Browse > Article
http://dx.doi.org/10.5808/GI.2013.11.3.102

Analytical Tools and Databases for Metagenomics in the Next-Generation Sequencing Era  

Kim, Mincheol (School of Biological Sciences & Institute of Bioinformatics (BIOMAX), Seoul National University)
Lee, Ki-Hyun (School of Biological Sciences & Institute of Bioinformatics (BIOMAX), Seoul National University)
Yoon, Seok-Whan (School of Biological Sciences & Institute of Bioinformatics (BIOMAX), Seoul National University)
Kim, Bong-Soo (Chunlab Inc., Seoul National University)
Chun, Jongsik (School of Biological Sciences & Institute of Bioinformatics (BIOMAX), Seoul National University)
Yi, Hana (Department of Environmental Health, Korea University)
Publication Information
Genomics & Informatics / v.11, no.3, 2013 , pp. 102-113 More about this Journal
Abstract
Metagenomics has become one of the indispensable tools in microbial ecology for the last few decades, and a new revolution in metagenomic studies is now about to begin, with the help of recent advances of sequencing techniques. The massive data production and substantial cost reduction in next-generation sequencing have led to the rapid growth of metagenomic research both quantitatively and qualitatively. It is evident that metagenomics will be a standard tool for studying the diversity and function of microbes in the near future, as fingerprinting methods did previously. As the speed of data accumulation is accelerating, bioinformatic tools and associated databases for handling those datasets have become more urgent and necessary. To facilitate the bioinformatics analysis of metagenomic data, we review some recent tools and databases that are used widely in this field and give insights into the current challenges and future of metagenomics from a bioinformatics perspective.
Keywords
computational biology; high-throughput nucleotide sequencing; metagenomics;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
연도 인용수 순위
1 Gianoulis TA, Raes J, Patel PV, Bjornson R, Korbel JO, Letunic I, et al. Quantifying environmental adaptation of metabolic pathways in metagenomics. Proc Natl Acad Sci U S A 2009;106:1374-1379.   DOI
2 Peng Y, Leung HC, Yiu SM, Chin FY. Meta-IDBA: a de novo assembler for metagenomic data. Bioinformatics 2011;27:i94- i101.   DOI
3 Yutin N, Suzuki MT, Teeling H, Weber M, Venter JC, Rusch DB, et al. Assessing diversity and biogeography of aerobic anoxygenic phototrophic bacteria in surface waters of the Atlantic and Pacific Oceans using the Global Ocean Sampling expedition metagenomes. Environ Microbiol 2007;9:1464- 1475.   DOI
4 Li R, Zhu H, Ruan J, Qian W, Fang X, Shi Z, et al. De novo assembly of human genomes with massively parallel short read sequencing. Genome Res 2010;20:265-272.   DOI
5 Laserson J, Jojic V, Koller D. Genovo: de novo assembly for metagenomes. J Comput Biol 2011;18:429-443.   DOI
6 Namiki T, Hachiya T, Tanaka H, Sakakibara Y. MetaVelvet: an extension of Velvet assembler to de novo metagenome assembly from short sequence reads. Nucleic Acids Res 2012;40:e155.   DOI
7 Lai B, Ding R, Li Y, Duan L, Zhu H. A de novo metagenomic assembly program for shotgun DNA reads. Bioinformatics 2012;28:1455-1462.   DOI
8 Boisvert S, Raymond F, Godzaridis E, Laviolette F, Corbeil J. Ray Meta: scalable de novo metagenome assembly and profiling. Genome Biol 2012;13:R122.   DOI
9 Koren S, Treangen TJ, Pop M. Bambus 2: scaffolding metagenomes. Bioinformatics 2011;27:2964-2971.   DOI
10 Gori F, Folino G, Jetten MS, Marchiori E. MTR: taxonomic annotation of short metagenomic reads using clustering at multiple taxonomic ranks. Bioinformatics 2011;27:196-203.   DOI
11 Gerlach W, Stoye J. Taxonomic classification of metagenomic shotgun sequences with CARMA3. Nucleic Acids Res 2011; 39:e91.   DOI
12 Monzoorul Haque M, Ghosh TS, Komanduri D, Mande SS. SOrt-ITEMS: sequence orthology based approach for improved taxonomic estimation of metagenomic sequences. Bioinformatics 2009;25:1722-1730.   DOI
13 Glass EM, Wilkening J, Wilke A, Antonopoulos D, Meyer F. Using the metagenomics RAST server (MG-RAST) for analyzing shotgun metagenomes. Cold Spring Harb Protoc 2010; 2010:pdb.prot5368.
