Skip to main content

Variations in 16S rRNA-based microbiome profiling between pyrosequencing runs and between pyrosequencing facilities

Journal of Microbiology volume 52, pages 355–365 (2014)Cite this article

Abstract

Pyrosequencing of 16S rRNA gene amplicons on the 454 FLX Titanium platform has been widely used to analyze microbiomes in various environments. However, different results may stem from variations among sequencing runs or among sequencing facilities. This study aimed to evaluate these variations between different pyrosequencing runs by sequencing 16S rRNA gene amplicon libraries generated from three sets of rumen samples twice each on the 454 FLX Titanium system at two independent sequencing facilities. Similar relative abundances were found for predominant taxa represented by large numbers of sequence reads but not for minor taxa represented by small numbers of sequence reads. The two sequencing facilities revealed different bacterial profiles with respect to both predominant taxa and minor taxa, including the most predominant genus Prevotella, the family Lachnospiraceae, and the phylum Proteobacteria. Differences in primers used to generate amplicon libraries may be a major source of variations in microbiome profiling. Because different primers and regions of 16S rRNA genes are often used by different researchers, significant variations likely exist among studies. Quantitative interpretation for relative abundance of taxa, especially minor taxa, from prevalence of sequence reads and comparisons of results from different studies should be done with caution.

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

Access options

Buy single article

Instant access to the full article PDF.

43,34 €

Price includes VAT (Finland)
Tax calculation will be finalised during checkout.

References

  • Barriuso, J., Valverde, J.R., and Mellado, R.P. 2011. Estimation of bacterial diversity using next generation sequencing of 16S rDNA: a comparison of different workflows. BMC Bioinformatics 12, 473.

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  • Benson, A.K., Kelly, S.A., Legge, R., Ma, F., Low, S.J., Kim, J., Zhang, M., Oh, P.L., Nehrenberg, D., Hua, K., and et al. 2010. Individuality in gut microbiota composition is a complex polygenic trait shaped by multiple environmental and host genetic factors. Proc. Natl. Acad. Sci. USA 107, 18933–18938.

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  • Callaway, T.R., Dowd, S.E., Edrington, T.S., Anderson, R.C., Krueger, N., Bauer, N., Kononoff, P.J., and Nisbet, D.J. 2010. Evaluation of bacterial diversity in the rumen and feces of cattle fed different levels of dried distillers grains plus solubles using bacterial tag-encoded FLX amplicon pyrosequencing. J. Anim. Sci. 88, 3977–3983.

    CAS  PubMed  Article  Google Scholar 

  • Caporaso, J.G., Kuczynski, J., Stombaugh, J., Bittinger, K., Bushman, F.D., Costello, E.K., Fierer, N., Pena, A.G., Goodrich, J.K., Gordon, J.I., and et al. 2010. QIIME allows analysis of high-throughput community sequencing data. Nat. Methods 7, 335–336.

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  • DeSantis, T.Z., Hugenholtz, P., Larsen, N., Rojas, M., Brodie, E.L., Keller, K., Huber, T., Dalevi, D., Hu, P., and Andersen, G.L. 2006. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl. Environ. Microbiol. 72, 5069–5072.

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  • Dowd, S.E., Callaway, T.R., Wolcott, R.D., Sun, Y., McKeehan, T., Hagevoort, R.G., and Edrington, T.S. 2008. Evaluation of the bacterial diversity in the feces of cattle using 16S rDNA bacterial tag-encoded FLX amplicon pyrosequencing (bTEFAP). BMC Microbiol. 8, 125.

    PubMed Central  PubMed  Article  Google Scholar 

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

    CAS  PubMed  Article  Google Scholar 

  • Edgar, R.C., Haas, B.J., Clemente, J.C., Quince, C., and Knight, R. 2011. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 27, 2194–2200.

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  • Felix, T.L. and Loerch, S.C. 2011. Effects of haylage and monensin supplementation on performance, carcass characteristics, and ruminal metabolism of feedlot cattle fed diets containing 60% dried distillers grains. J. Anim. Sci. 89, 2614–2623.

    CAS  PubMed  Article  Google Scholar 

  • Frank, J.A., Reich, C.I., Sharma, S., Weisbaum, J.S., Wilson, B.A., and Olsen, G.J. 2008. Critical evaluation of two primers commonly used for amplification of bacterial 16S rRNA genes. Appl. Environ. Microbiol. 74, 2461–2470.

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  • Gihring, T.M., Green, S.J., and Schadt, C.W. 2012. Massively parallel rRNA gene sequencing exacerbates the potential for biased community diversity comparisons due to variable library sizes. Environ. Microbiol. 14, 285–290.

    CAS  PubMed  Article  Google Scholar 

  • Gomez-Alvarez, V., Teal, T.K., and Schmidt, T.M. 2009. Systematic artifacts in metagenomes from complex microbial communities. ISME J. 3, 1314–1317.

    PubMed  Article  Google Scholar 

  • Kauserud, H., Kumar, S., Brysting, A.K., Norden, J., and Carlsen, T. 2012. High consistency between replicate 454 pyrosequencing analyses of ectomycorrhizal plant root samples. Mycorrhiza 22, 309–315.

    PubMed  Article  Google Scholar 

  • Kim, M., Morrison, M., and Yu, Z. 2011a. Phylogenetic diversity of bacterial communities in bovine rumen as affected by diets and microenvironments. Folia Microbiol (Praha) 56, 453–458.

    CAS  Article  Google Scholar 

  • Kim, M., Morrison, M., and Yu, Z. 2011b. Status of the phylogenetic diversity census of ruminal microbiomes. FEMS Microbiol. Ecol. 76, 49–63.

