Watered-down biodiversity? A comparison of metabarcoding results from DNA extracted from matched water and bulk tissue biomonitoring samples


Autoři: Mehrdad Hajibabaei aff001;  Teresita M. Porter aff001;  Chloe V. Robinson aff001;  Donald J. Baird aff003;  Shadi Shokralla aff001;  Michael T. G. Wright aff001
Působiště autorů: Centre for Biodiversity Genomics and Department of Integrative Biology, University of Guelph, Guelph, Ontario, Canada aff001;  Great Lakes Forestry Centre, Natural Resources Canada, Sault Ste. Marie, Ontario, Canada aff002;  Environment and Climate Change Canada @ Canadian Rivers Institute, Department of Biology, University of New Brunswick, Fredericton, New Brunswick, Canada aff003
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
doi: 10.1371/journal.pone.0225409

Souhrn

Biomonitoring programs have evolved beyond the sole use of morphological identification to determine the composition of invertebrate species assemblages in an array of ecosystems. The application of DNA metabarcoding in freshwater systems for assessing benthic invertebrate communities is now being employed to generate biological information for environmental monitoring and assessment. A possible shift from the extraction of DNA from net-collected bulk benthic samples to its extraction directly from water samples for metabarcoding has generated considerable interest based on the assumption that taxon detectability is comparable when using either method. To test this, we studied paired water and benthos samples from a taxon-rich wetland complex, to investigate differences in the detection of arthropod taxa from each sample type. We demonstrate that metabarcoding of DNA extracted directly from water samples is a poor surrogate for DNA extracted from bulk benthic samples, focusing on key bioindicator groups. Our results continue to support the use of bulk benthic samples as a basis for metabarcoding-based biomonitoring, with nearly three times greater total richness in benthic samples compared to water samples. We also demonstrated that few arthropod taxa are shared between collection methods, with a notable lack of key bioindicator EPTO taxa in the water samples. Although species coverage in water could likely be improved through increased sample replication and/or increased sequencing depth, benthic samples remain the most representative, cost-effective method of generating aquatic compositional information via metabarcoding.

Klíčová slova:

Arthropoda – Biodiversity – Delta ecosystems – DNA extraction – Polymerase chain reaction – Rivers – Surface water – Taxonomy


Zdroje

1. Bonada N, Prat N, Resh VH, Statzner B. DEVELOPMENTS IN AQUATIC INSECT BIOMONITORING: A Comparative Analysis of Recent Approaches. Annu Rev Entomol. 2006;51(1):495–523.

2. Friberg N, Bonada N, Bradley DC, Dunbar MJ, Edwards FK, Grey J, et al. Biomonitoring of Human Impacts in Freshwater Ecosystems: The Good, the Bad and the Ugly. In: Woodward G, editor. Advances in Ecological Research [Internet]. Academic Press; 2011 [cited 2019 Jun 24]. p. 1–68. http://www.sciencedirect.com/science/article/pii/B9780123747945000018

3. Baird DJ, Hajibabaei M. Biomonitoring 2.0: a new paradigm in ecosystem assessment made possible by next-generation DNA sequencing. Mol Ecol. 2012;21(8):2039–44. doi: 10.1111/j.1365-294x.2012.05519.x 22590728

4. Hajibabaei M, Baird Donald J., Fahner Nicole A., Beiko Robert, Golding G Brian. A new way to contemplate Darwin’s tangled bank: how DNA barcodes are reconnecting biodiversity science and biomonitoring. Philos Trans R Soc B Biol Sci. 2016 Sep 5;371(1702):20150330.

5. Dafforn KA, Johnston EL, Ferguson A, Humphrey CL, Monk W, Nichols SJ, et al. Big data opportunities and challenges for assessing multiple stressors across scales in aquatic ecosystems. Mar Freshw Res. 2016 Apr 14;67(4):393–413.

6. Hajibabaei M, Singer GAC, Hebert PDN, Hickey DA. DNA barcoding: how it complements taxonomy, molecular phylogenetics and population genetics. Trends Genet. 2007 Apr 1;23(4):167–72. doi: 10.1016/j.tig.2007.02.001 17316886

7. Hebert P. D. N., Hollingsworth P. M., Hajibabaei M. From writing to reading the encyclopedia of life. Philos Trans R Soc B Biol Sci. 2016 Sep 5;371(1702):20150321.

