Droplet digital PCR assays for the quantification of brown trout (Salmo trutta) and Arctic char (Salvelinus alpinus) from environmental DNA collected in the water of mountain lakes

Autoři: Eric Capo aff001;  Göran Spong aff002;  Sven Norman aff001;  Helena Königsson aff002;  Pia Bartels aff001;  Pär Byström aff001
Působiště autorů: Department of Ecology and Environmental Science, Umeå University, Umeå, Sweden aff001;  Molecular Ecology Group, Department of Wildlife, Fish and Environmental Studies, SLU, Umeå, Sweden aff002
Vyšlo v časopise: PLoS ONE 14(12)
Kategorie: Research Article
doi: 10.1371/journal.pone.0226638


Classical methods for estimating the abundance of fish populations are often both expensive, time-consuming and destructive. Analyses of the environmental DNA (eDNA) present in water samples could alleviate such constraints. Here, we developed protocols to detect and quantify brown trout (Salmo trutta) and Arctic char (Salvelinus alpinus) populations by applying the droplet digital PCR (ddPCR) method to eDNA molecules extracted from water samples collected in 28 Swedish mountain lakes. Overall, contemporary fish CPUE (catch per unit effort) estimates from standardized survey gill nettings were not correlated to eDNA concentrations for either of the species. In addition, the measured environmental variables (e.g. dissolved organic carbon concentrations, temperature, and pH) appear to not influence water eDNA concentrations of the studied fish species. Detection probabilities via eDNA analysis showed moderate success (less than 70% for both species) while the presence of eDNA from Arctic char (in six lakes) and brown trout (in one lake) was also indicated in lakes where the species were not detected with the gillnetting method. Such findings highlight the limits of one or both methods to reliably detect fish species presence in natural systems. Additional analysis showed that the filtration of water samples through 1.2 μm glass fiber filters and 0.45 μm mixed cellulose ester filters was more efficient in recovering DNA than using 0.22 μm enclosed polyethersulfone filters, probably due to differential efficiencies of DNA extraction. Altogether, this work showed the potentials and limits of the approach for the detection and the quantification of fish abundance in natural systems while providing new insights in the application of the ddPCR method applied to environmental DNA.

Klíčová slova:

DNA extraction – DNA filter assay – Fish – Freshwater fish – Lakes – Polymerase chain reaction – Surface water – Trout


1. 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;29: 358–367. doi: 10.1016/j.tree.2014.04.003 24821515

2. Bálint M, Pfenninger M, Grossart H-P, Taberlet P, Vellend M, Leibold MA, et al. Environmental DNA Time Series in Ecology. Trends Ecol Evol. 2018;33: 945–957. doi: 10.1016/j.tree.2018.09.003 30314916

3. Taberlet P, Bonin A, Zinger L, Coissac E. Environmental DNA: For biodiversity research and monitoring. Oxford Uni. 2018. doi: 10.1093/oso/9780198767220.001.0001

4. Taberlet P, Coissac E, Hajibabaei M, Rieseberg LH. Environmental DNA. Mol Ecol. 2012;21: 1789–93. doi: 10.1111/j.1365-294X.2012.05542.x 22486819

5. Coble AA, Flinders CA, Homyack JA, Penaluna BE, Cronn RC, Weitemier K. eDNA as a tool for identifying freshwater species in sustainable forestry: A critical review and potential future applications. Sci Total Environ. 2019;649: 1157–1170. doi: 10.1016/j.scitotenv.2018.08.370 30308887

6. Lodge DM, Turner CR, Jerde CL, Barnes MA, Chadderton L, Egan SP, et al. Conservation in a cup of water: Estimating biodiversity and population abundance from environmental DNA. Mol Ecol. 2012;21: 2555–2558. doi: 10.1111/j.1365-294X.2012.05600.x 22624944

7. Evans NT, Lamberti GA. Freshwater fisheries assessment using environmental DNA: A primer on the method, its potential, and shortcomings as a conservation tool. Fish Res. 2017;197: 60–66. doi: 10.1016/j.fishres.2017.09.013

8. Takahara T, Minamoto T, Yamanaka H, Doi H, Kawabata Z, Begon M, et al. Estimation of Fish Biomass Using Environmental DNA. PLoS One. 2012;7: e35868. doi: 10.1371/journal.pone.0035868 22563411

9. Doi H, Uchii K, Takahara T, Matsuhashi S, Yamanaka H, Minamoto T. Use of droplet digital PCR for estimation of fish abundance and biomass in environmental DNA surveys. PLoS One. 2015;10: 1–11. doi: 10.1371/journal.pone.0122763 25799582

