Novel molecular tools for optimizing surveillance of marine non-indigenous species

Abstract

Countries' economies, social values, ecosystem functioning and biodiversity are heavily impacted by marine non-indigenous species (NIS), mostly unintentionally transported via vessels' ballast water and hull biofouling. Costing billions of dollars annually, national and international conventions and legislations have been adopted to address this major threat but rely strongly on scientifically-validated data that can be applied to management plans. High-throughput molecular techniques using environmental DNA and RNA promise to be faster, more specific and have greater standardization for NIS monitoring than traditional surveillance programs based on morphology. However, remaining technical challenges may hinder reliable results. This thesis investigated novel molecular techniques for the use in marine NIS surveillance to implement an optimized molecular workflow into current NIS surveillance strategies. Three technical studies were undertaken, ranging from a broad metabarcoding screening of biofouling communities, to a close investigation of these communities for potential NIS, and finally to a species-specific targeted approach to better characterize erroneous detections. The differences among a range of biofouling communities were characterized using 16S rRNA, 18S rRNA and COI metabarcoding. Biofouling samples were taken from settlement plates simulating different ship hull conditions to attract NIS. The results were different patterns of change between bacterial and eukaryotic communities on artificial surfaces predicting their impacts on marine ecosystems. The same data were screened for NIS and bioinformatics pipelines were adjusted to explore different reference databases. The results were compared with the traditional morpho-taxonomic approach. The screening revealed considerable variation in potential NIS detections between 18S rRNA and COI metabarcoding, PR2, BOLD and NCBI databases, and when compared to the morpho-taxonomic approach. To address the issue of false positive and negative detections, target-optimized sampling was performed using species-specific droplet digital PCR. The focus on one NIS organism, Sabella spallanzanii, revealed detection errors through inhibition from the type of sampling matrix. Individually-designed sampling strategies are strongly advised. Overall, for molecular NIS surveillance, it is recommended to start with broad screening of multiple-marker metabarcoding data, filtered for potential NIS. Dependent on the risk assessment, further monitoring data and species-specific diagnostic tests may be needed to verify true detections. This thesis provides considerable base knowledge for managers and stakeholders to integrate molecular NIS surveillance and to evaluate the results for response plans.