Skip to main content
SpringerLink
Log in
Book cover

Hydrocarbon and Lipid Microbiology Protocols pp 89–113Cite as

Using QIIME to Evaluate the Microbial Communities Within Hydrocarbon Environments

  • Protocol
  • First Online:

Part of the book series: Springer Protocols Handbooks ((SPH))

Abstract

Interest in the microbiology of hydrocarbon-rich environments has increased rapidly in recent years, with applications ranging from oil spill cleanup to reservoir management. Modern techniques for reading out microbial communities using high-throughput sequencing produce vast amounts of data that cannot be processed by traditional methods. Here, we describe the use of the QIIME (Quantitative Insights into Microbial Ecology) pipeline for analyzing hydrocarbon-rich samples. This pipeline starts with the raw data from high-throughput sequence analysis and produces graphical and statistical analyses suitable for publication or for decision support. We illustrate the use of the QIIME pipeline using several recent datasets including sediments and water from the Deepwater Horizon spill and crude oil from a hydraulically fractured oil field in the United States, allowing better understanding of the microbiology of these systems. QIIME is a free, open-source software and can be deployed on systems ranging from laptops to cloud computing environments.

This is a preview of subscription content, log in via an institution.

Protocol
USD   49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD   84.99
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD   109.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD   109.99
Price excludes VAT (USA)
  • Durable hardcover edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info

Tax calculation will be finalised at checkout

Purchases are for personal use only

Learn about institutional subscriptions

Springer Nature is developing a new tool to find and evaluate Protocols. Learn more

Abbreviations

QIIME:

Quantitative Insights into Microbial Ecology, canonically pronounced “chime.”

OTU:

An operational taxonomic unit is a generic taxonomic grouping of organisms, similar to a phylum, genus, or species. When OTUs are defined based on gene sequence data, OTU definitions are generally based on sequence similarity. For example, in most sequence-based studies of microbial communities, 97% identity between a pair of ribosomal RNA sequences is used to group sequences into OTUs roughly corresponding to species-level groupings.

References

  1. Goodrich JK, Di Rienzi SC, Poole AC, Koren O, Walters WA, Caporaso JG, Knight R, Ley RE (2014) Conducting a microbiome study. Cell 158(2):250–262. doi:10.1016/j.cell.2014.06.037

    Article  CAS  PubMed  Google Scholar 

  2. Reeder J, Knight R (2009) The 'rare biosphere': a reality check. Nat Methods 6(9):636–637. doi:10.1038/nmeth0909-636

    Article  CAS  PubMed  Google Scholar 

  3. Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Fierer N, Peña 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 (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7(5):335–336. doi:10.1038/nmeth.f.303, Epub 2010 Apr 11

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Rideout JR, He Y, Navas-Molina JA, Walters WA, Ursell LK, Gibbons SM, Chase J, McDonald D, Gonzalez A, Robbins-Pianka A, Clemente JC, Gilbert JA, Huse SM, Zhou HW, Knight R, Caporaso JG (2014) Subsampled open-reference clustering creates consistent, comprehensive OTU definitions and scales to billions of sequences. PeerJ 2:e545. doi:10.7717/peerj.545, eCollection 2014

    Article  PubMed  PubMed Central  Google Scholar 

  5. Gilbert JA, Jansson JK, Knight R (2014) The Earth Microbiome project: successes and aspirations. BMC Biol 12(1):69

    Article  PubMed  PubMed Central  Google Scholar 

  6. Dong Y, Kumar CG, Chia N, Kim P-J, Miller PA, Price ND, Cann IK, Flynn TM, Sanford RA, Krapac IG, Locke RA 2nd, Hong PY, Tamaki H, Liu WT, Mackie RI, Hernandez AG, Wright CL, Mikel MA, Walker JL, Sivaguru M, Fried G, Yannarell AC, Fouke BW (2014) Halomonas sulfidaeris-dominated microbial community inhabits a 1.8 km-deep subsurface Cambrian Sandstone reservoir. Environ Microbiol 16(6):1695–1708. doi:10.1111/1462-2920.12325

    Article  CAS  PubMed  Google Scholar 

  7. Korenblum E, Souza DB, Penna M, Seldin L (2012) Molecular analysis of the bacterial communities in crude oil samples from two Brazilian offshore petroleum platforms. Int J Microbiol 2012:156537

