Skip to main content

Bioinformatics for Genomes and Metagenomes in Ecology Studies

  • Chapter
Infectious Microecology

Abstract

Major technological developments in the field of microbial ecology are redefining the science, moving the focus of research away from studies of individual isolates and species that are studied under carefully controlled conditions in the laboratory, towards the study of entire communities of organisms in their natural environments. Ever more efficient sequencing technologies mean that we can generate huge volumes of sequence data — shifting the cost burden from sequence generation to sequence analysis. The bioinformatic techniques for managing and analyzing both the new types of data and the vastly increased volumes of data are transforming our understanding of life and its interdependencies. These data sets, in conjunction with bioinformatics are enhancing our understanding of microbial diversity and microbial ecology in many different environments. In this chapter, we provide an overview of some of the genomic, metagenomic and informatics approaches currently being used and or being developed for the study of microbial diversity and ecology.

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

Access this chapter

Subscribe and save

Springer+ Basic
EUR 32.99 /Month
  • Get 10 units per month
  • Download Article/Chapter or Ebook
  • 1 Unit = 1 Article or 1 Chapter
  • Cancel anytime
Subscribe now

Buy Now

Chapter
USD 29.95
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
eBook
USD 129.00
Price excludes VAT (USA)
  • Available as PDF
  • Read on any device
  • Instant download
  • Own it forever
Hardcover Book
USD 169.99
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

Preview

Unable to display preview. Download preview PDF.

Unable to display preview. Download preview PDF.

Similar content being viewed by others

References

  1. Metzker M L. Sequencing technologies — the next generation. Nature Reviews Genetics, 2009, 11: 31–46.

    Article  PubMed  Google Scholar 

  2. Mylvaganam S, Dennis P P. Sequence heterogeneity between the two genes encoding 16S rRNA from the halophilic archaebacterium Haloarcula marismortui. Genetics, 1992, 130: 399–410.

    PubMed Central  CAS  PubMed  Google Scholar 

  3. López-López A, Benlloch S, Bonfá M, et al. Intragenomic 16S rDNA divergence in Haloarcula marismortui is an adaptation to different temperatures. Journal of molecular evolution, 2007, 65: 687–696.

    Article  PubMed  Google Scholar 

  4. Pei A Y, Oberdorf W E, Nossa C W, et al. Diversity of 16S rRNA genes within individual prokaryotic genomes. Applied and environmental microbiology, 2010,76: 3886–3897.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  5. Ray A E, Connon S A, Sheridan P P, et al. Intragenomic heterogeneity of the 16S rRNA gene in strain UFO1 caused by a 100 - bp insertion in helix 6. FEMS microbiology ecology, 2010, 72: 343–353.

    Article  CAS  PubMed  Google Scholar 

  6. Unno T, Jang J, Han D, et al. Use of barcoded pyrosequencing and shared OTUs to determine sources of fecal bacteria in watersheds. Environmental science & technology, 2010, 44: 7777–7782.

    Article  CAS  Google Scholar 

  7. Thompson F L, Bruce T, Gonzalez A, et al. Coastal bacterioplankton community diversity along a latitudinal gradient in Latin America by means of V6 tag pyrosequencing. Arch Microbiol, 2011, 193: 105–114.

    Article  CAS  PubMed  Google Scholar 

  8. Whittaker R H. Evolution and measurement of species diversity. Taxon, 1972, 21: 213–251.

    Article  Google Scholar 

  9. DeSantis T Z, Hugenholtz P, Larsen N, et al. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Applied and environmental microbiology, 2006, 72: 5069–5072.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  10. Pruesse E, Quast C, Knittel K, et al. SILVA: A comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic acids research, 2007, 35: 7188–7196.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  11. Cole J, Wang Q, Cardenas E, et al. The ribosomal database project: Improved alignments and new tools for rRNA analysis. Nucleic acids research, 2009, 37: D141–D145.

    Article  Google Scholar 

  12. Wu D, Hartman A, Ward N, et al. An automated phylogenetic tree-based small subunit rRNA taxonomy and alignment pipeline (STAP). P1oS one, 2008, 3: e2566.

    Google Scholar 

  13. Bond P L, Hugenholtz P, Keller J, et al. Bacterial community structures of phosphate-removing and non-phosphate-removing activated sludges from sequencing batch reactors. Applied and Environmental Microbiology, 1995, 61: 1910–1916.

    PubMed Central  CAS  PubMed  Google Scholar 

  14. McCaig A E, Glover L A, Prosser J I. Molecular analysis of bacterial community structure and diversity in unimproved and improved upland grass pastures. Applied and Environmental Microbiology, 1999, 65: 1721–1730.

