Sex-related differences in susceptibility to pathogens are a common phenomenon in animals. In the eusocial Hymenoptera the two female castes, workers and queens, are diploid and males are haploid. The haploid susceptibility hypothesis predicts that haploid males are more susceptible to pathogen infections compared to females. Here we test this hypothesis using adult male (drone) and female (worker) honey bees (Apis mellifera), inoculated with the gut endoparasite Nosema ceranae and/or black queen cell virus (BQCV). These pathogens were chosen due to previously reported synergistic interactions between Nosema apis and BQCV. Our data do not support synergistic interactions between N. ceranae and BQCV and also suggest that BQCV has limited effect on both drone and worker health, regardless of the infection level. However, the data clearly show that, despite lower levels of N. ceranae spores in drones than in workers, Nosema-infected drones had both a higher mortality and a lower body mass than non-infected drones, across all treatment groups, while the mortality and body mass of worker bees were largely unaffected by N. ceranae infection, suggesting that drones are more susceptible to this pathogen than workers. In conclusion, the data reveal considerable sex-specific differences in pathogen susceptibility in honey bees and highlight the importance of ultimate measures for determining susceptibility, such as mortality and body quality, rather than mere infection levels.
Citation: Retschnig G, Williams GR, Mehmann MM, Yañez O, de Miranda JR, Neumann P (2014) Sex-Specific Differences in Pathogen Susceptibility in Honey Bees (Apis mellifera). PLoS ONE 9(1): e85261. doi:10.1371/journal.pone.0085261
Editor: Wulfila Gronenberg, University of Arizona, United States of America
Received: July 18, 2013; Accepted: November 25, 2013; Published: January 17, 2014
Copyright: © 2014 Retschnig, et al. This is an open-access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Funding: The research has received funding from the European Union Seventh Framework Programme (FP7/2007-2013) under grant agreement no. (244956 CP-FP), BEEDOC (BEes in Europe and the Decline Of Colonies), as well as the Vinetum, Swiss National Science and Ricola foundations. The funders had no role in study design, data collection and analysis, decision to publish, or preparation of the manuscript.
Competing interests: The authors have declared that no competing interests exist.
Sex-specific phenotypic differences can influence susceptibility to various stressors encountered in the environment such as pathogens or toxins . Susceptibility, defined as the likelihood to develop ill effects from an external agent , can be measured using multiple indices. For example, susceptibility to a pathogen can not only refer to host mortality, but also to sub-lethal responses (e.g. reduced body mass), severity of infection (infection level susceptibility), or likelihood of infection (infection or disease susceptibility).
Differential susceptibility to pathogens between sexes is well known in numerous species, particularly in vertebrates –. For invertebrates, Morton and García del Pino (2013) demonstrated that in house crickets (Acheta domesticus), American cockroaches (Periplaneta americana), and flatheaded rootborers (Capnodis tenebrionis), males exhibited higher immunocompetence to pathogens than females ; the opposite was observed for crickets (Gryllus texensis) and scorpionflies (Panorpa vulgaris) –. Differences in immunocompetence between sexes are likely the result of complex investment strategies that differentially partition limited resources to vital functions and processes, including reproduction . For species exhibiting haplo-diploidy, the haploid susceptibility hypothesis proposes that the absence of heterozygosity at immune loci in haploid individuals may be responsible for differential immunocompetence between haploid and diploid individuals . Ruiz-González and Brown (2006) reviewed seven studies that examined the impact of the pathogens Crithidia bombi, Nosema bombi, or Locustacarus buchneri in various bumble bee (Bombus spp.) species . Haploid males had lower parasite prevalence than diploid females in 15 of 26 investigated host-parasite combinations.
This study investigated sex-specific differences in pathogen susceptibility in the western honey bee (Apis mellifera). The honey bee is the most important pollinator of agricultural crops –, and has over the last several decades suffered increasingly severe colony deaths in many regions of the northern hemisphere . Although the reasons for increased colony mortality are not fully understood, it is likely that multiple stressors, acting either alone or in combination, are to blame. These include changing agricultural practices, beekeeper management issues, as well as introduced parasites and pathogens –.
Honey bee microfloral communities consist of numerous viruses, fungi, microsporidia and bacteria –. This simultaneous co-infection offers a plethora of opportunities for inter-specific microbial interactions that could be symbiotic (co-dependence), synergistic (mutually or unilaterally facilitating), or antagonistic (mutually or unilaterally inhibitory), which could have considerable influence on both pathogen distribution and virulence . There are a number of examples of such interactions among honey bee parasites and pathogens. For example, the midgut microsporidian Nosema apis is a facultative requirement for successful infection of black queen cell virus (BQCV) and an obligatory requirement for bee virus Y (BVY) infection . Similarly, bee virus X (BVX) is associated with, and partially dependent on, co-infection with the protozoan Malphigamoeba mellifica . Conversely, a negative association was observed between Nosema ceranae and deformed wing virus (DWV) in the honey bee midgut, although not for whole bees or at colony level –. Further examples of antagonistic interactions include those between lactic acid bacteria and both Paenibacillus larvae – and Melissococcus plutonius ; causative agents of American foulbrood (AFB) and European foulbrood (EFB), respectively.
Most studies investigating interactions among honey bee pathogens have focussed on workers and queens , – rather than on drones . Drones are a critical element of both apicultural breeding and natural colony fitness selection . They exhibit substantial differences in behaviour and physiology compared to workers or queens  that may influence their susceptibility to pathogens. Although drones have been the subject of numerous studies relating to their reproductive and genetic functions –, relatively little is known about the impact and interactions between common honey bee pathogens in drones, and even less about differential disease susceptibility between the honey bee sexes. Drones are much more susceptible than workers to Varroa destructor, a parasitic mite that reproduces in brood –, but less susceptible to deformed wing virus, which is vectored by the mite, at least when comparing live (surviving) drones and workers . Both drones and workers are equally susceptible to N. apis infection . However, corresponding data for N. ceranae, a similar pathogen, is currently lacking. Both are widespread gut pathogens – transmitted horizontally via the faecal-oral route , inflicting gut tissue damage  and suppressing the honey bee immune response –, thereby possibly promoting viral infections and reducing honey bee longevity . BQCV is one such Nosema-associated virus . This virus also infects mid-gut tissues and can be transmitted via the faecal-oral route but does not cause visible symptoms in infected adult honey bees  and to date, very little is known about potential effects on honey bee health. BQCV is closely associated with N. apis infection  but how it interacts with N. ceranae is still unclear. Nothing is known about sex-specific differences in susceptibility to BQCV between drone and worker bees.
The aim of these experiments was to assess the susceptibility of workers and drones to N. ceranae and BQCV, as well as their inter-specific interaction, using common indices of honey bee health. We used host mortality (e.g. ), body mass (e.g. ) and pathogen infection level as measures of susceptibility. The experiments were conducted using standardized laboratory hoarding cages, in order to maximize control over the infection process and the environmental conditions.
No animal use protocol was required by the Veterinary Office of the district of Bern or the Federal Veterinary Office to perform this research on honey bees. No endangered or protected species were involved in the study. Privately owned land was used and accessed only after permission from the landowner.
