DNA metabarcoding

Genetic and morphological identification of dragonflies' larvae species in three high‐elevation Andean tropical lakes was done using DNA barcoding of the cytochrome oxidase 1 gene (COI). Phylogeny allowed inferring the evolutionary relationships of at least five species (from 74 samples) that belong to two different families within the Odonata order.

Understanding which flowers honey bees (Apis mellifera) use for forage can help us to provide suitable plants for healthy honey bee colonies. Accordingly, honey DNA metabarcoding provides a valuable tool for investigating pollen and nectar collection. We investigated early season (April and May) floral choice by honey bees provided with a very high diversity of flowering plants within the National Botanic Garden of Wales. There was a close correspondence between the phenology of flowering and the detection of plants within the honey. Within the study area there were 437 genera of plants in flower during April and May, but only 11% of these were used. Thirty-nine plant taxa were recorded from three hives but only ten at greater than 1%. All three colonies used the same core set of native or near-native plants, typically found in hedgerows and woodlands. The major plants were supplemented with a range of horticultural species, with more variation in plant choice between the honey bee colonies. We conclude that during the spring, honey bees need access to native hedgerows and woodlands to provide major plants for foraging. Gardens provide supplementary flowers that may increase the nutritional diversity of the honey bee diet.

Background: Ticks are obligate haematophagous ectoparasites of vertebrate hosts and transmit the widest range of pathogenic organisms of any arthropod vector. Seven tick species are known to feed on bare-nosed wombats (Vom-batus ursinus), in addition to the highly prevalent Sarcoptes scabiei mite which causes fatal sarcoptic mange in most bare-nosed wombat populations. Little is known about the pathogens carried by most wombat ticks or how they may impact wombats and wombat handlers. Methods: Wombat ticks were sourced from wildlife hospitals and sanctuaries across Australia and identified to species level using taxonomic keys. Genomic DNA was extracted from a subsample, and following the amplification of the bacterial 16S rRNA gene V3-V4 hypervariable region, next-generation sequencing (NGS) on the Illumina MiSeq platform was used to assess the microbial composition. Results: A total of 447 tick specimens were collected from 47 bare-nosed wombats between January 2019 and Janu-ary 2020. Five species of ticks were identified comprising wombat tick Bothriocroton auruginans (n = 420), wallaby tick Haemaphysalis bancrofti (n = 8), bush tick Haemaphysalis longicornis (n = 3), common marsupial tick Ixodes tasmani (n = 12), and Australian paralysis tick Ixodes holocyclus (n = 4). Tick infestations ranged from one to 73 ticks per wombat. The wombat tick was the most prevalent tick species comprising 94% of the total number of samples and was present on 97.9% (46/47) of wombat hosts. NGS results revealed the 16S rRNA gene diversity profile was predominantly Proteobacteria (55.1%) followed by Firmicutes (21.9%) and Actinobacteria (18.4%). A species of Coxiella sharing closest sequence identity to Coxiella burnetii (99.07%), was detected in 72% of B. auruginans and a Rickettsiella endosymbiont dominated the bacterial profile for I. tasmani. Conclusions: A new host record for H. longicornis is the bare-nosed wombat. One adult male and two engorged adult female specimens were found on an adult male wombat from Coolagolite in New South Wales, and more specimens should be collected to confirm this host record. The most prevalent tick found on bare-nosed wombats was B. auruginans, confirming previous records. Analysis of alpha-diversity showed high variability across both sample locations and instars, similar to previous studies. The detection of various Proteobacteria in this study highlights the high bacterial diversity in native Australian ticks.

