Abstract
Dolphin Morbillivirus (DMV) is one of the most frequently detected pathogens in stranded cetacean specimens worldwide as well as in Italy. Due to the persistence of DMV in the Mediterranean Sea and to the lack of information about the efficiency of the available diagnostic techniques, the Italian National Reference Centre for diagnostic activities on dead stranded marine mammals (C.Re.Di.Ma) performed the first inter-laboratory ring trial with the aim to standardize a diagnostic biomolecular approach for DMV in Italy. Viral isolation is usually considered the “gold standard” for the definitive diagnosis of most pathogens, but it is not often feasible in DMV diagnosis, due to the poor preservation of virus-targeted tissues in stranded cetacean carcasses, as well as to the lack of appropriate sensitivity of cell lines towards DMV variability. Therefore direct viral detection on tissues by means of reverse transcription-PCR (RT-PCR) represents a valuable option for DMV infection’s diagnosis. For detecting DMV in cetacean die-offs occurred in the Mediterranean basin since 2013, C.Re.Di.Ma developed an RT-PCR based method targeting to a 287 bp fragment of DMV nucleoprotein (N) gene. With the purpose to evaluate its performances in terms of accuracy (Se = sensitivity and Sp = specificity) and precision (reproducibility), it was submitted to a ring trial. So, 12 Public Laboratories belonging to the Italian dead stranded marine mammals diagnostic network were asked to analyze a panel of 40 samples (positive and negative for DMV, using different dilutions of a viral suspension obtained from a cell culture supernatant of a DMV strain) with the aforementioned technique. Furthermore, we also aimed at comparing the accuracy of other 7 molecular methods routinely applied for DMV detection in Italy. For this purpose, the second panel of identical 40 DMV +ve and -ve samples was provided to Laboratories that routinely used DMV detection methods other than those developed by C.Re.Di.Ma, in order to be analyzed simultaneously with the method they usually applied. The C.Re.Di.Ma technique showed high accuracy [mean Se = 97.8% (95% CI 84.2% - 99.3%), mean Sp = 98.1% (95% CI 72.5% - 99.9%)] and very good precision [k combined equal to 0.91 (95% CI 0.87 - 0.95)]. In conclusion, this study highlighted a satisfactory reliability of most of the molecular methods used in Italy for DMV detection.
Highlights
Dolphin Morbillivirus (DMV), a single negative stranded RNA virus within the genus Morbillivirus, subfamily Paramyxovirinae, family Paramyxoviridae [1], is included in the cluster of Cetacean Morbillivirus (CeMV) [2]
“gold standard” for the definitive diagnosis of morbilliviral infections [4]. This is often a challenging issue given the poor preservation of virus-targeted tissues when dealing with stranded cetacean carcasses; direct detection in tissues by means of reverse transcription-PCR (RT-PCR) followed by sequencing represents the first rapid, sensitive and specific tool for DMV detection
The average accuracy values assessed on the Verna et al method resulted as Se = 97.8%, Sp = 98.1%, PPV = 99%, NPV = 96.6% (71.4% - 99%)
Summary
Dolphin Morbillivirus (DMV), a single negative stranded RNA virus within the genus Morbillivirus, subfamily Paramyxovirinae, family Paramyxoviridae [1], is included in the cluster of Cetacean Morbillivirus (CeMV) [2]. DMV was deemed as the most likely cause of three cetacean unusual mortality events (UMEs) occurred since 2011 along Spanish [8] and Italian coastlines [9] [10]. Viral isolation and subsequent PCR identification are usually considered the “gold standard” for the definitive diagnosis of morbilliviral infections [4]. This is often a challenging issue given the poor preservation of virus-targeted tissues when dealing with stranded cetacean carcasses; direct detection in tissues by means of reverse transcription-PCR (RT-PCR) followed by sequencing represents the first rapid, sensitive and specific tool for DMV detection. In the last few years, many conventional and Real-time RT-PCR methods have been developed to detect the presence of DMV worldwide [11] [12] [13]
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