Can DNA-Based Ecosystem Assessments Quantify Species Abundance? Testing Primer Bias and Biomass—Sequence Relationships with an Innovative Metabarcoding Protocol

By Vasco Elbrecht, Florian Leese. PLoS ONE, 2015

698 citations recorded by the source corpus.

Metabarcoding is an emerging genetic tool to rapidly assess biodiversity in ecosystems. It involves high-throughput sequencing of a standard gene from an environmental sample and comparison to a reference database. However, no consensus has emerged regarding laboratory pipelines to screen species diversity and infer species abundances from environmental samples. In particular, the effect of primer bias and the detection limit for specimens with a low biomass has not been systematically examined, when processing samples in bulk. We developed and tested a DNA metabarcoding protocol that utilises the standard cytochrome c oxidase subunit I (COI) barcoding fragment to detect freshwater macroinvertebrate taxa. DNA was extracted in bulk, amplified in a single PCR step, and purified, and the libraries were directly sequenced in two independent MiSeq runs (300-bp paired-end reads). Specifically, we assessed the influence of specimen biomass on sequence read abundance by sequencing 31 specimens of a stonefly species with known haplotypes spanning three orders of magnitude in biomass (experiment I). Then, we tested the recovery of 52 different freshwater invertebrate taxa of similar biomass using the same standard barcoding primers (experiment II). Each experiment was replicated ten times to maximise statistical power. The results of both experiments were consistent across replicates. We found a distinct positive correlation between species biomass and resulting numbers of MiSeq reads. Furthermore, we reliably recovered 83% of the 52 taxa used to test primer bias. However, sequence abundance varied by four orders of magnitudes between taxa despite the use of similar amounts of biomass. Our metabarcoding approach yielded reliable results for high-throughput assessments. However, the results indicated that primer efficiency is highly species-specific, which would prevent straightforward assessments of species abundance and biomass in a sample. Thus, PCR-based metabarcoding assessments of biodiversity should rely on presence-absence metrics.

Subfields: Ecology, Molecular Biology

View Paper: https://www.semanticscholar.org/paper/5b5925709b20821df1f956c4c737e5fadb1e8b43

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

In Molecular Biology

Citations in the corpus

Methods for the extraction, storage, amplification and sequencing of DNA from environmental samples (2018, background): “Virome: The genetic material from all the viruses associated with a host or environment. specific taxa (Elbrecht & Leese 2015; Aylagas et al. 2016) or sample media (Drummond et al. 2015; Klymus et al. 2107).”
Environmental DNA metabarcoding: Transforming how we survey animal and plant communities (2017, methodology): “Selected strategies include filtering based on a lower Phred score cut-off, usually set at least above 20 or 30 (Bista (Continues) et al., 2017; Elbrecht & Leese, 2015; H€anfling et al., 2016).”
Avoiding quantification bias in metabarcoding: Application of a cell biovolume correction factor in diatom molecular biomonitoring (2017, background): “…density and species biomass are major biases likely to affect DNA metabarcoding quantification of multicellular organisms like macroinvertebrates (Elbrecht & Leese, 2015) or fish (Evans et al., 2016), diatoms are unicellular organisms for which gene copy number is mainly affected by the number…”
Metabarcoding of lake benthic diatoms: from structure assemblages to ecological assessment (2018, methodology): “…choice of a targeted gene for DNA barcode (Kermarrec et al., 2013; Valentini et al., 2016), the choice of the set of primers for DNA metabarcoding (Elbrecht & Leese 2015), the choice of the PCR amplification protocol (Kebschull & Zador, 2015), the choice of the sequencing technology (Quail et…”
Application of high-throughput sequencing (HTS) metabarcoding to diatom biomonitoring: Do DNA extraction methods matter? (2017, background): “…amplification efficiency that may differ among species; DNA sequencing errors and bioinformatics filtering that may affect DNA sequence reliability (Jeon et al. 2008, Amend et al. 2010, Bragg et al. 2013, Weber and Pawlowski 2013, Deiner et al. 2015, Elbrecht and Leese 2015, Schmidt et al. 2015).”
Comparing local‐ and regional‐scale estimations of the diversity of stream fish using eDNA metabarcoding and conventional observation methods (2018, methodology): “In 441 addition, we might reduce the effect of primer-bias (i.e., the variation in amplification 442 efficiency among species) by using multiple universal primers (Elbrecht & Leese, 2015; 443 Vallentini et al., 2016).”
Reference databases, primer choice, and assay sensitivity for environmental metabarcoding: Lessons learnt from a re‐evaluation of an eDNA fish assessment in the Volga headwaters (2020, background): “…sequence variation in the primer annealing sites among individual species, leading to higher efficiency of the PCR reaction for certain species in a mixed DNA template, while other species might get amplified less or not at all (Bylemans, Gleeson, Hardy, & Furlan, 2018; Elbrecht & Leese, 2015).”
Benchmarking DNA Metabarcoding for Biodiversity-Based Monitoring and Assessment (2016, background): “The abovementioned biases inherent to PCR-based analyses can lead to greater recovery of sequences of some species and the exclusion of others (Elbrecht and Leese, 2015; Piñol et al., 2015).”
Deep learning and computer vision will transform entomology (2020, background): “Molecular techniques such as DNA barcoding and metabarcoding will likely become 73 valuable tools for future insect monitoring based on field collected samples (10, 11), but at the 74 moment high-throughput methods cannot provide reliable abundance estimates (12, 13) leaving a 75 critical need for o”
DNA Sequencing as a Tool to Monitor Marine Ecological Status (2017, methodology): “Some studies report adequate estimates of relative abundance (Aylagas et al., 2014, 2016; Elbrecht and Leese, 2015; Tan et al., 2015; Thomsen and Willerslev, 2015) even though read abundance does not necessarily provide a direct correlation to organism abundance because of issues that include…”
Validation and Development of COI Metabarcoding Primers for Freshwater Macroinvertebrate Bioassessment (2017, positive): “Amplification success of the BF/BR primers was evaluated using 10 mock communities, each containing a set of 52 different freshwater invertebrates also used in previous studies (Elbrecht and Leese, 2015; Elbrecht et al., 2016).”
Counting with DNA in metabarcoding studies: How should we convert sequence reads to dietary data? (2018, background): “Many studies have sequenced DNA from insect mock communities; however, rather than considering if read counts are proxies for input biomass, the focus of these studies has generally been to test if taxa can be detected (Alberdi et al. 2017; Clarke et al. 2014; Elbrecht & Leese 2015; Yu et al. 2012).”
Temporal and spatial variation in distribution of fish environmental DNA in England’s largest lake (2018, background): “…which the number of sequence reads for a particular species can be heavily biased by differential primer binding (primer bias, Deiner et al., 2017; Elbrecht & Leese, 2015) and/or subsampling of species during library preparation (Leray & Knowlton, 2015; Shelton et al., 2016; Deiner et al., 2017).”