Deciphering the human microbiome using next-generation sequencing data and bioinformatics approaches.

The human microbiome is one of the key factors affecting the host immune system and metabolic functions that are not encoded in the human genome. Culture-independent analysis of the human microbiome using metagenomics approach allows us to investigate the compositions and functions of the human microbiome. Computational methods analyze the microbial community by using specific marker genes or by using shotgun sequencing of the entire microbial community. Taxonomy profiling is conducted by using the reference sequences or by de novo clustering of the specific region of sequences. Functional profiling, which is mainly based on the sequence similarity, is more challenging since about half of ORFs predicted in the metagenomic data could not find homology with known protein families. This review examines computational methods that are valuable for the analysis of human microbiome, and highlights the results of several large-scale human microbiome studies. It is becoming increasingly evident that dysbiosis of the gut microbiome is strongly associated with the development of immune disorder and metabolic dysfunction.

[1]  S. Massart,et al.  Impact of diet in shaping gut microbiota revealed by a comparative study in children from Europe and rural Africa , 2010, Proceedings of the National Academy of Sciences.

[2]  J. Izard,et al.  The Human Oral Microbiome , 2010, Journal of bacteriology.

[3]  Rob Knight,et al.  UniFrac – An online tool for comparing microbial community diversity in a phylogenetic context , 2006, BMC Bioinformatics.

[4]  James R. Cole,et al.  Ribosomal Database Project: data and tools for high throughput rRNA analysis , 2013, Nucleic Acids Res..

[5]  Kang Ning,et al.  Parallel-META 2.0: Enhanced Metagenomic Data Analysis with Functional Annotation, High Performance Computing and Advanced Visualization , 2014, PloS one.

[6]  Pelin Yilmaz,et al.  The SILVA ribosomal RNA gene database project: improved data processing and web-based tools , 2012, Nucleic Acids Res..

[7]  F. Bushman,et al.  Linking Long-Term Dietary Patterns with Gut Microbial Enterotypes , 2011, Science.

[8]  S. Beatson,et al.  Outsmarting Outbreaks , 2012, Science.

[9]  Mihai Pop,et al.  ARDB—Antibiotic Resistance Genes Database , 2008, Nucleic Acids Res..

[10]  Cynthia L Sears,et al.  A human colonic commensal promotes colon tumorigenesis via activation of T helper type 17 T cell responses , 2009, Nature Medicine.

[11]  Susumu Goto,et al.  KEGG: Kyoto Encyclopedia of Genes and Genomes , 2000, Nucleic Acids Res..

[12]  Julian Parkhill,et al.  Rapid whole-genome sequencing for investigation of a neonatal MRSA outbreak. , 2012, The New England journal of medicine.

[13]  P. Turnbaugh,et al.  Microbial ecology: Human gut microbes associated with obesity , 2006, Nature.

[14]  David R. Kelley,et al.  Gene prediction with Glimmer for metagenomic sequences augmented by classification and clustering , 2011, Nucleic acids research.

[15]  P. Bork,et al.  A human gut microbial gene catalogue established by metagenomic sequencing , 2010, Nature.

[16]  M. Borodovsky,et al.  Ab initio gene identification in metagenomic sequences , 2010, Nucleic acids research.

[17]  Sean R. Eddy,et al.  Accelerated Profile HMM Searches , 2011, PLoS Comput. Biol..

[18]  Robert C. Edgar,et al.  BIOINFORMATICS APPLICATIONS NOTE , 2001 .

[19]  Bernard Henrissat,et al.  The abundance and variety of carbohydrate-active enzymes in the human gut microbiota , 2013, Nature Reviews Microbiology.

[20]  K. Turner,et al.  Metatranscriptomics of the Human Oral Microbiome during Health and Disease , 2014, mBio.

[21]  Ting Chen,et al.  Clustering 16S rRNA for OTU prediction: a method of unsupervised Bayesian clustering , 2011, Bioinform..

[22]  D. Fouts.  Phage_Finder: Automated identification and classification of prophage regions in complete bacterial genome sequences , 2006, Nucleic acids research.

[23]  Haixu Tang,et al.  CRISPR-Cas systems target a diverse collection of invasive mobile genetic elements in human microbiomes , 2013, Genome Biology.

[24]  J. Koenderink.  Q… , 2014, Les noms officiels des communes de Wallonie, de Bruxelles-Capitale et de la communaute germanophone.

[25]  Carsten Damm,et al.  Score-based prediction of genomic islands in prokaryotic genomes using hidden Markov models , 2006, BMC Bioinformatics.

[26]  Huanming Yang,et al.  De novo assembly of human genomes with massively parallel short read sequencing. , 2010, Genome research.

[27]  Jian Wang,et al.  SOAPdenovo2: an empirically improved memory-efficient short-read de novo assembler , 2012, GigaScience.

