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

The first is to validate eDNA findings by comparing results from filter quarters versus whole filters and exploring whether the former resembles the same detection rate as the latter (experi- mental validation). Second, to compare molecular-based detection to traditional morphologi- cal-based classification (comparative morphological/ecological validation). The third is to compare outputs generated from two informatics pipelines for DNA data processing (bioin- formatic validation). Validation of bioinformatics pipelines can be daunting when considering the plethora of options available for DNA metabarcoding data analyses [18]. Among other things, bioinformatic pipeline selection is linked to the users’ needs and informatics expertise [18]. In a CFIA regulatory context, user-friendly pipelines can support end-user eDNA valida- tion by officially recognizing its utility and acceptable standards for case-specific studies such as IAS detection. In this context, we chose two bioinformatic pipelines (MetaWorks [19] and mBRAVE [https://www.mbrave.net/] [20]) out of the more than thirty-one available [18]. The Multiplex Barcode Research and Visualization Environment (mBRAVE) is a multi-user and friendly platform that supports storing, validating, and analyzing metabarcoding data. This free server-based system is built on the BOLD platform and supports rapid species identifica- tion without demanding a specific user’s informatics infrastructure or expertise. It also offers a secure collaboration and sharing environment [21], which can be essential for end-user eDNA

validity recognition, especially for industry collaborators and regulatory agencies. On the other hand, MetaWorks is a free and open-source software for scalable metabarcoding data analyses of the most popular DNA barcodes [19]. It uses a naive Bayesian classifier and allows sequence composition-based taxonomic assignments [19] with associated confidence mea- sures (bootstrap support values) [19, 22] but also requires a basic bioinformatics background and infrastructure. In the present study, eDNA metabarcoding was used for the molecular biosurveillance of Canadian-regulated terrestrial IAS in high-risk areas with four main objectives: i) validate the effectiveness of eDNA metabarcoding as a molecular technique for IAS detection during a multi-year sampling effort conducted by the CFIA within a regulatory context, ii) compare the capacity of IAS detection when using DNA extracts obtained from filter quarters versus whole filters; iii) benchmark two different bioinformatic pipelines for metabarcoding data analysis (MetaWorks [19] and mBRAVE [https://www.mbrave.net/] [20]) within the context of IAS detection; and iv) compare the capacity of IAS detection when sampling at the canopy and ground levels. To reach these goals, the present study employs an eDNA metabarcoding approach on saturated salt trap solutions (collection fluid) collected from Lindgren funnel traps and focuses on detecting IAS regulated by Canada, adopting a method similar to the one used in previous studies [4, 23]. Materials and methods Target species

The CFIA monitors species considered both invasive and regulated pests. The target species for the current study included all invasive insects regulated by the CFIA (Accessed on May 25, 2022). In addition to invasive species, the list of pests regulated by the CFIA includes 29 fami- lies and 64 genera of insects, five families and seven genera of bacteria, 22 families and 31 gen- era of fungi and 13 families and 23 genera of plants. For simplicity, we here refer to both CFIA-regulated invasive species and regulated pests as “invasive alien species” (IAS). The pres- ent study targeted wood-boring beetles considered as IAS, including long-horned beetles (Cer- ambycidae) (e.g., Anoplophora glabripennis, Anoplophora chinensis, Tetropium fuscum, Tetropium castaneum, and Aromia bungii). Additional species were added to the regulated species list based on noted exceptions in the CFIA list. For example, the CFIA-regulated PLOS ONE Unveiling invasive insect threats to plant biodiversity PLOS ONE | https://doi.org/10.1371/journal.pone.0290036 August 11, 2023 3 / 24