Skip to main content

Creation and Analysis of a Virome: Using CRISPR Spacers

  • Protocol
CRISPR

Part of the book series: Methods in Molecular Biology ((MIMB,volume 1311))

Abstract

Advances in sequencing technology have allowed for the study of complex and previously unexplored microbial and viral populations; however, linking host–phage partners using in silico techniques has been challenging. Here, we describe the flow-through for creation of a virome, and its subsequent analysis with the viral assembly and analysis module “Viritas,” which we have recently developed. This module allows for binning of contigs based on tetranucleotide frequencies, putative phage-host partner identification by CRISPR spacer matching, and identification of ORFs.

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

Access this chapter

Protocol
USD 49.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 99.00
Price excludes VAT (USA)
  • Available as EPUB and PDF
  • Read on any device
  • Instant download
  • Own it forever
Softcover Book
USD 129.99
Price excludes VAT (USA)
  • Compact, lightweight edition
  • Dispatched in 3 to 5 business days
  • Free shipping worldwide - see info
Hardcover Book
USD 199.99
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

Institutional subscriptions

References

  1. Emerson JB, Thomas BC, Andrade K, Heidelberg KB, Banfield JF (2013) New approaches indicate constant viral diversity despite shifts in assemblage structure in an Australian hypersaline lake. Appl Environ Microbiol 79.21(2013):6755–6764

    Google Scholar 

  2. Pride DT, Schoenfeld T (2008) Genome signature analysis of thermal virus metagenomes reveals Archaea and thermophilic signatures. BMC Genomics 9:420

    Article  PubMed Central  PubMed  Google Scholar 

  3. Fancello L, Raoult D, Desnues C (2012) Computational tools for viral metagenomics and their application in clinical research. Virology 434:162–174

    Article  CAS  PubMed  Google Scholar 

  4. Sullivan MB, Huang KH, Ignacio-Espinoza JC, Berlin AM, Kelly L, Weigele PR, DeFrancesco AS, Kern SE, Thompson LR, Young S et al (2010) Genomic analysis of oceanic cyanobacterial myoviruses compared with T4-like myoviruses from diverse hosts and environments. Environ Microbiol 12:3035–3056

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  5. Chitsaz H, Yee-Greenbaum JL, Tesler G, Lombardo M-J, Dupont CL, Badger JH, Novotny M, Rusch DB, Fraser LJ, Gormley NA et al (2011) Efficient de novo assembly of single-cell bacterial genomes from short-read data sets. Nat Biotech 29:915–921

    Article  CAS  Google Scholar 

  6. Peng Y, Leung HC, Yiu S, Chin FY (2012) IDBA-UD: a de novo assembler for single-cell and metagenomic sequencing data with highly uneven depth. Bioinformatics 28:1420–1428

    Article  CAS  PubMed  Google Scholar 

  7. Bankevich A, Nurk S, Antipov D, Gurevich AA, Dvorkin M, Kulikov AS, Lesin VM, Nikolenko SI, Pham S, Prjibelski AD, Pyshkin AV, Sirotkin AV, Vyahhi N, Tesler G, Alekseyev MA, Pevzner PA (2012) SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol 19:455–477

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  8. Boisvert S, Raymond F, Godzaridis E, Laviolette F, Corbeil J (2012) Ray Meta: scalable de novo metagenome assembly and profiling. Genome Biol 13:R122

    Article  PubMed Central  PubMed  Google Scholar 

  9. Namiki T, Hachiya T, Tanaka H, Sakakibara Y (2011) MetaVelvet: an extension of Velvet assembler to de novo metagenome assembly from short sequence reads. In: Proceedings of the 2nd ACM conference on bioinformatics, computational biology and biomedicine. pp. 116–124. Chicago, Illinois: ACM; 2011

    Google Scholar 

  10. Peng Y, Leung HCM, Yiu SM, Chin FYL (2011) Meta-IDBA: a de novo assembler for metagenomic data. Bioinformatics 27:i94–i101

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  11. Treangen T, Koren S, Astrovskaya I, Sommer D, Liu B, Pop M (2011) MetAMOS: a metagenomic assembly and analysis pipeline for AMOS. Genome Biol 12:P25

    Article  PubMed Central  Google Scholar 

  12. Kultima JR, Sunagawa S, Li J, Chen W, Chen H, Mende DR, Arumugam M, Pan Q, Liu B, Qin J et al (2012) MOCAT: a metagenomics assembly and gene prediction toolkit. PLoS One 7:e47656

    Article  PubMed Central  PubMed  Google Scholar 

  13. Heidelberg JF, Nelson WC, Schoenfeld T, Bhaya D (2009) Germ warfare in a microbial Mat community: CRISPRs provide insights into the Co-evolution of host and viral genomes. PLoS One 4:e4169