    PubMed Central  CAS  PubMed  Google Scholar 

  15. Schloss P D, Handelsman J. Introducing DOTUR, a computer program for defining operational taxonomic units and estimating species richness. Applied and environmental microbiology, 2005, 71: 1501–1506.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  16. Shuldiner A R, Nirula A, Roth J. Hybrid DNA artifact from PCR of closely related target sequences. Nucleic acids research, 1989, 17: 4409.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  17. Hugenholtz P, Huber T. Chimeric 16S rDNA sequences of diverse origin are accumulating in the public databases. International Journal of Systematic and Evolutionary Microbiology, 2003, 53: 289–293.

    Article  CAS  PubMed  Google Scholar 

  18. Ashelford K E, Chuzhanova N A, Fry J C, et al. At least 1 in 20 16S rRNA sequence records currently held in public repositories is estimated to contain substantial anomalies. Applied and Environmental Microbiology, 2005, 71: 7724–7736.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  19. Komatsoulis G A, Waterman M S. A new computational method for detection of chimeric 16S rRNA artifacts generated by PCR amplification from mixed bacterial populations. Applied and Environmental Microbiology, 1997, 63: 2338–2346.

    PubMed Central  CAS  PubMed  Google Scholar 

  20. Huber T, Faulkner G, Hugenholtz P. Bellerophon: A program to detect chimeric sequences in multiple sequence alignments. Bioinformatics, 2004, 20: 2317–2319.

    Article  CAS  PubMed  Google Scholar 

  21. Schloss P D, Westcott S L, Ryabin T, et al. Introducing mothur: Open-source, platform-independent, community-supported software for describing and comparing microbial communities. Applied and environmental microbiology, 2009, 75: 7537–7541.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  22. Sogin M L, Morrison H G, Huber J A, et al. Microbial diversity in the deep sea and the underexplored “rare biosphere”. Proceedings of the National Academy of Sciences, 2006, 103: 12115–12120.

    Article  CAS  Google Scholar 

  23. Hamady M, Knight R. Microbial community profiling for human microbiome projects: Tools, techniques, and challenges. Genome research, 2009, 19: 1141–1152.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  24. Turnbaugh P J, Hamady M, Yatsunenko T, et al. A core gut microbiome in obese and lean twins. Nature, 2008, 457: 480–484.

    Article  PubMed Central  PubMed  Google Scholar 

  25. Caporaso J G, Lauber C L, Walters W A, et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proceedings of the National Academy of Sciences, 2011, 108: 4516–4522.

    Article  CAS  Google Scholar 

  26. Liu Z, Lozupone C, Hamady M, et al. Short pyrosequencing reads suffice for accurate microbial community analysis. Nucleic acids research, 2007, 35: e120.

    Google Scholar 

  27. Reeder J, Knight R. The “rare biosphere”: A reality check. Nature Methods, 2009, 6: 636–637.

    Article  CAS  PubMed  Google Scholar 

  28. Kunin V, Engelbrektson A, Ochman H, et al. Wrinkles in the rare biosphere: Pyrosequencing errors can lead to artificial inflation of diversity estimates. Environmental microbiology, 2010, 12: 118–123.

    Article  CAS  PubMed  Google Scholar 

  29. Quince C, Lanzén A, Curtis T P, et al. Accurate determination of microbial diversity from 454 pyrosequencing data. Nature methods, 2009, 6: 639–641.

    Article  CAS  PubMed  Google Scholar 

  30. Huse S M, Welch D M, Morrison H G, et al. Ironing out the wrinkles in the rare biosphere through improved OTU clustering. Environmental Microbiology, 2010, 12: 1889–1898.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  31. Magurran A E. Ecological diversity and its measurement. Princeton: Princeton university press, 1988.

    Book  Google Scholar 

  32. Caporaso J G, Kuczynski J, Stombaugh J, et al. QIIME allows analysis of high-throughput community sequencing data. Nature methods, 2010, 7: 335–336.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  33. Venter J C, Remington K, Heidelberg J F, et al. Environmental genome shotgun sequencing of the Sargasso Sea. Science, 2004, 304: 66–74.

    Article  CAS  PubMed  Google Scholar 

  34. Rusch D B, Halpern A L, Sutton G, et al. The Sorcerer II global ocean sampling expedition: Northwest Atlantic through eastern tropical Pacific. PLoS biology, 2007, 5: e77.

    Google Scholar 

  35. Yooseph S, Sutton G, Rusch D B, et al. The Sorcerer II Global Ocean Sampling expedition: Expanding the universe of protein families. PLoS biology, 2007, 5: e16.

