Skip to main content

Metagenomic Methods: From Seawater to the Database

Abstract

In this article, methods or techniques of metagenomics including targeted 16S/18S rRNA analyses and shotgun sequencing will be discussed. It is sometimes difficult, especially for beginners, to follow the manufacturer’s recommendation as mentioned in the protocol and to go through different steps from the preparation of starting material (e.g., DNA), library preparation, and so on. We will try to explain all the steps in detail and share our experience here. It all starts with collection of samples and collection of ecological/environmental metadata followed by sample fractionation (optional), extraction of DNA, sequencing, and finally data analyses to interpret results. Sample collection has always been the most important part of a study as it requires proper planning, a good workforce to execute, permission(s) of sampling from appropriate authority, and precaution(s) about endangered species during sampling. Here, we first describe methodology for a shallow river and in the later section methodology for a deep marine bay. In either case, slight modifications can be made to succeed in sampling. Determination of physicochemical parameters as metadata simultaneously is also an important task. These samples are then processed to extract DNA which needs to be representative of all cells present in the sample. Finally, sequencing is done by a next-generation sequencer, and data analyses are completed. Through these methods, scientists are now able to overcome the unculturability problem of more than 99% of environmental microorganisms and uncovered functional gene diversity of environmental microorganisms.

Keywords

  • Free-living microorganisms
  • Particle-associated microorganisms
  • Shotgun metagenomics
  • Size fractionation
  • Targeted metagenomics

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

Buying options

Chapter
USD   29.95
Price excludes VAT (USA)
  • DOI: 10.1007/978-981-13-8134-8_1
  • Chapter length: 14 pages
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
eBook
USD   64.99
Price excludes VAT (USA)
  • ISBN: 978-981-13-8134-8
  • Instant PDF download
  • Readable on all devices
  • Own it forever
  • Exclusive offer for individuals only
  • Tax calculation will be finalised during checkout
Softcover Book
USD   84.99
Price excludes VAT (USA)
Hardcover Book
USD   119.99
Price excludes VAT (USA)
Fig. 1.1
Fig. 1.2
Fig. 1.3
Fig. 1.4
Fig. 1.5
Fig. 1.6

References

  • Camacho C, Coulouris G, Avagyan V, Ma N, Papadopoulos J, Bealer K, Madden TL (2009) BLAST +: architecture and applications. BMC Bioinform 10:421–429

    CrossRef  Google Scholar 

  • Ganesh S, Parris DJ, DeLong EF, Stewart FJ (2014) Metagenomic analysis of size-fractionated picoplankton in a marine oxygen minimum zone. ISME J 8:187–211

    CAS  CrossRef  PubMed  Google Scholar 

  • Huson DH, Auch AF, Qi J, Schuster SC (2007) MEGAN analysis of metagenomic data. Genome Res 17:377–386

    CAS  PubMed  PubMed Central  CrossRef  Google Scholar 

  • Klindworth A, Pruesse E, Schweer T, Peplies J, Quast C, Horn M, Glöckner FO (2013) Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing based diversity studies. Nucleic Acids Res 41:e1

    CAS  CrossRef  PubMed  Google Scholar 

  • Kobiyama A, Ikeo K, Reza MS, Rashid J, Yamada Y, Ikeda Y, Ikeda D, Mizusawa N, Sato S, Ogata T, Kudo T, Kaga S, Watanabe S, Naiki K, Kaga Y, Mineta K, Bajic V, Gojobori T, Watabe S (2018) Metagenome-based diversity analyses suggest a strong locality signal for bacterial communities associated with oyster aquaculture farms in Ofunato Bay. Gene 665:149–154

    CAS  CrossRef  PubMed  Google Scholar 

  • Kudo T, Kobiyama A, Rashid J, Reza MS, Yamada Y, Ikeda Y, Ikeda D, Mizusawa N, Ikeo K, Sato S, Ogata T, Jimbo M, Kaga S, Watanabe S, Naiki K, Kaga Y, Segawa S, Mineta K, Bajic V, Gojobori T, Watabe S (2018) Seasonal changes in the abundance of bacterial genes related to dimethylsulfoniopropionate catabolism in seawater from Ofunato Bay as revealed by metagenomic analysis. Gene 665:174–184

