Recovery of genomes from metagenomes via a dereplication, aggregation and scoring strategy

Nature Microbiology

Volumn 3, Issue 7, 2018, Pages 836-843

  Sieber, Christian M K ^a,b   Probst, Alexander J ^b   Sharrar, Allison ^b   Thomas, Brian C ^b   Hess, Matthias ^c   Tringe, Susannah G ^a   Banfield, Jillian F ^b  

^a DOE JOINT GENOME INSTITUTE   (United States)

^b UNIVERSITY OF CALIFORNIA   (United States)

^c UNIVERSITY OF CALIFORNIA   (United States)

Author keywords

[No Author keywords available]

Indexed keywords

ARTICLE; CONTROLLED STUDY; DEREPLICATION AGGREGATION AND SCORING TOOL; GENOME ANALYSIS; INTERMETHOD COMPARISON; LEARNING ALGORITHM; MEASUREMENT ACCURACY; METAGENOME; METAGENOMICS; MICROBIAL COMMUNITY; MICROBIAL GENOME; POPULATION ABUNDANCE; PREDICTION; PRIORITY JOURNAL; ALGORITHM; ANIMAL; BACTERIAL GENOME; BIOLOGY; COMPUTER INTERFACE; HUMAN; INFORMATION PROCESSING; INTESTINE FLORA; MICROBIOLOGY; MICROFLORA; PROCEDURES;

ALGORITHMS; ANIMALS; COMPUTATIONAL BIOLOGY; DATA CURATION; GASTROINTESTINAL MICROBIOME; GENOME, BACTERIAL; HUMANS; METAGENOMICS; MICROBIOTA; SOIL MICROBIOLOGY; USER-COMPUTER INTERFACE; WATER MICROBIOLOGY;

EID: 85047827857     PISSN: None     EISSN: 20585276     Source Type: Journal    
DOI: 10.1038/s41564-018-0171-1     Document Type: Article

References (46)

