermofisher), 0.9 μM of each primer, 0.25 μM of probe, and 2 μl of nucleic acid template with nuclease free water to a total reaction volume of 25 μl. The following thermocycling conditions were used for the RSIV RT assay: 50°C for 2 m, 95°C for 10 m, and 45 cycles of 95°C for 15 s and 60°C for 60 s. The qPCR assay reactions for the C1073/C1074 SYBR green assay [49] contained 12.5 μl QuantiTect SYBR Green Master Mix (Qiagen), 0.5 μM of each primer, 5 μl of nucleic acid template and nuclease free water for a total reaction volume of 25 μl. The C1073/C1074 assay was run using the thermal cycling conditions: 95°C for 15 m, followed by 40 cycles of 95°C for 30 s, 62°C for 30 s, and 72°C for 30 s followed by a melting curve. All PCR plates included duplicate reactions prepared with a no template control, negative extraction control and two positive controls containing ISKNV or RSIV genomic DNA. The appropriate plasmid DNA standard (MCP or ISKNV104R) was amplified (107−102 copies/reaction) on each plate to determine absolute quantification. The fluorescence threshold was set for each plate based on amplification of the standard and applied to the experimental samples to assign a Ct value or negative result. The samples were assessed for inhibition using a VetMax Xeno Internal Positive Control assay (Thermofisher). A positive sample for the TaqMan assays were defined as having at least one of two duplicate wells amplifying. A positive result for the SYBR green assay was defined as having a melting temperature of 85.0 ± 0.5°C.

A Bayesian approach to latent class analysis was used to analyze the diagnostic sensitivity and specificity of the three qPCR assays. It was assumed that the three tests were independent due to their different chemistry and/or different target genes for amplification. WinBUGS (Version 1.4.3, 2007) was used to run the model for 100,000 iterations, discarding the first 10,000.

Results

In silico TaqMan qPCR primer and probe design

Visual inspection and in silico analyses of the resulting consensus sequences led to the identification of ISKNV ORF104R (GenBank Acc. No. AF371960), which encodes a hypothetical protein, as a suitable target for this ISKNV TaqMan qPCR assay. The primer (ISKNV104R-F and ISKNV104R-R) and probe (ISKNV104R-P) sequences that were selected for the TaqMan qPCR assay targeted a 68 bp region for amplification of the hypothetical protein mentioned above (Table 3). In silico analysis of the ISKNV104R primers and probe revealed no mismatches to the original 12 MCV genomes that were used to develop the assay (Fig 1). Similarly, no mismatches were found after aligning the novel ISKNV104R primers/probe to an additional 11 ISKNV genomes, encompassing all 6 MCV clades within the species ISKNV, that subsequently became available in NCBI GenBank.

thumbnail
Fig 1. Aligned partial (68 bp) hypothetical protein ISKNV 104R (A) for 23 megalocytivirus strains illustrating the in silico specificity of the qPCR primers and probe of ISKNV TaqMan qPCR assay (this study).

Aligned partial major capsid protein (MCP) for the same 23 megalocytivirus strains illustrating the in silico specificity of the qPCR primers RSIV RT F/R and RSIV probe (B; [69]) and C1073/C1074 (C; [48]).

https://doi.org/10.1371/journal.pone.0281292.g001

thumbnail
Table 3. Primers and probe sequences used in the TaqMan ISKNV104R qPCR targeting the hypothetical protein (ISKNV ORF104R GenBank acc. no. AF371960).

https://doi.org/10.1371/journal.pone.0281292.t003

Estimation of qPCR assay analytic sensitivity and specificity

A 10-fold dilution series of linearized plasmid DNA (107–101 copies), carrying a 346 bp fragment of the TSGIV hypothetical protein (GenBank acc. no. MG570132, positions 91979–92755) was used for the standard curves. The amplification plot revealed that the qPCR assay was linear over 7 orders of magnitude (107–101) (Fig 2). The mean parameters (± SD) for the qPCR assay averaged over the 48 experiments were as follows: slope = -3.32 ± 0.07, y-intercept: 37.42 ± 0.60, R2: 1 ± 0.001, and efficiency: 99.97 ± 2.92% (Fig 2). The LOD of the assay (analytical sensitivity) was determined to be 10 copies of ISKNV DNA standard per reaction (positive in 144/144 of the reactions with 10 copies of template; Table 4). The coefficient of variation of intra- and inter-assay Ct values ranged from 0.1–2.25% and 0.15–1.55%, respectively (Table 4).

thumbnail
Fig 2. TaqMan ISKNV 104R qPCR assay standard curve generated using triplicate 10-fold serial dilutions of a MCV standard ranging from 107-101copies.

The mean qPCR assay parameters (± SD) averaged over the 48 experiments are provided. The x-axis shows the standard copy number, and the y-axis indicates the corresponding cycle threshold.

https://doi.org/10.1371/journal.pone.0281292.g002

thumbnail
Table 4. Inter-assay (reproducibility) and intra-assay (repeatability) variability of the TaqMan ISKNV104R qPCR assay.

To determine reproducibility, the reactions for each standard (107−101 copies) were run in triplicate across 48 experiments. To determine repeatability, data obtained in a single representative qPCR run using standard (107−101copies) in triplicate. Ct: threshold cycle number; CV: coefficient of variation; SD: standard deviation.

https://doi.org/10.1371/journal.pone.0281292.t004

The five samples representing five of six of the ISKNV clades tested positive. For analytical specificity, all samples tested negative. The VetMAX™ Xeno™ internal positive controls tested positive for all samples, indicating that the reactions were not inhibited by any of the substances in the samples.

