Quantitative Interspecific Approach to the Stylosphere: Patterns of Bacteria and Fungi Abundance on Passerine Bird Feathers

Abstract

Feathers are the habitat of a myriad of organisms, from fungi and bacteria to lice and mites. Although most studies focus on specific taxa and their interaction with the bird host, anecdotal data glimpse feathers as holders of a system with its own ecology, what we call here the stylosphere. A major gap in our knowledge of the stylosphere is the ecology of the total abundance of microorganisms, being also rare to find studies that analyze abundance of more than one group of microorganisms at the bird interspecific level. Here, we quantified bacterial and fungi abundances through qPCR on the wing feathers of 144 birds from 24 passerine and one non-passerine bird species from three localities in Southern Spain. Bacteria and fungi abundances spanned three orders of magnitude among individual birds, but were consistent when comparing the right and the left wing feathers of individuals. Sampling locality explained ca. 14% of the variation in both bacteria and fungi abundances. Even when statistically controlling for sampling locality, microbial abundances consistently differed between birds from different species, but these differences were not explained by bird phylogeny. Finally, bird individuals and species having more bacteria also tended to held larger abundances of fungi. Our results suggest a quite complex explanation for stylosphere microorganisms’ abundance, being shaped by bird individual and species traits, as well as environmental factors, and likely bacteria–fungi interactions.

This is a preview of subscription content, log in to check access.

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5

Data Availability

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.

References

  1. 1.

    Saag P, Tilgar V, Mänd R, Kilgas P, Mägi M (2011) Plumage bacterial assemblages in a breeding wild passerine: relationships with ecological factors and body condition. Microb. Ecol. 61:740–749. https://doi.org/10.1007/s00248-010-9789-0

    Article  PubMed  Google Scholar 

  2. 2.

    Giraudeau M, Stikeleather R, McKenna J, Hutton P, McGraw KJ (2016) Plumage micro-organisms and preen gland size in an urbanizing context. Sci. Total Environ. 580:425–429. https://doi.org/10.1016/j.scitotenv.2016.09.224

    CAS  Article  PubMed  Google Scholar 

  3. 3.

    Hamstra TL, Badyaev AV (2009) Comprehensive investigation of ectoparasite community and abundance across life history stages of avian host. J. Zool. 278:91–99. https://doi.org/10.1111/j.1469-7998.2008.00547.x

    Article  Google Scholar 

  4. 4.

    Moreno-Rueda G (2010) Uropygial gland size correlates with feather holes, body condition and wingbar size in the house sparrow Passer domesticus. J of Avian Biol 413:229–236. https://doi.org/10.1111/j.1600-048x.2009.04859.x

    Article  Google Scholar 

  5. 5.

    Doña J, Proctor H, Serrano D, Johnson KP, Oploo AO, Huguet-Tapia JC, Ascunce MS, Jovani R (2019) Feather mites play a role in cleaning host feathers: new insights from DNA metabarcoding and microscopy. Mol. Ecol. 28:203–218. https://doi.org/10.1111/mec.14581

    CAS  Article  PubMed  Google Scholar 

  6. 6.

    Lindow SE, Brandl MT (2003) Microbiology of the phyllosphere. Appl. Environ. Microbiol. 69(4):1875–1883

    CAS  Article  Google Scholar 

  7. 7.

    Bisson IA, Marra PP, Burtt Jr EH, Sikaroodi M, Gillevet PM (2009) Variation in plumage microbiota depends on season and migration. Microb. Ecol. 58:212–220. https://doi.org/10.1007/s00248-009-9490-3

    Article  PubMed  Google Scholar 

  8. 8.

    Fülöp A, Csongor IV, Pap PL (2017) Cohabitation with farm animals rather than breeding effort increases the infection with feather-associated bacteria in the barn swallow Hirundo rustica. J. Avian Biol. 48(7):1005–1014. https://doi.org/10.1111/ecog.02537

    Article  Google Scholar 

  9. 9.

