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MG-RAST, a Metagenomics Service for the Analysis of Microbial Community Structure and Function

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Hydrocarbon and Lipid Microbiology Protocols

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Abstract

Molecular ecology approaches are rapidly advancing our understanding of microbial communities involved in the synthesis and degradation of hydrophobic organics involved with major consequences for applications in climate change, environmental pollution, human health, and biotechnology. Metagenomics allows researchers to inventory microbial genes in various environments to understand the genetic potential of uncultured bacteria and archaea. Metagenomics enables us to sequence genomes from a complex assemblage of microbes in a culture-independent manner. Amplicon and WGS studies are the most widely employed methods to estimate “who is there” and “what they are doing.” Metagenomics allows researchers to access the functional and metabolic diversity of microbial communities.

Since 2008, MG-RAST serves as a repository for metagenomic datasets and as an analysis provider. Currently, the system has analyzed and hosts over 130,000 datasets. Over the years, MG-RAST has undergone a significant number of revisions to accommodate the dramatic growth in dataset size, new data types, and wider system adoption among the research community.

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References

  1. Wilkening J, Wilke A, Desai N, Meyer F (2009) Using clouds for metagenomics: a case study. In: Cluster. IEEE Computer Society, pp. 1–6. ISBN: 978-1-4244-5012-1

    Google Scholar 

  2. Angiuoli S, Matalka M, Gussman A et al (2011) Clovr: a virtual machine for automated and portable sequence analysis from the desktop using cloud computing. BMC Bioinformatics 12:356

    Article  PubMed  PubMed Central  Google Scholar 

  3. Meyer F, Paarmann D, D’Souza M et al (2008) The metagenomics RAST server – a public resource for the automatic phylogenetic and functional analysis of metagenomes. BMC Bioinformatics 9(1):386

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  4. Field D, Amaral-Zettler L, Cochrane G et al (2011) The genomic standards consortium. PLoS Biol 9(6), e1001088

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  5. Wilke A, Harrison T, Wilkening J et al (2012) The m5nr: a novel non-redundant database containing protein sequences and annotations from multiple sources and associated tools. BMC Bioinformatics 13:141

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  6. Altschul SF, Gish W, Miller W et al (1990) Basic local alignment search tool. J Mol Biol 215:403–410

    Article  CAS  PubMed  Google Scholar 

  7. Kent WJ (2002) Blat–the blast-like alignment tool. Genome Res 12(4):656–64

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  8. Brooksbank C, Bergman MT, Apweiler R et al (2014) The European bioinformatics Institute’s data resources 2014. Nucleic Acids Res 42(Database issue):D18–25

    Article  CAS  PubMed  Google Scholar 

  9. Reference Genome Group of the Gene Ontology Consortium (2009) The gene ontology’s reference genome project: a unified framework for functional annotation across species. PLoS Comput Biol 5(7):e1000431

    Article  Google Scholar 

  10. Markowitz VM, Ivanova NN, Szeto E et al (2008) IMG/M: a data management and analysis system for metagenomes. Nucleic Acids Res 36(Database issue):D534–538

    CAS  PubMed  Google Scholar 

  11. Kanehisa M (2002) The KEGG database. Novartis Found Symp 247:91–101

    Article  CAS  PubMed  Google Scholar 

  12. Benson DA, Cavanaugh M, Clark K (2013) Genbank. Nucleic Acids Res 41(Database issue):D36–42

    Article  CAS  PubMed  Google Scholar 

  13. Dwivedi B, Schmieder R, Goldsmith DB et al (2012) PhiSiGns: an online tool to identify signature genes in phages and design PCR primers for examining phage diversity. BMC Bioinformatics 4(13):37

    Article  Google Scholar 

  14. Overbeek R, Begley T, Butler RM et al (2005) The subsystems approach to genome annotation and its use in the project to annotate 1000 genomes. Nucleic Acids Res 33(17):5691–5702

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  15. Magrane M, Uniprot Consortium (2011) UniProt knowledgebase: a hub of integrated protein data. Database (Oxford). doi:10.1093/database/bar009

    Google Scholar 

  16. Snyder EE, Kampanya N, Lu J et al (2007) PATRIC: the VBI pathosystems resource integration center. Nucleic Acids Res 35(Database issue):D401–406

    Article  CAS  PubMed  Google Scholar 

  17. Jensen LJ, Julien P, Kuhn M et al (2008) Eggnog: automated construction and annotation of orthologous groups of genes. Nucleic Acids Res 36(Database issue):D250–4

