The challenge and potential of metagenomics in the clinic

Frontiers in Immunology

Volumn 7, Issue FEB, 2016, Pages

  Mulcahy O'Grady, Heidi ^a   Workentine, Matthew L ^b  

^a ALBERTA HEALTH SERVICES   (Canada)

^b UNIVERSITY OF CALGARY   (Canada)

Author keywords

Antibiotic resistance; Bioinformatics; Clinical research; Clostridium difficile; Diagnositics; Metagenomics; Microbiome; Pathogen detection

Indexed keywords

METRONIDAZOLE; VANCOMYCIN;

ANTIBIOTIC RESISTANCE; BIOINFORMATICS; CLOSTRIDIUM DIFFICILE INFECTION; DNA EXTRACTION; DYSBIOSIS; GENE SEQUENCE; HUMAN; METABOLITE; METAGENOMICS; MICROBIAL COMMUNITY; MICROBIAL DIVERSITY; MICROBIOME; MOLECULAR BIOLOGY; NONHUMAN; PREDICTION; REVIEW;

EID: 84962485152     PISSN: None     EISSN: 16643224     Source Type: Journal    
DOI: 10.3389/fimmu.2016.00029     Document Type: Review

References (87)

1. Cho I, Blaser MJ. The human microbiome: at the interface of health and disease. Nat Rev Genet (2012) 13:260-70. doi: 10.1038/nrg3182.
2. Tremaroli V, Bäckhed F. Functional interactions between the gut microbiota and host metabolism. Nature (2012) 489:242-9. doi:10.1038/nature11552.
3. Weyrich LS, Dixit S, Farrer AG, Cooper AJ. The skin microbiome: associations between altered microbial communities and disease. Australas J Dermatol (2015) 56:268-74. doi:10.1111/ajd.12253.
4. SanMiguel A, Grice EA. Interactions between host factors and the skin microbiome. Cell Mol Life Sci (2015) 72:1499-515. doi:10.1007/s00018-014-1812-z.
5. Oh J, Byrd AL, Deming C, Conlan S; NISC Comparative Sequencing Program, Kong HH, et al. Biogeography and individuality shape function in the human skin metagenome. Nature (2014) 514:59-64. doi:10.1038/nature13786.
6. Schloss PD. Microbiology: an integrated view of the skin microbiome. Nature (2014) 514:44-5. doi:10.1038/514044a.
7. Cryan JF, Dinan TG. Mind-altering microorganisms: the impact of the gut microbiota on brain and behaviour. Nat Rev Neurosci (2012) 13:701-12. doi:10.1038/nrn3346.
8. Trompette A, Gollwitzer ES, Yadava K, Sichelstiel AK, Sprenger N, Ngom-Bru C, et al. Gut microbiota metabolism of dietary fiber influences allergic airway disease and hematopoiesis. Nat Med (2014) 20:159-66. doi:10.1038/nm.3444.
9. Huang YJ, Boushey HA. The microbiome and asthma. Ann Am Thorac Soc (2014) 11:S48-51. doi:10.1513/AnnalsATS.201306-187MG.
10. Cammarota G, Ianiro G, Cianci R, Bibbò S, Gasbarrini A, Currò D. The involvement of gut microbiota in inflammatory bowel disease pathogenesis: potential for therapy. Pharmacol Ther (2015) 149:191-212. doi:10.1016/j.pharmthera.2014.12.006.
11. Ordovas JM, Mooser V. Metagenomics: the role of the microbiome in cardiovascular diseases. Curr Opin Lipidol (2006) 17:157-61. doi:10.1097/01.mol.0000217897.75068.ba.
12. Garrett WS. Cancer and the microbiota. Science (2015) 348:80-6. doi:10.1126/science.aaa4972.
13. Bultman SJ. Emerging roles of the microbiome in cancer. Carcinogenesis (2014) 35:249-55. doi:10.1093/carcin/bgt392.
14. Goodman AL, Kallstrom G, Faith JJ, Reyes A, Moore A, Dantas G, et al. Extensive personal human gut microbiota culture collections characterized and manipulated in gnotobiotic mice. Proc Natl Acad Sci USA (2011) 108:6252-7. doi:10.1073/pnas.1102938108.
15. Stewart EJ. Growing unculturable bacteria. J Bacteriol (2012) 194:4151-60. doi:10.1128/JB.00345-12.
16. Sibley CD, Grinwis ME, Field TR, Eshaghurshan CS, Faria MM, Dowd SE, et al. Culture enriched molecular profiling of the cystic fibrosis airway microbiome. PLoS One (2011) 6:e22702. doi:10.1371/journal.pone.0022702.
17. Lagier JC, Armougom F, Million M, Hugon P, Pagnier I, Robert C, et al. Microbial culturomics: paradigm shift in the human gut microbiome study. Clin Microbiol Infect (2012) 18:1185-93. doi:10.1111/1469-0691.12023.