Estimation of qPCR assay diagnostic performance and latent class analysis

Using the prior results and classification of the C1073/1074 assay [49] for the 397 panel of samples, the diagnostic sensitivity and specificity for the ISKNV104R qPCR was found to be 91.99% (95% Confidence Interval (CI): 87.28–95.6%) and 89.81% (95% CI: 83.53–94.84%), respectively (Table 5). The latent class analysis revealed that the C1073/C1074 assay had the highest diagnostic sensitivity at 93.54% (95% CI: 88.86–97.06%) while the RSIV RT assay had the lowest diagnostic sensitivity at 87.8% (95% CI: 82.35–92.22%). For diagnostic specificity, all three assays performed about the same with the RSIV RT assay performing slightly better than the other two at 91.83% (95% CI: 86.2–96.02%). The C1073/C1074 SYBR green assay was the second best performing at 90.71% (95% CI: 84.78–95.35%), followed by the ISKNV104R qPCR assay with 89.81% (95% CI: 83.53–94.84%).

thumbnail
Table 5. Summary of the characteristics and predicted diagnostic performance of the ISKNV TaqMan qPCR (this study), RSIV TaqMan qPCR, and ISKNV SYBR Green qPCR assays using a Bayesian latent class analysis with a 95% confidence interval (CI).

https://doi.org/10.1371/journal.pone.0281292.t005

Discussion

As a highly virulent virus in fish, ISKNV infections continue to be reported in new geographical regions around the world due to increased awareness, surveillance, and disease outbreaks [21, 77, 86, 87]. Since the first published report of RSIV in 1990 from red seabream, several diagnostic assays have been developed to identify ISKNV species [88]. The importance of a properly validated diagnostic tool became apparent when RSIVD was classified as an WOAH reportable disease in 2000 [67]. However, as outlined in the WOAH Manual of Diagnostic Tests for Aquatic Animals [67], only three assays have been partially validated for the detection of genotypes RSIV and ISKNV and none have been formally validated as outlined in the WOAH chapter Principles and Methods of Validation of Diagnostic Assays for Infectious Diseases [89]. At present, only two real-time PCR assays have been partially validated with consideration of all three ISKNV genotypes which presents a major gap in detecting this pathogen and preventing the pathogen from spreading further globally [90, 91]. The lack of a fully validated qPCR assay highlights the need for an assay that is applicable to surveillance and diagnosis of diseases caused by each of the ISKNV genotypes [49, 68, 70, 92]. The ISKNV104R qPCR assay reported here was optimized and partially validated to Stage 2 [89] to detect all 3 genotypes of the species ISKNV. This assay is further differentiated by testing against samples representing five of the six clades within the species ISKNV. After the completion of Stage 2 validation, a diagnostic assay can be given the designation of ‘provisional recognition’ and this will support the progression to Stage 3 evaluation and classification as being ‘validated for the original intended purposes’ [89].

The analytic performance of the ISKNV104R qPCR assay exhibited high coefficient of correlation, efficiency, sensitivity (LOD, was less than 10 copies reaction-1), specificity (100%), repeatability, and reproducibility. Recently, a TaqMan qPCR assay was developed targeting the RSIV major capsid protein and was partially validated with an even lower LOD of 2.5 viral genome copies [91]. Validation of diagnostic assays with extremely low limits of detections are important in subclinical cases where the animal may have early or recovering infection. These cases will be of utmost importance in surveillance and preventing the spread of the virus globally. In comparison to previous partially validated qPCR assays, other analytical sensitivity parameters (correlation coefficient and efficiency) of the ISKNV104R qPCR assay were found to be one of the highest resulting in an overall R2 value of 1 ± 0.001 and an efficiency of 99.97% ± 2.92% [49, 90, 91, 93]. A previous study however by Johnson et al. (2019) found that the analytical sensitivity of the C1073/C1074 SYBR green assay was reduced by two orders of magnitude when the plasmid was spiked into fish tissues compared to molecular grade water. These results suggest that there is some level of inhibition that is carried through the DNA extraction process and may result in decreased detection of the pathogen. So, while high analytical sensitivity is a good characteristic of a diagnostic tool, it is not truly representative of a tissue sample since the plasmid is in a matrix of molecular grade water. Analytical specificity was also found to be very high with no amplification of any of the divergent MCVs, related iridovirus genera, cypriniviruses, or CEV.

One of the main criteria for validation of a diagnostic assay is that it must be validated for the species for which the assay will be used for [89]. However, this would be very difficult given ISKNV has been detected in >160 species of fish [94]. In testing the analytical and diagnostic specificity of the ISKNV104R qPCR assay, DNA tissue samples from 397 individuals from 14 fish species were used to provide evidence that the assay is robust. Additionally, in comparison to other ISKNV qPCR studies [90, 91], the diagnostic performance of ISKNV104R qPCR assay was determined using the largest number of tissue samples and greatest range of host species. The samples that were used to test the analytical and diagnostic performance were also unique in that we used both freshwater and marine fish species which has not been done in previous qPCR studies. Moreover, DNA was extracted from different types of samples including fresh tissues, frozen tissues, and viral isolates which represent samples typically received by diagnostic laboratories. The usage of different types of samples helped prove the high performance of analytical selectivity with this assay and may provide a more realistic outlook when tested at the reproducibility and implementation stage of WOAH validation pathway. In testing for diagnostic performance of the three qPCR assays, the use of latent class analysis using Bayesian estimation was instrumental in making the comparison between the three [95]. This requires the assumption that qPCR assays with different detection chemistries and amplification targets are independent tests. In conclusion, all three assays performed relatively equally despite using different types of samples across 14 different fish species. The validation data can be used by regulator authorities and diagnostic laboratories involved in testing to support biosecurity for the international trade in fish and fish products.

