Microbial Ecology

, Volume 72, Issue 2, pp 460–469 | Cite as

Composition of the Cutaneous Bacterial Community in Japanese Amphibians: Effects of Captivity, Host Species, and Body Region

  • Joana Sabino-Pinto
  • Molly Catherine Bletz
  • Mohammed Mafizul Islam
  • Norio Shimizu
  • Sabin Bhuju
  • Robert Geffers
  • Michael Jarek
  • Atsushi Kurabayashi
  • Miguel Vences
Host Microbe Interactions


The cutaneous microbiota plays a significant role in the biology of their vertebrate hosts, and its composition is known to be influenced both by host and environment, with captive conditions often altering alpha diversity. Here, we compare the cutaneous bacterial communities of 61 amphibians (both wild and captive) from Hiroshima, Japan, using high-throughput amplicon sequencing of a segment of the 16S rRNA gene. The majority of these samples came from a captive breeding facility at Hiroshima University where specimens from six species are maintained under highly standardized conditions for several generations. This allowed to identify host effects on the bacterial communities under near identical environmental conditions in captivity. We found the structure of the cutaneous bacterial community significantly differing between wild and captive individuals of newts, Cynops pyrrhogaster, with a higher alpha diversity found in the wild individuals. Community structure also showed distinct patterns when comparing different species of amphibians kept under highly similar conditions, revealing an intrinsic host effect. Bacterial communities of dorsal vs. ventral skin surfaces did not significantly differ in most species, but a trend of higher alpha diversity on the ventral surface was found in Oriental fire-bellied toads, Bombina orientalis. This study confirms the cutaneous microbiota of amphibians as a highly dynamic system influenced by a complex interplay of numerous factors.


Microbiota Anura Caudata Japan 16S rRNA Illumina sequencing 



We are grateful to Meike Kondermann for their help in the lab and to Christoph Tebbe for helpful advice. We express our appreciation to the Board of Education of Kagoshima prefecture for allowing us to use live crocodile newts and Amami Ishikawa’s frogs protected by law. We thank the strain maintenance team of the Institute for Amphibian Biology for providing captive Japanese fire-bellied newts. This work was supported by a grant of the Deutsche Forschungsgemeinschaft (VE247/9-1) and by a guest researcher fellowship of Hiroshima University to MV.

Supplementary material

248_2016_797_MOESM1_ESM.pdf (53 kb)
Supplementary Fig. S1 Full legend for the taxa bar plots. Percentages of each taxa represented for each subset of the data. (PDF 52.9 kb)
248_2016_797_MOESM2_ESM.pdf (45 kb)
Supplementary Fig. S2 Results from LEfSe analysis showing taxa that significantly differ in abundance between wild and captive C. pyrrhogaster. Green taxa significantly characterize the wild community and blue taxa the captive community. (PDF 45.2 kb)
248_2016_797_MOESM3_ESM.pdf (34 kb)
Supplementary Fig. S3 Results from LEfSe analysis showing taxa that significantly differ in abundance between the different analyzed species. Purple taxa significantly characterize the community of B. orientalis; pink taxon the community of B. japonicus; red taxon the community of C. pyrrhogaster; green taxon the community of O. splendida; and the blue taxa the community of R. japonica. (PDF 33.7 kb)
248_2016_797_MOESM4_ESM.xlsx (11 kb)
Supplementary Table S1 Core bacterial OTUs from the wild and captive individuals. Abundance reflects the abundance of the OTU on the dataset and is in percentage. (XLSX 11 kb)
248_2016_797_MOESM5_ESM.xlsx (10 kb)
Supplementary Table S2 Lower triangle reflects the pair-wise comparisons of the composition of the communities between species analyzed with PERMANOVA; P values are represented. Higher triangle reflects the distances between the communities: top value when determined with the Bray-Curtis distance matrix; bottom value when determined with the unweighted UniFrac distance matrix. (XLSX 9 kb)
248_2016_797_MOESM6_ESM.xlsx (14 kb)
Supplementary Table S3 Core bacterial OTUs from B. orientalis (Bom), B. japonicus (Buf), C. pyrrhogaster (Cyn), O. splendida (Odo), and R. japonica (Ran). Abundance reflects the abundance of the OTU on the dataset and is in percentage. (XLSX 13 kb)
248_2016_797_MOESM7_ESM.xlsx (12 kb)
Supplementary Table S4 Core bacterial OTUs from the dorsal and ventral sides of B. orientalis. Abundance reflects the abundance of the OTU on the dataset and is in percentage. (XLSX 12 kb)
248_2016_797_MOESM8_ESM.xlsx (12 kb)
Supplementary Table S5 Core bacterial OTUs from the dorsal and ventral sides of B. japonicus. Abundance reflects the abundance of the OTU on the dataset and is in percentage. (XLSX 12 kb)
248_2016_797_MOESM9_ESM.xlsx (12 kb)
Supplementary Table S6 Core bacterial OTUs from the dorsal and ventral sides of C. pyrrhogaster. Abundance reflects the abundance of the OTU on the dataset and is in percentage. (XLSX 11 kb)
248_2016_797_MOESM10_ESM.xlsx (11 kb)
Supplementary Table S7 Core bacterial OTUs from the dorsal and ventral sides of E. andersoni. Abundance reflects the abundance of the OTU on the dataset and is in percentage. (XLSX 11 kb)
248_2016_797_MOESM11_ESM.xlsx (13 kb)
Supplementary Table S8 Core bacterial OTUs from the dorsal and ventral sides of O. splendida. Abundance reflects the abundance of the OTU on the dataset and is in percentage. (XLSX 12 kb)
248_2016_797_MOESM12_ESM.xlsx (12 kb)
Supplementary Table S9 Core bacterial OTUs from the dorsal and ventral sides of R. japonica. Abundance reflects the abundance of the OTU on the dataset and is in percentage. (XLSX 11 kb)