18. Staley JT, Konopka A. Measurement of in situ activities of nonphotosynthetic microorganisms in aquatic and terrestrial habitats. Annu Rev Microbiol (1985) 39:321-46. doi:10.1146/annurev.mi.39.100185.001541.
19. Vo ATE, Jedlicka JA. Protocols for metagenomic DNA extraction and Illumina amplicon library preparation for faecal and swab samples. Mol Ecol Resour (2014) 14:1183-97. doi:10.1111/1755-0998.12269.
20. Goodrich JK, Di Rienzi SC, Poole AC, Koren O, Walters WA, Caporaso JG, et al. Conducting a microbiome study. Cell (2014) 158:250-62. doi:10.1016/j.cell.2014.06.037.
21. Knight R, Jansson J, Field D, Fierer N, Desai N, Fuhrman JA, et al. Unlocking the potential of metagenomics through replicated experimental design. Nat Biotechnol (2012) 30:513-20. doi:10.1038/nbt.2235.
22. Thomas T, Gilbert J, Meyer F. Metagenomics-a guide from sampling to data analysis. Microb Inform Exp (2012) 2:3. doi:10.1186/2042-5783-2-3.
23. Miller RR, Montoya V, Gardy JL, Patrick DM, Tang P. Metagenomics for pathogen detection in public health. Genome Med (2013) 5:81. doi:10.1186/gm485.
24. Wesolowska-Andersen A, Bahl MI, Carvalho V, Kristiansen K, Sicheritz-Ponten T, Gupta R, et al. Choice of bacterial DNA extraction method from fecal material influences community structure as evaluated by metagenomic analysis. Microbiome (2014) 2:1. doi:10.1186/2049-2618-2-19.
25. Thurber RV, Haynes M, Breitbart M, Wegley L, Rohwer F. Laboratory procedures to generate viral metagenomes. Nat Protoc (2009) 4:470-83. doi:10.1038/nprot.2009.10.
26. Salter SJ, Cox MJ, Turek EM, Calus ST, Cookson WO, Moffatt MF, et al. Reagent and laboratory contamination can critically impact sequence-based microbiome analyses. BMC Biol (2014) 12:1. doi:10.1186/s12915-014-0087-z.
27. Turner P, Turner C, Jankhot A, Helen N, Lee SJ, Day NP, et al. A longitudinal study of Streptococcus pneumoniae carriage in a cohort of infants and their mothers on the Thailand-Myanmar border. PLoS One (2012) 7:e38271. doi:10.1371/journal.pone.0038271.
28. Leek JT, Scharpf RB, Bravo HC, Simcha D, Langmead B, Johnson WE, et al. Tackling the widespread and critical impact of batch effects in high-throughput data. Nat Rev Genet (2010) 11:733-9. doi:10.1038/nrg2825.
29. Ni J, Yan Q, Yu Y. How much metagenomic sequencing is enough to achieve a given goal? Sci Rep (2013) 3:1-7. doi:10.1038/srep01968.
30. Wood DE, Salzberg SL. Kraken: ultrafast metagenomic sequence classification using exact alignments. Genome Biol (2014) 15:R46. doi:10.1186/gb-2014-15-3-r46.
31. 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) 9:811-4. doi:10.1038/nmeth.2066.
32. 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) 9:1. doi:10.1186/1471-2105-9-386.
33. Huson DH, Mitra S, Ruscheweyh H-J, Weber N, Schuster SC. Integrative analysis of environmental sequences using MEGAN4. Genome Res (2011) 21:1552-60. doi:10.1101/gr.120618.111.
34. Abubucker S, Segata N, Goll J, Schubert AM, Izard J, Cantarel BL, et al. Metabolic reconstruction for metagenomic data and its application to the human microbiome. PLoS Comput Biol (2012) 8:e1002358. doi:10.1371/journal.pcbi.1002358.
35. Peng Y, Leung HCM, Yiu SM, Chin FYL. Meta-IDBA: a de novo assembler for metagenomic data. Bioinformatics (2011) 27:194-101. doi:10.1093/bioinformatics/btr216.
36. 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. doi:10.1038/nmeth.3103.
37. Eren AM, Esen ÖC, Quince C, Vineis JH, Morrison HG, Sogin ML, et al. Anvio: an advanced analysis and visualization platform for omics data. PeerJ (2015) 3:e1319. doi:10.7717/peerj.1319.
38. Luo C, Knight R, Siljander H, Knip M, Xavier RJ, Gevers D. Constrains identifies microbial strains in metagenomic datasets. Nat Biotechnol (2015) 33:1045-52. doi:10.1038/nbt.3319.
