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Analysis of methanotroph community composition using a pmoA-based microbial diagnostic microarray

Abstract

Microbial diagnostic microarrays (MDMs) are highly parallel hybridization platforms containing multiple sets of immobilized oligonucleotide probes used for parallel detection and identification of many different microorganisms in environmental and clinical samples. Each probe is approximately specific to a given group of organisms. Here we describe the protocol used to develop and validate an MDM method for the semiquantification of a range of functional genes—in this case, particulate methane monooxygenase (pmoA)—and we give an example of its application to the study of the community structure of methanotrophs and functionally related bacteria in the environment. The development and validation of an MDM, following this protocol, takes 6 months. The pmoA MDM described in detail comprises 199 probes and addresses 50 different species-level clades. An experiment comprising 24 samples can be completed, from DNA extraction to data acquisition, within 3 d (12–13 h bench work).

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Figure 1
Figure 2: An example of multivariate statistical analysis of square root-transformed microarray data.
Figure 3: An example of the application of the microarray for the study of methane oxidizing bacteria in environmental samples.
Figure 4: The Belly Dancer and its components.
Figure 5: An example of microarray layout versus spotting plate layout.

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References

  1. Liu, W.T., Marsh, T.L., Cheng, H. & Forney, L.J. Characterization of microbial diversity by determining terminal restriction fragment length polymorphisms of genes encoding 16S rRNA. Appl. Environ. Microbiol. 63, 4516–4522 (1997).

    CAS  PubMed  PubMed Central  Google Scholar 

  2. Muyzer, G. & Smalla, K. Application of denaturing gradient gel electrophoresis (DGGE) and temperature gradient gel electrophoresis (TGGE) in microbial ecology. Antonie van Leeuwenhoek 73, 127–141 (1998).

    Article  CAS  Google Scholar 

  3. Muyzer, G., Teske, A., Wirsen, C. & Jannasch, H. Phylogenetic relationships of Thiomicrospira species and their identification in deep-sea hydrothermal vent samples by denaturing gradient gel electrophoresis of 16S rDNA fragments. Arch. Microbiol. 164, 165–172 (1995).

    Article  CAS  Google Scholar 

  4. Brown, M.V. et al. Microbial community structure in the North Pacific ocean. ISME J. 3, 1374–1386 (2009).

    Article  CAS  Google Scholar 

  5. Sogin, M.L. et al. Microbial diversity in the deep sea and the underexplored 'rare biosphere'. Proc. Natl. Acad. Sci. USA 103, 12115–12120 (2006).

    Article  CAS  Google Scholar 

  6. Brodie, E.L. et al. Application of a high-density oligonucleotide microarray approach to study bacterial population dynamics during uranium reduction and reoxidation. Appl. Environ. Microbiol. 72, 6288–6298 (2006).

    Article  CAS  Google Scholar 

  7. Roh, S.W., Abell, G.C.J., Kim, K.-H., Nam, Y.-D. & Bae, J.-W. Comparing microarrays and next-generation sequencing technologies for microbial ecology research. Trends Biotechnol. 28, 291–299 (2010).

    Article  CAS  Google Scholar 

  8. Sessitsch, A. et al. Diagnostic microbial microarrays in soil ecology. New Phytol. 171, 719–735 (2006).

    Article  CAS  Google Scholar 

  9. Lee, D.Y., Shannon, K. & Beaudette, L.A. Detection of bacterial pathogens in municipal wastewater using an oligonucleotide microarray and real-time quantitative PCR. J. Microbiol. Methods 65, 453–467 (2006).

    Article  Google Scholar 

  10. Wiesinger-Mayr, H. et al. Identification of human pathogens isolated from blood using microarray hybridisation and signal pattern recognition. BMC Microbiol. 7, 78 (2007).

    Article  Google Scholar 

  11. Yoshida, C. et al. Methodologies towards the development of an oligonucleotide microarray for determination of Salmonella serotypes. J. Microbiol. Methods 70, 261–271 (2007).

    Article  CAS  Google Scholar 

  12. Rich, V.I., Konstantinidis, K. & DeLong, E.F. Design and testing of 'genome-proxy' microarrays to profile marine microbial communities. Environ. Microbiol. 10, 506–521 (2008).

    Article  CAS  Google Scholar 

  13. Kostic, T. et al. A microbial diagnostic microarray technique for the sensitive detection and identification of pathogenic bacteria in a background of nonpathogens. Anal. Biochem. 360, 244–254 (2007).

    Article  CAS  Google Scholar 

  14. Strommenger, B. et al. DNA microarray for the detection of therapeutically relevant antibiotic resistance determinants in clinical isolates of Staphylococcus aureus. Mol. Cell Probes 21, 161–170 (2007).

    Article  CAS  Google Scholar 

  15. Hemme, C.L. et al. Metagenomic insights into evolution of a heavy metal-contaminated groundwater microbial community. ISME J. 4, 660–672 (2010).

    Article  CAS  Google Scholar 

  16. Yergeau, E. et al. Environmental microarray analyses of Antarctic soil microbial communities. ISME J. 3, 340–351 (2009).

