Evaluation of DNA extraction kits for long-read shotgun metagenomics using Oxford Nanopore sequencing for rapid taxonomic and antimicrobial resistance detection

During a bacterial infection or colonization, the detection of antimicrobial resistance (AMR) is critical, but slow due to culture-based approaches for clinical and screening samples. Culture-based phenotypic AMR detection and confirmation require up to 72 hours (h) or even weeks for slow-growing bacteria. Direct shotgun metagenomics by long-read sequencing using Oxford Nanopore Technologies (ONT) may reduce the time for bacterial species and AMR gene identification. However, screening swabs for metagenomics is complex due to the range of Gram-negative and -positive bacteria, diverse AMR genes, and host DNA present in the samples. Therefore, DNA extraction is a critical initial step. We aimed to compare the performance of different DNA extraction protocols for ONT applications to reliably identify species and AMR genes using a shotgun long-read metagenomic approach. We included three different sample types: ZymoBIOMICS Microbial Community Standard, an in-house mock community of ESKAPE pathogens including Enterococcus faecium, Staphylococcus aureus, Klebsiella pneumoniae, Acinetobacter baumannii, Pseudomonas aeruginosa, and Escherichia coli (ESKAPE Mock), and anonymized clinical swab samples. We processed all sample types with four different DNA extraction kits utilizing different lysis (enzymatic vs. mechanical) and purification (spin-column vs. magnetic beads) methods. We used kits from Qiagen (QIAamp DNA Mini and QIAamp PowerFecal Pro DNA) and Promega (Maxwell RSC Cultured Cells and Maxwell RSC Buccal Swab DNA). After extraction, samples were subject to the Rapid Barcoding Kit (RBK004) for library preparation followed by sequencing on the GridION with R9.4.1 flow cells. The fast5 files were base called to fastq files using Guppy in High Accuracy (HAC) mode with the inbuilt MinKNOW software. Raw read quality was assessed using NanoPlot and human reads were removed using Minimap2 alignment against the Hg38 genome. Taxonomy identification was performed on the raw reads using Kraken2 and on assembled contigs using Minimap2. The AMR genes were identified using Minimap2 with alignment against the CARD database on both the raw reads and assembled contigs. We identified all bacterial species present in the Zymo Mock Community (8/8) and ESKAPE Mock (6/6) with Qiagen PowerFecal Pro DNA kit (chemical and mechanical lysis) at read and assembly levels. Enzymatic lysis retrieved fewer aligned bases for the Gram-positive species (Staphylococcus aureus and Enterococcus faecium) from the ESKAPE Mock on the assembly level compared to the mechanical lysis. We detected the AMR genes from Gram-negative and -positive species in the ESKAPE Mock with the QIAamp PowerFecal Pro DNA kit on reads level with a maximum median time of 1.9 h of sequencing. Long-read metagenomics with ONT may reduce the turnaround time in screening for AMR genes. Currently, the QIAamp PowerFecal Pro DNA kit (chemical and mechanical lysis) for DNA extraction along with the Rapid Barcoding Kit for the ONT sequencing captured the best taxonomy and AMR identification for our specific use case.