39. Nayfach S, Pollard KS. Population genetic analyses of metagenomes reveal extensive strain-level variation in prevalent human-associated bacteria. bioRxiv (2015):031757. doi:10.1101/031757.
40. Dreier J, Vollmer T, Freytag CC, Bäumer D, Körfer R, Kleesiek K. Culture-negative infectious endocarditis caused by Bartonella spp.: 2 case reports and a review of the literature. Diagn Microbiol Infect Dis (2008) 61:476-83. doi:10.1016/j.diagmicrobio.2008.03.008.
41. Richardson DC, Burrows LL, Korithoski B, Salit IE, Butany J, David TE, et al. Tropheryma whippelii as a cause of afebrile culture-negative endocarditis: the evolving spectrum of Whipple's disease. J Infect (2003) 47:170-3. doi:10.1016/S0163-4453(03)00015-X.
42. Nakamura S, Maeda N, Miron IM, Yoh M, Izutsu K, Kataoka C, et al. Metagenomic diagnosis of bacterial infections. Emerg Infect Dis (2008) 14:1784-6. doi:10.3201/eid1411.080589.
43. Pallen MJ, Loman NJ, Penn CW. High-throughput sequencing and clinical microbiology: progress, opportunities and challenges. Curr Opin Microbiol (2010) 13:625-31. doi:10.1016/j.mib.2010.08.003.
44. Loman NJ, Constantinidou C, Christner M, Rohde H, Chan JZ-M, Quick J, et al. A culture-independent sequence-based metagenomics approach to the investigation of an outbreak of shiga-toxigenic Escherichia coli O104:H4. JAMA (2013) 309:1502-10. doi:10.1001/jama.2013.3231.
45. Mokili JL, Rohwer F, Dutilh BE. Metagenomics and future perspectives in virus discovery. Curr Opin Virol (2012) 2:63-77. doi:10.1016/j.coviro.2011.12.004.
46. Kostic AD, Ojesina AI, Pedamallu CS, Jung J, Verhaak RGW, Getz G, et al. PathSeq: software to identify or discover microbes by deep sequencing of human tissue. Nat Biotechnol (2011) 29:393-6. doi:10.1038/nbt.1868.
47. Bhatt AS, Freeman SS, Herrera AF, Pedamallu CS, Gevers D, Duke F, et al. Sequence-based discovery of Bradyrhizobium entericain cord colitis syndrome. N Engl J Med (2013) 369:517-28. doi:10.1056/NEJMoa1211115.
48. Byrd AL, Perez-Rogers JF, Manimaran S, Castro-Nallar E, Toma I, McCaffrey T, et al. Clinical pathoscope: rapid alignment and filtration for accurate pathogen identification in clinical samples using unassembled sequencing data. BMC Bioinformatics (2014) 15:262. doi:10.1186/1471-2105-15-262.
49. Bhaduri A, Qu K, Lee CS, Ungewickell A, Khavari PA. Rapid identification of non-human sequences in high-throughput sequencing datasets. Bioinformatics (2012) 28:1174-5. doi:10.1093/bioinformatics/bts100.
50. Naeem R, Rashid M, Pain A. READSCAN: a fast and scalable pathogen discovery program with accurate genome relative abundance estimation. Bioinformatics (2013) 29:391-2. doi:10.1093/bioinformatics/bts684.
51. Naccache SN, Federman S, Veeraraghavan N, Zaharia M, Lee D, Samayoa E, et al. A cloud-compatible bioinformatics pipeline for ultrarapid pathogen identification from next-generation sequencing of clinical samples. Genome Res (2014) 24:1180-92. doi:10.1101/gr.171934.113.
52. Naccache SN, Peggs KS, Mattes FM, Phadke R, Garson JA, Grant P, et al. Diagnosis of neuroinvasive astrovirus infection in an immunocompromised adult with encephalitis by unbiased next-generation sequencing. Clin Infect Dis (2015) 60:919-23. doi:10.1093/cid/ciu912.
53. De La Cochetière MF, Durand T, Lalande V, Petit JC, Potel G, Beaugerie L. Effect of antibiotic therapy on human fecal microbiota and the relation to the development of Clostridium difficile. Microb Ecol (2008) 56:395-402. doi:10.1007/s00248-007-9356-5.
54. Deakin LJ, Clare S, Fagan RP, Dawson LF, Pickard DJ, West MR, et al. The Clostridium difficile spo0A Gene is a persistence and transmission factor. Infect Immun (2012) 80:2704-11. doi:10.1128/IAI.00147-12.
