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Dainat, B.

Publications and source records attributed to Dainat, B..

4 recordsLinked to original sources

Temporal, spatial, and parasitic drivers of microbial variation in European honey bees

Although the roles of host-associated microbiomes in animal health are increasingly recognised, the factors influencing their variation remain understudied. The relatively simple microbiome of honey bees is a relevant system to address this gap. In particular, the relationship between variations in microbiome composition and the ectoparasite Varroa destructor, the main threat to honey bee health worldwide, is poorly established. In this study, we used metagenomic and statistical analyses of 1442 European honey bee colonies to investigate the relationships between the honey bee microbiome, temporality, location, V. destructor load, and behavioural response to its infestation by the host. While season, year, and location were identified as the main drivers of microbiome variation, V. destructor load emerged as a significant factor associated with microbiome variation. Notably, we identify several pathogens and opportunists that correlated positively with V. destructor load, while the core symbiont Bombilactobacillus correlated negatively. This is compatible with a shift in the microbiome toward dysbiosis, which may be driven by or promote V. destructor parasitism. By contrast, we found only limited evidence of an association between the microbiome and resistance behaviours of the host against this parasite. While the study cannot establish causal relationships, we present the largest metagenomic analysis of honey bee microbiomes to date, providing robust, generalisable evidence about the factors driving variation in the microbiome composition of this ecologically and economically important pollinator. These findings may serve as additional markers in selective breeding programs targeting V. destructor resistance, which could ultimately improve honey bee health.

microbiology↗

Ecology and pathogenicity for honey bee brood of recently described Paenibacillus melissococcoides and comparison with Paenibacillus dendritiformis, Paenibacillus thiaminolyticus

Honey bee colonies contain thousands of individuals living in close proximity in a thermally homeostatic nest, creating ideal conditions for the thriving of numerous pathogens. Among the bacterial pathogens, Paenibacillus larvae infects larvae via the nutritive jelly that adult workers feed them, causing the highly contagious American foulbrood disease. Further Paenibacillus species were anecdotally found in association with honey bees, including when affected by another disease, European foulbrood (EFB). However, their pathogenicity remains largely unknown. Our results indicate that Paenibacillus dendritiformis, Paenibacillus thiaminolyticus and newly described Paenibacillus melissococcoides are pathogenic towards honey bee brood and that their virulence correlates with their sporulation ability, which confers them resistance to the bactericidal properties of the nutritive jelly. Our survey occasionally but increasingly detected P. melissococcoides in confirmed and idiopathic cases of EFB but never in healthy colonies, suggesting that this bacterium is an emerging pathogen of honey bee brood. Overall, our results suggest that virulence traits allowing a pathogenic or opportunistically pathogenic habit towards honey bee brood are frequent in Paenibacillus spp., but that their degree of adaptation to this host varies. Our study clarifies the ecology of this ubiquitous genus, especially when infecting honey bees.

microbiology↗

Sequence-based genome-wide association studies reveal the polygenic architecture of Varroa destructor resistance in Western honey bees Apis mellifera

Honey bees, Apis mellifera, have experienced the full impacts of globalisation, including the recent invasion by the parasitic mite Varroa destructor which has become one of the main causes of colony losses worldwide. Despite its lethal effects, some colonies have developed defence strategies conferring colony resistance and, assuming non-null heritability, selective breeding of naturally resistant bees could be a sustainable way to fight infestations. Here we report on the largest genome-wide association study performed on honey bees to understand the genetic basis of multiple phenotypes linked to varroa resistance. This study was performed on whole genome sequencing of more than 1,500 colonies belonging to different ancestries and combined in a meta-analysis. Results show that varroa resistance is polygenic. A total of 60 genetic markers were identified as having a significant impact in at least one of the tested populations pinpointing several regions of the honey bee genome. Our results also support strategies for genomic selection in honey bee breeding.

genetics↗

Characterisation of the UK honey bee (Apis mellifera) metagenome.

The European honey bee (Apis mellifera) plays a major role in pollination and food production, but is under threat from emerging pathogens and agro-environmental insults. As with other organisms, honey bee health is a complex product of environment, host genetics and associated microbes (commensal, opportunistic and pathogenic). Improved understanding of bee genetics and their molecular ecology can help manage modern challenges to bee health and production. Sampling bee and cobiont genomes, we characterised the metagenome of 19 honey bee colonies across Britain. Low heterozygosity was observed in bees from many Scottish colonies, sharing high similarity to the native dark bee, A. mellifera mellifera. Apiaries exhibited high diversity in the composition and relative abundance of individual microbiome taxa. Most non-bee sequences derived from known honey bee commensal bacteria or known pathogens, e.g. Lotmaria passim (Trypanosomatidae), and Nosema spp. (Microsporidia). However, DNA was also detected from numerous additional bacterial, plant (food source), protozoan and metazoan organisms. To classify sequences from cobionts lacking genomic information, we developed a novel network analysis approach clustering orphan contigs, allowing the identification of a pathogenic gregarine. Our analyses demonstrate the power of high-throughput, directed metagenomics in agroecosystems identifying potential threats to honey bees present in their microbiota.

genomics↗