Skip to main content

Thank you for visiting nature.com. You are using a browser version with limited support for CSS. To obtain the best experience, we recommend you use a more up to date browser (or turn off compatibility mode in Internet Explorer). In the meantime, to ensure continued support, we are displaying the site without styles and JavaScript.

  • Letter
  • Published:

Airborne microbial transport limitation to isolated Antarctic soil habitats

Abstract

Dispersal is a critical yet poorly understood factor underlying macroecological patterns in microbial communities1. Airborne microbial transport is assumed to occupy a central role in determining dispersal outcomes2,3, and extra-range dispersal has important implications for predicting ecosystem resilience and response to environmental change4. One of the most pertinent biomes in this regard is Antarctica, given its geographic isolation and vulnerability to climate change and human disturbance5. Here, we report microbial diversity in near-ground and high-altitude air above the largest ice-free Antarctic habitat, as well as that of underlying soil microbial communities. We found that persistent local airborne inputs were unable to fully explain Antarctic soil community assembly. Comparison with airborne microbial diversity from high-altitude and non-polar sources suggests that strong selection occurs during long-range atmospheric transport. The influence of selection during airborne transit and at sink locations varied between microbial phyla. Overall, the communities from this isolated Antarctic ecosystem displayed limited connectivity to the non-polar microbial pool, and alternative sources of recruitment are necessary to fully explain extant soil diversity. Our findings provide critical insights into the role of airborne transport limitation in determining microbial biogeographic patterns.

This is a preview of subscription content, access via your institution

Access options

Rent or buy this article

Prices vary by article type

from$1.95

to$39.95

Prices may be subject to local taxes which are calculated during checkout

Fig. 1: Antarctic air and soil habitats support distinct bacterial and fungal communities.
Fig. 2: Comparison of bacterial and fungal diversity from Antarctic and non-polar sources.
Fig. 3: Phylogenetic structuring of local and global pools for bacterial and fungal diversity.

Similar content being viewed by others

Data availability

The data that support the findings of this study are available from the corresponding author upon request. All sequence data generated by this study have been submitted to the EMBL European Nucleotide Archive under BioProject PRJEB27416 with accession numbers ERS2573837 to ERS2573946.

References

  1. Hanson, C. A., Fuhrman, J. A., Horner-Devine, M. C. & Martiny, J. B. H. Beyond biogeographic patterns: processes shaping the microbial landscape. Nat. Rev. Microbiol. 10, 497–506 (2012).

    Article  CAS  Google Scholar 

  2. Burrows, S. M., Elbert, W., Lawrence, M. G. & Pöschl, U. Bacteria in the global atmosphere—part 1: review and synthesis of literature data for different ecosystems. Atmos. Chem. Phys. 9, 9263–9280 (2009).

    Article  CAS  Google Scholar 

  3. Kellogg, C. A. & Griffin, D. W. Aerobiology and the global transport of desert dust. Trends Ecol. Evol. 21, 638–644 (2006).

    Article  Google Scholar 

  4. Wilson, J. R. U., Dormontt, E. E., Prentis, P. J., Lowe, A. J. & Richardson, D. M. Something in the way you move: dispersal pathways affect invasion success. Trends Ecol. Evol. 24, 136–144 (2009).

    Article  Google Scholar 

  5. Chown, S. L. et al. The changing form of Antarctic biodiversity. Nature 522, 431–438 (2015).

    Article  CAS  Google Scholar 

  6. De Wit, R. & Bouvier, T. ‘Everything is everywhere, but, the environment selects’; what did Baas Becking and Beijerinck really say? Environ. Microbiol. 8, 755–758 (2006).

    Article  Google Scholar 

  7. Finlay, B. J. & Clarke, K. J. Ubiquitous dispersal of microbial species. Nature 400, 828 (1999).

    Article  CAS  Google Scholar 

  8. Mayol, E. et al. Long-range transport of airborne microbes over the global tropical and subtropical ocean. Nat. Commun. 8, 201 (2017).

    Article  Google Scholar 

  9. Favet, J. et al. Microbial hitchhikers on intercontinental dust: catching a lift in Chad. ISME J. 7, 850–867 (2013).

    Article  CAS  Google Scholar 

  10. Delgado-Baquerizo, M. et al. A global atlas of the dominant bacteria found in soil. Science 359, 320–325 (2018).

    Article  CAS  Google Scholar 

  11. Wang, J. et al. Phylogenetic beta diversity in bacterial assemblages across ecosystems: deterministic versus stochastic processes. ISME J. 7, 1310–1321 (2013).

    Article  CAS  Google Scholar 

  12. Lowe, W. H. & McPeek, M. A. Is dispersal neutral? Trends Ecol. Evol. 29, 444–450 (2014).

    Article  Google Scholar 

  13. Pointing, S. B. et al. Highly specialized microbial diversity in hyper-arid polar desert. Proc. Natl Acad. Sci. USA 106, 19964–19969 (2009).

