Food from faeces: Evaluating the efficacy of scat DNA metabarcoding in dietary analyses
Autoři:
David Thuo aff001; Elise Furlan aff001; Femke Broekhuis aff002; Joseph Kamau aff004; Kyle Macdonald aff006; Dianne M. Gleeson aff001
Působiště autorů:
Institute for Applied Ecology, University of Canberra, Bruce, Australian Capital Territory, Australia
aff001; Kenya Wildlife Trust, Nairobi, Kenya
aff002; Wildlife Conservation Research Unit, Department of Zoology, University of Oxford, Recanati-Kaplan Centre, Tubney, United Kingdom
aff003; Molecular Biology Laboratory, Institute of Primate Research, Nairobi, Kenya
aff004; Department of Biochemistry, University of Nairobi, Nairobi, Kenya
aff005; National Zoo and Aquarium, Canberra, Yarralumla, Australian Capital Territory, Australia
aff006
Vyšlo v časopise:
PLoS ONE 14(12)
Kategorie:
Research Article
doi:
https://doi.org/10.1371/journal.pone.0225805
Souhrn
Scat DNA metabarcoding is increasingly being used to track the feeding ecology of elusive wildlife species. This approach has greatly increased the resolution and detection success of prey items contained in scats when compared with other classical methods. However, there have been few studies that have systematically tested the applicability and reliability of this approach to study the diet of large felids species in the wild. Here we assessed the effectiveness of this approach in the cheetah Acinonyx jubatus. We tested how scat degradation, meal size, prey species consumed and feeding day (the day a particular prey was consumed) influenced prey DNA detection success in captive cheetahs. We demonstrated that it is possible to obtain diet information from 60-day old scats using genetic approaches, but the efficiency decreased over time. Probability of species-identification was highest for food items consumed one day prior to scat collection and the probability of being able to identify the species consumed increased with the proportion of the prey consumed. Detection success varied among prey species but not by individual cheetah. Identification of prey species using DNA detection methods from a single consumption event worked for samples collected between 8 and 72 hours post-feeding. Our approach confirms the utility of genetic approaches to identify prey species in scats and highlight the need to account for the systematic bias in results to control for possible scat degradation, feeding day, meal size and prey species consumed especially in the wild-collected scats.
Klíčová slova:
Deer – Horses – Chickens – Predation – Quails – Rabbits – Trophic interactions – Cheetahs
Zdroje
1. Wachter B, Blanc AS, Melzheimer J, Höner OP, Jago M, Hofer H. An advanced method to assess the diet of free-ranging large carnivores based on scats. PLoS One. 2012;7(6).
2. Włodzimierz J, Schmidt K, Theuerkauf J, Jedrzejewska B, Selva N, Zub K, et al. Kill Rates and Predation by Wolves on Ungulate Populations in Bia owie a Primeval Forest (Poland). 2002;83(5):1341–56.
3. Ghoddousi A, Soofi M, Hamidi AK, Lumetsberger T, Egli L, Khorozyan I, et al. Assessing the role of livestock in big cat prey choice using spatiotemporal availability patterns. PLoS One. 2016;11(4):1–16.
4. Wittmer HU, Hasenbank M, Elbroch LM, Marshall AJ. Incorporating preferential prey selection and stochastic predation into population viability analysis for rare prey species. Biol Conserv [Internet]. 2014;172:8–14. Available from: https://doi.org/10.1016/j.biocon.2014.02.003
5. Broekhuis F, Thuo D, Hayward MW. Feeding ecology of cheetahs in the Maasai Mara, Kenya and the potential for intra- and interspecific competition. J Zool. 2017;304(1):65–72.
6. Long RA, Donovan TM, Mackay P, Zielinski WJ, Buzas JS. Effectiveness of Scat Detection Dogs for Detecting Forest Carnivores. J Wildl Manage. 2007;71(6):2007–17.
7. Ripple WJ, Estes JA, Beschta RL, Wilmers CC, Ritchie EG, Hebblewhite M, et al. Status and ecological effects of the world’s largest carnivores. Science (80-). 2014;343(6167).
8. Klare U, Kamler JF, MacDonald DW. A comparison and critique of different scat-analysis methods for determining carnivore diet. Mamm Rev. 2011;41(4):294–312.
