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

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.

[1]  S. Adamowicz,et al.  Ephemeroptera, Plecoptera, and Trichoptera fauna of Churchill (Manitoba, Canada): insights into biodiversity patterns from DNA barcoding , 2010, Journal of the North American Benthological Society.

[2]  S. Weisberg,et al.  Performance of Two Southern California Benthic Community Condition Indices Using Species Abundance and Presence-Only Data: Relevance to DNA Barcoding , 2012, PloS one.

[3]  Qing Yang,et al.  Ultra-deep sequencing enables high-fidelity recovery of biodiversity for bulk arthropod samples without PCR amplification , 2013, GigaScience.

[4]  W. Hilsenhoff An Introduction to the Aquatic Insects of North America , 1997 .

[5]  G. Daily,et al.  Biodiversity loss and its impact on humanity , 2012, Nature.

[6]  R. Naiman,et al.  Freshwater biodiversity: importance, threats, status and conservation challenges , 2006, Biological reviews of the Cambridge Philosophical Society.

[7]  P. Taberlet,et al.  Environmental DNA , 2012, Molecular ecology.

[8]  Martin F. Polz,et al.  Bias in Template-to-Product Ratios in Multitemplate PCR , 1998, Applied and Environmental Microbiology.

[9]  R Core Team,et al.  R: A language and environment for statistical computing. , 2014 .

[10]  Millenium Ecosystem Assessment Ecosystems and human well-being: synthesis , 2005 .

[11]  P. Taberlet,et al.  Towards next‐generation biodiversity assessment using DNA metabarcoding , 2012, Molecular ecology.

[12]  P. Hebert,et al.  Barcoding animal life: cytochrome c oxidase subunit 1 divergences among closely related species , 2003, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[13]  François Pompanon,et al.  DNA metabarcoding and the cytochrome c oxidase subunit I marker: not a perfect match , 2014, Biology Letters.

[14]  D. Baird,et al.  Environmental Barcoding: A Next-Generation Sequencing Approach for Biomonitoring Applications Using River Benthos , 2011, PloS one.

[15]  F. Chapin,et al.  A safe operating space for humanity , 2009, Nature.

[16]  William A. Walters,et al.  QIIME allows analysis of high-throughput community sequencing data , 2010, Nature Methods.

[17]  J. Piñol,et al.  Universal and blocking primer mismatches limit the use of high‐throughput DNA sequencing for the quantitative metabarcoding of arthropods , 2015, Molecular ecology resources.

[18]  Mehrdad Hajibabaei,et al.  Simultaneous assessment of the macrobiome and microbiome in a bulk sample of tropical arthropods through DNA metasystematics , 2014, Proceedings of the National Academy of Sciences.

[19]  P. Hebert,et al.  bold: The Barcode of Life Data System (http://www.barcodinglife.org) , 2007, Molecular ecology notes.

[20]  K. Kjer,et al.  Associating larvae and adults of Chinese Hydropsychidae caddisflies (Insecta:Trichoptera) using DNA sequences , 2007, Journal of the North American Benthological Society.

[21]  H. Lumbsch,et al.  Grazers, shredders and filtering carnivores--the evolution of feeding ecology in Drusinae (Trichoptera: Limnephilidae): insights from a molecular phylogeny. , 2008, Molecular phylogenetics and evolution.

[22]  P. Miller,et al.  Cryptic Biodiversity in Streams: A Comparison of Macroinvertebrate Communities Based on Morphological and DNA Barcode Identifications , 2014, Freshwater Science.

[23]  P. Mieczkowski,et al.  Practical innovations for high-throughput amplicon sequencing , 2013, Nature Methods.

[24]  Robert C. Edgar,et al.  UPARSE: highly accurate OTU sequences from microbial amplicon reads , 2013, Nature Methods.

[25]  S. Ratnasingham,et al.  BOLD : The Barcode of Life Data System (www.barcodinglife.org) , 2007 .

[26]  B. W. Sweeney,et al.  Can DNA barcodes of stream macroinvertebrates improve descriptions of community structure and water quality? , 2011, Journal of the North American Benthological Society.

[27]  R. Freckleton,et al.  Declines in the numbers of amateur and professional taxonomists: implications for conservation , 2002 .

[28]  Douglas W. Yu,et al.  Environmental DNA for wildlife biology and biodiversity monitoring. , 2014, Trends in ecology & evolution.

[29]  Á. Borja,et al.  Environmental Status Assessment Using DNA Metabarcoding: Towards a Genetics Based Marine Biotic Index (gAMBI) , 2014, PloS one.

[30]  W. Reid,et al.  Millennium Ecosystem Assessment , 2005 .

[31]  Kevin J. Gaston Biodiversity : loss , 1995 .

