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Early detection of a highly invasive bivalve based on environmental DNA (eDNA)

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Abstract

Management of non-indigenous invasive species (NIS) is challenging owing in part to limitations of early detection and identification. The advent of environmental DNA (eDNA) techniques provides an efficient way to detect NIS when their abundance is extremely low. However, eDNA-based methods often suffer from uncertain detection sensitivity, which requires detailed testing before applying these methods in the field. Here we developed an eDNA tool for early detection of the highly invasive golden mussel, Limnoperna fortunei, based on the mitochondrial cytochrome c oxidase subunit I gene (COI). Further, we tested technical issues, including sampling strategy and detection sensitivity, based on a laboratory experiment. We then applied the method to field samples collected from water bodies in China where this mussel has or is expected to colonize. Results showed that the detection limit varied extensively among our newly developed primer pairs, ranging from 4 × 10−2 to 4 × 10−6 ng of total genomic DNA. Laboratory detection was affected by the availability of eDNA (i.e., both mussel abundance and incubation time). Detection capacity was higher in laboratory samples containing re-suspended matter from the bottom layer versus that collected from the surface. Among 25 field sites, detection was 100% at sites with high mussel abundance and as low as 40% at sites with low abundance when tested using our most sensitive primer pair. Early detection of NIS present at low abundance in nature requires not only sensitive primers, but also an optimized sampling strategy to reduce the occurrence of false negatives. Careful selection and detailed testing of primer pairs ensures effective eDNA-based species detection in surveillance and management programs.

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Acknowledgements

Special thanks to the Subject Editor, Dr. John Darling, and two anonymous reviewers for insightful and constructive comments on early versions of this manuscript. We thank Xiaosong Zhao, Chuan Zhou for assistance collecting samples, and Wei Xiong, Ping Ni, Yuzhan Yang and Yaping Lin for assistance with primer design and DNA extraction. The Water Protection Bureau of Danjiangkou City and Miyun Reservoir Management kindly provided sampling boats and access. Funding was provided by the National Natural Science Foundation of China (31622011) to AZ, the Ontario-China Research Innovation Fund (2015DFG71210) to LZ, the Mitacs Globelink (Canada) to GDH, and NSERC Discovery grants and Canada Research Chairs to GDH and HJM.

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Authors and Affiliations

  1. Great Lakes Institute for Environmental Research, University of Windsor, Windsor, ON, N9B 3P4, Canada

    Zhiqiang Xia, G. Douglas Haffner & Hugh J. MacIsaac

  2. International S&T Collaborative Base for Water Environment Monitoring and Simulation in Three Gorges Reservoir Region, Chongqing, 400715, China

    Zhiqiang Xia, Lei Zhang & G. Douglas Haffner

  3. Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China

    Zhiqiang Xia, Aibin Zhan & Yangchun Gao

  4. University of Chinese Academy of Sciences, Beijing, 100049, China

    Aibin Zhan & Yangchun Gao

  5. College of Resources and Environment, Southwest University, Chongqing, 400715, China

    Lei Zhang & G. Douglas Haffner

  6. Yunnan University, Kunming, 650091, China

    Hugh J. MacIsaac

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  1. Zhiqiang Xia
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  2. Aibin Zhan
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  3. Yangchun Gao
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  4. Lei Zhang
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  6. Hugh J. MacIsaac
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Correspondence to Aibin Zhan.

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Xia, Z., Zhan, A., Gao, Y. et al. Early detection of a highly invasive bivalve based on environmental DNA (eDNA). Biol Invasions 20, 437–447 (2018). https://doi.org/10.1007/s10530-017-1545-7

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