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.

OPINION

Keystone taxa as drivers of microbiome structure and functioning

Abstract

Microorganisms have a pivotal role in the functioning of ecosystems. Recent studies have shown that microbial communities harbour keystone taxa, which drive community composition and function irrespective of their abundance. In this Opinion article, we propose a definition of keystone taxa in microbial ecology and summarize over 200 microbial keystone taxa that have been identified in soil, plant and marine ecosystems, as well as in the human microbiome. We explore the importance of keystone taxa and keystone guilds for microbiome structure and functioning and discuss the factors that determine their distribution and activities.

Access options

Rent or Buy article

Get time limited or full article access on ReadCube.

from$8.99

All prices are NET prices.

Fig. 1: Keystone taxa in the microbiome.
Fig. 2: Keystone taxa in microbial communities and the factors influencing their functioning in an environment.
Fig. 3: Characterizing and harnessing keystone taxa.

References

  1. 1.

    Fierer, N. Embracing the unknown: disentangling the complexities of the soil microbiome. Nat. Rev. Microbiol. 15, 579–590 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  2. 2.

    Bardgett, R. D. & van der Putten, W. H. Belowground biodiversity and ecosystem functioning. Nature 515, 505–511 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  3. 3.

    Fuhrman, J. A. Microbial community structure and its functional implications. Nature 459, 193–199 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  4. 4.

    van der Heijden, M. G. A., Bardgett, R. D. & Van Straalen, N. M. The unseen majority: soil microbes as drivers of plant diversity and productivity in terrestrial ecosystems. Ecol. Lett. 11, 296–310 (2008).

    PubMed  PubMed Central  Google Scholar 

  5. 5.

    Graham, E. B. et al. Microbes as engines of ecosystem function: when does community structure enhance predictions of ecosystem processes? Front. Microbiol. 7, 1–10 (2016).

    Google Scholar 

  6. 6.

    Hamady, M. & Knight, R. Microbial community profiling for human microbiome projects: tools, techniques, and challenges. Genome Res. 19, 1141–1152 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  7. 7.

    Barberán, A., Bates, S. T., Casamayor, E. O. & Fierer, N. Using network analysis to explore co-occurrence patterns in soil microbial communities. ISME J. 6, 343–351 (2012).

    PubMed  PubMed Central  Google Scholar 

  8. 8.

    Banerjee, S. et al. Determinants of bacterial communities in Canadian agroforestry systems. Environ. Microbiol. 18, 1805–1816 (2016).

    PubMed  PubMed Central  Google Scholar 

  9. 9.

    Zhang, Z. et al. Spatial heterogeneity and co-occurrence patterns of human mucosal-associated intestinal microbiota. ISME J. 8, 881–893 (2014).

    PubMed  PubMed Central  Google Scholar 

  10. 10.

    Fuhrman, J. A., Cram, J. A. & Needham, D. M. Marine microbial community dynamics and their ecological interpretation. Nat. Rev. Microbiol. 13, 133–146 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  11. 11.

    Prosser, J. I. et al. The role of ecological theory in microbial ecology. Nat. Rev. Microbiol. 5, 384–392 (2007).

    CAS  PubMed  PubMed Central  Google Scholar 

  12. 12.

    Costello, E. K., Stagaman, K., Dethlefsen, L. & Bohannan, B. J. M. & Relman, D. A. The application of ecological theory toward an understanding of the human microbiome. Science 336, 1255–1262 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  13. 13.

    Proulx, S. R., Promislow, D. E. L. & Phillips, P. C. Network thinking in ecology and evolution. Trends Ecol. Evol. 20, 345–353 (2005).

    PubMed  PubMed Central  Google Scholar 

  14. 14.

    Zhou, J. et al. Functional molecular ecological networks. MBio 1, e00169–00110 (2010).

    PubMed  PubMed Central  Google Scholar 

  15. 15.

    Reshef, D. N. et al. Detecting novel associations in large data sets. Science 334, 1518–1524 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  16. 16.

    Ruan, Q. et al. Local similarity analysis reveals unique associations among marine bacterioplankton species and environmental factors. Bioinformatics 22, 2532–2538 (2006).

    CAS  Google Scholar 

  17. 17.

    Friedman, J. & Alm, E. J. Inferring correlation networks from genomic survey data. PLoS Comput. Biol. 8, 1–11 (2012).

