Molecular sequencing and morphological identification reveal similar patterns in native bee communities across public and private grasslands of eastern North Dakota

English version

Autoři: Brian Darby ^aff001; Russ Bryant ^aff002; Abby Keller ^aff001; Madison Jochim ^aff001; Josephine Moe ^aff001; Zoe Schreiner ^aff001; Carrie Pratt ^aff001; Ned H. Euliss, Jr. ^aff002; Mia Park ^aff001; Rebecca Simmons ^aff001; Clint Otto ^aff002
Působiště autorů: Department of Biology, University of North Dakota, Grand Forks, North Dakota, United States of America ^aff001; U.S. Geological Survey, Northern Prairie Wildlife Research Center, Jamestown, North Dakota, United States of America ^aff002; Humboldt State University, College of Natural Resources and Sciences, Arcata, North Dakota, United States of America ^aff003; Department of Biological Sciences, North Dakota State University, Fargo, North Dakota, United States of America ^aff004
Vyšlo v časopise: PLoS ONE 15(1)
Kategorie: Research Article
doi: https://doi.org/10.1371/journal.pone.0227918

Souhrn

Bees play a key role in the functioning of human-modified and natural ecosystems by pollinating agricultural crops and wild plant communities. Global pollinator conservation efforts need large-scale and long-term monitoring to detect changes in species’ demographic patterns and shifts in bee community structure. The objective of this project was to test a molecular sequencing pipeline that would utilize a commonly used locus, produce accurate and precise identifications consistent with morphological identifications, and generate data that are both qualitative and quantitative. We applied this amplicon sequencing pipeline to native bee communities sampled across Conservation Reserve Program (CRP) lands and native grasslands in eastern North Dakota. We found the 28S LSU locus to be more capable of discriminating between species than the 18S SSU rRNA locus, and in some cases even resolved instances of cryptic species or morphologically ambiguous species complexes. Overall, we found the amplicon sequencing method to be a qualitatively accurate representation of the sampled bee community richness and species identity, especially when a well-curated database of known 28S LSU sequences is available. Both morphological identification and molecular sequencing revealed similar patterns in native bee community structure across CRP lands and native prairie. Additionally, a genetic algorithm approach to compute taxon-specific correction factors using a small subset of the most concordant samples demonstrated that a high level of quantitative accuracy could be possible if the specimens are fresh and processed soon after collection. Here we provide a first step to a molecular pipeline for identifying insect pollinator communities. This tool should prove useful for future national monitoring efforts as use of molecular tools becomes more affordable and as numbers of 28S LSU sequences for pollinator species increase in publicly-available databases.

Klíčová slova:

Bees – Genetic algorithms – Grasslands – Polymerase chain reaction – Ribosomal RNA – Sequence databases – Species diversity – Taxonomy

Zdroje

1. Klein A-M, Vaissière BE, Cane JH, Steffan-Dewenter I, Cunningham SA, Kremen C, et al. Importance of pollinators in changing landscapes for world crops. Proceedings of the Royal Society B: Biological Sciences. 2007;274(1608):303–13. doi: 10.1098/rspb.2006.3721 17164193

2. National Research Council. Status of Pollinators in North America. Washington, DC: The National Academies Press; 2007. 326 p.

3. Gallai N, Salles J-M, Settele J, Vaissière BE. Economic valuation of the vulnerability of world agriculture confronted with pollinator decline. Ecological Economics. 2009;68(3):810–21. https://doi.org/10.1016/j.ecolecon.2008.06.014.

4. Cameron SA, Lozier JD, Strange JP, Koch JB, Cordes N, Solter LF, et al. Patterns of widespread decline in North American bumble bees. Proceedings of the National Academy of Sciences. 2011;108(2):662–7. doi: 10.1073/pnas.1014743108 21199943

5. Bartomeus I, Ascher JS, Gibbs J, Danforth BN, Wagner DL, Hedtke SM, et al. Historical changes in northeastern US bee pollinators related to shared ecological traits. Proceedings of the National Academy of Sciences. 2013;110(12):4656–60. doi: 10.1073/pnas.1218503110 23487768

