A fecal sequel: Testing the limits of a genetic assay for bat species identification


Autoři: Faith M. Walker aff001;  Abby Tobin aff001;  Nancy B. Simmons aff003;  Colin J. Sobek aff001;  Daniel E. Sanchez aff001;  Carol L. Chambers aff001;  Viacheslav Y. Fofanov aff004
Působiště autorů: Bat Ecology & Genetics Lab, School of Forestry, Northern Arizona University, Flagstaff, Arizona, United States of America aff001;  Pathogen and Microbiome Institute, Northern Arizona University, Flagstaff, Arizona, United States of America aff002;  Department of Mammalogy, Division of Vertebrate Zoology, American Museum of Natural History, New York, New York, United States of America aff003;  School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, Arizona, United States of America aff004
Vyšlo v časopise: PLoS ONE 14(11)
Kategorie: Research Article
doi: 10.1371/journal.pone.0224969

Souhrn

DNA metabarcoding assays are powerful tools for delving into the DNA in wildlife feces, giving unprecedented ability to detect species, understand natural history, and identify pathogens for a range of applications in management, conservation, and research. Next-generation sequencing technology is developing rapidly, which makes it especially important that predictability and reproducibility of DNA metabarcoding assays are explored together with the post-depositional ecology of the target taxon’s fecal DNA. Here, we defined the constraints of an assay called ‘Species from Feces’ used by government agencies, research groups, and non-governmental organizations to identify bat species from guano. We tested assay sensitivity by examining how time and humidity affect the ability to recover and successfully sequence DNA in guano, assessing whether a fecal pellet from a rare bat species could be detected in a background of feces from other bat species, and evaluating the efficacy of Species from Feces as a survey tool for bat roosts in temperate and tropical areas. We found that the assay performs well with feces over two years old in dry, cool environments, and fails by 12 months at 100% relative humidity. We also found that it reliably identifies rare DNA, has great utility for surveying roosts in temperate and tropical regions, and detects more bat species than do visual surveys. We attribute the success of Species from Feces to characteristics of the assay paired with application in taxa that are particularly well-suited for fecal DNA survival. In a time of rapid evolution of DNA metabarcoding approaches and their use with feces, this study illustrates the strengths and limitations of applied assays.

Klíčová slova:

Archaeology – Bats – DNA – DNA extraction – DNA sequencing – Humidity – Sequence assembly tools – Taxonomy


Zdroje

1. Batovska J, Lynch SE, Cogan NOI, Brown K, Darbro JM, Kho EA, et al. Effective mosquito and arbovirus surveillance using metabarcoding. Mol Ecol Resour. 2018;18(1):32–40. doi: 10.1111/1755-0998.12682 28417591

2. Kaunisto KM, Roslin T, Saaksjarvi IE, Vesterinen EJ. Pellets of proof: First glimpse of the dietary composition of adult odonates as revealed by metabarcoding of feces. Ecol Evol. 2017;7(20):8588–98. doi: 10.1002/ece3.3404 29075474

3. Walker FM, Williamson CHD, Sanchez DE, Sobek CJ, Chambers CL. Species From Feces: Order-Wide Identification of Chiroptera From Guano and Other Non-Invasive Genetic Samples. PLoS One. 2016;11(9):e0162342. doi: 10.1371/journal.pone.0162342 27654850

4. Taberlet P, Waits LP, Luikart G. Noninvasive genetic sampling: look before you leap. Trends Ecol Evol. 1999;14(8):323–7. doi: 10.1016/s0169-5347(99)01637-7 10407432

5. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. QIIME allows analysis of high-throughput community sequencing data. Nature Methods. 2010;7(5):335–6. doi: 10.1038/nmeth.f.303 20383131

6. Bolyen E, Rideout JR, Dillon MR, Bokulich NA, Abnet C, Al-Ghalith GA, et al. Reproducible, interactive, scalable, and extensible microbiome data science using QIIME 2. Nat Biotechnol. 2019;8:852–7.

7. Shokralla S, Porter TM, Gibson JF, Dobosz R, Janzen DH, Hallwachs W, et al. Massively parallel multiplex DNA sequencing for specimen identification using an Illumina MiSeq platform. Scientific Reports. 2015;5:7.

8. Kerley GIH, Landman M, Ficetola GF, Boyer F, Bonin A, Rioux D, et al. Diet shifts by adult flightless dung beetles Circellium bacchus, revealed using DNA metabarcoding, reflect complex life histories. Oecologia. 2018;188(1):107–15. doi: 10.1007/s00442-018-4203-6 29961180

9. Poole KG, Reynolds DM, Mowat G, Paetkau D. Estimating Mountain Goat Abundance Using DNA From Fecal Pellets. Journal of Wildlife Management. 2011;75(6):1527–34.

