Advertisement

Microbiome: Current Status and Future Applications

  • Rafael G. Ramos-Jimenez
  • Michael J. MorowitzEmail author
Chapter
Part of the Success in Academic Surgery book series (SIAS)

Abstract

Humans are home to approximately 40 trillion microbes (Sender et al., PLoS Biol 14:e1002533, 2016). Most of these microbes inhabit our gastrointestinal (GI) tract, where they extract nutrients from our diet, synthesize vitamins, and educate our immune systems. Before the 1980s, our ability to study most bacteria was hampered by our inability to culture them. Three scientific advances allowed microbial studies to become culture-independent: high-throughput next-generation sequencing (NGS), the use of 16S ribosomal ribonucleic acid (rRNA) as a phylogenetic marker, and the development of bioinformatic methods to analyze and interpret large amounts of sequencing data. In this chapter, we describe the conduct of microbiome experiments from sample collection to data analysis and interpretation. We also discuss the clinical applications of microbiome science and the future of microbiome research.

Keywords

Human microbiome Academic surgery Operational taxonomic units (OTUs) Dysbiosis 

References

  1. 1.
    Sender R, Fuchs S, Milo R. Revised estimate for the number of human and bacterial cells in the body. PLoS Biol. 2016;14:e1002533.PubMedPubMedCentralCrossRefGoogle Scholar
  2. 2.
    NIH T & Working HMP. The NIH Human Microbiome Project. Genome Res. 2009;19:2317–23.CrossRefGoogle Scholar
  3. 3.
    Gill SR, et al. Metagenomic analysis of the human distal gut microbiome. Science (80). 2006;312:1355–9.CrossRefGoogle Scholar
  4. 4.
    Integrative HMP Research Network Consortium. T The integrative human microbiome project: dynamic analysis of microbiome-host omics profiles during periods of human health and disease corresponding author. Cell Host Microbe. 2014;16:276–89.CrossRefGoogle Scholar
  5. 5.
    Cani PD. Gut microbiota-at the intersection of everything? Nat Rev Gastroenterol Hepatol. 2017;14:321–2.PubMedCrossRefPubMedCentralGoogle Scholar
  6. 6.
    Morowitz MJ, et al. The human microbiome and surgical disease. Ann Surg. 2011;253:1094–101.PubMedPubMedCentralCrossRefGoogle Scholar
  7. 7.
    Meng M, Klingensmith NJ, Coopersmith CM. New insights into the gut as the driver of critical illness and organ failure. Curr Opin Crit Care. 2017;23:143–8.PubMedPubMedCentralCrossRefGoogle Scholar
  8. 8.
    Wiersinga WJ. The gut microbiome takes center stage in critical care. Curr Opin Crit Care. 2017;23:140–2.PubMedCrossRefPubMedCentralGoogle Scholar
  9. 9.
    Morgan XC, Huttenhower C. Human microbiome analysis. PLoS Comput Biol. 2012;8  https://doi.org/10.1371/journal.pcbi.1002808.PubMedPubMedCentralCrossRefGoogle Scholar
  10. 10.
    Knight R, et al. Best practices for analysing microbiomes. Nat Rev Microbiol. 2018;16:410–22.PubMedCrossRefPubMedCentralGoogle Scholar
  11. 11.
    Lloyd-Price J, Abu-Ali G, Huttenhower C. The healthy human microbiome. Genome Med. 2016;8:15.CrossRefGoogle Scholar
  12. 12.
    Segata N, et al. Metagenomic biomarker discovery and explanation. Genome Biol. 2011;12:R20.CrossRefGoogle Scholar
  13. 13.
    Postler TS, Ghosh S. Understanding the holobiont: how microbial metabolites affect human health and shape the immune system. Cell Metab. 2017;26:110–30.PubMedPubMedCentralCrossRefGoogle Scholar
  14. 14.
    Yatsunenko T, et al. Human gut microbiome viewed across age and geography. Nature. 2012;486:222–7.PubMedPubMedCentralCrossRefGoogle Scholar
  15. 15.