    CAS  PubMed  Article  Google Scholar 

  • Kunin, V., Engelbrektson, A., Ochman, H., and Hugenholtz, P. 2010. Wrinkles in the rare biosphere: pyrosequencing errors can lead to artificial inflation of diversity estimates. Environ. Microbiol. 12, 118–123.

    CAS  PubMed  Article  Google Scholar 

  • Lane, D.J. 1991. 16S/23S rRNA sequencing, pp. 115–175. In Stackebrandt, E. and Goodfellow, M.D. (ed.), Nucleic acid techniques in bacterial systematics. John Wiley and Sons, New York, N.Y., USA.

    Google Scholar 

  • Larue, R., Yu, Z., Parisi, V.A., Egan, A.R., and Morrison, M. 2005. Novel microbial diversity adherent to plant biomass in the herbivore gastrointestinal tract, as revealed by ribosomal intergenic spacer analysis and rrs gene sequencing. Environ. Microbiol. 7, 530–543.

    CAS  PubMed  Article  Google Scholar 

  • Mathew, B., Eastridge, M.L., Oelker, E.R., Firkins, J.L., and Karnati, S.K. 2011. Interactions of monensin with dietary fat and carbohydrate components on ruminal fermentation and production responses by dairy cows. J. Dairy Sci. 94, 396–409.

    CAS  PubMed  Article  Google Scholar 

  • Morales, S.E. and Holben, W.E. 2009. Empirical testing of 16S rRNA gene PCR primer pairs reveals variance in target specificity and efficacy not suggested by in silico analysis. Appl. Environ. Microbiol. 75, 2677–2683.

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  • Nelson, M.C. 2011. An integrated investigation of the microbial communities underpinning biogas production in anaerobic digestion systems. Ph. D. Dissertation, The Ohio State University, Columbus, Ohio, USA.

    Google Scholar 

  • Pace, N.R. 1997. A molecular view of microbial diversity and the biosphere. Science 276, 734–740.

    CAS  PubMed  Article  Google Scholar 

  • Petrosino, J.F., Highlander, S., Luna, R.A., Gibbs, R.A., and Versalovic, J. 2009. Metagenomic pyrosequencing and microbial identification. Clin. Chem. 55, 856–866.

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  • Pitta, D.W., Pinchak, E., Dowd, S.E., Osterstock, J., Gontcharova, V., Youn, E., Dorton, K., Yoon, I., Min, B.R., Fulford, J.D., and et al. 2010. Rumen bacterial diversity dynamics associated with changing from bermudagrass hay to grazed winter wheat diets. Microb. Ecol. 59, 511–522.

    PubMed  Article  Google Scholar 

  • Pruesse, E., Quast, C., Knittel, K., Fuchs, B.M., Ludwig, W., Peplies, J., and Glockner, F.O. 2007. SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res. 35, 7188–7196.

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  • Quince, C., Lanzen, A., Curtis, T.P., Davenport, R.J., Hall, N., Head, I.M., Read, L.F., and Sloan, W.T. 2009. Accurate determination of microbial diversity from 454 pyrosequencing data. Nat. Methods 6, 639–641.

    CAS  PubMed  Article  Google Scholar 

  • Rajendhran, J. and Gunasekaran, P. 2011. Microbial phylogeny and diversity: small subunit ribosomal RNA sequence analysis and beyond. Microbiol. Res. 166, 99–110.

    CAS  PubMed  Article  Google Scholar 

  • Reeder, J. and Knight, R. 2010. Rapidly denoising pyrosequencing amplicon reads by exploiting rank-abundance distributions. Nat. Methods 7, 668–669.

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  • Soergel, D.A., Dey, N., Knight, R., and Brenner, S.E. 2012. Selection of primers for optimal taxonomic classification of environmental 16S rRNA gene sequences. ISME J. 6, 1440–1444.

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  • Stanley, D., Denman, S.E., Hughes, R.J., Geier, M.S., Crowley, T.M., Chen, H., Haring, V.R., and Moore, R.J. 2012. Intestinal microbiota associated with differential feed conversion efficiency in chickens. Appl. Microbiol. Biotechnol. 96, 1361–1369.

    CAS  PubMed  Article  Google Scholar 

  • Stiverson, J., Morrison, M., and Yu, Z. 2011. Populations of select cultured and uncultured bacteria in the rumen of sheep and the effect of diets and ruminal fractions. Int. J. Microbiol. 2011, 750613.

    PubMed Central  PubMed  Article  Google Scholar 

  • Wang, Q., Garrity, G.M., Tiedje, J.M., and Cole, J.R. 2007. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl. Environ. Microbiol. 73, 5261–5267.

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  • Weinstock, G.M. 2012. Genomic approaches to studying the human microbiota. Nature 489, 250–256.

    CAS  PubMed Central  PubMed  Article  Google Scholar 

  • Yu, Z. and Morrison, M. 2004. Improved extraction of PCR-quality community DNA from digesta and fecal samples. Biotechniques 36, 808–812.

    CAS  PubMed  Google Scholar 

Download references

Author information

Author notes

  1. Minseok Kim

    Present address: USDA, ARS, USMARC, Clay Center, NE, 68933, USA

Affiliations

  1. Department of Animal Sciences, The Ohio State University, Columbus, OH, USA

    Minseok Kim & Zhongtang Yu

Authors
  1. Minseok Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Zhongtang Yu
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Zhongtang Yu.

Rights and permissions

Reprints and Permissions

About this article

Cite this article

Kim, M., Yu, Z. Variations in 16S rRNA-based microbiome profiling between pyrosequencing runs and between pyrosequencing facilities. J Microbiol. 52, 355–365 (2014). https://doi.org/10.1007/s12275-014-3443-3

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s12275-014-3443-3

Keywords

  • 16S rRNA genes
  • microbiomes
  • primers
  • pyrosequencing
  • sequencing facility