6. Koh I, Lonsdorf EV, Williams NM, Brittain C, Isaacs R, Gibbs J, et al. Modeling the status, trends, and impacts of wild bee abundance in the United States. Proceedings of the National Academy of Sciences. 2016;113(1):140–5. doi: 10.1073/pnas.1517685113 26699460

7. Goulson D, Nicholls E, Botías C, Rotheray EL. Bee declines driven by combined stress from parasites, pesticides, and lack of flowers. Science. 2015;347(6229):1255957. doi: 10.1126/science.1255957 25721506

8. Pollinator Task Force. Pollinator Research Action Plan 2015. Available from: http://www.whitehouse.gov/sites/default/files/microsites/ostp/pollinator_research_action_plan_2015.pdf.

9. Droege S, Tepedino VJ, Lebuhn G, Link W, Minckley RL, Chen Q, et al. Spatial patterns of bee captures in North American bowl trapping surveys. Insect Conservation and Diversity. 2010;3(1):15–23. doi: 10.1111/j.1752-4598.2009.00074.x

10. Michener CD. The Bees of the World: Johns Hopkins University Press; 2007.

11. Wheeler Q. What would NASA do? Mission-critical infrastructure for species exploration. Systematics and Biodiversity. 2010;8(1):11–5. doi: 10.1080/14772001003628075

12. Jha S, Kremen C. Resource diversity and landscape-level homogeneity drive native bee foraging. Proceedings of the National Academy of Sciences. 2013;110(2):555–8. doi: 10.1073/pnas.1208682110 23267118

13. McArt SH, Urbanowicz C, McCoshum S, Irwin RE, Adler LS. Landscape predictors of pathogen prevalence and range contractions in US bumblebees. Proceedings of the Royal Society B: Biological Sciences. 2017;284(1867):20172181. doi: 10.1098/rspb.2017.2181 29142119

14. Vaudo AD, Fritz ML, López-Uribe MM. Opening the Door to the Past: Accessing Phylogenetic, Pathogen, and Population Data From Museum Curated Bees. Insect Systematics and Diversity. 2018;2(5). doi: 10.1093/isd/ixy014

15. Lozier JD, Zayed A. Bee conservation in the age of genomics. Conservation Genetics. 2017;18(3):713–29. doi: 10.1007/s10592-016-0893-7

16. Johnson WC, Millett BV, Gilmanov T, Voldseth RA, Guntenspergen GR, and Naugle DE. Vulnerability of Northern Prairie Wetlands to Climate Change. Bioscience. 2005;55:863–872

17. Otto CRV, O’Dell S, Bryant RB, Euliss NH Jr., Bush RM, Smart MD. Using Publicly Available Data to Quantify Plant–Pollinator Interactions and Evaluate Conservation Seeding Mixes in the Northern Great Plains. Environmental Entomology. 2017;46(3):565–78. doi: 10.1093/ee/nvx070 28472369

18. Evans E, Smart M, Cariveau D, Spivak M. Wild, native bees and managed honey bees benefit from similar agricultural land uses. Agriculture, Ecosystems & Environment. 2018;268:162–70. https://doi.org/10.1016/j.agee.2018.09.014.

19. Bendel CR, Kral-O'Brien KC, Hovick TJ, Limb RF, Harmon JP. Plant–pollinator networks in grassland working landscapes reveal seasonal shifts in network structure and composition. Ecosphere. 2019;10(1):e02569. doi: 10.1002/ecs2.2569

20. Otto CRV, Roth CL, Carlson BL, Smart MD. Land-use change reduces habitat suitability for supporting managed honey bee colonies in the Northern Great Plains. Proceedings of the National Academy of Sciences. 2016;113(37):10430–5. doi: 10.1073/pnas.1603481113 27573824

21. Otto CRV, Zheng H, Gallant AL, Iovanna R, Carlson BL, Smart MD, et al. Past role and future outlook of the Conservation Reserve Program for supporting honey bees in the Great Plains. Proceedings of the National Academy of Sciences. 2018;115(29):7629–34. doi: 10.1073/pnas.1800057115 29967144

22. Durant JL, Otto CRV. Feeling the sting? Addressing land-use changes can mitigate bee declines. Land Use Policy. 2019;87:104005. https://doi.org/10.1016/j.landusepol.2019.05.024.