    Javůrková VG, Kreisinger J, Procházka P, Požgayová M, Ševčíková K, Brlík V, Adamík P, Heneberg P, Porkert J (2019) Unveiled feather microcosm: feather microbiota of passerine birds is closely associated with host species identity and bacteriocin producing bacteria. ISME J 13:2363–2376. https://doi.org/10.1038/s41396-019-0438-4

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  10. 10.

    Kilgas P, Saag P, Mägi M, Tilgar V, Mänd R (2012) Plumage bacterial load increases during nest-building in a passerine bird. J. Ornithol. 153:833–838. https://doi.org/10.1007/s10336-011-0801-3

    Article  Google Scholar 

  11. 11.

    Alt G, Saag P, Mägi M, Kisand V, Mänd R (2015) Manipulation of parental effort affects plumage bacterial load in a wild passerine. Oecologia 178:451–459. https://doi.org/10.1007/s00442-015-3238-1

    Article  PubMed  Google Scholar 

  12. 12.

    Jacob S, Immer A, Leclaire S, Nathalie Parthuisot N, Christine Ducamp C, Espinasse G, Heeb P (2014) Uropygial gland size and composition varies according to experimentally modified microbiome in great tits. BMC Evol. Biol. 14:134. https://doi.org/10.1186/1471-2148-14-134

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Møller AP, Peralta-Sánchez JM, Nielsen JT, López-Hernández E, Soler JJ (2012) Goshawk prey have more bacteria than non-prey. J. Anim. Ecol. 81:403–410. https://doi.org/10.1111/j.1365-2656.2011.01923.x

    Article  PubMed  Google Scholar 

  14. 14.

    Czirják GÁ, Pap PL, Vágási CI, Giraudeau M, Mureşan C, Mirleau P, Heeb P (2013) Preen gland removal increases plumage bacterial load but not that of feather-degrading bacteria. Naturwissenschaften 100(2):145–151. https://doi.org/10.1007/s00114-012-1005-2

    CAS  Article  PubMed  Google Scholar 

  15. 15.

    Gunderson AR, Forsyth MH, Swaddle JP (2009) Evidence that plumage bacteria influence feather coloration and body condition of eastern bluebirds Sialia sialis. J. Avian Biol. 40(4):440–447. https://doi.org/10.1111/j.1600-048X.2008.04650.x

    Article  Google Scholar 

  16. 16.

    Clayton DH, Lee PLM, Tompkins DM, Brodie Iii ED (1999) Reciprocal natural selection on host-parasite phenotypes. Am. Nat. 154(3):261–270. https://doi.org/10.1086/303237

    Article  PubMed  Google Scholar 

  17. 17.

    Leclaire S, Pierret P, Chatelain M, Gasparin J (2014) Feather bacterial load affects plumage condition, iridescent color, and investment in preening in pigeons. Behav. Ecol. 25(5):1192–1198. https://doi.org/10.1093/beheco/aru109

    Article  Google Scholar 

  18. 18.

    Shawkey MD, Pillai SR, Hill GE, Siefferman LM, Roberts SR (2007) Bacteria as an agent for change in structural plumage color: correlational and experimental evidence. Am. Nat. 169(S1):S112–S121. https://doi.org/10.1086/510100

    Article  PubMed  Google Scholar 

  19. 19.

    Leclaire S, Czirják GÁ, Hammouda A, Gasparini J (2015) Feather bacterial load shapes the trade-off between preening and immunity in pigeons. BCM Evol Biol 15:60. https://doi.org/10.1186/s12862-015-0338-9

    Article  Google Scholar 

  20. 20.

    Bar-On YM, Phillips R, Milo R (2018) The biomass distribution on earth. PNAS 115(25):6506–6511. https://doi.org/10.1073/pnas.1711842115

    CAS  Article  PubMed  Google Scholar 

  21. 21.

