Abstract
Over the last decade, biologists have come to appreciate that the human body is inhabited by thousands of bacterial species in diverse communities unique to each body site. Moreover, due to high-throughput sequencing methods for microbial characterization in a culture-independent manner, it is becoming evident that the microbiome plays an important role in human health and disease. This chapter focuses on the most common form of bacterial microbiome profiling, targeted amplicon sequencing of the 16S ribosomal RNA (rRNA) subunit encoded by 16S rDNA. We discuss important features for designing and performing microbiome experiments on human specimens, including experimental design, sample collection, DNA preparation, and selection of the 16S rDNA sequencing target. We also provide details for designing fusion primers required for targeted amplicon sequencing and selecting the most appropriate high-throughput sequencing platform. We conclude with a review of the fundamental concepts of data analysis and interpretation for these kinds of experiments. Our goal is to provide the reader with the essential knowledge needed to undertake microbiome experiments for application to human disease research questions.
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References
Bertelli C, Greub G (2013) Rapid bacterial genome sequencing: methods and applications in clinical microbiology. Clin Microbiol Infect 19(9):803–813. https://doi.org/10.1111/1469-0691.12217
Gilbert JA, Jansson JK, Knight R (2014) The earth microbiome project: successes and aspirations. BMC Biol 12:69. https://doi.org/10.1186/s12915-014-0069-1
Turnbaugh PJ, Ley RE, Hamady M, Fraser-Liggett CM, Knight R, Gordon JI (2007) The human microbiome project. Nature 449(7164):804–810. https://doi.org/10.1038/nature06244
Human Microbiome Project C (2012) Structure, function and diversity of the healthy human microbiome. Nature 486(7402):207–214. https://doi.org/10.1038/nature11234
Feazel LM, Baumgartner LK, Peterson KL, Frank DN, Harris JK, Pace NR (2009) Opportunistic pathogens enriched in showerhead biofilms. Proc Natl Acad Sci U S A 106(38):16393–16399. https://doi.org/10.1073/pnas.0908446106. 0908446106 [pii]
Ghurye JS, Cepeda-Espinoza V, Pop M (2016) Metagenomic assembly: overview, challenges and applications. Yale J Biol Med 89(3):353–362
Yang B, Wang Y, Qian PY (2016) Sensitivity and correlation of hypervariable regions in 16S rRNA genes in phylogenetic analysis. BMC Bioinformatics 17:135. https://doi.org/10.1186/s12859-016-0992-y
Claesson MJ, Wang Q, O'Sullivan O, Greene-Diniz R, Cole JR, Ross RP, O'Toole PW (2010) Comparison of two next-generation sequencing technologies for resolving highly complex microbiota composition using tandem variable 16S rRNA gene regions. Nucleic Acids Res 38(22):e200. https://doi.org/10.1093/nar/gkq873
Chakravorty S, Helb D, Burday M, Connell N, Alland D (2007) A detailed analysis of 16S ribosomal RNA gene segments for the diagnosis of pathogenic bacteria. J Microbiol Methods 69(2):330–339. https://doi.org/10.1016/j.mimet.2007.02.005
Barb JJ, Oler AJ, Kim HS, Chalmers N, Wallen GR, Cashion A, Munson PJ, Ames NJ (2016) Development of an analysis pipeline characterizing multiple hypervariable regions of 16S rRNA using mock samples. PLoS One 11(2):e0148047. https://doi.org/10.1371/journal.pone.0148047
Human Microbiome Project C (2012) A framework for human microbiome research. Nature 486(7402):215–221. https://doi.org/10.1038/nature11209
