Several parasite species are shared between humans and pigs. We explored the application of next-generation sequencing-based metabarcoding supplemented with real-time PCR to fecal DNAs from 259 samples from 116 pigs in Denmark to detect and differentiate single-celled intestinal parasites of zoonotic relevance. Enterocytozoon bieneusi, Balantioides coli, and Giardia duodenalis were observed in 34/37 (92%), 148/259 (57%), and 86/259 (33%) samples, respectively. Entamoeba polecki ST1, E. polecki ST3, and Entamoeba hartmanni were detected in 104/259 (40%), 161/259 (62%), and 8/259 (3%) samples, respectively. Metabarcoding and real-time PCR detected Cryptosporidium in 90/259 (35%) and 239/259 (92%) of the samples, respectively, with Cryptosporidium suis and Cryptosporidium scrofarum observed in nearly equal proportions. Blastocystis subtypes 1, 3, 5, and 15 were found in 72 (28%), 6 (2%), 176 (68%), and 36 (14%) of 259 samples, respectively. Iodamoeba was identified in 1/259 samples (<1%), while none of 37 tested samples was positive for Dientamoeba fragilis. Our results illustrate how metabarcoding exemplifies a 'one-fits-many' approach to detecting intestinal single-celled parasites in feces supplemented with real-time PCR for selected parasites. Using metabarcoding with pathogen-specific assays may help detect emerging and previously underdetected pathogens and further elucidate the role of micro-eukaryotic parasites in human and animal health and disease.
- Publication type
- Journal Article MeSH
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.
- MeSH
- DNA, Plant genetics MeSH
- Endangered Species * MeSH
- Reproducibility of Results MeSH
- Plants classification genetics MeSH
- DNA Barcoding, Taxonomic * MeSH
- Computational Biology MeSH
- Animals MeSH
- Check Tag
- Animals MeSH
- Publication type
- Journal Article MeSH
Strongylid nematodes in large terrestrial herbivores such as great apes, equids, elephants, and humans tend to occur in complex communities. However, identification of all species within strongylid communities using traditional methods based on coproscopy or single nematode amplification and sequencing is virtually impossible. High-throughput sequencing (HTS) technologies provide opportunities to generate large amounts of sequence data and enable analyses of samples containing a mixture of DNA from multiple species/genotypes. We designed and tested an HTS approach for strain-level identification of gastrointestinal strongylids using ITS-2 metabarcoding at the MiSeq Illumina platform in samples from two free-ranging non-human primate species inhabiting the same environment, but differing significantly in their host traits and ecology. Although we observed overlapping of particular haplotypes, overall the studied primate species differed in their strongylid nematode community composition. Using HTS, we revealed hidden diversity in the strongylid nematode communities in non-human primates, more than one haplotype was found in more than 90% of samples and coinfections of more than one putative species occurred in 80% of samples. In conclusion, the HTS approach on strongylid nematodes, preferably using fecal samples, represents a time and cost-efficient way of studying strongylid communities and provides a resolution superior to traditional approaches.
- MeSH
- Feces parasitology MeSH
- Genetic Variation MeSH
- Strongylida Infections genetics parasitology MeSH
- Horses genetics parasitology MeSH
- Horse Diseases genetics parasitology MeSH
- Interspersed Repetitive Sequences genetics MeSH
- Strongylida classification genetics MeSH
- Sympatry MeSH
- DNA Barcoding, Taxonomic * MeSH
- High-Throughput Nucleotide Sequencing MeSH
- Animals MeSH
- Check Tag
- Animals MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Understanding interactions between herbivores and parasitoids is essential for successful biodiversity protection and monitoring and for biological pest control. Morphological identifications employ insect rearing and are complicated by insects' high diversity and crypsis. DNA barcoding has been successfully used in studies of host-parasitoid interactions as it can substantially increase the recovered real host-parasitoid diversity distorted by overlooked species complexes, or by species with slight morphological differences. However, this approach does not allow the simultaneous detection and identification of host(s) and parasitoid(s). Recently, high-throughput sequencing has shown high potential for surveying ecological communities and trophic interactions. Using mock samples comprising insect larvae and their parasitoids, we tested the potential of DNA metabarcoding for identifying individuals involved in host-parasitoid interactions to different taxonomic levels, and compared it to standard DNA barcoding and morphological approaches. For DNA metabarcoding, we targeted the standard barcoding marker cytochrome oxidase subunit I using highly degenerate primers, 2*300 bp sequencing on a MiSeq platform, and RTAX classification using paired-end reads. Additionally, using a large host-parasitoid dataset from a Central European floodplain forest, we assess the completeness and usability of a local reference library by confronting the number of Barcoding Index Numbers obtained by standard barcoding with the number of morphotypes. Overall, metabarcoding recovery was high, identifying 92.8% of the taxa present in mock samples, and identification success within individual taxonomic levels did not significantly differ among metabarcoding, standard barcoding, and morphology. Based on the current local reference library, 39.4% parasitoid and 90.7% host taxa were identified to the species level. DNA barcoding estimated higher parasitoid diversity than morphotyping, especially in groups with high level of crypsis. This study suggests the potential of metabarcoding for effectively recovering host-parasitoid diversity, together with more accurate identifications obtained from building reliable and comprehensive reference libraries, especially for parasitoids.
