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Supplementary material 3 from: Harper L, Watson H, Donnelly R, Hampshire R, Sayer C, Breithaupt T, Hänfling B (2020) Using DNA metabarcoding to investigate diet and niche partitioning in the native European otter (Lutra lutra) and invasive American mink (Neovison vison). Metabarcoding and Metagenomics 4: e56087. https://doi.org/10.3897/mbmg.4.56087
Appendix 3: Predator assignment
Supplementary material 6 from: Harper L, Watson H, Donnelly R, Hampshire R, Sayer C, Breithaupt T, Hänfling B (2020) Using DNA metabarcoding to investigate diet and niche partitioning in the native European otter (Lutra lutra) and invasive American mink (Neovison vison). Metabarcoding and Metagenomics 4: e56087. https://doi.org/10.3897/mbmg.4.56087
Table S1
Supplementary material 1 from: Harper L, Watson H, Donnelly R, Hampshire R, Sayer C, Breithaupt T, Hänfling B (2020) Using DNA metabarcoding to investigate diet and niche partitioning in the native European otter (Lutra lutra) and invasive American mink (Neovison vison). Metabarcoding and Metagenomics 4: e56087. https://doi.org/10.3897/mbmg.4.56087
Appendix 1: Fish inventory
Supplementary material 2 from: Harper L, Watson H, Donnelly R, Hampshire R, Sayer C, Breithaupt T, Hänfling B (2020) Using DNA metabarcoding to investigate diet and niche partitioning in the native European otter (Lutra lutra) and invasive American mink (Neovison vison). Metabarcoding and Metagenomics 4: e56087. https://doi.org/10.3897/mbmg.4.56087
Appendix 2: Methods
Supplementary material 4 from: Harper L, Watson H, Donnelly R, Hampshire R, Sayer C, Breithaupt T, Hänfling B (2020) Using DNA metabarcoding to investigate diet and niche partitioning in the native European otter (Lutra lutra) and invasive American mink (Neovison vison). Metabarcoding and Metagenomics 4: e56087. https://doi.org/10.3897/mbmg.4.56087
Appendix 4: Samples from non-focal mammal predators
Supplementary material 5 from: Harper L, Watson H, Donnelly R, Hampshire R, Sayer C, Breithaupt T, Hänfling B (2020) Using DNA metabarcoding to investigate diet and niche partitioning in the native European otter (Lutra lutra) and invasive American mink (Neovison vison). Metabarcoding and Metagenomics 4: e56087. https://doi.org/10.3897/mbmg.4.56087
Appendix 5: Non-focal mammal diet
Additional information for manuscript entiteld "Host-parasitoid associations in marine planktonic time series: can metabarcoding help reveal them?" (PONE-D-20-17825R1)
<p><strong>Description:</strong></p> <p>This repository contains material to reproduce metabarcoding analyses based on the q-zip pipeline (https://github.com/PyoneerO/qzip). Raw fastq files can be downloaded from https://www.ebi.ac.uk/ena/browser/view/PRJEB37135. The used reference file can be downloaded from https://github.com/pr2database/pr2database/releases/tag/4.11.1. Please select the files created for the classifier implemented in mothur.</p> <p>The dockerfile in this repository can be used to set up the environment which inludes the installation of the needed versions of the needed tools.</p> <p>Twelve different analyses had been conducted. For each analysis one zip file had been created which contains the following files:</p> <p>- q-zip_commands.sh: the shell script to launch the pipeline</p> <p>- q-zip_parameters.txt: pipeline parameter file as input of the shell script</p> <p>- q-zip_workflow.log: log file containing stdout and sdterr</p> <p>- q-zip_seq_of_coms.txt: file containing each command executed during the pipeline run (minimal set of command to reproduce the results)</p> <p>- seq_number_stats.txt: file containing the sequence numbers at each filtering step</p> <p>- OTU tables in tsv and biom format (sequences and taxonomic annotation included)</p> <p>- Meta data map (here only including the raw file names)</p> <p>- swarm sequences in fasta format</p> <p> </p> <p><strong>The following analyses had been conducted:</strong></p> <p>- otu formation at swarm distance 1; default settings for preceding sequence filtering and subsequent taxonomic annotation</p> <p>- otu formation at swarm distance 2; default settings for preceding sequence filtering and subsequent taxonomic annotation</p> <p>- otu formation at swarm distance 3; default settings for preceding sequence filtering and subsequent taxonomic annotation</p> <p>- otu formation at swarm distance 5; default settings for preceding sequence filtering and subsequent taxonomic annotation</p> <p>- otu formation at swarm distance 10; default settings for preceding sequence filtering and subsequent taxonomic annotation</p> <p>- otu formation at