The experiment was conducted during summer 2011 at Agroscope Liebefeld-Posieux Research Station ALP-HARAS in Bern, Switzerland, and consisted of 80 cm3 disposable hoarding cages, each containing either 10 drones plus 10 attendant workers or 20 workers. The cages were assigned to a fully-crossed design of N. ceranae and BQCV treatments (Table 1), with four and five replicate cages per treatment group for the drone-plus-workers and the workers-only experimental groups, respectively. The 1∶1 drone:worker ratio for the drone part of the experiment was adapted from prior recommendations of 0.5∶1 , 1.5∶1  and 2∶1  drones∶workers, to ensure adequate attendance of the drones.
Source of honey bees
Experimental honey bees (A. mellifera) were obtained by collecting brood frames from 3 queen-right colonies during the local mating season (June 2011). Those colonies had low V. destructor infestation levels (<3 mites per 100 bees), as determined using the soapy water wash method .
To obtain uniformly aged drones, the queens of the 3 colonies were confined for 2 days to drone frames. Close to emergence the frames were removed and housed individually in a wood and glass frame cage in an incubator with typical brood nest conditions  of 34.5°C, ≥50% relative humidity and near total darkness –. The frames were removed at 2 hour intervals to detect drone emergence. When antennae appeared, the wax caps were carefully removed manually using blunt forceps and the emerged drone and its respective brood cell were inspected with an LED light for the presence of V. destructor. Drones that were exposed to V. destructor during development were discarded. Drones that developed in cells without V. destructor were collected in a large 600 cm3 metal hoarding cage together with equal numbers of newly emerged workers from the same colonies. When enough drones were collected for the entire experiment, they were randomly assigned to the experimental cages and treatment groups. A separate cage containing workers of the same age and origin as the drones was kept in the incubator under identical conditions throughout the experiment to replace any dead attendant workers in the drone experimental cages.
To obtain experimental worker bees, two brood frames from the same colonies supplying the experimental drones were placed in a metal and glass frame cage in the incubator as described above. Every 4–10 h, newly emerged workers were carefully collected from the frames using forceps, inspected individually for V. destructor and transferred to a large 600 cm3 metal hoarding cage. Only non-infested workers were included in the cage experiment. Since V. destructor mites have >8-fold higher preference for drone brood than for worker brood , –, the emerging drone brood was checked more intensively for mite infestation than the emerging worker brood. All experimental bees from the three source colonies were mixed and randomly allocated to their experimental cages within 2 days after collection. During this time they were maintained in large metal hoarding cages at incubator conditions and were supplied ad libitum with 50% sucrose solution.
Source of pathogens
Nosema ceranae spores were obtained by preparing an extract in water from the midguts of six highly infected foragers  collected from the entrances of two Nosema-infected colonies located at the local research apiary. Spores were counted using a haemocytometer (Thoma, L.O. Labor Optik) and the extract was diluted to 20,000 spores per µl. The spores were identified as N. ceranae by qualitative PCR using a set of species-specific Nosema primers . Briefly, genomic DNA of crushed midguts (in water) was extracted using the Nucleospin® Tissue kit (Macherey-Nagel) according to the manufacturer guidelines. The PCR was then performed using the Goldstar® DNA Polymerase (Eurogentec). The PCR involved 2 min at 94°C, 30 cycles of 30 s at 94°C, 30 s at 56°C, 30 s at 72°C and 7 minutes at 72°C. A control extract was prepared from the midguts of six non-infected adult bees that originated from the same two colonies and were found to be free from N. ceranae.
The BQCV inoculum was prepared by propagating a 10−4 dilution of a BQCV reference isolate  in 150 white-eyed honeybee pupae and preparing a chloroform-clarified extract in 10 mM phosphate buffer (pH 7.0)/0.02% diethyl dithiocarbamate, as described in de Miranda et al., (2013) . The inoculum contained ∼1.4×109 BQCV genome copies per µl extract and had no detectable contamination with ABPV, KBV, CBPV, DWV, VDV-1, LSV-1 and LSV-2; negligible (<0.0001%) contamination with IAPV and SBV, and <1% contamination with SBPV, as determined by RT-qPCR using the methods of Locke et al., (2012) . A control extract was prepared from non-inoculated pupae. None of the viruses could be detected in this control extract, except BQCV (∼1.5×103 copies/µl) and SBV (∼2.7×108 copies/µl).
Inoculation, incubation and sampling
For both the drone and worker part of the experiment, individual experimental drones and workers (but not the attendant workers in the drone cages) were each inoculated orally at 0 d with either 5 µl of the N. ceranae spore suspension (i.e. 100,000 spores per bee) or control suspension, both as 50% w/v sucrose solutions, using micropipettes (Table 1). Individuals were starved for 2 h before inoculation; those that did not consume the entire inoculum were discarded. Immediately after inoculation, workers were kept separated for approximately 20 min, the required time for the spores to be transported far enough in the intestinal system to avoid the transfer of the inoculum via trophallaxis , –. This precaution was not necessary for the drones because they are only recipients during trophallaxis .
BQCV inoculation took place 7 days after Nosema inoculation. Surviving individual experimental drones and workers (but not the attendant workers in the drone cages) each received an oral inoculum at 7 d of either 5 µl BQCV suspension (1 µl of pure extract in sucrose solution, i.e. 1.4×109 BQCV genome copies/bee) or control extract, both as 50% w/v sucrose solution (Table 1). After inoculation with BQCV the experimental drones and workers were again isolated for approximately 20 min to prevent transfer of the inoculum through trophallaxis .
The bees in the experimental cages were fed 50% (w/v) sucrose solution ad libitum, using 1.5 ml Eppendorf tubes containing a single basal perforation, as well as gamma-irradiated sterilized pollen paste (10% pollen, 60% sugar, 30% water in 0.2 ml tubes with a 0.8 mm opening) for the duration of each assay. The cages were maintained in an incubator in complete darkness at 30°C and ≥60% relative humidity, reflecting natural hive conditions . At 14 d, all surviving individuals were frozen and stored at −20°C until further analyses .
Host mortality and body mass
Dead individuals were removed daily from their cages, recorded and stored at −20°C. For the drone experiment, a 1∶1 drone∶worker ratio was maintained throughout the experiment by removing or adding attendant workers as required.
The body mass was determined at the end of the experiment, on day 14, for the surviving experimental drones (total n = 15, 13, 3, 5 for control, BQCV, N. ceranae & BQCV, N. ceranae treatment groups, respectively) and a subset of the experimental workers (n = 25 per treatment group). For both drones and workers, only live bees were collected for weighing, thereby excluding the possibility to dry out after death. Each bee was weighed individually to the nearest 0.1 mg using an analytic scale (Mettler Toledo AT400).