    Ley RE, Peterson DA, Gordon JI. Ecological and evolutionary forces shaping microbial diversity in the human intestine. Cell. 2006;124:837–48.PubMedCrossRefPubMedCentralGoogle Scholar
  16. 16.
    Klassen JL. Defining microbiome function. Nat Microbiol. 2018;3:864–9.PubMedCrossRefPubMedCentralGoogle Scholar
  17. 17.
    Qin J, et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature. 2010;464:59–65.PubMedPubMedCentralCrossRefGoogle Scholar
  18. 18.
    Huttenhower C, et al. Structure, function and diversity of the healthy human microbiome. Nature. 2012;486:207–14.CrossRefGoogle Scholar
  19. 19.
    Turnbaugh PJ, et al. A core gut microbiome in obese and lean twins. Nature. 2009;457:480–4.CrossRefGoogle Scholar
  20. 20.
    Kostic AD, et al. The dynamics of the human infant gut microbiome in development and in progression toward type 1 diabetes. Cell Host Microbe. 2015;17:260–73.PubMedPubMedCentralCrossRefGoogle Scholar
  21. 21.
    Xu Z, Malmer D, Langille MGI, Way SF, Knight R. Which is more important for classifying microbial communities: who’s there or what they can do? ISME J. 2014;8:2357–9.PubMedPubMedCentralCrossRefGoogle Scholar
  22. 22.
    Martiny JBH, Jones SE, Lennon JT, Martiny AC. Microbiomes in light of traits: a phylogenetic perspective. Science (80). 2015;350:aac9323.CrossRefGoogle Scholar
  23. 23.
    Thaiss CA, Zmora N, Levy M, Elinav E. The microbiome and innate immunity. Nature. 2016;535:65–74.PubMedCrossRefPubMedCentralGoogle Scholar
  24. 24.
    McClave SA, Lowen CC, Martindale RG. The 2016 ESPEN Arvid Wretlind lecture: the gut in stress. Clin Nutr. 2017;37:19–36.PubMedCrossRefPubMedCentralGoogle Scholar
  25. 25.
    Krezalek MA, Defazio J, Zaborina O, Zaborin A, Alverdy JC. The shift of an intestinal ‘Microbiome’ to a ‘Pathobiome’ governs the course and outcome of sepsis following surgical injury. Shock. 2016;45:475–82.PubMedPubMedCentralCrossRefGoogle Scholar
  26. 26.
    Guyton K, Alverdy JC. The gut microbiota and gastrointestinal surgery. Nat Rev Gastroenterol Hepatol. 2016;14:43–54.PubMedCrossRefPubMedCentralGoogle Scholar
  27. 27.
    Lee SM, et al. Bacterial colonization factors control specificity and stability of the gut microbiota. Nature. 2013;501:426–9.PubMedPubMedCentralCrossRefGoogle Scholar
  28. 28.
    Degruttola AK, Low D, Mizoguchi A, Mizoguchi E. Current understanding of dysbiosis in disease in human and animal models. Inflamm Bowel Dis. 2016;22:1137–50.PubMedPubMedCentralCrossRefGoogle Scholar
  29. 29.
    Da Silva HE, et al. Nonalcoholic fatty liver disease is associated with dysbiosis independent of body mass index and insulin resistance. Sci Rep. 2018;8:1466.PubMedPubMedCentralCrossRefGoogle Scholar
  30. 30.
    Wolff NS, Hugenholtz F, Wiersinga WJ. The emerging role of the microbiota in the ICU. Crit Care. 2018;22:78.PubMedPubMedCentralCrossRefGoogle Scholar
  31. 31.
    Bardou M, Quenot J-P, Barkun A. Stress-related mucosal disease in the critically ill patient. Nat Rev Gastroenterol Hepatol. 2015;12:98–107.PubMedCrossRefPubMedCentralGoogle Scholar
  32. 32.
    Magnúsdóttir S, Thiele I. Modeling metabolism of the human gut microbiome. Curr Opin Biotechnol. 2018;51:90–6.PubMedCrossRefPubMedCentralGoogle Scholar
  33. 33.
