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In spite of the implementation of control strategies in honey bee (Apis mellifera) keeping, the invasive parasitic mite Varroa destructor remains one of the main causes of colony losses in numerous countries. Therefore, this parasite represents a serious threat to beekeeping and agro-ecosystems that benefit from the pollination services provided by honey bees. To maintain their stocks, beekeepers have to treat their colonies with acaricides every year. Selecting lineages that are resistant to infestations is deemed to be a more sustainable approach. Over the last three decades, numerous selection programs have been initiated to improve the host-parasite relationship and to support honey bee survival in the presence of the parasite without the need for acaricide treatments. Although resistance traits have been included in the selection strategy of honey bees, it has not been possible to globally solve the V. destructor problem. In this study, we review the literature on the reasons that have potentially limited the success of such selection programs. We compile the available information to assess the relevance of selected traits and the potential environmental effects that distort trait expression and colony survival. Limitations to the implementation of these traits in the field are also discussed. Improving our knowledge of the mechanisms underlying resistance to V. destructor to increase trait relevance, optimizing selection programs to reduce environmental effects, and communicating selection outcomes are all crucial to efforts aiming at establishing a balanced relationship between the invasive parasite and its new host.

The European honey bee (Apis mellifera) plays a major role in pollination and food production. Honey bee health is a complex product of the environment, host genetics and associated microbes (commensal, opportunistic and pathogenic). Improved understanding of these factors will help manage modern challenges to bee health. Here we used DNA sequencing to characterise the genomes and metagenomes of 19 honey bee colonies from across Britain. Low heterozygosity was observed in many Scottish colonies which had high similarity to the native dark bee. Colonies exhibited high diversity in composition and relative abundance of individual microbiome taxa. Most non-bee sequences were derived from known honey bee commensal bacteria or pathogens. However, DNA was also detected from additional fungal, protozoan and metazoan species. To classify cobionts lacking genomic information, we developed a novel network analysis approach for clustering orphan DNA contigs. Our analyses shed light on microbial communities associated with honey bees and demonstrate the power of high-throughput, directed metagenomics for identifying novel biological threats in agroecosystems., Numerous microbial symbionts, both commensal and pathogenic, are associated with honey bees. Here, the authors genomically characterize this ‘metagenome’ of the British honey bee, identifying a diversity of commensal microbes as well as known and putative pathogens

As pollinators, bees are cornerstones for terrestrial ecosystem stability and key components in agricultural productivity. All animals, including bees, are associated with a diverse community of microbes, commonly referred to as the microbiome. The bee microbiome is likely to be a crucial factor affecting host health. However, with the exception of a few pathogens, the impacts of most members of the bee microbiome on host health are poorly understood. Further, the evolutionary and ecological forces that shape and change the microbiome are unclear. Here, we discuss recent progress in our understanding of the bee microbiome, and we present challenges associated with its investigation. We conclude that global coordination of research efforts is needed to fully understand the complex and highly dynamic nature of the interplay between the bee microbiome, its host, and the environment. High-throughput sequencing technologies are ideal for exploring complex biological systems, including host-microbe interactions. To maximize their value and to improve assessment of the factors affecting bee health, sequence data should be archived, curated, and analyzed in ways that promote the synthesis of different studies. To this end, the BeeBiome consortium aims to develop an online database which would provide reference sequences, archive metadata, and host analytical resources. The goal would be to support applied and fundamental research on bees and their associated microbes and to provide a collaborative framework for sharing primary data from different research programs, thus furthering our understanding of the bee microbiome and its impact on pollinator health.