Nosema ceranae species confirmation and quantification
For both the drone and worker parts of the experiment, N. ceranae spore amounts were quantified in randomly selected individuals terminated at 14 d (n = 5 per cage). If fewer than five live drones were available on 14 d, those drones that died immediately prior to termination on 14 d were also included for the pathogen analyses (total n = 16, 13, 7, 9 for control, BQCV, N. ceranae & BQCV, N. ceranae treatment groups, respectively). Each drone or worker abdomen was homogenised in a 2 ml Eppendorf tube using a bead mill homogeniser (MM300 Retsch), one metal bead and either 300 or 250 µl TN buffer, for drones and workers respectively. Each homogenate was diluted to 1 ml prior to spore quantification, which was done according to Cantwell (1970)  using a haemocytometer (Thoma, L.O. Labor Optik) and a light microscope (Laborlux K, Leitz Wetzlar, Germany).
RNA extraction and BQCV qPCR assays
For both the drone and worker parts of the experiment, BQCV was analysed in the same individuals as used for the N. ceranae quantification. Total RNA was extracted from aliquots of the homogenized abdomen suspension of each individual using the Nucleospin® RNA II kit (Macherey-Nagel) according to the manufacturer's guidelines. The extracted RNA was eluted in 50 µl of RNAse-free water. Reverse transcription was performed in 20 µl final volume using 10 µl of extracted RNA (2.5 ug), 200 ng of random hexamer primers using the Thermoscript™ RT system (Invitrogen), following the manufacturer guidelines. Before qPCR amplification, the cDNAs were diluted 10-fold in nuclease-free water. Each diluted cDNA sample was amplified in triplicate by qPCR using the KAPA SYBR® FAST Universal Mastermix kit (KAPA, Biosystems) in a RotorGene-3000A thermocycler (Corbett Research). Specific primers were used for BQCV (sequence 5′ - 3′: F: CGA CAG CGT GCC AAA GAG A, R: CGC CCA GCT TTG AAA CAG A) and for the honey bee β-Actin gene (sequence 5′ - 3′: F: CGT GCC GAT AGT ATT CTT G, R: CTT CGT CAC CAA CAT AGG), for virus and reference gene RNA quantification, respectively. The qPCR cycling conditions consisted of 3 min at 95°C, for enzyme activation, followed by 40 cycles of: 3 s at 95°C, for denaturation; 40 s at 60°C for annealing and extension, followed by fluorescence reading. Each run contained a 10-fold standard dilution series for both BQCV and the honey bee β-Actin gene. Runs were analysed using the programme LinRegPCR (HFRC, NL, v. 11.1). BQCV titres were normalised with those of the correspondent β-Actin. The data were converted to genome copies per bee by accounting for the various dilutions used in the cDNA preparation.
Survival analyses were performed in SPSS (IBM SPSS Statistics 19) using Kaplan Meier Log-Rank for censored data, since some individuals were terminated at 14 d. Comparison of body mass as well as N. ceranae and BQCV amounts among treatment groups were performed in R (R Foundation for Statistical Computing, version 2.15.2012-09-19) using ANOVA to detect overall differences, as well as Tukey's HSD for multiple comparisons within treatment groups. Nosema ceranae and BQCV amounts were square root- and log10-transformed, respectively, to improve fit to normality prior to parametric statistical tests. For all statistical analyses, a significance level of α = 0.05 was applied. For analysis of the inter-specific interactions, parametric Pearson test for correlations in SPSS (IBM SPSS Statistics 19) using log10-transformed BQCV and non-transformed N. ceranae data (normally distributed in this treatment group) was used.
Host mortality and body mass
Drones inoculated with N. ceranae spores, regardless of co-inoculation with BQCV, had significantly greater mortality than those not inoculated with Nosema (Kaplan-Meier Log-Rank, both Ps<0.04), whereas worker mortality did not differ significantly among treatment groups (Kaplan-Meier Log-Rank, P = 0.89; Fig. 1). In all treatment groups, 12 to 16% of the workers died during the experiment, whereas drone mortality rates were much higher at 62.5% (control), 65% (BQCV), 87.5% (N. ceranae) and 92.5% (N. ceranae & BQCV). Overall, drone survivorship was significantly lower than workers (Kaplan-Meier Log-Rank, all Ps<0.001; Fig. 1).
Bees that were terminated on day 14 were treated as censured in the analyses. Drones showed significant higher mortality in the treatment groups that were challenged with N. ceranae (Ps = 0.037), indicated by different letters (a, b) in the figure. Workers of the different treatment groups showed no differences in mortality. The groups with BQCV-inoculation differ from the other groups in terms of treatment from day 7 onwards.
The mean body mass of N. ceranae inoculated drones was 170.78 mg compared to 190.27 mg for N. ceranae & BQCV co-inoculated drones, while the control and BQCV-inoculated drones were 202.43 and 211.4 mg on average, respectively (Table 2). The mass of drones inoculated with N. ceranae spores alone was significantly lower than the control and BQCV treatment groups (Tukey's HSD, both Ps<0.05), but not significantly less than the mixed N. ceranae & BQCV treatment group (Tukey's HSD, P = 0.63; Fig. 2). No significant difference in drone mass was observed among control, BQCV, or N. ceranae & BQCV treatment groups (Tukey's HSD, all Ps>0.45). For the worker experiment, mean body mass ranged from 103.06 mg (N. ceranae) to 112.97 mg (control) for all treatment groups and did not significantly differ among the groups (Tukey's HSD, all Ps>0.45; Fig. 2 and Table 2).
The boxplots show interquartile range (box), median (black line within the interquartile range), data range (dashed vertical lines) and outliers (open dots). Significant differences (all Ps<0.05) were detected between the N. ceranae and control (* = P<0.05) as well as N. ceranae and BQCV (** = P<0.01) group in the drones as indicated by black horizontal bars between the respective treatment groups under the boxplots. No differences were detected between the treatment groups of the workers.
Nosema ceranae quantification
All individuals (workers and drones) that were experimentally inoculated with N. ceranae spores developed detectable Nosema infections. At 14 d after inoculation with N. ceranae, drones had mean spore amounts of 6.93×106 (SD (standard deviation): 3.88×106) spores per bee in the N. ceranae group and 11.62×106 (SD: 7.28×106) spores per bee when inoculated with both pathogens. Spore amounts in N. ceranae inoculated workers were 19.43×106 (SD: 11.47×106) spores per bee in the N. ceranae group and 16.6×106 (SD: 11.11.×106) in the N. ceranae & BQCV group, respectively. A small percentage of the non-inoculated drones (<16%) and workers (<24%) had low levels of spore amounts. The mean spore values of the non-inoculated drones were 0.0156×106 (SD: 0.044×106) spores per bee for the controls and 0.0154×106 (SD: 0.043×106) for the drones that were inoculated with BQCV only. For the workers, the controls showed mean spore amounts of 0.05×106 (SD: 0.13×106) spores per bee and the BQCV-inoculated workers 0.064×106 (SD: 0.16×106) spores per bee (Fig. 3). No differences in spore amounts were observed among treatment groups that were inoculated with N. ceranae, regardless of BQCV inoculation for both drones and workers (Tukey's HSD, all Ps>0.1). Drones inoculated with N. ceranae but not with BQCV showed significantly lower pathogen intensities than workers from the same treatment group (ANOVA, P<0.01; Fig. 3). The comparison of spore amounts in drones and workers revealed higher spore loads in workers in the N. ceranae treatment (Tukey's HSD, P<0.001, Fig. 3), but no differences in the other treatments.
