Skip to main content

Testing for Differentiation of Microbial Communities Using Phylogenetic Methods: Accounting for Uncertainty of Phylogenetic Inference and Character State Mapping

Microbial Ecology volume 52, pages 408–417 (2006)Cite this article

Abstract

Comparative analyses of microbial communities increasingly involve the assay of 16S rRNA (or other gene) sequences from environmental DNA. Determining whether the composition of two or more communities differ in their phylogenetic composition involves testing for covariation between phylogeny and community type. This approach requires estimating the phylogenetic relationships among all sampled sequences and assessing whether the distribution of sequences among communities differs from the null expectation that sequences are randomly distributed. One method developed for implementing the phylogeny-based test of differentiation, referred to as the Phylogenetic test, relies on a single estimate of the phylogeny. However, for most data sets, many alternative phylogenetic trees provide statistically equivalent descriptions of the data. Because the actual phylogeny is unknown, phylogenetic tests of differentiation among microbial communities must account for phylogenetic uncertainty. In this article, we evaluate bootstrapping and Bayesian phylogenetic methods when implementing the Phylogenetic test using parsimony to map character states, and we investigate the effects of character mapping uncertainty by using a Bayesian approach to stochastically map character states on trees. Our approaches incorporate uncertainty into the tests of two closely related null hypotheses: (1) populations are panmictic, and (2) identical communites existed in both environments over the course of evolutionary history. We use two data sets previously implemented in tests for community differentiation: nitrite reductase genes sampled from marsh and upland soils and 16S rDNA sequences sampled from the human mouth and gut. We show that accounting for phylogenetic and mapping uncertainties can drastically affect results when implementing the Phylogenetic test. Accounting for phylogenetic and character mapping uncertainty provides a more conservative and robust test of covariation between phylogeny and environment when comparing microbial communities using DNA sequences.

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

Access options

Buy single article

Instant access to the full article PDF.

USD 39.95

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Figure 1
Figure 2
Figure 3
Figure 4

References

  1. Acinas, SG, Klepac-Ceraj, V, Hunt, DE, Pharino, C, Ceraj, I, Distel, MF, Polz, MF (2004) Fine-scale phylogenetic arachitecture of a complex bacterial community. Nature 430(6999): 551–554

    Article  PubMed  CAS  Google Scholar 

  2. Alfaro, ME, Zoller, S, Lutzoni, F (2003) Bayes or bootstrap? A simulation study comparing the performance of Bayesian Markov chain Monte Carlo sampling and bootstrapping in assessing phylogenetic confidence. Mol Biol Evol 20: 255–266

    Article  PubMed  CAS  Google Scholar 

  3. Brauer, MJ, Holder, MT, Dries, LA, Zwickl, DJ, Lewis, PO, Hillis, DM (2002) Genetic algorithms and parallel processing in maximum-likelihood phylogeny inference. Mol Biol Evol 19(10): 1717–1726

    PubMed  CAS  Google Scholar 

  4. Cummings, MP, Handley, SA, Myers, DS, Reed, DL, Rokas, A, Winka, K (2003) Comparing bootstrap and posterior probability values in the four-taxon case. Syst Biol 52: 477–487

    Article  PubMed  Google Scholar 

  5. Donachie, SP, Hou, S, Lee, KS, Riley, CW, Pikina, A, Belisle, C, Kempe, S, Gregory, TS, Bossuyt, A, Boerema, J, Liu, J, Frietas, TA, Malahoff, A, Alam, M (2004) The Hawaiian Archipelago: a microbial diversity hotspot. Microb Ecol 48: 509–520

    Article  PubMed  CAS  Google Scholar 

  6. Eckburg, PB, Bik, EM, Bernstein, CN, Purdom, E, Dethlefsen, L, Sargent, M, Gill, SR, Nelson, KE, Relman, DA (2005) Diversity of the human intestinal microbial flora. Science 308: 1635–1638

    Article  PubMed  Google Scholar 

  7. Felsenstein, J (1985) Confidence limits on phylogenies: an approach using the bootstrap. Evolution 39: 783–791

    Article  Google Scholar 

  8. Giribet, G, Edgecombe, GD, Wheeler, WC (2001) Arthropod phylogeny based on eight molecular loci and morphology. Nature 413(6852): 157–161

