The microbiome of New World vultures

  • Nature Communications 5, Article number: 5498 (2014)
  • doi:10.1038/ncomms6498
  • Download Citation
Published online:


Vultures are scavengers that fill a key ecosystem niche, in which they have evolved a remarkable tolerance to bacterial toxins in decaying meat. Here we report the first deep metagenomic analysis of the vulture microbiome. Through face and gut comparisons of 50 vultures representing two species, we demonstrate a remarkably conserved low diversity of gut microbial flora. The gut samples contained an average of 76 operational taxonomic units (OTUs) per specimen, compared with 528 OTUs on the facial skin. Clostridia and Fusobacteria, widely pathogenic to other vertebrates, dominate the vulture’s gut microbiota. We reveal a likely faecal–oral–gut route for their origin. DNA of prey species detectable on facial swabs was completely degraded in the gut samples from most vultures, suggesting that the gastrointestinal tracts of vultures are extremely selective. Our findings show a strong adaption of vultures and their bacteria to their food source, exemplifying a specialized host–microbial alliance.

Additional access options:

Already a subscriber?  Log in  now or  Register  for online access.

Change history

  • Updated online 21 October 2015

    The original version of this Article contained an error in the spelling of the author Thomas Sicheritz-Pontén, which was incorrectly given as Thomas Sicheritz Pontén. This has now been corrected in both the PDF and HTML versions of the Article.


  1. 1.

    Beyond the grave—understanding human decomposition. Microbiol. Today 28, 190–193 (2001).

  2. 2.

    & The role of avian carcasses in botulism epizootics. Wildl. Soc. Bull. 20, 175–182 (1992).

  3. 3.

    Taphonomic effects of vulture scavenging. J Forensic Sci. 54, 523–528 (2009).

  4. 4.

    et al. Botulinum neurotoxin is shielded by NTNHA in an interlocked complex. Science 335, 977–981 (2002).

  5. 5.

    & The digestive tract of the whiteback griffon vulture and its role in disease transmission among wild ungulates. J. Wildl. Dis. 11, 306–313 (1975).

  6. 6.

    et al. Blocking human contaminant DNA during PCR allows amplification of rare mammal species from sedimentary ancient DNA. Mol. Ecol. 21, 1806–1815 (2012).

  7. 7.

    et al. Carrion fly‐derived DNA as a tool for comprehensive and cost‐effective assessment of mammalian biodiversity. Mol. Ecol. 22, 915–924 (2013).

  8. 8.

    et al. Metabarcoding avian diets at airports: implications for birdstrike hazard management planning. Investig. Genet. 4, 27 (2013).

  9. 9.

    Human Microbiome Project, C.. Structure, function and diversity of the healthy human microbiome. Nature 486, 207–214 (2012).

  10. 10.

    et al. The living dead: Bacterial community structure of a cadaver at the onset and end of the bloat stage of decomposition. PLoS ONE 8, e77733 (2013).

  11. 11.

    & The skin microbiome. Nat. Rev. Microbiol. 9, 244–253 (2011).

  12. 12.

    et al. Co-habiting amphibian species harbor unique skin bacterial communities in wild populations. ISME J. 6, 588–596 (2012).

  13. 13.

    et al. Diversity of the human skin microbiome early in life. J. Invest. Dermatol. 131, 2026–2032 (2011).

  14. 14.

    et al. Evolution of mammals and their gut microbes. Science 320, 1647–1651 (2008).

  15. 15.

    et al. Diet rapidly and reproducibly alters the human gut microbiome. Nature 505, 559–563 (2013).

  16. 16.

    , & The alligator gut microbiome and implications for archosaur symbioses. Sci. Rep. 3, 2877 (2013).

  17. 17.

    & Sporeforming anaerobic Bacilli. ed Baron S.) Medical Microbiology 4, Ch. 18University of Texas Medical Branch at Galveston (1996).

  18. 18.