[32]  P. Sunnucks,et al.  Numerous transposed sequences of mitochondrial cytochrome oxidase I-II in aphids of the genus Sitobion (Hemiptera: Aphididae). , 1996, Molecular biology and evolution.

[33]  P. McIntyre,et al.  Global threats to human water security and river biodiversity , 2010, Nature.

[34]  Cameron S. Osborne,et al.  Large Scale Loss of Data in Low-Diversity Illumina Sequencing Libraries Can Be Recovered by Deferred Cluster Calling , 2011, PloS one.

[35]  R. Tollrian,et al.  Genetic Diversity and Dispersal Potential of the Stonefly Dinocras cephalotes in a Central European Low Mountain Range , 2014, Freshwater Science.

[36]  Douglas W. Yu,et al.  Biodiversity soup: metabarcoding of arthropods for rapid biodiversity assessment and biomonitoring , 2012 .

[37]  P. Hebert,et al.  bold: The Barcode of Life Data System (http://www.barcodinglife.org) , 2007, Molecular ecology notes.

[38]  Leon Metzeling,et al.  Environmental monitoring using next generation sequencing: rapid identification of macroinvertebrate bioindicator species , 2013, Frontiers in Zoology.

[39]  T. Poisot,et al.  High-Throughput Sequencing: A Roadmap Toward Community Ecology , 2013, Ecology and evolution.

[40]  U. John,et al.  The complete mitochondrial genome of the stonefly Dinocras cephalotes (Plecoptera, Perlidae) , 2015, Mitochondrial DNA.

[41]  T. Backeljau,et al.  Dispersal and gene flow in free-living marine nematodes , 2013, Frontiers in Zoology.

[42]  王丽华,et al.  国际生命条形码计划—DNA Barcoding , 2009 .

[43]  Jeremy R. deWaard,et al.  Biological identifications through DNA barcodes , 2003, Proceedings of the Royal Society of London. Series B: Biological Sciences.

[44]  J. Flannagan An Introduction to the Aquatic Insects of North America. , 1979 .

[45]  R. Vrijenhoek,et al.  DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. , 1994, Molecular marine biology and biotechnology.

[46]  Mark Blaxter,et al.  Molecular systematics: Counting angels with DNA , 2003, Nature.

[47]  F. Altermatt,et al.  Utility of Environmental DNA for Monitoring Rare and Indicator Macroinvertebrate Species , 2014, Freshwater Science.

[48]  C. Hawkins,et al.  Assessing Macroinvertebrate Biodiversity in Freshwater Ecosystems: Advances and Challenges in DNA-based Approaches , 2010, The Quarterly Review of Biology.

[49]  Marcel Martin Cutadapt removes adapter sequences from high-throughput sequencing reads , 2011 .

[50]  Eric D. Stein,et al.  Is DNA Barcoding Actually Cheaper and Faster than Traditional Morphological Methods: Results from a Survey of Freshwater Bioassessment Efforts in the United States? , 2014, PloS one.

[51]  Douglas W. Yu,et al.  Reliable, verifiable and efficient monitoring of biodiversity via metabarcoding. , 2013, Ecology letters.

[52]  P. Taberlet,et al.  Who is eating what: diet assessment using next generation sequencing , 2012, Molecular ecology.

[53]  Ning Ma,et al.  BLAST+: architecture and applications , 2009, BMC Bioinformatics.

[54]  Gernot Glöckner,et al.  Metabarcoding vs. morphological identification to assess diatom diversity in environmental studies , 2015, Molecular ecology resources.

[55]  M. Grube,et al.  Taxonomy in a Changing World: Seeking Solutions for a Science in Crisis , 2007 .

[56]  F. Chris JonesF.C. Jones,et al.  Taxonomic sufficiency: The influence of taxonomic resolution on freshwater bioassessments using benthic macroinvertebrates , 2008 .

[57]  P. Hebert,et al.  Females do count: Documenting Chironomidae (Diptera) species diversity using DNA barcoding , 2010, Organisms Diversity & Evolution.

[58]  J. Landry,et al.  A universal DNA mini-barcode for biodiversity analysis , 2008, BMC Genomics.

[59]  M. Kenney,et al.  Benthic macroinvertebrates as indicators of water quality: The intersection of science and policy , 2009 .

[60]  L. Weyrich,et al.  Environmental metabarcodes for insects: in silico PCR reveals potential for taxonomic bias , 2014, Molecular ecology resources.

[61]  Martin Hartmann,et al.  Introducing mothur: Open-Source, Platform-Independent, Community-Supported Software for Describing and Comparing Microbial Communities , 2009, Applied and Environmental Microbiology.

[62]  Peter Haase,et al.  First audit of macroinvertebrate samples from an EU Water Framework Directive monitoring program: human error greatly lowers precision of assessment results , 2010, Journal of the North American Benthological Society.