Genomes from uncultivated prokaryotes: A comparison of metagenome-assembled and single-amplified genomes 06 Biological Sciences 0604 Genetics

Microbiome

Volumn 6, Issue 1, 2018, Pages

  Alneberg, Johannes ^a   Karlsson, Christofer M G ^b   Divne, Anna Maria ^c   Bergin, Claudia ^c   Homa, Felix ^c   Lindh, Markus V ^b,e   Hugerth, Luisa W ^a,d   Ettema, Thijs J G ^c   Bertilsson, Stefan ^c   Andersson, Anders F ^a   Pinhassi, Jarone ^b  

^a ROYAL INSTITUTE OF TECHNOLOGY   (Sweden)

^b LINNAEUS UNIVERSITY   (Sweden)

^c UPPSALA UNIVERSITY   (Sweden)

^d KAROLINSKA INSTITUTE   (Sweden)

^e LUND UNIVERSITY   (Sweden)

Author keywords

Binning; Metagenome assembled genomes; Metagenomics; Single amplified genomes; Single cell genomics

Indexed keywords

ARTICLE; BACTERIAL GENOME; BALTIC SEA; BIOMEDICINE; GENE AMPLIFICATION; HUMAN CELL; IDENTITY; METAGENOME; METAGENOMICS; MICROBIOME; NONHUMAN; PROKARYOTE; TIME SERIES ANALYSIS; BACTERIUM; CLASSIFICATION; GENETICS; HIGH THROUGHPUT SEQUENCING; MICROFLORA; NUCLEIC ACID AMPLIFICATION; PROCEDURES; SEA; SEQUENCE ALIGNMENT; SWEDEN; WHOLE GENOME SEQUENCING;

RNA 16S;

BACTERIA; GENOME, BACTERIAL; HIGH-THROUGHPUT NUCLEOTIDE SEQUENCING; METAGENOME; MICROBIOTA; NUCLEIC ACID AMPLIFICATION TECHNIQUES; OCEANS AND SEAS; RNA, RIBOSOMAL, 16S; SEQUENCE ALIGNMENT; SWEDEN; WHOLE GENOME SEQUENCING;

EID: 85054254141     PISSN: None     EISSN: 20492618     Source Type: Journal    
DOI: 10.1186/s40168-018-0550-0     Document Type: Article

References (97)