14 Overbeek R, Begley T, Butler RM, Choudhuri JV, Chuang HY, Cohoon M, et al. The subsystems approach to genome annotation and its use in the project to annotate 1000 genomes. Nucleic Acids Res 2005;33:5691-5702.   DOI
15 Wu M, Eisen JA. A simple, fast, and accurate method of phylogenomic inference. Genome Biol 2008;9:R151.   DOI
16 Liu B, Gibbons T, Ghodsi M, Treangen T, Pop M. Accurate and fast estimation of taxonomic profiles from metagenomic shotgun sequences. BMC Genomics 2011;12 Suppl 2:S4.
17 Rosen GL, Reichenberger ER, Rosenfeld AM. NBC: the naive Bayes classification tool webserver for taxonomic classification of metagenomic reads. Bioinformatics 2011;27: 127-129.   DOI
18 Brady A, Salzberg SL. Phymm and PhymmBL: metagenomic phylogenetic classification with interpolated Markov models. Nat Methods 2009;6:673-676.   DOI
19 McHardy AC, Martin HG, Tsirigos A, Hugenholtz P, Rigoutsos I. Accurate phylogenetic classification of variable- length DNA fragments. Nat Methods 2007;4:63-72.   DOI
20 Segata N, Waldron L, Ballarini A, Narasimhan V, Jousson O, Huttenhower C. Metagenomic microbial community profiling using unique clade-specific marker genes. Nat Methods 2012;9:811-814.   DOI
21 Diaz NN, Krause L, Goesmann A, Niehaus K, Nattkemper TW. TACOA: taxonomic classification of environmental genomic fragments using a kernelized nearest neighbor approach. BMC Bioinformatics 2009;10:56.   DOI
22 Weber M, Teeling H, Huang S, Waldmann J, Kassabgy M, Fuchs BM, et al. Practical application of self-organizing maps to interrelate biodiversity and functional data in NGS-based metagenomics. ISME J 2011;5:918-928.   DOI
23 Seshadri R, Kravitz SA, Smarr L, Gilna P, Frazier M. CAMERA: a community resource for metagenomics. PLoS Biol 2007;5:e75.   DOI
24 MacDonald NJ, Parks DH, Beiko RG. Rapid identification of high-confidence taxonomic assignments for metagenomic data. Nucleic Acids Res 2012;40:e111.   DOI
25 Markowitz VM, Chen IM, Chu K, Szeto E, Palaniappan K, Grechkin Y, et al. IMG/M: the integrated metagenome data management and comparative analysis system. Nucleic Acids Res 2012;40:D123-D129.   DOI
26 Goll J, Rusch DB, Tanenbaum DM, Thiagarajan M, Li K, Methe BA, et al. METAREP: JCVI metagenomics reports: an open source tool for high-performance comparative metagenomics. Bioinformatics 2010;26:2631-2632.   DOI
27 Meyer F, Paarmann D, D'Souza M, Olson R, Glass EM, Kubal M, et al. The metagenomics RAST server: a public resource for the automatic phylogenetic and functional analysis of metagenomes. BMC Bioinformatics 2008;9:386.   DOI
28 Rho M, Tang H, Ye Y. FragGeneScan: predicting genes in short and error-prone reads. Nucleic Acids Res 2010;38:e191.   DOI
29 Noguchi H, Park J, Takagi T. MetaGene: prokaryotic gene finding from environmental genome shotgun sequences. Nucleic Acids Res 2006;34:5623-5630.   DOI
30 Noguchi H, Taniguchi T, Itoh T. MetaGeneAnnotator: detecting species-specific patterns of ribosomal binding site for precise gene prediction in anonymous prokaryotic and phage genomes. DNA Res 2008;15:387-396.   DOI