8. Pilgrim EM, Jackson SA, Swenson S, Turcsanyi I, Friedman E, Weigt L, et al. Incorporation of DNA barcoding into a large-scale biomonitoring program: opportunities and pitfalls. J North Am Benthol Soc. 2011 Mar 1;30(1):217–31.

9. Sweeney BW, Battle JM, Jackson JK, Dapkey T. Can DNA barcodes of stream macroinvertebrates improve descriptions of community structure and water quality? J North Am Benthol Soc 2011 Mar 1;30(1):195–216.

10. Orlofske JM, Baird DJ. The tiny mayfly in the room: implications of size-dependent invertebrate taxonomic identification for biomonitoring data properties. Aquat Ecol. 2013 Dec 1;47(4):481–94.

11. Hajibabaei M, Spall JL, Shokralla S, van Konynenburg S. Assessing biodiversity of a freshwater benthic macroinvertebrate community through non-destructive environmental barcoding of DNA from preservative ethanol. BMC Ecol. 2012 Dec 23;12(1):28.

12. Shokralla S, Spall JL, Gibson JF, Hajibabaei M. Next-generation sequencing technologies for environmental DNA research. Mol Ecol. 2012;21(8):1794–805. doi: 10.1111/j.1365-294X.2012.05538.x 22486820

13. Hajibabaei M. The golden age of DNA metasystematics. Trends Genet. 2012 Nov 1;28(11):535–7. doi: 10.1016/j.tig.2012.08.001 22951138

14. Taberlet P, Coissac E, Pompanon F, Brochmann C, Willerslev E. Towards next-generation biodiversity assessment using DNA metabarcoding. Mol Ecol. 2012;21(8):2045–50. doi: 10.1111/j.1365-294X.2012.05470.x 22486824

15. Hajibabaei M, Shokralla S, Zhou X, Singer GAC, Baird DJ. Environmental Barcoding: A Next-Generation Sequencing Approach for Biomonitoring Applications Using River Benthos. PLOS ONE. 2011 Apr 13;6(4):e17497. doi: 10.1371/journal.pone.0017497 21533287

16. Gibson JF, Shokralla S, Curry C, Baird DJ, Monk WA, King I, et al. Large-Scale Biomonitoring of Remote and Threatened Ecosystems via High-Throughput Sequencing. PLOS ONE. 2015 Oct 21;10(10):e0138432. doi: 10.1371/journal.pone.0138432 26488407

17. Carew ME, Kellar CR, Pettigrove VJ, Hoffmann AA. Can high-throughput sequencing detect macroinvertebrate diversity for routine monitoring of an urban river? Ecol Indic. 2018 Feb 1;85:440–50.

18. Elbrecht V, Leese F. Can DNA-Based Ecosystem Assessments Quantify Species Abundance? Testing Primer Bias and Biomass—Sequence Relationships with an Innovative Metabarcoding Protocol. PLOS ONE. 2015 Jul 8;10(7):e0130324. doi: 10.1371/journal.pone.0130324 26154168

19. Lejzerowicz F, Esling P, Pillet L, Wilding TA, Black KD, Pawlowski J. High-throughput sequencing and morphology perform equally well for benthic monitoring of marine ecosystems. Sci Rep. 2015 Sep 10;5:13932. doi: 10.1038/srep13932 26355099

20. Dowle EJ, Pochon X, Banks JC, Shearer K, Wood SA. Targeted gene enrichment and high-throughput sequencing for environmental biomonitoring: a case study using freshwater macroinvertebrates. Mol Ecol Resour. 2016;16(5):1240–54. doi: 10.1111/1755-0998.12488 26583904

21. Gibson J, Shokralla S, Porter TM, King I, van Konynenburg S, Janzen DH, et al. Simultaneous assessment of the macrobiome and microbiome in a bulk sample of tropical arthropods through DNA metasystematics. Proc Natl Acad Sci. 2014 Jun 3;111(22):8007–12. doi: 10.1073/pnas.1406468111 24808136

22. Ficetola G. F., Miaud C, Pompanon F, Taberlet P. Species detection using environmental DNA from water samples. Biol Lett. 2008 Aug 23;4(4):423–5. doi: 10.1098/rsbl.2008.0118 18400683

