Dataset Information

Comparison of three different PCR protocols for the detection of ferlaviruses.

ABSTRACT: BACKGROUND:Ferlaviruses are important pathogens in snakes often associated with respiratory and neurological disease. The detection of ferlaviral RNA by PCR is considered to be the most reliable method for the diagnosis of infection. The PCRs that have been used most commonly for this purpose have not been properly assessed to determine their sensitivity, specificity and ability to detect the known genetic diversity of this group of viruses. The aim of this study was to compare three published PCR protocols so that a single method could be recommended to laboratories that perform this testing. RESULTS:Comparisons were carried out using cell culture isolates and tissues from snakes infected with specific virus genotypes. A single round PCR targeting a short segment of the viral polymerase (L) gene provided the highest sensitivity and specificity, and detected isolated ferlaviruses from all four described genogroups, as well as from tissues of infected snakes. CONCLUSION:A broadly-reactive PCR for the detection of all known ferlaviruses was found to provide a good combination of detection limit, specificity and speed. Based on these criteria, this method is recommended for the diagnosis of ferlavirus infections.

SUBMITTER: Kolesnik E

PROVIDER: S-EPMC6685236 | biostudies-literature | 2019 Aug

REPOSITORIES: biostudies-literature

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Comparison of three different PCR protocols for the detection of ferlaviruses.

Kolesnik Ekaterina E Hyndman Timothy H TH Müller Elisabeth E Pees Michael M Marschang Rachel E RE

BMC veterinary research 20190806 1

<h4>Background</h4>Ferlaviruses are important pathogens in snakes often associated with respiratory and neurological disease. The detection of ferlaviral RNA by PCR is considered to be the most reliable method for the diagnosis of infection. The PCRs that have been used most commonly for this purpose have not been properly assessed to determine their sensitivity, specificity and ability to detect the known genetic diversity of this group of viruses. The aim of this study was to compare three pub ...[more]

PMID: 31387580

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Project description:BACKGROUND:Notwithstanding the efforts of direct-acting antivirals (DAAs) for the treatment of chronically infected hepatitis C virus (HCV) patients, concerns exist regarding the emergence of resistance-associated substitutions (RAS) related to therapy failure. Sanger sequencing is still the reference technique used for the detection of RAS and it detects viral variants present up to 15%, meaning that minority variants are undetectable, using this technique. To date, many studies are focused on the analysis of the impact of HCV low variants using next-generation sequencing (NGS) techniques, but the importance of these minority variants is still debated, and importantly, a common data analysis method is still not defined. METHODS:Serum samples from four patients failing DAAs therapy were collected at baseline and failure, and amplification of NS3, NS5A and NS5B genes was performed on each sample. The genes amplified were sequenced using Sanger and NGS Illumina sequencing and the data generated were analyzed with different approaches. Three different NGS data analysis methods, two homemade in silico pipeline and one commercially available certified user-friendly software, were used to detect low-level variants. RESULTS:The NGS approach allowed to infer also very-low level virus variants. Moreover, data processing allowed to generate high accuracy data which results in reduction in the error rates for each single sequence polymorphism. The results improved the detection of low-level viral variants in the HCV quasispecies of the analyzed patients, and in one patient a low-level RAS related to treatment failure was identified. Importantly, the results obtained from only two out of the three data analysis strategies were in complete agreement in terms of both detection and frequency of RAS. CONCLUSIONS:These results highlight the need to find a robust NGS data analysis method to standardize NGS results for a better comprehension of the clinical role of low-level HCV variants. Based on the extreme importance of data analysis approaches for wet-data interpretation, a detailed description of the used pipelines and further standardization of the in silico analysis could allow increasing diagnostic laboratory networking to unleash true potentials of NGS.

Project description:The bovine udder is colonized by a huge quantity of microorganisms that constitute the intramammary ecosystem, with a specific role in modulating not only udder homeostasis and mastitis susceptibility, but also the quality of the dairy products. However, generating high-quality bacterial DNA can be critical, especially starting from a complex biological matrix like milk, characterized by high fat, protein, and calcium contents. Here, bacterial DNA was recovered from a commercial ultra-high-temperature (UHT) milk sample artificially spiked with a predetermined mock community composition and from three bulk tank milk (raw milk) samples. The DNA was isolated using three different protocols to evaluate the effect of the extraction procedures on the milk microbiota composition. In the mock community experiment, the bacterial profiles generated by the three DNA extraction protocols were profoundly different, with the genera Staphylococcus, Lactobacillus, Listeria, and Salmonella underestimated by all the protocols. Only one protocol revealed values close to the expected abundances for Escherichia/Shigella spp., Bacillus spp., Enterococcus spp., and Pseudomonas spp. On the other hand, the nonspiked UHT milk sample exhibited a similar microbiota composition, revealing the prevalence of Acinetobacter spp., for all the DNA extraction protocols. For the raw milk samples, the three DNA extraction kits performed differently, revealing significant separations in both the microbial richness (alpha diversity) and composition (beta diversity). Our study highlights the presence of significant differences among these procedures, probably due to the different DNA extracting capacities and to the different properties of the milk samples, revealing that the selection of DNA extraction protocol is a critical point. IMPORTANCE The advance of high-throughput technologies has increased our knowledge of the world of microorganisms, especially of microbial populations inhabiting living animals. This study provides evidence that milk, as other complex sources, could be critical for generating high-quality DNA for microbiota analysis. In addition, it demonstrates that the microbial population highlighted by metagenomic studies changes in relation to different DNA extraction procedures, revealing that attention should be paid especially when comparing different studies.

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Dataset Information

Comparison of three different PCR protocols for the detection of ferlaviruses.

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Comparison of three different PCR protocols for the detection of ferlaviruses.

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