Molecular techniques like metabarcoding, while promising for exploring diversity of communities, are often impeded by the lack of reference DNA sequences available for taxonomic annotation. Our study explores the benefits of combining targeted DNA barcoding and morphological taxonomy to improve metabarcoding efficiency, using beach meiofauna as a case study. Beaches are globally important ecosystems and are inhabited by meiofauna, microscopic animals living in the interstitial space between the sand grains, which play a key role in coastal biodiversity and ecosystem dynamics. However, research on meiofauna faces challenges due to limited taxonomic expertise and sparse sampling. We generated 775 new cytochrome c oxidase I DNA barcodes from meiofauna specimens collected along the Netherlands' west coast and combined them with the NCBI GenBank database. We analysed alpha and beta diversity in 561 metabarcoding samples from 24 North Sea beaches, a region extensively studied for meiofauna, using both the enriched reference database and the NCBI database without the additional reference barcodes. Our results show a 2.5-fold increase in sequence annotation and a doubling of species-level Operational Taxonomic Units (OTUs) identification when annotating the metabarcoding data with the enhanced database. Additionally, our analyses revealed a bell-shaped curve of OTU richness across the intertidal zone, aligning more closely with morphological analysis patterns, and more defined community dissimilarity patterns between supralittoral and intertidal sites. Our research highlights the importance of expanding molecular reference databases and combining morphological taxonomy with molecular techniques for biodiversity assessments, ultimately improving our understanding of coastal ecosystems.
- MeSH
- Invertebrates genetics classification MeSH
- Biodiversity MeSH
- Ecosystem MeSH
- Bathing Beaches MeSH
- Metagenomics methods MeSH
- Electron Transport Complex IV * genetics MeSH
- DNA Barcoding, Taxonomic * methods MeSH
- Animals MeSH
- Check Tag
- Animals MeSH
- Publication type
- Journal Article MeSH
- Geographicals
- Netherlands MeSH
- North Sea MeSH
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.
- MeSH
- Archaea MeSH
- Bacteria MeSH
- DNA, Environmental chemistry genetics MeSH
- Fungi MeSH
- Metagenomics methods standards MeSH
- Reference Standards MeSH
- Electron Transport Complex IV genetics MeSH
- RNA, Ribosomal, 16S genetics MeSH
- RNA, Ribosomal, 18S genetics MeSH
- Plants MeSH
- Sensitivity and Specificity MeSH
- Software MeSH
- DNA Barcoding, Taxonomic methods standards MeSH
- Animals MeSH
- Check Tag
- Animals MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
Ancient DNA from historical and subfossil wood has a great potential to provide new insights into the history of tree populations. However, its extraction and analysis have not become routine, mainly because contamination of the wood with modern plant material can complicate the verification of genetic information. Here, we used sapwood tissue from 22 subfossil pines that were growing c. 13 000 yr bp in Zurich, Switzerland. We developed and evaluated protocols to eliminate surface contamination, and we tested ancient DNA authenticity based on plastid DNA metabarcoding and the assessment of post-mortem DNA damage. A novel approach using laser irradiation coupled with bleaching and surface removal was most efficient in eliminating contaminating DNA. DNA metabarcoding confirmed which ancient DNA samples repeatedly amplified pine DNA and were free of exogenous plant taxa. Pine DNA sequences of these samples showed a high degree of cytosine to thymine mismatches, typical of post-mortem damage. Stringent decontamination of wood surfaces combined with DNA metabarcoding and assessment of post-mortem DNA damage allowed us to authenticate ancient DNA retrieved from the oldest Late Glacial pine forest. These techniques can be applied to any subfossil wood and are likely to improve the accessibility of relict wood for genome-scale ancient DNA studies.
