Environmental DNA metabarcoding of rivers: Not all eDNA is everywhere, and not all the time

AbstractEnvironmental DNA metabarcoding has become a popular tool for the assessment of freshwater biodiversity, but it is largely unclear how sampling time and location influence the assessment of communities. Abiotic factors in rivers can change on small spatial and temporal scale and might greatly influence eDNA metabarcoding results. In this study, we sampled three German rivers at four locations per sampling site: 1. Left river side, surface water 2. Right river side, surface water, 3. Left side, close to the riverbed, 4. Right side, close to the riverbed. For the rivers Ruhr and Möhne, sampling was conducted three times in spring, each sampling one week apart. The Ruhr was again sampled in autumn and the Gillbach was sampled in winter. Sequencing on an Illumina MiSeq with COI primers Bf2/BR2 revealed diverse communities (6493 Operational taxonomic units, OTUs), which largely differed between rivers. Communities changed significantly over time in the Ruhr, but not in the Möhne. Sampling location influenced recovered communities in the Möhne and in the Ruhr in autumn. Our results have important implications for future eDNA studies, which should take into account that not all eDNA in rivers is everywhere and not at all times.

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A new oomycete metabarcoding method using the rps10 gene

10.1101/2021.09.22.460084 ◽

2021 ◽

Author(s):

Zachary S. L. Foster ◽

Felipe E Albornoz ◽

Valerie J Fieland ◽

Meredith M Larsen ◽

Frank Andrew Jones ◽

...

Keyword(s):

Environmental Samples ◽

Illumina Miseq ◽

Taxonomic Resolution ◽

Reference Database ◽

Mock Community ◽

Operational Taxonomic Units ◽

Wide Range ◽

Dna Metabarcoding ◽

Improved Methods

Oomycetes are a group of eukaryotes related to brown algae and diatoms, many of which cause diseases in plants and animals. Improved methods are needed for rapid and accurate characterization of oomycete communities using DNA metabarcoding. We have identified the mitochondrial 40S ribosomal protein S10 gene (rps10) as a locus useful for oomycete metabarcoding and provide primers predicted to amplify all oomycetes based on available reference sequences from a wide range of taxa. We evaluated its utility relative to a popular barcode, the internal transcribed spacer 1 (ITS1), by sequencing environmental samples and a mock community using Illumina MiSeq. Amplified sequence variants (ASVs) and operational taxonomic units (OTUs) were identified per community. Both the sequence and predicted taxonomy of ASVs and OTUs were compared to the known composition of the mock community. Both rps10 and ITS yielded ASVs with sequences matching 21 of the 24 species in the mock community and matching all 24 when allowing for a 1 bp difference. Taxonomic classifications of ASVs included 23 members of the mock community for rps10 and 17 for ITS1. Sequencing results for the environmental samples suggest the proposed rps10 locus results in substantially less amplification of non-target organisms than the ITS1 method. The amplified rps10 region also has higher taxonomic resolution than ITS1, allowing for greater discrimination of closely related species. We present a new website with a searchable rps10 reference database for species identification and all protocols needed for oomycete metabarcoding. The rps10 barcode and methods described herein provide an effective tool for metabarcoding oomycetes using short-read sequencing.

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Random sampling causes the low reproducibility of rare eukaryotic OTUs in Illumina COI metabarcoding

PeerJ ◽

10.7717/peerj.3006 ◽

2017 ◽

Vol 5 ◽

pp. e3006 ◽

Cited By ~ 60

Author(s):

Matthieu Leray ◽

Nancy Knowlton

Keyword(s):