23. Farm Service Agency. 2019 Conservation Reserve Program Statistics [October 02, 2019]. Available from: https://www.fsa.usda.gov/programs-and-services/conservation-programs/reports-and-statistics/conservation-reserve-program-statistics/index.

24. Stephen WP, Rao S. Unscented Color Traps for non-Apis Bees (Hymenoptera: Apiformes). Journal of the Kansas Entomological Society. 2005;78(4):373–80, 8.

25. Danforth BN. Phylogeny of the bee genus Lasioglossum (Hymenoptera: Halictidae) based on mitochondrial COI sequence data. Systematic Entomology. 1999;24(4):377–93. doi: 10.1046/j.1365-3113.1999.00087.x

26. Mardulyn P, Whitfield JB. Phylogenetic Signal in the COI, 16S, and 28S Genes for Inferring Relationships among Genera of Microgastrinae (Hymenoptera; Braconidae): Evidence of a High Diversification Rate in This Group of Parasitoids. Molecular Phylogenetics and Evolution. 1999;12(3):282–94. doi: 10.1006/mpev.1999.0618 10413623

27. Arias MC, Sheppard WS. Phylogenetic relationships of honey bees (Hymenoptera:Apinae:Apini) inferred from nuclear and mitochondrial DNA sequence data. Molecular Phylogenetics and Evolution. 2005;37(1):25–35. doi: 10.1016/j.ympev.2005.02.017 16182149

28. Patiny S, Michez D, Danforth BN. Phylogenetic relationships and host-plant evolution within the basal clade of Halictidae (Hymenoptera, Apoidea). Cladistics. 2008;24(3):255–69. doi: 10.1111/j.1096-0031.2007.00182.x

29. Edgar RC, Flyvbjerg H. Error filtering, pair assembly and error correction for next-generation sequencing reads. Bioinformatics. 2015;31(21):3476–82. doi: 10.1093/bioinformatics/btv401 26139637

30. Edgar RC. Search and clustering orders of magnitude faster than BLAST. Bioinformatics. 2010;26(19):2460–1. doi: 10.1093/bioinformatics/btq461 20709691

31. Edgar RC. UPARSE: highly accurate OTU sequences from microbial amplicon reads. Nature Methods. 2013;10:996. doi: 10.1038/nmeth.2604 23955772

32. Edgar RC. MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics. 2004;5(1):113. doi: 10.1186/1471-2105-5-113 15318951

33. Edgar RC. UNOISE2: improved error-correction for Illumina 16S and ITS amplicon sequencing. bioRxiv. 2016:081257. doi: 10.1101/081257

34. Cock PJA, Antao T, Chang JT, Chapman BA, Cox CJ, Dalke A, et al. Biopython: freely available Python tools for computational molecular biology and bioinformatics. Bioinformatics. 2009;25(11):1422–3. doi: 10.1093/bioinformatics/btp163 19304878

35. Stoddard SF, Smith BJ, Hein R, Roller BRK, Schmidt TM. rrnDB: improved tools for interpreting rRNA gene abundance in bacteria and archaea and a new foundation for future development. Nucleic Acids Research. 2014. doi: 10.1093/nar/gku1201 25414355

36. Darby BJ, Todd TC, Herman MA. High-throughput amplicon sequencing of rRNA genes requires a copy number correction to accurately reflect the effects of management practices on soil nematode community structure. Molecular Ecology. 2013;22:5456–71. doi: 10.1111/mec.12480 24103081

37. Hsieh TC, Ma KH, Chao A. iNEXT: an R package for rarefaction and extrapolation of species diversity (Hill numbers). Methods in Ecology and Evolution. 2016;7(12):1451–6. doi: 10.1111/2041-210x.12613

38. Chao A, Gotelli NJ, Hsieh TC, Sander EL, Ma KH, Colwell RK, et al. Rarefaction and extrapolation with Hill numbers: a framework for sampling and estimation in species diversity studies. Ecological Monographs. 2014;84(1):45–67. doi: 10.1890/13-0133.1

39. Oksanen J, Blanchet FG, Kindt R, Legendre P, Minchin P, O’Hara RB, et al. Vegan: Community Ecology Package. R Package Version. 2.0–10. CRAN. 2013.

