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Microbiota Analysis Using Sequencing by Synthesis: From Library Preparation to Sequencing

  • Andrew NelsonEmail author
  • Christopher J. Stewart
Protocol
Part of the Methods in Molecular Biology book series (MIMB, volume 2121)

Abstract

The highly parallel nature of sequencing by synthesis (SBS) allows millions of amplicons to be sequenced simultaneously, which has led to enormous interest in the investigation of bacterial communities (often referred to as the microbiota). In this protocol, we describe a method for the ‘universal’ amplification of the v4 region of the bacterial 16S rRNA gene from genomic DNA and prepare these amplicons so that they can be sequenced using the MiSeq system (Illumina). The protocol provides instruction on sequencing of 188 genomic DNA samples plus PCR positive and negative controls, which can be applied to any sample type where bacterial DNA may be of interest.

Key words

DNA sequencing 16S rRNA Microbiota MiSeq PCR 

Notes

Acknowledgements

This work was supported by the European Union’s Horizon 2020 research and innovation programme under the Marie Skłodowska-Curie Grant Agreement No. 794771 to C.J.S.

References

  1. 1.
    Muyzer G, de Waal EC, Uitterlinden AG (1993) Profiling of complex microbial populations by denaturing gradient gel electrophoresis analysis of polymerase chain reaction-amplified genes coding for 16S rRNA. Appl Environ Microbiol 59(3):695–700CrossRefGoogle Scholar
  2. 2.
    Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, Fierer N et al (2012) Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J 6(8):1621–1624CrossRefGoogle Scholar
  3. 3.
    Kozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD (2013) Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl Environ Microbiol 79(17):5112–5120CrossRefGoogle Scholar
  4. 4.
    Stewart CJ, Ajami NJ, O’Brien JL, Hutchinson DS, Smith DP, Wong MC et al (2018) Temporal development of the gut microbiome in early childhood from the TEDDY study. Nature 562(7728):583–588CrossRefGoogle Scholar
  5. 5.
    Vatanen T, Franzosa EA, Schwager R, Tripathi S, Arthur TD, Vehik K et al (2018) The human gut microbiome in early-onset type 1 diabetes from the TEDDY study. Nature 562(7728):589–594CrossRefGoogle Scholar
  6. 6.
    Chakravorty S, Helb D, Burday M, Connell N, Alland D (2007) A detailed analysis of 16S ribosomal RNA gene segments for the diagnosis of pathogenic bacteria. J Microbiol Methods 69(2):330–339CrossRefGoogle Scholar
  7. 7.
    Schirmer M, Ijaz UZ, D’Amore R, Hall N, Sloan WT, Quince C (2015) Insight into biases and sequencing errors for amplicon sequencing with the Illumina MiSeq platform. Nucleic Acids Res 43(6):e37CrossRefGoogle Scholar
  8. 8.
    Edgar RC, Flyvbjerg H (2015) Error filtering, pair assembly and error correction for next-generation sequencing reads. Bioinformatics 31(21):3476–3482CrossRefGoogle Scholar
  9. 9.
    Salter SJ, Cox MJ, Turek EM, Calus ST, Cookson WO, Moffatt MF et al (2014) Reagent and laboratory contamination can critically impact sequence-based microbiome analyses. BMC Biol 12:87CrossRefGoogle Scholar
  10. 10.
    Davis NM, Proctor DM, Holmes SP, Relman DA, Callahan BJ (2018) Simple statistical identification and removal of contaminant sequences in marker-gene and metagenomics data. Microbiome 6(1):226CrossRefGoogle Scholar
  11. 11.
    Bokulich NA, Rideout JR, Mercurio WG, Shiffer A, Wolfe B, Maurice CF et al (2016) Mockrobiota: a public resource for microbiome bioinformatics benchmarking. mSystems 1(5)Google Scholar
  12. 12.
    Schrader C, Schielke A, Ellerbroek L, Johne R (2012) PCR inhibitors – occurrence, properties and removal. J Appl Microbiol 113(5):1014–1026CrossRefGoogle Scholar
  13. 13.
    Wang GC, Wang Y (1997) Frequency of formation of chimeric molecules as a consequence of PCR coamplification of 16S rRNA genes from mixed bacterial genomes. Appl Environ Microbiol 63(12):4645–4650CrossRefGoogle Scholar
  14. 14.
    Davies J, Denyer T, Hadfield J (2016) Bioanalyzer chips can be used interchangeably for many analyses of DNA or RNA. Biotechniques 60(4):197–199CrossRefGoogle Scholar
  15. 15.
    Nguyen T, Kwak S, Karpowicz SJ (2014) Re-use of commercial microfluidics chips for DNA, RNA, and protein electrophoresis. Biotechniques 57(5):267–271CrossRefGoogle Scholar
  16. 16.
    Quail MA, Kozarewa I, Smith F, Scally A, Stephens PJ, Durbin R et al (2008) A large genome center’s improvements to the Illumina sequencing system. Nat Methods 5(12):1005–1010CrossRefGoogle Scholar

Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2020

Authors and Affiliations

  1. 1.Faculty of Health and Life SciencesNorthumbria UniversityNewcastle upon TyneUK
  2. 2.Institute of Cellular MedicineNewcastle UniversityNewcastle upon TyneUK

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