Unveiling invasive insect threats to plant biodiversity: Leveraging eDNA metabarcoding and saturated salt trap solutions for biosurveillance

RESEARCH ARTICLE Unveiling invasive insect threats to plant biodiversity: Leveraging eDNA metabarcoding and saturated salt trap solutions for biosurveillance Yoamel Milia´ n-Garcı´aID1,2*, Cassandre Pyne1, Kate Lindsay1, Adriana Romero1, Robert H. Hanner1 1 Department of Integrative Biology, University of Guelph, Guelph, Ontario, Canada, 2 Ecological and Regulatory (Ecoreg) Solutions Inc., Guelph, Guelph, Ontario, Canada * ymiliang@uoguelph.ca, yoamelmg@gmail.com Abstract The negative global impacts of invasive alien species (IAS) on biodiversity are second only to habitat loss. eDNA metabarcoding allows for a faster and more comprehensive evaluation of community species composition, with a higher taxonomic resolution and less taxonomic expertise required than traditional morphological-based biosurveillance. These advantages have positioned eDNA metabarcoding as the standard method for molecular-based detec- tion of invasive alien species, where fast and accurate detectability allows prompt responses to mitigate their adverse effects. Here, eDNA metabarcoding is used for biosurveillance of invasive alien species regulated by Canada in high-risk areas with four main objectives: i) validate the effectiveness of eDNA metabarcoding of salt trap solutions as a molecular tech- nique for IAS detection, ii) compare detection from DNA extracts obtained from filter quar- ters versus whole filters, iii) benchmark two different bioinformatic pipelines (MetaWorks and mBRAVE), and iv) compare canopy and ground level trapping. eDNA from up to five

IAS (Agrilus planipennis, Daktulosphaira vitifoliae, Lymantria dispar, Popillia japonica, and Trichoferus campestris) were successfully detected across years from 2017 to 2022 in southern Ontario, Canada, with successful morphological validation for all except Lymantria dispar and Trichoferus campestris. Analysis of filter quarters in contrast to whole filters was demonstrated to be insufficient for effective IAS detection in each sample. All IAS were detected in only one filter quarter, suggesting a patchy eDNA distribution on the filter. The MetaWorks and mBRAVE bioinformatics pipelines proved effective in identifying IAS, with MetaWorks yielding a higher success rate when comparing molecular and morphological identifications. Ground-level and canopy-level sampling showed differential IAS recovery rates based on the molecular detection, which also varied per collection year, with all found IAS detected at the canopy level in 2022 while only one (Lymantria dispar) in 2020. The present study ratifies the efficacy and importance of eDNA-based detection in a regulatory context and the utility of adding eDNA metabarcoding of saturated salt trap solutions, a criti- cal tool for IAS detection. PLOS ONE PLOS ONE | https://doi.org/10.1371/journal.pone.0290036 August 11, 2023 1 / 24 a1111111111 a1111111111 a1111111111 a1111111111 a1111111111 OPEN ACCESS Citation: Milia´n-Garcı´a Y, Pyne C, Lindsay K, Romero A, Hanner RH (2023) Unveiling invasive insect threats to plant biodiversity: Leveraging eDNA metabarcoding and saturated salt trap

solutions for biosurveillance. PLoS ONE 18(8): e0290036. https://doi.org/10.1371/journal. pone.0290036 Editor: Ruslan Kalendar, University of Helsinki: Helsingin Yliopisto, FINLAND Received: May 8, 2023 Accepted: July 31, 2023 Published: August 11, 2023 Copyright: © 2023 Milia´n-Garcı´a et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: The raw data (FASTQ files) generated or analyzed during the current study was made publicly available in the Borealis Research Data Repository (2017 collection: https:// doi.org/10.5683/SP2/UM6RYF, 2018 collection: https://doi.org/10.5683/SP2/HTSZNS, and 2019, 2020, and 2022 collections: https://doi.org/10. 5683/SP3/AGUXKR). All images of the IAS specimens discovered in the 2022 collection have been deposited in the Barcode of Life Data Systems (BOLD): dx.doi.org/10.5883/DS-IAS2022.