    Bashiardes S, Zilberman-Schapira G, Elinav E. Use of metatranscriptomics in microbiome research. Bioinform Biol Insights. 2016;10:19–25.PubMedPubMedCentralCrossRefGoogle Scholar
  34. 34.
    Gray MW, Sankoff D, Cedergren R. On the evolutionary descent of organisms and organelles: a global phylogeny based on a highly conserved structural case in small subunit ribosomal RNA. Nucleic Acids Res. 1984;12:5837–52.PubMedPubMedCentralCrossRefGoogle Scholar
  35. 35.
    Woese CR, Kandlert O, Wheelis ML. Towards a natural system of organisms: proposal for the domains Archaea, Bacteria, and Eucarya (Euryarchaeota/Crenarchaeota/kingdom/evolution). Proc Natl Acad Sci U S A. 1990;87:4576–9.PubMedPubMedCentralCrossRefGoogle Scholar
  36. 36.
    Cole JR, et al. The Ribosomal Database Project: improved alignments and new tools for rRNA analysis. Nucleic Acids Res. 2008;37:141–5.CrossRefGoogle Scholar
  37. 37.
    Pruesse E, et al. SILVA: a comprehensive online resource for quality checked and aligned ribosomal RNA sequence data compatible with ARB. Nucleic Acids Res. 2007;35:7188–96.PubMedPubMedCentralCrossRefGoogle Scholar
  38. 38.
    Schloss PD, et al. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol. 2009;75:7537–41.PubMedPubMedCentralCrossRefGoogle Scholar
  39. 39.
    Hamady M, Lozupone C, Knight R. Fast UniFrac: facilitating high-throughput phylogenetic analyses of microbial communities including analysis of pyrosequencing and PhyloChip data. ISME J. 2010;4:17–27.PubMedCrossRefPubMedCentralGoogle Scholar
  40. 40.
    Caporaso JG, et al. QIIME allows analysis of high-throughput community sequencing data. Nat Methods. 2010;7:335–6.PubMedPubMedCentralCrossRefGoogle Scholar
  41. 41.
    Chen W, Zhang CK, Cheng Y, Zhang SK, Zhao H. A comparison of methods for clustering 16S rRNA sequences into OTUs. PLoS One. 2013;8:70837.CrossRefGoogle Scholar
  42. 42.
    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;6:19.CrossRefGoogle Scholar
  43. 43.
    Eren AM, et al. Oligotyping: differentiating between closely related microbial taxa using 16S rRNA gene data. Methods Ecol Evol. 2013;4:1111–9.PubMedCentralCrossRefGoogle Scholar
  44. 44.
    Tikhonov M, Leach RW, Wingreen NS. Interpreting 16S metagenomic data without clustering to achieve sub-OTU resolution. ISME J. 2015;9:68–80.PubMedCrossRefPubMedCentralGoogle Scholar
  45. 45.
    Callahan BJ, et al. DADA2: high-resolution sample inference from Illumina amplicon data. Nat Methods. 2016;13:581–3.PubMedPubMedCentralCrossRefGoogle Scholar
  46. 46.
    Callahan BJ, McMurdie PJ, Holmes SP. Exact sequence variants should replace operational taxonomic units in marker-gene data analysis. ISME J. 2017;11:2639–43.PubMedPubMedCentralCrossRefGoogle Scholar
  47. 47.
    Wang Q, Garrity GM, Tiedje JM, Cole JR. Naïve Bayesian classifier for rapid assignment of rRNA sequences into the new bacterial taxonomy. Appl Environ Microbiol. 2007;73:5261–7.PubMedPubMedCentralCrossRefGoogle Scholar
  48. 48.
    Chaudhary N, Sharma AK, Agarwal P, Gupta A, Sharma VK. 16S classifier: a tool for fast and accurate taxonomic classification of 16S rRNA hypervariable regions in metagenomic datasets. PLoS One. 2015;10:e0116106.PubMedPubMedCentralCrossRefGoogle Scholar
  49. 49.
    Hamady M, Knight R. Microbial community profiling for human microbiome projects: tools, techniques, and challenges. Genome Res. 2009;19:1141–52.PubMedPubMedCentralCrossRefGoogle Scholar
  50. 50.