The TaqMan ISKNV104R qPCR assay developed in this study represents the first qPCR assays to test five out of six ISKNV clades. The only ISKNV clade that was not tested due to limited access to samples was TRBIV Clade 1. However, in silico analyses have predicted that this assay is able to detect all six ISKNV clades (Fig 1). The genotype TRBIV has been excluded as a causative agent in RSIVD despite having high genetic similarity to the other two genotypes. Consequently, the WOAH Manual of Diagnostic Tests for Aquatic Animals [67] does not include validation against TRBIV when diagnostic assays for RSIVD were originally recommended over 20 years ago. A review of the literature shows that the genotype TRBIV was initially only reported in Asian flatfish species and has been reported less frequently in comparison to the genotypes ISKNV and RSIV which may be a reason for its exclusion [21, 39, 96101]. However, there was a recent TRBIV outbreak in 2017 reported from Taiwan in a popular food fish, barramundi Lates calcarifer [102]. Previously, TRBIV has also been confirmed by PCR in rock bream (Oplegnathus fasciatus) from Taiwan, another popular marine food fish species in Asia [103]. The WOAH Aquatic Animal Health Standards Commission is undertaking a review of the chapter addressing RSIVD with the consideration of including the TRBIV genotype in the definition of infection. If TRBIV is included, the partially validated pan-ISKNV assay developed herein could be considered for inclusion in the WOAH manual [67] and this would support future work to further validate the assay. The purpose of the TaqMan ISKNV104R qPCR assay was to develop and partially validate the first qPCR diagnostic tool for the intended purpose of ISKNV surveillance. Particularly, to certify freedom from infection or presence of the agent in individual animals and in a defined population in trade/movement as outlined in the WOAH validation of diagnostic assays for infectious diseases [89].

The reported ISKNV104R qPCR assay provides a diagnostic tool that is cost-effective, rapid, highly specific and sensitive, and quantitative in comparison to the other diagnostic tools such as conventional PCR and virus isolation. Analysis of the in silico primer and probe mapping to 23 MCVs representing all six MCV clades resulted in zero mismatches. Analytical and diagnostic performance of the TaqMan ISKNV104R qPCR assay was found to be high and comparable to that of the SYBR green C1073/C1074 and TaqMan RSIV RT. With the number of fish species reported to be susceptible to ISKNV infections continuing to increase, the need for validated qPCR assays for surveillance and diagnosis is extremely important. Stocks of many important food fish species such as Nile tilapia (Oreochromis niloticus), barramundi, red sea bream (Pagrus major), rock bream, and grouper species (Epinephelus spp.) have experienced significant mortality events due to ISKNV [10, 1518, 37, 38, 87, 101, 104106]. This is key for the aquaculture industry where there has been a continual increase in production which has also resulted in more frequent pathogen outbreaks [2]. Co-infections with two different ISKNV genotypes have also been reported in the literature and serve as another justification for the development of a pan-ISKNV assay [107, 108]. Thus, the ability to detect all ISKNV genotypes will be an important feature of any diagnostic tool used in global ISKNV surveillance efforts to ultimately prevent the spread of these pathogens. Additional efforts are needed to test the reported ISKNV TaqMan qPCR against other sample types including DNA derived from ISKNV isolates, RSIV samples, and TRBIV samples. Lastly, the next steps for validation of this assay would include testing this assay with the same panel of samples plus WOAH reference samples at multiple laboratories to determine reproducibility, and finally implementation.

Supporting information

S1 Table. Genome summary of the 23 megalocytivirus genomes used to develop and/or demonstrate the in silico specificity of the ISKNV TaqMan qPCR primers (ISKNV104R-F and ISKNV104R-R) and TaqMan probe (ISKNV104R-P).

https://doi.org/10.1371/journal.pone.0281292.s001

(DOCX)

S2 Table. Raw data used to determine the standard curve for the ISKNV 104R qPCR assay with the mean and standard deviation (SD) calculated for the 48 experiments at each serial dilution (10^7 to 10^1).

https://doi.org/10.1371/journal.pone.0281292.s002

(XLSX)