9. Pompanon F, Deagle BE, Symondson WOC, Brown DS, Jarman SN, Taberlet P. Who is eating what: Diet assessment using next generation sequencing. Mol Ecol. 2012;21(8):1931–50. doi: 10.1111/j.1365-294X.2011.05403.x 22171763
10. Shehzad W, Riaz T, Nawaz MA, Miquel C, Poillot C, Shah SA, et al. Carnivore diet analysis based on next-generation sequencing: Application to the leopard cat (Prionailurus bengalensis) in Pakistan. Mol Ecol. 2012;21(8):1951–65. doi: 10.1111/j.1365-294X.2011.05424.x 22250784
11. De Barba M, Miquel C, Boyer F, Mercier C, Rioux D, Coissac E, et al. DNA metabarcoding multiplexing and validation of data accuracy for diet assessment: Application to omnivorous diet. Mol Ecol Resour. 2014;14(2):306–23. doi: 10.1111/1755-0998.12188 24128180
12. Xiong M, Wang D, Bu H, Shao X, Zhang D, Li S, et al. Molecular dietary analysis of two sympatric felids in the Mountains of Southwest China biodiversity hotspot and conservation implications. Sci Rep [Internet]. 2017;7(December 2016):41909. Available from: http://www.nature.com/articles/srep41909 28195150
13. Deagle BE, Kirkwood R, Jarman SN. Analysis of Australian fur seal diet by pyrosequencing prey DNA in faeces. Mol Ecol. 2009;18(9):2022–38. doi: 10.1111/j.1365-294X.2009.04158.x 19317847
14. Piñol J, San Andrés V, Clare EL, Mir G, Symondson WOC. A pragmatic approach to the analysis of diets of generalist predators: The use of next-generation sequencing with no blocking probes. Mol Ecol Resour. 2014;14(1):18–26. doi: 10.1111/1755-0998.12156 23957910
15. Stein ED, Martinez MC, Stiles S, Miller PE, Zakharov E V. Is DNA barcoding actually cheaper and faster than traditional morphological methods: Results from a survey of freshwater bioassessment efforts in the United States? PLoS One. 2014;9(4).
16. Galan M, Pontier D, Leuchtmann M, Charbonnel N, Tournayre O, Pierre É, et al. Metabarcoding for the parallel identification of several hundred predators and their prey: Application to bat species diet analysis. Mol Ecol Resour. 2017;(December).
17. Riaz T, Shehzad W, Viari A, Pompanon F, Taberlet P, Coissac E. EcoPrimers: Inference of new DNA barcode markers from whole genome sequence analysis. Nucleic Acids Res. 2011;39(21):1–11.
18. Esnaola A, Arrizabalaga-Escudero A, González-Esteban J, Elosegi A, Aihartza J. Determining diet from faeces: Selection of metabarcoding primers for the insectivore Pyrenean desman (Galemys pyrenaicus). PLoS One. 2018;13(12):1–16.
19. Forin-Wiart MA, Poulle ML, Piry S, Cosson JF, Larose C, Galan M. Evaluating metabarcoding to analyse diet composition of species foraging in anthropogenic landscapes using Ion Torrent and Illumina sequencing. Sci Rep. 2018;8(1).
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. Carøe C, Gopalakrishnan S, Vinner L, Mak SST, Sinding MHS, Samaniego JA, et al. Single-tube library preparation for degraded DNA. Methods Ecol Evol. 2018;9(2):410–9.
22. McInnes JC, Deagle BE, Lea M-A, Jarman SN, Alderman R, Raymond B. Optimised scat collection protocols for dietary DNA metabarcoding in vertebrates. Methods Ecol Evol. 2017;8(2):192–202.
23. Oehm J, Juen A, Nagiller K, Neuhauser S, Traugott M. Molecular scatology: How to improve prey DNA detection success in avian faeces? Mol Ecol Resour. 2011;11(4):620–8. doi: 10.1111/j.1755-0998.2011.03001.x 21676193
24. Alberdi A, Aizpurua O, Bohmann K, Gopalakrishnan S, Lynggaard C, Nielsen M, et al. Promises and pitfalls of using high-throughput sequencing for diet analysis. Mol Ecol Resour. 2018;19(2):327–48. doi: 10.1111/1755-0998.12960 30358108
25. Marker LL, Muntifering JR, Dickman AJ, Mills MGL, Macdonald DW. Quantifying prey preferences of free-ranging Namibian cheetahs. 2003;33(April):43–53.