The boxplots show interquartile range (box), median (black line within the interquartile range), data range (dashed vertical lines) and outliers (open dots). Significant differences within the bee type (drones and workers) are marked through different letters. Significant differences between the treatment groups of workers and drones are indicated by a black horizontal bar (*** = P<0.001).
Drones inoculated with BQCV only showed an average (±SD) of 109.23±0.64 viral copies per bee, while those infected with both, N. ceranae and BQCV showed an average of 108.81±0.77 viral copies per bee. Non-BQCV-inoculated drones of the N. ceranae only group exhibited an average of 108.42±1.2 viral copies and the control drones 106.71±0.96 viral copies per bee, respectively. The mean viral copies of BQCV per bee in the workers were in the range of 109.91±0.48 for workers that were inoculated with N. ceranae and BQCV, to 1010.44±0.86 copies per bee for workers that were inoculated with BQCV only. The mean viral copies per bee for the workers that were not inoculated with BQCV was 106.49±1.77 viral copies in the N. ceranae only group to 106.55±1.68 viral copies per bee in the control group. At 14 d drones from the control treatment exhibited significantly lower BQCV loads than other treatment groups (Tukey's HSD test, all Ps<0.001); no difference was observed among BQCV alone, N. ceranae & BQCV, and N. ceranae alone treatments (Tukey's HSD test, all Ps>0.55; Fig. 4). For the worker experiment at the same time period, viral load was significantly greater in treatments inoculated with BQCV versus those that were not (Tukey's HSD test, all Ps<0.001), however, there was no difference in viral loads between treatments inoculated (BQCV versus N. ceranae & BQCV, Tukey's HSD test, P>0.49) or not inoculated with virus (Control versus N. ceranae, Tukey's HSD test, P>0.99). Significantly higher viral loads were observed in workers inoculated with BQCV compared to drones (ANOVA, all Ps<0.001; Fig. 4) apart from for the N. ceranae treatment group (ANOVA, P<0.001).
The boxplots show interquartile range (box), median (black line within the interquartile range), data range (dashed vertical lines) and outliers (open dots). Significant differences within the bee type (drones and workers) are marked through different letters. Significant differences between the treatment groups of workers and drones are indicated by black horizontal bars (***Ps<0.001).
No correlation was observed between the amounts of BQCV and N. ceranae in either drones or workers inoculated with both pathogens (Pearson Correlation, workers: R = −0.048, P = 0.82; drones R = 0.177, P = 0.704).
The data imply that there are sex-specific differences in honey bee susceptibility to the pathogens Nosema ceranae and, to a lesser degree, BQCV, as indexed by mortality, body mass and infection level. During the 14-day study period, drones suffered elevated mortality and those surviving had reduced body mass due to N. ceranae infection, but not BQCV infection, while worker mortality and body mass was unaffected by either N. ceranae or BQCV. Surviving drones also contained lower titres of both N. ceranae and BQCV than surviving workers, while there was no evidence of any specific interaction between N. ceranae and BQCV in these experiments: neither N. ceranae nor BQCV was particularly affected by co-infection with the other pathogen, in both drones and workers. These global findings support previous studies demonstrating differences between honey bee drone and worker susceptibility to pathogens –, –, , as well as similar studies on bumble bees (Bombus spp.) that observed no clear trend of sex-specific pathogen susceptibility differences . Previous reports of a co-dependent interaction between N. apis and BQCV  were not replicated here with N. ceranae and BQCV. However, these observations have to be interpreted within the context of the greater overall sensitivity of drones to the laboratory hoarding cage conditions, compared to the workers, as reflected by their different control mortalities during the 14 day trial period. This increased sensitivity and reduced lifespan has been observed repeatedly for drones maintained under artificial conditions (e.g. , ). In fact, the drones in this study showed considerably better control survival than previously reported (e.g. , ). Workers also survive less well in hoarding cages than in a natural colony environment, but are much more resilient to these conditions than drones. This reflects that drones and workers react differently to changes in their environments, and that hoarding cages are a more stressful environment (for both) than the natural colony environment. However, these (unavoidable) limitations to the experimental system used here have significant bearing on how the data may be interpreted, and pose clear corresponding limitations on how far they can be extrapolated. Broadly regarded, the observation that within the 14 day period of the experiment drones experience greater levels of stress in hoarding cages than workers, as evidenced by their greater background mortality, may also make them more susceptible to pathogens such as N. ceranae and BQCV. If the workers were investigated under conditions generating a similar background control mortality as for the drones here (for example, by extending the window of observation), they too might show elevated mortality due to pathogen infection. However, the existential differences between drones and workers and their relationship with stress will also affect their relationships with the pathogens that they share, which may ultimately be attributable to their very different roles for colony functionality  and/or ploidy levels . Below we discuss each of the major findings of this study in turn, and interpret them within the contexts outlined above, and the limitations set by the study conditions.
Nosema ceranae showed a strong effect on drones in the present study. Even though the overall mortality was higher in the drones, the impact of N. ceranae on drone survival in cages was significant, thereby highlighting the strong effect this midgut parasite can have on male bees. Consistent with the mortality data, N. ceranae infection also resulted in lower body mass in drones, which constitutes another commonly measured indicator for the health status of honey bees (e.g. ) and further confirms the considerable impact of N. ceranae on drones.
Nosema ceranae parasitism in drones has not yet been closely investigated. Natural infections occur in both immature and mature drones , and population-specific differences in host survivorship as a response to parasitism have been observed . Our experiments confirmed that N. ceranae can successfully invade and reproduce in drones, and that parasitism can result in increased host mortality. Interestingly, fewer than 2 million spores 8 days post-infection results in reduced survivorship . Our results also suggest that drone mortality due to N. ceranae infection can occur within one week of initial parasitism.
Numerous studies have investigated effects of N. ceranae in honey bee workers under in vitro conditions. In this study, no effect of N. ceranae parasitism on worker mortality or body condition was observed, whereas other studies have demonstrated varying levels of pathogenicity (e.g. –). These differences could be the result of various genetic , environment , or methodological ,  influences. The same factors may be responsible for differences in infection levels observed among studies. We observed spore amounts in the workers (∼ = 16–20 million spores per individual 14 d post-infection) that were similar to previous studies at approximately the same period post-infection (e.g. , ), but not all (e.g. ).