    Article  PubMed  CAS  Google Scholar 

  9. Hackl, E, Zechmeister-Boltenstern, S, Bodrossy, L, Sessitsch, A (2004) Comparison of diversities and compositions of bacterial populations inhabiting natural forest soils. Appl Environ Microbiol 70: 5057–5065

    Article  PubMed  CAS  Google Scholar 

  10. Harvey, PH, Pagel, MD (1991) The Comparative Method in Evolutionary Biology. Oxford University Press. Oxford, UK

    Google Scholar 

  11. Heijs, SK, Damste, JSS, Forney, LJ (2005) Characterization of a deep-sea microbial mat from an active cold seep at the Milano mud volcano in the Eastern Mediterranean Sea. FEMS Microb Ecol 54: 47–56

    Article  CAS  Google Scholar 

  12. Huelsenbeck, JP, Ronquist, FR (2001) MRBAYES: Bayesian inference of phylogeny. Biometrics 17: 754–756

    CAS  Google Scholar 

  13. Huelsenbeck, JP, Rannala, B, Masly, JP (2000) Accommodating phylogenetic uncertainty in evolutionary studies. Science 288: 2349–2350

    Article  PubMed  CAS  Google Scholar 

  14. Huelsenbeck, JP, Ronquist, F, Nielsen, R, Bollback, JP (2001) Bayesian inference of phylogeny and its impact on evolutionary biology. Science 2944: 2310–2314

    Article  Google Scholar 

  15. Huelsenbeck, JP, Nielsen, R, Bollback, JP (2003) Stochastic mapping of morphological characters. Syst Biol 52(2): 131–158

    Article  PubMed  Google Scholar 

  16. Hughes, JB, Hellmann, JJ, Ricketts, TH, Bohannan, BJ (2001) Counting the uncountable: statistical approaches to estimating microbial diversity. Appl Environ Microbiol 67: 4399–4406

    Article  PubMed  CAS  Google Scholar 

  17. Keane, TM, Naughton, TJ, Travers, SA, McInerney, JO, McCormack, GP (2004) DPRml: distributed phylogeny reconstruction by maximum likelihood. Bioinformatics. 2004 Oct. 28

  18. Kroes, R, Lepp, PW, Relman, D (1999) Bacterial diversity within the human subgingival crevice. Proc Natl Acad Sci USA 96: 14547–14552

    Article  PubMed  CAS  Google Scholar 

  19. Kumar, PS, Griffen, AL, Moeschberger, ML, Leys, EJ (2005) Identification of candidate periodontal pathogens and beneficial species by quantitative 16S clonal analysis. J Clin Microb 43: 3944–3955

    Article  CAS  Google Scholar 

  20. Leache, AD, Reeder, TW (2002) Molecular systematics of the eastern fence lizard (Sceloporus undulatus): a comparison of parsimony, likelihood and Bayesian approaches. Syst Biol 51: 44–68

    Article  PubMed  Google Scholar 

  21. Ley, RE, Backhed, F, Turnbaugh, P, Lozupone, CA, Knight, RD, Gordon, JI (2005) Obesity alters gut microbial community. Proc Natl Acad Sci USA 102: 11070–11075

    Article  PubMed  CAS  Google Scholar 

  22. Maddison, WP, Maddison, DR (1993) MacClade, v. 3. Sinauer Press. Sunderland, MA

    Google Scholar 

  23. Maddison, WP, Slatkin, M (1991) Null models for the number of evolutionary steps in a character on a phylogenetic tree. Evolution 45: 1184–1197

    Article  Google Scholar 

  24. Martin, AP (2002) Phylogenetic approaches for describing and comparing the diversity of microbial communities. Appl Environ Microbiol 68: 3673–3682

    Article  PubMed  CAS  Google Scholar 

  25. McGarvey, JA, Miller, WG, Sanchez, S, Stanker, L (2004) Identification of bacterial populations in dairy wastewaters by use of 16S rRNA gene sequences and other genetic markers. Appl Environ Microbiol 70: 4267–4275