    Article  CAS  Google Scholar 

  14. Chan, Y., Van Nostrand, J. D., Zhou, J., Pointing, S. B. & Farrell, R. L. Functional ecology of an Antarctic dry valley. Proc. Natl Acad. Sci. USA 110, 8990–8995 (2013).

    Article  CAS  Google Scholar 

  15. Bahl, J. et al. Ancient origins determine global biogeography of hot and cold desert cyanobacteria. Nat. Commun. 2, 163 (2011).

    Article  Google Scholar 

  16. Jungblut, A., Lovejoy, C. & Vincent, W. Global distribution of cyanobacterial ecotypes in the cold biosphere. ISME J. 4, 191–202 (2010).

    Article  CAS  Google Scholar 

  17. Vyverman, W. et al. Evidence for widespread endemism among Antarctic micro-organisms. Polar Sci. 4, 103–113 (2010).

    Article  Google Scholar 

  18. Fraser, C. I., Terauds, A., Smellie, J., Convey, P. & Chown, S. L. Geothermal activity helps life survive glacial cycles. Proc. Natl Acad. Sci. USA 111, 5634–5639 (2014).

    Article  CAS  Google Scholar 

  19. Burrows, S. M. et al. Bacteria in the global atmosphere—part 2: modeling of emissions and transport between different ecosystems. Atmos. Chem. Phys. 9, 9281–9297 (2009).

    Article  CAS  Google Scholar 

  20. Kleinteich, J. et al. Pole-to-pole connections: similarities between Arctic and Antarctic microbiomes and their vulnerability to environmental change. Front. Ecol. Evol. 5, 137 (2017).

    Article  Google Scholar 

  21. Cox, F., Newsham, K. K., Bol, R., Dungait, J. A. J. & Robinson, C. H. Not poles apart: Antarctic soil fungal communities show similarities to those of the distant Arctic. Ecol. Lett. 19, 528–536 (2016).

    Article  Google Scholar 

  22. Kobayashi, F. et al. Atmospheric bioaerosols originating from Adélie penguins (Pygoscelis adeliae): ecological observations of airborne bacteria at Hukuro Cove, Langhovde, Antarctica. Polar Sci. 10, 71–78 (2016).

    Article  Google Scholar 

  23. Pearce, D. A., Hughes, K. A., Lachlan-Cope, T., Harangozo, S. A. & Jones, A. E. Biodiversity of air-borne microorganisms at Halley Station, Antarctica. Extremophiles 14, 145–159 (2010).

    Article  Google Scholar 

  24. Bottos, E. M., Woo, A. C., Zawar-Reza, P., Pointing, S. B. & Cary, S. C. Airborne bacterial populations above desert soils of the McMurdo Dry Valleys, Antarctica. Microb. Ecol. 67, 120–128 (2013).

    Article  Google Scholar 

  25. Rao, S. et al. Low-diversity fungal assemblage in an Antarctic Dry Valleys soil. Polar. Biol. 35, 567–574 (2011).

    Article  Google Scholar 

  26. Brown, S. P. & Jumpponen, A. Phylogenetic diversity analyses reveal disparity between fungal and bacterial communities during microbial primary succession. Soil Biol. Biochem. 89, 52–60 (2015).

    Article  CAS  Google Scholar 

  27. Cowan, D. A., Makhalanyane, T. P., Dennis, P. G. & Hopkins, D. W. Microbial ecology and biogeochemistry of continental Antarctic soils. Front. Microbiol. 5, 154 (2014).

    Article  Google Scholar 

  28. Fierer, N. et al. Cross-biome metagenomic analyses of soil microbial communities and their functional attributes. Proc. Natl Acad. Sci. USA 109, 21390–21395 (2012).

    Article  CAS  Google Scholar 

  29. Atkins, C. B. & Dunbar, G. B. Aeolian sediment flux from sea ice into Southern McMurdo Sound, Antarctica. Glob. Planet. Change 69, 133–141 (2009).

    Article  Google Scholar 

  30. Pointing, S. B., Fierer, N., Smith, G. J. D., Steinberg, P. D. & Wiedmann, M. Quantifying human impact on Earth’s microbiome. Nat. Microbiol. 1, 16145 (2016).

    Article  CAS  Google Scholar 

  31. Dybwad, M., Skogan, G. & Blatny, J. M. Comparative testing and evaluation of nine different air samplers: end-to-end sampling efficiencies as specific performance measurements for bioaerosol applications. Aerosol Sci. Technol. 48, 282–295 (2014).

