Novel eDNA approaches to monitor Western honey bee (Apis mellifera L.) microbial and arthropod communities

Abstract

Abstract Pests and pathogens are a continuous threat to the health of Western honey bee Apis mellifera L. Monitoring honey bee colonies for arthropod pests, disease‐causing bacteria and fungi, and early detection of new invasions is essential to maintain the pollination services provided by honey bees. We investigated the feasibility of using eDNA metabarcoding to detect pests and pathogens in bee hives and across their foraging environment. We sampled 13 sources for eDNA within and outside hives from our test apiary to determine where the most informative eDNA could be obtained, with most sources sampled thrice. This resulted in 61 samples, 20 negative controls, and three positive controls. Furthermore, we compared two eDNA collection techniques—wiping surfaces with moistened forensic swabs and using a spray/wash technique that aggregated surface eDNA into a container, before collecting the eDNA on a filter. We used DNA metabarcoding with universal primer sets to target arthropod, bacterial, and fungal communities. Our results showed that most sources yielded sufficient eDNA and that results of the swab and spray/wash methods were similar when they could be applied to the same surface. We detected DNA from honey bee bacterial symbionts, mycotoxin‐producing fungi and Brachymyrmex sp. rover ants. Common pests and pathogens of concern to honey bees (i.e., [small hive beetle (Aethina tumida), Varroa destructor, and Melissococcus plutonius]) were detected. This matched our visual observations of clinical signs of these pests and pathogens in the hives we tested. DNA from some species was source specific, which has implications for using eDNA as a monitoring tool. Collectively, our data show that eDNA metabarcoding can accurately detect DNA from arthropods and microbes honey bees contact and can be used as a comprehensive molecular predictor tool for colony health surveys.

Keywords

• apiary
• Apis mellifera
• arthropod pests
• environmental DNA
• metabarcoding
• pathogens