40. Samways MJ. Insects in biodiversity conservation: some perspectives and directives. Biodiversity & Conservation. 1993;2(3):258–82. doi: 10.1007/bf00056672

41. Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, Fierer N, et al. Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J. 2012;6(8):1621–4. doi: 10.1038/ismej.2012.8 22402401

42. Ihrmark K, Bödeker ITM, Cruz-Martinez K, Friberg H, Kubartova A, Schenck J, et al. New primers to amplify the fungal ITS2 region–evaluation by 454-sequencing of artificial and natural communities. Fems Microbiology Ecology. 2012;82(3):666–77. doi: 10.1111/j.1574-6941.2012.01437.x 22738186

43. Amaral-Zettler LA, McCliment EA, Ducklow HW, Huse SM. A Method for Studying Protistan Diversity Using Massively Parallel Sequencing of V9 Hypervariable Regions of Small-Subunit Ribosomal RNA Genes. PLoS ONE. 2009;4(7):e6372. doi: 10.1371/journal.pone.0006372 19633714

44. Smart MD, Cornman RS, Iwanowicz DD, McDermott-Kubeczko M, Pettis JS, Spivak MS, et al. A Comparison of Honey Bee-Collected Pollen From Working Agricultural Lands Using Light Microscopy and ITS Metabarcoding. Environmental Entomology. 2017;46(1):38–49. doi: 10.1093/ee/nvw159 28062536

45. Pruesse E, Quast C, Knittel K, Fuchs BM, Ludwig W, Peplies Jr, et al. SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Research. 2007;35(21):7188–96. doi: 10.1093/nar/gkm864 17947321

46. Kumar A, Rai KS. Chromosomal localization and copy number of 18s + 28S ribosomal RNA genes in evolutionarily diverse mosquitoes (Diptera, Culicidae). Hereditas. 1990;113(3):277–89. doi: 10.1111/j.1601-5223.1990.tb00094.x 2093704

47. Donovan TM, Flather CH. Relationships among North American songbird trends, habitat fragmentation, and landscape occupancy. Ecological Applications. 2002;12(2):364–74. doi: 10.1890/1051-0761(2002)012[0364:ranast]2.0.co;2

48. Grant EHC, Miller DAW, Schmidt BR, Adams MJ, Amburgey SM, Chambert T, et al. Quantitative evidence for the effects of multiple drivers on continental-scale amphibian declines. Scientific Reports. 2016;6:25625. doi: 10.1038/srep25625 27212145

49. MacKenzie DI, Nichols JD, Royle JA, Pollock KH, Bailey LL, Hines JE. Occupancy Estimation and Modeling: Inferring Patterns and Dynamics of Species Occurrence. Burlington, MA: Elsevier/Academic Press; 2006.

50. Yoccoz NG, Nichols JD, Boulinier T. Monitoring of biological diversity in space and time. Trends in Ecology & Evolution. 2001;16(8):446–53. doi: 10.1016/S0169-5347(01)02205-4

51. Potts SG, Vulliamy B, Dafni A, Ne'eman G, Willmer P. Linking bees and flowers: how do floral communities structure pollinator communities? Ecology. 2003;84(10):2628–42. doi: 10.1890/02-0136

52. Williams NM, Ward KL, Pope N, Isaacs R, Wilson J, May EA, et al. Native wildflower plantings support wild bee abundance and diversity in agricultural landscapes across the United States. Ecological Applications. 2015;25(8):2119–31. doi: 10.1890/14-1748.1 26910943

Molecular sequencing and morphological identification reveal similar patterns in native bee communities across public and private grasslands of eastern North Dakota

Souhrn

Klíčová slova:

Zdroje

PLOS One

INSIGHTS from European Respiratory Congress

Současné pohledy na riziko v parodontologii

Svět praktické medicíny 3/2024 (znalostní test z časopisu)

Kardiologické projevy hypereozinofilií

Střevní příprava před kolonoskopií