Data from: Innovative airborne DNA approach for monitoring honey bee foraging and health
Data files
Abstract
Environmental DNA (eDNA) refers to genetic material collected from the environment and not directly from an organism. eDNA is best known as a tool in aquatic ecology but has been found associated with almost every substrate examined including soils, surfaces, and riding around on other animals. The collection of eDNA from air is one of the most recent advances and has been used to monitor a variety of organisms, including plants, animals, and microorganisms. Current evidence suggests a high turnover rate providing a recent signal for the presence of DNA associated with an organism. Here, we test whether material carried in air can be collected from honey bee hives to evaluate recent foraging behavior and colony health. We sampled air using purpose-built “bee safe” air filters operating for 5-6 hours at each colony. We successfully recovered plant, fungal and microbial DNA from the air within hives over a 3-week pilot period. From these data we identified the core honey bee microbiome and plant interaction data representing foraging behaviour. We calculated beta diversity to estimate the effects of apiary sites and sampling date on data recovery. We observed that variance in ITS data was influenced by sampling date. Given that honey bees are generalist pollinators our ability to detect temporal signals in associated plant sequence data suggest this method opens new avenues into the ecological analysis of short-term foraging behavior at the colony level. In comparison variance in microbial 16S sequencing data was more influenced by sampling location. As the assessment of colony health needs to be localized, spatial variance in these data indicate this may be an important tool in detecting infection. This pilot study demonstrates that colony air filtration has strong potential for the rapid screening of honey bee health and for the study of bee behaviour.
Dataset DOI: 10.5061/dryad.kwh70rzhh
Description of the data and file structure
This is an eDNA analysis of filtered air from bee hives. All methods are described in detail in the manuscript.
Files and variables
File: 16SV4
Description: Files associated with all data and correspond with Figure 2
Files are coded with "MP" in the file name after the gene name (16s). This MP code corresponds with samples from Figure 2 as follows
MP08 Fergus F01
MP09 Fergus F02
MP10 Fergus F03
MP11 Fergus F04
MP12 Fergus F05
MP13 Mono Week1 M06
MP14 Mono Week1 M07
MP15 Mono Week1 M08
MP16 Mono Week1 M09
MP17 Mono Week1 M10
MP18 Mono Week1 M11
MP19 Mono Week2 M12
MP20 Mono Week2 M13
MP21 Mono Week2 M14
MP22 Mono Week2 M15
MP23 Mono Week2 M16
MP24 Mono Week2 M17
MPCon Positive Control
MPNeg Negative Control
File: ITS
Description: Files are numbered to correspond with Samples from Figure 2 as follows
Files are coded with "MP" in the file name after the gene name (ITS). This MP code corresponds with samples from Figure 2 as follows
MP08 Fergus F01
MP09 Fergus F02
MP10 Fergus F03
MP11 Fergus F04
MP12 Fergus F05
MP13 Mono Week1 M06
MP14 Mono Week1 M07
MP15 Mono Week1 M08
MP16 Mono Week1 M09
MP17 Mono Week1 M10
MP18 Mono Week1 M11
MP19 Mono Week2 M12
MP20 Mono Week2 M13
MP21 Mono Week2 M14
MP22 Mono Week2 M15
MP23 Mono Week2 M16
MP24 Mono Week2 M17
MPCon Positive Control
MPNeg Negative Control
Code/software
These files can be analysed with any pipeline for NGS metabarcoding data. In our manuscript we use the QIIME2 v. 2019l10 pipeline. No extra coded scripts are used. We describe the subsequent steps and which reference databases we used in our methods.
Access information
Data was derived from the following sources:
- All data were generated new for this manuscript using the methods described in the manuscript.