Assessing strengths and weaknesses of DNA metabarcoding‐based macroinvertebrate identification for routine stream monitoring

Summary DNA metabarcoding holds great promise for the assessment of macroinvertebrates in stream ecosystems. However, few large-scale studies have compared the performance of DNA metabarcoding with that of routine morphological identification. We performed metabarcoding using four primer sets on macroinvertebrate samples from 18 stream sites across Finland. The samples were collected in 2013 and identified based on morphology as part of a Finnish stream monitoring program. Specimens were morphologically classified, following standardised protocols, to the lowest taxonomic level for which identification was feasible in the routine national monitoring. DNA metabarcoding identified more than twice the number of taxa than the morphology-based protocol, and also yielded a higher taxonomic resolution. For each sample, we detected more taxa by metabarcoding than by the morphological method, and all four primer sets exhibited comparably good performance. Sequence read abundance and the number of specimens per taxon (a proxy for biomass) were significantly correlated in each sample, although the adjusted R2 values were low. With a few exceptions, the ecological status assessment metrics calculated from morphological and DNA metabarcoding datasets were similar. Given the recent reduction in sequencing costs, metabarcoding is currently approximately as expensive as morphology-based identification. Using samples obtained in the field, we demonstrated that DNA metabarcoding can achieve comparable assessment results to current protocols relying on morphological identification. Thus, metabarcoding represents a feasible and reliable method to identify macroinvertebrates in stream bioassessment, and offers powerful advantage over morphological identification in providing identification for taxonomic groups that are unfeasible to identify in routine protocols. To unlock the full potential of DNA metabarcoding for ecosystem assessment, however, it will be necessary to address key problems with current laboratory protocols and reference databases.

[1]  Andrea Lanzini,et al.  Enhancing the Energy Efficiency of Wastewater Treatment Plants through Co-digestion and Fuel Cell Systems , 2017, Front. Environ. Sci..

[2]  Jesse A. Port,et al.  Indexed PCR Primers Induce Template-Specific Bias in Large-Scale DNA Sequencing Studies , 2016, PloS one.

[3]  Bernard W. Sweeney,et al.  Applying DNA barcoding in benthology: the state of the science , 2011, Journal of the North American Benthological Society.

[4]  Naiara Rodríguez-Ezpeleta,et al.  Benchmarking DNA Metabarcoding for Biodiversity-Based Monitoring and Assessment , 2016, Front. Mar. Sci..

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

[6]  Mehrdad Hajibabaei,et al.  Assessing biodiversity of a freshwater benthic macroinvertebrate community through non-destructive environmental barcoding of DNA from preservative ethanol , 2012, BMC Ecology.

[7]  P. Usseglio-Polatera,et al.  A new macroinvertebrate-based multimetric index (I2M2) to evaluate ecological quality of French wadeable streams fulfilling the WFD demands: A taxonomical and trait approach , 2012 .

[8]  V. Resh,et al.  Water quality monitoring and aquatic organisms: the importance of species identification. , 1975, Journal - Water Pollution Control Federation.

[9]  Javier R. Viguri,et al.  DNAqua-Net: Developing new genetic tools for bioassessment and monitoring of aquatic ecosystems in Europe , 2016 .

[10]  Tae-Soo Chon,et al.  Stream biomonitoring using macroinvertebrates around the globe: a comparison of large-scale programs , 2014, Environmental Monitoring and Assessment.

[11]  R. W. Bode,et al.  Percent Model Affinity: A New Measure of Macroinvertebrate Community Composition , 1992, Journal of the North American Benthological Society.

[12]  D. Hering,et al.  www.freshwaterecology.info – An online tool that unifies, standardises and codifies more than 20,000 European freshwater organisms and their ecological preferences ☆ , 2015 .

[13]  Mehrdad Hajibabaei,et al.  Large-Scale Biomonitoring of Remote and Threatened Ecosystems via High-Throughput Sequencing , 2015, PloS one.

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

[15]  Philippe Esling,et al.  High-throughput sequencing and morphology perform equally well for benthic monitoring of marine ecosystems , 2015, Scientific Reports.

[16]  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.

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

[18]  Á. Borja,et al.  Marine Sediment Sample Pre-processing for Macroinvertebrates Metabarcoding: Mechanical Enrichment and Homogenization , 2016, Front. Mar. Sci..

[19]  B. Deagle,et al.  Effect of marker choice and thermal cycling protocol on zooplankton DNA metabarcoding studies , 2017, Ecology and evolution.

[20]  PrimerMiner: an r package for development and in silico validation of DNA metabarcoding primers , 2017 .

[21]  Matthew A. Barnes,et al.  The ecology of environmental DNA and implications for conservation genetics , 2016, Conservation Genetics.