    CAS  PubMed  Google Scholar 

  18. Tang W, Wilkening J, Desai N, Gerlach W, Wilke A, Meyer F (2013) A scalable data analysis platform for metagenomics. In: IEEE international conference on Big Data, IEEE, pp. 21–26

    Google Scholar 

  19. Cox MP, Peterson DA, Biggs PJ (2010) Solexaqa: at-a-glance quality assessment of illumina second-generation sequencing data. BMC Bioinformatics 11:485

    Article  PubMed  PubMed Central  Google Scholar 

  20. Huse SM, Huber JA, Morrison HG et al (2007) Accuracy and quality of massively parallel DNA pyrosequencing. Genome Biol 8(7):R143

    Article  PubMed  PubMed Central  Google Scholar 

  21. Gomez-Alvarez V, Teal TK, Schmidt TM (2009) Systematic artifacts in metagenomes from complex microbial communities. ISME J 3(11):1314–1317

    Article  PubMed  Google Scholar 

  22. Keegan KP, Trimble WL, Wilkening J et al (2012) A platform-independent method for detecting errors in metagenomic sequencing data: drisee. PLoS Comput Biol 8(6), e1002541

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  23. Langmead B, Trapnell C, Pop M et al (2009) Ultrafast and memory-efficient alignment of short DNA sequences to the human genome. Genome Biol 10(3):R25

    Article  PubMed  PubMed Central  Google Scholar 

  24. Trimble WL, Keegan KP, D’Souza M et al (2012) Short-read reading-frame predictors are not created equal: sequence error causes loss of signal. BMC Bioinformatics 13(1):183

    Article  PubMed  PubMed Central  Google Scholar 

  25. Rho M, Tang H, Ye Y (2009) Fraggenescan: predicting genes in short and error prone reads. Nucleic Acids Res 38(20), e191

    Article  Google Scholar 

  26. Edgar RC (2010) Search and clustering orders of magnitude faster than blast. Bioinformatics 26(19):2460–2461

    Article  CAS  PubMed  Google Scholar 

  27. Caporaso JG, Kuczynski J, Stombaugh J et al (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7(5):335–336

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  28. Huson DH, Auch AF, Qi J et al (2007) Megan analysis of metagenomic data. Genome Res 17(3):377–86

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  29. Aziz R, Bartels B, Best A et al (2008) The RAST server: rapid annotations using subsystems technology. BMC Genomics 9(1):75

    Article  PubMed  PubMed Central  Google Scholar 

  30. Pruesse E, Quast C, Knittel K et al (2007) SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res 35(21):7188–7196

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  31. DeSantis TZ, Hugenholtz P, Larsen N et al (2006) Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol 72(7):5069–5072

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  32. Cole JR, Chai B, Marsh TL et al (2003) The ribosomal database project (RDP-II): previewing a new autoaligner that allows regular updates and the new prokaryotic taxonomy. Nucleic Acids Res 31(1):442–443

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  33. Yilmaz P, Kottmann R, Field D et al (2011) Minimum information about a marker gene sequence (MIMARKS) and minimum information about any (x) sequence (MIxS) specifications. Nat Biotechnol 29(5):415–420

    Article  CAS  PubMed  PubMed Central  Google Scholar 

  34. Bolotin A, Quinquis B, Sorokin A et al (2005) Clustered regularly interspaced short palindrome repeats (CRISPRS) have spacers of extrachromosomal origin. Microbiology 151(Pt 8):2551–2561

    Article  CAS  PubMed  Google Scholar 

  35. Reeder J, Knight R (2009) The ‘rare biosphere’: a reality check. Nat Methods 6(9):636–637

    Article  CAS  PubMed  Google Scholar 

  36. Ondov BD, Bergman NH, Phillippy AM (2011) z. BMC Bioinformatics 12:385

    Article  PubMed  PubMed Central  Google Scholar 

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Correspondence to Folker Meyer .

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© 2015 Springer-Verlag Berlin Heidelberg

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Glass, E.M., Meyer, F. (2015). MG-RAST, a Metagenomics Service for the Analysis of Microbial Community Structure and Function. 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_119

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  • DOI: https://doi.org/10.1007/8623_2015_119

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  • Publisher Name: Springer, Berlin, Heidelberg

  • Print ISBN: 978-3-662-49309-0

  • Online ISBN: 978-3-662-49310-6

  • eBook Packages: Springer Protocols

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