    Article  CAS  Google Scholar 

  17. Bodrossy, L. et al. Development and validation of a diagnostic microbial microarray for methanotrophs. Environ. Microbiol. 5, 566–582 (2003).

    Article  CAS  Google Scholar 

  18. Stralis-Pavese, N. et al. Optimization of diagnostic microarray for application in analysing landfill methanotroph communities under different plant covers. Environ. Microbiol. 6, 347–363 (2004).

    Article  CAS  Google Scholar 

  19. Taroncher-Oldenburg, G., Griner, E.M., Francis, C.A. & Ward, B.B. Oligonucleotide microarray for the study of functional gene diversity in the nitrogen cycle in the environment. Appl. Environ. Microbiol. 69, 1159–1171 (2003).

    Article  CAS  Google Scholar 

  20. Wu, L. et al. Development and evaluation of functional gene arrays for detection of selected genes in the environment. Appl. Environ. Microbiol. 67, 5780–5790 (2001).

    Article  CAS  Google Scholar 

  21. He, Z. et al. GeoChip 3.0 as a high-throughput tool for analyzing microbial community composition, structure and functional activity. ISME J. 4, 1167–1179 (2010).

    Article  CAS  Google Scholar 

  22. He, Z. et al. GeoChip: a comprehensive microarray for investigating biogeochemical, ecological and environmental processes. ISME J. 1, 67–77 (2007).

    Article  CAS  Google Scholar 

  23. Gebert, J., Singh, B.K., Pan, Y. & Bodrossy, L. Activity and structure of methanotrophic communities in landfill cover soils. Environ. Microbiol. Reports 1, 414–423 (2009).

    Article  CAS  Google Scholar 

  24. Bodrossy, L. et al. mRNA-based parallel detection of active methanotroph populations using a diagnostic microarray. Appl. Environ. Microbiol. 72, 1672–1676 (2006).

    Article  CAS  Google Scholar 

  25. Fjellbirkeland, A., Torsvik, V. & Øvreås, L. Methanotrophic diversity in an agricultural soil as evaluated by denaturing gradient gel electrophoresis profiles of pmoA, mxaF and 16S rDNA sequences. Antonie van Leeuwenhoek 79, 209–217 (2001).

    Article  CAS  Google Scholar 

  26. Horz, H.-P., Yimga, M.T. & Liesack, W. Detection of methanotroph diversity on roots of submerged rice plants by molecular retrieval of pmoA, mmoX, mxaF, and 16S rRNA and ribosomal DNA, including pmoA-based terminal restriction fragment length polymorphism profiling. Appl. Environ. Microbiol. 67, 4177–4185 (2001).

    Article  CAS  Google Scholar 

  27. Holmes, A.J., Costello, A., Lidstrom, M.E. & Murrell, J.C. Evidence that participate methane monooxygenase and ammonia monooxygenase may be evolutionarily related. FEMS Microbiol. Lett. 132, 203–208 (1995).

    Article  CAS  Google Scholar 

  28. Abell, G.C.J., Stralis-Pavese, N., Sessitsch, A. & Bodrossy, L. Grazing affects methanotroph activity and diversity in an alpine meadow soil. Environ. Microbiol. Rep. 1, 457–465 (2009).

    Article  CAS  Google Scholar 

  29. Han, B. et al. Diversity and activity of methanotrophs in alkaline soil from a Chinese coal mine. FEMS Microbiol. Ecol. 70, 40–51 (2009).

    Article  Google Scholar 

  30. Moussard, H., Stralis-Pavese, N., Bodrossy, L., Josh, D.N. & Murrell, J.C. Identification of active methylotrophic bacteria inhabiting surface sediment of a marine estuary. Environ. Microbiol. Rep. 1, 424–433 (2009).

    Article  CAS  Google Scholar 

  31. Chen, Y. et al. Diversity of the active methanotrophic community in acidic peatlands as assessed by mRNA and SIP-PLFA analyses. Environ. Microbiol. 10, 446–459 (2008).

    Article  CAS  Google Scholar 

  32. Kip, N. et al. Global prevalence of methane oxidation by symbiotic bacteria in peat-moss ecosystems. Nat. Geosci. 3, 617–621 (2010).

    Article  CAS  Google Scholar 

  33. Murrell, J.C. & Smith, T.J. Biochemistry and molecular biology of methane monooxygenase. Handbook of Hydrocarbon and Lipid Microbiology (ed. Timmis, K.N.) 1046–1055 (Springer-Verlag, 2010).

  34. Bodrossy, L. Diagnostic oligonucleotide microarrays for microbiology. in A Beginner's Guide to Microarrays, Vol 1 (ed. Blalock, E.) 43–92 (Kluwer Academic Publishers, 2003).

  35. Brown, T.J. & Anthony, R.M. The addition of low numbers of 3′ thymine bases can be used to improve the hybridization signal of oligonucleotides for use within arrays on nylon supports. J. Microbiol. Methods 42, 203–207 (2000).

    Article  CAS  Google Scholar 

  36. Guo, Z., Guilfoyle, R.A., Thiel, A.J., Wang, R. & Smith, L.M. Direct fluorescence analysis of genetic polymorphisms by hybridization with oligonucleotide arrays on glass supports. Nucleic Acids Res. 22, 5456–5465 (1994).