26. Durant, Mitchell N, Groom R, Pettorelli N, Ipavec A, Jacobson AP, et al. The global decline of cheetah Acinonyx jubatus and what it means for conservation. Proc Natl Acad Sci [Internet]. 2017;114(3):528–33. Available from: http://www.pnas.org/lookup/doi/10.1073/pnas.1611122114 28028225
27. Marnewick K, Somers MJ. Home Ranges of Cheetahs (Acinonyx jubatus) Outside Protected Areas in South Africa. African J Wildl Res. 2015;45(2):223–32.
28. Houser A, Somers MJ, Boast LK. Home Range Use of Free-Ranging Cheetah on Farm and Conservation Land in Botswana. South African J Wildl Res. 2009;39(1):11–22.
29. Mills MGL, Broomhall LS, du Toit JT, Toit JT. Cheetah Acinonyx jubatus feeding ecology in the Kruger National Park and a comparison across African savanna habitats: is the cheetah only a successful hunter on open grassland plains? Wildlife Biol. 2004;10(3):177–86.
30. Van Valkenburgh B. Feeding Behavior in Free-Ranging, Large African Carnivores. J Mammal. 2006;77(1):240–54.
31. Craig CA, Brassine EI, Parker DM. A record of cheetah (Acinonyx jubatus) diet in the Northern Tuli Game Reserve, Botswana. Afr J Ecol. 2017;55(4):697–700.
32. Boast L, Houser AM, Horgan J, Reeves H, Phale P, Klein R. Prey preferences of free-ranging cheetahs on farmland: scat analysis versus farmers’ perceptions. Afr J Ecol. 2016;54(4):424–33.
33. Schmidt-küntzel A, Wultsch C, Wachter B, Brummer R, Walker EH, Forsythe K, et al. Mining Black Gold—Insights From Cheetah Scat Using Noninvasive Techniques in the Field and Hormone Analyses [Internet]. Cheetahs. Elsevier Inc.; 2018. 437–446 p. Available from: https://doi.org/10.1016/B978-0-12-804088-1/00031-9
34. Fuller L, Meeks K, Dierenfeld E. Cheetah SSP Captive Body Condition Scores Cheetah SSP Captive Body Condition Scores. Assoc zoos aquariums. 2007;
35. Bus H. EAZA Best Practice Guidelines Cheetah (Acinonyx jubatus). 2018;(July).
36. Bolger AM, Lohse M, Usadel B, H. Trimmomatic: A flexible trimmer for Illumina sequence data. Bioinformatics. 2014;30(15):2114–20. doi: 10.1093/bioinformatics/btu170 24695404
37. Boyer F, Mercier C, Bonin A, Le Bras Y, Taberlet P, Coissac E. obitools: inspired software package for DNA metabarcoding. Mol Ecol Resour [Internet]. 2016 Jan;16(1):176–82. Available from: http://doi.wiley.com/10.1111/1755-0998.12428 25959493
38. Wickham H. Tidyverse: Easily Install and Load the “Tidyverse”. R package version 1.2.1. https://CRAN.R-project.org/package=tidyverse.CRANR-project.org. 2016;
39. Vitalie S, Grolemund G, Wickham H, Lyttle I, Constigan I, Law J, et al. Lubridate Package Manual. 2018;
40. Plummer M. JAGS: A program for analysis of Bayesian graphical models using Gibbs sampling. Int Work Distrib Stat Comput. 2003;3(Dsc):1–10.