    Article  PubMed Central  PubMed  Google Scholar 

  14. Deveau H, Barrangou R, Garneau JE, Labonte J, Fremaux C (2008) Phage response to CRISPR-encoded resistance in Streptococcus thermophilus. J Bacteriol 190:1390

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  15. Bhaya D, Davison M, Barrangou R (2011) CRISPR-Cas systems in bacteria and archaea: versatile small RNAs for adaptive defense and regulation. Annu Rev Genet 45:273–297

    Article  CAS  PubMed  Google Scholar 

  16. Davison M, Treangen TJ, Koren S, Gosrani S, Pop M, Bhaya, D. Analysis of virome diversity in a polymicrobial community Manuscript submitted for publication.

    Google Scholar 

  17. Bhaya D, Grossman AR, Steunou A-S, Khuri N, Cohan FM, Hamamura N, Melendrez MC, Bateson MM, Ward DM, Heidelberg JF (2007) Population level functional diversity in a microbial community revealed by comparative genomic and metagenomic analyses. ISME J 1:703–713

    Article  CAS  PubMed  Google Scholar 

  18. Grissa I, Vergnaud G, Pourcel C (2007) The CRISPRdb database and tools to display CRISPRs and to generate dictionaries of spacers and repeats. BMC Bioinformat 8:172

    Article  Google Scholar 

  19. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ (1990) Basic local alignment search tool. J Mol Biol 215:403–410

    Article  CAS  PubMed  Google Scholar 

  20. Schmieder R, Edwards R (2011) Quality control and preprocessing of metagenomic datasets. Bioinformatics 27:863–864

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  21. Kurtz S, Phillippy A, Delcher A, Smoot M, Shumway M, Antonescu C, Salzberg S (2004) Versatile and open software for comparing large genomes. Genome Biol 5:R12

    Article  PubMed Central  PubMed  Google Scholar 

  22. Zhu W, Lomsadze A, Borodovsky M (2010) Ab initio gene identification in metagenomic sequences. Nucleic Acids Res 38:e132–e132

    Article  PubMed Central  PubMed  Google Scholar 

  23. Lowe TM, Eddy SR (1997) TRNAscan-SE: a program for improved detection of transfer RNA genes in genomic sequence. Nucleic Acids Res 25:0955–0964

    Article  CAS  Google Scholar 

  24. Langfelder P, Horvath S (2008) WGCNA: an R package for weighted correlation network analysis. BMC Bioinformat 9:559

    Article  Google Scholar 

  25. Emerson JB, Thomas BC, Andrade K, Allen EE, Heidelberg KB, Banfield JF (2012) Dynamic viral populations in hypersaline systems as revealed by metagenomic assembly. Appl Environ Microbiol 78:6309–6320

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  26. Ballantyne KN, van Oorschot RAH, Muharam I, van Daal A, John Mitchell R (2007) Decreasing amplification bias associated with multiple displacement amplification and short tandem repeat genotyping. Anal Biochem 368:222–229

    Article  CAS  PubMed  Google Scholar 

  27. Sundquist A, Bigdeli S, Jalili R, Druzin M, Waller S, Pullen K, El-Sayed Y, Taslimi MM, Batzoglou S, Ronaghi M (2007) Bacterial flora-typing with targeted, chip-based Pyrosequencing. BMC Microbiol 7:108

    Article  PubMed Central  PubMed  Google Scholar 

  28. Eddy SR (2011) Accelerated profile HMM searches. PLoS Comput Biol 7:e1002195

    Article  PubMed Central  CAS  PubMed  Google Scholar 

Download references

Acknowledgments

DB acknowledges funding support from the NSF (MCB#1024755) and the Carnegie Institution of Science. This protocol is a modification of the Viritas pipeline described in Davison et al (in prep) which was carried out in collaboration with Mihai Pop, a the University of Maryland and his group. Viritas has been incorporated into the metAMOS pipeline (https://github.com/marbl/metAMOS).

Author information

Authors and Affiliations

Authors

Corresponding author

Correspondence to Devaki Bhaya .

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2015 Springer Science+Business Media New York

About this protocol

Cite this protocol

Davison, M., Bhaya, D. (2015). Creation and Analysis of a Virome: Using CRISPR Spacers. In: Lundgren, M., Charpentier, E., Fineran, P. (eds) CRISPR. Methods in Molecular Biology, vol 1311. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-2687-9_20

Download citation

  • DOI: https://doi.org/10.1007/978-1-4939-2687-9_20

  • Publisher Name: Humana Press, New York, NY

  • Print ISBN: 978-1-4939-2686-2

  • Online ISBN: 978-1-4939-2687-9

  • eBook Packages: Springer Protocols

Publish with us

Policies and ethics