The comparison of observed spore amounts in drones and workers of this study revealed significantly higher levels in workers than drones, demonstrating a sex-specific difference in infection level susceptibility. Interestingly, no sex-specific difference in susceptibility was observed for N. apis when measured as parasite prevalence in field-collected bees . This highlights the importance of type of study (laboratory or field), type of infection or susceptibility measurement. For example, Higes et al. (2008) argue that infection prevalence constitutes a better indicator for colony disease from N. ceranae infection than mean infection level . Differences in N. ceranae susceptibility between the sexes could be due to allelic variation associated with haplo-diploidy , or because of distinct resource investment strategies that influence resistance to disease . Another contributing factor may be differential immune responses to disease by drones and workers. Drones from honey bee lineages selected for Nosema tolerance have an up-regulated immune response, suggesting that the Toll pathway is important for defence against N. ceranae . However, N. ceranae-infected workers may suffer from immunosuppression through down-regulation of genes that are part of the honey bee's humoral (defensin, abaecin, apidaecin and hymenoptaecin) and cellular (glucose dehydrogenase) immune system –. The sex-specific differences in the measured infection levels may also be explained by general physiological differences between drones and workers  that could influence the dynamics of infection development and thereby the infection level at any given point in time. Indeed, it may be the case that the infection develops differentially in drones and workers over time for a variety of reasons, and that this might be a potential explanation for the differences in the titres since we looked at both drones and workers at the very same day. A further explanation for lower titres in surviving drones may actually be that higher titres would have killed them. Since infected workers do not show an increased mortality, they can tolerate higher pathogen titres, thereby also confirming differences in pathogen susceptibility.
Contrary to N. ceranae, inoculation with BQCV had no impact on the mortality or body mass of drones or workers. BQCV is a very common virus with a broad geographic distribution in European honey bees (e.g. , –), therefore it was not surprising that low levels of virus were detected in our non-inoculated bees. Very little is known of how BQCV affects individual drone and worker honey bees. It may damage and even kill developing drone  as well as queen larvae  during natural infections, but no information is currently available about potential effects of BQCV on adult bees, either drones or workers. In workers, detectable BQCV infections do not cause visible symptoms . At the colony level, infection could not be linked to Colony Collapse Disorder in the United States , although it was associated with reduced populations in Israel . Our data suggest that oral inoculation of BQCV, at the titres employed here, does not affect mortality and body mass of drones or workers. However, it is possible that such effects could occur at higher inoculum titres, or when acquired through a different transmission route. Brødsgaard et al. (2000) demonstrated that pathogenicity of ABPV was influenced by route of transmission . Unfortunately, few studies report quantities of BQCV or threshold levels for symptoms. Those that are available employed different sample types (e.g. pooled bees from a colony in Gauthier et al. 2007 ) or experimental set-up (e.g. natural infection as in Locke et al. 2012 ) that makes direct comparisons difficult and constitutes a potential explanation for the considerable differences in reported levels. While Gauthier et al. (2007) reported a mean of BQCV and ABPV of 1.52×108 equivalent copies per adult bee, Locke et al. (2012) displayed values in the range of 104 to 108 copies per bee. In the present study, median BQCV copies of inoculated bees were in the range of 107 to 1010 and therefore in line with reported field levels under natural conditions , . Similar to N. ceranae, pathogen levels of laboratory studies using artificial infections tend to be higher than field levels of pooled samples, due to the absence of potential dilution effects (e.g.  vs. ).
Workers from treatments inoculated with BQCV showed higher numbers of viral copies per bee than drones. Similar to N. ceranae, this result reveals sex-specific differences in infection level susceptibility of honey bees to BQCV. The higher infection levels of both pathogen and parasite in the workers contradict the initial hypothesis of drones being parasitized more intensively than workers. Potential reasons for the higher pathogen levels in the workers may be similar to those already mentioned for N. ceranae above. In contrast to Bailey et al. (1983) , our data suggest successful BQCV infection following oral inoculation regardless of N. apis or N. ceranae infection.
Our results do not suggest a close relationship between N. ceranae and BQCV. Unlike N. apis and BQCV , presence of N. ceranae did not promote infection of the virus in either drones or workers, despite inoculation by the former occurring 7 days prior that resulted in increased host mortality likely from gut tissue damage . Elevated BQCV quantities in the N. ceranae only treatment group resulted from two outliers. Because natural covert bee virus infections are common , even in the control groups, it is likely that these highly infected individuals were included by chance as no other data support this positive association. Furthermore, no correlation was observed between quantities of N. ceranae and BQCV in either drone or worker groups that were co-inoculated with both pathogens. Lack of a positive numeric response to co-infection could be explained by differences in host immune responses to N. ceranae compared to N. apis that in turn may influence susceptibility to BQCV. Conversely, a lack of negative response could result from N. ceranae and BQCV infections below respective carry capacities (e.g. for N. ceranae ), suggesting that competition for limited resources did not occur. Although co-infection resulted in significantly greater drone mortality compared to individuals inoculated by BQCV alone, no difference was observed between individuals co-infected and those parasitized by just N. ceranae. This suggests that the microsporidian parasite, and not co-infection or BQCV, influenced host survival, and is similar to results reported by Otteni and Ritter (2004) that found N. apis affected worker survival compared to ABPV .
Our data clearly demonstrated that under the experimental conditions honey bee drones are more susceptible to N. ceranae when the indices of host mortality and body condition are used. This highlights the importance of carefully choosing measures of susceptibility during evaluations, as well as the need to further study the influence of parasites and pathogens on drones due to their contribution to queen fertility. Future investigations should not only focus on understanding the influence of stress on drones, and how this may result in overall decreased colony health and fitness, but also on further improving methods for maintaining drones in the laboratory.
The observation that N. ceranae inoculation leads to higher mortality and lower body mass only in drones, despite lower spore amounts relative to those found in workers, clearly demonstrates increased susceptibility of the males. This particular outcome is in line with the haploid susceptibility hypothesis, stating higher susceptibility in haploid males due to hemizygosity at immune loci . Nevertheless, further work is needed to determine the mechanisms responsible for N. ceranae defence by both drones and workers to truly understand why differences may occur. Because of the importance of immunity, particularly to N. ceranae infection –, , comparative studies investigating host immune response are prudent.
We thank Laurent Gauthier for technical support, as well as Aline Troxler and Daniela Steiner for laboratory assistance.
Conceived and designed the experiments: GR GRW PN. Performed the experiments: GR GRW MMM. Analyzed the data: GR GRW. Contributed reagents/materials/analysis tools: JRdM OY. Wrote the paper: GR GRW OY JRdM PN.
- 1. Holmstrup M, Bindesbøl AM, Ostingh GJ, Duschl A, Scheil V, et al. (2010) Interactions between effects of environmental chemicals and natural stressors: A review. Sci Total Environ 408: 3746–3762 doi:10.1016/j.scitotenv.2009.10.067.
- 2. Stedman's Medical Dictionary. Lippincott Williams & Wilkins. Medilexicon website. Available: http://www.medilexicon.com/medicaldictionary.php?t=87108. Accessed 2013 June 14.
- 3. Zuk M, McKean KA (1996) Sex differences in parasite infections: patterns and processes. Int J Parasitol 26: 1009–1024 doi: 10.1016/S0020-7519(96)00086-0.
- 4. Grossman C (1989) Possible underlying mechanisms of sexual dimorphism in the immune response, fact and hypothesis. J Steroid Biochem 34: 241–251 doi: 10.1016/0022-4731(89)90088-5.
- 5. Morton A, García-del-Pino F (2013) Sex-related differences in the susceptibility of Periplaneta americana and Capnodis tenebrionis to the entomopathogenic nematode Steinernema carpocapsae. J Invertebr Pathol 112: 203–207 doi: 10.1016/j.jip.2012.11.012.
