Review
Status and prospects of marine NIS detection and monitoring through (e)DNA metabarcoding

https://doi.org/10.1016/j.scitotenv.2020.141729Get rights and content

Highlights

  • Metabarcoding can greatly improve early detection and monitoring of NIS.

  • Diverse set of approaches have been applied along the metabarcoding's workflow.

  • Main weaknesses include primers' insufficiencies and incomplete reference libraries.

  • Generalized DNA-based NIS monitoring would benefit from protocol harmonization.

  • Further minimization of false negatives and false positives still required.

Abstract

In coastal ecosystems, non-indigenous species (NIS) are recognized as a major threat to biodiversity, ecosystem functioning and socio-economic activities. Here we present a systematic review on the use of metabarcoding for NIS surveillance in marine and coastal ecosystems, through the analysis of 42 publications. Metabarcoding has been mainly applied to environmental DNA (eDNA) from water samples, but also to DNA extracted from bulk organismal samples. DNA extraction kits have been widely used and the 18S rRNA and the COI genes the most employed markers, but less than half of the studies targeted more than one marker loci. The Illumina MiSeq platform has been used in >50% of the publications. Current weaknesses include potential occurrence of false negatives due to the primer-biased or faulty DNA amplification and the incompleteness of reference libraries. This is particularly concerning in the case of NIS surveillance, where proficiency in species level detection is critical. Until these weaknesses are resolved, ideally NIS metabarcoding should be supported by complementary approaches, such as morphological analysis or more targeted molecular approaches (e.g. qPCR, ddPCR). Even so, metabarcoding has already proved to be a highly sensitive tool to detect small organisms or undifferentiated life stages across a wide taxonomic range. In addition, it also seems to be very effective in ballast water management and to improve the spatial and temporal sampling frequency of NIS surveillance in marine and coastal ecosystems. Although specific protocols may be required for species-specific NIS detection, for general monitoring it would be vital to settle on a standard protocol able to generate comparable results among surveillance campaigns and regions of the globe, seeking the best approach for detecting the broadest range of species, while minimizing the chances of a false positive or negative detection.

Introduction

Together with global climate change, overexploitation, pollution and habitat destruction, the spread of non-indigenous species (NIS) is among the major threats to marine and coastal ecosystems (Molnar et al., 2008; Rilov and Crooks, 2009). Non-indigenous species, which are introduced from outside of their natural (past or present) distributional range, deliberately or unintentionally by humans or other agents, can spread rapidly in the recipient system, become invasive and displace and out-compete native species (Rilov and Crooks, 2009; Simberloff et al., 2013). This can trigger severe ecological changes that threaten ecosystem integrity such as loss of native species and of ecosystem services (Molnar et al., 2008; Rilov and Crooks, 2009; Simberloff et al., 2013). One of the major vectors, responsible for the transfer of marine NIS, is transoceanic shipping via ballast waters and hull fouling, or canals connecting large water bodies (Ruiz et al., 2000; Molnar et al., 2008; Hulme, 2009). At smaller scales, intraregional or leisure boating may also enhance the spread of NIS (Fletcher et al., 2017; Pochon et al., 2017; Huhn et al., 2020). The ports and marinas, where these vessels dock, often act as hubs for the spread of NIS (Borrell et al., 2017; Grey et al., 2018; Holman et al., 2019). Artificial marine infrastructures (e.g. pontoons), which may be less attractive for native taxa, provide empty niches for opportunistic NIS where they can settle, establish prosperous populations and spread to close vicinities (Dafforn et al., 2015; Olenin et al., 2016).

While visual surveys based on morphological identification of taxa have greatly contributed to ascertain the current status of NIS in marine and coastal habitats (e.g. Borrell et al., 2018; von Ammon et al., 2018b), they require expertise, and are laborious and time consuming. The lack of available expertise on many different taxonomic groups can also pose a major constraint to bioinvasion assessments (e.g. protists: Pagenkopp Lohan et al., 2016, Pagenkopp Lohan et al., 2017). Moreover, an accurate identification in aquatic systems may be hindered by low visibility waters, as well as by the presence of various life stages not amenable to morphological identification (e.g. eggs, propagules, planktonic larvae, juveniles), because organisms are not large and distinctive (e.g. microalgae, zooplankton, protists) (Pochon et al., 2013; Zaiko et al., 2015b; Pagenkopp Lohan et al., 2016, Pagenkopp Lohan et al., 2017) or due to low density (e.g. newly arriving NIS) (Darling and Blum, 2007).

The detection of an invasive species soon after its introduction, when the population is still confined to a small area and at a low density, maximises the probability of eradication or effective local management (Simberloff, 2001; Anderson, 2005; Olenin et al., 2011; Pochon et al., 2013). Non-indigenous species are often extremely difficult and expensive to manage, once established (Thresher and Kuris, 2004; Olenin et al., 2011). For instance, the EU has spent around 12.5 billion euros annually to control and mitigate the damage caused by NIS (Kettunen et al., 2009). In the U.S., the annual costs of bioinvasions have been estimated at over 100 billion dollars (Pimentel et al., 2001).