    Article  PubMed  CAS  Google Scholar 

  26. Nielsen, R (2002) Mapping mutations on phylogenies. Syst Biol 51(5): 729–739

    Article  PubMed  Google Scholar 

  27. Pace, N (1997) A molecular view of microbial diversity and the biosphere. Science 276: 734–740

    Article  PubMed  CAS  Google Scholar 

  28. Posada, D, Crandall, KA (1998) Modeltest: testing the model of DNA substitution. Bioinformatics 14: 817–818

    Article  PubMed  CAS  Google Scholar 

  29. Prieme, A, Braker, G, Tiedje, JM (2002) Diversity of nitrite reductase (nirK and nirS) gene fragments in forested upland and wetland soils. Appl Environ Microbiol 68: 1893–1900

    Article  PubMed  CAS  Google Scholar 

  30. Ronquist, F (2004) Bayesian inference of character evolution. Trends Ecol Evol 19(9): 475–481

    Article  PubMed  Google Scholar 

  31. Schadt, CW, Martin, AP, Lipson, DA, Schmidt, SK (2003) Seasonal dynamics of previously unknown fungal lineages in tundra soils. Science 301: 1359–1361

    Article  PubMed  CAS  Google Scholar 

  32. Schloss, PD, Larget, BR, Handelsman, J (2004) Integration of microbial ecology and statistics: a test to compare gene libraries. Appl Environ Microbiol 70: 5485–5492

    Article  PubMed  CAS  Google Scholar 

  33. Schultz, TR, Churchill, GA (1999) The role of subjectivity in reconstructing ancestral character states: a Bayesian approach to unknown rates, states, and transformation asymmetries. Syst Biol 48(3): 651–664

    Article  Google Scholar 

  34. Suau, A, Bonnet, R, Sutren, M, Godon, JJ, Gibson, G, Collins, MD, Dore, J (1999) Direct analysis of genes encoding 16S rRNA from complex communities reveals many novel molecular species within the human gut. Appl Environ Microbiol 65: 4799–4807

    PubMed  CAS  Google Scholar 

  35. Suzuki, Y, Glazko, GV, Nei, M (2002) Overcredibility of molecular phylogenies obtained by Bayesian phylogenetics. Proc Natl Acad Sci USA 99: 16138–16143

    Article  PubMed  CAS  Google Scholar 

  36. Swofford, DL, Olsen, GJ, Waddell, PJ, Hillis, DM (1996) Phylogenetic inference. In: Hillis DM, Moritz C, Mable BK (Eds.) Molecular Systematics2Sinauer Press. Sunderland, MA, pp 407–514

    Google Scholar 

  37. Swofford, DS (2002) PAUP* 4.0. Sinauer Press. Sunderland, MA, USA

    Google Scholar 

  38. Theron, J, Cloete, TE (2000) Molecular techniques for determining microbial diversity and community structure in natural environments. Crit Rev Microbiol 26: 37–57

    Article  PubMed  CAS  Google Scholar 

Download references

Acknowledgments

This work was supported by an NSF Microbial Observatory grant to S. Schmidt and A. Martin. Thanks are due to Steve Schmidt, Sasha Reed, and Elizabeth Costello for editorial comments. We thank J. Bollback for help with SIMMAP. We would also like to thank an anonymous reviewer who helped us immensely with the direction of this article.

Author information

Authors and Affiliations

  1. Department of Ecology and Evolution, University of Colorado, Boulder, CO, 80309, USA

    Ryan T. Jones & Andrew P. Martin

Authors
  1. Ryan T. Jones
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Andrew P. Martin
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Ryan T. Jones.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Jones, R.T., Martin, A.P. Testing for Differentiation of Microbial Communities Using Phylogenetic Methods: Accounting for Uncertainty of Phylogenetic Inference and Character State Mapping. Microb Ecol 52, 408–417 (2006). https://doi.org/10.1007/s00248-006-9002-7

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00248-006-9002-7

Keywords

  • Microbial Community
  • Character State
  • Null Distribution
  • Terminal Restriction Fragment Length Polymorphism
  • Posterior Probability Distribution