References

  1. 1. FAO. The State of World Fisheries and Aquaculture 2020. Sustainability in action. Rome. 2020. Available from: https://doi.org/10.4060/ca9229en.
  2. 2. Murray AG, Peeler EJ. A framework for understanding the potential for emerging diseases in aquaculture. Prev Veterinary Med. 2005;67(2–3):223–35. pmid:15737433
  3. 3. Cartín-Rojas A. Transboundary Animal Diseases and International Trade. In: Bobek V., editor. International Trade from Economic and Policy Perspective [Internet]. London: IntechOpen; 2012 [cited 2021 Dec 16]. Available from: https://www.intechopen.com/chapters/38485 https://doi.org/10.5772/48151
  4. 4. Zhang X, Ming Y, Fu X, Niu Y, Lin Q, Liang H, et al. PI3K/AKT/p53 pathway inhibits infectious spleen and kidney necrosis virus infection by regulating autophagy and immune responses. Fish Shellfish Immunol. 2022;120:648–57. pmid:34968710
  5. 5. Jeong JB, Kim HY, Jun LJ, Lyu JH, Park NG, Kim JK, et al. Outbreaks and risks of infectious spleen and kidney necrosis virus disease in freshwater ornamental fishes. Dis Aquat Org. 2008;78(3):209–15. pmid:18380219
  6. 6. Nolan D, Stephens F, Crockford M, Jones JB, Snow M. Detection and characterization of viruses of the genus Megalocytivirus in ornamental fish imported into an Australian border quarantine premises: an emerging risk to national biosecurity. J Fish Dis. 2015;38(2):187–95.
  7. 7. Rimmer AE, Becker JA, Tweedie A, Lintermans M, Landos M, Stephens F, et al. Detection of dwarf gourami iridovirus (Infectious spleen and kidney necrosis virus) in populations of ornamental fish prior to and after importation into Australia, with the first evidence of infection in domestically farmed Platy (Xiphophorus maculatus). Prev Vet MedPrev Vet Med. 2015;122(1–2):181–94.
  8. 8. Koda SA, Subramaniam K, Francis-Floyd R, Yanong RP, Frasca S Jr, Groff JM, et al. Phylogenomic characterization of two novel members of the genus Megalocytivirus from archived ornamental fish samples. Dis Aquat Org. 2018;130(1):11–24.
  9. 9. Johnson SJ, Hick PM, Robinson AP, Rimmer AE, Tweedie A, Becker JA. The impact of pooling samples on surveillance sensitivity for the megalocytivirus Infectious spleen and kidney necrosis virus. Transbound Emerg Dis. 2019.
  10. 10. Jeong JB, Jun LJ, Yoo MH, Kim MS, Komisar JL, Jeong HD. Characterization of the DNA nucleotide sequences in the genome of red sea bream iridoviruses isolated in Korea. Aquaculture. 2003;220(1):119–33.
  11. 11. Jung S-J, Oh M-J. Iridovirus‐like infection associated with high mortalities of striped beakperch, Oplegnathus fasciatus (Temminck et Schlegel), in southern coastal areas of the Korean peninsula. J Fish Dis. 2000;23(3):223–6.
  12. 12. Kurita J, Nakajima K, Hirono I, Aoki T. Complete genome sequencing of red sea bream iridovirus (RSIV). Fish Sci. 2002;68(sup2):1113–5.
  13. 13. Sudthongkong C, Miyata M, Miyazaki T. Viral DNA sequences of genes encoding the ATPase and the major capsid protein of tropical iridovirus isolates which are pathogenic to fishes in Japan, South China Sea and Southeast Asian countries. Arch Virol. 2002;147(11):2089–109. pmid:12417946
  14. 14. Gibson-Kueh S, Netto P, Ngoh-Lim GH, Chang SF, Ho LL, Qin QW, et al. The pathology of systemic iridoviral disease in fish. J Comp Pathol. 2003;129(2–3):111–9. pmid:12921716
  15. 15. Nakajima K, Kunita J. Red sea bream iridoviral disease. Uirusu. 2005;55(1):115–25. pmid:16308538
  16. 16. Wang YQ, Lu L, Weng SP, Huang JN, Chan SM, He JG. Molecular epidemiology and phylogenetic analysis of a marine fish infectious spleen and kidney necrosis virus-like (ISKNV-like) virus. Arch Virol. 2007;152(4):763–73. pmid:17131065
  17. 17. Song JY, Kitamura S, Jung SJ, Miyadai T, Tanaka S, Fukuda Y, et al. Genetic variation and geographic distribution of megalocytiviruses. J Microbiol. 2008;46(1):29–33. pmid:18337689
  18. 18. Wang CS, Chao SY, Ku CC, Wen CM, Shih HH. PCR amplification and sequence analysis of the major capsid protein gene of megalocytiviruses isolated in Taiwan. J Fish Dis. 2009;32(6):543–50.
  19. 19. Yanong RPE, Waltzek TB. Megalocytivirus infections in fish, with emphasis on ornamental species. Program in Fish Aquatic Sci (FA182), University of Florida. 2010.
  20. 20. de Lucca Maganha SR, Cardoso PHM, de Carvalho Balian S, de Almeida-Queiroz SR, Fernandes AM, de Sousa RLM. Molecular detection and phylogenetic analysis of megalocytivirus in Brazilian ornamental fish. Arch Virol. 2018;163(8):2225–31. pmid:29623436
  21. 21. Girisha S, Puneeth T, Nithin M, Kumar BN, Ajay S, Vinay T, et al. Red sea bream iridovirus disease (RSIVD) outbreak in Asian seabass (Lates calcarifer) cultured in open estuarine cages along the west coast of India: First report. Aquaculture. 2020;520:734712.