1. Reddy T, Thomas AD, Stamatis D. The Genomes OnLine Database (GOLD) v. 5: a metadata management system based on a four level (meta) genome project classification. Nucleic acids Res. 2014;43(Database issue):D1099-106.
2. Mukherjee S, Stamatis D, Bertsch J, Ovchinnikova G, Verezemska O, Isbandi M, et al. Genomes OnLine Database (GOLD) v.6: data updates and feature enhancements. Nucleic Acids Res. 2016;45:gkw992.
3. Bult CJ, White O, Olsen GJ, Zhou L, Fleischmann RD, Sutton GG, et al. Complete genome sequence of the methanogenic archaeon, Methanococcus jannaschii. Science. 1996;273:1058-73.
4. Wu D, Hugenholtz P, Mavromatis K, Pukall R, Dalin E, Ivanova NN, et al. A phylogeny-driven genomic encyclopaedia of bacteria and archaea. Nature. 2009;462:1056-60.
5. Craig Venter J, Adams MD, Myers EW, Li PW, Mural RJ, Sutton Granger G, et al. The sequence of the human genome. Science. 2001;291:1304-51.
6. Turnbaugh PJ, Ley RE, Hamady M, Fraser-Liggett CM, Knight R, Gordon JI. The human microbiome project. Nature. 2007;449:804-10.
7. Nemergut DR, Costello EK, Hamady M, Lozupone C, Jiang L, Schmidt SK, et al. Global patterns in the biogeography of bacterial taxa. Environ Microbiol. 2011;13:135-44.
8. Sunagawa S, Coelho LP, Chaffron S, Kultima JR, Labadie K, Salazar G, et al. Ocean plankton. Structure and function of the global ocean microbiome. Science. 2015;348:1261359.
9. Durham BP, Sharma S, Luo H, Smith CB, Amin SA, Bender SJ, et al. Cryptic carbon and sulfur cycling between surface ocean plankton. Proc Natl Acad Sci USA. 2015;112:453-7.
10. Kanehisa M, Sato Y, Kawashima M, Furumichi M, Tanabe M. KEGG as a reference resource for gene and protein annotation. Nucleic Acids Res. 2016;44:D457-62.
11. Choi J, Yang F, Stepanauskas R, Cardenas E, Garoutte A, Williams R, et al. Strategies to improve reference databases for soil microbiomes. ISME J. 2016;11:829-34.
12. Whitman WB, Coleman DC, Wiebe WJ. Prokaryotes: the unseen majority. Proc Natl Acad Sci USA. 1998;95:6578-83.
13. Falkowski PG, Fenchel T, Delong EF. The microbial engines that drive Earth's biogeochemical cycles. Science. 2008;320:1034-9.
14. Amann RI, Ludwig W, Schleifer KH. Phylogenetic identification and in situ detection of individual microbial cells without cultivation. Microbiol Rev. 1995;59:143-69.
15. Zhang K, Martiny AC, Reppas NB, Barry KW, Malek J, Chisholm SW, et al. Sequencing genomes from single cells by polymerase cloning. Nat Biotechnol. 2006;24:680-6.
16. Woyke T, Tighe D, Mavromatis K, Clum A, Copeland A, Schackwitz W, et al. One bacterial cell, one complete genome. PLoS One. 2010;5:e10314.
17. Landry ZC, Giovanonni SJ, Quake SR, Blainey PC. Optofluidic cell selection from complex microbial communities for single-genome analysis. Methods Enzymol. 2013;531:61-90.
18. Rinke C, Lee J, Nath N, Goudeau D, Thompson B, Poulton N, et al. Obtaining genomes from uncultivated environmental microorganisms using FACS-based single-cell genomics. Nat Protoc. 2014;9:1038-48.
19. Navin N, Kendall J, Troge J, Andrews P, Rodgers L, McIndoo J, et al. Tumour evolution inferred by single-cell sequencing. Nature. 2011;472:90-4.
20. Marcy Y, Ouverney C, Bik EM, Losekann T, Ivanova N, Martin HG, et al. Dissecting biological "dark matter" with single-cell genetic analysis of rare and uncultivated TM7 microbes from the human mouth. Proc Natl Acad Sci USA. 2007;104:11889-94.
21. Gawad C, Koh W, Quake SR. Single-cell genome sequencing: current state of the science. Nat Rev Genet. 2016;17:175-88.
22. Kashtan N, Roggensack SE, Rodrigue S, Thompson JW, Biller SJ, Coe A, et al. Single-cell genomics reveals hundreds of coexisting subpopulations in wild Prochlorococcus. Science. 2014;344:416-20.
23. Hugerth LW, Larsson J, Alneberg J, Lindh MV, Legrand C, Pinhassi J, et al. Metagenome-assembled genomes uncover a global brackish microbiome. Genome Biol. 2015;16:279.
24. Bowers RM, Kyrpides NC, Stepanauskas R, Harmon-Smith M, Doud D, Reddy TBK, et al. Minimum information about a single amplified genome (MISAG) and a metagenome-assembled genome (MIMAG) of bacteria and archaea. Nat Biotechnol. 2017;35:725-31.