Caporaso JG, Lauber CL, Walters WA, Berg-Lyons D, Huntley J, Fierer N, Owens SM, Betley J, Fraser L, Bauer M, Gormley N, Gilbert JA, Smith G, Knight R (2012) Ultra-high-throughput microbial community analysis on the Illumina HiSeq and MiSeq platforms. ISME J 6(8):1621–1624. https://doi.org/10.1038/ismej.2012.8
Whiteley AS, Jenkins S, Waite I, Kresoje N, Payne H, Mullan B, Allcock R, O'Donnell A (2012) Microbial 16S rRNA ion tag and community metagenome sequencing using the ion torrent (PGM) platform. J Microbiol Methods 91(1):80–88. https://doi.org/10.1016/j.mimet.2012.07.008
Kozich JJ, Westcott SL, Baxter NT, Highlander SK, Schloss PD (2013) Development of a dual-index sequencing strategy and curation pipeline for analyzing amplicon sequence data on the MiSeq Illumina sequencing platform. Appl Environ Microbiol 79(17):5112–5120. https://doi.org/10.1128/AEM.01043-13
Goodrich JK, Di Rienzi SC, Poole AC, Koren O, Walters WA, Caporaso JG, Knight R, Ley RE (2014) Conducting a microbiome study. Cell 158(2):250–262. https://doi.org/10.1016/j.cell.2014.06.037
Meisel JS, Hannigan GD, Tyldsley AS, SanMiguel AJ, Hodkinson BP, Zheng Q, Grice EA (2016) Skin microbiome surveys are strongly influenced by experimental design. J Invest Dermatol 136(5):947–956. https://doi.org/10.1016/j.jid.2016.01.016
Laukens D, Brinkman BM, Raes J, De Vos M, Vandenabeele P (2016) Heterogeneity of the gut microbiome in mice: guidelines for optimizing experimental design. FEMS Microbiol Rev 40(1):117–132. https://doi.org/10.1093/femsre/fuv036
Moore RJ, Stanley D (2016) Experimental design considerations in microbiota/inflammation studies. Clin Transl Immunol 5(7):e92. https://doi.org/10.1038/cti.2016.41
Weiss S, Amir A, Hyde ER, Metcalf JL, Song SJ, Knight R (2014) Tracking down the sources of experimental contamination in microbiome studies. Genome Biol 15(12):564. https://doi.org/10.1186/s13059-014-0564-2
Salter SJ, Cox MJ, Turek EM, Calus ST, Cookson WO, Moffatt MF, Turner P, Parkhill J, Loman NJ, Walker AW (2014) Reagent and laboratory contamination can critically impact sequence-based microbiome analyses. BMC Biol 12:87. https://doi.org/10.1186/s12915-014-0087-z
Yuan S, Cohen DB, Ravel J, Abdo Z, Forney LJ (2012) Evaluation of methods for the extraction and purification of DNA from the human microbiome. PLoS One 7(3):e33865. https://doi.org/10.1371/journal.pone.0033865
Kaeser M, Ruf MT, Hauser J, Pluschke G (2010) Optimized DNA preparation from mycobacteria. Cold Spring Harb Protoc 2010(4):prot5408. https://doi.org/10.1101/pdb.prot5408
Caporaso JG, Kuczynski J, Stombaugh J, Bittinger K, Bushman FD, Costello EK, Fierer N, Pena AG, Goodrich JK, Gordon JI, Huttley GA, Kelley ST, Knights D, Koenig JE, Ley RE, Lozupone CA, McDonald D, Muegge BD, Pirrung M, Reeder J, Sevinsky JR, Turnbaugh PJ, Walters WA, Widmann J, Yatsunenko T, Zaneveld J, Knight R (2010) QIIME allows analysis of high-throughput community sequencing data. Nat Methods 7(5):335–336. https://doi.org/10.1038/nmeth.f.303. nmeth.f.303 [pii]
Schloss PD, Westcott SL, Ryabin T, Hall JR, Hartmann M, Hollister EB, Lesniewski RA, Oakley BB, Parks DH, Robinson CJ, Sahl JW, Stres B, Thallinger GG, Van Horn DJ, Weber CF (2009) Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl Environ Microbiol 75(23):7537–7541. https://doi.org/10.1128/AEM.01541-09
Ciccarelli FD, Doerks T, von Mering C, Creevey CJ, Snel B, Bork P (2006) Toward automatic reconstruction of a highly resolved tree of life. Science 311(5765):1283–1287. https://doi.org/10.1126/science.1123061
McDonald D, Clemente JC, Kuczynski J, Rideout JR, Stombaugh J, Wendel D, Wilke A, Huse S, Hufnagle J, Meyer F, Knight R, Caporaso JG (2012) The biological observation matrix (BIOM) format. Gigascience 1(1):7. https://doi.org/10.1186/2047-217X-1-7