  22. 22. Koda S. Object 1–1. Summary of reported or suspected cases of megalocytivirus through 2021. PhD Dissertation, The University of Florida. 2021. Available from: https://ufdc.ufl.edu/IR00011487/00001.
  23. 23. Kurita J, Nakajima K. Megalocytiviruses. Viruses. 2012;4(4):521–38. pmid:22590684
  24. 24. Subramaniam K, Shariff M, Omar AR, Hair‐Bejo M. Megalocytivirus infection in fish. Rev Aquac. 2012;4(4):221–33.
  25. 25. Go J, Waltzek TB, Subramaniam K, Yun SC, Groff JM, Anderson IG, et al. Detection of infectious spleen and kidney necrosis virus (ISKNV) and turbot reddish body iridovirus (TRBIV) from archival ornamental fish samples. Dis Aquat Organ. 2016;122(2):105–23. pmid:28000602
  26. 26. Johan CAC, Zainathan SC. Megalocytiviruses in ornamental fish: A review. Vet World. 2020;13(11):2565. pmid:33363355
  27. 27. Nakajima K, Sorimachi M. Biological and physico-chemical properties of the iridovirus isolated from cultured red sea bream, Pagrus major. Fish Pathol. 1994;29(1):29–33.
  28. 28. He JG, Wang SP, Zeng K, Huang ZJ, Chan SM. Systemic disease caused by an iridovirus‐like agent in cultured mandarinfish, Siniperca chuatsi (Basilewsky), in China. J Fish Dis. 2000;23(3):219–22.
  29. 29. Mahardika K, Yamamoto A, Miyazaki T. Susceptibility of juvenile humpback grouper Cromileptes altivelis to grouper sleepy disease iridovirus (GSDIV). Dis Aquat Org. 2004;59(1):1–9. pmid:15212286
  30. 30. Go J, Whittington R. Experimental transmission and virulence of a megalocytivirus (Family Iridoviridae) of dwarf gourami (Colisa lalia) from Asia in Murray cod (Maccullochella peelii peelii) in Australia. Aquaculture. 2006;258(1):140–9.
  31. 31. Oh MJ, Kitamura SI, Kim WS, Park MK, Jung SJ, Miyadai T, et al. Susceptibility of marine fish species to a megalocytivirus, turbot iridovirus, isolated from turbot, Psetta maximus (L.). J Fish Dis. 2006;29(7):415–21.
  32. 32. Dong C, Weng S, Luo Y, Huang M, Ai H, Yin Z, et al. A new marine megalocytivirus from spotted knifejaw, Oplegnathus punctatus, and its pathogenicity to freshwater mandarinfish, Siniperca chuatsi. Virus Res. 2010;147(1):98–106.
  33. 33. Kim WS, Oh MJ, Kim JO, Kim D, Jeon CH, Kim JH. Detection of megalocytivirus from imported tropical ornamental fish, paradise fish Macropodus opercularis. Dis Aquat Organ. 2010;90(3):235–9.
  34. 34. Zhang M, Xiao Zz, Hu Yh, Sun L. Characterization of a megalocytivirus from cultured rock bream, Oplegnathus fasciatus (Temminck & Schlege), in China. Aquac Res. 2012;43(4):556–64.
  35. 35. Jin JW, Kim KI, Kim JK, Park NG, Do Jeong H. Dynamics of megalocytivirus transmission between bivalve molluscs and rock bream Oplegnathus fasciatus. Aquaculture. 2014;428:29–34.
  36. 36. de Groof A, Guelen L, Deijs M, van der Wal Y, Miyata M, Ng KS, et al. A novel virus causes scale drop disease in Lates calcarifer. PLoS Pathog. 2015;11(8).
  37. 37. Dong HT, Jitrakorn S, Kayansamruaj P, Pirarat N, Rodkhum C, Rattanarojpong T, et al. Infectious spleen and kidney necrosis disease (ISKND) outbreaks in farmed barramundi (Lates calcarifer) in Vietnam. Fish Shellfish Immunol. 2017;68:65–73.
  38. 38. Fusianto C, Hick PM, Herlambang A, Whittington RJ, Becker JA. Outbreak investigation attributes Infectious spleen and kidney necrosis virus as a necessary cause of a mortality epidemic in farmed grouper (Epinephelus spp.) in Bali, Indonesia. Aquac Rep. 2021;20:100723.
  39. 39. Sukenda S, Gardenia L, Zairin M, Lusiastuti A, Alimudin A. Identification of giant gourami iridovirus (GGIV): a new infectious spleen and kidney necrosis virus (ISKNV) from natural outbreak in cultured Osphronemus goramy. Aquac Int. 2020:1–14.
  40. 40. Chinchar VG, Hick P, Ince IA, Jancovich JK, Marschang R, Qin Q, et al. ICTV virus taxonomy profile: Iridoviridae. J Gen Virol. 2017;98(5):890–1. pmid:28555546
  41. 41. Sriwanayos P, Francis-Floyd R, Stidworthy MF, Petty BD, Kelley K, Waltzek TB. Megalocytivirus infection in orbiculate batfish Platax orbicularis. Dis Aquat Org. 2013;105(1):1–8.
  42. 42. Health WOfA. Animal Diseases 2021. [cited 2021 Dec 16]. Available from: https://www.woah.org/en/what-we-do/animal-health-and-welfare/animal-diseases/
  43. 43. Fu Y, Li Y, Fu W, Su H, Zhang L, Huang C, et al. Scale Drop Disease Virus Associated Yellowfin Seabream (Acanthopagrus latus) Ascites Diseases, Zhuhai, Guangdong, Southern China: The First Description. Viruses. 2021;13(8):1617.
  44. 44. Waltzek TB, Marty GD, Alfaro ME, Bennett WR, Garver KA, Haulena M, et al. Systemic iridovirus from threespine stickleback Gasterosteus aculeatus represents a new megalocytivirus species (family Iridoviridae). Dis Aquat Org. 2012;98(1):41–56.