    Article  Google Scholar 

  36. Sharon I, Alperovitch A, Rohwer F, et al. Photosystem I gene cassettes are present in marine virus genomes. Nature, 2009, 461: 258–262.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  37. Comeau A M, Arbiol C, Krisch H. Gene network visualization and quantitative synteny analysis of more than 300 marine T4-like phage scaffolds from the GOS metagenome. Molecular biology and evolution, 2010, 27: 1935–1944.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  38. Sorokin V A, Gelfand M S, Artamonova II. Evolutionary dynamics of clustered irregularly interspaced short palindromic repeat systems in the ocean metagenome. Applied and environmental microbiology, 2010, 76: 2136–2144.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  39. Peterson J, Garges S, Giovanni M, et al. The NIH human microbiome project. Genome research, 2009, 19: 2317–2323.

    Article  PubMed Central  PubMed  Google Scholar 

  40. Yeoman C J, Yildirim S, Thomas S M, et al. Comparative genomics of Gardnerella vaginalis strains reveals substantial differences in metabolic and virulence potential. PLoS One, 2010, 5: e12411.

    Google Scholar 

  41. Nelson K E, Weinstock G M, Highlander S K, et al. A catalog of reference genomes from the human microbiome. Science (New York, NY), 2010, 328: 994.

    Article  CAS  Google Scholar 

  42. Qin J, Li R, Raes J, et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature, 2010, 464: 59–65.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  43. Brulc J M, Antonopoulos D A, Miller MEB, et al. Gene-centric metagenomics of the fiber-adherent bovine rumen microbiome reveals forage specific glycoside hydrolases. Proceedings of the National Academy of Sciences, 2009, 106: 1948–1953.

    Article  CAS  Google Scholar 

  44. Swanson K S, Dowd S E, Suchodolski J S, et al. Phylogenetic and gene-centric metagenomics of the canine intestinal microbiome reveals similarities with humans and mice. The ISME Journal, 2010, 5: 639–649.

    Article  PubMed Central  PubMed  Google Scholar 

  45. Qu A, Brulc J M, Wilson M K, et al. Comparative metagenomics reveals host specific metavirulomes and horizontal gene transfer elements in the chicken cecum microbiome. PLoS One, 2008, 3: e2945.

    Google Scholar 

  46. Yildirim S, Yeoman C J, Sipos M, et al. Characterization of the fecal microbiome from non-human wild primates reveals species specific microbial communities. PLoS One, 2010, 5: e13963.

    Google Scholar 

  47. Allen H K, Cloud-Hansen K A, Wolinski J M, et al. Resident microbiota of the gypsy moth midgut harbors antibiotic resistance determinants. DNA and cell biology, 2009, 28: 109–117.

    Article  CAS  PubMed  Google Scholar 

  48. Suen G, Scott J J, Aylward F O, et al. An insect herbivore microbiome with high plant biomass-degrading capacity. PLoS genetics, 2010, 6: e1001129.

    Google Scholar 

  49. Bishop-Lilly K A, Turell M J, Willner K M, et al. Arbovirus detection in insect vectors by rapid, high-throughput pyrosequencing. PLoS neglected tropical diseases, 2010, 4: e878.

    Google Scholar 

  50. Bench S R, Hanson T E, Williamson K E, et al. Metagenomic characterization of chesapeake bay virioplankton. Applied and Environ-mental Microbiology, 2007, 73: 7629–7641.

    Article  CAS  Google Scholar 

  51. Day J M, Ballard L L, Duke M V, et al. Metagenomic analysis of the turkey gut RNA virus community. Virol J, 2010, 7: 313.

    Article  PubMed Central  PubMed  Google Scholar 

  52. Reyes A, Haynes M, Hanson N, et al. Viruses in the faecal microbiota of monozygotic twins and their mothers. Nature, 2010, 466: 334–338.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  53. Sanger F, Coulson A R, Barrell B G, et al. Cloning in single-stranded bacteriophage as an aid to rapid DNA sequencing. J Mol Biol, 1980, 143: 161–178.

    Article  CAS  PubMed  Google Scholar 

  54. Fleischmann R D, Adams M D, White O, et al. Whole-genome random sequencing and assembly of Haemophilus influenzae Rd. Science, 1995, 269: 496–512.

    Article  CAS  PubMed  Google Scholar 

  55. Sutton G G, White O, Adams M D, et al. TIGR Assembler: A new tool for assembling large shotgun sequencing projects. Genome Science and Technology, 1995, 1: 9–19.

    Article  CAS  Google Scholar 

  56. Adams M D, Celniker S E, Holt R A, et al. The genome sequence of Drosophila melanogaster. Science, 2000, 287: 2185–2195.

