DNA metabarcoding provides a scalable alternative to traditional botanical surveys, which are often time-consuming and reliant on taxonomic expertise. Here, we compare DNA metabarcoding with quadrat-based botanical surveys to assess plant species composition in experimental grassland plots under four defoliation regimes (continuous grazing, rotational grazing, frequent cutting and conservation cutting). Botanical surveys identified 16 taxa, while metabarcoding detected 25 taxa, including the dominant species Holcus lanatus and Lolium perenne. Despite detecting more taxa, there were some discrepancies in identification, with the sequence data only able to resolve some taxa at the genus level (e.g., Agrostis spp. instead of Agrostis capillaris) and potential species misidentifications (e.g., Cardaminopsis helleri vs. Cardamine flexuosa). However, both methods provided comparable results and revealed statistically significant differences in species composition between treatments, with higher diversity in cut versus grazed plots. The semi-quantitative nature of metabarcoding limits its capacity to accurately reflect species abundance, posing challenges for ecological interpretations where precise quantification is required. However, it provides a broader view of biodiversity and can complement traditional methods, offering new opportunities for efficient biodiversity monitoring. The findings support the integration of DNA metabarcoding into biodiversity assessments, particularly when used alongside traditional techniques. Further refinement of bioinformatics tools and reference databases will enhance their accuracy and reliability, enabling more effective monitoring of grassland biodiversity and sustainable management practices. This study highlights DNA metabarcoding as a valuable tool for understanding plant community responses to management interventions.

• Keywords
• DNA metabarcoding, botanical survey, ecological monitoring, grassland biodiversity, species composition,
• Publication type
• Journal Article MeSH

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.

• Keywords
• DNA, PCR, genetic diversity, host specificity, metabarcoding, next-generation sequencing, parasite, parasitology, zoonotic infections,
• Publication type
• Journal Article MeSH

Environmental DNA (eDNA) metabarcoding (parallel sequencing of DNA/RNA for identification of whole communities within a targeted group) is revolutionizing the field of aquatic biomonitoring. To date, most metabarcoding studies aiming to assess the ecological status of aquatic ecosystems have focused on water eDNA and macroinvertebrate bulk samples. However, the eDNA metabarcoding has also been applied to soft sediment samples, mainly for assessing microbial or meiofaunal biota. Compared to classical methodologies based on manual sorting and morphological identification of benthic taxa, eDNA metabarcoding offers potentially important advantages for assessing the environmental quality of sediments. The methods and protocols utilized for sediment eDNA metabarcoding can vary considerably among studies, and standardization efforts are needed to improve their robustness, comparability and use within regulatory frameworks. Here, we review the available information on eDNA metabarcoding applied to sediment samples, with a focus on sampling, preservation, and DNA extraction steps. We discuss challenges specific to sediment eDNA analysis, including the variety of different sources and states of eDNA and its persistence in the sediment. This paper aims to identify good-practice strategies and facilitate method harmonization for routine use of sediment eDNA in future benthic monitoring.

• Keywords
• Aquatic ecosystems, Environmental DNA, Metabarcoding, Monitoring, Sediments,
• MeSH
• Biodiversity MeSH
• DNA genetics   MeSH
• Ecosystem MeSH
• DNA, Environmental * MeSH
• Environmental Monitoring methods   MeSH
• DNA Barcoding, Taxonomic MeSH
• Publication type
• Journal Article MeSH
• Review MeSH
• Names of Substances
• DNA MeSH
• DNA, Environmental * MeSH

Environmental DNA (eDNA) metabarcoding has gained growing attention as a strategy for monitoring biodiversity in ecology. However, taxa identifications produced through metabarcoding require sophisticated processing of high-throughput sequencing data from taxonomically informative DNA barcodes. Various sets of universal and taxon-specific primers have been developed, extending the usability of metabarcoding across archaea, bacteria and eukaryotes. Accordingly, a multitude of metabarcoding data analysis tools and pipelines have also been developed. Often, several developed workflows are designed to process the same amplicon sequencing data, making it somewhat puzzling to choose one among the plethora of existing pipelines. However, each pipeline has its own specific philosophy, strengths and limitations, which should be considered depending on the aims of any specific study, as well as the bioinformatics expertise of the user. In this review, we outline the input data requirements, supported operating systems and particular attributes of thirty-two amplicon processing pipelines with the goal of helping users to select a pipeline for their metabarcoding projects.