31 Hoff KJ, Lingner T, Meinicke P, Tech M. Orphelia: predicting genes in metagenomic sequencing reads. Nucleic Acids Res 2009;37:W101-W105.   DOI
32 Kelley DR, Liu B, Delcher AL, Pop M, Salzberg SL. Gene prediction with Glimmer for metagenomic sequences augmented by classification and clustering. Nucleic Acids Res 2012;40:e9.   DOI
33 Zhu W, Lomsadze A, Borodovsky M. Ab initio gene identification in metagenomic sequences. Nucleic Acids Res 2010;38:e132.   DOI
34 Prakash T, Taylor TD. Functional assignment of metagenomic data: challenges and applications. Brief Bioinform 2012;13:711-727.   DOI
35 Hayes WS, Borodovsky M. How to interpret an anonymous bacterial genome: machine learning approach to gene identification. Genome Res 1998;8:1154-1171.   DOI
36 Yada T, Nakao M, Totoki Y, Nakai K. Modeling and predicting transcriptional units of Escherichia coli genes using hidden Markov models. Bioinformatics 1999;15:987-993.   DOI
37 Nguyen MN, Ma J, Fogel GB, Rajapakse JC. Di-codon usage for classification of genes. Biosystems 2009;98:1-6.   DOI
38 Hyatt D, Chen GL, Locascio PF, Land ML, Larimer FW, Hauser LJ. Prodigal: prokaryotic gene recognition and translation initiation site identification. BMC Bioinformatics 2010; 11:119.   DOI
39 Tanenbaum DM, Goll J, Murphy S, Kumar P, Zafar N, Thiagarajan M, et al. The JCVI standard operating procedure for annotating prokaryotic metagenomic shotgun sequencing data. Stand Genomic Sci 2010;2:229-237.   DOI
40 Salzberg SL, Delcher AL, Kasif S, White O. Microbial gene identification using interpolated Markov models. Nucleic Acids Res 1998;26:544-548.   DOI
41 Tatusov RL, Fedorova ND, Jackson JD, Jacobs AR, Kiryutin B, Koonin EV, et al. The COG database: an updated version includes eukaryotes. BMC Bioinformatics 2003;4:41.   DOI
42 Powell S, Szklarczyk D, Trachana K, Roth A, Kuhn M, Muller J, et al. eggNOG v3.0: orthologous groups covering 1133 organisms at 41 different taxonomic ranges. Nucleic Acids Res 2012;40:D284-D289.   DOI
43 Punta M, Coggill PC, Eberhardt RY, Mistry J, Tate J, Boursnell C, et al. The Pfam protein families database. Nucleic Acids Res 2012;40:D290-D301.   DOI
44 Haft DH, Selengut JD, White O. The TIGRFAMs database of protein families. Nucleic Acids Res 2003;31:371-373.   DOI
45 Fuhrman JA, Steele JA, Hewson I, Schwalbach MS, Brown MV, Green JL, et al. A latitudinal diversity gradient in planktonic marine bacteria. Proc Natl Acad Sci U S A 2008; 105:7774-7778.   DOI
46 Gilles A, Meglecz E, Pech N, Ferreira S, Malausa T, Martin JF. Accuracy and quality assessment of 454 GS-FLX titanium pyrosequencing. BMC Genomics 2011;12:245.   DOI
47 Handelsman J, Rondon MR, Brady SF, Clardy J, Goodman RM. Molecular biological access to the chemistry of unknown soil microbes: a new frontier for natural products. Chem Biol 1998;5:R245-R249.   DOI
48 Beja O, Aravind L, Koonin EV, Suzuki MT, Hadd A, Nguyen LP, et al. Bacterial rhodopsin: evidence for a new type of phototrophy in the sea. Science 2000;289:1902-1906.   DOI
49 Fierer N, Leff JW, Adams BJ, Nielsen UN, Bates ST, Lauber CL, et al. Cross-biome metagenomic analyses of soil microbial communities and their functional attributes. Proc Natl Acad Sci U S A 2012;109:21390-21395.   DOI