[28]  Sergey Koren,et al.  Bambus 2: scaffolding metagenomes , 2011, Bioinform..

[29]  Thomas Ludwig,et al.  RAxML-III: a fast program for maximum likelihood-based inference of large phylogenetic trees , 2005, Bioinform..

[30]  Brian C. Thomas,et al.  Time series community genomics analysis reveals rapid shifts in bacterial species, strains, and phage during infant gut colonization , 2013, Genome research.

[31]  Steven J. M. Jones,et al.  IslandPath: aiding detection of genomic islands in prokaryotes , 2003, Bioinform..

[32]  Pavel A Pevzner,et al.  How to apply de Bruijn graphs to genome assembly. , 2011, Nature biotechnology.

[33]  Ulrich Dobrindt,et al.  Genomic islands in pathogenic and environmental microorganisms , 2004, Nature Reviews Microbiology.

[34]  Katherine H. Huang,et al.  A framework for human microbiome research , 2012, Nature.

[35]  William A. Walters,et al.  QIIME allows analysis of high-throughput community sequencing data , 2010, Nature Methods.

[36]  John C. Wooley,et al.  Expansion of the Protein Repertoire in Newly Explored Environments: Human Gut Microbiome Specific Protein Families , 2010, PLoS Comput. Biol..

[37]  J. Montoya-Burgos,et al.  Optimization of de novo transcriptome assembly from next-generation sequencing data. , 2010, Genome research.

[38]  L. T. Angenent,et al.  Succession of microbial consortia in the developing infant gut microbiome , 2010, Proceedings of the National Academy of Sciences.

[39]  Haixu Tang,et al.  Diverse CRISPRs Evolving in Human Microbiomes , 2012, PLoS genetics.

[40]  J. Handelsman,et al.  Metagenomics: genomic analysis of microbial communities. , 2004, Annual review of genetics.

[41]  Mihai Pop,et al.  Genome assembly reborn: recent computational challenges , 2009, Briefings Bioinform..

[42]  P. Bork,et al.  Enterotypes of the human gut microbiome , 2011, Nature.

[43]  J. Petrosino,et al.  The Gut Microbiome Modulates Colon Tumorigenesis , 2013, mBio.

[44]  Robert C. Edgar,et al.  MUSCLE: multiple sequence alignment with high accuracy and high throughput. , 2004, Nucleic acids research.

[45]  R. Knight,et al.  Delivery mode shapes the acquisition and structure of the initial microbiota across multiple body habitats in newborns , 2010, Proceedings of the National Academy of Sciences.

[46]  J. Hacker,et al.  Pathogenicity islands and the evolution of microbes. , 2000, Annual review of microbiology.

[47]  William G. Mckendree,et al.  ESPRIT: estimating species richness using large collections of 16S rRNA pyrosequences , 2009, Nucleic acids research.

[48]  Fiona S. L. Brinkman,et al.  Detecting genomic islands using bioinformatics approaches , 2010, Nature Reviews Microbiology.

[49]  Mario Recker,et al.  Predicting the virulence of MRSA from its genome sequence , 2014, Genome research.

[50]  Xin Chen,et al.  dbCAN: a web resource for automated carbohydrate-active enzyme annotation , 2012, Nucleic Acids Res..

[51]  Yuzhen Ye,et al.  A Parsimony Approach to Biological Pathway Reconstruction/Inference for Genomes and Metagenomes , 2009, PLoS Comput. Biol..

[52]  R. Durbin,et al.  Efficient de novo assembly of large genomes using compressed data structures. , 2012, Genome research.

[53]  Bernard Henrissat,et al.  Metabolic Reconstruction for Metagenomic Data and Its Application to the Human Microbiome , 2012, PLoS Comput. Biol..

[54]  S. Salzberg,et al.  Improved microbial gene identification with GLIMMER. , 1999, Nucleic acids research.

[55]  Fiona S. L. Brinkman,et al.  Evaluation of genomic island predictors using a comparative genomics approach , 2008, BMC Bioinformatics.

[56]  K. Kinzler,et al.  Cancer genes and the pathways they control , 2004, Nature Medicine.

[57]  Haixu Tang,et al.  FragGeneScan: predicting genes in short and error-prone reads , 2010, Nucleic acids research.

[58]  G. Getz,et al.  PathSeq: software to identify or discover microbes by deep sequencing of human tissue , 2011, Nature Biotechnology.

[59]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[60]  Yasubumi Sakakibara,et al.  MetaVelvet: an extension of Velvet assembler to de novo metagenome assembly from short sequence reads , 2012, Nucleic acids research.

[61]  Katherine H. Huang,et al.  Structure, Function and Diversity of the Healthy Human Microbiome , 2012, Nature.

