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

RESEARCH ARTICLE Can DNA-Based Ecosystem Assessments Quantify Species Abundance? Testing Primer Bias and Biomass—Sequence Relationships with an Innovative Metabarcoding Protocol Vasco Elbrecht, Florian Leese* Department of Animal Ecology, Evolution and Biodiversity, Ruhr University Bochum, Universitaetsstrasse 150, D-44801 Bochum, Germany * Abstract OPEN ACCESS Citation: Elbrecht V, Leese F (2015) Can DNABased Ecosystem Assessments Quantify Species Abundance? Testing Primer Bias and Biomass— Sequence Relationships with an Innovative Metabarcoding Protocol. PLoS ONE 10(7): e0130324. doi:10.1371/journal.pone.0130324 Academic Editor: Mehrdad Hajibabaei, University of Guelph, CANADA Received: January 22, 2015 Accepted: May 19, 2015 Published: July 8, 2015 Copyright: © 2015 Elbrecht, Leese. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited. Data Availability Statement: The Illumina sequencing data are available via the Short Read Archive (accession numbers SRS731403 and SRS733820). 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. Funding: This work was supported by a grant of the Kurt Eberhard Bode Foundation to FL. Competing Interests: The authors have declared that no competing interests exist. PLOS ONE | DOI:10.1371/journal.pone.0130324 July 8, 2015 1 / 16 Biomass and Primer Bias in DNA Metabarcoding Introduction A minor proportion of all species on Earth are known [1]. At the same time, anthropogenic impacts have initiated a mass extinction of species in the “Anthropocene” [2], with pervasive and often negative consequences for ecosystem functioning and human well-being [3,4]. To counteract biodiversity loss, fast and reliable tools are needed to assess and monitor biodiversity [5]. Stream biodiversity is particularity affected by anthropogenic degradation [6,7]. Therefore, large-scale monitoring and management programs have been established, for example, the European Union Water Framework Directive and the US Clean Water Act. In these biomonitoring programs, species lists, particularly of benthic invertebrate indicator species, are the central metric to assess the ecological status of freshwater ecosystems. For stream assessments, hundreds of benthic organisms are sampled in a standardised fashion, sorted, identified, and used in standardised analytical work flows (e.g. [8,9]). However, many benthic invertebrate larvae are difficult to identify at the species level, and thus the most practical taxonomic level for the identification of these organisms is often only the genus or family [10]. This is a major concern, as different species within a genus or subfamily can have different ecological preferences and stress tolerances and belong to different functional feeding groups [11,12] see [13] for review. Even worse, frequent identification errors occur and many specimens are not detected in samples [10]; these limitations have direct consequences for the inferred ecosystem assessment metrics [10,14] and thus management decisions. DNA barcoding allows for standardized and accurate species identification [15–18]. As this method is DNA based, it can be used to identify species reliably even when juvenile instars or fragments of organisms are available. For animals, a 658-bp standardized fragment of the mitochondrial gene COI (cytochrome c oxidase subunit 1) is typically used [19]. DNA barcoding requires the establishment of an accurate reference database. For macroinvertebrates, this is best achieved by determining diagnostic characters (usually in male adult specimens [13,20,21]), sequencing the specimens, and depositing the COI sequences in a database such as the BOLD database [22]. In times of declining taxonomic expertise [23,24], these curated and public barcode databases are indispensible to conserve taxonomic knowledge. COI barcoding methods are well established for freshwater organisms [16,17,25] and initial studies have tested their potential for freshwater ecosystem assessments using classical Sangerbased sequencing [14,26]. Stein and co-authors showed that ten of 16 assessment metrics had higher statistical power using DNA barcoding than morphological assessment [14]. However, Sanger sequencing requires that each specimen is processed individually in the laboratory, which is costly and extremely time-consuming for routine community assessments involving hundreds or thousands of specimens per sample. This challenge can be overcome with the aid of next-generation sequencing, which enables the simultaneous analysis of millions of sequences. One next-generation sequencing technique termed metabarcoding (also called community barcoding) utilises the same principle as classical barcoding, yet with much higher throughput, allowing the simultaneous processing of hundreds of samples in a single analysi (...truncated)