Baseline human gut microbiota profile in healthy people and standard reporting template


Autoři: Charles H. King aff001;  Hiral Desai aff001;  Allison C. Sylvetsky aff003;  Jonathan LoTempio aff004;  Shant Ayanyan aff001;  Jill Carrie aff001;  Keith A. Crandall aff006;  Brian C. Fochtman aff001;  Lusine Gasparyan aff001;  Naila Gulzar aff001;  Paul Howell aff007;  Najy Issa aff003;  Konstantinos Krampis aff008;  Lopa Mishra aff009;  Hiroki Morizono aff005;  Joseph R. Pisegna aff010;  Shuyun Rao aff009;  Yao Ren aff001;  Vahan Simonyan aff001;  Krista Smith aff001;  Sharanjit VedBrat aff007;  Michael D. Yao aff011;  Raja Mazumder aff001
Působiště autorů: The Department of Biochemistry & Molecular Medicine, School of Medicine and Health Sciences, George Washington University Medical Center, Washington, DC, United States of America aff001;  McCormick Genomic and Proteomic Center, George Washington University, Washington, DC, United States of America aff002;  The Department of Exercise and Nutrition Sciences, Milken Institute School of Public Health, George Washington University, Washington, DC, United States of America aff003;  The Institute for Biomedical Science, School of Medicine and Health Sciences, George Washington University, Washington, DC, United States of America aff004;  Center for Genetic Medicine, Children’s National Medical Center, George Washington University, Washington, DC, United States of America aff005;  Computational Biology Institute and The Department of Biostatistics and Bioinformatics, Milken Institute School of Public Health, George Washington University, Washington, DC, United States of America aff006;  KamTek Inc, Frederick, Maryland, United States of America aff007;  Department of Biological Sciences, Hunter College, City University of New York, New York, New York, United States of America aff008;  Center for Translational Medicine, Department of Surgery, George Washington University, Washington, DC, United States of America aff009;  Division of Gastroenterology and Hepatology VA Greater Los Angeles Healthcare System and Department of Medicine and Human Genetics, University of California, Los Angeles, Los Angeles, California, United States of America aff010;  Washington DC VA Medical Center, Gastroenterology & Hepatology Section, Washington, DC, United States of America aff011;  Department of Medicine, School of Medicine and Health Sciences, George Washington University, Washington, DC, United States of America aff012
Vyšlo v časopise: PLoS ONE 14(9)
Kategorie: Research Article
doi: 10.1371/journal.pone.0206484

Souhrn

A comprehensive knowledge of the types and ratios of microbes that inhabit the healthy human gut is necessary before any kind of pre-clinical or clinical study can be performed that attempts to alter the microbiome to treat a condition or improve therapy outcome. To address this need we present an innovative scalable comprehensive analysis workflow, a healthy human reference microbiome list and abundance profile (GutFeelingKB), and a novel Fecal Biome Population Report (FecalBiome) with clinical applicability. GutFeelingKB provides a list of 157 organisms (8 phyla, 18 classes, 23 orders, 38 families, 59 genera and 109 species) that forms the baseline biome and therefore can be used as healthy controls for studies related to dysbiosis. This list can be expanded to 863 organisms if closely related proteomes are considered. The incorporation of microbiome science into routine clinical practice necessitates a standard report for comparison of an individual’s microbiome to the growing knowledgebase of “normal” microbiome data. The FecalBiome and the underlying technology of GutFeelingKB address this need. The knowledgebase can be useful to regulatory agencies for the assessment of fecal transplant and other microbiome products, as it contains a list of organisms from healthy individuals. In addition to the list of organisms and their abundances, this study also generated a collection of assembled contiguous sequences (contigs) of metagenomics dark matter. In this study, metagenomic dark matter represents sequences that cannot be mapped to any known sequence but can be assembled into contigs of 10,000 nucleotides or higher. These sequences can be used to create primers to study potential novel organisms. All data is freely available from https://hive.biochemistry.gwu.edu/gfkb and NCBI’s Short Read Archive.

Klíčová slova:

Biology and life sciences – Microbiology – Medical microbiology – Microbiome – Microbial genomics – Genetics – Genomics – Metagenomics – Organisms – Bacteria – Gut bacteria – Bifidobacterium – Bacteroides – Taxonomy – Biochemistry – Proteins – Proteomes – Research and analysis methods – Database and informatics methods – Biological databases – Bioinformatics – Sequence analysis – Sequence databases – Sequence alignment – Computer and information sciences – Data management


Zdroje

1. Huttenhower C, Gevers D, Knight R, Abubucker S, Badger JH, Chinwalla AT, et al. Structure, function and diversity of the healthy human microbiome. Nature. 2012;486: 207–214. doi: 10.1038/nature11234 22699609

2. Chen X, Ling H-F, Vance D, Shields-Zhou GA, Zhu M, Poulton SW, et al. Rise to modern levels of ocean oxygenation coincided with the Cambrian radiation of animals. Nat Commun. 2015;6. doi: 10.1038/ncomms8142 25980960

3. Wang H, Zheng H, Browne F, Roehe R, Dewhurst RJ, Engel F, et al. Integrated metagenomic analysis of the rumen microbiome of cattle reveals key biological mechanisms associated with methane traits. Methods. 2017;124: 108–119. doi: 10.1016/j.ymeth.2017.05.029 28602995

4. Gao B, Chi L, Mahbub R, Bian X, Tu P, Ru H, et al. Multi-Omics Reveals that Lead Exposure Disturbs Gut Microbiome Development, Key Metabolites and Metabolic Pathways. Chem Res Toxicol. 2017;30: 996. doi: 10.1021/acs.chemrestox.6b00401 28234468