10. Klymus KE, Richter CA, Chapman DC, Paukert C. Quantification of eDNA shedding rates from invasive bighead carp Hypophthalmichthys nobilis and silver carp Hypophthalmichthys molitrix. Biol Conserv. 2015;183: 77–84. doi: 10.1016/j.biocon.2014.11.020

11. Spear SF, Groves JD, Williams LA, Waits LP. Using environmental DNA methods to improve detectability in a hellbender (Cryptobranchus alleganiensis) monitoring program. Biol Conserv. 2015;183: 38–45. doi: 10.1016/j.biocon.2014.11.016

12. Yamamoto S, Masuda R, Sato Y, Sado T, Araki H, Kondoh M, et al. Environmental DNA metabarcoding reveals local fish communities in a species-rich coastal sea. Sci Rep. 2017;7: 1–12. doi: 10.1038/s41598-016-0028-x

13. Deutschmann B, Müller AK, Hollert H, Brinkmann M. Assessing the fate of brown trout (Salmo trutta) environmental DNA in a natural stream using a sensitive and specific dual-labelled probe. Sci Total Environ. 2019;655: 321–327. doi: 10.1016/j.scitotenv.2018.11.247 30471600

14. Hansen BK, Bekkevold D, Clausen LW, Nielsen EE. The sceptical optimist: challenges and perspectives for the application of environmental DNA in marine fisheries. Fish Fish. 2018;19: 751–768. doi: 10.1111/faf.12286

15. Jerde CL, Chadderton WL, Mahon AR, Renshaw M a, Corush J, Budny ML, et al. Detection of Asian carp DNA as part of a Great Lakes basin-wide surveillance program. Can J Fish Aquat Sci. 2013;70: 522–526. doi: 10.1139/cjfas-2012-0478

16. Secondi J, Dejean T, Valentini A, Audebaud B, Miaud C. Detection of a global aquatic invasive amphibian, Xenopus laevis, using environmental DNA. Amphibia-Reptilia. 2016;37: 131–136. doi: 10.1163/15685381-00003036

17. Bylemans J, Gleeson DM, Lintermans M, Hardy CM, Beitzel M, Gilligan DM, et al. Monitoring riverine fish communities through eDNA metabarcoding: determining optimal sampling strategies along an altitudinal and biodiversity gradient. Metabarcoding and Metagenomics. 2018;2: e30457. doi: 10.3897/mbmg.2.30457

18. Quist MC, Bonvechio KI, Allen MS. Chapter 11: Statistical Analysis and Data Management. Standard Methods for Sampling North American Freshwater Fishes. eds W.A. H. 2009. pp. 171–194.

19. Hubert W, Fabrizio M. Relative abundance and catch per unit effort. Analysis and interpretation of freshwater fisheries data. 2007.

20. Bonar SA, Hubert WA, Willis DW. Standard methods for sampling North American freshwater fishes [Internet]. American Fisheries Society; 2009.

21. Pope K, Lochmann S, Young M. Methods for Assessing Fish Populations. Inland fisheries management in North America. 2010. pp. 325–351.

22. Šmejkal M, Ricard D, Prchalová M, Říha M, Muška M, Blabolil P, et al. Biomass and Abundance Biases in European Standard Gillnet Sampling. Britton R, editor. PLoS One. 2015;10: e0122437. doi: 10.1371/journal.pone.0122437 25793776

23. Jenkins JA, Bart HL, Bowker JD, Bowser PR, Macmillan JR, Nickum JG, et al. Guidelines for the Use of Fishes in Research [Internet]. Library of Congress Control Number. 2014.

24. Doi H, Takahara T, Minamoto T, Matsuhashi S, Uchii K, Yamanaka H. Droplet digital polymerase chain reaction (PCR) outperforms real-time PCR in the detection of environmental DNA from an invasive fish species. Environ Sci Technol. 2015;49: 5601–8. doi: 10.1021/acs.est.5b00253 25850372

25. Nathan LM, Simmons M, Wegleitner BJ, Jerde CL, Mahon AR. Quantifying environmental DNA signals for aquatic invasive species across multiple detection platforms. Environ Sci Technol. 2014;48: 12800–12806. doi: 10.1021/es5034052 25299381

26. Hunter ME, Ferrante JA, Meigs-Friend G, Ulmer A. Improving eDNA yield and inhibitor reduction through increased water volumes and multi-filter isolation techniques. Sci Rep. 2019;9: 1–9. doi: 10.1038/s41598-018-37186-2

27. Capo E, Spong G, Königsson H, Byström P. Effects of filtration methods and water volume on the quantification of brown trout (Salmo trutta) and Arctic char (Salvelinus alpinus) eDNA concentrations via droplet digital PCR. Environ DNA. 2019;0: 1–9. doi: 10.1002/edn3.52