55. Hopkins MJ, Sharp R, Macfarlane GT. Age and disease related changes in intestinal bacterial populations assessed by cell culture, 16S rRNA abundance, and community cellular fatty acid profiles. Gut (2001) 48:198-205. doi:10.1136/gut.48.2.198.
56. Louie TJ, Byrne B, Emery J, Ward L, Krulicki W, Nguyen D, et al. Differences of the fecal microflora with Clostridium difficile therapies. Clin Infect Dis (2015) 60(Suppl 2):S91-7. doi:10.1093/cid/civ252.
57. Antharam VC, Li EC, Ishmael A, Sharma A, Mai V, Rand KH, et al. Intestinal dysbiosis and depletion of butyrogenic bacteria in Clostridium difficile infection and nosocomial diarrhea. J Clin Microbiol (2013) 51:2884-92. doi:10.1128/JCM.00845-13.
58. Schubert AM, Rogers MAM, Ring C, Mogle J, Petrosino JP, Young VB, et al. Microbiome data distinguish patients with Clostridium difficile infection and non-C. difficile-associated diarrhea from healthy controls. MBio (2014) 5:e1021-1014. doi:10.1128/mBio.01021-14.
59. Rea MC, O'Sullivan O, Shanahan F, O'Toole PW, Stanton C, Ross RP, et al. Clostridium difficile carriage in elderly subjects and associated changes in the intestinal microbiota. J Clin Microbiol (2012) 50:867-75. doi:10.1128/JCM.05176-11.
60. Johnson S, Louie TJ, Gerding DN, Cornely OA, Chasan-Taber S, Fitts D, et al. Vancomycin, metronidazole, or tolevamer for Clostridium difficile infection: results from two multinational, randomized, controlled trials. Clin Infect Dis (2014) 59:345-54. doi:10.1093/cid/ciu313.
61. Louie TJ, Cannon K, Byrne B, Emery J, Ward L, Eyben M, et al. Fidaxomicin preserves the intestinal microbiome during and after treatment of Clostridium difficile infection (CDI) and reduces both toxin reexpression and recurrence of CDI. Clin Infect Dis (2012) 55(Suppl 2):S132-42. doi:10.1093/cid/cis338.
62. Viaud S, Saccheri F, Mignot G, Yamazaki T, Daillère R, Hannani D, et al. The intestinal microbiota modulates the anticancer immune effects of cyclophosphamide. Science (2013) 342:971-6. doi:10.1126/science.1240537.
63. Gough E, Shaikh H, Manges AR. Systematic review of intestinal microbiota transplantation (fecal bacteriotherapy) for recurrent Clostridium difficile infection. Clin Infect Dis (2011) 53:994-1002. doi:10.1093/cid/cir632.
64. Louie TJ, Cannon K, O'Grady H, Wu K, Ward L. Fecal microbiome transplantation (FMT) via oral fecal microbial capsules for recurrent Clostridium difficile infection (rCDI). Oral Abstract Session: New Considerations in C. difficile Prevention and Treatment. San Diego, CA: ID week 2013 (2013). Available from: https://idsa.confex.com/idsa/2013/webprogram/Paper41627.html.
65. Song Y, Garg S, Girotra M, Maddox C, von Rosenvinge EC, Dutta A, et al. Microbiota dynamics in patients treated with fecal microbiota transplantation for recurrent Clostridium difficile infection. PLoS One (2013) 8:e81330. doi:10.1371/journal.pone.0081330.
66. Fuentes S, van Nood E, Tims S, Heikamp-de Jong I, ter Braak CJ, Keller JJ, et al. Reset of a critically disturbed microbial ecosystem: faecal transplant in recurrent Clostridium difficile infection. ISME J (2014) 8:1621-33. doi:10.1038/ismej.2014.13.
67. Lawley TD, Clare S, Walker AW, Stares MD, Connor TR, Raisen C, et al. Targeted restoration of the intestinal microbiota with a simple, defined bacteriotherapy resolves relapsing Clostridium difficile disease in mice. PLoS Pathog (2012) 8:e1002995. doi:10.1371/journal.ppat.1002995.
68. Tvede M, Rask-Madsen J. Bacteriotherapy for chronic relapsing Clostridium difficile diarrhoea in six patients. Lancet (1989) 1:1156-60. doi:10.1016/S0140-6736(89)92749-9.