[22]  Vasco Elbrecht,et al.  Can DNA-Based Ecosystem Assessments Quantify Species Abundance? Testing Primer Bias and Biomass—Sequence Relationships with an Innovative Metabarcoding Protocol , 2015, PloS one.

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

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

[25]  Kristine Bohmann,et al.  Tag jumps illuminated – reducing sequence‐to‐sample misidentifications in metabarcoding studies , 2015, Molecular ecology resources.

[26]  R. Tollrian,et al.  Multiple-stressor effects on stream invertebrates: DNA barcoding reveals contrasting responses of cryptic mayfly species , 2016 .

[27]  P. Hernandez,et al.  Plant and animal endemism in the eastern Andean slope: challenges to conservation , 2012, BMC Ecology.

[28]  E. Gaino,et al.  Geographical and seasonal evidence of cryptic diversity in the Baetis rhodani complex (Ephemeroptera, Baetidae) revealed by means of DNA taxonomy , 2011, Hydrobiologia.

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

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

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

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

[33]  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.

[34]  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.

[35]  P. Miller,et al.  Does DNA Barcoding Improve Performance of Traditional Stream Bioassessment Metrics? , 2013, Freshwater Science.

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

[37]  Anne Courrat,et al.  Three hundred ways to assess Europe's surface waters: An almost complete overview of biological methods to implement the Water Framework Directive , 2012 .

[38]  F. Leese,et al.  Validation and development of freshwater invertebrate metabarcoding COI primers for Environmental Impact Assessment , 2016 .

[39]  K. Meissner,et al.  Title : Assessing strengths and weaknesses of DNA metabarcoding based 1 macroinvertebrate identification for routine stream monitoring , 2017 .

[40]  P. Miller,et al.  Evaluating Ethanol-based Sample Preservation to Facilitate Use of DNA Barcoding in Routine Freshwater Biomonitoring Programs Using Benthic Macroinvertebrates , 2013, PloS one.

[41]  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.

[42]  M. Bruford,et al.  Molecular systematics and phylogeography of the cryptic species complex Baetis rhodani (Ephemeroptera, Baetidae). , 2006, Molecular phylogenetics and evolution.

[43]  D. Hering,et al.  Assessing streams in Germany with benthic invertebrates: development of a practical standardised protocol for macroinvertebrate sampling and sorting , 2004 .

[44]  Robert C. Edgar,et al.  Error filtering, pair assembly and error correction for next-generation sequencing reads , 2015, Bioinform..

[45]  Mehrdad Hajibabaei,et al.  Biomonitoring 2.0: a new paradigm in ecosystem assessment made possible by next‐generation DNA sequencing , 2012, Molecular ecology.

[46]  H. Hämäläinen,et al.  A Priori Typology-Based Prediction of Benthic Macroinvertebrate Fauna for Ecological Classification of Rivers , 2008, Environmental management.

[47]  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.

[48]  S. Narum,et al.  Technology in the field of molecular ecology continues to advance rapidly. Introduction. , 2015, Molecular ecology resources.

[49]  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.

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

[51]  Sujeevan Ratnasingham,et al.  A DNA-Based Registry for All Animal Species: The Barcode Index Number (BIN) System , 2013, PloS one.

[52]  Xavier Pochon,et al.  Targeted gene enrichment and high‐throughput sequencing for environmental biomonitoring: a case study using freshwater macroinvertebrates , 2016, Molecular ecology resources.

[53]  B. Deagle,et al.  Quantitative DNA metabarcoding: improved estimates of species proportional biomass using correction factors derived from control material , 2016, Molecular ecology resources.

[54]  Henrik Nygård,et al.  Proficiency Test 04/2016 - Taxonomic identification of boreal freshwater lotic, lentic, profundal and North-Eastern Baltic benthic macroinvertebrates , 2017 .

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

[56]  S. Karjalainen,et al.  Disentangling the responses of boreal stream assemblages to low stressor levels of diffuse pollution and altered channel morphology. , 2016, The Science of the total environment.

[57]  Nancy Knowlton,et al.  DNA barcoding and metabarcoding of standardized samples reveal patterns of marine benthic diversity , 2015, Proceedings of the National Academy of Sciences.

[58]  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.

[59]  Philippe Esling,et al.  Accurate multiplexing and filtering for high-throughput amplicon-sequencing , 2015, Nucleic acids research.

[60]  M. Drotz,et al.  The Baetis vernus group (Ephemeroptera: Baetidae) of northernmost Europe: an evidently diverse but poorly understood group of mayflies , 2007 .

[61]  F. Leese,et al.  Sorting things out: Assessing effects of unequal specimen biomass on DNA metabarcoding , 2017, Ecology and evolution.

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