Comparison of nine extraction methods for bacterial identification using the ONT MinION sequencer

The Anthrax mailings bioterrorism attack in 2001 revealed the need for universal and rapid microbial forensic analyses on unknown biological evidence. However, the gold standard for bacterial identification includes culturing isolates, which is laborious. Molecular approaches for bacterial identification revolve around 16S ribosomal gene sequencing using Sanger or next generation sequencing (NGS) platforms, but these techniques are laboratory-based and can also be time-consuming. The Oxford Nanopore Technologies (ONT) MinION sequencer can generate long read lengths that span the entire bacterial 16S rRNA gene and accurately identify the species level. This platform can be used in the field, allowing on-site evidence analysis. However, it requires higher quantities of pure DNA compared to other sequencing platforms; thus, the extraction method for bacterial DNA is critical for downstream analysis, which to date are tailored toward a priori knowledge of the species’ taxonomic grouping. During an attack, the investigative team may not know what species they are handling; therefore, identifying an extraction method that can handle all bacterial groups and generate clean DNA for the MinION is useful for microbial forensic analysis. The purpose of this study was to identify a “universal” extraction method that can be coupled with ONT MinION sequencing for use in forensic situations for rapid identification. It also evaluated the cloud-based data analysis software provided by ONT, EPI2ME. No “universal” extraction method was identified as optimal for downstream MinION sequencing. However, the DNeasy PowerSoil Kit and Noda et al. Chelex-100 method gave comparable sequencing results and could be used as rapid extraction techniques. This study showed that the ONT 16S Barcoding Kit 1–24 coupled with the 16S FASTQ workflow might not be the best for use in forensic situations where species-level identification needs to be obtained, as most alignments were approximately 89% accurate. In all seven test organisms and nine extraction methods, accurate species identification was only obtained in 63% of the cases.