Background: Environmental DNA and metabarcoding allow the identification of a mixture of species and launch a new era in bio-and eco-assessment. Many steps are required to obtain taxonomically assigned matrices from raw data. For most of these, a plethora of tools are available; each tool's execution parameters need to be tailored to reflect each experiment's idiosyncrasy. Adding to this complexity, the computation capacity of high-performance computing systems is frequently required for such analyses. To address the difficulties, bioinformatic pipelines need to combine state-of-the art technologies and algorithms with an easy to get-set-use framework, allowing researchers to tune each study. Software containerization technologies ease the sharing and running of software packages across operating systems; thus, they strongly facilitate pipeline development and usage. Likewise programming languages specialized for big data pipelines incorporate features like roll-back checkpoints and on-demand partial pipeline execution. Findings: PEMA is a containerized assembly of key metabarcoding analysis tools that requires low effort in setting up, running, and customizing to researchers' needs. Based on third-party tools, PEMA performs read pre-processing, (molecular) operational taxonomic unit clustering, amplicon sequence variant inference, and taxonomy assignment for 16S and 18S ribosomal RNA, as well as ITS and COI marker gene data. Owing to its simplified parameterization and checkpoint support, PEMA allows users to explore alternative algorithms for specific steps of the pipeline without the need of a complete re-execution. PEMA was evaluated against both mock communities and previously published datasets and achieved results of comparable quality. Conclusions: A high-performance computing-based approach was used to develop PEMA; however, it can be used in personal computers as well. PEMA's time-efficient performance and good results will allow it to be used for accurate environmental DNA metabarcoding analysis, thus enhancing the applicability of next-generation biodiversity assessment studies.

Diatoms are important organisms in freshwater ecosystems due to their position as primary producers and therefore, analyzing their assemblages provides relevant information on ecosystem functioning. Diatoms have historically been identified based on morphological traits, which is time-consuming and requires well-trained specialists. Nevertheless, DNA barcoding offers an alternative approach to overcome some limitations of the morphological method. Here, we assess if both approaches are comparable methods to study patterns and mechanisms (including environmental filtering and dispersal limitation) of epiphytic diatom metacommunities using a comprehensive dataset from 22 Mediterranean ponds at different taxonomic resolutions. We used a fragment of rbcL barcode gene combined with High-Throughput Sequencing to infer diatom community composition. The overall degree of correspondence between both approaches was assessed by Procrustean rotation analysis and Procrustean randomization tests, whereas the role of local environmental variables and geographical distances was studied using a comprehensive combination of BIOENV, Mantel tests and distance-based redundancy analysis. Our results showed a relatively poor correspondence in the compositional variation of diatom metacommunity between both approaches. We speculate that the incompleteness of the reference database and the bioinformatics processing are the biases most likely affecting the molecular approach, whereas the limited counting effort and the presence of cryptic species are presumably the major biases related with the morphological method. On the other hand, variation in diatom community composition detected with both approaches was strongly related to the environmental template, which may be related with the narrow community-environment relationships in diatoms. Nevertheless, we found no significant relationship between compositional variation and geographical distances. Overall, our work shows the complementary nature of both approaches and highlights the importance of DNA metabarcoding to address empirical research questions of community ecology in freshwaters, especially once the reference databases include most genotypes of occurring taxa and bioinformatics biases are overcome.

DNA-metabarcoding of the fungal communities in environmental samples has greatly enhanced our knowledge of fungal diversity. However, linking taxonomic information to fungal traits is often challenging because of the immense species diversity encountered in most samples. This complicates inferring functional roles in ecosystem processes from biodiversity patterns. We have therefore made ecological traits of Ascomycete genera, compiled in a previous study, digitally accessible and searchable.

Cephalopods are primarily active predators throughout life. Flying squids (family Ommastrephidae) represents the most widely distributed and ecologically important family of cephalopods. While the diets of adult flying squids have been extensively studied, the first feeding diet of early paralarvae remains a mystery. The morphology of this ontogenetic stage notably differs from other cephalopod paralarvae, suggesting a different feeding strategy. Here, a combination of Laser Capture Microdissection (LCM) and DNA metabarcoding of wild-collected paralarvae gut contents for eukaryotic 18S v9 and prokaryotic 16S rRNA was applied, covering almost every life domain. The gut contents were mainly composed by fungus, plants, algae and animals of marine and terrestrial origin, as well as eukaryotic and prokaryotic microorganisms commonly found in fecal pellets and particulate organic matter. This assemblage of gut contents is consistent with a diet based on detritus. The ontogenetic shift of diet from detritivore suspension feeding to active predation represents a unique life strategy among cephalopods and allows ommastrephid squids to take advantage of an almost ubiquitous and accessible food resource during their early stages. LCM was successfully applied for the first time to tiny, wild-collected marine organisms, proving its utility in combination with DNA metabarcoding for dietary studies.