Due to the above-mentioned reasons, the development of novel detection methods capable of overcoming some of these challenges becomes a priority in order to contain and eradicate NIS, before they harm ecosystems and result in considerable economic costs (Darling and Blum, 2007; Darling and Mahon, 2011; Xiong et al., 2016; Darling and Frederick, 2018). One such method - DNA metabarcoding - consists on the combination of DNA barcoding (Hebert et al., 2003) with high-throughput sequencing (HTS) and has the potential to bolster current biodiversity assessment techniques (Hajibabaei, 2012; Cristescu, 2014). In (e)DNA metabarcoding, DNA is extracted from bulk collections of organisms or environmental samples (e.g. water, sediments); one short barcode locus is amplified, and resultant amplicon libraries are sequenced in HTS platforms. Thousands to millions of sequences can be generated in the same reaction, which are processed through a bioinformatics pipeline, where the sequences can be clustered into operational taxonomic units (OTUs) and these OTUs or the sequences directly (exact sequence variants - ESV) are then compared to a reference sequence database to get taxonomic identities, ideally at species level (Hajibabaei, 2012; Taberlet et al., 2012; Cristescu, 2014; Creer et al., 2016).

DNA metabarcoding is rapidly becoming an important approach for direct measurement of biodiversity from environments such as soil, water and air (Baird and Hajibabaei, 2012; Taberlet et al., 2012; Deiner et al., 2017) and promises a number of potential benefits over traditional methods. In addition, this approach is easy to implement, which makes DNA metabarcoding one of the tools of choice for the 21st century's next-generation biodiversity monitoring (Leese et al., 2018; Zinger et al., 2019). The potential for a high sensitivity, greater throughput and accuracy, propensity for standardization and automation, faster responses and cost effectiveness (Ji et al., 2013; Pochon et al., 2015; Leese et al., 2016; Zinger et al., 2019), makes DNA metabarcoding a particularly well-suited approach for the early detection of NIS and to improve NIS monitoring in biosurveillance programmes (Zaiko et al., 2015a, Zaiko et al., 2015b, Zaiko et al., 2016; von Ammon et al., 2018b; Rey et al., 2019, Rey et al., 2020).

Despite the great potential of DNA metabarcoding to improve NIS monitoring in marine and coastal ecosystems (Pochon et al., 2013; Ardura et al., 2015; Zaiko et al., 2015a, Zaiko et al., 2015b, Zaiko et al., 2015c; Borrell et al., 2018; Westfall et al., 2020), the widespread and routine implementation of this method is still highly dependent on reliable and cost-effective standardization (Leese et al., 2016; Rey et al., 2020). In this study, we carried out a comprehensive compilation and evaluation of methodologies employed across the full workflow (e.g. sampling design, DNA extraction, targeted genetic markers, sequencing platform, sequence data processing) of DNA metabarcoding applied to eukaryotic NIS detection. We evaluate the current potential for the application of metabarcoding in bioinvasion ecology and assess major weaknesses, challenges and hindrances that still need to be addressed for wider implementation.

Section snippets

Methodology

A search of the scientific literature was conducted on the Web of Science database (28th March 2020). We searched by topic (which includes words in the title, abstract and keywords) by using all possible combinations of terms that can designate non-indigenous species (i.e. non-indigenous species, invasive species, alien species, exotic species, marine pest) and DNA metabarcoding (i.e. metabarcoding, high throughput sequencing and next generation sequencing) plus the term “marine” or “coastal”,

Results and discussion

Our literature search yielded 121 papers published between 2010 and 2020. The combinations returning the highest number of matches were: “Invasive species*” or “non-indigenous species*” with “*metabarcoding” (n = 31 and 18) or “*high throughput sequencing” (n = 20 and 14) plus “*marine”, and “ballast water*” and “*metabarcoding” (n = 17) or “*high throughput sequencing” (n = 17) (Table S1). After careful inspection we found 34 papers that indeed employed metabarcoding for NIS surveillance in

Final considerations

During our review we found several strengths and opportunities of the metabarcoding approach, highlighting its great potential to become a valuable monitoring tool of biological invasions in marine and coastal ecosystems (Fig. 5). These include:

  • i)

    improved resolution, enabling the identification of morphologically similar species and eventually cryptic species, due to a higher taxonomic accuracy;

  • ii)

    increased ability to detect smaller organisms, undifferentiated life stages and rare species, enabling

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Acknowledgements

This work was supported by national funds through the Portuguese Foundation for Science and Technology (FCT, I.P.) in the scope of the project “NIS-DNA: Early detection and monitoring of non-indigenous species (NIS) in coastal ecosystems based on high-throughput sequencing tools” (PTDC/BIA-BMA/29754/2017). We are also grateful to two reviewers for comments and suggestions that greatly improved the manuscript.

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