High-Molecular-Weight DNA Extraction and Sample Storage Strategies for Nanopore-Based Long-Read Sequencing of Municipal Wastewater Treatment Systems
Nanopore-based long-read DNA sequencing of wastewater treatment systems is an emerging tool to improve process performance and optimization through near-real-time microbial community monitoring. The goal of this study was to evaluate different DNA extraction protocols for various wastewater sample matrices and to determine an optimal approach for implementing long-read metagenomic sequencing of wastewater treatment systems using the Nanopore platform. We investigated eight DNA extraction protocols and six sample storage methods for Nanopore long-read sequencing of three wastewater matrices: influent, activated sludge, and anaerobic digester mixed liquor. Performance of these protocols was assessed based on DNA yield and integrity, along with measurements of observed microbial diversity in long-read metagenomes. The results suggested that magnetic-bead-based DNA extraction recovered higher-molecular-weight DNA that was suitable for long-read metagenomics. In terms of sample storage strategies, flocculation performed the best for influent and activated sludge samples, while centrifugation was superior for anaerobic digester samples. Together, this work provides current best practices for preparing wastewater DNA for Nanopore-based long-read metagenomic sequencing, advancing its application for treatment system monitoring and control.
Authors
- Ryan Ziels (ORCID: https://orcid.org/0000-0003-3705-6078)
- Xuan Lin (ORCID: https://orcid.org/0000-0002-4988-1668)
- Aditi N. Nallan (ORCID: https://orcid.org/0000-0001-5261-1530)
- Steven Hallam (ORCID: https://orcid.org/0000-0002-4889-6876)
Institutions
- University of British Columbia (CA)
- Scope Group (United States) (US)
Publication Details
- Journal
- ACS ES&T Water
- Published
- 2026-07-02
- DOI
- https://doi.org/10.1021/acsestwater.6c00423
- Primary Topic
- Nanopore and Nanochannel Transport Studies
- Type
- article
- Field-Weighted Citation Impact
- 0.00