  1. 1.
    Clarke BT (1997) The natural history of amphibian skin secretions, their normal function and potential medical applications. Biol Rev 72:365–379CrossRefPubMedGoogle Scholar
  2. 2.
    Rosenthal M, Goldberg D, Aiello A, Larson E, Foxman B (2011) Skin microbiota: microbial community structure and its potential association with health and disease. Infect Genet Evol 11:839–848CrossRefPubMedPubMedCentralGoogle Scholar
  3. 3.
    Grice EA, Segre JA (2011) The skin microbiome. Nat Rev Microbiol 9:244–253CrossRefPubMedPubMedCentralGoogle Scholar
  4. 4.
    Naik S, Bouladoux N, Wilhelm C, Molloy MJ, Salcedo R, Kastenmuller W et al (2012) Compartmentalized control of skin immunity by resident commensals. Science 337:1115–1119CrossRefPubMedPubMedCentralGoogle Scholar
  5. 5.
    Belden LK, Harris RN (2007) Infectious diseases in wildlife: the community ecology context. Front Ecol Environ 5:533–539CrossRefGoogle Scholar
  6. 6.
    Reid G, Younes JA, Van Der Mei HC, Gloor GB, Knight R, Busscher HJ (2011) Microbiota restoration: natural and supplemented recovery of human microbial communities. Nat Rev Microbiol 9:27–38CrossRefPubMedGoogle Scholar
  7. 7.
    Fierer N, Ferrenberg S, Flores GE, Gonzalez A, Kueneman J, Legg T et al (2012) From animalcules to an ecosystem: application of ecological concepts of the human microbiome. Ann Rev Ecol Evol S 43:137–155CrossRefGoogle Scholar
  8. 8.
    Woodhams DC, Brandt H, Baumgartner S, Kielgast J, Küpfer E, Tobler U et al (2014) Interacting symbionts and immunity in the amphibian skin mucosome predict disease risk and probiotic effectiveness. PLoS One 9, e96375CrossRefPubMedPubMedCentralGoogle Scholar
  9. 9.
    Daly JW, Myers CW, Whittaker N (1987) Further classification of skin alkaloids from Neotropical poison frogs (Dendrobatidae), with a general survey of toxic/noxious substances in the amphibia. Toxicon 25:1023–1095CrossRefPubMedGoogle Scholar
  10. 10.
    Woodhams DC, Ardipradja K, Alford RA, Marantelli G, Reinert LK, Rollins‐Smith LA (2007) Resistance to chytridiomycosis varies among amphibian species and is correlated with skin peptide defenses. Anim Conserv 10:409–417CrossRefGoogle Scholar
  11. 11.
    Rollins-Smith LA (2009) The role of amphibian antimicrobial peptides in protection of amphibians from pathogens linked to global amphibian declines. BBA-Biomembranes 1788:1593–1599CrossRefPubMedGoogle Scholar
  12. 12.
    Becker MH, Harris RN (2010) Cutaneous bacteria of the redback salamander prevent morbidity associated with a lethal disease. PLoS One 5, e10957CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Myers JM, Ramsey JP, Blackman AL, Nichols AE, Minbiole KP, Harris RN (2012) Synergistic inhibition of the lethal fungal pathogen Batrachochytrium dendrobatidis: the combined effect of symbiotic bacterial metabolites and antimicrobial peptides of the frog Rana muscosa. J Chem Ecol 38:958–965CrossRefPubMedGoogle Scholar
  14. 14.
    Bletz MC, Loudon AH, Becker MH, Bell SC, Woodhams DC, Minbiole KP, Harris RN (2013) Mitigating amphibian chytridiomycosis with bioaugmentation: characteristics of effective probiotics and strategies for their selection and use. Ecol Lett 16:807–820CrossRefPubMedGoogle Scholar
  15. 15.
    Walke JB, Becker MH, Loftus SC, House LL, Teotonio TL, Minbiole KP, Belden LK (2015) Community structure and function of amphibian skin microbes: an experiment with bullfrogs exposed to a chytrid fungus. PLoS One 10, e0139848CrossRefPubMedPubMedCentralGoogle Scholar
  16. 16.
