A new sampling device for metabarcoding surveillance of port communities and detection of non-indigenous species.

Metabarcoding techniques are revolutionizing studies of marine biodiversity. They can be used for monitoring non-indigenous species (NIS) in ports and harbors. However, they are often biased by inconsistent sampling methods and incomplete reference databases. Logistic constraints in ports prompt the development of simple, easy-to-deploy samplers. We tested a new device called polyamide mesh for ports organismal monitoring (POMPOM) with a high surface-to-volume ratio. POMPOMS were deployed inside a fishing and recreational port in the Mediterranean alongside conventional settlement plates. We also compiled a curated database with cytochrome oxidase (COI) sequences of Mediterranean NIS. COI metabarcoding of the communities settled in the POMPOMs captured a similar biodiversity than settlement plates, with shared molecular operational units (MOTUs) representing ca. 99% of reads. 38 NIS were detected in the port accounting for ca. 26% of reads. POMPOMs were easy to deploy and handle and provide an efficient method for NIS surveillance.

From biomarkers to community composition: Negative effects of UV/chlorine-treated reclaimed urban wastewater on freshwater biota.

The use of urban wastewater reclaimed water has recently increased across the globe to restore stream environmental flows and mitigate the effects of water scarcity. Reclaimed water is disinfected using different treatments, but their effects into the receiving rivers are little studied. Physiological bioassays and biomarkers can detect sub-lethal effects on target species, but do not provide information on changes in community structure. In contrast, official monitoring programs use community structure information but often at coarse taxonomic resolution level that may fail to detect species level impacts. Here, we combined commonly used biomonitoring approaches from organism physiology to community species composition to scan a broad range of effects of disinfection of reclaimed water by UV-light only and both UV/chlorine on the biota. We (1) performed bioassays in one laboratory species (water flea Daphnia magna) and measured biomarkers in two wild species (caddisfly Hydropsyche exocellata and the barbel Luciobarbus graellsii), (2) calculated standard indices of biotic quality (IBQ) for diatoms, benthic macroinvertebrates, and fishes, and (3) analysed community species composition of eukaryotes determined by Cytochrome Oxidase C subunit I (cox1) metabarcoding. Only the UV/chlorine treatment caused significant changes in feeding rates of D. magna and reduced antioxidant defenses, increased anaerobic metabolism and altered the levels of lipid peroxidiation in H. exocellata. However, inputs of reclaimed water were significantly associated with a greater proportion of circulating neutrophils and LG-PAS cells in L. graellsii. Despite IBQ did not discriminate between the two water treatments, metabarcoding data detected community composition changes upon exposure to UV/chlorine reclaimed water. Overall, despite the effects of UV/chlorine-treated water were transient, our study suggests that UV-light treated is less harmful for freshwater biota than UV/chlorine-treated reclaimed water, but those effects depend of the organizational level.

DnoisE: distance denoising by entropy. An open-source parallelizable alternative for denoising sequence datasets.

DNA metabarcoding is broadly used in biodiversity studies encompassing a wide range of organisms. Erroneous amplicons, generated during amplification and sequencing procedures, constitute one of the major sources of concern for the interpretation of metabarcoding results. Several denoising programs have been implemented to detect and eliminate these errors. However, almost all denoising software currently available has been designed to process non-coding ribosomal sequences, most notably prokaryotic 16S rDNA. The growing number of metabarcoding studies using coding markers such as COI or RuBisCO demands a re-assessment and calibration of denoising algorithms. Here we present DnoisE, the first denoising program designed to detect erroneous reads and merge them with the correct ones using information from the natural variability (entropy) associated to each codon position in coding barcodes. We have developed an open-source software using a modified version of the UNOISE algorithm. DnoisE implements different merging procedures as options, and can incorporate codon entropy information either retrieved from the data or supplied by the user. In addition, the algorithm of DnoisE is parallelizable, greatly reducing runtimes on computer clusters. Our program also allows different input file formats, so it can be readily incorporated into existing metabarcoding pipelines.

To denoise or to cluster, that is not the question: optimizing pipelines for COI metabarcoding and metaphylogeography.