  45. 45. Halaly MA, Subramaniam K, Koda SA, Popov VL, Stone D, Way K, et al. Characterization of a Novel Megalocytivirus Isolated from European Chub (Squalius cephalus). Viruses. 2019;11(5).
  46. 46. Kurita J, Nakajima K, Hirono I, Aoki T. Polymerase chain reaction (PCR) amplification of DNA of red sea bream iridovirus (RSIV). Fish Pathol. 1998;33(1):17–23.
  47. 47. Kim KI, Lee ES, Do JW, Hwang SD, Cho M, Jung SH, et al. Genetic diversity of Megalocytivirus from cultured fish in Korea. Aquaculture. 2019;509:16–22.
  48. 48. Crane M, Davies K. Aquatic animal health subprogram: establishment of diagnostic expertise for detection and identification of red sea bream iridovirus (RSIV). Project number 2003/620. Canberra: Fisheries Research and Development Corporation; 2006.
  49. 49. Rimmer AE, Becker JA, Tweedie A, Whittington RJ. Development of a quantitative polymerase chain reaction (qPCR) assay for the detection of dwarf gourami iridovirus (DGIV) and other megalocytiviruses and comparison with the Office International des Epizooties (OIE) reference PCR protocol. Aquaculture. 2012;358:155–63.
  50. 50. Jung M-H, Nikapitiya C, Song J-Y, Lee J-H, Lee J, Oh M-J, et al. Gene expression of pro- and anti-apoptotic proteins in rock bream (Oplegnathus fasciatus) infected with megalocytivirus (family Iridoviridae). Fish Shellfish Immunol. 2014;37(1):122–30.
  51. 51. Jin JW, Kim YK, Hong S, Kim YC, Kwon WJ, Jeong HD. Identification and Characterization of Megalocytivirus Type 3 Infection with Low Mortality in Starry Flounder, Platichthys stellatus, in Korea. J World Aquac Soc. 2018;49(1):229–39.
  52. 52. Mishra A, Nam GH, Gim JA, Lee HE, Jo A, Yoon D, et al. Comparative evaluation of MCP gene in worldwide strains of Megalocytivirus (Iridoviridae family) for early diagnostic marker. J Fish Dis. 2018;41(1):105–16. pmid:28914452
  53. 53. Nakajima K, Maeno Y, Fukudome M, Fukuda Y, Tanaka S, Matsuoka S, et al. Immunofluorescence test for the rapid diagnosis of red sea bream iridovirus infection using monoclonal antibody. Fish Pathol. 1995;30(2):115–9.
  54. 54. Nakajima K, Sorimachi M. Production of monoclonal antibodies against red sea bream iridovirus. Fish Pathol. 1995;30:47–52.
  55. 55. Nakajima K, Maeno Y, Yokoyama K, Kaji C, Manabe S. Antigen analysis of red sea bream iridovirus and comparison with other fish iridoviruses. Fish Pathol. 1998;33:73–8.
  56. 56. Imajoh M, Ikawa T, Oshima S. Characterization of a new fibroblast cell line from a tail fin of red sea bream, Pagrus major, and phylogenetic relationships of a recent RSIV isolate in Japan. Virus Res. 2007;126(1–2):45–52.
  57. 57. Dong C, Weng S, Shi X, Xu X, Shi N, He J. Development of a mandarin fish Siniperca chuatsi fry cell line suitable for the study of infectious spleen and kidney necrosis virus (ISKNV). Virus Res. 2008;135(2):273–81.
  58. 58. Fan TJ, Ren BX, Geng XF, Yu QT, Wang LY. Establishment of a turbot fin cell line and its susceptibility to turbot reddish body iridovirus. Cytotechnology. 2010;62(3):217–23. pmid:20502962
  59. 59. Oh SY, Nishizawa T. Establishment of rock bream Oplegnathus fasciatus embryo (RoBE-4) cells with cytolytic infection of red seabream iridovirus (RSIV). J Virol Methods. 2016;238:1–5.
  60. 60. Huang S-M, Kuo S-T, Kuo H-C, Chang S-K. Assessment of fish iridoviruses using a novel cell line GS-1, derived from the spleen of orange-spotted grouper Epinephelus coioides (Hamilton) and susceptible to ranavirus and megalocytivirus. J Vet Med Sci. 2018:18–0078.
  61. 61. Liu XF, Wu YH, Wei SN, Wang N, Li PF, Li YZ, et al. Establishment and characterization of a kidney cell line from kelp grouper Epinephelus moara. Fish Physiol Biochem. 2018;44(1):87–93.
  62. 62. Lua DT, Yasuike M, Hirono I, Aoki T. Transcription program of red sea bream iridovirus as revealed by DNA microarrays. J Virol. 2005;79(24):15151–64. pmid:16306587
  63. 63. Dang TL, Yasuike M, Hirono I, Kondo H, Aoki T. Transcriptional profile of red seabream iridovirus in a fish model as revealed by viral DNA microarrays. Virus Genes. 2007;35(2):449–61. pmid:17393296
  64. 64. Caipang CM, Haraguchi I, Ohira T, Hirono I, Aoki T. Rapid detection of a fish iridovirus using loop-mediated isothermal amplification (LAMP). J Virol Methods. 2004;121(2):155–61. pmid:15381352
  65. 65. Zhang Q, Shi C, Huang J, Jia K, Chen X, Liu H. Rapid diagnosis of turbot reddish body iridovirus in turbot using the loop-mediated isothermal amplification method. J Virol Methods. 2009;158(1–2):18–23. pmid:19187785
  66. 66. Subramaniam K, Shariff M, Omar AR, Hair-Bejo M, Ong BL. Use of acridine orange to visually improve the loop-mediated isothermal amplification for detection of infectious spleen and kidney necrosis virus. 魚病研究. 2014;49(4):173–80.
