Optimizing a metabarcoding primer portfolio for species-level detection of taxa in complex mixtures of diverse fishes

Abstract

DNA metabarcoding is used to enumerate and identify taxa in both environmental samples and tissue mixtures. The composition and resolution of metabarcoding data depend on the primer(s) used. Markers that amplify different genes can mitigate biases in primer affinity, amplification efficiency, and reference database resolution, but few empirical studies have evaluated markers for complementary performance. Here, we assess the individual and joint performance of 22 markers for detecting species in a DNA pool of >100 species of primarily marine and freshwater fishes, but also including representatives of elasmobranchs, cephalopods, and crustaceans. Marker performance includes the integrated effect of primer specificity and reference availability. We find that a portfolio of four markers targeting 12S, 16S, and multiple regions of COI identifies 100% of reference taxa to family and nearly 60% to species. We then use the four markers in this portfolio to evaluate metabarcoding of heterogeneous tissue mixtures, using experimental fishmeal to test: 1) the tissue input threshold to ensure detection; 2) how read depth scales with tissue abundance; and 3) the effect of non-target material in the mixture on recovery of target taxa. We consistently detect taxa that make up >1% of fishmeal mixtures and can detect taxa at the lowest input level of 0.01%, but rare taxa (<1%) were detected inconsistently across markers and replicates. Read counts showed weak correlation with tissue input, suggesting they are not a valid proxy for relative abundance. Despite this limitation, our results demonstrate the value of a primer portfolio approach—tailored to the taxa of interest—for detecting and identifying both rare and abundant species in heterogeneous tissue mixtures.

A next-generation sequencing approach for the detection of mixed species in canned tuna

“…Taking the low proportions of the assigned species that were not actually entered into our artificial mixtures into account, regardless of whether they are due to the algorithms used, sequencing errors, databases or impurities in the laboratory ( Burns et al, 2016 ), we decided to use a threshold of 1 %. Additionally, in a metabarcoding study for seafood identification, taxa that make up > 1 % of fishmeal mixtures could consistently be detected, but rare taxa (<1 %) were detected inconsistently across markers and replicates ( Baetscher et al, 2021 ), supporting our threshold set at 1 %. In the CR results, after applying the threshold, no species were found that were not actually added to the mixtures.…”

“…In the area of seafood identification, an increasing number of studies on metabarcoding approaches have been published in recent years, with focus mainly on qualitative identification of diverse species in processed surimi, fish products, and bivalve products in which thresholds for species detection ranged between 0.5 and 1 % (e.g. Baetscher et al, 2021 , Gense et al, 2021 , Giusti et al, 2019 ). Several NGS-based or metabarcoding methods also exist in the field of meat analysis ( Ballin et al, 2009 ).…”

“…Next-generation sequencing is a method for massive parallel sequencing to overcome this problem and is considered as a promising tool for routine analysis for mixed products to control authenticity ( Haynes et al, 2019 , Szabo et al, 2020 ). This method is rather untargeted and can therefore identify a higher number of species that would be ignored in targeted approaches such as real-time PCR ( Baetscher et al, 2021 ). Thus, NGS allows the identification of unexpected species in food products and several studies, especially metabarcoding methods, exist for the analyses of various foods ( Baetscher et al, 2021 , Piredda et al, 2022 , Varunjikar et al, 2022 ).…”

“…This method is rather untargeted and can therefore identify a higher number of species that would be ignored in targeted approaches such as real-time PCR ( Baetscher et al, 2021 ). Thus, NGS allows the identification of unexpected species in food products and several studies, especially metabarcoding methods, exist for the analyses of various foods ( Baetscher et al, 2021 , Piredda et al, 2022 , Varunjikar et al, 2022 ). Metabarcoding by the use of universal primers is suitable for identifying a range of species, but in some cases cannot distinguish between closely related ones such as tuna.…”

Is the metabarcoding ripe enough to be applied to the authentication of foodstuff of animal origin? A systematic review

“…However, with poor exceptions, the different sets of primers used by the SPs showed good taxonomic coverage with respect to the considered food matrices analyzed, proving the authors’ consciousness about the importance of the primer selection. Using a single universal primer pair is attractive because a single marker can amplify a wide range of taxa, but the greater the breadth of taxa covered, the less likely that species‐level identification is possible because of a lack of sequence resolution when priming sites are conserved across divergent taxonomic groups (Baetscher et al., 2021). In this respect, the choice to rely on multi‐target approaches can overcome this limit and lead to the reduction of sources of error (e.g., limiting false negatives) in the final data.…”