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Background: Organisms typically face infection by diverse pathogens, and hosts are thought to have developed specific responses to each type of pathogen they encounter. The advent of transcriptomics now makes it possible to test this hypothesis and compare host gene expression responses to multiple pathogens at a genome-wide scale. Here, we performed a meta-analysis of multiple published and new transcriptomes using a newly developed bioinformatics approach that filters genes based on their expression profile across datasets. Thereby, we identified common and unique molecular responses of a model host species, the honey bee (Apis mellifera), to its major pathogens and parasites: the Microsporidia Nosema apis and Nosema ceranae, RNA viruses, and the ectoparasitic mite Varroa destructor, which transmits viruses. Results: We identified a common suite of genes and conserved molecular pathways that respond to all investigated pathogens, a result that suggests a commonality in response mechanisms to diverse pathogens. We found that genes differentially expressed after infection exhibit a higher evolutionary rate than non-differentially expressed genes. Using our new bioinformatics approach, we unveiled additional pathogen-specific responses of honey bees; we found that apoptosis appeared to be an important response following microsporidian infection, while genes from the immune signalling pathways, Toll and Imd, were differentially expressed after Varroa/virus infection. Finally, we applied our bioinformatics approach and generated a gene co-expression network to identify highly connected (hub) genes that may represent important mediators and regulators of anti-pathogen responses. Conclusions: Our meta-analysis generated a comprehensive overview of the host metabolic and other biological processes that mediate interactions between insects and their pathogens. We identified key host genes and pathways that respond to phylogenetically diverse pathogens, representing an important source for future functional studies as well as offering new routes to identify or generate pathogen resilient honey bee stocks. The statistical and bioinformatics approaches that were developed for this study are broadly applicable to synthesize information across transcriptomic datasets. These approaches will likely have utility in addressing a variety of biological questions. [ABSTRACT FROM AUTHOR]

Nosema ceranae and Nosema apis are two fungal pathogens belonging to the phylum Microsporidia and infecting the European honeybee, Apis mellifera. Recent studies have suggested that N. ceranae is more virulent than N. apis both at the individual insect level and at the colony level. Severe colony losses could be attributed to N. ceranae infections, and an unusual form of nosemosis is caused by this pathogen. In the present study, data from a 5-year cohort study of the prevalence of Nosema spp. in Germany, involving about 220 honeybee colonies and a total of 1,997 samples collected from these colonies each spring and autumn and analyzed via species-specific PCR-restriction fragment length polymorphism (RFLP), are described. Statistical analysis of the data revealed no relation between colony mortality and detectable levels of infection with N. ceranae or N. apis. In addition, N. apis is still more prevalent than N. ceranae in the cohort of the German bee population that was analyzed. A possible explanation for these findings could be the marked decrease in spore germination that was observed after even a short exposure to low temperatures (+4°C) for N. ceranae only. Reduced or inhibited N. ceranae spore germination at low temperatures should hamper the infectivity and spread of this pathogen in climatic regions characterized by a rather cold winter season. [ABSTRACT FROM AUTHOR]