Bee viral ecology is a fascinating emerging area of research: viruses exert a range of effects on their hosts, exacerbate impacts of other environmental stressors, and, importantly, are readily shared across multiple bee species in a community. However, our understanding of bee viral communities is limited, as it is primarily derived from studies of North American and European Apis mellifera populations. Here, we examined viruses in populations of A. mellifera and 11 other bee species from 9 countries, across 4 continents and Oceania. We developed a novel pipeline to rapidly and inexpensively screen for bee viruses. This pipeline includes purification of encapsulated RNA/DNA viruses, sequence-independent amplification, high throughput sequencing, integrated assembly of contigs, and filtering to identify contigs specifically corresponding to viral sequences. We identified sequences for (+)ssRNA, (−)ssRNA, dsRNA, and ssDNA viruses. Overall, we found 127 contigs corresponding to novel viruses (i.e. previously not observed in bees), with 27 represented by >0.1% of the reads in a given sample, and 7 contained an RdRp or replicase sequence which could be used for robust phylogenetic analysis. This study provides a sequence-independent pipeline for viral metagenomics analysis, and greatly expands our understanding of the diversity of viruses found in bee communities.

Honey bee populations have been declining precipitously over the past decade, and multiple causative factors have been identified. Recent research indicates that these frequently co-occurring stressors interact, often in unpredictable ways, therefore it has become important to develop robust methods to assess their effects both in isolation and in combination. Most such efforts focus on honey bee workers, but the state of a colony also depends on the health and productivity of its queen. However, it is much more difficult to quantify the performance of queens relative to workers in the field, and there are no laboratory assays for queen performance. Here, we present a new system to monitor honey bee queen egg laying under laboratory conditions and report the results of experiments showing the effects of pollen nutrition on egg laying. These findings suggest that queen egg laying and worker physiology can be manipulated in this system through pollen nutrition, which is consistent with findings from field colonies. The results generated using this controlled, laboratory-based system suggest that worker physiology controls queen egg laying behavior. Additionally, the quantitative data generated in these experiments highlight the utility of the system for further use as a risk assessment tool.

Understanding how vectors alter the interactions between viruses and their hosts is a fundamental question in virology and disease ecology. In honey bees, transmission of deformed wing virus (DWV) by parasitic Varroa mites has been associated with elevated disease and host mortality, and Varroa transmission has been hypothesized to lead to increased viral titres or select for more virulent variants. Here, we mimicked Varroa transmission by serially passaging a mixed population of two DWV variants, A and B, by injection through in vitro reared honey bee pupae and tracking these viral populations through five passages. The DWV-A and DWV-B variant proportions shifted dynamically through passaging, with DWV-B outcompeting DWV-A after one passage, but levels of both variants becoming equivalent by Passage 5. Sequencing analysis revealed a dominant, recombinant DWV-B strain (DWV-A derived 5′ IRES region with the rest of the genome DWV-B), with low nucleotide diversity that decreased through passaging. DWV-A populations had higher nucleotide diversity compared to DWV-B, but this also decreased through passaging. Selection signatures were found across functional regions of the DWV-A and DWV-B genomes, including amino acid mutations in the putative capsid protein region. Simulated vector transmission differentially impacted two closely related viral variants which could influence viral interactions with the host, demonstrating surprising plasticity in vector-host-viral dynamics.

Studies in evolutionary and developmental biology show that relationships between transcription factors (TFs) and their target genes can be altered to result in novel regulatory relationships that generate phenotypic plasticity. We hypothesized that contextdependent shifts in the nervous system associated with behavior may also be linked to changes in TF-target relationships over physiological time scales. We tested this hypothesis using honey bee (Apis mellifera) division of labor as a model system by performing bioinformatic analyses of previously published brain transcriptomic profiles together with new RNAi and behavioral experiments. The bioinformatic analyses identified five TFs that exhibited strong signatures of regulatory plasticity as a function of division of labor. RNAi targeting of one of these TFs (broad complex) and a related TF that did not exhibit plasticity (fushi tarazu transcription factor 1) was administered in conjunction with automated analyses of foraging behavior in the field, laboratory assays of aggression and brood care behavior, and endocrine treatments. The results showed that changes in the regulatory relationships of these TFs were associated with behavioral state, social context and endocrine state. These findings provide the first empirical evidence that TF-target relationships in the brain are altered in conjunction with behavior and social context. They also suggest that one mechanism for this plasticity involves pleiotropic TFs high up in regulatory hierarchies producing behavior-specific transcriptional responses by activating different downstream TFs to induce discrete context-dependent transcriptional cascades. These findings provide new insights into the dynamic nature of the transcriptional regulatory architecture underlying behavior in the brain.