50 Metzker ML. Sequencing technologies: the next generation. Nat Rev Genet 2010;11:31-46.   DOI
51 Teeling H, Glockner FO. Current opportunities and challenges in microbial metagenome analysis: a bioinformatic perspective. Brief Bioinform 2012;13:728-742.   DOI
52 Suenaga H. Targeted metagenomics: a high-resolution metagenomics approach for specific gene clusters in complex microbial communities. Environ Microbiol 2012;14:13-22.   DOI
53 Fox GE, Wisotzkey JD, Jurtshuk P Jr. How close is close: 16S rRNA sequence identity may not be sufficient to guarantee species identity. Int J Syst Bacteriol 1992;42:166-170.   DOI
54 Kunin V, Copeland A, Lapidus A, Mavromatis K, Hugenholtz P. A bioinformatician's guide to metagenomics. Microbiol Mol Biol Rev 2008;72:557-578.   DOI
55 Bragg L, Stone G, Imelfort M, Hugenholtz P, Tyson GW. Fast, accurate error-correction of amplicon pyrosequences using Acacia. Nat Methods 2012;9:425-426.   DOI
56 Franceschini A, Szklarczyk D, Frankild S, Kuhn M, Simonovic M, Roth A, et al. STRING v9.1: protein-protein interaction networks, with increased coverage and integration. Nucleic Acids Res 2013;41:D808-D815.   DOI
57 Eddy SR. Accelerated profile HMM searches. PLoS Comput Biol 2011;7:e1002195.   DOI
58 Meyer F, Overbeek R, Rodriguez A. FIGfams: yet another set of protein families. Nucleic Acids Res 2009;37:6643-6654.   DOI
59 Bairoch A. The ENZYME database in 2000. Nucleic Acids Res 2000;28:304-305.   DOI
60 Kanehisa M, Goto S. KEGG: kyoto encyclopedia of genes and genomes. Nucleic Acids Res 2000;28:27-30.   DOI
61 Claudel-Renard C, Chevalet C, Faraut T, Kahn D. Enzymespecific profiles for genome annotation: PRIAM. Nucleic Acids Res 2003;31:6633-6639.   DOI
62 Caspi R, Altman T, Dreher K, Fulcher CA, Subhraveti P, Keseler IM, et al. The MetaCyc database of metabolic pathways and enzymes and the BioCyc collection of pathway/ genome databases. Nucleic Acids Res 2012;40:D742- D753.   DOI
63 Liu B, Pop M. MetaPath: identifying differentially abundant metabolic pathways in metagenomic datasets. BMC Proc 2011;5 Suppl 2:S9.
64 Parks DH, Beiko RG. Identifying biologically relevant differences between metagenomic communities. Bioinformatics 2010;26:715-721.   DOI
65 Yilmaz P, Kottmann R, Field D, Knight R, Cole JR, Amaral-Zettler L, et al. Minimum information about a marker gene sequence (MIMARKS) and minimum information about any (x) sequence (MIxS) specifications. Nat Biotechnol 2011;29:415-420.   DOI
66 Stepanauskas R. Single cell genomics: an individual look at microbes. Curr Opin Microbiol 2012;15:613-620.   DOI
67 Baran Y, Halperin E. Joint analysis of multiple metagenomic samples. PLoS Comput Biol 2012;8:e1002373.   DOI
68 Rosen MJ, Callahan BJ, Fisher DS, Holmes SP. Denoising PCR-amplified metagenome data. BMC Bioinformatics 2012; 13:283.   DOI
69 Quince C, Lanzen A, Davenport RJ, Turnbaugh PJ. Removing noise from pyrosequenced amplicons. BMC Bioinformatics 2011;12:38.   DOI
70 Reeder J, Knight R. Rapidly denoising pyrosequencing amplicon reads by exploiting rank-abundance distributions. Nat Methods 2010;7:668-669.
