Deborah Kukielka Zunzunegui defended the PhD Thesis at the Faculty of Veterinary Medicine of the Complutense University of Madrid

June 30^th, 2010

Spain is the main honeybee producer country in Europe holding approximately 2.500.000 beehives. Honeybees are highly important insects due to the honeybee production and their use as natural pollinators of several agricultural products. Therefore, the problems they suffer affect beekeepers, the agricultural and the scientific community.
Due to the increasing disappearance phenomena that Apis mellifera has been suffering in the last years, known as Colony Collapse Disorder (CCD), several research lines have arisen with the goal of reaching a deeper knowledge of the pathologies that affect the honeybees. In general and more concisely related to the viral diseases, the information about these problems is still scarce due to the absence of suitable, specific and sensitive diagnosis methods. Therefore, there is a need to develop new viral diagnostic techniques, and based on them, perform prevalence and distribution studies to analyze the health status of honeybees and be able to look for solutions to their problems. Then, supported by two research projects (API06-005. COORD-2 and RTA2005-00164-C02-02), several diagnostic methods and studies focused on discerning the viral distribution and their potential diffusion routes among Spanish beehives have been developed. To do so, SYBR Green (SG) real time RT-PCR techniques were developed for the first time to detect black queen cell virus (BQCV), deformed wing virus (DWV) and sacbrood bee virus (SBV). Moreover, conventional RT-PCR were adapted to SG real time RT-PCR to detect acute bee paralysis virus (ABPV), Kashmir bee virus (KBV), chronic bee paralysis virus (CBPV) and Israeli acute paralysis virus (IAPV). All of them were optimized and validated determining their sensitivity limits and specificity. Due to the SG real time RT-PCR advantages, standard curves were developed to quantify the viral load of the analyzed samples.
In addition, the number of beehives per region was adjusted to the number of total collected samples per region and by using mixed Bayesian regression models, the risk of finding BQCV, DWV and KBV in Spain, was calculated. Results show it increases when there is a higher number of beehives in the area. Based on the existing residual risk in the rest of the country, it can be concluded that the presence of these viral diseases in the South-East is also influenced by other risk factors not included in the analysis.
As conclusion, new diagnostic techniques have been developed and adapted for the detection and quantification of viral diseases in honeybees as well as a first analysis of their geographical distribution in Spain