Random Sampling ◽

Marine Invertebrates ◽

Illumina Miseq ◽

Pcr Primers ◽

Biodiversity Monitoring ◽

Analysis Pipeline ◽

Operational Taxonomic Units ◽

Abundance Patterns ◽

Dna Metabarcoding ◽

Data Reproducibility

DNA metabarcoding, the PCR-based profiling of natural communities, is becoming the method of choice for biodiversity monitoring because it circumvents some of the limitations inherent to traditional ecological surveys. However, potential sources of bias that can affect the reproducibility of this method remain to be quantified. The interpretation of differences in patterns of sequence abundance and the ecological relevance of rare sequences remain particularly uncertain. Here we used one artificial mock community to explore the significance of abundance patterns and disentangle the effects of two potential biases on data reproducibility: indexed PCR primers and random sampling during Illumina MiSeq sequencing. We amplified a short fragment of the mitochondrial Cytochrome c Oxidase Subunit I (COI) for a single mock sample containing equimolar amounts of total genomic DNA from 34 marine invertebrates belonging to six phyla. We used seven indexed broad-range primers and sequenced the resulting library on two consecutive Illumina MiSeq runs. The total number of Operational Taxonomic Units (OTUs) was ∼4 times higher than expected based on the composition of the mock sample. Moreover, the total number of reads for the 34 components of the mock sample differed by up to three orders of magnitude. However, 79 out of 86 of the unexpected OTUs were represented by <10 sequences that did not appear consistently across replicates. Our data suggest that random sampling of rare OTUs (e.g., small associated fauna such as parasites) accounted for most of variation in OTU presence–absence, whereas biases associated with indexed PCRs accounted for a larger amount of variation in relative abundance patterns. These results suggest that random sampling during sequencing leads to the low reproducibility of rare OTUs. We suggest that the strategy for handling rare OTUs should depend on the objectives of the study. Systematic removal of rare OTUs may avoid inflating diversity based on commonβdescriptors but will exclude positive records of taxa that are functionally important. Our results further reinforce the need for technical replicates (parallel PCR and sequencing from the same sample) in metabarcoding experimental designs. Data reproducibility should be determined empirically as it will depend upon the sequencing depth, the type of sample, the sequence analysis pipeline, and the number of replicates. Moreover, estimating relative biomasses or abundances based on read counts remains elusive at the OTU level.

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Diversity and substrate-specificity of green algae and other micro-eukaryotes colonizing amphibian clutches in Germany, revealed by DNA metabarcoding

The Science of Nature ◽

10.1007/s00114-021-01734-0 ◽

2021 ◽

Vol 108 (4) ◽

Author(s):

Sten Anslan ◽

Maria Sachs ◽

Lois Rancilhac ◽

Henner Brinkmann ◽

Jörn Petersen ◽

...

Keyword(s):

Green Algae ◽

Phylogenetic Analyses ◽

Sampling Location ◽

Operational Taxonomic Units ◽

Clade B ◽

Unicellular Green Alga ◽

Dna Metabarcoding ◽

Oophila Amblystomatis ◽

Micro Organisms ◽

Rana Dalmatina

AbstractAmphibian clutches are colonized by diverse but poorly studied communities of micro-organisms. One of the most noted ones is the unicellular green alga, Oophila amblystomatis, but the occurrence and role of other micro-organisms in the capsular chamber surrounding amphibian clutches have remained largely unstudied. Here, we undertook a multi-marker DNA metabarcoding study to characterize the community of algae and other micro-eukaryotes associated with agile frog (Rana dalmatina) clutches. Samplings were performed at three small ponds in Germany, from four substrates: water, sediment, tree leaves from the bottom of the pond, and R. dalmatina clutches. Sampling substrate strongly determined the community compositions of algae and other micro-eukaryotes. Therefore, as expected, the frog clutch-associated communities formed clearly distinct clusters. Clutch-associated communities in our study were structured by a plethora of not only green algae, but also diatoms and other ochrophytes. The most abundant operational taxonomic units (OTUs) in clutch samples were taxa from Chlamydomonas, Oophila, but also from Nitzschia and other ochrophytes. Sequences of Oophila “Clade B” were found exclusively in clutches. Based on additional phylogenetic analyses of 18S rDNA and of a matrix of 18 nuclear genes derived from transcriptomes, we confirmed in our samples the existence of two distinct clades of green algae assigned to Oophila in past studies. We hypothesize that “Clade B” algae correspond to the true Oophila, whereas “Clade A” algae are a series of Chlorococcum species that, along with other green algae, ochrophytes and protists, colonize amphibian clutches opportunistically and are often cultured from clutch samples due to their robust growth performance. The clutch-associated communities were subject to filtering by sampling location, suggesting that the taxa colonizing amphibian clutches can drastically differ depending on environmental conditions.

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Illumina iSeq 100 and MiSeq exhibit similar performance in freshwater fish environmental DNA metabarcoding

10.1101/2020.08.04.228080 ◽

2020 ◽

Author(s):

Ryohei Nakao ◽

Ryutei Inui ◽

Yoshihisa Akamatsu ◽

Masuji Goto ◽

Hideyuki Doi ◽

...