swarm distance 1; relaxt settings for preceding sequence filtering and subsequent taxonomic annotation</p> <p>- otu formation at swarm distance 2; relaxt settings for preceding sequence filtering and subsequent taxonomic annotation</p> <p>- otu formation at swarm distance 3; relaxt settings for preceding sequence filtering and subsequent taxonomic annotation</p> <p>- otu formation at swarm distance 1; strict settings for preceding sequence filtering and subsequent taxonomic annotation</p> <p>- otu formation at swarm distance 2; strict settings for preceding sequence filtering and subsequent taxonomic annotation</p> <p>- otu formation at swarm distance 3; strict settings for preceding sequence filtering and subsequent taxonomic annotation</p> <p>- otu formation at swarm distance 1; very strict settings settings for preceding sequence filtering and subsequent taxonomic annotation</p> <p><strong>Settings into more detail:</strong></p> <p>relaxt settings:</p> <ul> <li>trimmomatic filtering: sliding window length of 3 bp - threshold of average quality within of 5</li> <li>vsearch paired-end merging: length of minimum overlap of 25 bp - number of mismatches allowed of 5 bp</li> <li>cutadapt primer removal: percentage primer to sequence overlap of 75% - percentage mismatches allowed of 20%</li> <li>vsearch eeMax filtering: max number of errors expected per sequence of 1 bp</li> <li>minimum sequence length of 300 bp and maximum sequence length of 550 bp</li> <li>mothur classification cutoff (refers to confidence threshold of NBC) of 0.6</li> </ul> <p>default settings (used for the manuscript):</p> <ul> <li>trimmomatic filtering: sliding window length of 3 bp - threshold of average quality within of 8</li> <li>vsearch paired-end merging: length of minimum overlap of 50 bp - number of mismatches allowed of 5</li> <li>cutadapt primer removal: percentage primer to sequence overlap of 90% - percentage mismatches allowed of 10%</li> <li>vsearch eeMax filtering: max number of errors expected per sequence of 0.25 bp</li> <li>minimum sequence length of 300 bp and maximum sequence length of 550 bp</li> <li>mothur classification cutoff (refers to confidence threshold of NBC) of 0.8</li> </ul> <p>strict settings:</p> <ul> <li>trimmomatic filtering: sliding window length of 1 bp - threshold of average quality within of 15</li> <li>vsearch paired-end merging: length of minimum overlap of 50 bp - number of mismatches allowed of 0</li> <li>cutadapt primer removal: percentage primer to sequence overlap of 90% - percentage mismatches allowed of 10%</li> <li>vsearch eeMax filtering: max number of errors expected per sequence of 0.1 bp</li> <li>minimum sequence length of 300 bp and maximum sequence length of 550 bp</li> <li>mothur classification cutoff (refers to confidence threshold of NBC) of 0.9</li> </ul> <ul> </ul> <p>very strict settings:</p> <ul> <li>trimmomatic filtering: sliding window length of 1 bp - threshold of average quality within of 15</li> <li>vsearch paired-end merging: length of minimum overlap of 50 bp - number of mismatches allowed of 0</li> <li>cutadapt primer removal: percentage primer to sequence overlap of 100% - percentage mismatches allowed of 0%</li> <li>vsearch eeMax filtering: max number of errors expected per sequence of 0.1 bp</li> <li>minimum sequence length of 300 bp and maximum sequence length of 550 bp</li> <li>mothur classification cutoff (refers to confidence threshold of NBC) of 0.9</li> </ul>
Supplementary material 2 from: Basset Y, Donoso DA, Hajibabaei M, Wright MTG, Perez KHJ, Lamarre GPA, De León LF, Palacios-Vargas JG, Castaño-Meneses G, Rivera M, Perez F, Bobadilla R, Lopez Y, Ramirez JA, Barrios H (2020) Methodological considerations for monitoring soil/litter arthropods in tropical rainforests using DNA metabarcoding, with a special emphasis on ants, springtails and termites. Metabarcoding and Metagenomics 4: e58572. https://doi.org/10.3897/mbmg.4.58572
Appendix S2
Data from: Comparing the effectiveness of metagenomics and metabarcoding for diet analysis of a leaf-feeding monkey (Pygathrix nemaeus)