    Article  CAS  Google Scholar 

  32. Šantl-Temkiv, T. et al. High-flow-rate impinger for the study of concentration, viability, metabolic activity, and ice-nucleation activity of airborne bacteria. Environ. Sci. Technol. 51, 11224–11234 (2017).

    Article  Google Scholar 

  33. Archer, S. D. J., McDonald, I. R., Herbold, C. W., Lee, C. K. & Cary, C. S. Benthic microbial communities of coastal terrestrial and ice shelf Antarctic meltwater ponds. Front. Microbiol. 6, 485 (2015).

    Article  Google Scholar 

  34. Metagenomic Sequencing Library Preparation Part # 15044223 Rev. B (Illumina, 2013).

  35. Warren-Rhodes, K. et al. Subsurface microbial habitats in an extreme desert Mars-analogue environment. Preprint at https://www.biorxiv.org/content/10.1101/269605v4 (2018).

  36. Schoch, C. L. et al. Nuclear ribosomal internal transcribed spacer (ITS) region as a universal DNA barcode marker for Fungi. Proc. Natl Acad. Sci. USA 109, 6241–6246 (2012).

    Article  CAS  Google Scholar 

  37. Thompson, L. R. et al. A communal catalogue reveals Earth’s multiscale microbial diversity. Nature 551, 457–463 (2017).

    Article  CAS  Google Scholar 

  38. Callahan, B. J. et al. DADA2: high resolution sample inference from Illumina amplicon data. Nat. Methods 13, 581–583 (2016).

    Article  CAS  Google Scholar 

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

    Article  Google Scholar 

  40. Callahan, B. J., McMurdie, P. J. & Holmes, S. P. Exact sequence variants should replace operational taxonomic units in marker-gene data analysis. ISME J. 11, 2639–2643 (2017).

    Article  Google Scholar 

  41. Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, 590–596 (2013).

    Article  Google Scholar 

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

    Article  CAS  Google Scholar 

  43. Deshpande, V. et al. Fungal identification using a Bayesian classifier and the Warcup training set of internal transcribed spacer sequences. Mycologia 108, 1–5 (2016).

    Article  Google Scholar 

  44. Maki, T. et al. Variations in the structure of airborne bacterial communities in Tsogt-Ovoo of Gobi desert area during dust events. Air Qual. Atmos. Health 10, 249–260 (2017).

    Article  CAS  Google Scholar 

  45. McMurdie, P. J. & Holmes, S. phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS ONE 8, e61217 (2013).

    Article  CAS  Google Scholar 

  46. Love, M. I., Huber, W. & Anders, S. Moderated estimation of fold change and dispersion for RNA-Seq data with DESeq2. Genome. Biol. 15, 550 (2014).

    Article  Google Scholar 

  47. Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer, New York, 2009).

  48. Pointing, S. B. et al. Biogeography of photoautotrophs in the high polar biome. Front. Plant Sci. 6, 692 (2015).

    Article  Google Scholar 

  49. Nguyen, N. H. et al. FUNGuild: an open annotation tool for parsing fungal community datasets by ecological guild. Fungal Ecol. 20, 241–248 (2016).

    Article  Google Scholar 

  50. Tedersoo, L. et al. Global diversity and geography of soil fungi. Science 346, 1256688 (2014).

    Article  Google Scholar 

  51. Ulrich, W., Almeida-Neto, M. & Gotelli, N. J. A consumer’s guide to nestedness analysis. Oikos 118, 3–17 (2009).

    Article  Google Scholar 

  52. Fruchterman, T. M. J. & Reingold, E. M. Graph drawing by force-directed placement. Software Pract. Exper. 21, 1129–1164 (1991).

    Article  Google Scholar 

  53. Almeida-Neto, M., Guimarães, P., Guimarães, P. R., Loyola, R. D. & Ulrich, W. A consistent metric for nestedness analysis in ecological systems: reconciling concept and measurement. Oikos 117, 1227–1239 (2008).

    Article  Google Scholar 

  54. Ulrich, W. et al. A comprehensive framework for the study of species co-occurrences, nestedness and turnover. Oikos 126, 1607–1616 (2017).

    Article  Google Scholar 

  55. Oksanen, J. et al. Vegan: Community Ecology Package. v. 2.5-3 (2017); https://cran.r-project.org/web/packages/vegan/index.html

  56. Swenson, N. G. Functional and Phylogenetic Ecology in R (Springer, New York, 2014).

  57. Kembel, S. W. et al. Picante: R tools for integrating phylogenies and ecology. Bioinformatics 26, 1463–1464 (2010).

    Article  CAS  Google Scholar 

  58. Paradis, E. Ape: analyses of phylogenetics and evolution v. 5.2 (2018); https://www.rdocumentation.org/packages/ape/versions/5.2