1. Tyson, G. W. et al. Community structure and metabolism through reconstruction of microbial genomes from the environment. Nature 428, 37-43 (2004).
2. Teeling, H., Meyerdierks, A., Bauer, M., Amann, R. &Glöckner, F. O. Application of tetranucleotide frequencies for the assignment of genomic fragments. Environ. Microbiol. 6, 938-947 (2004).
3. Abe, T. et al. A novel bioinformatic strategy for unveiling hidden genome signatures of eukaryotes: self-organizing map of oligonucleotide frequency. Genome Inform. 13, 12-20 (2002).
4. Dick, G. J. et al. Community-wide analysis of microbial genome sequence signatures. Genome Biol. 10, R85 (2009).
5. Anantharaman, K., Breier, J. A. &Dick, G. J. Metagenomic resolution of microbial functions in deep-sea hydrothermal plumes across the Eastern Lau Spreading Center. ISME J. 10, 225-239 (2016).
6. Hug, L. A. et al. Critical biogeochemical functions in the subsurface are associated with bacteria from new phyla and little studied lineages. Env. Microbiol. 18, 159-173 (2015).
7. Sharon, I. et al. Time series community genomics analysis reveals rapid shifts in bacterial species, strains, and phage during infant gut colonization. Genome Res. 23, 111-120 (2013).
8. Albertsen, M. et al. Genome sequences of rare, uncultured bacteria obtained by differential coverage binning of multiple metagenomes. Nat. Biotechnol. 31, 533-538 (2013).
9. Alneberg, J. et al. Binning metagenomic contigs by coverage and composition. Nat. Methods 11, 1144-1146 (2014).
10. Kang, D. D., Froula, J., Egan, R. &Wang, Z. MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. PeerJ 3, e1165 (2015).
11. Lu, Y. Y., Chen, T., Fuhrman, J. A. &Sun, F. COCACOLA: binning metagenomic contigs using sequence COmposition, read CoverAge, CO-alignment and paired-end read LinkAge. Bioinformatics 33, 791-798 (2017).
12. Graham, E. D., Heidelberg, J. F. &Tully, B. J. BinSanity: unsupervised clustering of environmental microbial assemblies using coverage and affinity propagation. PeerJ 5, e3035 (2017).
13. Wu, Y.-W. W., Simmons, B. A. &Singer, S. W. MaxBin 2.0: an automated binning algorithm to recover genomes from multiple metagenomic datasets. Bioinformatics 32, 605-607 (2015).
14. Lin, H.-H. &Liao, Y.-C. Accurate binning of metagenomic contigs via automated clustering sequences using information of genomic signatures and marker genes. Sci. Rep. 6, 24175 (2016).
15. Parks, D. H., Imelfort, M., Skennerton, C. T., Hugenholtz, P. &Tyson, G. W. CheckM: assessing the quality of microbial genomes recovered from isolates, single cells, and metagenomes. Genome Res. 25, 1043-1055 (2015).
16. Simao, F. A., Waterhouse, R. M., Ioannidis, P., Kriventseva, E. V. &Zdobnov, E. M. BUSCO: assessing genome assembly and annotation completeness with single-copy orthologs. Bioinformatics 31, 3210-3212 (2015).
17. Probst, A. J. et al. Genomic resolution of a cold subsurface aquifer community provides metabolic insights for novel microbes adapted to high CO2 concentrations. Environ. Microbiol. 19, 459-474 (2017).
18. Song, W.-Z. &Thomas, T. Binning-refiner: improving genome bins through the combination of different binning programs. Bioinformatics 33, 1873-1875 2017).
19. Sczyrba, A. et al. Critical Assessment of Metagenome Interpretation-A benchmark of metagenomics software. Nat. Methods 14, 1063-1071 (2017).
20. Di Rienzi, S. C. et al. The human gut and groundwater harbor nonphotosynthetic bacteria belonging to a new candidate phylum sibling to Cyanobacteria. Elife 2, e01102 (2013).
21. Hawley, E. R. et al. Metagenomes from two microbial consortia associated with Santa Barbara seep oil. Mar. Genomics 18, 97-99 (2014).
22. Hawley, E. R. et al. Metagenomic analysis of microbial consortium from natural crude oil that seeps into the marine ecosystem offshore Southern California. Stand. Genom. Sci. 9, 1259-1274 (2014).
23. Quast, C. et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res. 41, D590-D596 (2013).
24. Butterfield, C. N. et al. Proteogenomic analyses indicate bacterial methylotrophy and archaeal heterotrophy are prevalent below the grass root zone. PeerJ 4, e2687 (2016).
25. R Core Team. R: A Language and Environment for Statistical Computing (R Foundation for Statistical Computing, 2015).
26. Weston, S. &Calaway, R. doMC: Foreach Parallel Adaptor for 'parallel' (2015); https://cran.r-project.org/web/packages/doMC
27. Dowle, M., Srinivasan, A., Short, T., Saporta, S. L. &Antonyan, E. data.table: Extension of Data.frame (2015); https://cran.r-project.org/web/packages/ data.table
28. Wickham, H. ggplot2: Elegant Graphics for Data Analysis (Springer-Verlag, New York, 2009).
29. Hyatt, D., Locascio, P. F., Hauser, L. J. &Uberbacher, E. C. Gene and translation initiation site prediction in metagenomic sequences. Bioinformatics 28, 2223-2230 (2012).
30. Brown, C. T. et al. Unusual biology across a group comprising more than 15% of domain Bacteria. Nature 523, 208-211 (2015).
31. Edgar, R. C. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 26, 2460-2461 (2010).
32. Buchfink, B., Xie, C. &Huson, D. H. Fast and sensitive protein alignment using DIAMOND. Nat. Methods 12, 59-60 (2015).
33. Altschul, S. F., Gish, W., Miller, W., Myers, E. W. &Lipman, D. J. Basic local alignment search tool. J. Mol. Biol. 215, 403-410 (1990).
34. Singer, E. et al. Next generation sequencing data of a defined microbial mock community. Sci. Data 3, 160081 (2016).
35. Peng, Y., Leung, H. C. M., Yiu, S. M. &Chin, F. Y. L. IDBA-UD: a de novo assembler for single-cell and metagenomic sequencing data with highly uneven depth. Bioinformatics 28, 1420-1428 (2012).
36. Langmead, B. &Salzberg, S. L. Fast gapped-read alignment with Bowtie 2. Nat. Methods 9, 357-359 (2012).
37. Ultsch, A. &Mörchen, F. ESOM-Maps: Tools for Clustering, Visualization, and Classification with Emergent SOM (2005); http://databionic-esom. sourceforge.net
38. Wrighton, K. C. et al. Fermentation, hydrogen, and sulfur metabolism in multiple uncultivated bacterial phyla. Science 337, 1661-1665 (2012).
39. Kanehisa, M. &Goto, S. KEGG: Kyoto Encyclopedia of Genes and Genomes. Nucleic Acids Res. 28, 27-30 (2000).
40. Suzek, B. E., Huang, H., McGarvey, P., Mazumder, R. &Wu, C. H. UniRef: comprehensive and non-redundant UniProt reference clusters. Bioinformatics 23, 1282-1288 (2007).
41. UniProt Consortium. UniProt: a hub for protein information. Nucleic Acids Res. 43, D204-D212 (2015).
42. Edgar, R. C. MUSCLE: a multiple sequence alignment method with reduced time and space complexity. BMC Bioinformatics 5, 113 (2004).
43. Stamatakis, A. RAxML version 8: a tool for phylogenetic analysis and post-analysis of large phylogenies. Bioinformatics 30, 1312-1313 (2014).
44. Miller, M. A., Pfeiffer, W. &Schwartz, T. Creating the CIPRES Science Gateway for inference of large phylogenetic trees. Gatew. Comput. Environ. Work. (GCE) 2010, 1-8 (2010).
45. Nawrocki, E. P. Structural RNA Homology Search and Alignment using Covariance Models All Theses and Dissertations (ETDs) (Washington University in Saint Louis, School of Medicine, 2009).
46. Paradis, E., Claude, J. &Strimmer, K. APE: analyses of phylogenetics and evolution in R language. Bioinformatics 20, 289-290 (2004).