BACKGROUND: The recent blooming of metabarcoding applications to biodiversity studies comes with some relevant methodological debates. One such issue concerns the treatment of reads by denoising or by clustering methods, which have been wrongly presented as alternatives. It has also been suggested that denoised sequence variants should replace clusters as the basic unit of metabarcoding analyses, missing the fact that sequence clusters are a proxy for species-level entities, the basic unit in biodiversity studies. We argue here that methods developed and tested for ribosomal markers have been uncritically applied to highly variable markers such as cytochrome oxidase I (COI) without conceptual or operational (e.g., parameter setting) adjustment. COI has a naturally high intraspecies variability that should be assessed and reported, as it is a source of highly valuable information. We contend that denoising and clustering are not alternatives. Rather, they are complementary and both should be used together in COI metabarcoding pipelines. RESULTS: Using a COI dataset from benthic marine communities, we compared two denoising procedures (based on the UNOISE3 and the DADA2 algorithms), set suitable parameters for denoising and clustering, and applied these steps in different orders. Our results indicated that the UNOISE3 algorithm preserved a higher intra-cluster variability. We introduce the program DnoisE to implement the UNOISE3 algorithm taking into account the natural variability (measured as entropy) of each codon position in protein-coding genes.  This correction increased the number of sequences retained by 88%. The order of the steps (denoising and clustering) had little influence on the final outcome. CONCLUSIONS: We highlight the need for combining denoising and clustering, with adequate choice of stringency parameters, in COI metabarcoding. We present a program that uses the coding properties of this marker to improve the denoising step. We recommend researchers to report their results in terms of both denoised sequences (a proxy for haplotypes) and clusters formed (a proxy for species), and to avoid collapsing the sequences of the latter into a single representative. This will allow studies at the cluster (ideally equating species-level diversity) and at the intra-cluster level, and will ease additivity and comparability between studies.

Marine biomonitoring with eDNA: Can metabarcoding of water samples cut it as a tool for surveying benthic communities?

In the marine realm, biomonitoring using environmental DNA (eDNA) of benthic communities requires destructive direct sampling or the setting-up of settlement structures. Comparatively much less effort is required to sample the water column, which can be accessed remotely. In this study we assess the feasibility of obtaining information from the eukaryotic benthic communities by sampling the adjacent water layer. We studied two different rocky-substrate benthic communities with a technique based on quadrat sampling. We also took replicate water samples at four distances (0, 0.5, 1.5, and 20 m) from the benthic habitat. Using broad range primers to amplify a ca. 313 bp fragment of the cytochrome oxidase subunit I gene, we obtained a total of 3,543 molecular operational taxonomic units (MOTUs). The structure obtained in the two environments was markedly different, with Metazoa, Archaeplastida and Stramenopiles being the most diverse groups in benthic samples, and Hacrobia, Metazoa and Alveolata in the water. Only 265 MOTUs (7.5%) were shared between benthos and water samples and, of these, 180 (5.1%) were identified as benthic taxa that left their DNA in the water. Most of them were found immediately adjacent to the benthos, and their number decreased as we moved apart from the benthic habitat. It was concluded that water eDNA, even in the close vicinity of the benthos, was a poor proxy for the analysis of benthic structure, and that direct sampling methods are required for monitoring these complex communities via metabarcoding.

From metabarcoding to metaphylogeography: separating the wheat from the chaff.

Metabarcoding is by now a well-established method for biodiversity assessment in terrestrial, freshwater, and marine environments. Metabarcoding data sets are usually used for α- and ß-diversity estimates, that is, interspecies (or inter-MOTU [molecular operational taxonomic unit]) patterns. However, the use of hypervariable metabarcoding markers may provide an enormous amount of intraspecies (intra-MOTU) information-mostly untapped so far. The use of cytochrome oxidase (COI) amplicons is gaining momentum in metabarcoding studies targeting eukaryote richness. COI has been for a long time the marker of choice in population genetics and phylogeographic studies. Therefore, COI metabarcoding data sets may be used to study intraspecies patterns and phylogeographic features for hundreds of species simultaneously, opening a new field that we suggest to name metaphylogeography. The main challenge for the implementation of this approach is the separation of erroneous sequences from true intra-MOTU variation. Here, we develop a cleaning protocol based on changes in entropy of the different codon positions of the COI sequence, together with co-occurrence patterns of sequences. Using a data set of community DNA from several benthic littoral communities in the Mediterranean and Atlantic seas, we first tested by simulation on a subset of sequences a two-step cleaning approach consisting of a denoising step followed by a minimal abundance filtering. The procedure was then applied to the whole data set. We obtained a total of 563 MOTUs that were usable for phylogeographic inference. We used semiquantitative rank data instead of read abundances to perform AMOVAs and haplotype networks. Genetic variability was mainly concentrated within samples, but with an important between seas component as well. There were intergroup differences in the amount of variability between and within communities in each sea. For two species, the results could be compared with traditional Sanger sequence data available for the same zones, giving similar patterns. Our study shows that metabarcoding data can be used to infer intra- and interpopulation genetic variability of many species at a time, providing a new method with great potential for basic biogeography, connectivity and dispersal studies, and for the more applied fields of conservation genetics, invasion genetics, and design of protected areas.