69. Petrof EO, Gloor GB, Vanner SJ, Weese SJ, Carter D, Daigneault MC, et al. Stool substitute transplant therapy for the eradication of Clostridium dif ficile infection: 'RePOOPulating' the gut. Microbiome (2013) 1:3. doi:10.1186/2049-2618-1-3.
70. Reeves AE, Koenigsknecht MJ, Bergin IL, Young VB. Suppression of Clostridium difficile in the gastrointestinal tracts of germfree mice inoculated with a murine isolate from the family lachnospiraceae. Infect Immun (2012) 80:3786-94. doi:10.1128/IAI.00647-12.
71. Power ME, Tilman D, Estes JA, Menge BA, Bond WJ. Challenges in the quest for keystones. Bioscience (1996) 46(8):609-20. doi:10.2307/1312990.
72. Weingarden AR, Chen C, Bobr A, Yao D, Lu Y, Nelson VM, et al. Microbiota transplantation restores normal fecal bile acid composition in recurrent Clostridium difficile infection. Am J Physiol Gastrointest Liver Physiol (2014) 306:G310-9. doi:10.1152/ajpgi.00282.2013.
73. O'Keefe SJD. Tube feeding, the microbiota, and Clostridium difficile infection. World J Gastroenterol (2010) 16:139-42. doi:10.3748/wjg.v16.i2.139.
74. May T, Mackie RI, Fahey GC, Cremin JC, Garleb KA. Effect of fiber source on short-chain fatty acid production and on the growth and toxin production by Clostridium difficile. Scand J Gastroenterol (1994) 29:916-22. doi:10.3109/00365529409094863.
75. Bouillaut L, Dubois T, Sonenshein AL, Dupuy B. Integration of metabolism and virulence in Clostridium difficile. Res Microbiol (2015) 166:375-83. doi:10.1016/j.resmic.2014.10.002.
76. Ferreyra JA, Wu KJ, Hryckowian AJ, Bouley DM, Weimer BC, Sonnenburg JL. Gut microbiota-produced succinate promotes C. difficile infection after antibiotic treatment or motility disturbance. Cell Host Microbe (2014) 16:770-7. doi:10.1016/j.chom.2014.11.003.
77. Bhalla A, Pultz NJ, Ray AJ, Hoyen CK, Eckstein EC, Donskey CJ. Antianaerobic antibiotic therapy promotes overgrowth of antibiotic-resistant, gram-negative bacilli and vancomycin-resistant Enterococci in the stool of colonized patients. Infect Control Hosp Epidemiol (2003) 24:644-9. doi:10.1086/502267.
78. Ubeda C, Taur Y, Jenq RR, Equinda MJ, Son T, Samstein M, et al. Vancomycin-resistant Enterococcus domination of intestinal microbiota is enabled by antibiotic treatment in mice and precedes bloodstream invasion in humans. J Clin Invest (2010) 120:4332-41. doi:10.1172/JCI43918.
79. Wright GD. The antibiotic resistome: the nexus of chemical and genetic diversity. Nat Rev Microbiol (2007) 5:175-86. doi:10.1038/nrmicro1614.
80. Schmieder R, Edwards R. Insights into antibiotic resistance through metagenomic approaches. Future Microbiol (2012) 7:73-89. doi:10.2217/fmb.11.135.
81. Bradley P, Gordon NC, Walker TM, Dunn L, Heys S, Huang B, et al. Rapid antibiotic resistance predictions from genome sequence data for S. aureus and M. tuberculosis. bioRxiv (2015):018564. doi:10.1101/018564.
82. Hu Y, Yang X, Qin J, Lu N, Cheng G, Wu N, et al. Metagenome-wide analysis of antibiotic resistance genes in a large cohort of human gut microbiota. Nat Commun (2013) 4:2151. doi:10.1038/ncomms3151.
83. Forslund K, Sunagawa S, Coelho LP, Bork P. Metagenomic insights into the human gut resistome and the forces that shape it. Bioessays (2014) 36:316-29. doi:10.1002/bies.201300143.
84. McArthur AG, Waglechner N, Nizam F, Yan A, Azad MA, Baylay AJ, et al. The comprehensive antibiotic resistance database. Antimicrob Agents Chemother (2013) 57:3348-57. doi:10.1128/AAC.00419-13.
85. Liu B, Pop M. ARDB-Antibiotic resistance genes database. Nucleic Acids Res (2009) 37:D443-7. doi:10.1093/nar/gkn656.
86. Vincent AT, Charette SJ. Who qualifies to be a bioinformatician? Front Genet (2015) 6:164. doi:10.3389/fgene.2015.00164.
87. Smith DR. Broadening the definition of a bioinformatician. Front Genet (2015) 6:258. doi:10.3389/fgene.2015.00258.