    Lozupone C, Knight R. UniFrac: a new phylogenetic method for comparing microbial communities. Appl Environ Microbiol. 2005;71:8228–35.PubMedPubMedCentralCrossRefGoogle Scholar
  51. 51.
    Kelly BJ, et al. Power and sample-size estimation for microbiome studies using pairwise distances and PERMANOVA. Bioinformatics. 2015;31:2461–8.PubMedPubMedCentralCrossRefGoogle Scholar
  52. 52.
    Brown CT, et al. Unusual biology across a group comprising more than 15% of domain bacteria. Nature. 2015;523:208–11.CrossRefGoogle Scholar
  53. 53.
    Mukherjee S, et al. 1,003 Reference genomes of bacterial and archaeal isolates expand coverage of the tree of life. Nat Biotechnol. 2017;35:676–83.PubMedCrossRefPubMedCentralGoogle Scholar
  54. 54.
    Abubucker S, et al. Metabolic reconstruction for metagenomic data and its application to the human microbiome. PLoS Comput Biol. 2012;8:1002358.CrossRefGoogle Scholar
  55. 55.
    Baym M, et al. Inexpensive multiplexed library preparation for megabase-sized genomes. PLoS One. 2015;10:e0128036.PubMedPubMedCentralCrossRefGoogle Scholar
  56. 56.
    Jones MB, et al. Library preparation methodology can influence genomic and functional predictions in human microbiome research. Proc Natl Acad Sci. 2015;112:14024–9.PubMedCrossRefPubMedCentralGoogle Scholar
  57. 57.
    Quince C, Walker AW, Simpson JT, Loman NJ, Segata N. Shotgun metagenomics, from sampling to analysis. Nat Biotechnol. 2017;35:833–44.PubMedCrossRefPubMedCentralGoogle Scholar
  58. 58.
    O’Leary NA, et al. Reference sequence (RefSeq) database at NCBI: current status, taxonomic expansion, and functional annotation. Nucleic Acids Res. 2016;44:D733–45.PubMedCrossRefPubMedCentralGoogle Scholar
  59. 59.
    Finn RD, et al. The Pfam protein families database: towards a more sustainable future. Nucleic Acids Res. 2016;44:D279–85.PubMedCrossRefPubMedCentralGoogle Scholar
  60. 60.
    Suzek BE, Wang Y, Huang H, McGarvey PB, Wu CH. UniRef clusters: a comprehensive and scalable alternative for improving sequence similarity searches. Bioinformatics. 2015;31:926–32.PubMedCrossRefPubMedCentralGoogle Scholar
  61. 61.
    Nelson KE, et al. A catalog of reference genomes from the human microbiome. Science. 2010;328:994–9.CrossRefGoogle Scholar
  62. 62.
    Wang Z, Gerstein M, Snyder M. RNA-Seq: a revolutionary tool for transcriptomics. Nat Rev Genet. 2009;10:57–63.PubMedPubMedCentralCrossRefGoogle Scholar
  63. 63.
    Hawkins RD, Hon GC, Ren B. Next-generation genomics: an integrative approach. Nat Rev Genet. 2010;11:476–86.PubMedPubMedCentralCrossRefGoogle Scholar
  64. 64.
    Sultan M, et al. Influence of RNA extraction methods and library selection schemes on RNA-seq data. BMC Genomics. 2014;15:675.PubMedPubMedCentralCrossRefGoogle Scholar
  65. 65.
    Giannoukos G, et al. Efficient and robust RNA-seq process for cultured bacteria and complex community transcriptomes. Genome Biol. 2012;13:R23.PubMedPubMedCentralCrossRefGoogle Scholar
  66. 66.
    Fang Z, Cui X. Design and validation issues in RNA-seq experiments. Brief Bioinform. 2011;12:280–7.PubMedCrossRefPubMedCentralGoogle Scholar
  67. 67.
    Petriz BA, Franco OL. Metaproteomics as a complementary approach to gut microbiota in health and disease. Front Chem. 2017;5:4.PubMedPubMedCentralCrossRefGoogle Scholar
  68. 68.
