Comparative DNA extraction kit study
Background: Pseudomonas aeruginosa and Enterobacter cloacae, both members of the ESKAPE group, are multidrug-resistant pathogens that pose significant challenges in clinical care. The high GC-content (~67%) of the P. aeruginosa genome complicates DNA extraction and long-read sequencing, with downstream effects on genome assembly and analyses. We compared three commercial extraction kits for isolating high-quality DNA suitable for Oxford Nanopore sequencing from clinical isolates of P. aeruginosa and E. cloacae. Methods: Genomic DNA was extracted from P. aeruginosa (n=63; 3 x 21) and E. cloacae (n=96; 3 x 32) clinical isolates using the MagAttract HMW DNA Kit (Qiagen), the DNeasy UltraClean Microbial Kit (Qiagen), and the MagMAX™ Microbiome Ultra Nucleic Acid Isolation Kit (ThermoFisher). DNA quantity/quality was assessed by spectrophotometry (NanoDrop, Thermo Fisher Scientific), fluorometry (Qubit, ThermoFisher), and capillary electrophoresis (TapeStation 2200, Agilent). Libraries were prepared and sequenced using Oxford Nanopore Technologies platforms. Assemblies were generated with Unicycler (v.0.5.1) and Flye (v.2.9.6); quality was assessed with QUAST (v.5.3) and visualized with Bandage. Genome completeness was evaluated by CheckM (v.1.1.6). Antimicrobial resistance determinants were identified with AMRFinderPlus (v.4.1.19). Results: DNeasy yielded up to 4.7× higher DNA and ~50% higher sequencing output than MagAttract, while MagAttract produced higher DNA integrity and more contiguous assemblies. The choice of assembly had a greater impact on the detection of AMR determinants than the extraction method alone. Across workflows, Flye outperformed Unicycler, increasing detection by 2–14 percentage points. The best-performing combination (DNeasy + Flye) achieved 95.2% AMR determinants, compared to 67.8% for MagMAX + Unicycler, with the most significant difference (37.5%) in efflux pump genes.  Conclusions: This systematic comparison highlights trade-offs between DNA yield, integrity, and downstream assembly performance, demonstrating that assembler choice critically impacts the detection of AMR determinants. These findings provide practical guidance for optimizing long-read-based sequencing workflows to support AMR surveillance and genomic epidemiology.