25. Tyson GW, Chapman J, Hugenholtz P, Allen EE, Ram RJ, Richardson PM, et al. Community structure and metabolism through reconstruction of microbial genomes from the environment. Nature. 2004;428:37-43.
26. Sharon I, Morowitz MJ, Thomas BC, Costello EK, Relman DA, Banfield JF. Time series community genomics analysis reveals rapid shifts in bacterial species, strains, and phage during infant gut colonization. Genome Res. 2013;23:111-20.
27. Albertsen M, Hugenholtz P, Skarshewski A, Nielsen KL, Tyson GW, Nielsen PH. Genome sequences of rare, uncultured bacteria obtained by differential coverage binning of multiple metagenomes. Nature Biotechnol. 2013;31:533-8.
28. Alneberg J, Bjarnason BS, de Bruijn I, Schirmer M, Quick J, Ijaz UZ, et al. Binning metagenomic contigs by coverage and composition. Nat Methods. 2014;11:1144-6.
29. Imelfort M, Parks D, Woodcroft BJ, Dennis P, Hugenholtz P, Tyson GW. GroopM: an automated tool for the recovery of population genomes from related metagenomes. PeerJ. 2014;2:e603.
30. Swan BK, Martinez-Garcia M, Preston CM, Sczyrba A, Woyke T, Lamy D, et al. Potential for chemolithoautotrophy among ubiquitous bacteria lineages in the dark ocean. Science. 2011;333:1296-300.
31. Rinke C, Schwientek P, Sczyrba A, Ivanova NN, Anderson IJ, Cheng J-F, et al. Insights into the phylogeny and coding potential of microbial dark matter. Nature. 2013;499:431-7.
32. Spang A, Saw JH, Jørgensen SL, Zaremba-Niedzwiedzka K, Martijn J, Lind AE, et al. Complex archaea that bridge the gap between prokaryotes and eukaryotes. Nature. 2015;521:173-9.
33. Zaremba-Niedzwiedzka K, Caceres EF, Saw JH, Backstrom D, Juzokaite L, Vancaester E, et al. Metagenomic exploration of Asgard archaea illuminates the origin of eukaryotic cellular complexity. Nature. 2017;541:353-8.
34. Stewart RD, Auffret MD, Warr A, Wiser AH, Press MO, Langford KW, et al. Assembly of 913 microbial genomes from metagenomic sequencing of the cow rumen. Nat Commun. 2018;9:870.
35. Parks DH, Rinke C, Chuvochina M, Chaumeil PA, Woodcroft BJ, Evans PN, Hugenholtz P, Tyson GW. Recovery of nearly 8,000 metagenome-assembled genomes substantially expands the tree of life. Nature Microbiol. 2017;2:1533-42.
36. Stepanauskas R. Single cell genomics: an individual look at microbes. Curr Opin Microbiol. 2012;15:613-20.
37. Troell K, Hallström B, Divne A-M, Alsmark C, Arrighi R, Huss M, et al. Cryptosporidium as a testbed for single cell genome characterization of unicellular eukaryotes. BMC Genomics. 2016;17:471.
38. Lasken RS, Stockwell TB. Mechanism of chimera formation during the multiple displacement amplification reaction. BMC Biotechnol. 2007;7:19.
39. Woyke T, Sczyrba A, Lee J, Rinke C, Tighe D, Clingenpeel S, et al. Decontamination of MDA reagents for single cell whole genome amplification. PLoS One. 2011;6:e26161.
40. Clingenpeel S, Clum A, Schwientek P, Rinke C, Woyke T. Reconstructing each cell's genome within complex microbial communities-dream or reality? Front Microbiol. 2015;6:1-6.
41. Sangwan N, Xia F, Gilbert JA. Recovering complete and draft population genomes from metagenome datasets. Microbiome. 2016;4:8.
42. Kang DD, Froula J, Egan R, Wang Z. MetaBAT, an efficient tool for accurately reconstructing single genomes from complex microbial communities. PeerJ. 2015;3:e1165.
43. Nobu MK, Dodsworth JA, Murugapiran SK, Rinke C, Gies EA, Webster G, et al. Phylogeny and physiology of candidate phylum "Atribacteria" (OP9/JS1) inferred from cultivation-independent genomics. ISME J. 2016;10:273-86.
44. Mason OU, Hazen TC, Borglin S, Chain PSG, Dubinsky EA, Fortney JL, et al. Metagenome, metatranscriptome and single-cell sequencing reveal microbial response to Deepwater Horizon oil spill. ISME J. 2012;6:1715-27.
45. Mende DR, Aylward FO, Eppley JM, Nielsen TN, DeLong EF. Improved environmental genomes via integration of metagenomic and single-cell assemblies. Front Microbiol. 2016;7:1-9.
46. Becraft ED, Dodsworth JA, Murugapiran SK, Ohlsson JI, Briggs BR, Kanbar J, et al. Single-cell-genomics-facilitated read binning of candidate phylum EM19 genomes from geothermal spring metagenomes. Appl Environ Microbiol. 2015;82:992-1003.