Fecal samples are of great value as a non-invasive means to gather information on the genetics, distribution, demography, diet, and parasite infestation of endangered species. Direct shotgun sequencing of fecal DNA could give information on these simultaneously, but this approach is largely untested. Here we use two fecal samples to characterize the diet of two Red-Shanked Doucs Langurs (Pygathrix nemaeus) that were fed a known combination of foliage, fruits, vegetables and cereals. Illumina HiSeq sequencing produced ~70 million paired reads per sample, of which ~10000 (0.014%) and ~44000 (0.066%) respectively corresponded to chloroplast genomes. Sequences were matched against a database of available chloroplast 'barcodes' for angiosperms. The results were compared with 'metabarcoding' using PCR amplification of the P6 loop of trnL. Shotgun sequencing identified 7 and 9 of the likely 16 diet plants, against 6 and 5 plant species identified by metabarcoding. Metabarcoding produced thousands of reads that were consistent with the known diet, but the barcodes were too short to identify several diet plants to genus. Metagenomics could utilize multiple, longer barcodes that combined had greater power of identification, but rare diet items were not recovered. Read numbers for diet species in metagenomic and metabarcoding data were correlated, indicating that both approaches are useful for determining relative sequence abundance. Metagenomic reads were uniformly distributed across the chloroplast genomes; thus if chloroplast genomes were to be used as reference, the precision of identifications and species recovery would improve further. Metagenomics also recovered the host mitochondrial genome and numerous intestinal parasite sequences in addition to generating data useful for characterizing the microbiome.
Data from: Universal and blocking primer mismatches limit the use of high-throughput DNA sequencing for the quantitative metabarcoding of arthropods
The quantification of the biological diversity in environmental samples using high-throughput DNA sequencing is hindered by the PCR bias caused by variable primer–template mismatches of the individual species. In some dietary studies, there is the added problem that samples are enriched with predator DNA, so often a predator-specific blocking oligonucleotide is used to alleviate the problem. However, specific blocking oligonucleotides could coblock nontarget species to some degree. Here, we accurately estimate the extent of the PCR biases induced by universal and blocking primers on a mock community prepared with DNA of twelve species of terrestrial arthropods. We also compare universal and blocking primer biases with those induced by variable annealing temperature and number of PCR cycles. The results show that reads of all species were recovered after PCR enrichment at our control conditions (no blocking oligonucleotide, 45 °C annealing temperature and 40 cycles) and high-throughput sequencing. They also show that the four factors considered biased the final proportions of the species to some degree. Among these factors, the number of primer–template mismatches of each species had a disproportionate effect (up to five orders of magnitude) on the amplification efficiency. In particular, the number of primer–template mismatches explained most of the variation (~3/4) in the amplification efficiency of the species. The effect of blocking oligonucleotide concentration on nontarget species relative abundance was also significant, but less important (below one order of magnitude). Considering the results reported here, the quantitative potential of the technique is limited, and only qualitative results (the species list) are reliable, at least when targeting the barcoding COI region.
Data from: Soil sampling and isolation of extracellular DNA from large amount of starting material suitable for metabarcoding studies
DNA metabarcoding corresponds to the DNA-based identification of multiple species from a single complex and degraded environmental sample. We developed new sampling and extraction protocols suitable for DNA metabarcoding analyses, targeting soil extracellular DNA. The proposed sampling protocol has been designed to reduce as much as possible the influence of the local heterogeneity by processing large amount of soil, resulting from the mixing of many different cores. The DNA extraction is based on the use of saturated phosphate buffer. The sampling and extraction protocols were validated first by analyzing plant DNA from a set of 12 plots corresponding to four plant communities in alpine meadows, and second by conducting pilot experiments on fungi and earthworms. The results of the validation experiments clearly demonstrated that sound biological information can be retrieved when following these sampling and extraction procedures. Such a protocol can be implemented at any time of the year without any preliminary knowledge of specific types of organisms during the sampling. It offers the opportunity to analyze all groups of organisms using a single sampling/extraction procedure and opens the possibility to fully standardize biodiversity surveys.