Background: Microsporidia is a large group of eukaryotic obligate intracellular spore-forming parasites, of which 17 species can cause microsporidiosis in humans. Most human-infecting microsporidians belong to the genera Enterocytozoon and Encephalitozoon. To date, only five microsporidian species, including Encephalitozoon-like, have been found in hard ticks (Ixodidae) using microscopic methods, but no sequence data are available for them. Furthermore, no widespread screening for microsporidian-infected ticks based on DNA analysis has been carried out to date. Thus, in this study, we applied a recently developed DNA metabarcoding method for efficient microsporidian DNA identification to assess the role of ticks as potential vectors of microsporidian species causing diseases in humans. Methods: In total, 1070 (493 juvenile and 577 adult) unfed host-seeking Ixodes ricinus ticks collected at urban parks in the city of Poznan, Poland, and 94 engorged tick females fed on dogs and cats were screened for microsporidian DNA. Microsporidians were detected by PCR amplification and sequencing of the hypervariable V5 region of 18S rRNA gene (18S profiling) using the microsporidian-specific primer set. Tick species were identified morphologically and confirmed by amplification and sequencing of the shortened fragment of cytochrome c oxidase subunit I gene (mini-COI). Results: All collected ticks were unambiguously assigned to I. ricinus. Potentially zoonotic Encephalitozoon intestinalis was identified in three fed ticks (3.2%) collected from three different dogs. In eight unfed host-seeking ticks (0.8%), including three males (1.1%), two females (0.7%) and three nymphs (0.7%), the new microsporidian sequence representing a species belonging to the genus Endoreticulatus was identified. Conclusions: The lack of zoonotic microsporidians in host-seeking ticks suggests that I. ricinus is not involved in transmission of human-infecting microsporidians. Moreover, a very low occurrence of the other microsporidian species in both fed and host-seeking ticks implies that mechanisms exist to defend ticks against infection with these parasites.

Benthic diatoms have traditionally been used as bioindicators of aquatic ecosystems. Because diatom-based monitoring of water quality is required by European legislation, molecular-based methods had emerged as useful alternatives to classical methods based on morphological identification using light microscopy. The aim of this study was to test the reliability of DNA metabarcoding combined with High-Throughput Sequencing (HTS) techniques in the bioassessment of the trophic status of 22 Mediterranean shallow ponds in NW Spain. For each pond, the Trophic Diatom Index (TDI) was calculated from inventories obtained by identification using light microscopy (LM) followed by high-throughput sequencing (HTS) at the molecular level. Ponds were subsequently classified into five water quality classes. The results showed a good correspondence between both methods, especially after applying a correction factor that depended on the biovolume of the cells. This correspondence led to the assignment to the same quality class in 59% of the ponds. The determination and quantification of valves or DNA sequences was one of the main pitfalls, which mainly included those related to the variability in the relative abundances of some species. Accordingly, ponds with similar relative abundances for the dominant species were assigned to the same quality class. Moreover, other difficulties leading the discrepancies were the misidentification of some species due to the presence of semi-cryptic taxa, the incompleteness of the reference database and the bioinformatic protocol. Thus, the validation of DNA-based methods for the identification of freshwater diatoms represents an important goal, as an alternative to using traditional methods in Mediterranean shallow ponds.

Community composition data are essential for conservation management, facilitating identification of rare native and invasive species, along with abundant ones. However, traditional capture-based morphological surveys require considerable taxonomic expertise, are time consuming and expensive, can kill rare taxa and damage habitats, and often are prone to false negatives. Alternatively, metabarcoding assays can be used to assess the genetic identity and compositions of entire communities from environmental samples, comprising a more sensitive, less damaging, and relatively time- and cost-efficient approach. However, there is a trade-off between the stringency of bioinformatic filtering needed to remove false positives and the potential for false negatives. The present investigation thus evaluated use of four mitochondrial (mt) DNA metabarcoding assays and a customized bioinformatic pipeline to increase confidence in species identifications by removing false positives, while achieving high detection probability. Positive controls were used to calculate sequencing error, and results that fell below those cutoff values were removed, unless found with multiple assays. The performance of this approach was tested to discern and identify North American freshwater fishes using lab experiments (mock communities and aquarium experiments) and processing of a bulk ichthyoplankton sample. The method then was
applied to field environmental (e) DNA water samples taken concomitant with electrofishing surveys and morphological identifications. This protocol detected 100% of species present in concomitant electrofishing surveys in the Wabash River and an additional 21 that were absent from traditional sampling. Using single 1 L water samples collected from just four locations, the metabarcoding assays discerned 73% of the total fish species that were discerned during four months of an extensive electrofishing river survey in the Maumee River, along with an additional nine species. In both rivers, total fish species diversity was best resolved when all four
metabarcoding assays were used together, which identified 35 additional species missed by electrofishing. Ecological distinction and diversity levels among the fish communities also were better resolved with the metabarcoding assays than with morphological sampling and identifications, especially using all four assays together. At the population-level, metabarcoding analyses targeting the invasive round goby Neogobius melanostomus and the silver carp Hypophthalmichthys molitrix identified all population haplotype variants found using Sanger sequencing of morphologically sampled fish, along with additional intra-specific diversity, meriting further investigation. Overall findings demonstrated that the use of multiple metabarcoding assays and custom bioinformatics that filter potential error from true positive detections improves confidence in evaluating biodiversity.