    Article  PubMed  Google Scholar 

  57. Myers E W, Sutton G G, Delcher A L, et al. A whole-genome assembly of Drosophila. Science, 2000, 287: 2196–2204.

    Article  CAS  PubMed  Google Scholar 

  58. Istrail S, Sutton G G, Florea L, et al. Whole-genome shotgun assembly and comparison of human genome assemblies. Proceedings of the National Academy of Sciences of the United States of America, 2004, 101: 1916–1921.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  59. Pop M. Genome assembly reborn: Recent computational challenges. Briefings in bioinformatics, 2009, 10: 354–366.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  60. Miller J R, Koren S, Sutton G. Assembly algorithms for next-generation sequencing data. Genomics, 2010, 95: 315.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  61. Miller J R, Delcher A L, Koren S, et al. Aggressive assembly of pyrosequencing reads with mates. Bioinformatics, 2008, 24: 2818–2824.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  62. Niu B, Fu L, Sun S, et al. Artificial and natural duplicates in pyrosequencing reads of metagenomic data. BMC bioinformatics, 2010, 11: 187.

    Article  PubMed Central  PubMed  Google Scholar 

  63. Teal T K, Schmidt T M. Identifying and removing artificial replicates from 454 pyrosequencing data. Cold Spring Harbor Protocols, 2010, 2010: prot5409.

    Article  Google Scholar 

  64. Rusch D B, Martiny A C, Dupont C L, et al. Characterization of Prochlorococcus clades from iron-depleted oceanic regions. Proc Natl Acad Sci USA, 2010, 107: 16184–16189.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  65. Woyke T, Tighe D, Mavromatis K, et al. One bacterial cell, one complete genome. PLoS One, 2010, 5: e10314.

    Google Scholar 

  66. McHardy A C, Martin H G, Tsirigos A, et al. Accurate phylogenetic classification of variable-length DNA fragments. Nat Methods, 2007, 4: 63–72.

    Article  CAS  PubMed  Google Scholar 

  67. Brady A, Salzberg S L. Phymm and PhymmBL: Metagenomic phylogenetic classification with interpolated Markov models. Nat Methods, 2009, 6: 673–676.

    Article  PubMed Central  CAS  PubMed  Google Scholar 

  68. Lucks J B, Nelson D R, Kudla G R, et al. Genome landscapes and bacteriophage codon usage. PLoS Comput Biol, 2008, 4: e1000001.

    Google Scholar 

  69. Haft D H, Selengut J, Mongodin E F, et al. A guild of 45 CRISPR-associated (Cas) protein families and multiple CRISPR/Cas subtypes exist in prokaryotic genomes. PLoS computational biology, 2005, 1: e60.

    Google Scholar 

  70. Barrangou R, Fremaux C, Deveau H, et al. CRISPR provides acquired resistance against viruses in prokaryotes. Science, 2007, 315: 1709–1712.

    Article  CAS  PubMed  Google Scholar 

  71. Yooseph S, Nealson K H, Rusch D B, et al. Genomic and functional adaptation in surface ocean planktonic prokaryotes. Nature, 2010, 468: 60–66.

    Article  CAS  PubMed  Google Scholar 

  72. Camacho C, Coulouris G, Avagyan V, et al. BLAST+: Architecture and applications. BMC Bioinformatics, 2009, 10: 421.

    Article  PubMed Central  PubMed  Google Scholar 

  73. Wooley J C, Godzik A, Friedberg I. A primer on metagenomics. PLoS computational biology, 2010, 6: e1000667.

    Google Scholar 

  74. Piganeau G, Moreau H. Screening the Sargasso Sea metagenome for data to investigate genome evolution in Ostreococcus (Prasinophyceae, Chlorophyta). Gene, 2007, 406: 184–190.

    Article  CAS  PubMed  Google Scholar 

  75. Piganeau G, Desdevises Y, Derelle E, et al. Picoeukaryotic sequences in the Sargasso sea metagenome. Genome Biol, 2008, 9: R5.

    Article  Google Scholar 

  76. Johnson M, Zaretskaya I, Raytselis Y, et al. NCBI BLAST: A better web interface. Nucleic Acids Res, 2008, 36: W5-W9.

    Article  Google Scholar 

  77. Sansom C. Up in a cloud? Nat Biotechnol, 2010, 28: 13–15.

    Article  CAS  PubMed  Google Scholar 

  78. Lasken R. Genomic DNA amplification by the multiple displacement amplification (MDA) method. Biochemical Society Transactions, 2009, 37: 450.

    Article  CAS  PubMed  Google Scholar 

Download references

Author information

Authors and Affiliations

Authors

Editor information

Editors and Affiliations

Rights and permissions

Reprints and permissions

Copyright information

© 2014 Zhejiang University Press, Hangzhou and Springer-Verlag Berlin Heidelberg

About this chapter

Cite this chapter

Rusch, D.B. et al. (2014). Bioinformatics for Genomes and Metagenomes in Ecology Studies. In: Li, L. (eds) Infectious Microecology. Advanced Topics in Science and Technology in China. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-662-43883-1_9

Download citation

Publish with us

Policies and ethics