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

Methods in Ecology and Evolution

Volumn 8, Issue 10, 2017, Pages 1265-1275

  Elbrecht, Vasco ^a   Vamos, Ecaterina Edith ^a   Meissner, Kristian ^b   Aroviita, Jukka ^b   Leese, Florian ^a  

^a UNIVERSITY OF DUISBURG ESSEN   (Germany)

^b FINNISH ENVIRONMENT INSTITUTE   (Finland)

Author keywords

biomass bias; ecological status; high throughput sequencing; macroinvertebrates; metabarcoding

Indexed keywords

EID: 85019221524     PISSN: None     EISSN: 2041210X     Source Type: Journal    
DOI: 10.1111/2041-210X.12789     Document Type: Article

References (60)

1. Aroviita, J., Hellsten, S., Jyväsjärvi, J. (2012) Guidelines for the ecological and chemical status classification of surface waters for 2012–2013 – updated assessment criteria and their application. Environmental Administration Guidelines, 7/2012, 1–144. (in Finnish). Available at: http://hdl.handle.net/10138/41788 (accessed 10 January 2017).
2. Aroviita, J., Koskenniemi, E., Kotanen, J. & Hämäläinen, H. (2008) A priori typology-based prediction of benthic macroinvertebrate fauna for ecological classification of rivers. Environmental Management, 42, 894–906.
3. Aroviita, J., Vuori, K.-M., Hellsten, S. et al. (2014) Ecological status and monitoring of surface waters polluted by agriculture and forestry. Reports of the Finnish Environment Institute, 12/2014, 1–96. (in Finnish). Available at: http://hdl.handle.net/10138/45017 (accessed 10 January 2017).
4. Aylagas, E., Borja, A., Irigoien, X. & Rodríguez-Ezpeleta, N. (2016a) Benchmarking DNA metabarcoding for biodiversity-based monitoring and assessment. Frontiers in Freshwater Science, 3, 1809–1812.
5. Aylagas, E., Borja, A. & Rodríguez-Ezpeleta, N. (2014) Environmental status assessment using DNA metabarcoding: towards a genetics based Marine Biotic Index (gAMBI). PLoS ONE, 9, e90529.
6. Aylagas, E., Mendibil, I., Borja, A. & Rodríguez-Ezpeleta, N. (2016b) Marine sediment sample pre-processing for macroinvertebrates metabarcoding: mechanical enrichment and homogenization. Frontiers in Freshwater Science, 3, 1452–1458.
7. Baird, D.J. & Hajibabaei, M. (2012) Biomonitoring 2.0: a new paradigm in ecosystem assessment made possible by next-generation DNA sequencing. Molecular Ecology, 21, 2039–2044.
8. Baird, D.J. & Sweeney, B.W. (2011) Applying DNA barcoding in benthology: the state of the science. Journal of the North American Benthological Society, 30, 122–124.
9. Barnes, M.A. & Turner, C.R. (2015) The ecology of environmental DNA and implications for conservation genetics. Conservation Genetics, 1–17.
10. Birk, S., Bonne, W., Borja, A. et al. (2012) Three hundred ways to assess Europe's surface waters: an almost complete overview of biological methods to implement the Water Framework Directive. Ecological Indicators, 18, 31–41.
11. Buss, D.F., Carlisle, D.M., Chon, T.-S. et al. (2015) Stream biomonitoring using macroinvertebrates around the globe: a comparison of large-scale programs. Environmental Monitoring and Assessment, 187, 4132.
12. Carew, M.E., Pettigrove, V.J., Metzeling, L. & Hoffmann, A.A. (2013) Environmental monitoring using next generation sequencing: rapid identification of macroinvertebrate bioindicator species. Frontiers in Zoology, 10, 1–1.
13. Clarke, L.J., Beard, J.M., Swadling, K.M. & Deagle, B.E. (2017) Effect of marker choice and thermal cycling protocol on zooplankton DNA metabarcoding studies. Ecology and Evolution, 7, 873–883.