    Harris RN, Lauer A, Simon MA, Banning JL, Alford RA (2008) Addition of antifungal skin bacteria to salamanders ameliorates the effects of chytridiomycosis. Dis Aquat Org 83:11CrossRefGoogle Scholar
  17. 17.
    McKenzie VJ, Bowers RM, Fierer N, Knight R, Lauber CL (2012) Co-habiting amphibian species harbor unique skin bacterial communities in wild populations. ISME J 6:588–596CrossRefPubMedGoogle Scholar
  18. 18.
    Antwis RE, Haworth RL, Engelmoer DJ, Ogilvy V, Fidgett AL, Preziosi RF (2014) Ex situ diet influences the bacterial community associated with the skin of red-eyed tree frogs (Agalychnis callidryas). PLoS One 9, e85563CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Becker MH, Richards-Zawacki CL, Gratwicke B, Belden LK (2014) The effect of captivity on the cutaneous bacterial community of the critically endangered Panamanian golden frog (Atelopus zeteki). Biol Conserv 176:199–206CrossRefGoogle Scholar
  20. 20.
    Kueneman JG, Parfrey L, Woodhams DC, Archer HM, Knight R, McKenzie VJ (2014) The amphibian skin-associated microbiome across species, space and life history stages. Mol Ecol 23:1238–1250CrossRefPubMedGoogle Scholar
  21. 21.
    Loudon AH, Woodhams DC, Parfrey LW, Archer H, Knight R, McKenzie V, Harris RN (2014) Microbial community dynamics and effect of environmental microbial reservoirs on red-backed salamanders (Plethodon cinereus). ISME J 8:830–840CrossRefPubMedGoogle Scholar
  22. 22.
    Walke JB, Becker MH, Loftus SC, House LL, Cormier G, Jensen RV, Belden LK (2014) Amphibian skin may select for rare environmental microbes. ISME J 8:2207–2217CrossRefPubMedGoogle Scholar
  23. 23.
    Toledo RD, Jared C (1995) Cutaneous granular glands and amphibian venoms. Comp Biochem Phys A 111:1–29CrossRefGoogle Scholar
  24. 24.
    Bataille A, Lee-Cruz L, Tripathi B, Kim H, Waldman B (2016) Microbiome variation across amphibian skin regions: implications for chytridiomycosis mitigation efforts. Microb Ecol 71:221–232CrossRefPubMedGoogle Scholar
  25. 25.
    Brosius J, Dull TJ, Sleeter DD, Noller HF (1981) Gene organization and primary structure of a ribosomal RNA operon from Escherichia coli. J Mol Biol 148:107–127CrossRefPubMedGoogle Scholar
  26. 26.
    Kozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD (2013) Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl Environ Microbiol 79:5112–5120CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK et al (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7:335–336CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Aronesty E (2011) ea–utils: command–line tools for processing biological sequencing data.–utils. Accessed 1 Oct 2015
  29. 29.
    Aronesty E (2013) TOBioiJ: comparison of sequencing utility programs. Open Bioinforma J 7:8CrossRefGoogle Scholar
  30. 30.
    Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R (2011) UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27:2194–2200CrossRefPubMedPubMedCentralGoogle Scholar
  31. 31.
    Rideout JR, He Y, Navas-Molina JA, Walters WA, Ursell LK, Gibbons SM (2014) Subsampled open-reference clustering creates consistent, comprehensive OTU definitions and scales to billions of sequences. Peer J 2, e545CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Edgar RC (2010) Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26:2460–2461CrossRefPubMedGoogle Scholar
  33. 33.
    Caporaso JG, Bittinger K, Bushman FD, DeSantis TZ, Andersen GL, Knight R (2010) PyNAST: a flexible tool for aligning sequences to a template alignment. Bioinformatics 26:266–267CrossRefPubMedGoogle Scholar
  34. 34.
