Efficacy of metabarcoding for identification of fish eggs evaluated with mock communities.

There is urgent need for effective and efficient monitoring of marine fish populations. Monitoring eggs and larval fish may be more informative than that traditional fish surveys since ichthyoplankton surveys reveal the reproductive activities of fish populations, which directly impact their population trajectories. Ichthyoplankton surveys have turned to molecular methods (DNA barcoding & metabarcoding) for identification of eggs and larval fish due to challenges of morphological identification. In this study, we examine the effectiveness of using metabarcoding methods on mock communities of known fish egg DNA. We constructed six mock communities with known ratios of species. In addition, we analyzed two samples from a large field collection of fish eggs and compared metabarcoding results with traditional DNA barcoding results. We examine the ability of our metabarcoding methods to detect species and relative proportion of species identified in each mock community. We found that our metabarcoding methods were able to detect species at very low input proportions; however, levels of successful detection depended on the markers used in amplification, suggesting that the use of multiple markers is desirable. Variability in our quantitative results may result from amplification bias as well as interspecific variation in mitochondrial DNA copy number. Our results demonstrate that there remain significant challenges to using metabarcoding for estimating proportional species composition; however, the results provide important insights into understanding how to interpret metabarcoding data. This study will aid in the continuing development of efficient molecular methods of biological monitoring for fisheries management

Merging DNA metabarcoding and ecological network analysis to understand and build resilient terrestrial ecosystems

Summary 1. Significant advances in both mathematical and molecular approaches in ecology offer unprecedented opportunities to describe and understand ecosystem functioning. Ecological networks describe interactions between species, the underlying structure of communities and the function and stability of ecosystems. They provide the ability to assess the robustness of complex ecological communities to species loss, as well as a novel way of guiding restoration. However, empirically quantifying the interactions between entire communities remains a significant challenge. 2. Concomitantly, advances in DNA sequencing technologies are resolving previously intractable questions in functional and taxonomic biodiversity and provide enormous potential to determine hitherto difficult to observe species interactions. Combining DNA metabarcoding approaches with ecological network analysis presents important new opportunities for understanding large-scale ecological and evolutionary processes, as well as providing powerful tools for building ecosystems that are resilient to environmental change. 3. We propose a novel ‘nested tagging’ metabarcoding approach for the rapid construction of large, phylogenetically structured species-interaction networks. Taking tree–insect–parasitoid ecological networks as an illustration, we show how measures of network robustness, constructed using DNA metabarcoding, can be used to determine the consequences of tree species loss within forests, and forest habitat loss within wider landscapes. By determining which species and habitats are important to network integrity, we propose new directions for forest management. 4. Merging metabarcoding with ecological network analysis provides a revolutionary opportunity to construct some of the largest, phylogenetically structured species-interaction networks to date, providing new ways to: (i) monitor biodiversity and ecosystem functioning; (ii) assess the robustness of interacting communities to species loss; and (iii) build ecosystems that are more resilient to environmental change

What goes in, must come out:combining scat-based molecular diet analysis and quantification of ingested microplastics in a marine top predator

Context: Microplastics (plastic particles &lt;5 mm in size) are highly available for ingestion by a wide range of organisms, either through direct consumption or indirectly, via trophic transfer, from prey to predator. The latter is a poorly understood, but potentially major, route of microplastic ingestion for marine top predators.Approach: We developed a novel and effective methodology pipeline to investigate dietary exposure of wild top predators (grey seals; Halichoerus grypus) to microplastics, by combining scat-based molecular techniques with a microplastic isolation method. We employed DNA metabarcoding, a rapid method of biodiversity assessment, to garner detailed information on prey composition from scats, and investigated the potential relationship between diet and microplastic burden.Results: Outcomes of the method development process and results of both diet composition from metabarcoding analysis and detection of microplastics are presented. Importantly, the pipeline performed well and initial results suggest the frequency of microplastics detected in seal scats may be related to the type of prey consumed. Conclusions: Our non-invasive, data rich approach maximises time and resource-efficiency, while minimising costs and sample volumes required for analysis. This pipeline could be used to underpin a much-needed increase in understanding of the relationship between diet composition and rates of microplastic ingestion in high trophic-level species.<br/

ranacapa: An R package and Shiny web app to explore environmental DNA data with exploratory statistics and interactive visualizations.