- 6. Adamo SA, Jensen M, Younger M (2001) Changes in lifetime immunocompetence in male and female Gryllus texensis (formerly G. integer)*: trade-offs between immunity and reproduction. Anim Behav: 417–425. doi: 10.1006/anbe.2001.1786.
- 7. Kurtz J, Wiesner A, Götz P, Sauer KP (2000) Gender differences and individual variation in the immune system of the scorpionfly Panorpa vulgaris (Insecta: Mecoptera). Dev Comp Immunol 24: 1–12 doi: 10.1016/S0145-305X(99)00057-9.
- 8. Roff DA (1992) Evolution of life histories: theory and analysis. Routledge, Chapman & Hall, New York, USA.
- 9. O'Donnell S, Beshers SN (2004) The role of male disease susceptibility in the evolution of haplodiploid insect societies. Proc R Soc Lond B 271: 979–983 doi: 10.1098/rspb.2004.2685.
- 10. Ruiz-González MX, Brown MJF (2006) Males vs. workers: testing the assumptions of the haploid susceptibility hypothesis in bumblebees. Behav Ecol Sociobiol 60: 501–509 doi: 10.1007/s00265-006-0192-2.
- 11. Klein AM, Vaissière BE, Cane JH, Steffen-Dewenter I, Cunningham SA, et al. (2007) Importance of pollinators in changing landscapes for world crops. Proc R Soc B 274: 303–313 doi: 10.1098/rspb.2006.3721.
- 12. Garibaldi LA, Steffen-Dewenter I, Winfree R, Aizen MA, Bommarco R, et al. (2013) Wild pollinators enhance fruit set of crops regardless of honey bee abundance. Science 339: 1608–1611 doi: 10.1126/science.1230200.
- 13. Neumann P, Carreck NL (2010) Honey bee colony losses. J Apic Res 49: 1–6 doi: 10.3896/IBRA.1.49.1.01.
- 14. Potts SG, Biesmeijer JC, Kremen C, Neumann P, Schweiger O, et al. (2010) Global pollinator declines: trends, impacts and drivers. Trends Ecol Evol 25: 345–353 doi: 10.1016/j.tree.2010.01.007.
- 15. VanEngelsdorp D, Meixner MD (2010) A historical review of managed honey bee populations in Europe and the United States and the factors that may affect them. J Invertebr Pathol 103: 80–95 doi: 10.1016/j.jip.2009.06.011.
- 16. Williams GR, Shafer ABA, Rogers REL, Shutler D, Stewart DT (2008) First detection of Nosema ceranae, a microsporidian parasite of European honey bees (Apis mellifera), in Canada and central USA. J Invertebr Pathol 97: 189–192 doi: 10.1016/j.jip.2007.08.005.
- 17. Pettis JS, vanEngelsdorp D, Johnson J, Dively G (2012) Pesticide exposure in honey bees results in increased levels of the gut pathogen Nosema. Naturwissenschaften 99: 153–158 doi: 10.1007/s00114-011-0881-1.
- 18. Bailey L, Ball B (1991) Honeybee pathology. 2nd edition. Academic Press.
- 19. Tentcheva D, Gauthier L, Zappulla N, Dainat B, Cousserans F, et al. (2004) Prevalence and Seasonal Variations of Six Bee Viruses in Apis mellifera L. and Varroa destructor Mite Populations in France. Appl Environ Microbiol 70: 7185–7191 doi: 10.1128/AEM.70.12.7185-7191.2004.
- 20. Cox-Foster DL, Conlan S, Holmes EC, Palacios G, Evans JD, et al. (2007) A metagenomic survey of microbes in honey bee colony collapse disorder. Science 318: 283–287 doi: 10.1126/science.1146498.
- 21. Burgher-MacLellan KL, Williams GR, Shutler D, Rogers REL, Mackenzie K (2010) Optimization of duplex real-time PCR with melting curve analysis for detection of microsporidian parasites Nosema apis and Nosema ceranae in Apis mellifera. Can Entomol 142: 271–283 doi: 10.4039/n10-010.
- 22. Genersch E, Von der Ohe W, Kaatz H, Schroeder A, Otten C, et al. (2010) The German bee monitoring project: a long term study to understand periodically high winter losses of honey bee colonies. Apidologie 41: 332–352 doi: 10.1051/apido/2010014.
- 23. Runckel C, Flenniken ML, Engel JC, Ruby JG, Ganem D, et al. (2011) Temporal analysis of the honey bee microbiome reveals four novel viruses and seasonal prevalence of known viruses, nosema and crithidia. PLoS ONE 6: e20656 doi: 10.1371/journal.pone.0020656.
- 24. Poulin R (2007) Interactions between species and the parasite niche. Evolutionary Ecology of Parasites. Princeton University Press. Second Edition, pp. 188–190.
- 25. Bailey L, Ball BV, Perry JN (1983) Association of virus with two protozoal pathogens of the honey bee. Ann Appl Biol 103: 13–20 doi: 10.1111/j.1744-7348.1983.tb02735.x.
- 26. Costa C, Tanner G, Lodesani M, Maistrello L, Neumann P (2011) Negative correlation between Nosema ceranae spore loads and deformed wing virus infection levels in adult honey bee workers. J Invertebr Pathol 108: 224–225 doi: 10.1016/j.jip.2011.08.012.
- 27. Martin SJ, Hardy J, Villalobos E, Martín-Hernández R, Nikaido S, et al.. (2013) Do the honeybee pathogens Nosema ceranae and deformed wing virus act synergistically? Environ Microbiol Rep: 1–5. doi: 10.1111/1758-2229.12052.
- 28. Evans JD, Armstrong TN (2005) Inhibition of the American foulbrood bacterium, Paenibacillus larvae larvae, by bacteria isolated from honey bees. J Apic Res 44: , 168–171.
- 29. Evans JD, Armstrong TN (2006) Antagonistic interactions between honey bee bacterial symbionts and implications for disease. BMC Ecol. 6: , e4.
- 30. Forsgren E, Olofsson TC, Vazquéz A, Fries I (2010) Novel lactic acid bacteria inhibiting Paenibacillus larvae in honey bee larvae. Apidologie 41: 99–108 doi: 10.1051/apido/2009065.
- 31. Vásquez A, Forsgren E, Fries I, Flaberg E, Szekely L, et al.. (2012) Symbionts as major modulators of insect health: Lactic acid bacteria and honeybees. PLoS One 7(3): e33188. doi: 10.1371/journal.pone.0033188.
- 32. Gauthier L, Ravallec M, Tournaire M, Cousserans F, Bergoin M, et al. (2011) Viruses associated with ovarian degeneration in Apis mellifera L. queens. PLoS ONE 6: e16217 doi: 10.1371/journal.pone.0016217.
- 33. Alaux C, Brunet JL, Dussaubat C, Mondet F, Tchamitchan S, et al. (2010) Interactions between Nosema microspores and a neonicotinoid weaken honey bees (Apis mellifera). Environ Microbiol 12: 774–782 doi: 10.1111/j.1462-2920.2009.02123.x.