28. Gustavson MS, Collins PC, Finarelli JA, Egan D, Conchúir R, Wightman GD, et al. An eDNA assay for Irish Petromyzon marinus and Salmo trutta and field validation in running water. J Fish Biol. 2015;87: 1254–1262. doi: 10.1111/jfb.12781 26377304

29. Klobucar SL, Rodgers TW, Budy P. At the forefront: evidence of the applicability of using environmental DNA to quantify the abundance of fish populations in natural lentic waters with additional sampling considerations. Can J Fish Aquat Sci. 2017;74: 1–5. doi: 10.1139/cjfas-2017-0114

30. Rodgers TW, Olson JR, Klobucar SL, Mock KE. Quantitative PCR assays for detection of five arctic fish species: Lota lota, Cottus cognatus, Salvelinus alpinus, Salvelinus malma, and Thymallus arcticus from environmental DNA. Conserv Genet Resour. 2018;10: 859–865. doi: 10.1007/s12686-017-0883-1

31. Johnson L. Long-term Experiments on the Stability of Two Fish Populations in Previously Unexploited Arctic Lakes. Can J Fish Aquat Sci. 1994;51: 209–225. doi: 10.1139/f94-023

32. Byström P. Recruitment pulses induce cannibalistic giants in Arctic char. J Anim Ecol. 2006;75: 434–444. doi: 10.1111/j.1365-2656.2006.01064.x 16637996

33. Barnes MA, Turner CR. The ecology of environmental DNA and implications for conservation genetics. Conserv Genet. 2016;17: 1–17. doi: 10.1007/s10592-015-0775-4

34. Eichmiller JJ, Best SE, Sorensen PW. Effects of Temperature and Trophic State on Degradation of Environmental DNA in Lake Water. Environ Sci Technol. 2016;50: 1859–1867. doi: 10.1021/acs.est.5b05672 26771292

35. Darling JA, Mahon AR. From molecules to management: Adopting DNA-based methods for monitoring biological invasions in aquatic environments. Environ Res. 2011;111: 978–988. doi: 10.1016/j.envres.2011.02.001 21353670

36. Klemetsen A, Amundsen P, Dempson J, Jonsson B, Jonsson N, O´Connell M, et al. Atlantic salmon Salmo salar L., brown trout Salmo trutta L. and Arctic charr Salvelinus alpinus (L.): a review of aspects of their life histories. Ecol Freshw Fish. 2003;12: 1–59.

37. CEN. Water quality-Sampling of fish with multi-mesh gillnets. 2005. Available: https://infostore.saiglobal.com/preview/is/en/2005/i.s.en14757-2005.pdf?sku=675315Bates D,

38. Karlsson J, Bergström AK, Byström P, Gudasz C, Rodríguez P, Hein C. Terrestrial organic matter input suppresses biomass production in lake ecosystems. Ecology. 2015;96: 2870–2876. doi: 10.1890/15-0515.1 27070007

39. Karlsson J, Byström P, Ask J, Ask P, Persson L, Jansson M. Light limitation of nutrient-poor lake ecosystems. Nature. 2009;460: 506–509. doi: 10.1038/nature08179 19626113

40. Ye J, Coulouris G, Zaretskaya I, Cutcutache I, Rozen S, Madden TL. Primer-BLAST: A tool to design target-specific primers for polymerase chain reaction. BMC Bioinformatics. 2012;13: 134. doi: 10.1186/1471-2105-13-134 22708584

41. Harper LR, Griffiths NP, Lawson Handley L, Sayer CD, Read DS, Harper KJ, et al. Development and application of environmental DNA surveillance for the threatened crucian carp (Carassius carassius). Freshw Biol. 2019;64: 93–107. doi: 10.1111/fwb.13197

42. Bates D, Mächler M, Bolker B, Walker S (2015) Fitting Linear Mixed-Effects Models Using lme4. Journal of Statistical Software, 67, 1–48.

43. Skaug H, Fournier D, Nielsen A, Magnusson A (2015) GlmmADMB: generalized linear mixed models using AD model builder. 1–21. [Computer software manual]

44. Brooks ME, Kristensen K, Benthem KJ van et al. (2017) glmmTMB balances speed and flexibility among packages for zero-inflated generalized linear mixed modeling. The R journal, 9, 378–400.

45. Fox J, Weisberg S (2018) Multivariate Linear Models in R. In: An R Companion to Applied Regression, third regression, pp. 1–30.

