Computational Evaluation of DNA Metabarcoding for Universal Diagnostics of Invasive Insect Pests

Abstract

Appropriate design and selection of PCR primers plays a critical role in determining the sensitivity and specificity of a metabarcoding assay. Despite several studies applying metabarcoding to insect pest surveillance, the diagnostic performance of the short "mini-barcodes" required by high-throughput sequencing platforms has not been established across the broader taxonomic diversity of invasive insects. We address this by computationally evaluating the diagnostic sensitivity and predicted amplification bias for 68 published and novel cytochrome c oxidase subunit 1 (COI) primers on a curated database of 110,676 insect species, including 2,625 registered on global invasive species lists. We find that mini-barcodes between 125-257 bp can provide comparable resolution to the full-length barcode for both invasive insect pests and the broader Insecta, conditional upon the subregion of COI targeted and the genetic similarity threshold used to identify species. Taxa that could not be identified by any barcode lengths were phylogenetically clustered within "problem groups", many arising through taxonomic inconsistencies rather than insufficient diagnostic information within the barcode itself. Substantial variation in predicted PCR bias was seen across published primers, with those including 4-5 degenerate nucleotide bases showing almost no mismatch to major insect orders. While not completely universal, a single COI mini-barcode can successfully differentiate the majority of pest and non-pest insects from their congenerics, even at the small amplicon size imposed by 2 x 150 bp sequencing. We provide a ranked summary of high-performing primers and discuss the bioinformatic steps required to curate reliable reference databases for metabarcoding studies.

Disentangling bias for non-destructive insect metabarcoding

“…Alternatively, the smaller contribution of the PCR process to total protocol bias could have been due to the two primer pairs employed in this study containing a number of degenerate bases, having been designed to be generic for insects ( Vamos, Elbrecht & Leese, 2017 ; Marquina, Andersson & Ronquist, 2018 ; Elbrecht et al, 2019 ). Previous studies that have found high levels of PCR bias have mostly used less-degenerate primers or primers which have since been identified to contain critical design flaws ( Elbrecht & Leese, 2017 ; Piper et al, 2021 ). Nevertheless, some species included in our study still showed mismatch to these generic primers ( Table 2 ), and this was a primary driver of reduced efficiency at the PCR stage ( Fig.…”

“…Following denoising, amplicon sequence variants (ASVs) inferred separately from each sequencing run were combined into a single table and any chimeric sequences removed de-novo using the “removeBimeraDenovo” function in DADA2. To further filter any non-specific amplification products and pseudogenes the ASV’s were aligned to a profile hidden Markov model ( Eddy, 1998 ) of the COI barcode region from Piper et al (2021) using the aphid v1.3.3 R package ( Wilkinson, 2019 ), retaining sequences that met a minimum log-odds alignment score of 100 with a minimum match length of 100 bp. Retained ASVs were then checked for frame shifts and stop codons that commonly indicate pseudogenes ( Roe & Sperling, 2007 ).…”

DNA Metabarcoding Enables High-Throughput Detection of Spotted Wing Drosophila (Drosophila suzukii) Within Unsorted Trap Catches

“…This aspect of metabarcoding is particularly promising for revealing historical introductions that have gone undiscovered due to the lack of targeted surveillance for that species (Essl et al, 2011;Maclachlan et al, 2021). While the ability for metabarcoding to be conducted on unsorted trap catches represents a significant advance in itself, this universal nature of metabarcoding primers could substantially expand the range of organisms within the scope of a diagnostic laboratory (Piper et al, 2021). Adoption of high-throughput metabarcoding assays for screening of mixed trap catches therefore offers a viable method for increasing the geographic scale and intensity of invasive insect surveillance that could be readily adapted to the next emerging threat.…”

“…Following denoising, the Amplicon Sequence Variants (ASVs) inferred separately from each sequencing run were combined into a single table and any chimeric sequences removed de novo using the removeBimeraDenovo function in DADA2 v1.20. The remaining ASVs were aligned to a Profile Hidden Markov Model (PHMM) of the COI barcode region (Piper et al, 2021) using the aphid v1.3.3 R package (Wilkinson, 2019) to remove any non-specific amplification products, then checked for frame shifts or stop codons that commonly indicate pseudogenes (Roe and Sperling, 2007).…”

“…Hierarchical taxonomy was assigned to the filtered ASVs with a minimum bootstrap support of 50% using the IDTAXA algorithm in DECIPHER v3.13 (Murali et al, 2018), trained on the curated insect reference database of Piper et al (2021). This was followed by additional species level assignment using a nucleotide BLAST v2.11 (Altschul et al, 1990) search against the same reference database.…”