Keyword(s):

Environmental Samples ◽

Environmental Dna ◽

Illumina Miseq ◽

Common Species ◽

Species Numbers ◽

Amplicon Library ◽

Dna Metabarcoding ◽

Biomonitoring Tool ◽

The Common ◽

Conventional Methods

AbstractEnvironmental DNA (eDNA) analysis is a method of detecting DNA from environmental samples, and it is used as a biomonitoring tool. In recent studies, Illumina MiSeq has been the most extensively used tool for eDNA metabarcoding, one of the eDNA analysis approaches. The Illumina iSeq 100 (hereafter, iSeq) is one of the numerous high-throughput sequencers (HTS). It has a relatively simple workflow and is potentially more affordable than other sequencers for deployment in HTS environments. However, to date, only a few studies have adopted iSeq, and its utility in eDNA metabarcoding has still not been investigated comprehensively. In the present study, we applied fish eDNA metabarcoding to river and lake environmental samples using iSeq and MiSeq approaches. We also assessed differences in fish species detectability among iSeq, MiSeq, and conventional approaches. Twenty-seven river and 13 lake samples were amplified using MiFish primers and sequenced with iSeq and MiSeq, respectively. The iSeq and MiSeq metabarcoding achieved high detectability for fish taxa in the ecosystems. Species numbers and compositions in each river detected using iSeq were almost consistent with those of MiSeq, indicating detectability of both techniques was comparable. The comparison of the species compositions of the two HTSs with those of conventional methods showed that the common species between each HTS and the conventional methods were exactly similar. According to the results, if the same amplicon library were used for sequencing, there would be negligible detectability differences between iSeq and MiSeq based on eDNA metabarcoding.

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Illumina iSeq 100 and MiSeq exhibit similar performance in freshwater fish environmental DNA metabarcoding

Scientific Reports ◽

10.1038/s41598-021-95360-5 ◽

2021 ◽

Vol 11 (1) ◽

Author(s):

Ryohei Nakao ◽

Ryutei Inui ◽

Yoshihisa Akamatsu ◽

Masuji Goto ◽

Hideyuki Doi ◽

...

Keyword(s):

Environmental Dna ◽

Illumina Miseq ◽

Lake Ecosystems ◽

Similar Performance ◽

Amplicon Library ◽

Significant Difference ◽

Dna Metabarcoding ◽

Biomonitoring Tool ◽

The Difference ◽

Sequence Quality

AbstractEnvironmental DNA (eDNA) analysis is a method of detecting DNA from environmental samples and is used as a biomonitoring tool. In recent studies, Illumina MiSeq has been the most extensively used tool for eDNA metabarcoding. The Illumina iSeq 100 (hereafter, iSeq), one of the high-throughput sequencers (HTS), has a relatively simple workflow and is potentially more affordable than other HTS. However, its utility in eDNA metabarcoding has still not been investigated. In the present study, we applied fish eDNA metabarcoding to 40 water samples from river and lake ecosystems to assess the difference in species detectability and composition between iSeq and MiSeq. To check differences in sequence quality and errors, we also assessed differences in read changes between the two HTS. There were similar sequence qualities between iSeq and MiSeq. Significant difference was observed in the number of species between two HTS, but no difference was observed in species composition between the two HTS. Additionally, the species compositions in common with the conventional method were the same between the two HTS. According to the results, using the same amplicon library for sequencing, two HTS would exhibit a similar performance of fish species detection using eDNA metabarcoding.

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Illumina MiSeq Analysis and Comparison of Freshwater Microalgal Communities on Ulleungdo and Dokdo Islands

Polish Journal of Microbiology ◽

10.33073/pjm-2019-053 ◽

2019 ◽

Vol 68 (4) ◽

pp. 527-539

Author(s):

HYUN-SIK YUN ◽

YOUNG-SAENG KIM ◽

HO-SUNG YOON

Keyword(s):