    Google Scholar 

  18. 18.

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

    Google Scholar 

  19. 19.

    Weiss, S. et al. Correlation detection strategies in microbial data sets vary widely in sensitivity and precision. ISME J. 10, 1–13 (2016).

    CAS  Google Scholar 

  20. 20.

    Agler, M. T. et al. Microbial hub taxa link host and abiotic factors to plant microbiome variation. PLoS Biol. 14, 1–31 (2016).

    Google Scholar 

  21. 21.

    Gilbert, J. a et al. Defining seasonal marine microbial community dynamics. ISME J. 6, 298–308 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  22. 22.

    Fisher, C. K. & Mehta, P. Identifying keystone species in the human gut microbiome from metagenomic timeseries using sparse linear regression. PLoS ONE 9, 1–10 (2014).

    Google Scholar 

  23. 23.

    Shetty, S. A., Hugenholtz, F., Lahti, L., Smidt, H. & de Vos, W. M. Intestinal microbiome landscaping: insight in community assemblage and implications for microbial modulation strategies. FEMS Microbiol. Rev. 41, 182–199 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  24. 24.

    Vick-Majors, T. J., Priscu, J. C. & Amaral-Zettler, L. A. Modular community structure suggests metabolic plasticity during the transition to polar night in ice-covered Antarctic lakes. ISME J. 8, 778–789 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  25. 25.

    Gokul, J. K. et al. Taxon interactions control the distributions of cryoconite bacteria colonizing a high Arctic ice cap. Mol. Ecol. 25, 3752–3767 (2016).

    PubMed  PubMed Central  Google Scholar 

  26. 26.

    Comte, J., Lovejoy, C., Crevecoeur, S. & Vincent, W. F. Co-occurrence patterns in aquatic bacterial communities across changing permafrost landscapes. Biogeosciences 13, 175–190 (2016).

    CAS  Google Scholar 

  27. 27.

    Berry, D. & Widder, S. Deciphering microbial interactions and detecting keystone species with co-occurrence networks. Front. Microbiol. 5, 1–14 (2014).

    Google Scholar 

  28. 28.

    Paine, R. T. Food web complexity and species diversity. Am. Nat. 100, 65–75 (1966).

    Google Scholar 

  29. 29.

    Mills, L. S. & Doak, D. F. The keystone-species concept in ecology and conservation. BioScience 43, 219–224 (1993).

    Google Scholar 

  30. 30.

    Cottee-Jones, H. E. W. & Whittaker, R. J. The keystone species concept: a critical appraisal. Front. Biogeogr. 4, 217–220 (2012).

    Google Scholar 

  31. 31.

    Power, M. E. et al. Challenges in the quest for keystones. Bioscience 46, 609–620 (1996).

    Google Scholar 

  32. 32.

    Paine, R. T. A note on trophic complexity and community stability. Am. Nat. 103, 91–93 (1969).

    Google Scholar 

  33. 33.

    Dunne, J. A., Williams, R. J. & Martinez, N. D. Network structure and biodiversity loss in food webs: robustness increase with connectance. Ecol. Lett. 5, 558–567 (2002).

    Google Scholar 

  34. 34.

    Deng, Y. et al. Molecular ecological network analyses. BMC Bioinformatics 13, 113 (2012).

    PubMed  PubMed Central  Google Scholar 

  35. 35.

    Lupatini, M. et al. Network topology reveals high connectance levels and few key microbial genera within soils. Front. Environ. Sci. 2, 1–11 (2014).

    Google Scholar 

  36. 36.

    Zhou, J., Deng, Y., Luo, F., He, Z. & Yang, Y. Phylogenetic molecular ecological network of soil microbial communities in response to elevated CO2. MBio 2, e00122–e00111 (2011).

    PubMed  PubMed Central  Google Scholar 

  37. 37.

    Eldridge, D. J. et al. Soil-foraging animals alter the composition and co-occurrence of microbial communities in a desert shrubland. ISME J. 9, 1–11 (2015).

    Google Scholar 

  38. 38.

    Ma, B. et al. Geographic patterns of co-occurrence network topological features for soil microbiota at continental scale in eastern China. ISME J. 10, 1–11 (2016).

    Google Scholar 

  39. 39.

