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Clearing muddied waters: Capture of environmental DNA from turbid waters

Understanding the differences in efficiencies of various methods to concentrate, extract, and amplify environmental DNA (eDNA) is vital for best performance of eDNA detection. Aquatic systems vary in characteristics such as turbidity, eDNA concentration, and inhibitor load, thus affecting eDNA captu...

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Detalles Bibliográficos
Autores principales: Williams, Kelly E., Huyvaert, Kathryn P., Piaggio, Antoinette J.
Formato: Online Artículo Texto
Lenguaje:English
Publicado: Public Library of Science 2017
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC5501390/
https://www.ncbi.nlm.nih.gov/pubmed/28686659
http://dx.doi.org/10.1371/journal.pone.0179282
Descripción
Sumario:Understanding the differences in efficiencies of various methods to concentrate, extract, and amplify environmental DNA (eDNA) is vital for best performance of eDNA detection. Aquatic systems vary in characteristics such as turbidity, eDNA concentration, and inhibitor load, thus affecting eDNA capture efficiency. Application of eDNA techniques to the detection of terrestrial invasive or endangered species may require sampling at intermittent water sources that are used for drinking and cooling; these water bodies may often be stagnant and turbid. We present our best practices technique for the detection of wild pig eDNA in water samples, a protocol that will have wide applicability to the detection of elusive vertebrate species. We determined the best practice for eDNA capture in a turbid water system was to concentrate DNA from a 15 mL water sample via centrifugation, purify DNA with the DNeasy mericon Food kit, and remove inhibitors with Zymo Inhibitor Removal Technology columns. Further, we compared the sensitivity of conventional PCR to quantitative PCR and found that quantitative PCR was more sensitive in detecting lower concentrations of eDNA. We show significant differences in efficiencies among methods in each step of eDNA capture, emphasizing the importance of optimizing best practices for the system of interest.