• Keywords
• amplicon data analysis, bioinformatics, environmental DNA, metabarcoding, pipeline, review,
• MeSH
• Data Analysis MeSH
• Archaea genetics   classification   MeSH
• Bacteria genetics   classification   MeSH
• DNA, Environmental genetics   MeSH
• Eukaryota genetics   classification   MeSH
• Metagenomics methods   MeSH
• Software * MeSH
• DNA Barcoding, Taxonomic * methods   MeSH
• Computational Biology * methods   MeSH
• High-Throughput Nucleotide Sequencing methods   MeSH
• Publication type
• Journal Article MeSH
• Review MeSH
• Names of Substances
• DNA, Environmental MeSH

Fish are vital in river ecosystems; however, traditional investigations of fish usually cause ecological damage. Extracting DNA from aquatic environments and identifying DNA sequences offer an alternative, noninvasive approach for detecting fish species. In this study, the effects of environmental DNA (eDNA), coupled with PCR and next-generation sequencing, and electrofishing for identifying fish community composition and diversity were compared. In three subtropical rivers of southern China, fish specimens and eDNA in water were collected along the longitudinal (upstream-downstream) gradient of the rivers. Both fish population parameters, including species abundance and biomass, and eDNA OTU richness grouped 38 sampling sites into eight spatial zones with significant differences in local fish community composition. Compared with order-/family-level grouping, genus-/species-level grouping could more accurately reveal the differences between upstream zones I-III, midstream zones IV-V, and downstream zones VI-VIII. From the headwaters to the estuary, two environmental gradients significantly influenced the longitudinal distribution of the fish species, including the first gradient composed of habitat and physical water parameters and the second gradient composed of chemical water parameters. The high regression coefficient of alpha diversity between eDNA and electrofishing methods as well as the accurate identification of dominant, alien, and biomarker species in each spatial zone indicated that eDNA could characterize fish community attributes at a level similar to that of traditional approaches. Overall, our results demonstrated that eDNA metabarcoding can be used as an effective tool for revealing fish composition and diversity, which is important for using the eDNA technique in aquatic field monitoring.

• Keywords
• biomarker, fish community, high‐throughput sequencing, metabarcoding, monitoring tool, river food web,
• 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.

• Keywords
• CITES, COI, Customs agencies, DNA metabarcoding, Endangered species, Traditional medicines, cyt b, matK, mini-barcodes, rbcL,
• 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
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• DNA, Plant 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.

• Keywords
• Docker, HPC, container, eDNA, high performance computing, metabarcoding, pipeline, singularity,
• 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
• Names of Substances
• DNA, Environmental MeSH
• Electron Transport Complex IV MeSH
• RNA, Ribosomal, 16S MeSH
• RNA, Ribosomal, 18S MeSH

Metabarcoding is revolutionizing fundamental research in ecology by enabling large-scale detection of species and producing data that are rich with community context. However, the benefits of metabarcoding have yet to be fully realized in fields of applied ecology, especially those such as classical biological control (CBC) research that involve hyperdiverse taxa. Here, we discuss some of the opportunities that metabarcoding provides CBC and solutions to the main methodological challenges that have limited the integration of metabarcoding in existing CBC workflows. We focus on insect parasitoids, which are popular and effective biological control agents (BCAs) of invasive species and agricultural pests. Accurately identifying native, invasive and BCA species is paramount, since misidentification can undermine control efforts and lead to large negative socio-economic impacts. Unfortunately, most existing publicly accessible genetic databases cannot be used to reliably identify parasitoid species, thereby limiting the accuracy of metabarcoding in CBC research. To address this issue, we argue for the establishment of authoritative genetic databases that link metabarcoding data to taxonomically identified specimens. We further suggest using multiple genetic markers to reduce primer bias and increase taxonomic resolution. We also provide suggestions for biological control-specific metabarcoding workflows intended to track the long-term effectiveness of introduced BCAs. Finally, we use the example of an invasive pest, Drosophila suzukii, in a reflective "what if" thought experiment to explore the potential power of community metabarcoding in CBC.