    Banerjee, S. et al. Network analysis reveals functional redundancy and keystone taxa amongst bacterial and fungal communities during organic matter decomposition in an arable soil. Soil Biol. Biochem. 97, 188–198 (2016).

    CAS  Google Scholar 

  40. 40.

    Jiang, Y. et al. Plant cultivars imprint the rhizosphere bacterial community composition and association networks. Soil Biol. Biochem. 109, 145–155 (2017).

    CAS  Google Scholar 

  41. 41.

    Li, F., Chen, L., Zhang, J., Yin, J. & Huang, S. Bacterial community structure after long-term organic and inorganic fertilization reveals important associations between soil nutrients and specific taxa involved in nutrient transformations. Front. Microbiol. 8, 187 (2017).

    PubMed  PubMed Central  Google Scholar 

  42. 42.

    Liang, Y. et al. Long-term oil contamination alters the molecular ecological networks of soil microbial functional genes. Front. Microbiol. 7, 1–13 (2016).

    Google Scholar 

  43. 43.

    Wang, H. et al. Combined use of network inference tools identifies ecologically meaningful bacterial associations in a paddy soil. Soil Biol. Biochem. 105, 227–235 (2017).

    CAS  Google Scholar 

  44. 44.

    Hill, R. et al. Temporal and spatial influences incur reconfiguration of Arctic heathland soil bacterial community structure. Environ. Microbiol. 18, 1942–1953 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  45. 45.

    Li, B. et al. Metagenomic and network analysis reveal wide distribution and co-occurrence of environmental antibiotic resistance genes. ISME J. 9, 1–13 (2015).

    Google Scholar 

  46. 46.

    Yang, S. et al. Hydrocarbon degraders establish at the costs of microbial richness, abundance and keystone taxa after crude oil contamination in permafrost environments. Sci. Rep. 6, 37473 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  47. 47.

    Chao, Y. et al. Structure, variation, and co-occurrence of soil microbial communities in abandoned sites of a rare earth elements mine. Environ. Sci. Technol. 50, 11481–11490 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  48. 48.

    Jiao, S. et al. Bacterial communities in oil contaminated soils: biogeography and co-occurrence patterns. Soil Biol. Biochem. 98, 64–73 (2016).

    CAS  Google Scholar 

  49. 49.

    Shi, S. et al. The interconnected rhizosphere: high network complexity dominates rhizosphere assemblages. Ecol. Lett. 19, 926–936 (2016).

    PubMed  PubMed Central  Google Scholar 

  50. 50.

    Yan, Y., Kuramae, E. E., De Hollander, M., Klinkhamer, P. G. & Van Veen, J. A. Functional traits dominate the diversity-related selection of bacterial communities in the rhizosphere. ISME J. 11, 1–11 (2016).

    Google Scholar 

  51. 51.

    Geng, H., Tran-Gyamfi, M. B., Lane, T. W., Sale, K. L. & Yu, E. T. Changes in the structure of the microbial community associated with Nannochloropsis salina following treatments with antibiotics and bioactive compounds. Front. Microbiol. 7, 1–13 (2016).

    Google Scholar 

  52. 52.

    Graham, E. B. et al. Deterministic influences exceed dispersal effects on hydrologically-connected microbiomes. Environ. Microbiol. 19, 1552–1567 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  53. 53.

    Ji, Y. et al. Structure and function of methanogenic microbial communities in sediments of Amazonian lakes with different water types. Environ. Microbiol. 18, 5082–5100 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  54. 54.

    Musat, N. et al. A single-cell view on the ecophysiology of anaerobic phototrophic bacteria. Proc. Natl Acad. Sci. USA 105, 17861–17866 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  55. 55.

    Zhao, D. et al. Network analysis reveals seasonal variation of co-occurrence correlations between Cyanobacteria and other bacterioplankton. Sci. Total Environ. 573, 817–825 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  56. 56.

    Curtis, M. M. et al. The gut commensal bacteroides thetaiotaomicron exacerbates enteric infection through modification of the metabolic landscape. Cell Host Microbe 16, 759–769 (2014).

    CAS  PubMed  PubMed Central  Google Scholar 

  57. 57.

    Maldonado-Contreras, A. et al. Structure of the human gastric bacterial community in relation to Helicobacter pylori status. ISME J. 5, 574–579 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  58. 58.

