Viral transfer from managed pollinators potentially threatens wild pollinators and may be exacerbated by land-use changes. Our causal models and plant-pollinator network data from 48 European urban and agricultural landscapes revealed the ecological mechanisms underpinning viral transmission. Host identity, network architecture and land-use modulated viral dynamics (black queen cell virus, BQCV; deformed wing virus, DWV-A and DWV-B). Viral prevalence in wild pollinators was driven by viral density in the reservoir host: honey bees, and secondarily by trophic niche overlap with these managed pollinators. Modular networks limited BQCV prevalence, which was driven by reduced honey bee niche overlap, suggesting minimal onward transmission among wild pollinators. Landscapes supporting greater wild pollinator abundance diluted DWV-B transmission; in urban landscapes managed honey bees and wild pollinators experienced higher and lower BQCV prevalence, respectively. Disease in managed bee colonies and land-use changes that concentrate pollinator foraging interactions present potential viral risks to wild pollinator health.

BACKGROUND:Honey bees are the principal commercial pollinators. Along with other arthropods, they are increasingly under threat from anthropogenic factors such as the incursion of invasive honey bee subspecies, pathogens and parasites. Better tools are needed to identify bee subspecies. Genomic data for economic and ecologically important organisms is increasing, but in its basic form its practical application to address ecological problems is limited. RESULTS:We introduce HBeeID a means to identify honey bees. The tool utilizes a knowledge-based network and diagnostic SNPs identified by discriminant analysis of principle components and hierarchical agglomerative clustering. Tests of HBeeID showed that it identifies African, Americas-Africanized, Asian, and European honey bees with a high degree of certainty even when samples lack the full 272 SNPs of HBeeID. Its prediction capacity decreases with highly admixed samples. CONCLUSION:HBeeID is a high-resolution genomic, SNP based tool, that can be used to identify honey bees and screen species that are invasive. Its flexible design allows for future improvements via sample data additions from other localities.

Honey bee colonies have great societal and economic importance. The main challenge that beekeepers face is keeping bee colonies healthy under ever-changing environmental conditions. In the past two decades, beekeepers that manage colonies of Western honey bees (Apis mellifera) have become increasingly concerned by the presence of parasites and pathogens affecting the bees, the reduction in pollen and nectar availability, and the colonies’ exposure to pesticides, among others. Hence, beekeepers need to know the health condition of their colonies and how to keep them alive and thriving, which creates a need for a new holistic data collection method to harmonize the flow of information from various sources that can be linked at the colony level for different health determinants, such as bee colony, environmental, socioeconomic, and genetic statuses. For this purpose, we have developed and implemented the B-GOOD (Giving Beekeeping Guidance by computational-assisted Decision Making) project as a case study to categorize the colony’s health condition and find a Health Status Index (HSI). Using a 3-tier setup guided by work plans and standardized protocols, we have collected data from inside the colonies (amount of brood, disease load, honey harvest, etc.) and from their environment (floral resource availability). Most of the project’s data was automatically collected by the BEEP Base Sensor System. This continuous stream of data served as the basis to determine and validate an algorithm to calculate the HSI using machine learning. In this article, we share our insights on this holistic methodology and also highlight the importance of using a standardized data language to increase the compatibility between different current and future studies. We argue that the combined management of big data will be an essential building block in the development of targeted guidance for beekeepers and for the future of sustainable beekeeping.

