Identifying archived insect bulk samples using DNA metabarcoding: A case study using the long-term Rothamsted Insect Survey

A - Papers appearing in refereed journals

Petsopoulos, D., Cuff, J. P., Bell, J. R., Kitson, J. J. N., Collins, L., Boonham, N., Morales-Hojas, R. and Evans, D. M. 2024. Identifying archived insect bulk samples using DNA metabarcoding: A case study using the long-term Rothamsted Insect Survey. Environmental DNA. 6 (3), p. e542. https://doi.org/10.1002/edn3.542

AuthorsPetsopoulos, D., Cuff, J. P., Bell, J. R., Kitson, J. J. N., Collins, L., Boonham, N., Morales-Hojas, R. and Evans, D. M.
Abstract

Insect populations are declining in many parts of the world, but a lack of long-term monitoring data is impeding our ability to understand and mitigate the causes of insect biodiversity loss. Whilst high-throughput sequencing (HTS) approaches, such as DNA metabarcoding, have the potential to revolutionize insect biomonitoring through rapid scalable identification, it is unclear to what extent HTS can be applied to long-term stored insect samples. Archived insect samples could inform forecasting and provide valuable information regarding past changes to biodiversity. Here, we assess the efficacy of DNA metabarcoding to identify archived samples from the longest passive monitoring scheme in the United Kingdom: the Rothamsted Insect Survey (RIS). With a focus on aphids as the target taxa of a national network of suction-traps, we analyze a 16-year time-series of stored samples (2003–2018) using DNA metabarcoding from one of the RIS suction traps as an exemplar. We achieved this by using a non-destructive DNA extraction protocol, ensuring the integrity of archival samples for further studies. We compared the identities of aphids determined by both metabarcoding (as inferred amplicon sequence variants [ASVs]) and morphological identification and found that metabarcoding detected most genera with varying success (mean > 76%). When comparing the two methods objectively (i.e., including taxa not detected morphologically), however, congruence decreased (51%). We show that minimum sequence copy thresholds can minimize metabarcoding false positives, but at the expense of introducing false negatives, highlighting the need for careful data curation. Detectability of taxa identified morphologically and similarity between the two methods did not significantly vary over time, demonstrating the viability of metabarcoding for screening archival samples. We discuss the advantages and challenges of metabarcoding for insect biomonitoring, particularly from archival samples, including improvements to sample handling, processing, and archiving. We highlight the wider potential of HTS approaches for stored samples from insect monitoring schemes, unlocking the immense potential of global historical time series.

Year of Publication2024
JournalEnvironmental DNA
Journal citation6 (3), p. e542
Digital Object Identifier (DOI)https://doi.org/10.1002/edn3.542
Open accessPublished as ‘gold’ (paid) open access
FunderBiotechnology and Biological Sciences Research Council
Institute for Agri-food Research and Innovation
Funder project or codeThe Rothamsted Insect Survey - National Capability [2017-2023]
Publisher's version
Output statusPublished
Publication dates
Online04 May 2024
Publication process dates
Accepted20 Mar 2024
ISSN2637-4943
PublisherWiley

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