    Trosvik, P. & de Muinck, E. J. Ecology of bacteria in the human gastrointestinal tract — identification of keystone and foundation taxa. Microbiome 3, 44 (2015).

    PubMed  PubMed Central  Google Scholar 

  59. 59.

    Wu, S. et al. A human colonic commensal promotes colon tumorigenesis via activation of T helper type 17 T cell responses. Nat. Med. 15, 1016–1022 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  60. 60.

    Ze, X., Duncan, S. H., Louis, P. & Flint, H. J. Ruminococcus bromii is a keystone species for the degradation of resistant starch in the human colon. ISME J. 6, 1535–1543 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  61. 61.

    Ding, J. et al. Soil organic matter quantity and quality shape microbial community compositions of subtropical broadleaved forests. Mol. Ecol. 24, 5175–5185 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  62. 62.

    Nunez, M. A. & Dimarco, R. D. The encyclopedia of sustainability, vol. 5: ecosystem management and sustainability (eds Craig, R. K., Nagle, J. C., Pardy, B., Schmitz, O. J. & Smith, W. K.) 226–230 (Berkshire Publishing, 2012).

  63. 63.

    Hector, A. et al. Plant diversity and productivity experiments in European grasslands. Science 286, 1123–1127 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  64. 64.

    Hajishengallis, G. et al. Low-abundance biofilm species orchestrates inflammatory periodontal disease through the commensal microbiota and complement. Cell Host Microbe 10, 497–506 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  65. 65.

    Faust, K. & Raes, J. Microbial interactions: from networks to models. Nat. Rev. Microbiol. 10, 538–550 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  66. 66.

    Cardona, C., Weisenhorn, P., Henry, C. & Gilbert, J. A. Network-based metabolic analysis and microbial community modeling. Curr. Opin. Microbiol. 31, 124–131 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  67. 67.

    Strogatz, S. H. Exploring complex networks. Nature 410, 268–276 (2001).

    CAS  PubMed  PubMed Central  Google Scholar 

  68. 68.

    Newman, M. E. J. The structure and function of complex networks. Soc. Ind. Appl. Math. Rev. 45, 167–256 (2003).

    Google Scholar 

  69. 69.

    van der Heijden, M. G. A. & Hartmann, M. Networking in the plant microbiome. PLoS Biol. 14, 1–9 (2016).

    Google Scholar 

  70. 70.

    Barabási, A. L., Gulbahce, N. & Loscalzo, J. Network medicine: a network-based approach to human disease. Nat. Rev. Genet. 12, 56–68 (2011).

    PubMed  PubMed Central  Google Scholar 

  71. 71.

    Hartman, K. et al. Cropping practices manipulate abundance patterns of root and soil microbiome members paving the way to smart farming. Microbiome 6, 14 (2018).

    PubMed  PubMed Central  Google Scholar 

  72. 72.

    Steele, J. A. et al. Marine bacterial, archaeal and protistan association networks reveal ecological linkages. ISME J. 5, 1414–1425 (2011).

    PubMed  PubMed Central  Google Scholar 

  73. 73.

    Andreote, F. D. et al. Culture-independent assessment of rhizobiales-related alphaproteobacteria and the diversity of Methylobacterium in the rhizosphere and rhizoplane of transgenic eucalyptus. Microb. Ecol. 57, 82–93 (2009).

    PubMed  PubMed Central  Google Scholar 

  74. 74.

    Hajishengallis, G., Darveau, R. P. & Curtis, M. A. The keystone-pathogen hypothesis. Nat. Rev. Microbiol. 10, 717–725 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  75. 75.

    Bäckhed, F., Ley, R. E., Sonnenburg, J. L., Peterson, D. A. & Gordon, J. I. Host-bacterial mutualism in the human intestine. Science 307, 1915–1920 (2005).

    PubMed  PubMed Central  Google Scholar 

  76. 76.

    Garrett, W. S. et al. Enterobacteriaceae act in concert with the gut microbiota to induce spontaneous and maternally transmitted colitis. Cell Host Microbe 8, 292–300 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  77. 77.

    Van Der Heijden, M. G. A. et al. Symbiotic bacteria as a determinant of plant community structure and plant productivity in dune grassland. FEMS Microbiol. Ecol. 56, 178–187 (2006).

