The detection of a non-anemophilous plant species using airborne eDNA

Autoři: Mark D. Johnson aff001;  Robert D. Cox aff001;  Matthew A. Barnes aff001
Působiště autorů: Department of Natural Resources Management, Texas Tech University, Lubbock, TX, United States of America aff001
Vyšlo v časopise: PLoS ONE 14(11)
Kategorie: Research Article
doi: 10.1371/journal.pone.0225262


Genetic analysis of airborne plant material has historically focused (generally implicitly rather than as a stated goal) on pollen from anemophilous (wind-pollinated) species, such as in multiple studies examining the relationship of allergens to human health. Inspired by the recent influx of literature applying environmental DNA (eDNA) approaches to targeted-species and whole-ecosystem study, we conducted a proof-of-concept experiment to determine whether airborne samples reliably detect genetic material from non-anemophilous species that may not be releasing large plumes of pollen. We collected airborne eDNA using Big Spring Number Eight dust traps and quantified the amount of eDNA present for a flowering wind-pollinated genus (Bouteloua) and insect-pollinated honey mesquite (Prosopis glandulosa) that was not flowering at the time of the study. We were able to detect airborne eDNA from both species. Since honey mesquite is insect-pollinated and was not flowering during the time of this study, our results confirm that airborne eDNA consists of and can detect species through more than just pollen. Additionally, we were able to detect temporal patterns reflecting Bouteloua reproductive ecology and suggest that airborne honey mesquite eDNA responded to weather conditions during our study. These findings suggest a need for more study of the ecology of airborne eDNA to uncover its potential for single-species and whole-community research and management in terrestrial ecosystems.

Klíčová slova:

DNA extraction – Dust – Flowering plants – Honey – Invasive species – Plant genetics – Pollen – Polymerase chain reaction


1. Ficetola GF, Miaud C, Pompanon F, Taberlet P. Species detection using environmental DNA from water samples. Biology Letters. 2008;4(4):423–425. doi: 10.1098/rsbl.2008.0118 18400683

2. Willerslev E, Hansen AJ, Binladen J, Brand TB, Gilbert MTP, Shapiro B, et al. Diverse plant and animal genetic records from Holocene and Pleistocene Sediments. Science. 2003;300(5620):791. doi: 10.1126/science.1084114 12702808

3. Dejean T, Valentini A, Miquel C, Taberlet P, Bellemain E, Miaud C. Improved detection of an alien invasive species through environmental DNA barcoding: the example of the American bullfrog Lithobates catesbeianus. Journal of Applied Ecology. 2012;49(4):953–959. doi: 10.1111/j.1365-2664.2012.02171.x

4. Klymus KE, Marshall NT, Stepien CA. Environmental DNA (eDNA) metabarcoding assays to detect invasive invertebrate species in the Great Lakes. PLoS ONE. 2017;12(5):e0177643. doi: 10.1371/journal.pone.0177643 28542313

5. Kraaijeveld K, De Wegner L, Garcia M, Buermans H, Frank J, Hiemstra P, et al. Efficient and sensitive identification and quantification of airborne pollen using next-generation DNA sequencing. Molecular Ecology Resources. 2015;15(1):8–16. doi: 10.1111/1755-0998.12288 24893805

6. Leontidou K, Vernesi C, De Groeve J, Cristofolini F, Vokou D, Cristofori A. DNA metabarcoding of airborne pollen: new protocols for improved taxonomic identification of environmental samples. Aerobiologia. 2018;34:63–74. doi: 10.1016/j.foodchem.2008.09.063

7. Longhi S, Cristofori A, Gatto P, Cristofolini F, Grando MS, Gottardini E. Biomolecular identification of allergenic pollen: a new perspective for aerobiological monitoring? Ann Allergy Asthma Immunol. 2009;103(6):508–514. doi: 10.1016/S1081-1206(10)60268-2 20084845

8. Hawkins J, Vere N, Griffith A, Ford R, Allainguillaume J, Hegarty MJ, et al. Using DNA metabarcoding to identify the floral composition of honey: a new tool for investigating honey bee foraging preferences. PLoS ONE. 2015;10;e0134735. doi: 10.1371/journal.pone.0134735 26308362

9. Jain S, Jesus F, Marchioro GM, Divino de Araujo E. Extraction of DNA from honey and its amplification by PCR for botanical identification. Food Science and technology (Campinas). 2013;33(4):753–756. doi: 10.1590/S0101-20612013000400022

10. Laube I, Hird H, Brodmann P, Ullmann S, Schone-Michling M, Chisholm J, et al. Development of primer and probe sets for the detection of plant species in honey. Food Chemistry. 2010;118(4):979–986.