    Peralta-Sánchez JM, Martín-Platero AM, Wegener-Parfrey L, Martínez-Bueno M, Rodríguez-Ruano S, Navas-Molina J, Vázquez-Baeza Y, Martín-Gálvez D, Martín-Vivaldi M, Ibáñez-Álamo JD, Knight R, Soler JJ (2018) Bacterial density rather than diversity correlates with hatching success across different avian species. FEMS Microbiol. Ecol. 94(3). https://doi.org/10.1093/femsec/fiy022

  22. 22.

    Lim SJ, Bordenstein SR (2020) An introduction to phylosymbiosis. Proc. R. Soc. B 287:20192900. https://doi.org/10.1098/rspb.2019.2900

    Article  PubMed  Google Scholar 

  23. 23.

    Trevelline BK, Sosa J, Hartup BK, Kohl KD (2020) A bird’s-eye view of phylosymbiosis: weak signatures of phylosymbiosis among all 15 species of cranes. Proc. R. Soc. B 287:20192988. https://doi.org/10.1098/rspb.2019.2988

    CAS  Article  PubMed  Google Scholar 

  24. 24.

    Doña J, Herrera SV, Nyman T, Kunnasranta M, Johnson KP (2020) Patterns of microbiome variation among infrapopulations of permanent bloodsucking parasites. bioRxiv. 2020.05.27.118331. https://doi.org/10.1101/2020.05.27.118331

  25. 25.

    Lauber CL, Zhou N, Gordon JI, Knight R, Fierer N (2010) Effect of storage conditions on the assessment of bacterial community structure in soil and human-associated samples. FEMS Microbiol. Lett. 307(1):80–86. https://doi.org/10.1111/j.1574-6968.2010.01965.x

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  26. 26.

    Herlemann DP, Labrenz M, Jürgens K, Bertilsson S, Waniek JJ, Andersson AF (2011) Transitions in bacterial communities along the 2000 km salinity gradient of the Baltic Sea. ISME J 5(10):1571–1579. https://doi.org/10.1038/ismej.2011.41

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  27. 27.

    Turenne CY, Sanche SE, Hoban DJ, Karlowsky JA, Kabani AM (1999) Rapid identification of fungi by using the ITS2 genetic region and an automated fluorescent capillary electrophoresis system [published correction appears in journal of clinical microbiology 2000 38(2): 944]. J. Clin. Microbiol. 37(6):1846–1851

    CAS  Article  Google Scholar 

  28. 28.

    White TJ, Bruns T, Lee S, Taylor JW (1990) Amplification and direct sequencing of fungal ribosomal RNA genes for phylogenetics. In: Innis MA, Gelfand DH, Sninsky JJ, White TJ (eds) PCR protocols: a guide to methods and applications. Academic Press, Inc, New York, pp 315–322

    Google Scholar 

  29. 29.

    Guallar S, Jovani R (2020) Moult nestedness and its imperfections: insights to unravel the nature of passerine wing-feather moult rules. J. Avian Biol. https://doi.org/10.1111/jav.02553

  30. 30.

    R Core Team (2019) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL http://www.R-project.org/

  31. 31.

    Hackett SJ, Kimball RT, Reddy S, Bowie RCK, Braun EL, Braun MJ, Chojnowski JL, Cox WA, Han KL, Harshman J, Huddleston CJ, Marks BD, Miglia KJ, Moore WS, Sheldon FH, Steadman DW, Witt CC, Yuri T (2008) A phylogenomic study of birds reveals their evolutionary history. Science 320:1763–1768. https://doi.org/10.1126/science.1157704

    CAS  Article  PubMed  Google Scholar 

  32. 32.

    Jetz W, Thomas GH, Joy JB, Hartmann K, Mooers AO (2012) The global diversity of birds in space and time. Nature 491:444–448. https://doi.org/10.1038/nature11631

    CAS  Article  PubMed  Google Scholar 

  33. 33.