Wong RG, Wu JR, Gloor GB (2016) Expanding the unifrac toolbox. PLoS One 11(9):e0161196. https://doi.org/10.1371/journal.pone.0161196
Lozupone C, Lladser ME, Knights D, Stombaugh J, Knight R (2011) UniFrac: an effective distance metric for microbial community comparison. ISME J 5(2):169–172. https://doi.org/10.1038/ismej.2010.133
McMurdie PJ, Holmes S (2013) Phyloseq: an R package for reproducible interactive analysis and graphics of microbiome census data. PLoS One 8(4):e61217. https://doi.org/10.1371/journal.pone.0061217
Yilmaz P, Kottmann R, Field D, Knight R, Cole JR, Amaral-Zettler L, Gilbert JA, Karsch-Mizrachi I, Johnston A, Cochrane G, Vaughan R, Hunter C, Park J, Morrison N, Rocca-Serra P, Sterk P, Arumugam M, Bailey M, Baumgartner L, Birren BW, Blaser MJ, Bonazzi V, Booth T, Bork P, Bushman FD, Buttigieg PL, Chain PS, Charlson E, Costello EK, Huot-Creasy H, Dawyndt P, DeSantis T, Fierer N, Fuhrman JA, Gallery RE, Gevers D, Gibbs RA, San Gil I, Gonzalez A, Gordon JI, Guralnick R, Hankeln W, Highlander S, Hugenholtz P, Jansson J, Kau AL, Kelley ST, Kennedy J, Knights D, Koren O, Kuczynski J, Kyrpides N, Larsen R, Lauber CL, Legg T, Ley RE, Lozupone CA, Ludwig W, Lyons D, Maguire E, Methe BA, Meyer F, Muegge B, Nakielny S, Nelson KE, Nemergut D, Neufeld JD, Newbold LK, Oliver AE, Pace NR, Palanisamy G, Peplies J, Petrosino J, Proctor L, Pruesse E, Quast C, Raes J, Ratnasingham S, Ravel J, Relman DA, Assunta-Sansone S, Schloss PD, Schriml L, Sinha R, Smith MI, Sodergren E, Spo A, Stombaugh J, Tiedje JM, Ward DV, Weinstock GM, Wendel D, White O, Whiteley A, Wilke A, Wortman JR, Yatsunenko T, Glockner FO (2011) Minimum information about a marker gene sequence (MIMARKS) and minimum information about any (x) sequence (MIxS) specifications. Nat Biotechnol 29(5):415–420. https://doi.org/10.1038/nbt.1823
Rosser EC, Mauri C (2016) A clinical update on the significance of the gut microbiota in systemic autoimmunity. J Autoimmun 74:85–93. https://doi.org/10.1016/j.jaut.2016.06.009
Arumugam M, Raes J, Pelletier E, Le Paslier D, Yamada T, Mende DR, Fernandes GR, Tap J, Bruls T, Batto JM, Bertalan M, Borruel N, Casellas F, Fernandez L, Gautier L, Hansen T, Hattori M, Hayashi T, Kleerebezem M, Kurokawa K, Leclerc M, Levenez F, Manichanh C, Nielsen HB, Nielsen T, Pons N, Poulain J, Qin J, Sicheritz-Ponten T, Tims S, Torrents D, Ugarte E, Zoetendal EG, Wang J, Guarner F, Pedersen O, de Vos WM, Brunak S, Dore J, Meta HITC, Antolin M, Artiguenave F, Blottiere HM, Almeida M, Brechot C, Cara C, Chervaux C, Cultrone A, Delorme C, Denariaz G, Dervyn R, Foerstner KU, Friss C, van de Guchte M, Guedon E, Haimet F, Huber W, van Hylckama-Vlieg J, Jamet A, Juste C, Kaci G, Knol J, Lakhdari O, Layec S, Le Roux K, Maguin E, Merieux A, Melo Minardi R, M'Rini C, Muller J, Oozeer R, Parkhill J, Renault P, Rescigno M, Sanchez N, Sunagawa S, Torrejon A, Turner K, Vandemeulebrouck G, Varela E, Winogradsky Y, Zeller G, Weissenbach J, Ehrlich SD, Bork P (2011) Enterotypes of the human gut microbiome. Nature 473(7346):174–180. https://doi.org/10.1038/nature09944
Honda K, Littman DR (2012) The microbiome in infectious disease and inflammation. Annu Rev Immunol 30:759–795. https://doi.org/10.1146/annurev-immunol-020711-074937
Ishikawa D, Sasaki T, Osada T, Kuwahara-Arai K, Haga K, Shibuya T, Hiramatsu K, Watanabe S (2016) Changes in intestinal microbiota following combination therapy with fecal microbial transplantation and antibiotics for ulcerative colitis. Inflamm Bowel Dis 23(1):116–125. https://doi.org/10.1097/MIB.0000000000000975