11. Bell KL, Fowler J, Burgess KS, Dobbs EK, Gruenewald D, Lawley B, et al. Applying pollen DNA metabarcoding to the study of plant-pollinator interactions. Applications in Plant Sciences. 2017;5(6):1600124. doi: 10.3732/apps.1600124 28690929

12. Galliot J, Brunel D, Berard A, Chauveau A, Blanchetete A, Lanore L, et al. Investigating a flower-insect forager network in a mountain grassland community using pollen DNA barcoding. Journal of Insect Conservation. 2017;21(5–6):827–837. doi: 10.1007/s10841-017-0022-z

13. Pornon A, Escaravage N, Burrus M, Holota H, Khimoun A, Mariette J, et al. Using metabarcoding to reveal and quantify plant-pollinator interactions. Scientific Reports. 2016;6:27282. doi: 10.1038/srep27282 27255732

14. Sickel W, Ankenbrand MJ, Grimmer G, Holzschuh A, Hartel S, Lanzen J, et al. Increased efficiency in identifying mixed pollen samples by meta-barcoding with a dual-indexing approach. BMC Ecology. 2015;15(1):1–9. doi: 10.1186/s12898-015-0051-y 26194794

15. Folloni S, Kagkli D, Rajcevic B, Guimaraes NCC, Van Droogenbroeck B, Valicente FH, et al. Detection of airborne genetically modified maize pollen by real-time PCR. Molecular Ecology Resources. 2012;12(5):810–821. doi: 10.1111/j.1755-0998.2012.03168.x 22805239

16. Mohanty R, Buchheim M, Levetin E. Molecular approaches for the analysis of airborne pollen a case study of Juniperus pollen. Annals of Alergy, Asthma, and Immunology. 2017;118(2):204–211. doi: 10.1016/j.anai.2016.11.015 28024990

17. Nuñez A, Amo de Paz G, Ferencova Z, Rastrojo A, Guantes R, Garcia A.M, et al. Validation of the hirst-type spore trap for simultaneous monitoring of prokaryotic and eukaryotic biodiversities in urban air samples by next-generation sequencing. Applied and Environmental Microbiology. 2017;83(13):e00472–17. doi: 10.1128/AEM.00472-17 28455334

18. Korpelainen H, Pietilainen M. Biodiversity of pollen in indoor air samples as revealed by DNA metabarcoding. Nordic Journal of Botany. 2017;35:602–608. doi: 10.1111/njb.01623

19. Craine JM, Barberan A, Lynch RC, Menninger HL, Dunn RR, Fierer N. Molecular analysis of environmental plant DNA in house dust across the United States. Aerobiologia. 2016;33(1):71–86. doi: 10.1007/s10453-016-9451-5

20. Hoyt C. Pollen signatures of the arid to humid grasslands of North America. Journal of Biogeography. 2000;27(3):687–696.

21. Lopez-Portillo J, Eguiarte L, Montana C. Nectarless honey mesquites. Functional Ecology. 1993;7(4):452–461. doi: 10.2307/2390032

22. Minckley RL, Roulston TH. Incidental mutualisms and pollen specialization among bees. In Waser NM, Ollerton J, editors. Plant-pollinator Interactions from Specialization to Generalization. Illinois: The University of Chicago Press; 2006. pp 69–68.

23. Zobeck TM. Erosion by wind: Field measurement. Encyclopedia of Soil Science. 2006;1:607–612.

24. Goossens D, Buck BJ. Can BSNE (Big Spring Number Eight) samplers be used to measure PM10, respirable dust, PM2.5 and PM1.0? Aeolian Research. 2012;5;43–49. doi: 10.1016/j.aeolia.2012.03.002

25. Mendez MJ, Funk R, Buschiazzo DE. Efficiency of Big Spring Number Eight (BSNE) and Modified Wilson and Cook (MWAC) samplers to collect PM10, PM2.5 and PM1. Aeolian Research. 2016;21:37–44. doi: 10.1016/j.aeolia.2016.02.003

26. Hurlbert SH. Pseudoreplication and the design of ecological field experiments. Ecological Monographs. 1984;54(2):87–211.

27. Ellison SLR, English CA, Burns MJ, Keer JT. Routes to improving the reliability of low level DNA analysis using real-time PCR. BMC Biotechnology. 2006. doi: 10.1186/1472-6750-6-33 16824215

28. Anderson M. Bouteloua gracilis. Fire Effects Information System. U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station, Fire Science Laboratory. 2003.

29. Riegal A. Life history and habits of blue grama. Transactions of the Kansas Academy of Science. 1941;44:76–85.

30. Golubov J, Mandujano MDC, Franco M, Montana C, Eguiarte LE, Lopez-Portillo J. Demography of the invasive woody perennial Prosopis glandulosa (honey mesquite). Journal of Ecology. 1999;87(6):955–962. doi: 10.1046/j.1365-2745.1999.00420.x

31. Acosta-Martinez V, Van Pelt S, Moore-Kucera J, Baddock MC, Zobeck TM. Microbiology of wind-eroded sediments: current knowledge and future directions. Aeolian Research. 2015;18:99–113. doi: 10.1016/j.aeolia.2015.06.001

32. Lodge DM, Simonin PW, Burgiel SW, Keller RP, Brossenbroek JM, Jerde CL, et al. Risk analysis and bioeconomics of invasive species to inform policy and management. Annual Review of Environment and Resources. 2016;41(17):453–488. doi: 10.1146/annurev-environ-110615-085532

33. Jerde C, Mahon A, Chadderton L, Lodge D. “Sight-unseen” detection of rare aquatic species using environmental DNA. Conservation Letters. 2011;4:150–157. doi: 10.1111/j.1755-263X.2010.00158.x

34. Thomsen F, Kielgast J, Iverse LL, Wiuf C, Rasmussen M, Gilbert TP, et al. Monitoring endangered freshwater biodiversity using environmental DNA. Molecular Ecology. 2012;21(11):2565–2573. doi: 10.1111/j.1365-294X.2011.05418.x 22151771

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