A Rapid and Accurate MinION-Based Workflow for Tracking Species Biodiversity in the Field

Abstract

Genetic markers (DNA barcodes) are often used to support and confirm species identification. Barcode sequences can be generated in the field using portable systems based on the Oxford Nanopore Technologies (ONT) MinION sequencer. However, to achieve a broader application, current proof-of-principle workflows for on-site barcoding analysis must be standardized to ensure a reliable and robust performance under suboptimal field conditions without increasing costs. Here, we demonstrate the implementation of a new on-site workflow for DNA extraction, PCR-based barcoding, and the generation of consensus sequences. The portable laboratory features inexpensive instruments that can be carried as hand luggage and uses standard molecular biology protocols and reagents that tolerate adverse environmental conditions. Barcodes are sequenced using MinION technology and analyzed with ONTrack, an original de novo assembly pipeline that requires as few as 1000 reads per sample. ONTrack-derived consensus barcodes have a high accuracy, ranging from 99.8 to 100%, despite the presence of homopolymer runs. The ONTrack pipeline has a user-friendly interface and returns consensus sequences in minutes. The remarkable accuracy and low computational demand of the ONTrack pipeline, together with the inexpensive equipment and simple protocols, make the proposed workflow particularly suitable for tracking species under field conditions.

A sample-to-report solution for taxonomic identification of cultured bacteria in the clinical setting based on nanopore sequencing

“…We therefore chose a reference-based approach allowing us to separate reads originating from mixed cultures while using standard ONT protocols. Furthermore, and in contrast to most previous studies, we omitted consensus error correction which is commonly applied to remove homopolymer errors from consensus sequences and assemblies produced from nanopore reads [22,23] because we did not detect a negative influence of the latter errors in our taxonomic classification approach.…”

“…De novo assembly or consensus generation from the individual reads are therefore commonly used to generate sequences that are virtually free from substitution errors [20]. Additionally, polishing tools can be applied to remove remaining non-random errors such as indels in homopolymer regions [20][21][22][23]. Resulting sequences can then be directly substituted to Sanger sequences in existing classification pipelines or, due to the added flexibility in read length, may provide far higher resolution if the analyses are based on full-length marker genes or entire operons [24].…”

“…One obstacle for a broad adoption of nanopore sequencing in routine diagnostic laboratories is the added bioinformatic complexity as compared to established Sanger sequencing workflows. Furthermore, available workflows are often limited to the analysis of pure amplicons [20][21][22][23], include complex modifications of the ONT laboratory workflows [25,26], or lack published validation by using samples other than mock communities [27,28].…”

“…Most computational workflows ether include reference-based consensus generation or de novo assembly, in combination with additional error correction steps. They were reported to perform similarly in terms of the accuracy of the produced sequences[22,23,25,27,42]. De novo approaches are preferable when reference sequences are missing, however, so far the only studies demonstrating ʺreference-freeʺ consensus generation from complex samples (e.g.…”

MinION-based DNA barcoding of preserved and non-invasively collected wildlife samples

“…High purity genomic DNA of sufficient concentration is ideal for optimal sequencing results and to minimize sequencing errors on the MinION (manufacturer's recommendations). Thus, MinION DNA barcoding studies have primarily used laboratory-based Qiagen kits for reliable and pure DNA extraction products (e.g., Pomerantz et al, 2018;Krehenwinkel, Pomerantz, Henderson, et al, 2019;Maestri et al, 2019). To expand the potential for portable sequencing applications, field-friendly DNA extraction methods can be used to reduce lab equipment requirements.…”