14. Deagle, B.E., Jarman, S.N., Coissac, E., Pompanon, F. & Taberlet, P. (2014) DNA metabarcoding and the cytochrome c oxidase subunit I marker: not a perfect match. Biology Letters, 10, 20140562–20140562.
15. Dowle, E.J., Pochon, X. & Banks, J.C. (2015) Targeted gene enrichment and high-throughput sequencing for environmental biomonitoring: a case study using freshwater macroinvertebrates. Molecular Ecology, 10, 10–11.
16. Edgar, R.C. (2013) UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nature Methods, 10, 996–998.
17. Edgar, R.C. & Flyvbjerg, H. (2015) Error filtering, pair assembly and error correction for next-generation sequencing reads. Bioinformatics, 31, 3476–3482.
18. Elbrecht, V. & Leese, F. (2015) Can DNA-based ecosystem assessments quantify species abundance? Testing primer bias and biomass – sequence relationships with an innovative metabarcoding protocol. PLoS ONE, 10, e0130324–16.
19. Elbrecht, V. & Leese, F. (2016) PrimerMiner: an r package for development and in silico validation of DNA metabarcoding primers. Methods in Ecology and Evolution, 1–5.
20. Elbrecht, V. & Leese, F. (2017) Validation and development of freshwater invertebrate metabarcoding COI primers for environmental impact assessment. Frontiers in Environmental Science, 5, 1–11.
21. Elbrecht, V., Peinert, B. & Leese, F. (2017) Sorting things out – assessing effects of unequal specimen biomass on DNA metabarcoding. PeerJ PrePrints, 1–16.
22. Elbrecht, V., Vamos, E.E., Meissner, K., Aroviita, J. & Leese, F. (2017) Data from: Assessing strengths and weaknesses of DNA metabarcoding based macroinvertebrate identification for routine stream monitoring. Dryad Digital Repository, https://doi.org/10.5061/dryad.nm3pq
23. Esling, P., Lejzerowicz, F. & Pawlowski, J. (2015) Accurate multiplexing and filtering for high-throughput amplicon-sequencing. Nucleic Acids Research, 43, 2513–2524.
24. Folmer, O., Black, M., Hoeh, W., Lutz, R. & Vrijenhoek, R. (1994) DNA primers for amplification of mitochondrial cytochrome c oxidase subunit I from diverse metazoan invertebrates. Molecular Marine Biology and Biotechnology, 3, 294–299.
25. Gibson, J.F., Shokralla, S., Curry, C., Baird, D.J., Monk, W.A., King, I. & Hajibabaei, M. (2015) Large-scale biomonitoring of remote and threatened ecosystems via high-throughput sequencing. PLoS ONE, 10, e0138432–15.
26. Gibson, J., Shokralla, S., Porter, T.M., King, I., van Konynenburg, S., Janzen, D.H., Hallwachs, W. & Hajibabaei, M. (2014) Simultaneous assessment of the macrobiome and microbiome in a bulk sample of tropical arthropods through DNA metasystematics. Proceedings of the National Academy of Sciences, 111, 8007–8012.
27. Haase, P., Lohse, S., Pauls, S. & Schindehütte, K. (2004) Assessing streams in Germany with benthic invertebrates: development of a practical standardised protocol for macroinvertebrate sampling and sorting. Limnologica, 34, 349–365.
28. Haase, P., Pauls, S.U., Schindehütte, K. & Sundermann, A. (2010) First audit of macroinvertebrate samples from an EU Water Framework Directive monitoring program: human error greatly lowers precision of assessment results. Journal of the North American Benthological Society, 29, 1279–1291.
29. Hajibabaei, M., Shokralla, S., Zhou, X., Singer, G. & Baird, D.J. (2011) Environmental barcoding: a next-generation sequencing approach for biomonitoring applications using river Benthos. PLoS ONE, 6, e17497.
30. Hajibabaei, M., Spall, J.L., Shokralla, S. & van Konynenburg, S. (2012) Assessing biodiversity of a freshwater benthic macroinvertebrate community through non-destructive environmental barcoding of DNA from preservative ethanol. BMC Ecology, 12, 1–1.
