Advertisement

Characterization of Microbial Diversity in Food Chain: A Molecular Review

  • Wentao Xu
Chapter

Abstract

Three kinds of traditional molecular methods are available for the detection of microbial community diversity: nucleic-acid-hybridization-based methods, PCR-electrophoresis-based methods, and Sanger-sequencing-based methods. Distinct from Sanger sequencing, high-throughput sequencing is based on the sequencing-by-synthesis principle and the massively parallel signature sequencing strategy, allowing the simultaneous determination of the sequences of millions of different DNA templates. Thus, the metagenome of an entire microbial community can be sequenced simultaneously, without the need to isolate unique sequences through clone library construction and subculturing. High-throughput-sequencing-based methods are highly sensitive and specific, are inexpensive, and require relatively little time compared with traditional molecular methods for microbial diversity research. In the last section of this chapter, we introduce several traditionally used gene targets for microbial identification.

Keywords

Microbial diversity PCR Hybridization High-throughput sequencing Food safety 

Notes

Acknowledgments

This work is supported by the Ministry of Science and Technology of Beijing (XX2014B069). Many thanks to Mingzhang Guo, for his kind help in manuscript conception and preparation.

References

  1. 1.
    Whittaker RH. Vegetation of the Siskiyou mountains, Oregon and California. Ecol Monogr. 1960;30(3):279–338.CrossRefGoogle Scholar
  2. 2.
    Havelaar AH, Brul S, de Jong A, de Jonge R, Zwietering MH, Ter Kuile BH. Future challenges to microbial food safety. Int J Food Microbiol. 2010;139 Suppl 1:S79–94.CrossRefPubMedGoogle Scholar
  3. 3.
    Powell SM, Tamplin ML. Microbial communities on Australian modified atmosphere packaged Atlantic salmon. Food Microbiol. 2012;30(1):226–32.CrossRefPubMedGoogle Scholar
  4. 4.
    Felsenfeld G, Miles HT. The physical and chemical properties of nucleic acids. Annu Rev Biochem. 1967;36:407–48.CrossRefPubMedGoogle Scholar
  5. 5.
    Moter A, Gobel UB. Fluorescence in situ hybridization (FISH) for direct visualization of microorganisms. J Microbiol Methods. 2000;41(2):85–112.CrossRefPubMedGoogle Scholar
  6. 6.
    Giraffa G, Neviani E. DNA-based, culture-independent strategies for evaluating microbial communities in food-associated ecosystems. Int J Food Microbiol. 2001;67(1-2):19–34.CrossRefPubMedGoogle Scholar
  7. 7.
    Schutte UM, Abdo Z, Bent SJ, Shyu C, Williams CJ, Pierson JD, Forney LJ. Advances in the use of terminal restriction fragment length polymorphism (T-RFLP) analysis of 16S rRNA genes to characterize microbial communities. Appl Microbiol Biotechnol. 2008;80(3):365–80.CrossRefPubMedGoogle Scholar
  8. 8.
    Vaneechoutte M. DNA fingerprinting techniques for microorganisms. A proposal for classification and nomenclature. Mol Biotechnol. 1996;6(2):115–42.CrossRefPubMedGoogle Scholar
  9. 9.
    Muyzer G. DGGE/TGGE a method for identifying genes from natural ecosystems. Curr Opin Microbiol. 1999;2(3):317–22.CrossRefPubMedGoogle Scholar
  10. 10.
    Schwartz DC, Cantor CR. Separation of yeast chromosome-sized DNAs by pulsed field gradient gel electrophoresis. Cell. 1984;37(1):67–75.CrossRefPubMedGoogle Scholar
  11. 11.
    Sanger F, Coulson AR. A rapid method for determining sequences in DNA by primed synthesis with DNA polymerase. J Mol Biol. 1975;94(3):441–8.CrossRefPubMedGoogle Scholar
  12. 12.
    Brooks JP, Edwards DJ, Harwich Jr MD, Rivera MC, Fettweis JM, Serrano MG, Reris RA, Sheth NU, Huang B, Girerd P, Strauss 3rd JF, Jefferson KK, Buck GA. The truth about metagenomics: quantifying and counteracting bias in 16S rRNA studies. BMC Microbiol. 2015;15:66.CrossRefPubMedPubMedCentralGoogle Scholar