  67. 67. WOAH (OIE). Chapter 2.3.7 Red sea bream iridoviral disease. In: Manual of diagnostic tests for aquatic animals (World Organisation for Animal Health). 2021 [cited 2021 Dec 16]. Available from: https://www.oie.int/fileadmin/Home/eng/Health_standards/aahm/current/chapitre_rsbid.pdf.
  68. 68. Caipang CM, Hirono I, Aoki T. Development of a real-time PCR assay for the detection and quantification of red seabream iridovirus (RSIV). Fish Pathol. 2003;38(1):1–7.
  69. 69. Sah Putra B, Hick PM, Hall E, Whittington RJ, Khairul R, Becker JA. Prevalence of infectious spleen and kidney necrosis virus (ISKNV), nervous necrosis virus (NNV) and ectoparasites in juvenile Epinephelus spp. farmed in Aceh, Indonesia. Pathogens. 2020;9(7):578.
  70. 70. Mohr PG, Moody NJG, Williams LM, Hoad J, Cummins DM, Davies KR, et al. Molecular confirmation of infectious spleen and kidney necrosis virus (ISKNV) in farmed and imported ornamental fish in Australia. Dis Aquat Org. 2015;116(2):103–10. pmid:26480913
  71. 71. Darling AE, Mau B, Perna NT. progressiveMauve: multiple genome alignment with gene gain, loss and rearrangement. PLoS One. 2010;5(6):e11147. pmid:20593022
  72. 72. Katoh K, Rozewicki J, Yamada KD. MAFFT online service: multiple sequence alignment, interactive sequence choice and visualization. Brief Bioinformatics. 2019;20(4):1160–6. pmid:28968734
  73. 73. Hall TA, editor BioEdit: a user-friendly biological sequence alignment editor and analysis program for Windows 95/98/NT1999 1999: [London]: Information Retrieval Ltd., c1979–c2000.
  74. 74. Stilwell NK, Whittington RJ, Hick PM, Becker JA, Ariel E, van Beurden S, et al. Partial validation of a TaqMan real-time quantitative PCR for the detection of ranaviruses. Dis Aquat Org. 2018;128(2):105–16. pmid:29733025
  75. 75. Clark AS, Behringer DC, Small JM, Waltzek TB. Partial validation of a TaqMan real-time quantitative PCR assay for the detection of Panulirus argus virus 1. Dis Aquat Org. 2018;129(3):193–8. pmid:30154279
  76. 76. Bustin SA, Benes V, Garson JA, Hellemans J, Huggett J, Kubista M, et al. The MIQE Guidelines: M inimum I nformation for Publication of Q uantitative Real-Time PCR E xperiments. Oxford University Press; 2009.
  77. 77. Koda SA, Subramaniam K, Pouder DB, Yanong RP, Frasca S, Popov VL, et al. Complete genome sequences of infectious spleen and kidney necrosis virus isolated from farmed albino rainbow sharks Epalzeorhynchos frenatum in the United States. Virus Genes. 2021;57(5):448–52.
  78. 78. Koda SA, Subramaniam K, Pouder DB, Yanong RP, Waltzek TB. Phylogenomic characterization of red seabream iridovirus from Florida pompano Trachinotus carolinus maricultured in the Caribbean Sea. Arch Virol. 2019;164(4):1209–12.
  79. 79. Stillwell NK. Ranaviruses in aquaculture: genetic diversity, improved molecular tools, and experimental analysis of husbandry factors influencing morbidity. PhD Dissertation, University of Florida. ProQuest Dissertations Publishing. 2017.
  80. 80. Waltzek TB, Miller DL, Gray MJ, Drecktrah B, Briggler JT, MacConnell B, et al. New disease records for hatchery-reared sturgeon. I. Expansion of frog virus 3 host range into Scaphirhynchus albus. Dis Aquat Org. 2014;111(3):219–27.
  81. 81. Viadanna PH, Miller-Morgan T, Peterson T, Way K, Stone DM, Marty GD, et al. Development of a PCR assay to detect cyprinid herpesvirus 1 in koi and common carp. Dis Aquat Org. 2017;123(1):19–27. pmid:28177290
  82. 82. Viadanna PH. Epidemiological and pathological aspects of viral diseases in koi and kinguio. PhD Dissertation, Sao Paulo State University. 2016.
  83. 83. Becker J, Hick P, Hutson K, Trujillo-González A, Tweedie A, Miller T, et al. Aquatic Animal Health Subprogram: Strategic approaches to identifying pathogens of quarantine concern associated with the importation of ornamental fish. Fisheries Research and Development Corporation, Project. 2016(2014/001):83.
  84. 84. Fusianto C, Hick PM, Becker JA. Stability of Infectious spleen and kidney necrosis virus and susceptibility to physical and chemical disinfectants. Aquaculture. 2019;506:104–11.
  85. 85. Crane M, Moody N. Australian and New Zealand standard diagnostic procedures (ANZSDP) for Megalocytivirus infections of finfish. 2018.
  86. 86. Figueiredo HCP, Tavares GC, Dorella FA, Rosa JCC, Marcelino SAC, Pierezan F, et al. First report of infectious spleen and kidney necrosis virus in Nile tilapia in Brazil. Transbound Emerg Dis. 2021. pmid:34223695
  87. 87. Ramírez‐Paredes JG, Paley RK, Hunt W, Feist SW, Stone DM, Field TR, et al. First detection of infectious spleen and kidney necrosis virus (ISKNV) associated with massive mortalities in farmed tilapia in Africa. Transbound Emerg Dis. 2021;68(3):1550–63. pmid:32920975
