Data from: Metabarcoding for the parallel identification of several hundred predators and their preys: application to bat species diet analysis

Assessing diet variability is of main importance to better understand the
biology of bats and design conservation strategies. Although the advent of
metabarcoding has facilitated such analyses, this approach does not come
without challenges. Biases may occur throughout the whole experiment, from
fieldwork to biostatistics, resulting in the detection of false negatives,
false positives or low taxonomic resolution. We detail a rigorous
metabarcoding approach based on a short COI minibarcode and two-step PCR
protocol enabling the ‘all at once’ taxonomic identification of bats and
their arthropod preys for several hundreds of samples. Our study includes
faecal pellets collected in France from 357 bats representing 16 species,
as well as insect mock communities that mimic bat meals of known
composition, negative and positive controls. All samples were analysed
using three replicates. We compare the efficiency of DNA extraction
methods and we evaluate the effectiveness of our protocol using
identification success, taxonomic resolution, sensitivity, and
amplification biases. Our parallel identification strategy of predators
and preys reduces the risk of mis-assigning preys to wrong predators and
decreases the number of molecular steps. Controls and replicates enable to
filter the data and limit the risk of false positives, hence guaranteeing
high confidence results for both prey occurrence and bat species
identification. We validate 551 COI variants from arthropod including 18
orders, 117 family, 282 genus and 290 species. Our method therefore
provides a rapid, resolutive and cost-effective screening tool for
addressing evolutionary ecological issues or developing
‘chirosurveillance’ and conservation strategies.