  13. 13.
    Claesson MJ, Wang Q, O’Sullivan O, Greene-Diniz R, Cole JR, Ross RP, O’Toole PW. Comparison of two next-generation sequencing technologies for resolving highly complex microbiota composition using tandem variable 16S rRNA gene regions. Nucleic Acids Res. 2010;38(22):e200.CrossRefPubMedPubMedCentralGoogle Scholar
  14. 14.
    Kozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD. Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl Environ Microbiol. 2013;79(17):5112–20.CrossRefPubMedPubMedCentralGoogle Scholar
  15. 15.
    Lundin D, Severin I, Logue JB, Ostman O, Andersson AF, Lindstrom ES. Which sequencing depth is sufficient to describe patterns in bacterial alpha- and beta-diversity? Environ Microbiol Rep. 2012;4(3):367–72.CrossRefPubMedGoogle Scholar
  16. 16.
    Wang X, Cai Y, Sun Y, Knight R, Mai V. Secondary structure information does not improve OTU assignment for partial 16s rRNA sequences. ISME J. 2012;6(7):1277–80.CrossRefPubMedGoogle Scholar
  17. 17.
    Li W, Godzik A. Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics. 2006;22(13):1658–9.CrossRefPubMedGoogle Scholar
  18. 18.
    Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, Lesniewski RA, Oakley BB, Parks DH, Robinson CJ, Sahl JW, Stres B, Thallinger GG, Van Horn DJ, Weber CF. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol. 2009;75(23):7537–41.CrossRefPubMedPubMedCentralGoogle Scholar
  19. 19.
    Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Fierer N, Pena AG, Goodrich JK, Gordon JI, Huttley GA, Kelley ST, Knights D, Koenig JE, Ley RE, Lozupone CA, McDonald D, Muegge BD, Pirrung M, Reeder J, Sevinsky JR, Turnbaugh PJ, Walters WA, Widmann J, Yatsunenko T, Zaneveld J, Knight R. QIIME allows analysis of high-throughput community sequencing data. Nat Methods. 2010;7(5):335–6.CrossRefPubMedPubMedCentralGoogle Scholar
  20. 20.
    Schloss PD, Handelsman J. Introducing DOTUR, a computer program for defining operational taxonomic units and estimating species richness. Appl Environ Microbiol. 2005;71(3):1501–6.CrossRefPubMedPubMedCentralGoogle Scholar
  21. 21.
    Segata N, Izard J, Waldron L, Gevers D, Miropolsky L, Garrett WS, Huttenhower C. Metagenomic biomarker discovery and explanation. Genome Biol. 2011;12(6):R60.CrossRefPubMedPubMedCentralGoogle Scholar
  22. 22.
    Fettweis JM, Serrano MG, Sheth NU, Mayer CM, Glascock AL, Brooks JP, Jefferson KK, Buck GA. Species-level classification of the vaginal microbiome. BMC Genomics. 2012;13 Suppl 8:S17.PubMedPubMedCentralGoogle Scholar
  23. 23.
    Miller CS, Baker BJ, Thomas BC, Singer SW, Banfield JF. EMIRGE: reconstruction of full-length ribosomal genes from microbial community short read sequencing data. Genome Biol. 2011;12(5):R44.CrossRefPubMedPubMedCentralGoogle Scholar
  24. 24.
    Dempster AP, Laird NM, Rubin DB. Maximum likelihood from incomplete data via the EM algorithm. J R Stat Soc Ser B (Methodol). 1977;39:1–38.Google Scholar
  25. 25.
    Fan L, McElroy K, Thomas T. Reconstruction of ribosomal RNA genes from metagenomic data. PLoS One. 2012;7(6):e39948.CrossRefPubMedPubMedCentralGoogle Scholar
  26. 26.
    Ong SH, Kukkillaya VU, Wilm A, Lay C, Ho EX, Low L, Hibberd ML, Nagarajan N. Species identification and profiling of complex microbial communities using shotgun Illumina sequencing of 16S rRNA amplicon sequences. PLoS One. 2013;8(4):e60811.CrossRefPubMedPubMedCentralGoogle Scholar
  27. 27.