31. Ji, Y., Ashton, L., Pedley, S.M. et al. (2013) Reliable, verifiable and efficient monitoring of biodiversity via metabarcoding. Ecology Letters, 16, 1245–1257.
32. Leese, F., Altermatt, F., Bouchez, A. et al. (2016) DNAqua-Net: developing new genetic tools for bioassessment and monitoring of aquatic ecosystems in Europe. Research Ideas and Outcomes, 2, e11321.
33. Lejzerowicz, F., Esling, P., Pillet, L., Wilding, T.A., Black, K.D. & Pawlowski, J. (2015) High-throughput sequencing and morphology perform equally well for benthic monitoring of marine ecosystems. Scientific Reports, 1–10.
34. Leray, M. & Knowlton, N. (2015) DNA barcoding and metabarcoding of standardized samples reveal patterns of marine benthic diversity. Proceedings of the National Academy of Sciences of the United States of America, 112, 2076–2081.
35. Lucentini, L., Rebora, M., Puletti, M.E., Gigliarelli, L., Fontaneto, D., Gaino, E. & Panara, F. (2011) Geographical and seasonal evidence of cryptic diversity in the Baetis rhodani complex (Ephemeroptera, Baetidae) revealed by means of DNA taxonomy. Hydrobiologia, 673, 215–228.
36. Macher, J.N., Salis, R.K., Blakemore, K.S. & Tollrian, R. (2016) Multiple-stressor effects on stream invertebrates: DNA barcoding reveals contrasting responses of cryptic mayfly species. Ecological Indicators, 61, 159–169.
37. Martin, M. (2011) Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet Journal, 17, 10–12.
38. Meissner, K., Aroviita, J., Hellsten, S., Järvinen, M., Karjalainen, S.M., Kuoppala, M. & Vuori, H.M.J.K.-M. (2016a). Jokien ja Järvien Biologinen Seuranta–Näytteenotosta Tiedon Tallentamiseen.(Biological Monitoring of Rivers and Lakes–From Sampling to Data Recording) in Finnish. Finnish Environment, 42 pages. Available at: http://www.ymparisto.fi/download/noname/%7BB948034F-7F9D-4EAB-A153-92FA2DDEDBBE%7D/29725 (accessed 10 January 2017).
39. Meissner, K., Nygård, H., Björklöf, K., Jaale, M., Hasari, M., Laitila, L., Rissanen, J. & Leivuori, M. (2016b) Proficiency Test 04/2016 Taxonomic identification of boreal freshwater lotic, lentic, profundal and North-Eastern Baltic benthic macroinvertebrates. Reports of the Finnish Environment Institute, 4, 24 pages. Available at: http://hdl.handle.net/10138/173237 (accessed 10 January 2017).
40. Mondy, C.P., Villeneuve, B., Archaimbault, V. & Usseglio-Polateraa, P. (2012) A new macroinvertebrate-based multimetric index (I 2 M 2) to evaluate ecological quality of French wadeable streams fulfilling the WFD demands: a taxonomical and trait apporach. Ecological Indicators, 18, 452–467.
41. Novak, M.A. & Bode, R.W. (1992) Percent model affinity: a new measure of macroinvertebrate community composition. Journal of the North American Benthological Society, 11, 80–85.
42. O'Donnell, J.L., Kelly, R.P., Lowell, N.C. & Port, J.A. (2016) Indexed PCR primers induce template-specific bias in large-scale DNA sequencing studies. PLoS ONE, 11, e0148698–11.
43. Piñol, J., Mir, G., Gomez-Polo, P. & Agustí, N. (2014) Universal and blocking primer mismatches limit the use of high-throughput DNA sequencing for the quantitative metabarcoding of arthropods. Molecular Ecology Resources, 15, 1–12.
44. Ratnasingham, S. & Hebert, P. (2007) BOLD: The Barcode of Life Data System (http://www.barcodinglife.org). Molecular Ecology Notes, 7, 355–364.