    PubMed  PubMed Central  Google Scholar 

  78. 78.

    Kommineni, S. et al. Bacteriocin production augments niche competition by enterococci in the mammalian gastrointestinal tract. Nature 526, 719–722 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  79. 79.

    van der Heijden, M. G. A. et al. Mycorrhizal fungal diversity determines plant biodiversity, ecosystem variability and productivity. Nature 396, 69–72 (1998).

    Google Scholar 

  80. 80.

    Herren, C. M. & McMahon, K. D. Small subsets of highly connected taxa predict compositional change in microbial communities. bioRxiv https://doi.org/10.1101/159087 (2017).

  81. 81.

    Grace, J. B., Anderson, T., Olff, H. & Scheiner, S. On the specification of structural equation models for ecological systems. Ecol. Monogr. 80, 67–87 (2010).

    Google Scholar 

  82. 82.

    Lamb, E. G., Shirtliffe, S. J. & May, W. E. Structural equation modeling in the plant sciences: an example using yield components in oat. Can. J. Plant Sci. 91, 603–619 (2011).

    Google Scholar 

  83. 83.

    Banerjee, S., Bora, S., Thrall, P. H. & Richardson, A. E. Soil C and N as causal factors of spatial variation in extracellular enzyme activity across grassland-woodland ecotones. Appl. Soil Ecol. 105, 1–8 (2016).

    Google Scholar 

  84. 84.

    Mouquet, N., Gravel, D., Massol, F. & Calcagno, V. Extending the concept of keystone species to communities and ecosystems. Ecol. Lett. 16, 1–8 (2013).

    Google Scholar 

  85. 85.

    Nichols, D. et al. Use of ichip for high-throughput in situ cultivation of ‘uncultivable’ microbial species. Appl. Environ. Microbiol. 76, 2445–2450 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  86. 86.

    Gavrish, E., Bollmann, A., Epstein, S. & Lewis, K. A trap for in situ cultivation of filamentous actinobacteria. J. Microbiol. Methods 72, 257–262 (2008).

    CAS  PubMed  PubMed Central  Google Scholar 

  87. 87.

    Bouguelia, S. et al. On-chip microbial culture for the specific detection of very low levels of bacteria. Lab. Chip 13, 4024 (2013).

    CAS  PubMed  PubMed Central  Google Scholar 

  88. 88.

    Park, J., Kerner, A., Burns, M. A. & Lin, X. N. Microdroplet-enabled highly parallel co-cultivation of microbial communities. PLoS ONE 6, e17019 (2011).

    Google Scholar 

  89. 89.

    Stanley, C. E. & van der Heijden, M. G. A. Microbiome-on-a-chip: new frontiers in plant–microbiota research. Trends Microbiol. 25, 610–613 (2017).

    CAS  PubMed  PubMed Central  Google Scholar 

  90. 90.

    Scheffer, M., Hosper, S. H., Meijer, M. L., Moss, B. & Jeppesen, E. Alternative equilibria in shallow lakes. Trends Ecol. Evol. 8, 275–279 (1993).

    CAS  PubMed  PubMed Central  Google Scholar 

  91. 91.

    Schimel, J. P. & Schaeffer, S. M. Microbial control over carbon cycling in soil. Front. Microbiol. 3, 1–11 (2012).

    Google Scholar 

  92. 92.

    Vandenkoornhuyse, P., Quaiser, A., Duhamel, M., Le Van, A. & Dufresne, A. The importance of the microbiome of the plant holobiont. New Phytol. 206, 1196–1206 (2015).

    PubMed  PubMed Central  Google Scholar 

  93. 93.

    Maloy, K. J. & Powrie, F. Intestinal homeostasis and its breakdown in inflammatory bowel disease. Nature 474, 298–306 (2011).

    CAS  PubMed  PubMed Central  Google Scholar 

  94. 94.

    Hajishengallis, G. & Lamont, R. J. Dancing with the stars: how choreographed bacterial interactions dictate nososymbiocity and give rise to keystone pathogens, accessory pathogens, and pathobionts. Trends Microbiol. 24, 477–489 (2016).

    CAS  PubMed  PubMed Central  Google Scholar 

  95. 95.

    Hill, D. & Artis, D. Intestinal bacteria and the regulation of immune cell homeostasis. Annu. Rev. Immunol. 28, 623–667 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  96. 96.

