Résumé
The main objective of this work was to develop and validate a robust and
reliable ‘from benchtop-to-desktop’ metabarcoding workflow to investigate
the diet of invertebrate-eaters. We applied our workflow to fecal DNA
samples of an invertebrate-eating fish species. A fragment of the COI gene
was amplified by combining two minibarcoding primer sets to maximize the
taxonomic coverage. Amplicons were sequenced by an Illumina MiSeq
platform. We developed a filtering approach based on a series of
non-arbitrary thresholds established from control samples and from
molecular replicates in order to address the elimination of
cross-contamination, PCR/sequencing errors and mistagging artifacts. This
resulted in a conservative and informative metabarcoding dataset. We
developed a taxonomic assignment procedure that combines different
approaches and that allowed the identification of ~75% of invertebrate COI
variants to the species level. Moreover, based on the diversity of the
variants, we introduced a semi-quantitative statistic in our diet study,
the Minimum Number of Individuals (MNI), which is based on the number of
distinct variants in each sample. The metabarcoding approach described in
this paper may guide future diet studies that aim to produce robust
datasets associated with a fine and accurate identification of prey items.