Monitoring virus infections can be an important selection tool in honey bee breeding. A recent study pointed towards an association between the virus-free status of eggs and an increased virus resistance to deformed wing virus (DWV) at the colony level. In this study, eggs from both naturally surviving and traditionally managed colonies from across Europe were screened for the prevalence of different viruses. Screenings were performed using the phenotyping protocol of the ‘suppressed in ovo virus infection’ trait but with qPCR instead of end-point PCR and a primer set that covers all DWV genotypes. Of the 213 screened samples, 109 were infected with DWV, 54 were infected with black queen cell virus (BQCV), 3 were infected with the sacbrood virus, and 2 were infected with the acute bee paralyses virus. It was demonstrated that incidences of the vertical transmission of DWV were more frequent in naturally surviving than in traditionally managed colonies, although the virus loads in the eggs remained the same. When comparing virus infections with queen age, older queens showed significantly lower infection loads of DWV in both traditionally managed and naturally surviving colonies, as well as reduced DWV infection frequencies in traditionally managed colonies. We determined that the detection frequencies of DWV and BQCV in honey bee eggs were lower in samples obtained in the spring than in those collected in the summer, indicating that vertical transmission may be lower in spring. Together, these patterns in vertical transmission show that honey bee queens have the potential to reduce the degree of vertical transmission over time.

In 1977, a sample of diseased adult honeybees (Apis mellifera) from Egypt was found to contain large amounts of a previously unknown virus, Egypt bee virus, which was subsequently shown to be serologically related to deformed wing virus (DWV). By sequencing the original isolate, we demonstrate that Egypt bee virus is in fact a fourth unique, major variant of DWV (DWV-D): more closely related to DWV-C than to either DWV-A or DWV-B. DWV-A and DWV-B are the most common DWV variants worldwide due to their close relationship and transmission by Varroa destructor. However, we could not find any trace of DWV-D in several hundred RNA sequencing libraries from a worldwide selection of honeybee, varroa and bumblebee samples. This means that DWV-D has either become extinct, been replaced by other DWV variants better adapted to varroa-mediated transmission, or persists only in a narrow geographic or host range, isolated from common bee and beekeeping trade routes.

In this study, we gathered sequence data from the tRNA leu -cox2 intergenic mitochondrial (mtDNA) region concurrently with single nucleotide polymorphism (SNP) data from 91 loci of nuclear DNA (ncDNA).The data was obtained from 156 colonies sampled in six apiaries from four countries.The full dataset was analysed and discussed for genetic patterns with a focus on cytonuclear diversity and admixture levels.

Viruses are omnipresent, yet the knowledge on drivers of viral prevalence in wild host populations is often limited. Biotic factors, such as sympatric managed host species, as well as abiotic factors, such as climatic variables, are likely to impact viral prevalence. Managed and wild bees, which harbor several multi-host viruses with a mostly fecal–oral between-species transmission route, provide an excellent system with which to test for the impact of biotic and abiotic factors on viral prevalence in wild host populations. Here we show on a continental scale that the prevalence of three broad host viruses: the AKI-complex ( Acute bee paralysis virus , Kashmir bee virus and Israeli acute paralysis virus ), Deformed wing virus , and Slow bee paralysis virus in wild bee populations (bumble bees and solitary bees) is positively related to viral prevalence of sympatric honey bees as well as being impacted by climatic variables. The former highlights the need for good beekeeping practices, including Varroa destructor management to reduce honey bee viral infection and hive placement. Furthermore, we found that viral prevalence in wild bees is at its lowest at the extreme ends of both temperature and precipitation ranges. Under predicted climate change, the frequency of extremes in precipitation and temperature will continue to increase and may hence impact viral prevalence in wild bee communities.

The ‘suppressed in-ovo virus infection’ trait (SOV) was the first trait applied in honey bee breeding programs aimed to increase resilience to virus infections, a major threat for colony survival. By screening drone eggs for viruses, the SOV trait scores the antiviral resistance of queens and its implications for vertical transmission. In this study, queens from both naturally surviving and traditionally managed colonies from across Europe were screened using a two-fold improved SOV phenotyping protocol. First, a gel-based RT-PCR was replaced by a RT-qPCR. This not only allowed quantification of the infection load but also increased the test sensitivity. Second, a genotype specific primer set was replaced by a primer set that covered all known deformed wing virus (DWV) genotypes, which resulted in higher virus loads and fewer false negative results. It was demonstrated that incidences of vertical transmission of DWV were more frequent in naturally surviving populations than in traditionally managed colonies, although the virus load in the eggs remained the same. Dynamics in vertical transmission were further emphasized when comparing virus infections with queen age. Interestingly, older queens showed significantly lower infection loads of DWV in both traditionally managed and naturally surviving colonies, as well as reduced DWV infection frequencies in traditionally managed colonies when compared with younger queens. Seasonal variation in vertical transmission was found with lower infection frequencies in spring compared to summer for DWV and black queen cell virus. Together, these patterns in vertical transmission suggest an adaptive antiviral response of queens aimed at reducing vertical transmission over time.

