Comparing species detection success between molecular markers in DNA metabarcoding of coastal macroinvertebrates

Abstract

DNA metabarcoding has great potential to improve marine biomonitoring programs by providing a rapid and accurate assessment of species composition in zoobenthic communities. However, some methodological improvements are still required, especially regarding failed detections, primers efficiency and incompleteness of databases. Here we assessed the efficiency of two different marker loci (COI and 18S) and three primer pairs in marine species detection through DNA metabarcoding of the macrozoobenthic communities colonizing three types of artificial substrates (slate, PVC and granite), sampled between 3 and 15 months of deployment. To accurately compare detection success between markers, we also compared the representativeness of the detected species in public databases and revised the reliability of the taxonomic assignments. Globally, we recorded extensive complementarity in the species detected by each marker, with 69% of the species exclusively detected by either 18S or COI. Individually, each of the three primer pairs recovered, at most, 52% of all species detected on the samples, showing also different abilities to amplify specific taxonomic groups. Most of the detected species have reliable reference sequences in their respective databases (82% for COI and 72% for 18S), meaning that when a species was detected by one marker and not by the other, it was most likely due to faulty amplification, and not by lack of matching sequences in the database. Overall, results showed the impact of marker and primer applied on species detection ability and indicated that, currently, if only a single marker or primer pair is employed in marine zoobenthos metabarcoding, a fair portion of the diversity may be overlooked.

Comparing DNA metabarcoding with morphology in the assessment of macrozoobenthos in Portuguese transitional waters in the scope of the Water Framework Directive monitoring

“…In a recent review where 90 publications where analysed (Duarte et al 2021), partial segments of the COI gene have been by far the most used for targeting benthic invertebrate communities in marine ecosystems, including transitional ecosystems, while 18S has been less used, whereas the concurrent use of both markers is less common (e.g. Cowart et al 2015, Wangensteen et al 2018a,b, Leite et al 2021).…”

“…The primer pair mlCOIintF (5’-GGWACWGGWTGAACWGTWTAYCCYCC -3’) (Leray et al 2013) and LoboR1 (5’-TAAACYTCWGGRTGWCCRAARAAYCA -3’) (Lobo et al 2013) was used to amplify an internal region of 313 bp of the mitochondrial cytochrome c oxidase I (COI) gene and the primer pair TAReuk454FWD1 (5’-CCAGCASCYGCGGTAATTCC -3’) and TAReukREV3 (5’-ACTTTCGTTCTTGATYRA -3’) (Stoeck et al 2010, Lejzerowicz et al 2015) was used to amplify ∼400 bp of the V4 hypervariable region of the 18S rRNA gene (18S). The two primer pairs were selected based on previous studies on marine invertebrates of the region (macrozoobenthos and meiofauna) as the ones that captured the most diverse taxa among four tested primers pairs for COI (Fais et al 2020, Leite et al 2021) and three tested primers for 18S (Fais et al 2020). PCR reactions were performed for each sample using KAPA HiFi HotStart PCR kit according to manufacturer instructions, 0.3 μM of each primer and 50 ng of template DNA, in a total volume of 25 μL.…”

“…The usable reads were then processed in two public databases pipelines (Leite et al 2021): COI reads were submitted to mBrave – Multiplex Barcode Research and Visualization Environment (www.mbrave.net; Ratnasingham 2019), which is linked with BOLD (Ratnasingham and Hebert 2007) and 18S reads were analysed in SILVAngs database (https://ngs.arb-silva.de/silvangs/; Quast et al 2013).…”

“…The usable reads were then processed in two public databases pipelines (Leite et al 2021) In mBrave, COI reads were uploaded using the sample batch function and only the trimming by length was applied (maximum of 313 bp). Low quality reads were then removed if the average quality value (QV) was less than 20 or sequences shorter than 150 bp.…”

“…However, despite the demonstrated utility of metabarcoding to reliably generate assessments of aquatic environmental status, in particular based on benthic invertebrates (Aylagas et al 2014, 2018, Cowart et al 2015, Lobo et al 2017b, Derycke et al 2021, Duarte et al 2021, Van den Bulcke et al 2021), the adoption of metabarcoding in biomonitoring still face several challenges, in particular in coastal and transitional ecosystems. These ecosystems hold very different features from freshwaters, and are highly diverse, thereby requiring a tailored tool in order to overcome existing technological shortcomings that can prevent the detection of all taxa within a sample (e.g., Leite et al 2021, Wangensteen et al 2018a,b). In addition, one of the greatest challenges would be to establish a framework for implementation of metabarcoding into monitoring programs, which is currently lacking.…”