71 Edgar RC, Haas BJ, Clemente JC, Quince C, Knight R. UCHIME improves sensitivity and speed of chimera detection. Bioinformatics 2011;27:2194-2200.   DOI
72 Haas BJ, Gevers D, Earl AM, Feldgarden M, Ward DV, Giannoukos G, et al. Chimeric 16S rRNA sequence formation and detection in Sanger and 454-pyrosequenced PCR amplicons. Genome Res 2011;21:494-504.   DOI
73 Wright ES, Yilmaz LS, Noguera DR. DECIPHER, a searchbased approach to chimera identification for 16S rRNA sequences. Appl Environ Microbiol 2012;78:717-725.   DOI
74 Edgar RC. Search and clustering orders of magnitude faster than BLAST. Bioinformatics 2010;26:2460-2461.   DOI
75 Fu L, Niu B, Zhu Z, Wu S, Li W. CD-HIT: accelerated for clustering the next-generation sequencing data. Bioinformatics 2012;28:3150-3152.   DOI
76 Cai Y, Sun Y. ESPRIT-Tree: hierarchical clustering analysis of millions of 16S rRNA pyrosequences in quasilinear computational time. Nucleic Acids Res 2011;39:e95.   DOI
77 DeSantis TZ, Hugenholtz P, Larsen N, Rojas M, Brodie EL, Keller K, et al. Greengenes, a chimera-checked 16S rRNA gene database and workbench compatible with ARB. Appl Environ Microbiol 2006;72:5069-5072.   DOI
78 Lee JH, Yi H, Jeon YS, Won S, Chun J. TBC: a clustering algorithm based on prokaryotic taxonomy. J Microbiol 2012;50: 181-185.   DOI
79 Quast C, Pruesse E, Yilmaz P, Gerken J, Schweer T, Yarza P, et al. The SILVA ribosomal RNA gene database project: improved data processing and web-based tools. Nucleic Acids Res 2013;41:D590-D596.   DOI
80 Cole JR, Wang Q, Cardenas E, Fish J, Chai B, Farris RJ, et al. The Ribosomal Database Project: improved alignments and new tools for rRNA analysis. Nucleic Acids Res 2009;37: D141-D145.   DOI
81 Kim OS, Cho YJ, Lee K, Yoon SH, Kim M, Na H, et al. Introducing EzTaxon-e: a prokaryotic 16S rRNA gene sequence database with phylotypes that represent uncultured species. Int J Syst Evol Microbiol 2012;62(Pt 3):716-721.   DOI
82 Abarenkov K, Henrik Nilsson R, Larsson KH, Alexander IJ, Eberhardt U, Erland S, et al. The UNITE database for molecular identification of fungi: recent updates and future perspectives. New Phytol 2010;186:281-285.   DOI
83 Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, et al. Introducing mothur: open-source, platform- independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol 2009;75:7537-7541.   DOI
84 Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods 2010;7:335-336.   DOI
85 Hugenholtzt P, Huber T. Chimeric 16S rDNA sequences of diverse origin are accumulating in the public databases. Int J Syst Evol Microbiol 2003;53(Pt 1):289-293.   DOI
86 Huson DH, Mitra S, Ruscheweyh HJ, Weber N, Schuster SC. Integrative analysis of environmental sequences using MEGAN4. Genome Res 2011;21:1552-1560.   DOI
87 Huse SM, Welch DM, Morrison HG, Sogin ML. Ironing out the wrinkles in the rare biosphere through improved OTU clustering. Environ Microbiol 2010;12:1889-1898.   DOI
88 Bradley RD, Hillis DM. Recombinant DNA sequences generated by PCR amplification. Mol Biol Evol 1997;14:592-593.   DOI
89 DeSantis TZ Jr, Hugenholtz P, Keller K, Brodie EL, Larsen N, Piceno YM, et al. NAST: a multiple sequence alignment server for comparative analysis of 16S rRNA genes. Nucleic Acids Res 2006;34:W394-W399.