Invasive parasites are major threats to biodiversity. The honey bee ectoparasite, Varroa destructor, has shifted host and spread almost globally several decades ago. This pest is generally considered to be the main global threat to Western honey bees, Apis mellifera, although the damages it causes are not equivalent in all its new host's populations. Due to the high virulence of this parasite and the viruses it vectors, beekeepers generally rely on acaricide treatments to keep their colonies alive. However, some populations of A. mellifera can survive without anthropogenic mite control, through the expression of diverse resistance and tolerance traits. Such surviving colonies are currently found throughout the globe, with the biggest populations being found in Sub-Saharan Africa and Latin America. Recently, genetic differences between mite populations infesting surviving and treated A. mellifera colonies in Europe were found, suggesting that adaptations of honey bees drive mite evolution. Yet, the prevalence of such co-evolutionary adaptations in other invasive populations of V. destructor remain unknown. Using the previous data from Europe and novel genetic data from V. destructor populations in South America and Africa, we here investigated whether mites display signs of adaptations to different host populations of diverse origins and undergoing differing management. Our results show that, contrary to the differences previously documented in Europe, mites infesting treated and untreated honey bee populations in Africa and South America are genetically similar. However, strong levels of genetic differentiation were found when comparing mites across continents, suggesting ongoing allopatric speciation despite a recent spread from genetically homogenous lineages. This study provides novel insights into the co-evolution of V. destructor and A. mellifera, and confirms that these species are ideal to investigate coevolution in newly established host-parasite systems.

Introduction Viruses significantly contribute to losses of western honey bee, Apis mellifera, colonies (Berthoud et al., 2010; Carreck et al., 2010). The incorporation of high throughput sequencing methods to investigate the presence of DNA and RNA viruses in honey bee colonies has led to the detection of a significant number of new viruses, as well as a deeper insight of the presence of variants of known viruses (McMenamin & Flenniken, 2018). This includes recently described viruses such as Moku virus (Mordecai et al., 2016), Apis Nora virus (ANV), Apis bunya virus-1,2 (ABV-1, ABV-2), Apis dicistrovirus (ADV), Apis flavivirus (AFV) (Remnant et al., 2017), Apis mellifera filamentous virus (AmFV) (Gauthier et al., 2015), Apis rhabdovirus-1,2 (ARV-1,-2)/Bee rhabdovirus-1,2 (BRV-1,-2) (Levin et al., 2017; Remnant et al., 2017), new viruses from the families Iflaviridae, Tymoviridae, Nudiviridae, and Parvoviridae (Gebremedhn et al., 2020; Schoonvaere et al., 2018), new Tymo-, Seco-, Partiti-, Noda-, Dicistro-, Circo-, Nege-, Sobemo-, and Toti-like viruses (Galbraith et al., 2018; Schoonvaere et al., 2018), and the many picorna-like viruses identified in Australian honey bees (Roberts et al., 2018).