  59. Michonneau, F. Phylobase: base package for phylogenetic structures and comparative data v. 0.8.4 (2018); https://www.rdocumentation.org/packages/phylobase/versions/0.8.4

  60. Dray, S. Adephylo: exploratory analyses for the phylogenetic comparative method. v. 1.1-11 (2018); https://www.rdocumentation.org/packages/adephylo/versions/1.1-11

  61. Zhang, J. Phylotools: phylogenetic tools for eco-phylogenetics v. 0.2.2 (2018); https://besjournals.onlinelibrary.wiley.com/doi/10.1111/j.2041-210X.2011.00169.x

  62. Höhl, M., Rigoutsos, I. & Ragan, M. A. Pattern-based phylogenetic distance estimation and tree reconstruction. Evol. Bioinform. Online 2, 359–375 (2007).

    PubMed  PubMed Central  Google Scholar 

  63. Choi, J. & Kim, S.-H. A genome tree of life for the fungi kingdom. Proc. Natl Acad. Sci. USA 114, 9391–9396 (2017).

    Article  CAS  Google Scholar 

  64. Ebersberger, I. et al. A consistent phylogenetic backbone for the fungi. Mol. Biol. Evol. 29, 1319–1334 (2012).

    Article  CAS  Google Scholar 

  65. Boyle, E. E. & Adamowicz, S. J. Community phylogenetics: assessing tree reconstruction methods and the utility of DNA barcodes. PLoS ONE 10, e0126662 (2015).

    Article  Google Scholar 

  66. Kembel, S. W. & Hubbell, S. P. The phylogenetic structure of a neotropical forest tree community. Ecology 87, 86–99 (2006).

    Article  Google Scholar 

  67. Webb, C. O., Ackerly, D. D. & Kembel, S. W. Phylocom: software for the analysis of phylogenetic community structure and trait evolution. Bioinformatics 24, 2098–2100 (2008).

    Article  CAS  Google Scholar 

  68. Horner-Devine, M. C. & Bohannan, B. J. M. Phylogenetic clustering and overdispersion in bacterial communities. Ecology 87, S100–S108 (2006).

    Article  Google Scholar 

Download references

Acknowledgements

Field and logistical support was provided by Antarctica New Zealand. The research was funded by a grant from the New Zealand Ministry of Business, Innovation and Employment (UOWX1401) and Yale-NUS College Start-Up Fund. F.T.M. is supported by the European Research Council (BIODESERT project; ERC grant agreement number 647038).

Author information

Authors and Affiliations

Authors

Contributions

S.D.J.A. and S.B.P. conceived the study. C.K.L., S.C.C. and S.B.P. secured the research funding. S.D.J.A. and C.K.L. conducted the fieldwork. S.C.C. was the field event leader. T.M. developed and validated the helicopter sampling method. S.D.J.A. performed the laboratory experiments. S.D.J.A., K.C.L., T.C. and S.B.P. performed the data analysis and interpretation. D.A.C., F.T.M. and S.B.P. critically assessed and interpreted the findings. S.B.P. wrote the manuscript.

Corresponding author

Correspondence to Stephen B. Pointing.

Ethics declarations

Competing interests

The authors declare no competing interests.

Additional information

Publisher’s note: Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Supplementary Information

Supplementary Information

Supplementary Figure 1, legends for Supplementary Figures 2–4, Supplementary Figure 5, Supplementary legends for Figures 6–8, Supplementary Figure 9 and legends for Supplementary Datasets 1–6.

Reporting Summary

Supplementary Dataset 1

Taxonomic identity of bacteria by phylum in each air and soil sample. This raw data file accompanies Supplementary Figure 2.

Supplementary Dataset 2

Taxonomic identity of bacteria by class in each air and soil sample. This raw data file accompanies Supplementary Figure 3.

Supplementary Dataset 3

Taxonomic identity of bacteria by genus in each air and soil sample. This raw data file accompanies Supplementary Figure 4.

Supplementary Dataset 4

Taxonomic identity of fungi by phylum in each air and soil sample. This raw data file accompanies Supplementary Figure 6.

Supplementary Dataset 5

Taxonomic identity of fungi by class in each air and soil sample. This raw data file accompanies Supplementary Figure 7.

Supplementary Dataset 6

Taxonomic identity of fungi by genus in each air and soil sample. This raw data file accompanies Supplementary Figure 8.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Archer, S.D.J., Lee, K.C., Caruso, T. et al. Airborne microbial transport limitation to isolated Antarctic soil habitats. Nat Microbiol 4, 925–932 (2019). https://doi.org/10.1038/s41564-019-0370-4

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1038/s41564-019-0370-4

This article is cited by

Search

Quick links

Nature Briefing

Sign up for the Nature Briefing newsletter — what matters in science, free to your inbox daily.

Get the most important science stories of the day, free in your inbox. Sign up for Nature Briefing