Evaluation of Oxford Nanopore Technologies MinION Sequencer as a Novel Short Amplicon Metabarcoding Tool Using Arthropod Mock Sample and Irish Bat Diet Characterisation

TL;DR

This study compares the MinION sequencer to Illumina for analyzing bat diets and arthropod biodiversity, showing MinION can be effective with the right tools and databases.

Contribution

Demonstrates the feasibility of using MinION with a simplified pipeline for metabarcoding, particularly for bat diet analysis.

Findings

MinION provided similar taxonomic results to Illumina when using a comprehensive reference database.

NanoPipe effectively processed MinION data to identify host species and diet composition from bat droppings.

Higher sample numbers, not sequencing depth, were needed for complete species detection with MinION.

Abstract

Biodiversity monitoring using metabarcoding is now widely used as a routine environmental management tool. However, despite the rapid advancement of third‐generation high‐throughput sequencing platforms, there are limited studies assessing the most suitable tools and approaches for environmental metabarcoding studies. We tested the utility of Oxford Nanopore Technologies MinION sequencing for short‐read amplicon sequencing of mitochondrial COI mini‐barcodes from a known composition of arthropod species and compared its performance with more commonly used Illumina NovaSeq sequencing. The mock arthropod species assemblage allowed us to optimise a bioinformatic filtering pipeline to identify arthropod species using MinION long reads. Using this pipeline, we identified host species and diet composition by sequencing droppings collected from five individual Irish brown long‐eared bats (
Plecotus auritus
) roosts. We showed that MinION data provided a similar taxonomic assignment to NovaSeq but only if the reference species barcode database was accurate and comprehensive. The
P. auritus
diet inferred was as expected based on previous morphological and Illumina metabarcoding studies. We showed that less sequencing depth, but a higher number of biological samples were necessary for complete species composition detection by MinION. A relatively simple bioinformatic filtering tool such as NanoPipe could adequately retrieve both host species and diet composition. The biggest standing challenge was the reference database format transferability and comprehensiveness. This pipeline can be used to guide future metabarcoding studies using nanopore sequencing to minimise the cost and effort while optimising results.

Oxford Nanopore Technologies MinION (ONT) Nanopore‐NanoPipe pipeline was compared to Illumina‐Obitools command‐line pipeline by using arthropod mock community input DNA for metabarcoding analysis. We demonstrated that a relatively simple ONT sequencing metabarcoding procedure followed by user‐friendly bioinformatics processing by graphical interface NanoPipe can be used to reliably and quickly characterise bat diet from faeces and thus has potential for other biodiversity monitoring programs.

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