Soil environmental DNA metabarcoding in low-biomass regions requires protocol optimization: a case study in Antarctica

Abstract Environmental DNA is a powerful tool for monitoring biodiversity. Although environmental DNA surveys have successfully been implemented in various environments, protocol choice has been shown to affect results and inferences. Thus far, few method comparison studies for soil have been undert...

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Bibliographic Details
Published in:Antarctic Science
Main Authors: Olmedo-Rojas, Pamela, Jeunen, Gert-Jan, Lamare, Miles, Turnbull, Johanna, Terauds, Aleks, Gemmell, Neil, Fraser, Ceridwen I.
Format: Article in Journal/Newspaper
Language:English
Published: Cambridge University Press (CUP) 2023
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Online Access:http://dx.doi.org/10.1017/s0954102022000384
https://www.cambridge.org/core/services/aop-cambridge-core/content/view/S0954102022000384
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Summary:Abstract Environmental DNA is a powerful tool for monitoring biodiversity. Although environmental DNA surveys have successfully been implemented in various environments, protocol choice has been shown to affect results and inferences. Thus far, few method comparison studies for soil have been undertaken. Here, we optimized the workflow for soil metabarcoding through a comparative study encompassing variation in sampling strategy (individual and combined samples), DNA extraction (PowerSoil ® , NucleoSpin ® Soil, PowerSoil ® + phosphate buffer and NucleoSpin ® Soil + phosphate buffer) and library preparation (one-step and two-step quantitative polymerase chain reaction methods). Using a partial 18S rRNA marker, a total of 309 eukaryotic taxa across 21 phyla were identified from Antarctic soil from one site in the Larsemann Hills. Our optimized workflow was effective with no notable reduction in data quality for a considerable increase in time and cost efficiency. The NucleoSpin ® Soil + phosphate buffer was the best-performing extraction method. Compared to similar studies in other regions, we obtained low taxonomic coverage, perhaps because of the paucity of Antarctic terrestrial organisms in genetic reference databases. Our findings provide useful methodological insights for maximizing efficiency in soil metabarcoding studies in Antarctica and other low-biomass environments.