    Article  CAS  Google Scholar 

  37. Shchepinov, M.S., Case-Green, S.C. & Southern, E.M. Steric factors influencing hybridisation of nucleic acids to oligonucleotide arrays. Nucleic Acids Res. 25, 1155–1161 (1997).

    Article  CAS  Google Scholar 

  38. Peplies, J., Glockner, F.O. & Amann, R. Optimization strategies for DNA microarray-based detection of bacteria with 16S rRNA-targeting oligonucleotide probes. Appl. Environ. Microbiol. 69, 1397–1407 (2003).

    Article  CAS  Google Scholar 

  39. Hughes, J.B., Hellmann, J.J., Ricketts, T.H. & Bohannan, B.J. Counting the uncountable: statistical approaches to estimating microbial diversity. Appl. Environ. Microbiol. 67, 4399–4406 (2001).

    Article  CAS  Google Scholar 

  40. Costello, A.M. & Lidstrom, M.E. Molecular characterization of functional and phylogenetic genes from natural populations of methanotrophs in lake sediments. Appl. Environ. Microbiol. 65, 5066–5074 (1999).

    CAS  PubMed  PubMed Central  Google Scholar 

  41. Bourne, D.G., McDonald, I.R. & Murrell, J.C. Comparison of pmoA PCR primer sets as tools for investigating methanotroph diversity in three Danish soils. Appl. Environ. Microbiol. 67, 3802–3809 (2001).

    Article  CAS  Google Scholar 

  42. Ramette, A. Multivariate analyses in microbial ecology. FEMS Microbiol. Ecol. 62, 142–160 (2007).

    Article  CAS  Google Scholar 

  43. Clarke, K.R. Non-parametric multivariate analyses of changes in community structure. Australian J. Ecol. 18, 117–143 (1993).

    Article  Google Scholar 

  44. Anderson, M.J., Gorley, R.N. & Clarke, K.R. PERMANOVA+ for PRIMER: Guide to Software and Statistical Methods (Primer-E, Plymouth, UK, 2008).

  45. Cebron, A. et al. Identity of active methanotrophs in landfill cover soil as revealed by DNA-stable isotope probing. FEMS Microbiol. Ecol. 62, 12–23 (2007).

    Article  CAS  Google Scholar 

  46. Cebron, A. et al. Nutrient amendments in soil DNA stable isotope probing experiments reduce the observed methanotroph diversity. Appl. Environ. Microbiol. 73, 798–807 (2007).

    Article  CAS  Google Scholar 

  47. Chen, Y. et al. Revealing the uncultivated majority: combining DNA stable-isotope probing, multiple displacement amplification and metagenomic analyses of uncultivated Methylocystis in acidic peatlands. Environ. Microbiol. 10, 2609–2622 (2008).

    Article  CAS  Google Scholar 

  48. Chen, Y. et al. The impact of burning and Calluna removal on below-ground methanotroph diversity and activity in a peatland soil. Appl. Soil Ecol. 40, 291–298 (2008).

    Article  Google Scholar 

  49. Gebert, J., Stralis-Pavese, N., Alawi, M. & Bodrossy, L. Analysis of methanotrophic communities in landfill biofilters using diagnostic microarray. Environ. Microbiol. 10, 1175–1188 (2008).

    Article  CAS  Google Scholar 

  50. Hery, M. et al. Effect of earthworms on the community structure of active methanotrophic bacteria in a landfill cover soil. ISME J. 2, 92–104 (2008).

    Article  CAS  Google Scholar 

  51. Kumaresan, D., Abell, G.C.J., Bodrossy, L., Stralis-Pavese, N. & Murrell, J.C. Spatial and temporal diversity of methanotrophs in a landfill cover soil are differentially related to soil abiotic factors. Environ. Microbiol. Rep. 1, 398–407 (2009).

    Article  CAS  Google Scholar 

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Acknowledgements

Research at AIT was supported by the Fonds zur Förderung der wissenschaftlichen Forschung (FWF), Austria (project number P15044) and by the European Science Foundation EuroDiversity microbial methane oxidation as a modelsystem for microbial ecology (METHECO) program (Nr. FP018, national funding agency: FWF, Austria, project number I40-B06).

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Authors

Contributions

N.S.-P., L.B. and G.C.J.A. contributed to protocol development and subsequent refinement, L.B. and A.S. sourced funding and all authors participated in the writing of the manuscript.

Corresponding author

Correspondence to Guy C J Abell.

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Competing interests

The authors declare no competing financial interests.

Supplementary information

Supplementary Table 1

Excel macro for the analysis of raw GenePix microarray results (XLS 56 kb)

Supplementary Data 1

Current probes on pmoA FGA (DOC 58 kb)

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Stralis-Pavese, N., Abell, G., Sessitsch, A. et al. Analysis of methanotroph community composition using a pmoA-based microbial diagnostic microarray. Nat Protoc 6, 609–624 (2011). https://doi.org/10.1038/nprot.2010.191

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