    Wang Q, Garrity GM, Tiedje JM, Cole JR (2007) Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 73:5261–5267CrossRefPubMedPubMedCentralGoogle Scholar
  35. 35.
    Price MN, Dehal PS, Arkin AP (2010) FastTree 2—approximately maximum-likelihood trees for large alignments. PLoS One 5, e9490CrossRefPubMedPubMedCentralGoogle Scholar
  36. 36.
    Bokulich NA, Subramanian S, Faith JJ, Gevers D, Gordon JI, Knight R, Mills DA, Caporaso JG (2013) Quality–filtering vastly improves diversity estimates from Illumina amplicon sequencing. Nat Methods 10:57–59CrossRefPubMedGoogle Scholar
  37. 37.
    R Development Core Team (2011) R: a language and environment for statistical computing. Vienna: the R Foundation for Statistical Computing. ISBN: 3-900051-07-0. Available online at
  38. 38.
    Lozupone C, Knight R (2005) UniFrac: a new phylogenetic method for comparing microbial communities. Appl Environ Microbiol 71:8228–8235CrossRefPubMedPubMedCentralGoogle Scholar
  39. 39.
    Belden LK, Hughey MC, Rebollar EA, Umile TP, Loftus SC, Burzynski EA, Minbiole KP, House LL, Jensen RV, Becker MH, Walke JB, Medina D, Ibáñez R, Harris RN (2015) Panamanian frog species host unique skin bacterial communities. Front Microbiol 6:1171CrossRefPubMedPubMedCentralGoogle Scholar
  40. 40.
    Rebollar EA, Hughey MC, Medina D, Harris RN, Ibáñez R, Belden LK (2016) Skin bacterial diversity of Panamanian frogs is associated with host susceptibility and presence of Batrachochytrium dendrobatidis. ISME J. doi: 10.1038/ismej.2015.234 PubMedGoogle Scholar
  41. 41.
    Vences M, Dohrmann AB, Künzel S, Granzow S, Baines JF, Tebbe CC (2015) Composition and variation of the skin microbiota in sympatric species of European newts (Salamandridae). Amphibia-Reptilia 36:5–12CrossRefGoogle Scholar
  42. 42.
    Kohl KD, Skopec MM, Dearing MD (2014) Captivity results in disparate loss of gut microbial diversity in closely related hosts. Conserv Physiol 2, cou009CrossRefPubMedPubMedCentralGoogle Scholar
  43. 43.
    Gibson BW, Tang DZ, Mandrell R, Kelly M, Spindel ER (1991) Bombinin-like peptides with antimicrobial activity from skin secretions of the Asian toad, Bombina orientalis. J Biol Chem 266:23103–23111PubMedGoogle Scholar
  44. 44.
    Kohl KD, Yahn J (2016) Effects of environmental temperature on the gut microbial communities of tadpoles. Environ Microbiol, in pressGoogle Scholar
  45. 45.
    Shade A, Jones SE, Caporaso JG, Handelsman J, Knight R, Fierer N, Gilbert JA (2014) Conditionally rare taxa disproportionately contribute to temporal changes in microbial diversity. mBio 5, e01371-14CrossRefPubMedPubMedCentralGoogle Scholar
  46. 46.
    Sanford JA, Gallo RL (2013) Functions of the skin microbiota in health and disease. Semin Immunol 25:370–377CrossRefPubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Science+Business Media New York 2016

Authors and Affiliations

  • Joana Sabino-Pinto
    • 1
  • Molly Catherine Bletz
    • 1
  • Mohammed Mafizul Islam
    • 2
  • Norio Shimizu
    • 3
  • Sabin Bhuju
    • 4
  • Robert Geffers
    • 4
  • Michael Jarek
    • 4
  • Atsushi Kurabayashi
    • 2
  • Miguel Vences
    • 1
  1. 1.Zoological InstituteBraunschweig University of TechnologyBraunschweigGermany
  2. 2.Institute for Amphibian Biology, Graduate School of ScienceHiroshima UniversityHigashi-HiroshimaJapan
  3. 3.Hiroshima University MuseumsHiroshima UniversityHigashi-HiroshimaJapan
  4. 4.Department of Genome AnalyticsHelmholtz Centre for Infection ResearchBraunschweigGermany

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