As many ecosystems are under increasing pressure from invasive species, habitat degradation, overgrazing and overharvesting, pollution, and climate change, dietary niche monitoring is gaining importance. The Malai Mahadeshwara Wildlife Sanctuary (MMH) in southern India is home to several long-standing ethnic and tribal groups and supports a considerable number of domestic herbivores (cattle, goats and water buffalo) as well as a range of wildlife (including several species of deer, bonnet macaque, and Asian elephant). We reconstructed dietary niche partitioning of the herbivores occurring in MMH using eDNA metabarcoding to quantify diet richness, composition, and overlap. In total, we distinguish 134 diet items (molecular operational taxonomic units), covering 31 plant families. Overall, our results indicate 35% overlap in domestic and wild herbivore diet items. The greatest overlap is found for the dietary niches of cattle and sambar deer (Pianka's niche overlap index: 0.68), and the dietary niche of cattle also overlaps considerably with those of Indian hare (0.65) and Asian
elephant (0.46). This suggests that these herbivores may compete for these food plants in the case of limited availability, which could lead to exclusion of some herbivore species. Particular concern should go to bonnet macaque and Asian elephant as their below average dietary richness could make them vulnerable to changes in their environment. With increasing pressures on local wildlife from a range of different factors, DNA metabarcoding of fecal samples is a non-invasive method for monitoring
changes in animal diets, providing valuable information for the management of biodiversity in mosaic natural and anthropogenic landscapes.

DNA metabarcoding provides great potential for species identification in complex samples such as food supplements and traditional medicines. Such a method would aid Convention on International Trade in Endangered Species of Wild Fauna and Flora (CITES) enforcement officers to combat wildlife crime by preventing illegal trade of endangered plant and animal species. The objective of this research was to develop a multi-locus DNA metabarcoding method for forensic wildlife species identification and to evaluate the applicability and reproducibility of this approach across different laboratories. A DNA metabarcoding method was developed that makes use of 12 DNA barcode markers that have demonstrated universal applicability across a wide range of plant and animal taxa and that facilitate the identification of species in samples containing degraded DNA. The DNA metabarcoding method was developed based on Illumina MiSeq amplicon sequencing of well-defined experimental mixtures, for which a bioinformatics pipeline with user-friendly web-interface was developed. The performance of the DNA metabarcoding method was assessed in an international validation trial by 16 laboratories, in which the method was found to be highly reproducible and sensitive enough to identify species present in a mixture at 1% dry weight content. The advanced multi-locus DNA metabarcoding method assessed in this study provides reliable and detailed data on the composition of complex food products, including information on the presence of CITES-listed species. The method can provide improved resolution for species identification, while verifying species with multiple DNA barcodes contributes to an enhanced quality assurance.

The main objective of this work was to develop and validate a robust and reliable " from-benchtop-to-desktop " metabarcoding workflow to investigate the diet of invertebrate-eaters. We applied our workflow to faecal DNA samples of an invertebrate eating fish species. A fragment of the cytochrome c oxidase I (COI) gene was amplified by combining two minibarcoding primer sets to maximize the taxonomic coverage. Amplicons were sequenced by an Illumina MiSeq platform. We developed a filtering approach based on a series of nonarbitrary thresholds established from control samples and from molecular replicates to address the elimination of cross-contamination, PCR/sequencing errors and mistagging artefacts. This resulted in a conservative and informative metabarcoding data set. We developed a taxonomic assignment procedure that combines different approaches and that allowed the identification of ~75% of invertebrate COI variants to the species level. Moreover, based on the diversity of the variants, we introduced a semiquantitative statistic in our diet study, the minimum number of individuals, which is based on the number of distinct variants in each sample. The metabarcoding approach described in this article may guide future diet studies that aim to produce robust data sets associated with a fine and accurate identification of prey items.

