A from-benchtop-to-desktop workflow for validating HTS data and for taxonomic identification in diet metabarcoding...

Area of Science:

• Ecology
• Molecular Biology
• Bioinformatics

Background:

• Dietary analysis of invertebrate-eaters is crucial for understanding food webs.
• Traditional methods for diet analysis can be labor-intensive and may lack precision.
• Metabarcoding offers a high-throughput approach to identify prey from environmental DNA.

Purpose of the Study:

• To develop and validate a robust "from-benchtop-to-desktop" metabarcoding workflow.
• To investigate the diet of invertebrate-eating species using faecal DNA.
• To establish a reliable method for accurate prey item identification.

Main Methods:

• Amplification of the cytochrome c oxidase I (COI) gene using combined minibarcoding primer sets.
• Sequencing of amplicons using the Illumina MiSeq platform.
• Development of a filtering approach for data cleaning and a taxonomic assignment procedure.

Main Results:

• A robust and informative metabarcoding dataset was generated.
• Approximately 75% of invertebrate COI variants were identified to the species level.
• A novel semi-quantitative statistic, the minimum number of individuals, was introduced for diet studies.

Conclusions:

• The developed metabarcoding workflow provides a reliable and accurate method for invertebrate diet analysis.
• This approach enhances the precision of prey item identification in ecological studies.
• The workflow can guide future research aiming for robust dietary data and fine-scale prey identification.