47. Herlemann DP, Labrenz M, Jürgens K, Bertilsson S, Waniek JJ, Andersson AF. Transitions in bacterial communities along the 2000 km salinity gradient of the Baltic Sea. ISME J. 2011;5:1571-9.
48. Andersson AF, Riemann L, Bertilsson S. Pyrosequencing reveals contrasting seasonal dynamics of taxa within Baltic Sea bacterioplankton communities. ISME J. 2010;4:171-81.
49. Lindh MV, Sjöstedt J, Andersson AF, Baltar F, Hugerth LW, Lundin D, et al. Disentangling seasonal bacterioplankton population dynamics by high-frequency sampling. Environ Microbiol. 2015;17:2459-76.
50. Dupont CL, Larsson J, Yooseph S, Ininbergs K, Goll J, Asplund-Samuelsson J, et al. Functional tradeoffs underpin salinity-driven divergence in microbial community composition. PLoS One. 2014;9:e89549.
51. Ondov BD, Treangen TJ, Melsted P, Mallonee AB, Bergman NH, Koren S, et al. Mash: fast genome and metagenome distance estimation using MinHash. Genome Biol. 2016;17:132.
52. Eren AM, Esen ÖC, Quince C, Vineis JH, Morrison HG, Sogin ML, et al. Anvi'o: an advanced analysis and visualization platform for 'omics data. PeerJ. 2015;3:e1319.
53. Dick GJ, Andersson AF, Baker BJ, Simmons SL, Thomas BC, Yelton AP, et al. Community-wide analysis of microbial genome sequence signatures. Genome Biol. 2009;10:R85.
54. Konstantinidis KT, Tiedje JM. Genomic insights that advance the species definition for prokaryotes. Proc Natl Acad Sci USA. 2005;102:2567-72.
55. Konstantinidis KT, Rosselló-Móra R. Classifying the uncultivated microbial majority: a place for metagenomic data in the candidatus proposal. Syst Appl Microbiol. 2015;38:223-30.
56. Goris J, Konstantinidis KT, Klappenbach JA, Coenye T, Vandamme P, Tiedje JM. DNA-DNA hybridization values and their relationship to whole-genome sequence similarities. Int J Syst Evol Microbiol. 2007;57:81-91.
57. Richter M, Rosselló-Móra R. Shifting the genomic gold standard for the prokaryotic species definition. Proc Natl Acad Sci USA. 2009;106:19126-31.
58. Varghese NJ, Mukherjee S, Ivanova N, Konstantinidis KT, Mavrommatis K, Kyrpides NC, et al. Microbial species delineation using whole genome sequences. Nucleic Acids Res. 2015;43:6761-71.
59. Sczyrba A, Hofmann P, Belmann P, Koslicki D, Janssen S, Dröge J, et al. Critical assessment of metagenome interpretation - a benchmark of metagenomics software. Nat Methods. 2017;14:1063-71.
60. Quince C, Delmont TO, Raguideau S, Alneberg J, Darling AE, Collins G, Eren AM. DESMAN: a new tool for de novo extraction of strains from metagenomes. Genome Biol. 2017;18:181.
61. Schloissnig S, Arumugam M, Sunagawa S, Mitreva M, Tap J, Zhu A, et al. Genomic variation landscape of the human gut microbiome. Nature. 2012;493:45-50.
62. Nayfach S, Rodriguez-Mueller B, Garud N, Pollard KS. An integrated metagenomics pipeline for strain profiling reveals novel patterns of bacterial transmission and biogeography. Genome Res. 2016;26:1612-25.
63. Andersson AF, Sjöqvist C. POGENOM. POGENOM: population genomics from metagenomes. 2017. Available from: https://github.com/EnvGen/POGENOM
64. Ghylin TW, Garcia SL, Moya F, Oyserman BO, Schwientek P, Forest KT, et al. Comparative single-cell genomics reveals potential ecological niches for the freshwater acI Actinobacteria lineage. ISME J. 2014;8:2503-16.
65. Eiler A, Mondav R, Sinclair L, Fernandez-Vidal L, Scofield DG, Schwientek P, et al. Tuning fresh: radiation through rewiring of central metabolism in streamlined bacteria. ISME J. 2016;10:1902-14.
66. Chen C, Xing D, Tan L, Li H, Zhou G, Huang L, et al. Single-cell whole-genome analyses by Linear Amplification via Transposon Insertion (LIANTI). Science. 2017;356:189-94.
67. Leung K, Klaus A, Lin BK, Laks E, Biele J, Lai D, et al. Robust high-performance nanoliter-volume single-cell multiple displacement amplification on planar substrates. Proc Natl Acad Sci USA. 2016;113:8484-9.
68. Li D, Liu C-M, Luo R, Sadakane K, Lam T-W. MEGAHIT: an ultra-fast single-node solution for large and complex metagenomics assembly via succinct de Bruijn graph. Bioinformatics. 2015;31:1674-6.