• Keywords
• Drosophila suzukii, invasive species, molecular identification, reference library,
• MeSH
• Drosophila MeSH
• Ecology * MeSH
• Genetic Markers MeSH
• Insecta * MeSH
• DNA Barcoding, Taxonomic MeSH
• Animals MeSH
• Check Tag
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• Genetic Markers MeSH

Metabarcoding revolutionized our understanding of diversity and ecology of microorganisms in different habitats. However, it is also associated with several inherent biases, one of which is associated with intragenomic diversity of a molecular barcode. Here, we compare intragenomic variability of the V9 region of the 18S rRNA gene in 19 eukaryotic phyla abundant in marine plankton. The level of intragenomic variability is comparable across all the phyla, and in most genomes and transcriptomes one V9 sequence and one OTU is predominant. However, most of the variability observed at the barcode level is probably caused by sequencing errors and is mitigated by using a denoising tool, DADA2. The SWARM algorithm commonly used in metabarcoding studies is not optimal for collapsing genuine and erroneous sequences into a single OTU, leading to an overestimation of diversity in metabarcoding data. For an unknown reason, SWARM inflates diversity of eupelagonemids more than that of other eukaryotes.

• Keywords
• Computational bioinformatics, Genetics, Genomics,
• Publication type
• Journal Article MeSH

The soil fauna of the tropics remains one of the least known components of the biosphere. Long-term monitoring of this fauna is hampered by the lack of taxonomic expertise and funding. These obstacles may potentially be lifted with DNA metabarcoding. To validate this approach, we studied the ants, springtails and termites of 100 paired soil samples from Barro Colorado Island, Panama. The fauna was extracted with Berlese-Tullgren funnels and then either sorted with traditional taxonomy and known, individual DNA barcodes ("traditional samples") or processed with metabarcoding ("metabarcoding samples"). We detected 49 ant, 37 springtail and 34 termite species with 3.46 million reads of the COI gene, at a mean sequence length of 233 bp. Traditional identification yielded 80, 111 and 15 species of ants, springtails and termites, respectively; 98%, 37% and 100% of these species had a Barcode Index Number (BIN) allowing for direct comparison with metabarcoding. Ants were best surveyed through traditional methods, termites were better detected by metabarcoding, and springtails were equally well detected by both techniques. Species richness was underestimated, and faunal composition was different in metabarcoding samples, mostly because 37% of ant species were not detected. The prevalence of species in metabarcoding samples increased with their abundance in traditional samples, and seasonal shifts in species prevalence and faunal composition were similar between traditional and metabarcoding samples. Probable false positive and negative species records were reasonably low (13-18% of common species). We conclude that metabarcoding of samples extracted with Berlese-Tullgren funnels appear suitable for the long-term monitoring of termites and springtails in tropical rainforests. For ants, metabarcoding schemes should be complemented by additional samples of alates from Malaise or light traps.

• MeSH
• Biodiversity MeSH
• Arthropods * genetics   MeSH
• DNA genetics   MeSH
• Ants * genetics   MeSH
• Isoptera * genetics   MeSH
• Soil MeSH
• DNA Barcoding, Taxonomic methods   MeSH
• Animals MeSH
• Check Tag
• Animals MeSH
• Publication type
• Journal Article MeSH
• Research Support, Non-U.S. Gov't MeSH
• Names of Substances
• DNA MeSH
• Soil MeSH