Data from: Counting with DNA in metabarcoding studies: how should we convert sequence reads to dietary data?
Advances in DNA sequencing technology have revolutionised the field of molecular analysis of trophic interactions and it is now possible to recover counts of food DNA sequences from a wide range of dietary samples. But what do these counts mean? To obtain an accurate estimate of a consumer's diet should we work strictly with datasets summarising frequency of occurrence of different food taxa, or is it possible to use relative number of sequences? Both approaches are applied to obtain semi-quantitative diet summaries, but occurrence data is often promoted as a more conservative and reliable option due to taxa-specific biases in recovery of sequences. We explore representative dietary metabarcoding datasets and point out that diet summaries based on occurrence data often overestimate the importance of food consumed in small quantities (potentially including low-level contaminants) and are sensitive to the count threshold used to define an occurrence. Our simulations indicate that using relative read abundance (RRA) information often provide a more accurate view of population-level diet even with moderate recovery biases incorporated; however, RRA summaries are sensitive to recovery biases impacting common diet taxa. Both approaches are more accurate when the mean number of food taxa in samples is small. The ideas presented here highlight the need to consider all sources of bias and to justify the methods used to interpret count data in dietary metabarcoding studies. We encourage researchers to continue addressing methodological challenges, and acknowledge unanswered questions to help spur future investigations in this rapidly developing area of research.
Data from: Towards accurate species-level metabarcoding of arthropod communities from the tropical forest canopy
Metabarcoding of arthropod communities can be used for assessing species diversity in tropical forests but the methodology requires validation for accurate and repeatable species occurrences in complex mixtures. This study investigates how the composition of ecological samples affects the accuracy of species recovery. Starting with field-collected bulk samples from the tropical canopy, the recovery of specimens was tested for subsets of different body sizes and major taxa, by assembling these subsets into increasingly complex composite pools. After metabarcoding, we track whether richness, diversity and most importantly composition of any size class or taxonomic subset is affected by the presence of other subsets in the mixture. Operational Taxonomic Units (OTUs) greatly exceeded the number of morphospecies in most taxa, even under very stringent sequencing read filtering. There was no significant effect on the recovered OTU richness of small and medium-sized arthropods when metabarcoded alongside larger arthropods, despite substantial biomass differences in the mixture. The recovery of taxonomic subsets was not generally influenced by the presence of other taxa, although with some exceptions likely due to primer mismatches. Considerable compositional variation within size and taxon-based subcommunities were evident resulting in high beta diversity among samples from within a single tree canopy, but this beta diversity was not affected by experimental manipulation. We conclude that OTU recovery in complex arthropod communities, with sufficient sequencing depth and within reasonable size ranges, is not skewed by variable biomass of the constituent species. This could remove the need for time-intensive manual sorting prior to metabarcoding. However, there remains a chance of taxonomic bias, which may be primer-dependent. There will never be a panacea primer; instead, metabarcoding studies should carefully consider whether the aim is broad-scale turnover, in which case these biases may not be important, or species lists, in which case separate PCRs and sequencing might be necessary. OTU number inflation remains an issue in metabarcoding and requires bioinformatic development, particularly in read filtering and OTU clustering, and/or greater use of species-identifying sequences generated outside of bulk sequencing.
Data from: PrimerMiner: an R package for development and in silico validation of DNA metabarcoding primers
1. DNA metabarcoding is a powerful tool to assess biodiversity by amplifying and sequencing a standardized gene marker region. Its success is often limited due to variable binding sites that introduce amplification biases. Thus the development of optimized primers for communities or taxa under study in a certain geographic region and/or ecosystems is of critical importance. However, no tool for obtaining and processing of reference sequence data in bulk that can serve as a backbone for primer design is currently available. 2. We developed the R package PrimerMiner, which batch downloads DNA barcode gene sequences from BOLD and NCBI databases for specified target taxonomic groups and then applies sequence clustering into operational taxonomic units (OTUs) to reduce biases introduced by the different number of available sequences per species. Additionally, PrimerMiner offers functionalities to evaluate primers in silico, which are in our opinion more realistic then the strategy employed in another available software for that purpose, ecoPCR. 3. We used PrimerMiner to download cytochrome c oxidase subunit I (COI) sequences for 15 important freshwater invertebrate groups, relevant for ecosystem assessment. By processing COI markers from both databases, we were able to increase the amount of reference data 249-fold on average, compared to using complete mitochondrial genomes alone. Furthermore, we visualized the generated OTU sequence alignments and describe how to evaluate primers in silico using PrimerMiner. 4. With PrimerMiner we provide a useful tool to obtain relevant sequence data for targeted primer development and evaluation. The OTU based reference alignments generated with PrimerMiner can be used for manual primer design, or processed with bioinformatic tools for primer development.