90 Schloss PD, Gevers D, Westcott SL. Reducing the effects of PCR amplification and sequencing artifacts on 16S rRNAbased studies. PLoS One 2011;6:e27310.   DOI
91 Thompson JD, Higgins DG, Gibson TJ. CLUSTAL W: improving the sensitivity of progressive multiple sequence alignment through sequence weighting, position-specific gap penalties and weight matrix choice. Nucleic Acids Res 1994;22:4673-4680.   DOI
92 Schloss PD. The effects of alignment quality, distance calculation method, sequence filtering, and region on the analysis of 16S rRNA gene-based studies. PLoS Comput Biol 2010; 6:e1000844.   DOI
93 Schloss PD. Secondary structure improves OTU assignments of 16S rRNA gene sequences. ISME J 2013;7:457-460.   DOI
94 Hartmann M, Howes CG, VanInsberghe D, Yu H, Bachar D, Christen R, et al. Significant and persistent impact of timber harvesting on soil microbial communities in Northern coniferous forests. ISME J 2012;6:2199-2218.   DOI
95 Pruesse E, Peplies J, Glockner FO. SINA: accurate highthroughput multiple sequence alignment of ribosomal RNA genes. Bioinformatics 2012;28:1823-1829.   DOI
96 Nawrocki EP, Kolbe DL, Eddy SR. Infernal 1.0: inference of RNA alignments. Bioinformatics 2009;25:1335-1337.   DOI
97 Kumar S, Carlsen T, Mevik BH, Enger P, Blaalid R, Shalchian-Tabrizi K, et al. CLOTU: an online pipeline for processing and clustering of 454 amplicon reads into OTUs followed by taxonomic annotation. BMC Bioinformatics 2011; 12:182.   DOI
98 Sul WJ, Cole JR, Jesus EC, Wang Q, Farris RJ, Fish JA, et al. Bacterial community comparisons by taxonomy-supervised analysis independent of sequence alignment and clustering. Proc Natl Acad Sci U S A 2011;108:14637-14642.   DOI
99 Soergel DA, Dey N, Knight R, Brenner SE. Selection of primers for optimal taxonomic classification of environmental 16S rRNA gene sequences. ISME J 2012;6:1440-1444.   DOI
100 Lan Y, Wang Q, Cole JR, Rosen GL. Using the RDP classifier to predict taxonomic novelty and reduce the search space for finding novel organisms. PLoS One 2012;7:e32491.   DOI
101 Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol 1990;215:403-410.
102 Huson DH, Auch AF, Qi J, Schuster SC. MEGAN analysis of metagenomic data. Genome Res 2007;17:377-386.   DOI
103 Matsen FA, Kodner RB, Armbrust EV. pplacer: linear time maximum-likelihood and Bayesian phylogenetic placement of sequences onto a fixed reference tree. BMC Bioinformatics 2010;11:538.   DOI
104 Clemente JC, Jansson J, Valiente G. Flexible taxonomic assignment of ambiguous sequencing reads. BMC Bioinformatics 2011;12:8.   DOI
105 Wang Q, Garrity GM, Tiedje JM, Cole JR. Naive Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol 2007;73: 5261-5267.   DOI
106 Berger SA, Krompass D, Stamatakis A. Performance, accuracy, and Web server for evolutionary placement of short sequence reads under maximum likelihood. Syst Biol 2011; 60:291-302.   DOI
107 Mirarab S, Nguyen N, Warnow T. SEPP: SATe-enabled phylogenetic placement. Pac Symp Biocomput 2012:247-258.
108 Wu M, Scott AJ. Phylogenomic analysis of bacterial and archaeal sequences with AMPHORA2. Bioinformatics 2012;28: 1033-1034.   DOI
109 Vergin KL, Urbach E, Stein JL, DeLong EF, Lanoil BD, Giovannoni SJ. Screening of a fosmid library of marine environmental genomic DNA fragments reveals four clones related to members of the order Planctomycetales. Appl Environ Microbiol 1998;64:3075-3078.