    CAS  PubMed  CrossRef  Google Scholar 

  • Li W, Godzik A (2006) Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences. Bioinformatics 22:1658–1659

    CAS  PubMed  CrossRef  Google Scholar 

  • Magoc T, Salzberg SL (2011) FLASH: fast length adjustment of short reads to improve genome assemblies. Bioinformatics 27:2957–2963

    CAS  PubMed  PubMed Central  CrossRef  Google Scholar 

  • Padilla CC, Ganesh S, Gantt S, Huhman A, Parris DJ, Sarode N, Stewart FJ (2015) Standard filtration practices may significantly distort planktonic microbial diversity estimates. Front Microbiol 6:547

    PubMed  PubMed Central  CrossRef  Google Scholar 

  • Pruesse E, Peplies J, Glöckner FO (2012) SINA: accurate high-throughput multiple sequence alignment of ribosomal RNA genes. Bioinformatics 28:1823–1829

    CAS  PubMed  PubMed Central  CrossRef  Google Scholar 

  • Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, Peplies J, Glöckner FO (2013) The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res 41:D590–D596. (database issue)

    CAS  CrossRef  PubMed  Google Scholar 

  • Rashid J, Kobiyama A, Reza MS, Yamada Y, Ikeda Y, Ikeda D, Mizusawa N, Ikeo K, Sato S, Ogata T, Kudo T, Kaga S, Watanabe S, Naiki K, Kaga Y, Mineta K, Bajic V, Gojobori T, Watabe S (2018) Seasonal changes in the communities of photosynthetic picoeukaryotes in Ofunato Bay as revealed by shotgun metagenomic sequencing. Gene 665:127–132

    CAS  PubMed  CrossRef  Google Scholar 

  • Reza MS, Kobiyama A, Yamada Y, Ikeda Y, Ikeda D, Mizusawa N, Ikeo K, Sato S, Ogata T, Jimbo M, Kudo T, Kaga S, Watanabe S, Naiki K, Kaga Y, Mineta K, Bajic V, Gojobori T, Watabe S (2018a) Taxonomic profiles in metagenomic analyses of free-living microbial communities in the Ofunato Bay. Gene 665:192–200

    CAS  CrossRef  PubMed  Google Scholar 

  • Reza MS, Kobiyama A, Yamada Y, Ikeda Y, Ikeda D, Mizusawa N, Ikeo K, Sato S, Ogata T, Jimbo M, Kudo T, Kaga S, Watanabe S, Naiki K, Kaga Y, Mineta K, Bajic V, Gojobori T, Watabe S (2018b) Basin-scale seasonal changes in marine free-living bacterioplankton community in the Ofunato Bay. Gene 665:185–191

    CAS  PubMed  CrossRef  Google Scholar 

  • Reza MS, Mizusawa N, Kumano A, Oikawa C, Ouchi D, Kobiyama A, Yamada Y, Ikeda Y, Ikeda D, Ikeo K, Sato S, Ogata T, Kudo T, Jimbo M, Yasumoto K, Yoshitake K, Watabe S (2018c) Metagenomic analysis using 16S ribosomal RNA genes of a bacterial community in an urban stream, the Tama River, Tokyo. Fish Sci 84:563–577

    CAS  CrossRef  Google Scholar 

  • R Development Core Team (2008) R: a language and environment for statistical computing. R Foundation for Statistical Computing, Vienna. ISBN 3-900051-07-0

    Google Scholar 

  • Yamada Y, Kaga S, Kaga Y, Naiki K, Watanabe S (2017) Changes of seawater quality in Ofunto Bay, Iwate, after the 2011 off the Pacific coast of Tohoku Earthquake. J Oceanogr 73:11–24

    CrossRef  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Shugo Watabe .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and Permissions

Copyright information

© 2019 Springer Nature Singapore Pte Ltd.

About this chapter

Verify currency and authenticity via CrossMark

Cite this chapter

Reza, M.S. et al. (2019). Metagenomic Methods: From Seawater to the Database. In: Gojobori, T., Wada, T., Kobayashi, T., Mineta, K. (eds) Marine Metagenomics. Springer, Singapore. https://doi.org/10.1007/978-981-13-8134-8_1

Download citation