Background Environmental DNA and metabarcoding allow the identification of a mixture of species and launch a new era in bio- and eco-assessment. Many steps are required to obtain taxonomically assigned matrices from raw data. For most of these, a plethora of tools are available; each tool's execution parameters need to be tailored to reflect each experiment's idiosyncrasy. Adding to this complexity, the computation capacity of high-performance computing systems is frequently required for such analyses. To address the difficulties, bioinformatic pipelines need to combine state-of-the art technologies and algorithms with an easy to get-set-use framework, allowing researchers to tune each study. Software containerization technologies ease the sharing and running of software packages across operating systems; thus, they strongly facilitate pipeline development and usage. Likewise programming languages specialized for big data pipelines incorporate features like roll-back checkpo...

Species compositions and diversity levels of aquatic macroinvertebrate
communities provide important indicators of ecosystem health. However,
such community analyses typically are limited by time and effort of sampling,
sorting, and identifications, as well as morphological character uncertainty
for some taxa, especially at early life stages. Our objective was to evaluate a
suite of targeted metabarcode high‐throughput sequencing assays to
characterize the macroinvertebrate communities (specifically targeting
Annelida, Bryozoa, Crustacea, Insecta, and Mollusca) from environmental
(e)DNA water samples along 160 km of the Maumee River, OH (a major Lake
Erie, Laurentian Great Lakes tributary). Multiple alpha (richness, Shannon
Index, and Simpson's Index) and beta (Bray–Curtis and Sørensen
dissimilarities) diversity metrics from the metabarcode assays were
compared with an Invertebrate Community Index (ICI) metric calculated from
traditional morphological sampling surveys conducted by the Ohio
Environmental Protection Agency. The 15 Maumee River sites varied in their
ICI scores (ranging from 4 to 46), with seven sites rated as “poor” or “very
poor” and eight scoring “fair” or “good.” Metabarcoding assays yielded
greater gamma richness, delineating 181 Operational Taxonomic Units
versus 172 taxa from morphology (the latter often limited to family or genuslevel
identifications). Both datasets supported similar river‐wide trends, with
comparable gamma, alpha, and beta diversity patterns and community
compositions across habitat types and habitat quality scores. Metabarcode
assays revealed similar detection of important bioindicator Insecta, but
missed most Trichoptera (caddisflies). eDNA identified eight aquatic invasive
species on the GLANSIS (Great Lakes Aquatic Nonindigenous Species
Information System) list, including three missed by the morphological surveys
(Branchiura sowerbyi , Potamothrix bedoti , and Skistodiaptomus pallidus;
with Lophopodella carteri , Faxonius rusticus , Corbicula fluminea ,
Dreissena polymorpha , and Valvata piscinalis in both datasets). Findings
illustrate the utility of eDNA sampling and targeted metabarcode assays to
enhance and complement environmental assessments of aquatic
ecosystems.

Members of the family Cranchiidae Prosch, 1847, commonly known as glass or bathyscaphoid squids, range from small translucent species to the massive-sized colossal squid. Those cephalopods are widely distributed in all oceans, also representing one of the more diverse families of squids and, despite their ecological importance, their diet is almost unknown. Cranchiids represent a significant prey for many organisms in the mesopelagic zone, from fishes to marine megafauna, as sharks, swordfishes and whales. Their trophic role is mostly unknown and only few studies are available. Aims: characterize for the first time the diet of cranchiid squids through DNA metabarcoding. Methods (see figure for a graphical abstract of the workflow): gut contents of 62 squids collected in the Atlantic, belonging to 10 genera were used to amplify a fragment of the mitochondrial gene cytochrome c oxidase subunit I, and sequenced in the high-throughput sequencing platform Illumina. Sequencing reads were identified using published sequences. Results: A preliminary bioinformatic analysis of the reads from the gut contents shows a wide diversity of eukaryotic sequences. The more represented reads belong to Malacostraca, Actinopterygii, Cephalopoda, Hydrozoa and Insecta. Conclusion: Molecular assessment of the diet of 10 of the 13 described genera of cranchiids revealed the taxonomic spectrum of their ingested items, helping to understand the role of these squids in the mesopelagic realm.