45. Ratnasingham, S. & Hebert, P.D.N. (2013) A DNA-based registry for all animal species: the Barcode Index Number (BIN) system. PLoS ONE, 8, e66213.
46. Resh, V.H. & Unzicker, J.D. (1975) Water quality monitoring and aquatic organisms: the importance of species identification. Journal – Water Pollution Control Federation, 47, 9–19.
47. Savolainen, E., Drotz, M.K. & Hoffsten, P. (2007) The Baetis vernus group (Ephemeroptera: Baetidae) of northernmost Europe: an evidently diverse but poorly understood group of mayflies. Entomologica, 18, 160–167.
48. Schmidt-Kloiber, A. & Hering, D. (2015) www.freshwaterecology.info – An online tool that unifies, standardises and codifies more than 20,000 European freshwater organisms and their ecological preferences. Ecological Indicators, 53, 271–282.
49. Schnell, I.B., Bohmann, K. & Gilbert, M.T.P. (2015) Tag jumps illuminated – reducing sequence-to-sample misidentifications in metabarcoding studies. Molecular Ecology Resources, 15, 1289–1303.
50. Stein, E.D., Martinez, M.C., Stiles, S., Miller, P.E. & Zakharov, E.V. (2014) Is DNA barcoding actually cheaper and faster than traditional morphological methods: results from a survey of freshwater bioassessment efforts in the United States? PLoS ONE, 9, e95525.
51. Stein, E.D., White, B.P., Mazor, R.D., Jackson, J.K. & Battle, J.M. (2013a) Does DNA barcoding improve performance of traditional stream bioassessment metrics? Freshwater Science, 33, 302–311.
52. Stein, E.D., White, B.P., Mazor, R.D., Miller, P.E. & Pilgrim, E.M. (2013b) Evaluating ethanol-based sample preservation to facilitate use of DNA barcoding in routine freshwater biomonitoring programs using benthic macroinvertebrates. PLoS ONE, 8, e51273–e51277.
53. Sunnucks, P. & Hales, D.F. (1996) Numerous transposed sequences of mitochondrial cytochrome oxidase I-II in aphids of the genus Sitobion (Hemiptera: Aphididae). Molecular Biology and Evolution, 13, 510–524.
54. Sweeney, B.W., Battle, J.M., Jackson, J.K. & Dapkey, T. (2011) Can DNA barcodes of stream macroinvertebrates improve descriptions of community structure and water quality? Journal of the North American Benthological Society, 30, 195–216.
55. Taberlet, P., Coissac, E., Pompanon, F., Brochmann, C. & Willerslev, E. (2012) Towards next-generation biodiversity assessment using DNA metabarcoding. Molecular Ecology, 21, 2045–2050.
56. Thomas, A.C., Deagle, B.E., Paige Eveson, J., Harsch, C.H. & Trites, A.W. (2015) Quantitative DNA metabarcoding: improved estimates of species proportional biomass using correction factors derived from control material. Molecular Ecology Resources, 16, 714–726.
57. Turunen, J., Muotka, T., Vuori, K.-M., Karjalainen, S.M., Rääpysjärvi, J., Sutela, T. & Aroviita, J. (2016) Disentangling the responses of boreal stream assemblages to low stressor levels of diffuse pollution and altered channel morphology. Science of the Total Environment, 544, 954–962.
58. Williams, H.C., Ormerod, S.J. & Bruford, M.W. (2006) Molecular systematics and phylogeography of the cryptic species complex Baetis rhodani (Ephemeroptera, Baetidae). Molecular Phylogenetics and Evolution, 40, 370–382.
59. Yu, D.W., Ji, Y., Emerson, B.C., Wang, X., Ye, C., Yang, C. & Ding, Z. (2012) Biodiversity soup: metabarcoding of arthropods for rapid biodiversity assessment and biomonitoring. Methods in Ecology and Evolution, 3, 613–623.
60. Zimmermann, J., Glöckner, G., Jahn, R., Enke, N. & Gemeinholzer, B. (2014) Metabarcoding vs. morphological identification to assess diatom diversity in environmental studies. Molecular Ecology Resources, 1–17.