- 34. Aufauvre J, Biron DG, Vidau C, Fontbonne R, Roudel M, et al. (2012) Parasite-insecticide interactions: a case study of Nosema ceranae and fipronil synergy on honeybee. Sci Rep 2: 1–7 doi: 10.1038/srep00326.
- 35. Koeniger G (2005) The neglected gender – males in bees. Apidologie 36: 143–144 doi: 10.1051/apido:2005017.
- 36. Neumann P, Moritz RFA (2000) Testing genetic variance hypotheses for the evolution of polyandry in the honeybee (Apis mellifera L.). Insectes Soc 47: 271–279 doi: 10.1007/PL00001714.
- 37. Hrassnigg N, Crailsheim K (2005) Differences in drone and worker physiology in honeybees (Apis mellifera). Apidologie 36: 255–277 doi: 10.1051/apido:2005015.
- 38. Yue C, Schröder M, Bienefeld K, Genersch E (2006) Detection of viral sequences in semen of honeybees (Apis mellifera): Evidence for vertical transmission of viruses through drones. J Invertebr Pathol 92: 93–96 doi: 10.1099/vir.0.83101-0.
- 39. Locke SJ, Peng YS (1993) The effect of drone age, semen storage and contamination on semen quality in the honey bee (Apis mellifera). Physiol Entomol 18: 144–148 doi: 10.1111/j.1365-3032.1993.tb00461.x.
- 40. Duay P, De Jong D, Engels W (2002) Decreased flight performance and sperm production in drones of the honey bee (Apis mellifera) slightly infested by Varroa destructor mites during pupal development. Genet Mol Res 1: 227–232.
- 41. Koeniger N, Koeniger G, Gries M, Tingek S (2005) Drone competition at drone congregation areas in four Apis species. Apidologie 36: 211–221 doi: 10.1007/apido.s00114-005-0044-3.
- 42. Rhodes JW, Harden S, Spooner-Hart R, Anderson DL, Wheen G (2010) Effects of age, season and genetics on semen and sperm production in Apis mellifera drones. Apidologie 42: 29–38 doi: 10.1051/apido.2010026.
- 43. Camazine S (1989) Differential Reproduction of the Mite, Varroa jacobsoni (Mesostigmata: Varroidae), on Africanized and European Honey Bees (Hymenoptera: Apidae). Ann Entomol Soc Am 79: 801–803.
- 44. Rosenkranz P, Aumeier P, Ziegelmann B (2010) Biology and control of Varroa destructor. J Invertebr Pathol 103: 96–119 doi: 10.1016/j.jip.2009.07.016.
- 45. Chen YP, Higgins JA, Feldlaufer MF (2005) Quantitative real-time reverse transcription-PCR analysis of deformed wing virus infection in the honeybee (Apis mellifera L.). Appl Environ Microbiol 71: 436–441 doi: 10.1128/AEM.71.1.436-441.2005.
- 46. Bailey L (1972) Nosema apis in drone honeybees. J Apic Res 11: 171–174.
- 47. Klee J, Besana AM, Genersch E, Gisder S, Nanetti A, et al. (2007) Widespread dispersal of the microsporidian Nosema ceranae, an emergent pathogen of the western honey bee, Apis mellifera. J Invertebr Pathol 96: 1–10 doi: 10.1016/j.jip.2007.02.014.
- 48. Fries I (2010) Nosema ceranae in European honey bees (Apis mellifera). J Invertebr Pathol 103: 73–79 doi: 10.1016/j.jip.2009.06.017.
- 49. Dussaubat C, Brunet JL, Higes M, Colbourne JK, Lopez J, et al. (2012) Gut Pathology and Responses to the Microsporidium Nosema ceranae in the Honey Bee Apis mellifera. PLoS ONE 7: e37017 doi: 10.1371/journal.pone.0037017.
- 50. Antúnez K, Martín-Hernández R, Prieto L, Meana A, Zunino P, et al. (2009) Immune suppression in the honey bee (Apis mellifera) following infection by Nosema ceranae (Microsporidia). Environ Microbiol 11: 2284–2290 doi:10.1111/j.1462-2920.2009.01953.x.
- 51. Chaimanee V, Chantawannakul P, Chen YP, Evans JD, Pettis JS (2012) Differential expression of immune genes of adult honey bee (Apis mellifera) after inoculated by Nosema ceranae. J Insect Physiol 58: 1090–1095 doi: 10.1016/j.jinsphys.2012.04.016.
- 52. Chen YP, Siede R (2007) Honey Bee Viruses. Adv Virus Res 70: 33–80 doi: 10.1016/S0065-3527(07)70002-7.
- 53. Huang Q, Kryger P, Le Conte Y, Moritz RFA (2012) Survival and immune response of drones of a Nosemosis tolerant honey bee strain towards N. ceranae infections. J Invertebr Pathol 109: 297–302 doi: 10.1016/j.jip.2012.01.004.
- 54. Oertel E, Emerson RB, Wheeler HE (1953) Transfer of radioactivity from worker to drone honey bees after ingestion of radioactive sucrose. Ann Entomol Soc Am 46: 596–598.
- 55. Dietemann V, Nazzi F, Martin SJ, Anderson DL, Locke B, et al. (2013) Standard methods for varroa research. In: J Apic Res Dietemann V, Ellis JD, Neumann P, The COLOSS BEEBOOK, Volume II: standard methods for Apis mellifera pest and pathogen research. 52: 1–54 doi: 10.3896/IBRA.1.52.1.09.
- 56. Winston ML (1987) The biology of the honey bee. Harvard University Press, USA.
- 57. Crailsheim K, Brodschneider R, Aupinel P, Behrens D, Genersch E, et al. (2013) Standard methods for artificial rearing of Apis mellifera larvae. In: J Apic Res Dietemann V, Ellis JD, Neumann P, The COLOSS BEEBOOK, Volume I: standard methods for Apis mellifera research. 52: 1–15 doi: 10.3896/IBRA.1.52.1.05.
- 58. Williams GR, Alaux C, Costa C, Csáki T, Doublet V, et al. (2013) Standard methods for maintaining adult Apis mellifera in cages under in vitro laboratory conditions. In: J Apic Res Dietemann V, Ellis JD, Neumann P, The COLOSS BEEBOOK, Volume I: standard methods for Apis mellifera research. 52: 1–36 doi: 10.3896/IBRA.1.52.1.04.
- 59. Fuchs S (1990) Preference for drone brood cells by Varroa jacobsoni Oud. in colonies of Apis mellifera carnica. Apidologie 21: 193–196 doi: 10.1051/apido.19900304.
- 60. Boot WJ, Schoenmaker J, Calis JNM, Beetsma J (1995) Invasion of Varroa jacobsoni into drone brood cells of the honey bee, Apis mellifera. Apidologie 26: 109–118 doi: 10.1051/apido.19950204.
- 61. Fries I, Chauzat MP, Chen YP, Doublet V, Genersch E, et al. (2013) Standard methods for Nosema research. In: J Apic Res Dietemann V, Ellis JD, Neumann P, The COLOSS BEEBOOK, Volume II: standard methods for Apis mellifera pest and pathogen research. 52: 1–28 doi: 10.3896/IBRA.220.127.116.11.