    Amir A, Zeisel A, Zuk O, Elgart M, Stern S, Shamir O, Turnbaugh PJ, Soen Y, Shental N. High-resolution microbial community reconstruction by integrating short reads from multiple 16S rRNA regions. Nucleic Acids Res. 2013;41(22):e205.CrossRefPubMedPubMedCentralGoogle Scholar
  28. 28.
    Sunagawa S, Mende DR, Zeller G, Izquierdo-Carrasco F, Berger SA, Kultima JR, Coelho LP, Arumugam M, Tap J, Nielsen HB, Rasmussen S, Brunak S, Pedersen O, Guarner F, de Vos WM, Wang J, Li J, Dore J, Ehrlich SD, Stamatakis A, Bork P. Metagenomic species profiling using universal phylogenetic marker genes. Nat Methods. 2013;10(12):1196–9.CrossRefPubMedGoogle Scholar
  29. 29.
    Engelbrektson A, Kunin V, Wrighton KC, Zvenigorodsky N, Chen F, Ochman H, Hugenholtz P. Experimental factors affecting PCR-based estimates of microbial species richness and evenness. ISME J. 2010;4(5):642–7.CrossRefPubMedGoogle Scholar
  30. 30.
    Nielsen HB, Almeida M, Juncker AS, Rasmussen S, Li J, Sunagawa S, Plichta DR, Gautier L, Pedersen AG, Le Chatelier E, Pelletier E, Bonde I, Nielsen T, Manichanh C, Arumugam M, Batto JM, Quintanilha Dos Santos MB, Blom N, Borruel N, Burgdorf KS, Boumezbeur F, Casellas F, Dore J, Dworzynski P, Guarner F, Hansen T, Hildebrand F, Kaas RS, Kennedy S, Kristiansen K, Kultima JR, Leonard P, Levenez F, Lund O, Moumen B, Le Paslier D, Pons N, Pedersen O, Prifti E, Qin J, Raes J, Sorensen S, Tap J, Tims S, Ussery DW, Yamada T, Renault P, Sicheritz-Ponten T, Bork P, Wang J, Brunak S, Ehrlich SD. Identification and assembly of genomes and genetic elements in complex metagenomic samples without using reference genomes. Nat Biotechnol. 2014;32(8):822–8.CrossRefPubMedGoogle Scholar
  31. 31.
    Woese CR, Fox GE. Phylogenetic structure of the prokaryotic domain: the primary kingdoms. Proc Natl Acad Sci U S A. 1977;74(11):5088–90.CrossRefPubMedPubMedCentralGoogle Scholar
  32. 32.
    Woese CR, Kandler O, Wheelis ML. Towards a natural system of organisms: proposal for the domains Archaea, Bacteria, and Eucarya. Proc Natl Acad Sci U S A. 1990;87(12):4576–9.CrossRefPubMedPubMedCentralGoogle Scholar
  33. 33.
    Naser SM, Thompson FL, Hoste B, Gevers D, Dawyndt P, Vancanneyt M, Swings J. Application of multilocus sequence analysis (MLSA) for rapid identification of Enterococcus species based on rpoA and pheS genes. Microbiology. 2005;151(Pt 7):2141–50. doi:151/7/2141 [pii]  10.1099/mic.0.27840-0.
  34. 34.
    Klenk HP, Zillig W. DNA-dependent RNA polymerase subunit B as a tool for phylogenetic reconstructions: branching topology of the archaeal domain. J Mol Evol. 1994;38(4):420–32.CrossRefPubMedGoogle Scholar
  35. 35.
    Karlin S, Weinstock GM, Brendel V. Bacterial classifications derived from recA protein sequence comparisons. J Bacteriol. 1995;177(23):6881–93.PubMedPubMedCentralGoogle Scholar
  36. 36.
    Eisen JA. The RecA protein as a model molecule for molecular systematic studies of bacteria: comparison of trees of RecAs and 16S rRNAs from the same species. J Mol Evol. 1995;41(6):1105–23.CrossRefPubMedPubMedCentralGoogle Scholar
  37. 37.
    Wang LT, Lee FL, Tai CJ, Kasai H. Comparison of gyrB gene sequences, 16S rRNA gene sequences and DNA-DNA hybridization in the Bacillus subtilis group. Int J Syst Evol Microbiol. 2007;57(Pt 8):1846–50.CrossRefPubMedGoogle Scholar

Copyright information

© Springer Science+Business Media Singapore 2016

Authors and Affiliations

  • Wentao Xu
    • 1
    • 2
  1. 1.Beijing Advanced Innovation Center for Food Nutrition and Human Health, College of Food Science & Nutritional EngineeringChina Agricultural UniversityBeijingChina
  2. 2.Beijing Laboratory for Food Quality and Safety, College of Food Science & Nutritional EngineeringChina Agricultural UniversityBeijingChina

Personalised recommendations