    , & Epidemiology of foodborne disease outbreaks caused by Clostridium perfringens, United States, 1998-2010. Foodborne Pathog. Dis. 10, 131–136 (2013).

  19. 19.

    et al. Clostridium perfringens in poultry: an emerging threat for animal and public health. Avian Pathol. 33, 537–549 (2004).

  20. 20.

    , & An outbreak of botulism in waterfowl and fly larvae in New York State. J. Wildl. Dis. 20, 86–89 (1984).

  21. 21.

    , & Disease emergence in birds: challenges for the twenty-first century. Auk 118, 290–303 (2001).

  22. 22.

    et al. Fusobacterium nucleatum promotes colorectal carcinogenesis by modulating E-Cadherin/β-Catenin signaling via its FadA adhesin. Cell Host Microbe 14, 195–206 (2013).

  23. 23.

    et al. Fusobacterium nucleatum potentiates intestinal tumorigenesis and modulates the tumor-immune microenvironment. Cell Host Microbe 14, 207–215 (2013).

  24. 24.

    et al. Antibodies to Clostridium botulinum toxins in free-living birds and mammals. J. Wildl. Dis. 15, 3–9 (1979).

  25. 25.

    et al. The gut microbiome modulates colon tumorigenesis. MBio 4, e00692–13 (2013).

  26. 26.

    Reproducibility of ancient DNA sequences from extinct Pleistocene fauna. Mol. Biol. Evol. 13, 283–285 (1996).

  27. 27.

    & Blocking primers to enhance PCR amplification of rare sequences in mixed samples–a case study on prey DNA in Antarctic krill stomachs. Front. Zool. 5, 12 (2008).

  28. 28.

    AdapterRemoval: easy cleaning of next-generation sequencing reads. BMC Res. Notes 5, 337 (2012).

  29. 29.

    Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460–2461 (2010).

  30. 30.

    et al. Early life treatment with vancomycin propagates Akkermansia muciniphila and reduces diabetes incidence in the NOD mouse. Diabetologia 55, 2285–2294 (2012).

  31. 31.

    et al. Qime allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335–336 (2010).

  32. 32.

    et al. Uchime improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194–2200 (2011).

  33. 33.

    , , & Removing noise from pyrosequenced amplicons. BMC Bioinformatics 12, 38 (2011).

  34. 34.

    et al. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73, 5261–5267 (2007).

  35. 35.

    et al. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl. Environ. Microbiol. 72, 5069–5072 (2006).

  36. 36.

    The comprehensive R archive network. Wiley Interdiscip. Rev. Comput. Stat. 4, 394–398 (2012).

  37. 37.

    et al. Using network analysis to explore co-occurrence patterns in soil microbial communities. ISME J. 6, 343–351 (2012).

  38. 38.

    et al. Microbial co-occurrence relationships in the human microbiome. PLoS Comput. Biol. 8, e1002606 (2012).

  39. 39.

    et al. A travel guide to Cytoscape plugins. Nat. Methods 9, 1069–1076 (2012).

  40. 40.

    Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet J. 17, 10–12 (2011).

  41. 41.

    et al. The avian phylogenomic project data. GigaScience Database in press.

  42. 42.

    & Fast and accurate short read alignment with Burrows–Wheeler transform. Bioinformatics 25, 1754–1760 (2009).

  43. 43.

    , & Applying the ResFinder and VirulenceFinder web-services for easy identification of acquired antibiotic resistance and E. coli virulence genes in bacteriophage and prophage nucleotide sequences. Bacteriophage 4, e27943 (2014).

