ArticleMicrobial genomics2025
Optimization of DNA extraction methods from pig farm wastewater for pathogen detection using metagenomic sequencing.
Article in Microbial genomics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.
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Abstract
Wastewater can be a useful sample to monitor disease outbreaks in the community, as it was demonstrated during the recent Severe acute respiratory syndrome coronavirus 2 pandemic. Due to housing conditions, diseases can rapidly spread within pig herds, resulting in high mortalities and significant economic losses. Monitoring piggery wastewater using Oxford Nanopore Technology's (ONT) sequencing platform combined with metagenomic analysis can provide early disease detection to deploy preventative measures. Nevertheless, obtaining DNA of the required purity and integrity from piggery wastewater is a major challenge. This study aims to identify and optimize the most effective method for obtaining high-quality and quantity DNA, which can be used in downstream applications for pathogen detection. Six DNA extraction protocols were tested on piggery wastewater samples and evaluated based on yield and overall DNA quality. The three best-performing methods, using commercially available kits (QIAGEN QIAamp® PowerFecal® Pro, QIAGEN DNeasy® PowerLyzer® PowerSoil® and Macherey-Nagel NucleoSpin® Soil), were then used to extract DNA from piggery wastewater samples spiked with a mock community composed of known pig pathogens. The extracted DNA samples were then sequenced on the ONT platform, and the effectiveness of the methods was evaluated using kraken2 taxonomic classifier and an in-house database. Results demonstrated that the optimized QIAGEN PowerFecal® Pro protocol was the most suitable and reliable extraction method. Overall, this study highlights the importance of determining the optimal DNA extraction method in effective disease surveillance using a complex environmental sample and takes an important step in making metagenomic disease surveillance a practical reality.
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