    Article  PubMed  PubMed Central  Google Scholar 

  8. Kobayashi H, Endo K, Sakata S, Mayumi D, Kawaguchi H, Ikarashi M, Miyagawa Y, Maeda H, Sato K (2012) Phylogenetic diversity of microbial communities associated with the crude-oil, large-insoluble-particle and formation-water components of the reservoir fluid from a non-flooded high-temperature petroleum reservoir. J Biosci Bioeng 113(2):204–210. doi:10.1016/j.jbiosc.2011.09.015

    Article  CAS  PubMed  Google Scholar 

  9. Murali Mohan A, Hartsock A, Bibby KJ, Hammack RW, Vidic RD, Gregory KB (2013) Microbial community changes in hydraulic fracturing fluids and produced water from shale gas extraction. Environ Sci Technol 47(22):13141–13150. doi:10.1021/es402928b

    Article  CAS  PubMed  Google Scholar 

  10. Murali Mohan A, Hartsock A, Hammack RW, Vidic RD, Gregory KB (2013) Microbial communities in flowback water impoundments from hydraulic fracturing for recovery of shale gas. FEMS Microbiol Ecol 86(3):567–580. doi:10.1111/1574-6941.12183

    Article  CAS  PubMed  Google Scholar 

  11. Valentine DL, Kessler JD, Redmond MC, Mendes SD, Heintz MB, Farwell C, Hu L, Kinnaman FS, Yvon-Lewis S, Du M, Chan EW, Garcia Tigreros F, Villanueva CJ (2010) Propane respiration jump-starts microbial response to a deep oil spill. Science 330(6001):208–211. doi:10.1126/science.1196830

    Article  CAS  PubMed  Google Scholar 

  12. Wang LY, Ke WJ, Sun XB, Liu JF, Gu JD, Mu BZ (2014) Comparison of bacterial community in aqueous and oil phases of water-flooded petroleum reservoirs using pyrosequencing and clone library approaches. Appl Microbiol Biotechnol 98(9):4209–4221. doi:10.1007/s00253-013-5472-y

    Article  CAS  PubMed  Google Scholar 

  13. Hayatdavoudi A, Chegenizadeh N, Chistoserdov A, Boukadi F, Bajpai R (2013) Application of new fingerprinting bacteria DNA in crude oil for reservoir characterization – Part II. In: SPE annual technical conference and exhibition, September 2013. Society of Petroleum Engineers

    Google Scholar 

  14. Mason OU, Scott NM, Gonzalez A, Robbins-Pianka A, Bælum J, Kimbrel J, Bouskill NJ, Prestat E, Borglin S, Joyner DC, Fortney JL, Jurelevicius D, Stringfellow WT, Alvarez-Cohen L, Hazen TC, Knight R, Gilbert JA, Jansson JK (2014) Metagenomics reveals sediment microbial community response to Deepwater Horizon oil spill. ISME J 8(7):1464–1475. doi:10.1038/ismej.2013.254

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Scott NM, Hess M, Bouskill NJ, Mason OU, Jansson JK, Gilbert JA (2014) The microbial nitrogen cycling potential is impacted by polyaromatic hydrocarbon pollution of marine sediments. Front Microbiol 5:108. doi:10.3389/fmicb.2014.00108

    Article  PubMed  PubMed Central  Google Scholar 

  16. Valentine DL, Mezic I, Macesic S, Crnjaric-Zic N, Ivic S, Hogan PJ, Fonoberov VA, Loire S (2012) Dynamic autoinoculation and the microbial ecology of a deep water hydrocarbon irruption. Proc Natl Acad Sci U S A 109(50):20286–20291. doi:10.1073/pnas.1108820109

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  17. Bælum J, Borglin S, Chakraborty R, Fortney JL, Lamendella R, Mason OU, Auer M, Jansson JK (2012) Deep-sea bacteria enriched by oil and dispersant from the Deepwater Horizon spill. Environ Microbiol 14(9):2405–2416. doi:10.1111/j.1462-2920.2012.02780.x

    Article  PubMed  Google Scholar 

  18. Redmond MC, Valentine DL (2012) Natural gas and temperature structured a microbial community response to the Deepwater Horizon oil spill. Proc Natl Acad Sci U S A 109(50):20292–20297. doi:10.1073/pnas.1108756108, PMID: 21969552