Data from: Metabarcoding of freshwater invertebrates to detect the effects of a pesticide spill
Biomonitoring underpins the environmental assessment of freshwater ecosystems and guides management and conservation. Current methodology for surveys of (macro)invertebrates uses coarse taxonomic identification where species-level resolution is difficult to obtain. Next-generation sequencing of entire assemblages (metabarcoding) provides a new approach for species detection, but requires further validation. We used metabarcoding of invertebrate assemblages with two fragments of the cox1 "barcode" and partial nuclear ribosomal (SSU) genes, to assess the effects of a pesticide spill in the River Kennet (Southern England). Operational Taxonomic Unit (OTU) recovery was tested under72 parameters (read denoising, filtering, pair merging and clustering). Similar taxonomic profiles were obtained under a broad range of parameters. The SSU marker recovered Platyhelminthes and Nematoda, missed by cox1,while Rotifera were only amplified with cox1. A reference set was created from all available barcode entries for Arthropoda in the BOLD database and clustered into OTUs. The River Kennet metabarcoding produced matches to 207 of these reference OTUs, five times the number of species recognised with morphological monitoring. The increase was due to: greater taxonomic resolution (e.g. splitting a single morphotaxon 'Chironomidae' into 55 named OTUs); splitting of binomial species names into multiple molecular OTUs in species complexes; and the use of a filtration-flotation protocol for extraction of minute specimens (meiofauna). Community analyses revealed strong differences between "impacted" vs. "control" samples, detectable with each gene marker, for each major taxonomic group, and for meio- and macro-faunal samples separately. Thus, highly resolved taxonomic data can be extracted at a fraction of the time and cost of traditional non-molecular methods, opening new avenues for freshwater invertebrate biodiversity monitoring and molecular ecology.
Data from: ITS1 versus ITS2 as DNA metabarcodes for fungi
The nuclear ribosomal Internal Transcribed Spacer ITS region is widely used as a DNA metabarcoding marker to characterize the diversity and composition of fungal communities. In amplicon pyrosequencing studies of fungal diversity, one of the spacers ITS1 or ITS2 of the ITS region is normally used. In this methodological study we evaluate the usability of ITS1 vs. ITS2 as a DNA metabarcoding marker for fungi. We analyse three data sets: two comprising ITS1 and ITS2 sequences of known taxonomic affiliations and a third comprising ITS1 and ITS2 environmental amplicon pyrosequencing data. Clustering analyses of sequences with known taxonomy using the bioinformatics pipeline ClustEx revealed that a 97% similarity cut-off represent a reasonable threshold for estimating the number of known species in the data sets for both ITS1 and ITS2. However, no single threshold value worked well for all fungi at the same time within the curated UNITE database, and we found that the Operational Taxonomic Unit (OTU) concept is not easily translated into the level of species because many species are distributed over several clusters. Clustering analyses of the 134 692 ITS1 and ITS2 pyrosequences using a 97% similarity cut-off revealed a high similarity between the two data sets when it comes to taxonomic coverage. Although some groups are under- or unrepresented in the two data sets due to, e.g. primer mismatches, our results indicate that ITS1 and ITS2 to a large extent yield similar results when used as DNA metabarcodes for fungi.