Environmental DNA (eDNA) metabarcoding is becoming a core tool in ecology and conservation biology, and is being used in a growing number of education, biodiversity monitoring, and public outreach programs in which professional research scientists engage community partners in primary research. Results from eDNA analyses can engage and educate natural resource managers, students, community scientists, and naturalists, but without significant training in bioinformatics, it can be difficult for this diverse audience to interact with eDNA results. Here we present the R package ranacapa, at the core of which is a Shiny web app that helps perform exploratory biodiversity analyses and visualizations of eDNA results. The app requires a taxonomy-by-sample matrix and a simple metadata file with descriptive information about each sample. The app enables users to explore the data with interactive figures and presents results from simple community ecology analyses. We demonstrate the value of ranacapa to two groups of community partners engaging with eDNA metabarcoding results

DNA Authentication of St John’s Wort (Hypericum perforatum L.) Commercial Products Targeting the ITS Region

open access articleThere is considerable potential for the use of DNA barcoding methods to authenticate raw medicinal plant materials, but their application to testing commercial products has been controversial. A simple PCR test targeting species-specific sequences within the nuclear ribosomal internal transcribed spacer (ITS) region was adapted to screen commercial products for the presence of Hypericum perforatum L. material. DNA differing widely in amount and extent of fragmentation was detected in a number of product types. Two assays were designed to further analyse this DNA using a curated database of selected Hypericum ITS sequences: A qPCR assay based on a species-specific primer pair spanning the ITS1 and ITS2 regions, using synthetic DNA reference standards for DNA quantitation and a Next Generation Sequencing (NGS) assay separately targeting the ITS1 and ITS2 regions. The ability of the assays to detect H. perforatum DNA sequences in processed medicines was investigated. Out of twenty different matrices tested, both assays detected H. perforatum DNA in five samples with more than 103 ITS copies µL−1 DNA extract, whilst the qPCR assay was also able to detect lower levels of DNA in two further samples. The NGS assay confirmed that H. perforatum was the major species in all five positive samples, though trace contaminants were also detected

Small subunit ribosomal metabarcoding reveals extraordinary trypanosomatid diversity in Brazilian bats

Background: Bats are a highly successful, globally dispersed order of mammals that occupy a wide array of ecological niches. They are also intensely parasitized and implicated in multiple viral, bacterial and parasitic zoonoses. Trypanosomes are thought to be especially abundant and diverse in bats. In this study, we used 18S ribosomal RNA metabarcoding to probe bat trypanosome diversity in unprecedented detail. Methodology/Principal Findings: Total DNA was extracted from the blood of 90 bat individuals (17 species) captured along Atlantic Forest fragments of Espírito Santo state, southeast Brazil. 18S ribosomal RNA was amplified by standard and/or nested PCR, then deep sequenced to recover and identify Operational Taxonomic Units (OTUs) for phylogenetic analysis. Blood samples from 34 bat individuals (13 species) tested positive for infection by 18S rRNA amplification. Amplicon sequences clustered to 14 OTUs, of which five were identified as Trypanosoma cruzi I, T. cruzi III/V, Trypanosoma cruzi marinkellei, Trypanosoma rangeli, and Trypanosoma dionisii, and seven were identified as novel genotypes monophyletic to basal T. cruzi clade types of the New World. Another OTU was identified as a trypanosome like those found in reptiles. Surprisingly, the remaining OTU was identified as Bodo saltans–closest non-parasitic relative of the trypanosomatid order. While three blood samples featured just one OTU (T. dionisii), all others resolved as mixed infections of up to eight OTUs. Conclusions/Significance: This study demonstrates the utility of next-generation barcoding methods to screen parasite diversity in mammalian reservoir hosts. We exposed high rates of local bat parasitism by multiple trypanosome species, some known to cause fatal human disease, others non-pathogenic, novel or yet little understood. Our results highlight bats as a long-standing nexus among host-parasite interactions of multiple niches, sustained in part by opportunistic and incidental infections of consequence to evolutionary theory as much as to public health. Author summary: Bats make up a mega-diverse, intensely parasitized order of volant mammals whose unique behavioural and physiological adaptations promote infection by a vast array of microorganisms. Trypanosomes stand out as ancient protozoan parasites of bats. As cryptic morphology, low parasitaemia and selective growth in culture have recurrently biased survey, we used 18S ribosomal RNA metabarcoding to resolve bat trypanosomatid diversity in Atlantic Forest fragments of southeast Brazil. Next to several unknown species, our deep sequence-based detection and assignment protocol recognized multiple known human-pathogenic trypanosomes, another linked to reptile hosts as well as a non-parasitic kinetoplastid in the blood of various phyllostomid bats. The striking permissivity exposed here, in a region where bat trypanosomes recently featured in a fatal case of Chagas disease, compels further research on bats’ role in the dispersal and spill-over of various microorganisms among humans and wildlife

PIA : more accurate taxonomic assignment of metagenomic data demonstrated on sedaDNA from the North sea

Assigning metagenomic reads to taxa presents significant challenges. Existing approaches address some issues, but are mostly limited to metabarcoding or optimized for microbial data. We present PIA (Phylogenetic Intersection Analysis): a taxonomic binner that works from standard BLAST output while mitigating key effects of incomplete databases. Benchmarking against MEGAN using sedaDNA suggests that, while PIA is less sensitive, it can be more accurate. We use known sequences to estimate the accuracy of PIA at up to 96% when the real organism is not represented in the database. For ancient DNA, where taxa of interest are frequently over-represented domesticates or absent, poorly-known organisms, more accurate assignment is critical, even at the expense of sensitivity. PIA offers an approach to objectively filter out false positive hits without the need to manually remove taxa and so make presuppositions about past environments and their palaeoecologies