- 62. Chen YP, Evans JD, Smith IB, Pettis JS (2008) Nosema ceranae is a long-present and wide-spread microsporidium infection of the European honey bee (Apis mellifera) in the States. J Invertebr Pathol 97: 186–188 doi: 10.1016/j.jip.2007.07.010.
- 63. Bailey L, Woods RD (1977) Two more small RNA viruses from honey bees and further observations on sacbrood and acute bee-paralysis viruses. J Gen Virol 37: 175–182. doi: 10.1099/0022-1317-37-1-175
- 64. de Miranda JR, Bailey L, Ball BV, Blanchard P, Budge G, et al. (2013) Standard methods for virus research in Apis mellifera. In: J Apic Res Dietemann V, Ellis JD, Neumann P, The COLOSS BEEBOOK, Volume II: standard methods for Apis mellifera pest and pathogen research. 52: 1–55 doi: 10.3896/IBRA.18.104.22.168.
- 65. Locke B, Forsgren E, Fries I, de MirandaJR (2012) Acaricide treatment affects viral dynamics in varroa destructor-infested colonies via both host physiology and mite control. Applied and environmental Microbiology 78: 227–235 doi: 10.1128/AEM.06094-11.
- 66. Kellner N, Jacobs FJ (1978) In hoeveel tijd bereiken de sporen van Nosema apis Zander de ventriculus van de honingbij (Apis mellifera L.)? Vlaams Diergeneeskundig Tijdschrift 47: 252–259.
- 67. Verbeke M, Jacobs FJ, De Rycke PH (1984) Passage of various particles through the ventriculus in the honey bee (Apis mellifera L.). Am Bee J 123: 468–470.
- 68. Crailsheim K (1998) Trophallactic interactions in the adult honey bee (Apis mellifera L.). Apidologie 29: 97–112 doi: 10.1051/apido.19980106.
- 69. Human H, Brodschneider R, Dietemann V, Dively G, Ellis JD, et al. (2013) Miscellaneous standard methods for Apis mellifera research. In: J Apic Res Dietemann V, Ellis JD, Neumann P, The COLOSS BEEBOOK, Volume I: standard methods for Apis mellifera research. 52: 1–55 doi: 10.3896/IBRA.22.214.171.124.
- 70. Cantwell GE (1970) Standard methods for counting Nosema spores. American Bee Journal 110: 222–223.
- 71. Rinderer TE, Rothenbuhler WC (1969) Resistance to American Foulbrood in honey bees. Comparative mortality of queen, worker and drone larvae. J Invertebr Pathol 13: 81–86 doi: 10.1016/0022-2011(69)90241-9.
- 72. Adam R, Adriana M, Ewa P (2010) An influence of chosen feed additives on the life-span of laboratory held drones and the possibility of semen collection. J Apic Sci 54: 25–36.
- 73. Wilson EO (1971) The insect societies. Belknap Press of Harvard University Press. 548.
- 74. Traver BE, Fell RD (2011) Nosema ceranae in drone honey bees (Apis mellifera). J Invertebr Pathol 107: 234–236 doi: 10.1016/j.jip.2011.05.016.
- 75. Paxton RJ, Klee J, Korpela S, Fries I (2007) Nosema ceranae has infected Apis mellifera in Europe since at least 1998 and may be more virulent than Nosema apis. Apidologie 38: 558–565 doi: 10.1051/apido.2007037.
- 76. Higes M, Garcia-Palencia P, Martín-Hernández R, Meana A (2007) Experimental infection of Apis mellifera honeybees with Nosema ceranae (Microsporidia). J Invertebr Pathol 94: 211–217 doi: 10.1016/j.jip.2006.11.001.
- 77. Mayack C, Naug D (2009) Energetic stress in the honeybee Apis mellifera from Nosema ceranae infection. J Invertebr Pathol 100: 185–188 doi: 10.1016/j.jip.2008.12.001.
- 78. Mayack C, Naug D (2010) Parasitic infection leads to decline in hemolymph sugar levels in honeybee foragers. J Insect Physiol 56: 1572–1575 doi: 10.1016/j.jinsphys.2010.05.016.
- 79. Forsgren E, Fries I (2010) Comparative virulence of Nosema ceranae and Nosema apis in individual European honey bees. Vet Parasitol 170: 212–217 doi: 10.1016/j.vetpar.2010.02.010.
- 80. Higes M, Martín-Hernández R, Botías C, Bailón EG, González-Porto AV, et al. (2008) How natural infection by Nosema ceranae causes honey bee colony collapse. Environ Microbiol 10: 2659–2669 doi: 10.1111/j.1462-2920.2008.01687.x.
- 81. Chen YP, Zhao Y, Hammond J, Hsu HT, Evans J, et al. (2004) Multiple virus infections in the honey bee and genome divergence of honey bee viruses. J Invertebr Pathol 87: 84–93 doi: 10.1016/j.jip.2004.07.005.
- 82. Ribière M, Ball B, Aubert MFA (2008) Natural history and geographical distribution of honey bee viruses. In: Virology and the Honey Bee.European Commission- BRAVE project: 29–32.
- 83. Siede R, Büchler R (2003) Symptomatic black queen cell virus infection of drone brood on hessian bee yards. Berliner und Münchener tierärztliche Wochenschrift 116: 130–133.
- 84. Anderson DL (1993) Pathogens and queen bees. Australasian Beekeeper 94: 292–296.
- 85. Soroker V, Hetzroni A, Yakobson B, David D, David A, et al. (2010) Evaluation of colony losses in Israel in relation to the incidence of pathogens and pests. Apidologie 42: 192–199 doi: 10.1051/apido.2010047.
- 86. Brødsgaard CJ, Ritter W, Hansen H, Brødsgaard HF (2000) Interactions among Varroa jacobsoni mites, acute paralysis virus, and Paenibacillus larvae larvae and their influence on mortality of larval honeybees in vitro. Apidologie 31: 543–554.
- 87. Gauthier L, Tentcheva D, Tournaire M, Dainat B, Cousserans F, et al. (2007) Viral load estimation in asymptomatic honey bee colonies using the quantitative RT-PCR technique. Apidologie 38: 426–435 doi: 10.1051/apido.2007026.
- 88. Traver BA, Williams MR, Fell RD (2012) Comparison of within hive sampling and seasonal activity of Nosema ceranae in honey bee colonies. Journal of Invertebrate Pathology 109: 187–193 doi: 10.1016/j.jip.2011.11.001.
- 89. Chen YP, Evans J, Feldlaufer M (2006) Horizontal and vertical transmission of viruses in the honey bee, Apis mellifera. J Invertebr Pathol 92: 152–159 doi: 10.1016/j.jip.2006.03.010.
- 90. Otteni M, Ritter W (2004) Effects of the acute paralysis virus on honey bees (Apis mellifera l.) infested by Nosema apis Z. APIACTA 39: 91–97.
- 91. Azzami K, Ritter W, Tautz J, Beier H (2012) Infection of honey bees with acute bee paralysis virus does not trigger humoral or cellular immune responses. Arch Virol 157: 689–702 doi: 10.1007/s00705-012-1223-0.