  88. 88. Inouye K, Yamano K, Maeno Y, Nakajima K, Matsuoka M, Wada Y, et al. Iridovirus infection of cultured red sea bream, Pagrus major. Fish Pathol. 1992;27(1):19–27.
  89. 89. WOAH (OIE). Chapter 1.1.2 Principles and methods of validation of diagnostic assays for infectious diseases. OIE Terrestrial Manual. 2019. Available from: https://www.woah.org/fileadmin/Home/eng/Health_standards/aahm/current/chapitre_validation_diagnostics_assays.pdf
  90. 90. Lee ES, Cho M, Min EY, Jung SH, Kim KI. Novel peptide nucleic acid-based real-time PCR assay for detection and genotyping of Megalocytivirus. Aquaculture. 2020;518:734818.
  91. 91. Kim GH, Kim MJ, Choi HJ, Koo MJ, Kim MJ, Min JG, et al. Evaluation of a novel TaqMan probe-based real-time polymerase chain reaction (PCR) assay for detection and quantitation of red sea bream iridovirus. Fish Aquatic Sci. 2021;24(11):351–9.
  92. 92. Ito T, Yoshiura Y, Kamaishi T, Yoshida K, Nakajima K. Prevalence of red sea bream iridovirus among organs of Japanese amberjack (Seriola quinqueradiata) exposed to cultured red sea bream iridovirus. J Gen Virol. 2013;94(9):2094–101.
  93. 93. Gias E, Johnston C, Keeling S, Spence RP, McDonald WL. Development of real‐time PCR assays for detection of megalocytiviruses in imported ornamental fish. J Fish Dis. 2011;34(8):609–18. pmid:21762172
  94. 94. Hick P, Becker J, Whittington R. Chapter 8: Iridoviruses of fish. Aquaculture virology: Elsevier; 2016. p. 127–52.
  95. 95. Jaramillo D, Dürr S, Hick P, Whittington R. Bayesian estimation of diagnostic sensitivity and specificity of a nervous necrosis virus antibody ELISA. Prev Vet Med. 2016;123:138–42. pmid:26702588
  96. 96. Liu L, Yu L, Fu X, Lin Q, Liang H, Niu Y, et al. First report of megalocytivirus (iridoviridae) in cultured bluegill sunfish, Lepomis macrochirus, in China. Microb Pathog. 2019;135:103617. pmid:31283962
  97. 97. Thanasaksiri K, Takano R, Fukuda K, Chaweepack T, Wongtavatchai J. Identification of infectious spleen and kidney necrosis virus from farmed barramundi Lates calcarifer in Thailand and study of its pathogenicity. Aquaculture. 2019;500:188–91.
  98. 98. Kawato Y, Mohr PG, Crane MSJ, Williams LM, Neave MJ, Cummins DM, et al. Isolation and characterisation of an ISKNV-genotype megalocytivirus from imported angelfish Pterophyllum scalare. Dis Aquat Organ. 2020;140:129–41.
  99. 99. Ni S-Z, Wang Y-J, Hu J-B, Shi J, Xu Y, Zhou S-M, et al. Identification, histopathology, and phylogenetic analysis of an iridovirus from cultivated silver pomfret in Zhejiang Province, East China. Aquaculture. 2021;530:735619.
  100. 100. Sakseepipad C, Nozaki R, Yoshii K, Fukuda Y, Mizuno K, Kawakami H, et al. Development of single nucleotide polymorphism (SNP) application for detection and genotyping of RSIV‐type megalocytiviruses. J Fish Dis. 2021;44(9):1337–42. pmid:33966277
  101. 101. Zhu Z, Duan C, Li Y, Huang C, Weng S, He J, et al. Pathogenicity and histopathology of infectious spleen and kidney necrosis virus genotype II (ISKNV-II) recovering from mass mortality of farmed Asian seabass, Lates calcarifer, in Southern China. Aquaculture. 2021;534:736326.
  102. 102. Tsai J-M, Huang S-L, Yang C-D. PCR Detection and Phylogenetic Analysis of Megalocytivirus Isolates in Farmed Giant Sea Perch Lates calcarifer in Southern Taiwan. Viruses. 2020;12(6):681.
  103. 103. Huang S-M, Tu C, Tseng C-H, Huang C-C, Chou C-C, Kuo H-C, et al. Genetic analysis of fish iridoviruses isolated in Taiwan during 2001–2009. Arch Virol. 2011;156(9):1505–15. pmid:21603939
  104. 104. Kim YJ, Jung SJ, Choi TJ, Kim HR, Rajendran KV, Oh MJ. PCR amplification and sequence analysis of irido-like virus infecting fish in Korea. J Fish Dis. 2002;25(2):121–4.
  105. 105. Do JW, Cha SJ, Kim JS, An EJ, Park MS, Kim JW, et al. Sequence variation in the gene encoding the major capsid protein of Korean fish iridoviruses. Arch Virol. 2005;150(2):351–9. pmid:15549489
  106. 106. Subramaniam K, Gotesman M, Smith CE, Steckler NK, Kelley KL, Groff JM, et al. Megalocytivirus infection in cultured Nile tilapia Oreochromis niloticus. Dis Aquat Org. 2016;119(3):253–8.
  107. 107. Sudthongkong C, Miyata M, Miyazaki T. Iridovirus disease in two ornamental tropical fresh-water fishes: African lampeye and dwarf gourami. Dis Aquat Org. 2002;48(3):163–73. pmid:12033703
  108. 108. Shiu J-Y, Hong J-R, Ku C-C, Wen C-M. Complete genome sequence and phylogenetic analysis of megalocytivirus RSIV-Ku: A natural recombination infectious spleen and kidney necrosis virus. Arch Virol. 2018;163(4):1037–42. pmid:29282546