23. Deiner K, Fronhofer EA, Mächler E, Walser J-C, Altermatt F. Environmental DNA reveals that rivers are conveyer belts of biodiversity information. Nat Commun. 2016 Aug 30;7:12544. doi: 10.1038/ncomms12544 27572523

24. Macher J-N, Vivancos A, Piggott JJ, Centeno FC, Matthaei CD, Leese F. Comparison of environmental DNA and bulk-sample metabarcoding using highly degenerate cytochrome c oxidase I primers. Mol Ecol Resour. 2018 Nov;18(6):1456–68. doi: 10.1111/1755-0998.12940 30129704

25. Environment and Climate Change Canada. CABIN Wetland Macroinvertebrate Protocol. Httppublicationsgccacollectionscollection2018ecccCW66-571-2018-Engpdf. 2018;

26. St. John, J. SeqPrep. HttpsgithubcomjstjohnSeqPrepreleases. 2016;

27. Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet.journal. 2011 May 2;17(1):10–2.

28. Rognes T, Flouri T, Nichols B, Quince C, Mahé F. VSEARCH: a versatile open source tool for metagenomics. PeerJ. 2016 Oct 18;4:e2584. doi: 10.7717/peerj.2584 27781170

29. Edgar RC. UNOISE2: improved error-correction for Illumina 16S and ITS amplicon sequencing. bioRxiv. 2016 Oct 15;081257.

30. Callahan BJ, McMurdie PJ, Holmes SP. Exact sequence variants should replace operational taxonomic units in marker-gene data analysis. ISME J. 2017 Dec;11(12):2639–43. doi: 10.1038/ismej.2017.119 28731476

31. Porter TM, Hajibabaei M. Over 2.5 million COI sequences in GenBank and growing. PLOS ONE. 2018 Sep 7;13(9):e0200177. doi: 10.1371/journal.pone.0200177 30192752

32. Dixon P. VEGAN, a package of R functions for community ecology. J Veg Sci. 2003;14(6):927–30.

33. RStudio Team. RStudio: Integrated Development Environment for R. Retrieved http://www.rstudio.com. 2016;

34. Weiss S, Xu ZZ, Peddada S, Amir A, Bittinger K, Gonzalez A, et al. Normalization and microbial differential abundance strategies depend upon data characteristics. Microbiome. 2017 Mar 3;5(1):27. doi: 10.1186/s40168-017-0237-y 28253908

35. Suzuki MT, Giovannoni SJ. Bias caused by template annealing in the amplification of mixtures of 16S rRNA genes by PCR. Appl Environ Microbiol. 1996 Feb 1;62(2):625–30. 8593063

36. Polz MF, Cavanaugh CM. Bias in Template-to-Product Ratios in Multitemplate PCR. Appl Environ Microbiol. 1998 Oct 1;64(10):3724–30. 9758791

37. McLaren MR, Willis AD, Callahan BJ. Consistent and correctable bias in metagenomic sequencing measurements. bioRxiv. 2019 Feb 25;559831.

38. Shapiro SS, Wilk MB. An Analysis of Variance Test for Normality (Complete Samples). Biometrika. 1965;52(3/4):591–611.

39. Wilcoxon F. Individual Comparisons by Ranking Methods. Biom Bull. 1945;1(6):80–3.

40. Smith MR. Ternary: An R Package for Creating Ternary Plots version 1.1.1 from CRAN [Internet]. [cited 2019 Sep 10]. https://rdrr.io/cran/Ternary/

41. Anderson MJ, Walsh DCI. PERMANOVA, ANOSIM, and the Mantel test in the face of heterogeneous dispersions: What null hypothesis are you testing? Ecol Monogr. 2018;(83) 557–74.

42. Dickie IA, Boyer S, Buckley HL, Duncan RP, Gardner PP, Hogg ID, et al. Towards robust and repeatable sampling methods in eDNA-based studies. Mol Ecol Resour. 2018;18(5):940–52.

43. Rees HC, Maddison BC, Middleditch DJ, Patmore JRM, Gough KC. REVIEW: The detection of aquatic animal species using environmental DNA–a review of eDNA as a survey tool in ecology. J Appl Ecol. 2014;51(5):1450–9.