    Kolmeder CA, de Vos WM. Metaproteomics of our microbiome – developing insight in function and activity in man and model systems. J Proteome. 2014;97:3–16.CrossRefGoogle Scholar
  69. 69.
    Heyer R, et al. Challenges and perspectives of metaproteomic data analysis. J Biotechnol. 2017;261:24–36.PubMedCrossRefPubMedCentralGoogle Scholar
  70. 70.
    Verberkmoes NC, et al. Shotgun metaproteomics of the human distal gut microbiota. ISME J. 2009;3:179–89.PubMedCrossRefPubMedCentralGoogle Scholar
  71. 71.
    Joglekar P, Segre JA. Building a translational microbiome toolbox. Cell. 2017;169:378–80.PubMedCrossRefPubMedCentralGoogle Scholar
  72. 72.
    Casadevall A, Fang FC. Rigorous science: a how-to guide. mBio. 2016;7:e01902–16.PubMedPubMedCentralGoogle Scholar
  73. 73.
    Bernardo J. Maternal effects in animal ecology. Am Zool. 1996;36:83–105.CrossRefGoogle Scholar
  74. 74.
    Simecek P, Dzur-gejdosova M, Chvatalova I, Forejt J. Litter effect in mouse phenotypic studies. Methods. 2009;2009:238–43.  https://doi.org/10.5220/0003173602380243.CrossRefGoogle Scholar
  75. 75.
    Ridaura VK, et al. Cultured gut microbiota from twins discordant for obesity modulate adiposity and metabolic phenotypes in mice. Science (80). 2013;341:PMC3829625.Google Scholar
  76. 76.
    Reber SO, et al. Immunization with a heat-killed preparation of the environmental bacterium Mycobacterium vaccae promotes stress resilience in mice. Proc Natl Acad Sci. 2016;113:E3130–9.PubMedCrossRefPubMedCentralGoogle Scholar
  77. 77.
    Miyoshi J, et al. Minimizing confounders and increasing data quality in murine models for studies of the gut microbiome. Peer J. 2018;6:e5166.PubMedCrossRefPubMedCentralGoogle Scholar
  78. 78.
    Zhong D, Brower-Sinning R, Firek B, Morowitz MJ. Acute appendicitis in children is associated with an abundance of bacteria from the phylum Fusobacteria. J Pediatr Surg. 2014;49:441–6.PubMedCrossRefPubMedCentralGoogle Scholar
  79. 79.
    Rogers MB, Brower-Sinning R, Firek B, Zhong D, Morowitz MJ. Acute appendicitis in children is associated with a local expansion of fusobacteria. Clin Infect Dis. 2016;63:71–8.PubMedCrossRefPubMedCentralGoogle Scholar
  80. 80.
    Goyal A, et al. Safety, clinical response, and microbiome findings following fecal microbiota transplant in children with inflammatory bowel disease. Inflamm Bowel Dis. 2018;24:410–21.PubMedCrossRefPubMedCentralGoogle Scholar
  81. 81.
    Abt MC, McKenney PT, Pamer EG. Clostridium difficile colitis: pathogenesis and host defence. Nat Rev Microbiol. 2016;14:609–20.PubMedPubMedCentralCrossRefGoogle Scholar
  82. 82.
    Rohlke F, Stollman N. Fecal microbiota transplantation in relapsing Clostridium difficile infection. Ther Adv Gastroenterol. 2012;5:403–20.CrossRefGoogle Scholar
  83. 83.
    Juul FE, et al. Fecal microbiota transplantation for primary Clostridium difficile infection. N Engl J Med. 2018;378:2535–6.PubMedCrossRefPubMedCentralGoogle Scholar
  84. 84.
    Smillie CS, et al. Strain tracking reveals the determinants of bacterial engraftment in the human gut following fecal microbiota transplantation. Cell Host Microbe. 2018;23:229–240.e5.PubMedCrossRefPubMedCentralGoogle Scholar
  85. 85.