    Revell L (2012) Phytools: an R package for phylogenetic comparative biology (and other things). Methods Ecol. Evol. 3:217–223. https://doi.org/10.1111/j.2041-210X.2011.00169.x

    Article  Google Scholar 

  34. 34.

    Oksanen J, Blanchet FG, Friendly M, Kindt R, Legendre P, McGlinn D, Minchin PR, O’Hara RB, Simpson GL, Solymos P, Stevens MHH, Szoecs E, Wagner H (2019). Vegan: community ecology package. R package version 2.5–6. https://CRAN.R-project.org/package=vegan

  35. 35.

    Paradis E, Schliep K (2018) Ape 5.0: an environment for modern phylogenetics and evolutionary analyses in R. Bioinformatics 35:526–528. https://doi.org/10.1093/bioinformatics/bty633

    CAS  Article  Google Scholar 

  36. 36.

    Paterno GB, Penone C, Werner GDA (2018) sensiPHY: an r-package for sensitivity analysis in phylogenetic comparative methods. Methods Ecol. Evol. 9(6):1461–1467. https://doi.org/10.1111/2041-210X.12990

    Article  Google Scholar 

  37. 37.

    Barton K (2019) MuMIn: multi-model inference. R package version 1.43.15. https://CRAN.R-project.org/package=MuMIn

  38. 38.

    Stoffel MA, Nakagawa S, Schielzeth H (2017) rptR: repeatability estimation and variance decomposition by generalized linear mixed-effects models. Methods Ecol. Evol. 8:1639–1644. https://doi.org/10.1111/2041-210X.12797

    Article  Google Scholar 

  39. 39.

    Bisson IA, Marra PP, Burtt Jr EH, Sikaroodi M, Gillivet PM (2007) A molecular comparison of plumage and soil bacteria across biogeographic, ecological, and taxonomic scales. Microb. Ecol. 54(1):65–81. https://doi.org/10.1007/s00248-006-9173-2

    Article  PubMed  Google Scholar 

  40. 40.

    Møller AP, Czirjak GÁ, Heeb P (2009) Feather micro-organisms and uropygial antimicrobial defences in a colonial passerine bird. Funct. Ecol. 23(6):1097–1102. https://doi.org/10.1111/j.1365-2435.2009.01594.x

    Article  Google Scholar 

  41. 41.

    Czirják GÁ, Møller AP, Mousseau TA, Heeb P (2010) Microorganisms associated with feathers of barn swallows in radioactively contaminated areas around Chernobyl. Microb. Ecol. 60(2):373–380. https://doi.org/10.1007/s00248-010-9716-4

    Article  PubMed  Google Scholar 

  42. 42.

    Burtt Jr EH, Ichida JM (1999) Occurrence of feather-degrading bacilli in the plumage of birds. Auk 116(2):364–372. https://doi.org/10.2307/4089371

    Article  Google Scholar 

  43. 43.

    Kent CM, Burtt Jr EH (2016) Feather-degrading bacilli in the plumage of wild birds: prevalence and relation to feather wear. Auk 133:583–592. https://doi.org/10.1642/AUK-16-39.1

    Article  Google Scholar 

  44. 44.

    Mazel F, Davis KM, Loudon A, Kwong WK, Groussin M, Parfrey LW (2018) Is host filtering the main driver of phylosymbiosis across the tree of life? mSystems 3:e00097-18. https://doi.org/10.1128/mSystems.00097-18

  45. 45.

    van Veelen HPJ, Falcao Salles J, Tieleman BI (2017) Multi-level comparisons of cloacal, skin, feather and nest-associated microbiota suggest considerable influence of horizontal acquisition on the microbiota assembly of sympatric woodlarks and skylarks. Microbiome 5(1):156. https://doi.org/10.1186/s40168-017-0371-6

    Article  PubMed  PubMed Central  Google Scholar 

  46. 46.

