Post-bioinformatic methods to identify and reduce the prevalence of artefacts in metabarcoding data

Metabarcoding provides a powerful tool for investigating biodiversity and
trophic interactions, but the high sensitivity of this methodology makes
it vulnerable to errors, resulting in artefacts in the final data.
Metabarcoding studies thus often utilise minimum sequence copy thresholds
(MSCTs) to remove artefacts that remain in datasets; however, there is no
consensus on best practice for the use of MSCTs. To mitigate erroneous
reporting of results and inconsistencies, this study discusses and
provides guidance for best-practice filtering of metabarcoding data for
the ascertainment of conservative and accurate data. The most common MSCTs
identified in the literature were applied to example datasets of Eurasian
otter (Lutra lutra) and cereal crop spider (Araneae: Linyphiidae and
Lycosidae) diets. Changes in both the method and threshold value
considerably affected the resultant data. Of the MSCTs tested, it was
concluded that the optimal method for the examples given combined a
sample-based threshold with removal of maximum taxon contamination,
providing stringent filtering of artefacts whilst retaining target data.
Choice of threshold value differed between datasets due to variation in
artefact abundance and sequencing depth, thus studies should employ
controls (mock communities, negative controls with no DNA and unused
MID-tag combinations) to select threshold values appropriate for each
individual study.