Download references


We thank Brian Schmidt and Christina Gebhard (both Smithsonian Institution) for necropsying vultures; Blaine Hyle, Talon Redding, William Simmons and J.D. Freye (all USDA) for collecting vultures; and Keith Wehner, Blaine Hyle and Brett Dunlap (all USDA) for providing critical logistic support in Nashville. The Alexander Wetmore Fund of the Smithsonian Institution provided funding for fieldwork. G.R.G. thanks the Smoketree Trust for support. M.R. acknowledges the financial support of a PhD scholarship from the Center for Environmental and Agricultural Microbiology (CREAM) in Copenhagen, Denmark. L.H.H. thanks the Lundbeck grant no. R44-A4384. M.T.P.G. acknowledges the Lundbeck grant no. R52-A5062. Furthermore, we thank Nina Christiansen and Lillian Anne Petersen, from the Danish National High-Throughput DNA Sequencing Centre, who constructed the 16S rRNA gene amplicon and the shotgun metagenomic libraries. We also thank Gisle Vestergaard (Section for microbiology, University of Copenhagen) and Shaun Nielsen (UNSW, Sydney, Australia) for analytical support. Last but not least, we thank Jessica Metcalf, Tony Walters and Juan Manuel Peralta Sanchez from the Rob Knight lab for helpful discussion.

Author information


  1. Department of Biology, Section of Microbiology, University of Copenhagen, 2100 Copenhagen, Denmark

    • Michael Roggenbuck
    •  & Søren Johannes Sørensen
  2. Center for GeoGenetics, Natural History Museum of Denmark, University of Copenhagen, 1350 Copenhagen, Denmark

    • Ida Bærholm Schnell
    •  & M. Thomas P. Gilbert
  3. Center for Zoo and Wild Animal Health, Copenhagen Zoo, 2000 Frederiksberg, Denmark

    • Ida Bærholm Schnell
    •  & Mads Frost Bertelsen
  4. Center for Biological Sequence Analysis, Technical University of Denmark, 2800 Kongens Lyngby, Denmark

    • Nikolaj Blom
    • , Jacob Bælum
    •  & Thomas Sicheritz-Pontén
  5. Center for Biosustainability, Technical University of Denmark, 2970 Hørsholm, Denmark

    • Nikolaj Blom
  6. Department of Vertebrate Zoology, National Museum of Natural History, Smithsonian Institution, Washington, DC 20013-7012, USA

    • Gary R. Graves
  7. Center for Macroecology, Evolution and Climate, Natural History Museum of Denmark, University of Copenhagen, 2100 Copenhagen, Denmark

    • Gary R. Graves
  8. Department of Environmental Science, Aarhus University, 4000 Roskilde, Denmark

    • Lars H Hansen


  1. Search for Michael Roggenbuck in:

  2. Search for Ida Bærholm Schnell in:

  3. Search for Nikolaj Blom in:

  4. Search for Jacob Bælum in:

  5. Search for Mads Frost Bertelsen in:

  6. Search for Thomas Sicheritz-Pontén in:

  7. Search for Søren Johannes Sørensen in:

  8. Search for M. Thomas P. Gilbert in:

  9. Search for Gary R. Graves in:

  10. Search for Lars H Hansen in:


M.R. and L.H.H. analysed the microbial survey and are the main authors of this manuscript. M.R., L.H.H. and M.T.P.G. generated the microbial data. I.B.S., and M.T.P.G. profiled the mammalian dietary composition. N.B., J.B. and T.S.P. did the metagenomic analysis. The sampling was performed by G.R.G. (wild vultures) and M.F.B. (zoo samples). S.J.S. helped interpret the data. This project was conceived and designed by G.R.G., M.T.P.G. and L.H.H. All the authors have read and understood the manuscript.

Competing interests

The authors declare no competing financial interests.

Corresponding authors

Correspondence to Gary R. Graves or Lars H Hansen.

Supplementary information

PDF files

  1. 1.

    Supplementary Information

    Supplementary Figure 1, Supplementary Tables 1-9 and Supplementary Notes 1-3


By submitting a comment you agree to abide by our Terms and Community Guidelines. If you find something abusive or that does not comply with our terms or guidelines please flag it as inappropriate.