Species Richness ◽

Illumina Miseq ◽

Taxonomic Composition ◽

Eastern Coast ◽

Sampling Location ◽

Composition Analysis ◽

Operational Taxonomic Units ◽

Oceanic Climate ◽

Eukaryotic Microorganisms ◽

Volcanic Islands

Ulleungdo and Dokdo are volcanic islands with an oceanic climate located off the eastern coast of South Korea. In the present study, we used barcoded Illumina MiSeq to analyze eukaryotic microalgal genera collected from Seonginbong, the highest peak on Ulleungdo, and from groundwater sites on Dongdo and Seodo Islands, which are part of Dokdo. Species richness was significantly greater in the Seonginbong samples than in the Dongdo and Seodo samples, with 834 operational taxonomic units (OTUs) identified from Seonginbong compared with 203 OTUs and 182 OTUs from Dongdo and Seodo, respectively. Taxonomic composition analysis was also used to identify the dominant microalgal phyla at each of the three sites, with Chlorophyta (green algae) the most abundant phyla on Seonginbong and Dongdo, and Bacillariophyta (diatoms) the most abundant on Seodo. These findings suggest that differences in the abundances of Chlorophyta and Bacillariophyta species in the Seonginbong, Dongdo, and Seodo samples are due to variations in species richness and freshwater resources at each sampling location. To the best of our knowledge, this is the first report to detail freshwater microalgal communities on Ulleungdo and Dokdo. As such, the number of species identified in the Seonginbong, Dongdo, and Seodo samples might be an indicator of the ecological differences among these sites and varying characteristics of their microbial communities. Information regarding the microalgal communities also provides a basis for understanding the ecological interactions between microalgae species and other eukaryotic microorganisms.

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COMPARATIVE STUDY BETWEEN FISH COLLECTION BY NATIONAL CENSUS ON RIVER ENVIRONMENT AND ENVIRONMENTAL DNA METABARCODING

Journal of Japan Society of Civil Engineers Ser B1 (Hydraulic Engineering) ◽

10.2208/jscejhe.74.5_i_415 ◽

2018 ◽

Vol 74 (5) ◽

pp. I_415-I_420 ◽

Cited By ~ 1

Author(s):

Yoshihisa AKAMATSU ◽

Takayoshi TSUZUKI ◽

Ryota YOKOYAMA ◽

Yayoi FUNAHASHI ◽

Munehiro OHTA ◽

...

Keyword(s):

Comparative Study ◽

Environmental Dna ◽

Dna Metabarcoding ◽

Fish Collection

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Environmental DNA for functional diversity

10.1093/oso/9780198767220.003.0010 ◽

2018 ◽

Cited By ~ 1

Author(s):

Pierre Taberlet ◽

Aurélie Bonin ◽

Lucie Zinger ◽

Eric Coissac

Keyword(s):

Functional Groups ◽

Functional Diversity ◽

Environmental Dna ◽

Soil Organisms ◽

Meaningful Information ◽

Dna Metabarcoding ◽

Pros And Cons ◽

Target Community

Chapter 10 “Environmental DNA for functional diversity” discusses the potential of environmental DNA to assess functional diversity. It first focuses on DNA metabarcoding and discusses the extent to which this approach can be used and/or optimized to retrieve meaningful information on the functions of the target community. This knowledge usually involves coarsely defined functional groups (e.g., woody, leguminous, graminoid plants; shredders or decomposer soil organisms; pathogenicity or decomposition role of certain microorganisms). Chapter 10 then introduces metagenomics and metatranscriptomics approaches, their advantages, but also the challenges and solutions to appropriately sampling, sequencing these complex DNA/RNA populations. Chapter 10 finally presents several strategies and software to analyze metagenomes/metatranscriptomes, and discusses their pros and cons.

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Environmental DNA

10.1093/oso/9780198767220.001.0001 ◽

2018 ◽

Cited By ~ 137

Author(s):

Pierre Taberlet ◽

Aurélie Bonin ◽

Lucie Zinger ◽

Eric Coissac

Keyword(s):

Graduate Students ◽

Feeding Habits ◽

Environmental Dna ◽

Research Field ◽

Background Information ◽

Ecological Processes ◽

Biodiversity Research ◽

Dna Metabarcoding ◽

Standard Information

Environmental DNA (eDNA), i.e. DNA released in the environment by any living form, represents a formidable opportunity to gather high-throughput and standard information on the distribution or feeding habits of species. It has therefore great potential for applications in ecology and biodiversity management. However, this research field is fast-moving, involves different areas of expertise and currently lacks standard approaches, which calls for an up-to-date and comprehensive synthesis. Environmental DNA for biodiversity research and monitoring covers current methods based on eDNA, with a particular focus on “eDNA metabarcoding”. Intended for scientists and managers, it provides the background information to allow the design of sound experiments. It revisits all steps necessary to produce high-quality metabarcoding data such as sampling, metabarcode design, optimization of PCR and sequencing protocols, as well as analysis of large sequencing datasets. All these different steps are presented by discussing the potential and current challenges of eDNA-based approaches to infer parameters on biodiversity or ecological processes. The last chapters of this book review how DNA metabarcoding has been used so far to unravel novel patterns of diversity in space and time, to detect particular species, and to answer new ecological questions in various ecosystems and for various organisms. Environmental DNA for biodiversity research and monitoring constitutes an essential reading for all graduate students, researchers and practitioners who do not have a strong background in molecular genetics and who are willing to use eDNA approaches in ecology and biomonitoring.

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