10. Murphy MA, Kendall KC, Robinson A, Waits LP. The impact of time and field conditions on brown bear (Ursus arctos) faecal DNA amplification. Conservation Genetics. 2007;8(5):1219–24.

11. Maudet C, Luikart G, Dubray D, Von Hardenberg A, Taberlet P. Low genotyping error rates in wild ungulate faeces sampled in winter. Molecular Ecology Notes. 2004;4(4):772–5.

12. Lucchini V, Fabbri E, Marucco F, Ricci S, Boitani L, Randi E. Noninvasive molecular tracking of colonizing wolf (Canis lupus) packs in the western Italian Alps. Molecular Ecology. 2002;11(5):857–68. doi: 10.1046/j.1365-294x.2002.01489.x 11975702

13. Harestad AS, Bunnell FL. Persistence of black-tailed deer fecal pellets in coastal habitats. Journal of Wildlife Management. 1987;51(1):33–7.

14. Ravanat JL, Douki T, Cadet J. Direct and indirect effects of UV radiation on DNA and its components. Journal of Photochemistry and Photobiology B-Biology. 2001;63(1–3):88–102.

15. King S, Schoenecker K, Fike J, Oyler-McCance S. Long-term persistence of horse fecal DNA in the environment makes equids particularly good candidates for noninvasive sampling. Ecol Evol. 2018;8:4053–64. doi: 10.1002/ece3.3956 29721279

16. Panasci M, Ballard WB, Breck S, Rodriguez D, Densmore LD, Wester DB, et al. Evaluation of fecal DNA preservation techniques and effects of sample age and diet on genotyping success. Journal of Wildlife Management. 2011;75:1616–24.

17. Fofanov VY, Furstenau TN, Sanchez DE, Hepp CM, Cocking J, Sobek CJ, et al. Guano exposed: Impact of aerobic conditions on bat fecal microbiota. Ecol Evol. 2018:1–12.

18. Drakulovski P, Locatelli S, Butel C, Pion S, Krasteva D, Mougdi-Pole E, et al. Use of RNAlater (R) as a preservation method for parasitic coprology studies in wild-living chimpanzees. Experimental Parasitology. 2013;135(2):257–61. doi: 10.1016/j.exppara.2013.07.002 23850999

19. Walker FM, Horsup A, Taylor AC. Leader of the pack: faecal pellet deposition order impacts PCR amplification in wombats. Mol Ecol Resour. 2009;9(3):720–4. doi: 10.1111/j.1755-0998.2009.02582.x 21564730

20. Divoll TJ, Brown VA, Kinne J, McCracken GF, O’Keefe JM. Disparities in second-generation DNA metabarcoding results exposed with accessible and repeatable workflows. Mol Ecol Resour. 2018;18(3):590–601. doi: 10.1111/1755-0998.12770 29455464

21. Cassey P, Blackburn TM. Reproducibility and repeatability in ecology. Bioscience. 2006;56(12):958–9.

22. Walker FM. Bat "Species from Feces" Online Search Tool 2016 https://www5.nau.edu/cefns/forestry/research/bats/public/index/

23. Heim O, Puisto AIE, Fukui D, Vesterinen EJ. Molecular evidence of bird-eating behavior in Nyctalus aviator. Acta Ethologica. 2019.

24. Tobin A, Corbett RJM, Walker FM, Chambers CL. Acceptance of bats to gates at abandoned mines. Journal of Wildlife Management. 2018;82(7):1345–58.

25. Vesterinen EJ, Puisto AIE, Blomberg AS, Lilley TM. Table for five, please: Dietary partitioning in boreal bats. Ecol Evol. 2018;8(22):10914–37. doi: 10.1002/ece3.4559 30519417

26. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. Journal of Molecular Biology. 1990;215:403–10. doi: 10.1016/S0022-2836(05)80360-2 2231712

27. Colman RE, Schupp JM, Hicks ND, Smith DE, Buchhagen JL, Valafar F, et al. Detection of Low-Level Mixed-Population Drug Resistance in Mycobacterium tuberculosis Using High Fidelity Amplicon Sequencing. PLoS One. 2015;10(5):e0126626. doi: 10.1371/journal.pone.0126626 25970423

28. Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnetJournal. 2011;17(1):10–2.

29. Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, et al. Introducing mothur: Open-Source, Platform-Independent, Community-Supported Software for Describing and Comparing Microbial Communities. Appl Environ Microbiol. 2009;75(23):7537–41. doi: 10.1128/AEM.01541-09 19801464

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. Rognes T, Flouri T, Nichols B, Quince C, Mahe F. VSEARCH: a versatile open source tool for metagenomics. Peerj. 2016;4:22.