41. Kellner K. jagsUI: a wrapper around rjags to streamline JAGS analyses. 2015; Available from: https://github.com/kenkellner/jagsUI
42. R Development Core Team. R: A language and environment for statistical computing [Internet]. Vol. 2, Vienna, Austria. 2015. Available from: http://www.r-project.org/
43. Rubin DB, Gelman A. Inference from Iterative Simulation Using Multiple Sequences. Stat Sci [Internet]. 1992;7(4):457–72. Available from: http://www.jstor.org/stable/2246093%0Ahttp://dash.harvard.edu/handle/1/3630270
44. Thuo DN, Furlan E, Broekhuis F, Kamau J, Macdonald K, Gleeson DM. Data from: Food from faeces: evaluating the efficacy of scat DNA metabarcoding in dietary analyses. Dryad Digit Repos [Internet]. 2019;72. Available from: https://doi.org/10.5061/dryad.2z34tmpgs
45. Kaunisto KM, Roslin T, Sääksjärvi 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
46. Deagle BE, Eveson JP, Jarman SN. Quantification of damage in DNA recovered from highly degraded samples—A case study on DNA in faeces. Front Zool. 2006;3:1–10. doi: 10.1186/1742-9994-3-1
47. Clemens ET, Stevens CE. A comparison of gastrointestinal transit time in ten species of mammal. J Agric Sci. 1980;94(3):735–7.
48. Peachey SE, Dawson JM, Harper EJ. Gastrointestinal transit times in young and old cats. Comp Biochem Physiol—A Mol Integr Physiol. 2000;126(1):85–90. doi: 10.1016/s1095-6433(00)00189-6 10908855
49. Sá FC, Silva FL, Gomes M de OS, Brunetto MA, Bazolli RS, Giraldi T, et al. Comparison of the digestive efficiency of extruded diets fed to ferrets (Mustela putorius furo), dogs (Canis familiaris) and cats (Felis catus). J Nutr Sci. 2014;3:1–5.
50. Weaver JL. Refining the Equation for Interpreting Prey Occurrence in Gray Wolf Scats Author. J Wildl Manage. 1993;57(3):534–8.
51. Deagle BE, Tollit DJ, Jarman SN, Hindell MA, Trites AW, Gales NJ. Molecular scatology as a tool to study diet: Analysis of prey DNA in scats from captive Steller sea lions. Mol Ecol. 2005;14(6):1831–42. doi: 10.1111/j.1365-294X.2005.02531.x 15836654
52. Hofreiter M, Poinar HN, Spaulding WG, Bauer K, Martin PS. A molecular analysis of ground sloth diet through the last glaciation. Mol Ecol. 2000;1975–84. doi: 10.1046/j.1365-294x.2000.01106.x 11123610
53. Thomas AC, Jarman SN, Haman KH, Trites AW, Deagle BE. Improving accuracy of DNA diet estimates using food tissue control materials and an evaluation of proxies for digestion bias. Mol Ecol. 2014;23(15):3706–18. doi: 10.1111/mec.12523 24102760
54. Hart ML, Meyer A, Johnson PJ, Ericsson AC. Comparative evaluation of DNA extraction methods from feces of multiple host species for downstream next-generation sequencing. PLoS One. 2015;10(11):1–16.
55. Markman S. Sex differences in food intake and digestive constraints in a nectarivorous bird. J Exp Biol. 2006;209(6):1058–63.
56. King RA, Vaughan IP, Bell JR, Bohan DA, Symondson WOC. Prey choice by carabid beetles feeding on an earthworm community analysed using species- and lineage-specific PCR primers. Mol Ecol. 2010;19(8):1721–32. doi: 10.1111/j.1365-294X.2010.04602.x 20345680
57. Greenstone MH, Payton ME, Weber DC, Simmons AM. The detectability half-life in arthropod predator-prey research: What it is, why we need it, how to measure it, and how to use it. Mol Ecol. 2014;23(15):3799–813. doi: 10.1111/mec.12552 24303920
58. Thalinger B, Oehm J, Obwexer A, Traugott M. The influence of meal size on prey DNA detectability in piscivorous birds. Mol Ecol Resour. 2017;17(6):e174–86. doi: 10.1111/1755-0998.12706 28776942
59. Eaton R. The Cheetah—The biology, ecology, and behavior of an endangered species. New York: Van Nostrand Reinhold Company; p 41–87. 1974;
60. Mills MGL. A Comparison of Methods Used to Study Food Habits of Large African Carnivores. Wildl 2001 Popul. 1992;1112–24.
61. Vestheim H, Deagle BE, Jarman SN. Application of Blocking Oligonucleotides to Improve Signal-to-Noise Ratio in a PCR. In: Plant Science [Internet]. 2011. p. 265–74. Available from: http://link.springer.com/10.1007/978-1-60761-944-4_19
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