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Publication Details
AFRICAN RESEARCH NEXUS
SHINING A SPOTLIGHT ON AFRICAN RESEARCH
immunology and microbiology
Sampling and RNA quality for diagnosis of honey bee viruses using quantitative PCR
Journal of Virological Methods, Volume 174, No. 1-2, Year 2011
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Description
Molecular diagnoses of pathogens via ribonucleic acid (RNA) signatures are used widely in honey bee pathology. Such diagnoses can be compromised by ubiquitous and endogenous RNA-degrading enzymes activated after the death of sampled bees. RNA degradation can be minimized by storage at ultra-cold temperatures or by immersion in high-salt buffers. However, these methods are not always available in the field or are costly, driving a search for alternative methods to store and transport bees for RNA analyses. While the impact of storage conditions on RNA integrity has been evaluated, the tolerance of standard RT-qPCR diagnostic methods of honey bee pathogens for suboptimal collection and storage is unknown. Given the short regions of RNA used for pathogen diagnosis (generally amplified regions of 100-200 nucleotides), it is conceivable that even degraded RNA will provide a template for precise diagnosis. In this study, the impact of the two most convenient sample storage and handling methods (+4 °C and ambient temperature) for identifying honey bee virus infections was evaluated by RT-qPCR. The aim was to streamline the methods needed to collect, transport, and store honey bee samples destined for pathogen diagnosis. The data show that samples held at room temperature for times anticipated for sample transport for up to 5 days are suitable for diagnosis of two of the most common and prevalent honey bee viruses, deformed wing virus (DWV) and black queen cell virus (BQCV). The results will be useful for the standardisation of sampling methods across countries and laboratories. © 2011 Elsevier B.V.
Authors & Co-Authors
Dainat, Benjamin
Switzerland, Posieux
Forschungsanstalt Agroscope Liebefeld-posieux
Evans, Jay D.
United States, Beltsville
Usda Ars Beltsville Agricultural Research Center
Chen, Yanping
United States, Beltsville
Usda Ars Beltsville Agricultural Research Center
Neumann, Peter
Switzerland, Posieux
Forschungsanstalt Agroscope Liebefeld-posieux
South Africa, Grahamstown
Rhodes University
Statistics
Citations: 25
Authors: 4
Affiliations: 3
Identifiers
Doi:
10.1016/j.jviromet.2011.03.029
ISSN:
01660934
Study Approach
Quantitative