Integration of DNA extraction, metabarcoding and an informatics pipeline to underpin a national citizen science honey monitoring scheme

Anna E Oliver; Lindsay K Newbold; Hyun S Gweon; Daniel S Read; Ben A Woodcock; Richard F Pywell

doi:10.1016/j.mex.2021.101303

Integration of DNA extraction, metabarcoding and an informatics pipeline to underpin a national citizen science honey monitoring scheme

MethodsX. 2021 Mar 11:8:101303. doi: 10.1016/j.mex.2021.101303. eCollection 2021.

Authors

Anna E Oliver¹, Lindsay K Newbold¹, Hyun S Gweon², Daniel S Read¹, Ben A Woodcock¹, Richard F Pywell¹

Affiliations

¹ UK Centre for Ecology and Hydrology, Wallingford, Oxfordshire OX10 8BB, UK.
² School of Biological Sciences, University of Reading, Reading RG6 6UR, UK.

Abstract

Worldwide honeybees (Apis mellifera L.) are one of the most widely kept domesticated animals, supporting domestic and commercial livelihoods through the production of honey and wax, as well as in the delivery of pollination services to crops. Quantifying which plant species are foraged upon by honeybees provides insights into their nutritional status as well as patterns of landscape scale habitat utilization. Here we outline a rapid and reproducible methodology for identifying environmental DNA (eDNA) originating principally from pollen grains suspended within honey. The process is based on a DNA extraction incorporating vacuum filtration prior to universal eukaryotic internal transcribed spacer 2 region (ITS2) amplicon generation, sequencing and identification. To provide a pre-cursor to sequence phylotyping, we outline systems for error-corrected processing amplicon sequence variant abundance tables that removes chimeras. This methodology underpins the new UK National Honey Monitoring Scheme.•We compare the efficacy and speed of centrifugation and filtration systems for removing pollen from honey samples as a precursor to plant DNA barcoding.•We introduce the 'HONEYPI' informatics pipeline, an open access resource implemented in python 2.7, to ensure long-term reproducibility during the process of amplicon sequence variant classification.

Keywords: Amplicon sequence variants (ASV); ITS2; Illumina generated PhiX control library; Internal transcribed spacer 2; MiSeq platform; Naive bayesian classifier; Vacuum filtration.