Data from: MiFish, a set of universal PCR primers for metabarcoding environmental DNA from fishes: detection of more than 230 subtropical marine species
We developed a set of universal PCR primers (MiFish-U/E) for metabarcoding environmental DNA (eDNA) from fishes. Primers were designed using aligned whole mitochondrial genome (mitogenome) sequences from 880 species, supplemented by partial mitogenome sequences from 160 elasmobranchs (sharks and rays). The primers target a hypervariable region of the 12S rRNA gene (163–185 bp), which contains sufficient information to identify fishes to taxonomic family, genus and species except for some closely related congeners. To test versatility of the primers across a diverse range of fishes, we sampled eDNA from four tanks in the Okinawa Churaumi Aquarium with known species compositions, prepared dual-indexed libraries and performed paired-end sequencing of the region using high-throughput next-generation sequencing technologies. Out of the 180 marine fish species contained in the four tanks with reference sequences in a custom database, we detected 168 species (93.3%) distributed across 59 families and 123 genera. These fishes are not only taxonomically diverse, ranging from sharks and rays to higher teleosts, but are also greatly varied in their ecology, including both pelagic and benthic species living in shallow coastal to deep waters. We also sampled natural seawaters around coral reefs near the aquarium and detected 93 fish species using this approach. Of the 93 species, 64 were not detected in the four aquarium tanks, rendering the total number of species detected to 232 (from 70 families and 152 genera). The metabarcoding approach presented here is non-invasive, more efficient, more cost-effective and more sensitive than the traditional survey methods. It has the potential to serve as an alternative (or complementary) tool for biodiversity monitoring that revolutionizes natural resource management and ecological studies of fish communities on larger spatial and temporal scales.
Data from: Comparative authentication of Hypericum perforatum herbal products using DNA metabarcoding, TLC and HPLC-MS
Many herbal products have a long history of use, but there are increasing concerns over product efficacy, safety and quality in the wake of recent cases exposing discrepancies between labeling and constituents. When it comes to St. John's wort (Hypericum perforatum L.) herbal products, there is limited oversight, frequent off-label use and insufficient monitoring of adverse drug reactions. In this study, we use amplicon metabarcoding (AMB) to authenticate 78 H. perforatum herbal products and evaluate its ability to detect substitution compared to standard methods using thin-layer chromatography (TLC) and high performance liquid chromatography coupled with mass spectrometry (HPLC-MS). Hypericum perforatum was detected in 68% of the products using AMB. Furthermore, AMB detected incongruence between constituent species and those listed on the label in all products. Neither TLC nor HPLC-MS could be used to unambiguously identify H. perforatum. They are accurate methods for authenticating presence of the target compounds, but have limited efficiency in detecting infrageneric substitution and do not yield any information on other plant ingredients in the products. Random post-marketing AMB of herbal products by regulatory agencies could raise awareness among consumers of substitution and would provide an incentive to manufacturers to increase quality control from raw ingredients to commercialized products.
Data from: Quantification of mesocosm fish and amphibian species diversity via eDNA metabarcoding
Freshwater fauna are particularly sensitive to environmental change and disturbance. Management agencies frequently use fish and amphibian biodiversity as indicators of ecosystem health and a way to prioritize and assess management strategies. Traditional aquatic bioassessment that relies on capture of organisms via nets, traps and electrofishing gear typically has low detection probabilities for rare species and can injure individuals of protected species. Our objective was to determine whether environmental DNA (eDNA) sampling and metabarcoding analysis can be used to accurately measure species diversity in aquatic assemblages with differing structures. We manipulated the density and relative abundance of eight fish and one amphibian species in replicated 206-L mesocosms. Environmental DNA was filtered from water samples, and six mitochondrial gene fragments were Illumina-sequenced to measure species diversity in each mesocosm. Metabarcoding detected all nine species in all treatment replicates. Additionally, we found a modest, but positive relationship between species abundance and sequencing read abundance. Our results illustrate the potential for eDNA sampling and metabarcoding approaches to improve quantification of aquatic species diversity in natural environments and point the way towards using eDNA metabarcoding as an index of macrofaunal species abundance.
Supplementary material 1 from: Paez-Triana L, Herrera G, Vega L, Garcia-Corredor D, Pulido Medellín MO, Paniz-Mondolfi A, Muñoz M, Ramírez JD (2023) Metagenomic exploration of endosymbionts and pathogens in the tropical lineage of Rhipicephalus sanguineus sensu lato (s.l.) ticks in Colombia. Metabarcoding and Metagenomics 7: e109085. https://doi.org/10.3897/mbmg.7.109085
Geographic locations where samples were collected
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