[62]  J. Burton,et al.  Rapid Pneumococcal Evolution in Response to Clinical Interventions , 2011, Science.

[63]  M. Blaser,et al.  The human microbiome: at the interface of health and disease , 2012, Nature Reviews Genetics.

[64]  Jun Yu,et al.  VFDB: a reference database for bacterial virulence factors , 2004, Nucleic Acids Res..

[65]  Jian Xu,et al.  Meta-Storms: efficient search for similar microbial communities based on a novel indexing scheme and similarity score for metagenomic data , 2012, Bioinform..

[66]  Arthur Brady,et al.  MetaRef: a pan-genomic database for comparative and community microbial genomics , 2013, Nucleic Acids Res..

[67]  Paolo Fontana,et al.  Bioinformatic approaches for functional annotation and pathway inference in metagenomics data , 2012, Briefings Bioinform..

[68]  Miss A.O. Penney.  (b) , 1974, The New Yale Book of Quotations.

[69]  I-Min A. Chen,et al.  IMG 4 version of the integrated microbial genomes comparative analysis system , 2013, Nucleic Acids Res..

[70]  P. Pevzner,et al.  An Eulerian path approach to DNA fragment assembly , 2001, Proceedings of the National Academy of Sciences of the United States of America.

[71]  F. Bäckhed,et al.  Defining a healthy human gut microbiome: current concepts, future directions, and clinical applications. , 2012, Cell host & microbe.

[72]  Fabian Schreiber,et al.  CoMet—a web server for comparative functional profiling of metagenomes , 2011, Nucleic Acids Res..

[73]  Adam Godzik,et al.  Cd-hit: a fast program for clustering and comparing large sets of protein or nucleotide sequences , 2006, Bioinform..

[74]  F. Bushman,et al.  The human gut virome: inter-individual variation and dynamic response to diet. , 2011, Genome research.

[75]  Steven Salzberg,et al.  Clustering metagenomic sequences with interpolated Markov models , 2010, BMC Bioinformatics.

[76]  F. Raymond,et al.  which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Ray Meta: scalable de novo metagenome assembly and profiling , 2012 .

[77]  E. Kimes,et al.  Evaluation of Vancomycin TDM Strategies: Prediction and Prevention of Kidney Injuries Based on Vancomycin TDM Results , 2023, Journal of Korean medical science.

[78]  Siu-Ming Yiu,et al.  Meta-IDBA: a de Novo assembler for metagenomic data , 2011, Bioinform..

[79]  Steven Salzberg,et al.  GAGE-B: an evaluation of genome assemblers for bacterial organisms , 2013, Bioinform..

[80]  Gabriel Núñez,et al.  Control of pathogens and pathobionts by the gut microbiota , 2013, Nature Immunology.

[81]  Eoin L. Brodie,et al.  Greengenes, a Chimera-Checked 16S rRNA Gene Database and Workbench Compatible with ARB , 2006, Applied and Environmental Microbiology.

[82]  Forest Rohwer,et al.  Viruses in the fecal microbiota of monozygotic twins and their mothers , 2010, Nature.

[83]  Daphne Koller,et al.  Genovo: De Novo Assembly for Metagenomes , 2010, RECOMB.

[84]  E. Cheek,et al.  Genome signature-based dissection of human gut metagenomes to extract subliminal viral sequences , 2013, Nature Communications.

[85]  R. Novick,et al.  Phage-Mediated Intergeneric Transfer of Toxin Genes , 2009, Science.

[86]  S. Salzberg,et al.  Phymm and PhymmBL: Metagenomic Phylogenetic Classification with Interpolated Markov Models , 2009, Nature Methods.

[87]  Alexander F. Auch,et al.  MEGAN analysis of metagenomic data. , 2007, Genome research.

[88]  Andreas Wilke,et al.  phylogenetic and functional analysis of metagenomes , 2022 .

[89]  E. Birney,et al.  Velvet: algorithms for de novo short read assembly using de Bruijn graphs. , 2008, Genome research.

[90]  V. Tremaroli,et al.  Functional interactions between the gut microbiota and host metabolism , 2012, Nature.

[91]  Claudio Donati,et al.  Genome sequencing of disease and carriage isolates of nontypeable Haemophilus influenzae identifies discrete population structure , 2014, Proceedings of the National Academy of Sciences.

[92]  Mark Johnson,et al.  NCBI BLAST: a better web interface , 2008, Nucleic Acids Res..

[93]  Joshua LaBaer,et al.  Reduced Incidence of Prevotella and Other Fermenters in Intestinal Microflora of Autistic Children , 2013, PloS one.

[94]  Hiroshi Mori,et al.  Comparative Metagenomics Revealed Commonly Enriched Gene Sets in Human Gut Microbiomes , 2007, DNA research : an international journal for rapid publication of reports on genes and genomes.