32. Wang Q, Garrity GM, Tiedje JM, Cole JR. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol. 2007;73(16):5261–7. doi: 10.1128/AEM.00062-07 17586664

33. Meier L, Garcia J, editors. Importance of mines for bat conservation. Proceedings of bat conservation and mining: a technical interactive forum; 2001; St. Louis, Missouri, USA: Office of Surface Mining Reclamation and Enforcement.

34. Ramsey FL, Schafer DW. The statistical sleuth. Belmont, CA: Duxbury Press; 1997.

35. Fenton MB, Bernard E, Bouchard S, Hollis L, Johnston DS, Lausen CL, et al. The bat fauna of Lamanai, Belize: Roosts and trophic roles. Journal of Tropical Ecology. 2001;17:511–24.

36. Herrera JP, Duncan N, Clare E, Fenton MB, Simmons N. Disassembly of fragmented bat communities in Orange Walk District, Belize. Acta Chiropt. 2018;20(1):147–59.

37. Lambert JDH, Arnason T. Distribution of vegetation on Maya ruins and its relationship to ancient land-use at Lamanai, Belize. Turrialba. 1978;28(1):33–41.

38. Eckert KA, Hahn NE, Genz A, Kitchen DM, Stuart MD, Averbeck GA, et al. Coprological Surveys of Alouatta pigra at Two Sites in Belize. International Journal of Primatology. 2006;27(1):227–38.

39. Bobrowiec PED, Lemes MR, Gribel R. Prey preference of the common vampire bat (Desmodus rotundus, Chiroptera) using molecular analysis. Journal of Mammalogy. 2015;96(1):54–63.

40. Brigham RM, Broders HG, Toth CA, Reimer JP, Barclay RMR. Observations on the roosting and foraging behavior of Woolly false vampire bats, Chrotopterus auritus, in Belize. Caribbean Naturalist. 2018;47:1–7.

41. Becker DJ, Czirják GA, Volokhov DV, Bentz AB, Carrera JE, Camus MS, et al. Livestock abundance predicts vampire bat demography, immune profiles, and bacterial infection risk. Phil Trans Roy Soc London B 2018;373.

42. Ando H, Fujii C, Kawanabe M, Ao Y, Inoue T, Takenaka A. Evaluation of plant contamination in metabarcoding diet analysis of a herbivore. Scientific Reports. 2018;8(1):15563. doi: 10.1038/s41598-018-32845-w 30349088

43. McInnes JC, Alderman R, Deagle BE, Lea MA, Raymond B, Jarman SN. Optimised scat collection protocols for dietary DNA metabarcoding in vertebrates. Methods in Ecology and Evolution. 2017;8(2):192–202.

44. Lindahl T. Instability and decay of the primary structure of DNA. Nature. 1993;362:709. doi: 10.1038/362709a0 8469282

45. 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;10(7):e0130324. doi: 10.1371/journal.pone.0130324 26154168

46. Nelson MC, Morrison HG, Benjamino J, Grim SL, Graf J. Analysis, Optimization and Verification of Illumina-Generated 16S rRNA Gene Amplicon Surveys. PLoS One. 2014;9(4):e94249. doi: 10.1371/journal.pone.0094249 24722003

47. Kircher M, Sawyer S, Meyer M. Double indexing overcomes inaccuracies in multiplex sequencing on the Illumina platform. Nucleic Acids Res. 2012;40(1):8.

48. Blehert DS, Hicks AC, Behr M, Meteyer CU, Berlowski-Zier BM, Buckles EL, et al. Bat white-nose syndrome: an emerging fungal pathogen? Science. 2009;323(5911):227. doi: 10.1126/science.1163874 18974316

49. Langwig KE, Hoyt JR, Parise KL, Kath J, Kirk D, Frick WF, et al. Invasion Dynamics of White-Nose Syndrome Fungus, Midwestern United States, 2012–2014. Emerg Infect Dis. 2015;21(6):1023–6. doi: 10.3201/eid2106.150123 25989230

50. Michalski F, Valdez FP, Norris D, Zieminski C, Kashivakura CK, Trinca CS, et al. Successful carnivore identification with faecal DNA across a fragmented Amazonian landscape. Mol Ecol Resour. 2011;11(5):862–71. doi: 10.1111/j.1755-0998.2011.03031.x 21676206

51. Vynne C, Baker MR, Breuer ZK, Wasser SK. Factors influencing degradation of DNA and hormones in maned wolf scat. Animal Conservation. 2012;15(2):184–94.


Článek vyšel v časopise

PLOS One


2019 Číslo 11