    Kohl KD (2020) Ecological and evolutionary mechanisms underlying patterns of phylosymbiosis in host-associated microbial communities. Phil Trans R Soc B 375:20190251. https://doi.org/10.1098/rstb.2019.0251

    CAS  Article  PubMed  Google Scholar 

  47. 47.

    Díaz-Real J, Serrano D, Pérez-Tris J et al (2014) Repeatability of feather mite prevalence and intensity in passerine birds. PLoS One 9:e107341. https://doi.org/10.1371/journal.pone.0107341

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  48. 48.

    Whitaker JM, Cristol DA, Forsyth MH (2005) Prevalence and genetic diversity of Bacillus licheniformis in avian plumage. J Field Ornithol 76(3):264–270. https://doi.org/10.1648/0273-8570-76.3.264

    Article  Google Scholar 

  49. 49.

    Williams CM, Richter CS, Mackenzie JM, Shih JC (1990) Isolation, identification, and characterization of a feather-degrading bacterium. Appl. Environ. Microbiol. 56(6):1509–1515. https://doi.org/10.1128/AEM.56.6.1509-1515.1990

    CAS  Article  PubMed  PubMed Central  Google Scholar 

  50. 50.

    Sanders JG, Lukasik P, Frederickson ME, Russell JA, Koga R, Knight R, Pierce NE (2017) Dramatic differences in gut bacterial densities correlate with diet and habitat in rainforest ants. Integr. Comp. Biol. 57(4):705–722. https://doi.org/10.1093/icb/icx088

    CAS  Article  PubMed  Google Scholar 

Download references

Acknowledgments

Marina Moreno, Walo Moreno, Laura Gangoso, and Santi Guallar for feather mass data. This manuscript benefited from comments of two anonymous referees.

Funding

Funding was provided by the Ministry of Economy and Competitiveness CGL2015–69,650-P project to RJ and DS, European Commission H2020-MSCA-IF-2019 program (id 886532) to JD, and La Caixa-Severo Ochoa International PhD Program 2016 to ML.

Author information

Affiliations

Authors

Contributions

All authors contributed to the study, commented on previous versions of the manuscript, and read and approved the final manuscript.

Corresponding author

Correspondence to María del Mar Labrador.

Ethics declarations

Conflict of Interest

The authors declare that they have no conflict of interest.

Ethics Approval

The study was conducted in compliance with the current laws of the Spanish Government. Bird ringing was done by RJ under the Spanish Ministry ringing license number 300111. All applicable national guidelines for the care and use of animals were followed.

No endangered species were involved in this study. All birds were studied with mild severity methods and released at sampling locality some minutes after capture. Birds were captured and feathers were collected under a permit granted by Consejería de Agricultura, Pesca y Desarrollo Rural de la Junta de Andalucía, and permit from the Parque Natural Sierra de Aracena y Picos de Aroche. The sampling protocol was approved by the Dirección General de Gestión del Medio Natural de la Consejería de Medio Ambiente y Ordenación del Territorio and the Subcomité de Bioética (CSIC). The study from which feather masses were obtained [29] had permits that were granted by the Spanish regional administration Consejería de Medio Ambiente, Caza y Patrimonio, Cabildo de Lanzarote (permit ES-000687/2015), and Departament de Territori i Sostenibilitat, Generalitat de Catalunya (permit SF/0229/2019).

Consent to Participate

Not applicable.

Consent for Publication

Not applicable.

Code Availability

The code generated during the current study is available from the corresponding author on reasonable request.

Supplementary Information

ESM 1

(DOCX 114 kb)

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Labrador, M., Doña, J., Serrano, D. et al. Quantitative Interspecific Approach to the Stylosphere: Patterns of Bacteria and Fungi Abundance on Passerine Bird Feathers. Microb Ecol (2020). https://doi.org/10.1007/s00248-020-01634-2

Download citation

Keywords

  • Mantel test
  • Microorganisms
  • Phylogenetic signal
  • Plumage
  • qPCR
  • Repeatability