46. Hosmer DW, Lemeshow S (2000) Applied logistic regression. Wiley.

47. Lele S, Keim J, Solymos P, Solymos M, Imports M (2019) Package “ResourceSelection.”

48. Degerman E, Nyberg P, Appelberg M. Estimating the number of species and relative abundance of fish in oligotrophic Swedish lakes using multi-mesh gillnets. Nord J Freshw Res. 1988;64: 91–100.

49. Dunker KJ, Sepulveda AJ, Massengill RL, Olsen JB, Russ OL, Wenburg JK, et al. Potential of environmental DNA to evaluate northern pike (Esox lucius) eradication efforts: An experimental test and case study. PLoS One. 2016;11: 1–21. doi: 10.1371/journal.pone.0162277 27626271

50. Merkes CM, McCalla SG, Jensen NR, Gaikowski MP, Amberg JJ. Persistence of DNA in Carcasses, Slime and Avian Feces May Affect Interpretation of Environmental DNA Data. Willson RC, editor. PLoS One. 2014;9: e113346. doi: 10.1371/journal.pone.0113346 25402206

51. Guilfoyle MP, Schultz MT. The contribution of double-crested cormorants (Phalacrocorax auritus) to silver carp (Hypophthalmichthys molitrix) DNA loads in the Chicago Area Waterway System. J Great Lakes Res. 2017;43: 1181–1185. doi: 10.1016/j.jglr.2017.09.008

52. Iversen LL, Kielgast J, Sand-Jensen K. Monitoring of animal abundance by environmental DNA: An increasingly obscure perspective: A reply to Klymus et al., 2015. Biol Conserv. 2015;192: 479–480. doi: 10.1016/j.biocon.2015.09.024

53. Sassoubre LM, Yamahara KM, Gardner LD, Block BA, Boehm AB. Quantification of Environmental DNA (eDNA) Shedding and Decay Rates for Three Marine Fish. Environ Sci Technol. 2016;50: 10456–10464. doi: 10.1021/acs.est.6b03114 27580258

54. Lacoursière-Roussel A, Rosabal M, Bernatchez L. Estimating fish abundance and biomass from eDNA concentrations: variability among capture methods and environmental conditions. Mol Ecol Resour. 2016;16: 1401–1414. doi: 10.1111/1755-0998.12522 26946353

55. Ulibarri RM, Bonar SA, Rees C, Amberg J, Ladell B, Jackson C. Comparing efficiency of American fisheries society standard snorkeling techniques to environmental DNA sampling techniques. North Am J Fish Manag. 2017;37: 644–651. doi: 10.1080/02755947.2017.1306005

56. Perez CR, Bonar SA, Amberg JJ, Ladell B, Rees C, Stewart WT, et al. Comparison of american fisheries society (AFS) standard fish sampling techniques and environmental DNA for characterizing fish communities in a large reservoir. North Am J Fish Manag. 2017;37: 1010–1027. doi: 10.1080/02755947.2017.1342721

57. Maruyama A, Nakamura K, Yamanaka H, Kondoh M, Minamoto T. The release rate of environmental DNA from juvenile and adult fish. PLoS One. 2014;9: 1–13. doi: 10.1371/journal.pone.0114639 25479160

58. Lacoursière-Roussel A, Côté G, Leclerc V, Bernatchez L, Cadotte M. Quantifying relative fish abundance with eDNA: a promising tool for fisheries management. J Appl Ecol. 2016;53: 1148–1157. doi: 10.1111/1365-2664.12598

59. Robson HLA, Noble TH, Saunders RJ, Robson SKA, Burrows DW, Jerry DR. Fine-tuning for the tropics: application of eDNA technology for invasive fish detection in tropical freshwater ecosystems. Mol Ecol Resour. 2016;16: 922–932. doi: 10.1111/1755-0998.12505 26849294

60. Spens J, Evans AR, Halfmaerten D, Knudsen SW, Sengupta ME, Mak SST, et al. Comparison of capture and storage methods for aqueous macrobial eDNA using an optimized extraction protocol: Advantage of enclosed filter. Methods Ecol Evol. 2017;8: 635–645. doi: 10.1111/2041-210X.12683

61. 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: 929–942. doi: 10.1111/mec.13428 26479867

62. Li J, Lawson Handley LJ, Read DS, Hänfling B. The effect of filtration method on the efficiency of environmental DNA capture and quantification via metabarcoding. Mol Ecol Resour. 2018;18: 1102–1114. doi: 10.1111/1755-0998.12899 29766663

63. Sigsgaard EE, Nielsen IB, Bach SS, Lorenzen ED, Robinson DP, Knudsen SW, et al. Population characteristics of a large whale shark aggregation inferred from seawater environmental DNA. Nat Ecol Evol. 2017;1: 1–4. doi: 10.1038/s41559-016-0001

Článek vyšel v časopise


2019 Číslo 12