    Article  CAS  PubMed  Google Scholar 

  19. Kessler JD, Valentine DL, Redmond MC, Du M, Chan EW, Mendes SD, Quiroz EW, Villanueva CJ, Shusta SS, Werra LM, Yvon-Lewis SA, Weber TC (2011) A persistent oxygen anomaly reveals the fate of spilled methane in the deep Gulf of Mexico. Science 331(6015):312–315. doi:10.1126/science.1199697

    Article  CAS  PubMed  Google Scholar 

  20. Goecks J, Nekrutenko A, Taylor J, Galaxy Team (2010) Galaxy: a comprehensive approach for supporting accessible, reproducible, and transparent computational research in the life sciences. Genome Biol 11(8):R86. doi:10.1186/gb-2010-11-8-r86, Epub 2010 Aug 25

    Article  PubMed  PubMed Central  Google Scholar 

  21. Knights D, Costello EK, Knight R (2011) Supervised classification of human microbiota. FEMS Microbiol Rev 35(2):343–359. doi:10.1111/j.1574-6976.2010.00251.x, Epub 2010 Oct 7

    Article  CAS  PubMed  Google Scholar 

  22. Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Lozupone CA, Turnbaugh PJ, Fierer N, Knight R (2011) Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci U S A 108(Suppl 1):4516–4522. doi:10.1073/pnas.1000080107, Epub 2010 Jun 3

    Article  CAS  PubMed  Google Scholar 

  23. Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, Fierer N, Owens SM, Betley J, Fraser L, Bauer M, Gormley N, Gilbert JA, Smith G, Knight R (2012) Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J 6(8):1621–1624. doi:10.1038/ismej.2012.8, Epub 2012 Mar 8

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  24. Werner JJ, Zhou D, Caporaso JG, Knight R, Angenent LT (2012) Comparison of Illumina paired-end and single-direction sequencing for microbial 16S rRNA gene amplicon surveys. ISME J 6(7):1273–1276. doi:10.1038/ismej.2011.186x, Epub 2011 Dec 15

    Article  CAS  PubMed  Google Scholar 

  25. Aronesty E (2011) ea-utils: Command-line tools for processing biological sequencing data. http://code.google.com/p/ea-utils

  26. Bokulich NA, Subramanian S, Faith JJ, Gevers D, Gordon JI, Knight R, Mills DA, Caporaso JG (2013) Quality-filtering vastly improves diversity estimates from Illumina amplicon sequencing. Nat Methods 10(1):57–59. doi:10.1038/nmeth.2276, Epub 2012 Dec 2

    Article  CAS  PubMed  Google Scholar 

  27. Edgar RC (2010) Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26(19):2460–2461. doi:10.1093/bioinformatics/btq461, Epub 2010 Aug 12

    Article  CAS  PubMed  Google Scholar 

  28. Fu L, Niu B, Zhu Z, Wu S, Li W (2012) CD-HIT: accelerated for clustering the next-generation sequencing data. Bioinformatics 28(23):3150–3152. doi:10.1093/bioinformatics/bts565, Epub 2012 Oct 11

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. 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 (2009) Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol 75(23):7537–7541. doi:10.1128/AEM.01541-09, Epub 2009 Oct 2

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  30. Kopylova E, Noé L, Touzet H (2012) SortMeRNA: fast and accurate filtering of ribosomal RNAs in metatranscriptomic data. Bioinformatics 28(24):3211–3217. doi:10.1093/bioinformatics/bts611. Epub 2012 Oct 15

    Google Scholar 

  31. Mahé F, Rognes T, Quince C, de Vargas C, Dunthorn M (2014) Swarm: robust and fast clustering method for amplicon-based studies. PeerJ 2:e593. doi:10.7717/peerj.593, eCollection 2014

    Article  PubMed  PubMed Central  Google Scholar 

  32. McDonald D, Clemente JC, Kuczynski J, Rideout JR, Stombaugh J, Wendel D, Wilke A, Huse S, Hufnagle J, Meyer F, Knight R, Caporaso JG (2012) The Biological Observation Matrix (BIOM) format or: how I learned to stop worrying and love the ome-ome. Gigascience 1(1):7. doi:10.1186/2047-217X-1-7

    Article  PubMed  PubMed Central  Google Scholar 

  33. McDonald D, Price MN, Goodrich J, Nawrocki EP, DeSantis TZ, Probst A, Andersen GL, Knight R, Hugenholtz P (2012) An improved Greengenes taxonomy with explicit ranks for ecological and evolutionary analyses of bacteria and archaea. ISME J 6(3):610–618. doi:10.1038/ismej.2011.139, Epub 2011 Dec 1