Khoruts A, Dicksved J, Jansson JK, Sadowsky MJ (2010) Changes in the composition of the human fecal microbiome after bacteriotherapy for recurrent Clostridium Difficile-associated diarrhea. J Clin Gastroenterol 44(5):354–360. https://doi.org/10.1097/MCG.0b013e3181c87e02
Carmody LA, Zhao J, Kalikin LM, LeBar W, Simon RH, Venkataraman A, Schmidt TM, Abdo Z, Schloss PD, LiPuma JJ (2015) The daily dynamics of cystic fibrosis airway microbiota during clinical stability and at exacerbation. Microbiome 3:12. https://doi.org/10.1186/s40168-015-0074-9
Zemanick ET, Wagner BD, Robertson CE, Stevens MJ, Szefler SJ, Accurso FJ, Sagel SD, Harris JK (2014) Assessment of airway microbiota and inflammation in cystic fibrosis using multiple sampling methods. Ann Am Thorac Soc 12(2):221–229. https://doi.org/10.1513/AnnalsATS.201407-310OC
Huffnagle GB (2016) Another piece in the “research mosaic” that describes the role of the lung microbiome in COPD. Thorax 71(9):777–778. https://doi.org/10.1136/thoraxjnl-2015-207415
Stokell JR, Gharaibeh RZ, Hamp TJ, Zapata MJ, Fodor AA, Steck TR (2015) Analysis of changes in diversity and abundance of the microbial community in a cystic fibrosis patient over a multiyear period. J Clin Microbiol 53(1):237–247. https://doi.org/10.1128/JCM.02555-14.JCM.02555-14[pii]
Coburn B, Wang PW, Diaz Caballero J, Clark ST, Brahma V, Donaldson S, Zhang Y, Surendra A, Gong Y, Elizabeth Tullis D, Yau YC, Waters VJ, Hwang DM, Guttman DS (2015) Lung microbiota across age and disease stage in cystic fibrosis. Sci Rep 5:10241. https://doi.org/10.1038/srep10241
Cox MJ, Allgaier M, Taylor B, Baek MS, Huang YJ, Daly RA, Karaoz U, Andersen GL, Brown R, Fujimura KE, Wu B, Tran D, Koff J, Kleinhenz ME, Nielson D, Brodie EL, Lynch SV (2010) Airway microbiota and pathogen abundance in age-stratified cystic fibrosis patients. PLoS One 5(6):e11044. https://doi.org/10.1371/journal.pone.0011044
Beck JM, Young VB, Huffnagle GB (2012) The microbiome of the lung. Transl Res 160(4):258–266. https://doi.org/10.1016/j.trsl.2012.02.005
Noval Rivas M, Crother TR, Arditi M (2016) The microbiome in asthma. Curr Opin Pediatr 135(1):25–30. https://doi.org/10.1097/MOP.0000000000000419
Hanson BM, Weinstock GM (2016) The importance of the microbiome in epidemiologic research. Ann Epidemiol 26(5):301–305. https://doi.org/10.1016/j.annepidem.2016.03.008
Wu H, Tremaroli V, Backhed F (2015) Linking microbiota to human diseases: a systems biology perspective. Trends Endocrinol Metab 26(12):758–770. https://doi.org/10.1016/j.tem.2015.09.011
Blekhman R, Goodrich JK, Huang K, Sun Q, Bukowski R, Bell JT, Spector TD, Keinan A, Ley RE, Gevers D, Clark AG (2015) Host genetic variation impacts microbiome composition across human body sites. Genome Biol 16:191. https://doi.org/10.1186/s13059-015-0759-1
Dabrowska K, Witkiewicz W (2016) Correlations of host genetics and gut microbiome composition. Front Microbiol 7:1357. https://doi.org/10.3389/fmicb.2016.01357
Goodrich JK, Waters JL, Poole AC, Sutter JL, Koren O, Blekhman R, Beaumont M, Van Treuren W, Knight R, Bell JT, Spector TD, Clark AG, Ley RE (2014) Human genetics shape the gut microbiome. Cell 159(4):789–799. https://doi.org/10.1016/j.cell.2014.09.053
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Davidson, R.M., Epperson, L.E. (2018). Microbiome Sequencing Methods for Studying Human Diseases. In: DiStefano, J. (eds) Disease Gene Identification. Methods in Molecular Biology, vol 1706. Humana Press, New York, NY. https://doi.org/10.1007/978-1-4939-7471-9_5
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