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Recent molecular biology methods for foulbrood and nosemosis diagnosis.

Authors: M P, Rivière; M, Ribière; M P, Chauzat;

Recent molecular biology methods for foulbrood and nosemosis diagnosis.

Abstract

Honey-bee colony losses are an increasing problem in Western countries. There are many different causes, including infections due to various pathogens. Molecular biology techniques have been developed to reliably detect and identify honey-bee pathogens. The most sensitive, specific and reliable is the quantitative real-time polymerase chain reaction (qPCR) methodology. This review of the literature describes various studies where qPCR was used to detect, identify and quantify four major honey-bee pathogens: the bacteria Paenibacillus larvae and Melissococcus plutonius (the causative agents of American foulbrood and European foulbrood, respectively) and the microsporidia Nosema apis and N. ceranae (the causative agents of nosemosis). The application of qPCR to honey-bee pathogens is very recent, and techniques are expected to improve rapidly, leading to potential new prospects for diagnosis and control. Thus, qPCR techniques could shortly become a powerful tool for investigating pathogenic infections and increasing our understanding of colony losses.

Keywords

Nosema, Host-Pathogen Interactions, Enterococcaceae, Animals, Bees, Real-Time Polymerase Chain Reaction, Paenibacillus

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Powered by OpenAIRE graph
Found an issue? Give us feedback
selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
8
Top 10%
Average
Average
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