    Halfvarson J, et al. Dynamics of the human gut microbiome in inflammatory bowel disease. Nat Microbiol. 2017;2:17004.PubMedPubMedCentralCrossRefGoogle Scholar
  86. 86.
    Gevers D, et al. The treatment-naive microbiome in new-onset Crohn’s disease. Cell Host Microbe. 2014;15:382–92.PubMedPubMedCentralCrossRefGoogle Scholar
  87. 87.
    Naser SA, Ghobrial G, Romero C, Valentine JF. Culture of Mycobacterium avium subspecies paratuberculosis from the blood of patients with Crohn’s disease. Lancet. 2004;364:1039–44.PubMedCrossRefPubMedCentralGoogle Scholar
  88. 88.
    Bull TJ, et al. Detection and verification of Mycobacterium avium subsp paratuberculosis in fresh ileocolonic mucosal biopsy specimens from individuals with and without Crohn’s disease. J Clin Microbiol. 2003;41:2915–23.PubMedPubMedCentralCrossRefGoogle Scholar
  89. 89.
    Glasser AL, et al. Adherent invasive Escherichia coli strains from patients with Crohn’s disease survive and replicate within macrophages without inducing host cell death. Infect Immun. 2001;69:5529–37.PubMedPubMedCentralCrossRefGoogle Scholar
  90. 90.
    Frank DN, et al. Molecular-phylogenetic characterization of microbial community imbalances in human inflammatory bowel diseases. Proc Natl Acad Sci U S A. 2007;104:13780–5.PubMedPubMedCentralCrossRefGoogle Scholar
  91. 91.
    Gilbert JA, et al. Current understanding of the human microbiome. Nat Med. 2018;24:392–400.CrossRefGoogle Scholar
  92. 92.
    Washburne AD, et al. Methods for phylogenetic analysis of microbiome. Nat Microbiol. 2018;3:652–61.PubMedCrossRefPubMedCentralGoogle Scholar
  93. 93.
    Magis AT, et al. Challenges in modeling the human gut microbiome, vol. 36. Washington, DC: US National Academies Press; 2018.Google Scholar
  94. 94.
    Douglas AE. Fundamentals of microbiome science: how microbes shape animal biology. Princeton, NJ: Princeton; 2018.CrossRefGoogle Scholar
  95. 95.
    Niu S-Y, et al. Bioinformatics tools for quantitative and functional metagenome and metatranscriptome data analysis in microbes. Brief Bioinform. 2018;19:360.PubMedCrossRefPubMedCentralGoogle Scholar
  96. 96.
    Browne HP, et al. Culturing of ‘unculturable’ human microbiota reveals novel taxa and extensive sporulation. Nature. 2016;533:543–6.PubMedPubMedCentralCrossRefGoogle Scholar
  97. 97.
    Geva-Zatorsky N, et al. Mining the human gut microbiota for immunomodulatory organisms. Cell. 2017;168:928–943.e11.PubMedCrossRefPubMedCentralGoogle Scholar
  98. 98.
    Chen G, The Y. Role of the gut microbiome in colorectal cancer. Clin Colon Rectal Surg. 2018;31:192–8.PubMedCrossRefPubMedCentralGoogle Scholar
  99. 99.
    Sivan A, et al. Commensal bifidobacterium promotes antitumor immunity and facilitates anti-PD-L1 efficacy. Science (80). 2015;350:1084–9.CrossRefGoogle Scholar
  100. 100.
    Alderton GK. Tumour immunology: intestinal bacteria are in command. Nat Rev Cancer. 2016;16:4.PubMedCrossRefPubMedCentralGoogle Scholar
  101. 101.
    Sinha R, et al. Assessment of variation in microbial community amplicon sequencing by the microbiome quality control (MBQC) project consortium. Nat Biotechnol. 2017;35:1077–86.PubMedPubMedCentralGoogle Scholar

Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Rafael G. Ramos-Jimenez
    • 1
  • Michael J. Morowitz
    • 1
    Email author
  1. 1.Division of Pediatric General and Thoracic SurgeryUPMC Children’s Hospital of PittsburghPittsburghUSA

Personalised recommendations