The world's oceans represent by far the largest biome, with great importance for the global ecosystem [1-4]. The vast majority of ocean biomass and biodiversity is composed of microscopic plankton. Recent results from the Tara Oceans metabarcoding study revealed that a significant part of the plankton in the upper sunlit layer of the ocean is represented by an understudied group of heterotrophic excavate flagellates called diplonemids [5, 6]. We have analyzed the diversity and distribution patterns of diplonemid populations on the extended set of Tara Oceans V9 18S rDNA metabarcodes amplified from 850 size- fractionated plankton communities sampled across 123 globally distributed locations, for the first time also including samples from the mesopelagic zone, which spans the depth from about 200 to 1,000 meters. Diplonemids separate into four major clades, with the vast majority falling into the deep-sea pelagic diplonemid clade. Remarkably, diversity of this clade inferred from metabarcoding data surpasses even that of dinoflagellates, metazoans, and rhizarians, qualifying diplonemids as possibly the most diverse group of marine planktonic eukaryotes. Diplonemids display strong vertical separation between the photic and mesopelagic layers, with the majority of their relative abundance and diversity occurring in deeper waters. Globally, diplonemids display no apparent biogeographic structuring, with a few hyperabundant cosmopolitan operational taxonomic units (OTUs) dominating their communities. Our results suggest that the planktonic diplonemids are among the key heterotrophic players in the largest ecosystem of our biosphere, yet their roles in this ecosystem remain unknown.
- MeSH
- Biodiversity * MeSH
- Ecosystem * MeSH
- Euglenozoa classification genetics MeSH
- Oceans and Seas MeSH
- Plankton classification genetics MeSH
- RNA, Protozoan genetics MeSH
- RNA, Ribosomal, 18S genetics MeSH
- Sequence Analysis, RNA MeSH
- DNA Barcoding, Taxonomic MeSH
- Aquatic Organisms physiology MeSH
- Publication type
- Journal Article MeSH
- Geographicals
- Oceans and Seas MeSH
The way pollinators gather resources may play a key role for buffering their population declines. Social pollinators like bumblebees could adjust their foraging after significant workforce reductions to keep provisions to the colony optimal, especially in terms of pollen diversity and quantity. To test what effects a workforce reduction causes on the foraging for pollen, commercially-acquired colonies of the bumblebee Bombus terrestris were allowed to forage in the field and they were experimentally manipulated by removing half the number of workers. For each bumblebee, the pollen pellets were taxonomically identified with DNA metabarcoding of the ITS2 region followed by a statistical filtering based on ROC curves to filter out underrepresented OTUs. Video cameras and network analyses were employed to investigate changes in foraging strategies and behaviour. After filtering out the false-positives, HTS metabarcoding yielded a high plant diversity in the pollen pellets; for plant identity and pollen quantity traits no differences emerged between samples from treated and from control colonies, suggesting that plant choice was influenced mainly by external factors such as the plant phenology. The colonies responded to the removal of 50% of their workers by increasing the foraging activity of the remaining workers, while only negligible changes were found in diet breadth and indices describing the structure of the pollen transport network. Therefore, a consistency in the bumblebees' feeding strategies emerges in the short term despite the lowered workforce.
- MeSH
- Biodiversity MeSH
- Animal Nutritional Physiological Phenomena MeSH
- Pollination physiology MeSH
- Population Dynamics MeSH
- Pollen * genetics MeSH
- Plants classification genetics MeSH
- Feeding Behavior MeSH
- DNA Barcoding, Taxonomic MeSH
- Bees physiology MeSH
- Animals MeSH
- Check Tag
- Animals MeSH
- Publication type
- Journal Article MeSH
- Research Support, Non-U.S. Gov't MeSH
- Geographicals
- Czech Republic MeSH
