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ARS Home » Northeast Area » Beltsville, Maryland (BARC) » Beltsville Agricultural Research Center » Bee Research Laboratory » Research » Research Project #440224

Research Project: Using Big Data to Improve Diagnosis of Larval Disease in Honey Bees

Location: Bee Research Laboratory

Project Number: 8042-21000-291-039-I
Project Type: Interagency Reimbursable Agreement

Start Date: Jan 1, 2021
End Date: Dec 31, 2024

The major goals of this project are to understand the microbial context associated with various types of larval disease in honey bees, and improve diagnostic and decision making tools for beekeepers. Objective 1) Determine the microbiome associated with larval health and disease. Collaborating with large scale beekeepers, extension agents, and apiary inspectors to quantify the larval disease microbiome will further define known disease states, reveal novel disease states, and provide targeted hypotheses for disease testing, diagnosis and treatment. Objective 2) Determine virulence in vitro of major disease associated microbial strains with regard to microbial interaction, larval nutrition, and environmental context. Verifying the effects of putative disease causing microbes alone or in combination will provide information to differentiate virulence from susceptibility in the colony context, differentiate cause from consequence and suggest approaches and compounds to mitigate disease, and potentially reduce colony loss. Objective 3) Determine the distribution of Melissococcus clonal groups and virulence genes within apiaries across landscapes, and throughout the US. Determining the distribution and variation associated with virulent microbes across spatial scales will produce a framework to quantify and predict disease epidemiology, and reveal the effect of modern beekeeping on the spread of disease. Objective 4) Improve the detection and diagnosis of larval disease, both known and discovered. The ability to quickly and cheaply diagnose various forms of brood disease is a fundamental step forward for honey bee disease epidemiology and the development of management strategies for industry.

Collaborations will be established with industry partners to collect longitudinal samples from commercial and non-commercial apiaries infected with brood disease. Known and unknown disease phenotypes will be tied to microbial community character across seasons and regions. Validation of causative agents in vitro combined with whole genome sequencing analysis will aid in the determination of virulence with respect to microbial and environmental context. Finally, collaborations will generate informatics tools for bee health, through a more complete set of diagnostic markers to monitor disease onset and progression in honey bee colonies. Visibly diseased and "non-diseased" areas of the colony will be photographed, constructing a detailed (numbered) spatial map of individual brood samples (marked with pins) from the frame including a disease description, noting diagnostic characteristics associated with the disease state and non-diseased state. High throughput analysis of bacterial, fungal and viral microbiomes will be carried out from healthy and diseased hives. Nucleic acids (DNA and/or RNA) will be extracted using TriReagent. mRNA will be converted into cDNA using random hexamer primers and reverse transcriptase. Both cDNA and DNA are subject to polymerase chain reaction (PCR) using either fungal- or bacterial-specific amplicon primers that also contain a unique nucleotide sequence for the discernment of multiplexed samples.