    Article  CAS  PubMed  Google Scholar 

  34. Hamady M, Lozupone C, Knight R (2010) Fast UniFrac: facilitating high-throughput phylogenetic analyses of microbial communities including analysis of pyrosequencing and PhyloChip data. ISME J 4(1):17–27. doi:10.1038/ismej.2009.97, Epub 2009 Aug 27

    Article  CAS  PubMed  Google Scholar 

  35. McMurdie PJ, Holmes S (2014) Waste not, want not: why rarefying microbiome data is inadmissible. PLoS Comput Biol 10(4):e1003531. doi:10.1371/journal.pcbi.1003531, eCollection 2014

    Article  PubMed  PubMed Central  Google Scholar 

  36. Lozupone C, Knight R (2005) UniFrac: a new phylogenetic method for comparing microbial communities. Appl Environ Microbiol 71(12):8228–8235

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  37. Vázquez-Baeza Y, Pirrung M, Gonzalez A, Knight R (2013) EMPeror: a tool for visualizing high-throughput microbial community data. Gigascience 2(1):16. doi:10.1186/2047-217X-2-16

    Article  PubMed  PubMed Central  Google Scholar 

  38. Jari Oksanen F, Blanchet G, Kindt R, Legendre P, Minchin PR, O’Hara RB, Simpson GL, Solymos P, Henry M, Stevens H, Wagner H (2014) vegan: community ecology package. R package version 2.2-0. http://CRAN.R-project.org/package = vegan

  39. Knights D, Kuczynski J, Charlson ES, Zaneveld J, Mozer MC, Collman RG, Bushman FD, Knight R, Kelley ST (2011) Bayesian community-wide culture-independent microbial source tracking. Nat Methods 8(9):761–763. doi:10.1038/nmeth.1650

    Article  CAS  PubMed  PubMed Central  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Biota Technology Inc., 2025 Ash St., Denver, CO, 80201, USA

    Luke K. Ursell, Nicole Scott, Ajay Kshatriya, J. Gregory Caporaso & Rob Knight

  2. Biofrontiers Institute, University of Colorado at Boulder, Boulder, CO, 80309, USA

    Adam Robbins-Pianka

  3. Department of Computer Science, University of Colorado, Boulder, CO, 80309, USA

    Antonio Gonzalez

  4. Department of Computer Science and Engineering, University of Minnesota, Minneapolis, MN, 55455, USA

    Dan Knights

  5. Center for Microbial Genetics and Genomics, Northern Arizona University, 1298 S. Knoles Dr., Flagstaff, AZ, 86011, USA

    Jai Ram Rideout & J. Gregory Caporaso

  6. Department of Biological Sciences, Northern Arizona University, 617 S. Beaver St., Flagstaff, AZ, 86011, USA

    J. Gregory Caporaso

  7. Departments of Pediatrics and Computer Science & Engineering, University of California San Diego, La Jolla, CA, 92093, USA

    Rob Knight

Authors
  1. Luke K. Ursell
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Adam Robbins-Pianka
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Nicole Scott
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Antonio Gonzalez
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Dan Knights
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Jai Ram Rideout
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Ajay Kshatriya
    View author publications

    You can also search for this author in PubMed Google Scholar

  8. J. Gregory Caporaso
    View author publications

    You can also search for this author in PubMed Google Scholar

  9. Rob Knight
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Rob Knight .

Editor information

Editors and Affiliations

  1. Dept. Biological Sciences, University of Essex Dept. Biological Sciences, Colchester, Essex, United Kingdom

    Terry J. McGenity

  2. Braunschweig, Germany

    Kenneth N. Timmis

  3. University of the Balearic Islands , Palma de Mallorca, Spain

    Balbina Nogales Fernández

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer-Verlag Berlin Heidelberg

About this protocol

Cite this protocol

Ursell, L.K. et al. (2015). Using QIIME to Evaluate the Microbial Communities Within Hydrocarbon Environments. In: McGenity, T., Timmis, K., Nogales Fernández, B. (eds) Hydrocarbon and Lipid Microbiology Protocols. Springer Protocols Handbooks. Springer, Berlin, Heidelberg. https://doi.org/10.1007/8623_2015_175

Download citation

  • DOI: https://doi.org/10.1007/8623_2015_175

  • Published:

  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-49309-0

  • Online ISBN: 978-3-662-49310-6

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics

Search

Navigation