69. Nurk S, Meleshko D, Korobeynikov A, Pevzner PA. metaSPAdes: a new versatile metagenomic assembler. Genome Res. 2017;27:824-34.
70. Sandberg R, Winberg G, Bränden CI, Kaske A, Ernberg I, Cöster J. Capturing whole-genome characteristics in short sequences using a naïve Bayesian classifier. Genome Res. 2001;11:1404-9.
71. Boisvert S, Raymond F, Godzaridis E, Laviolette F, Corbeil J. Ray Meta: scalable de novo metagenome assembly and profiling. Genome Biol. 2012;13:R122.
72. Langmead B, Salzberg SL. Fast gapped-read alignment with Bowtie 2. Nat Methods. 2012;9:357-9.
73. Quince C, Walker AW, Simpson JT, Loman NJ, Segata N. Shotgun metagenomics, from sampling to analysis. Nat Biotechnol. 2017;35:833-44.
74. Kurtz S, Phillippy A, Delcher AL, Smoot M, Shumway M, Antonescu C, et al. Versatile and open software for comparing large genomes. Genome Biol. 2004;5:R12.
75. Seemann T. Prokka: rapid prokaryotic genome annotation. Bioinformatics. 2014;30:2068-9.
76. Tatusov RL, Galperin MY, Natale DA, Koonin EV. The COG database: a tool for genome-scale analysis of protein functions and evolution. Nucleic Acids Res. 2000;28:33-6.
77. Darling AE, Jospin G, Lowe E, Matsen FA 4th, Bik HM, Eisen JA. PhyloSift: phylogenetic analysis of genomes and metagenomes. PeerJ. 2014;2:e243.
78. Wu S, Zhu Z, Fu L, Niu B, Li W. WebMGA: a customizable web server for fast metagenomic sequence analysis. BMC Genomics. 2011;12:444.
79. Andrews S. FastQC: a quality control tool for high throughput sequence data. 2010. Available from: http://www.bioinformatics.babraham.ac.uk/projects/fastqc/
80. Martin M. Cutadapt removes adapter sequences from high-throughput sequencing reads. EMBnet. J. 2011;17:10-2.
81. Bankevich A, Nurk S, Antipov D, Gurevich A, Dvorkin M, Kulikov AS, et al. SPAdes: a new genome assembly algorithm and its applications to single-cell sequencing. J Comput Biol. 2012;19:455-77.
82. Gurevich A, Saveliev V, Vyahhi N, Tesler G. QUAST: quality assessment tool for genome assemblies. Bioinformatics. 2013;29:1072-5.
83. van d WS, Colbert SC, Varoquaux G. The NumPy array: a structure for efficient numerical computation. Comput Sci Eng. 2011;13:22-30.
84. Hunter JD. Matplotlib: a 2D graphics environment. Comput Sci Eng. 2007;9:90-5.
85. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215:403-10.
86. Witten DM. Classification and clustering of sequencing data using a Poisson model. Ann Appl Stat. 2011;5:2493-518.
87. Buchfink B, Xie C, Huson DH. Fast and sensitive protein alignment using DIAMOND. Nat Methods. 2015;12:59-60.
88. van Dongen S, Abreu-Goodger C. Using MCL to extract clusters from networks. Methods Mol Biol. 2012;804:281-95.
89. Hyatt D, Chen G-L, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics. 2010;11:119.
90. Eddy SR. Accelerated profile HMM searches. PLoS Comput Biol. 2011;7:e1002195.
91. Campbell JH, O'Donoghue P, Campbell AG, Schwientek P, Sczyrba A, Woyke T, et al. UGA is an additional glycine codon in uncultured SR1 bacteria from the human microbiota. Proc Natl Acad Sci USA. 2013;110:5540-5.
92. Li H, Handsaker B, Wysoker A, Fennell T, Ruan J, Homer N, et al. The sequence alignment/map format and SAMtools. Bioinformatics. 2009;25:2078-9.
93. McKinney W, et al. Data structures for statistical computing in python. In: van der Voort S, Millman J, editors. Proceedings of the 9th Python in Science Conference; 2010. p. 51-6.
94. Waskom M, Botvinnik O, Hobson P, Warmenhoven J, Cole JB, Halchenko Y, et al. Seaborn: statistical data visualization. Seaborn: Statistical Data Visualization Seaborn 0 5, vol. 1; 2014.
95. Seemann T. Barrnap: rapid ribosomal RNA prediction. 2015 [cited 2016 Jul 21]. Available from: https://github.com/tseemann/barrnap
96. Pruesse E, Peplies J, Glöckner FO. SINA: accurate high-throughput multiple sequence alignment of ribosomal RNA genes. Bioinformatics. 2012;28:1823-9.
97. BLASTN: Standard Nucleotide BLAST. [cited 2017 Apr 21]. Available from: https://blast.ncbi.nlm.nih.gov/Blast.cgi?PAGE-TYPE=BlastSearch