Viruses are known to contribute to bee population decline. Possible spillover is suspected from the co-occurrence of viruses in wild bees and honey bees. In order to study the risk of virus transmission between wild and managed bee species sharing the same floral resource, we tried to maximize the possible cross-infections using Phacelia tanacetifolia, which is highly attractive to honey bees and a broad range of wild bee species. Virus prevalence was compared over two years in Southern France. A total of 1137 wild bees from 29 wild bee species (based on COI barcoding) and 920 honey bees (Apis mellifera) were checked for the seven most common honey bee RNA viruses. Halictid bees were the most abundant. Co-infections were frequent, and Sacbrood virus (SBV), Black queen cell virus (BQCV), Acute bee paralysis virus (ABPV) and Israeli acute paralysis virus (IAPV) were widespread in the hymenopteran pollinator community. Conversely, Deformed wing virus (DWV) was detected at low levels in wild bees, whereas it was highly prevalent in honey bees (78.3% of the samples). Both wild bee and honey bee virus isolates were sequenced to look for possible host-specificity or geographical structuring. ABPV phylogeny suggested a specific cluster for Eucera bees, while isolates of DWV from bumble bees (Bombus spp.) clustered together with honey bee isolates, suggesting a possible spillover.

RNA viruses play a significant role in the current high losses of pollinators. Although many studies have focused on the epidemiology of western honey bee (Apis mellifera) viruses at the colony level, the dynamics of virus infection within colonies remains poorly explored. In this study, the two main variants of the ubiquitous honey bee virus DWV as well as three major honey bee viruses (SBV, ABPV and BQCV) were analyzed from Varroa-destructor-parasitized pupae. More precisely, RT-qPCR was used to quantify and compare virus genome copies across honey bee pupae at the individual and subfamily levels (i.e., patrilines, sharing the same mother queen but with different drones as fathers). Additionally, virus genome copies were compared in cells parasitized by reproducing and non-reproducing mite foundresses to assess the role of this vector. Only DWV was detected in the samples, and the two variants of this virus significantly differed when comparing the sampling period, colonies and patrilines. Moreover, DWV-A and DWV-B exhibited different infection patterns, reflecting contrasting dynamics. Altogether, these results provide new insight into honey bee diseases and stress the need for more studies about the mechanisms of intra-colonial disease variation in social insects.

Abstract This protocol was developed for the COST-Action “Super-B”, whose purpose was to coordinate research, outreach and policy towards sustainable pollination1-3. The protocol addresses the detection of parasites and pathogens across bee species, as one of several possible drivers of bee decline4,5. It consists of four major components:1. A sample collecting protocol, based around a dominant bee species driving pathogen distribution among other bee species2. A sample processing protocol, based on analyzing nucleic acids from individual bees3. A pathogen detection protocol, based on RT-qPCR with broad-range primers for several common pathogens4. A barcoding protocol, for accurate bee species identification The protocols have largely been adapted from existing knowledge and protocols but also include two key innovations: the use of passive reference nucleic acids and synthetic positive controls, that significantly improve the quality and robustness of the raw data, and thus the reliability of the analyses and conclusions.

With a growing number of parasites and pathogens experiencing large-scale range expansions, monitoring diversity in immune genes of host populations has never been so important because it can inform on the adaptive potential to resist the invaders. Population surveys of immune genes are becoming common in many organisms, yet they are missing in the honey bee ( Apis mellifera L.), a key managed pollinator species that has been severely affected by biological invasions. To fill the gap, here we identified single nucleotide polymorphisms (SNPs) in a wide range of honey bee immune genes and developed a medium-density assay targeting a subset of these genes. Using a discovery panel of 123 whole-genomes, representing seven A. mellifera subspecies and three evolutionary lineages, 180 immune genes were scanned for SNPs in exons, introns (< 4 bp from exons), 3’ and 5´UTR, and < 1 kb upstream of the transcription start site. After application of multiple filtering criteria and validation, the final medium-density assay combines 91 quality-proved functional SNPs marking 89 innate immune genes and these can be readily typed using the high-sample-throughput iPLEX MassARRAY system. This medium-density-SNP assay was applied to 156 samples from four countries and the admixture analysis clustered the samples according to their lineage and subspecies, suggesting that honey bee ancestry can be delineated from functional variation. In addition to allowing analysis of immunogenetic variation, this newly-developed SNP assay can be used for inferring genetic structure and admixture in the honey bee.