44. Valentini A, Taberlet P, Miaud C, Civade R, Herder J, Thomsen PF, et al. Next-generation monitoring of aquatic biodiversity using environmental DNA metabarcoding. Mol Ecol. 2016;25(4):929–42. doi: 10.1111/mec.13428 26479867

45. Culp JM, Armanini DG, Dunbar MJ, Orlofske JM, Poff NL, Pollard AI, et al. Incorporating traits in aquatic biomonitoring to enhance causal diagnosis and prediction. Integr Environ Assess Manag. 2011 Apr;7(2):187–97. doi: 10.1002/ieam.128 21442732

46. Tréguier A, Paillisson J-M, Dejean T, Valentini A, Schlaepfer MA, Roussel J-M. Environmental DNA surveillance for invertebrate species: advantages and technical limitations to detect invasive crayfish Procambarus clarkii in freshwater ponds. J Appl Ecol. 2014;51(4):871–9.

47. Koziol A, Stat M, Simpson T, Jarman S, DiBattista JD, Harvey ES, et al. Environmental DNA metabarcoding studies are critically affected by substrate selection. Mol Ecol Resour. 2019;19(2):366–76. doi: 10.1111/1755-0998.12971 30485662

48. Yoccoz NG, Bråthen KA, Gielly L, Haile J, Edwards ME, Goslar T, et al. DNA from soil mirrors plant taxonomic and growth form diversity. Mol Ecol. 2012;21(15):3647–55. doi: 10.1111/j.1365-294X.2012.05545.x 22507540

49. Roussel J-M, Paillisson J-M, Tréguier A, Petit E. The downside of eDNA as a survey tool in water bodies. J Appl Ecol. 2015;52(4):823–6.

50. Bohmann K, Evans A, Gilbert MTP, Carvalho GR, Creer S, Knapp M, et al. Environmental DNA for wildlife biology and biodiversity monitoring. Trends Ecol Evol. 2014 Jun 1;29(6):358–67. doi: 10.1016/j.tree.2014.04.003 24821515

51. Schultz MT, Lance RF. Modeling the Sensitivity of Field Surveys for Detection of Environmental DNA (eDNA). PLOS ONE. 2015 Oct 28;10(10):e0141503. doi: 10.1371/journal.pone.0141503 26509674

52. Ficetola GF, Pansu J, Bonin A, Coissac E, Giguet‐Covex C, Barba MD, et al. Replication levels, false presences and the estimation of the presence/absence from eDNA metabarcoding data. Mol Ecol Resour. 2015;15(3):543–56. doi: 10.1111/1755-0998.12338 25327646

53. Alberdi A, Aizpurua O, Gilbert MTP, Bohmann K. Scrutinizing key steps for reliable metabarcoding of environmental samples. Methods Ecol Evol. 2018;9(1):134–47.

54. Mächler E, Deiner K, Spahn F, Altermatt F. Fishing in the Water: Effect of Sampled Water Volume on Environmental DNA-Based Detection of Macroinvertebrates. Environ Sci Technol. 2016;50(1):305–12. doi: 10.1021/acs.est.5b04188 26560432

55. Furlan EM, Gleeson D, Hardy CM, Duncan RP. A framework for estimating the sensitivity of eDNA surveys. Mol Ecol Resour. 2016;16(3):641–54. doi: 10.1111/1755-0998.12483 26536842

56. Lanzén A, Lekang K, Jonassen I, Thompson EM, Troedsson C. DNA extraction replicates improve diversity and compositional dissimilarity in metabarcoding of eukaryotes in marine sediments. PLOS ONE. 2017 Jun 16;12(6):e0179443. doi: 10.1371/journal.pone.0179443 28622351

57. Elbrecht V, Leese F. Validation and Development of COI Metabarcoding Primers for Freshwater Macroinvertebrate Bioassessment. Front Environ Sci [Internet]. 2017 [cited 2019 Jun 24];5. https://www.frontiersin.org/articles/10.3389/fenvs.2017.00011/full?&utm_source=Email_to_authors_&utm_medium=Email&utm_content=T1_11.5e1_author&utm_campaign=Email_publication&field=&journalName=Frontiers_in_Environmental_Science&id=237020

58. Weigand AM, Macher J-N. A DNA metabarcoding protocol for hyporheic freshwater meiofauna: Evaluating highly degenerate COI primers and replication strategy. Metabarcoding Metagenomics. 2018 Aug 23;2:e26869.


Článek vyšel v časopise

PLOS One


2019 Číslo 12