The impact of DNA extraction methodology for multi-kingdom river biofilm community analysis
收藏NIAID Data Ecosystem2026-05-02 收录
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https://www.ncbi.nlm.nih.gov/sra/ERP156610
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There is a growing body of evidence that the study river community environmental DNA (eDNA) can be used as a reliable alternative to traditional biodiversity and ecological quality assessments. However, for such technologies to be fully integrated into current monitoring programmes it is necessary to demonstrate the reliability of such techniques and propose unbiased practices and methodologies which access the whole benthic community. The extraction of DNA from environmental samples, including sediments, water, and biofilms, is a crucial stage in the analysis of environmental microbial communities, yet current workflows often focus on individual kingdoms or communities. In this work we look at how extraction methodology can bias microbial community composition, at a cross kingdom level. Four commercial extraction methodologies were used to extract 23 biofilm samples taken from a nutrient gradient. Quantitative PCR and Metabarcoding of four amplicons (16S, 18S, ITS and rbcL) targeting bacterial, eukaryotic, fungal and diatom communities was used to assess the impact of extraction upon community assessment. This study found that there was a high level of similarity between methods employing the addition of mechanical lysis with higher PCR and sequence success rate and an increased cross-kingdom taxonomic abundance when compared to chemical and enzymatic lysis alone. However, the most significant factor linking samples was sample origin rather than extraction methodology. This would suggest that for long-term monitoring eDNA studies moving forward we recommend the use of mechanical lysis to optimise cross-kingdom recovery. However, the high correlation between sample origin irrespective of extraction method employed would imply that existing data collected using alternative methodologies are still valid to include and inform future monitoring practices.
创建时间:
2024-12-03