    Raaijmakers, J. M. & Weller, D. M. Natural plant protection by 2,4-diacetylphloroglucinol - producing Pseudomonas spp. in take-all decline soils. APS. 11, 144–152 (1998).

    CAS  Google Scholar 

  97. 97.

    van Der Heijden, M. G. A., Martin, F. M., Selosse, M. A. & Sanders, I. R. Mycorrhizal ecology and evolution: the past, the present, and the future. New Phytol. 205, 1406–1423 (2015).

    PubMed  PubMed Central  Google Scholar 

  98. 98.

    Shade, A. & Handelsman, J. Beyond the Venn diagram: the hunt for a core microbiome. Environ. Microbiol. 14, 4–12 (2012).

    CAS  PubMed  PubMed Central  Google Scholar 

  99. 99.

    Turnbaugh, P. J. et al. A core gut microbiom in obese and lean twins. Nature 457, 480–484 (2009).

    CAS  PubMed  PubMed Central  Google Scholar 

  100. 100.

    Yeoh, Y. K. et al. Evolutionary conservation of a core root microbiome across plant phyla along a tropical soil chronosequence. Nat. Commun. 8, 215 (2017).

    PubMed  PubMed Central  Google Scholar 

  101. 101.

    Brown, J. H. & Heske, E. J. Control of a desert-grassland transition by a keystone rodent guild. Science 250, 1705–1707 (1990).

    CAS  PubMed  PubMed Central  Google Scholar 

  102. 102.

    Jones, C. M. et al. Recently identified microbial guild mediates soil N2O sink capacity. Nat. Clim. Chang. 4, 801–805 (2014).

    CAS  Google Scholar 

  103. 103.

    Lynch, M. D. J. & Neufeld, J. D. Ecology and exploration of the rare biosphere. Nat. Rev. Microbiol. 13, 217–229 (2015).

    CAS  PubMed  PubMed Central  Google Scholar 

  104. 104.

    Jousset, A. et al. Where less may be more: how the rare biosphere pulls ecosystems strings. ISME J. 11, 853–862 (2017).

    PubMed  PubMed Central  Google Scholar 

  105. 105.

    Pester, M., Bittner, N., Deevong, P., Wagner, M. & Loy, A. A ‘rare biosphere’ microorganism contributes to sulfate reduction in a peatland. ISME J. 4, 1591–1602 (2010).

    CAS  PubMed  PubMed Central  Google Scholar 

  106. 106.

    Stinson, K. A. et al. Invasive plant suppresses the growth of native tree seedlings by disrupting belowground mutualisms. PLoS Biol. 4, 727–731 (2006).

    CAS  Google Scholar 

  107. 107.

    Manefield, M., Whiteley, A. S., Griffiths, R. I. & Bailey, M. J. RNA stable isotope probing, a novel means of linking microbial community function to phylogeny. Appl. Environ. Microbiol. 68, 5367–5373 (2002).

    CAS  PubMed  PubMed Central  Google Scholar 

Download references

Acknowledgements

The authors thank the referees, whose constructive comments and insightful suggestions greatly improved the quality of the manuscript. They also thank U. Kaufmann for help with a figure and C. Stanley for proofreading the manuscript. Work in the author’s laboratory was supported by the Swiss National Science Foundation (Grant No. 31003A_166079 awarded to M.G.A.v.d.H.).

Reviewer information

Nature Reviews Microbiology thanks Janet Jansson and the other anonymous reviewer(s) for their contribution to the peer review of this work.

Author information

Affiliations

Authors

Contributions

S.B. researched data for the article. S.B. and M.G.A.v.d.H made substantial contributions to the discussion of content and writing of the article. S.B, K.S. and M.G.A.v.d.H. reviewed and edited the manuscript before submission.

Corresponding authors

Correspondence to Samiran Banerjee or Marcel G. A. van der Heijden.

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.

Electronic supplementary material

Rights and permissions

Reprints and Permissions

About this article

Verify currency and authenticity via CrossMark

Cite this article

Banerjee, S., Schlaeppi, K. & van der Heijden, M.G.A. Keystone taxa as drivers of microbiome structure and functioning. Nat Rev Microbiol 16, 567–576 (2018). https://doi.org/10.1038/s41579-018-0024-1

Download citation

Further reading

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