5. Mayer EA, Tillisch K, Gupta A. Gut/brain axis and the microbiota. J Clin Invest. 2015;125: 926–38. doi: 10.1172/JCI76304 25689247

6. O’Dwyer DN, Dickson RP, Moore BB. The Lung Microbiome, Immunity, and the Pathogenesis of Chronic Lung Disease. J Immunol. 2016;196: 4839–47. doi: 10.4049/jimmunol.1600279 27260767

7. Marshall B, Adams PC. Helicobacter pylori—a Nobel pursuit? Can J Gastroenterol. 2008;22: 895–6. doi: 10.1155/2008/459810 19018331

8. Ege MJ. The Hygiene Hypothesis in the Age of the Microbiome. Ann Am Thorac Soc. 2017;14: S348–S353. doi: 10.1513/AnnalsATS.201702-139AW 29161087

9. Lederberg J, McCray A. ‘Ome Sweet ‘Omics—A Genealogical Treasury of Words | The Scientist Magazine®. Sci. 2001;15: 8.

10. The Integrative Human Microbiome Project: Dynamic Analysis of Microbiome-Host Omics Profiles during Periods of Human Health and Disease. Cell Host Microbe. 2014;16: 276–289. doi: 10.1016/j.chom.2014.08.014 25211071

11. NIH HMP Working Group TNHW, Peterson J, Garges S, Giovanni M, McInnes P, Wang L, et al. The NIH Human Microbiome Project. Genome Res. 2009;19: 2317–23. doi: 10.1101/gr.096651.109 19819907

12. Donia MS, Cimermancic P, Schulze CJ, Wieland Brown LC, Martin J, Mitreva M, et al. A systematic analysis of biosynthetic gene clusters in the human microbiome reveals a common family of antibiotics. Cell. 2014;158: 1402–1414. doi: 10.1016/j.cell.2014.08.032 25215495

13. Korem T, Zeevi D, Suez J, Weinberger A, Avnit-Sagi T, Pompan-Lotan M, et al. Growth dynamics of gut microbiota in health and disease inferred from single metagenomic samples. Science. 2015;349: 1101–1106. doi: 10.1126/science.aac4812 26229116

14. Council NR. The New Science of Metagenomics [Internet]. Washington, D.C.: National Academies Press; 2007. doi: 10.17226/11902 21678629

15. Lloyd-Price J, Mahurkar A, Rahnavard G, Crabtree J, Orvis J, Hall AB, et al. Strains, functions and dynamics in the expanded Human Microbiome Project. Nature. 2017;550: 61–66. doi: 10.1038/nature23889 28953883

16. Proctor LM. The Human Microbiome Project in 2011 and Beyond. Cell Host Microbe. 2011;10: 287–291. doi: 10.1016/j.chom.2011.10.001 22018227

17. Liang D, Leung RK-K, Guan W, Au WW. Involvement of gut microbiome in human health and disease: brief overview, knowledge gaps and research opportunities. Gut Pathog. 2018;10: 3. doi: 10.1186/s13099-018-0230-4 29416567

18. Qin J, Li R, Raes J, Arumugam M, Burgdorf KS, Manichanh C, et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature. 2010;464. doi: 10.1038/nature08821 20203603

19. Stulberg E, Fravel D, Proctor LM, Murray DM, LoTempio J, Chrisey L, et al. An assessment of US microbiome research. Nat Microbiol. 2016;1: 15015. doi: 10.1038/nmicrobiol.2015.15 27571759

20. Almonacid DE, Kraal L, Ossandon FJ, Budovskaya YV., Cardenas JP, Bik EM, et al. 16S rRNA gene sequencing and healthy reference ranges for 28 clinically relevant microbial taxa from the human gut microbiome. Suchodolski JS, editor. PLoS One. 2017;12: e0176555. doi: 10.1371/journal.pone.0176555 28467461

21. Nasko DJ, Koren S, Phillippy AM, Treangen TJ. RefSeq database growth influences the accuracy of k-mer-based lowest common ancestor species identification. Genome Biol. 2018;19: 165. doi: 10.1186/s13059-018-1554-6 30373669

22. NCBI Resource Coordinators NR. Database resources of the National Center for Biotechnology Information. Nucleic Acids Res. 2018;46: D8–D13. doi: 10.1093/nar/gkx1095 29140470

23. Shamsaddini A, Pan Y, Johnson WE, Krampis K, Shcheglovitova M, Simonyan V, et al. Census-based rapid and accurate metagenome taxonomic profiling. BMC Genomics. 2014;15: 918. doi: 10.1186/1471-2164-15-918 25336203

24. Lobb B, Kurtz DA, Moreno-Hagelsieb G, Doxey AC. Remote homology and the functions of metagenomic dark matter. Front Genet. 2015;6: 234. doi: 10.3389/fgene.2015.00234 26257768

25. Bernard G, Pathmanathan JS, Lannes R, Lopez P, Bapteste E. Microbial Dark Matter Investigations: How Microbial Studies Transform Biological Knowledge and Empirically Sketch a Logic of Scientific Discovery. Genome Biol Evol. 2018;10: 707–715. doi: 10.1093/gbe/evy031 29420719

26. Scrimshaw NS. INFOODS: the international network of food data systems. Am J Clin Nutr. 1997;65: 1190S–1193S. doi: 10.1093/ajcn/65.4.1190S 9094920

27. Simonyan V, Mazumder R. High-performance integrated virtual environment (hive) tools and applications for big data analysis. Genes (Basel). 2014;5: 957–981. doi: 10.3390/genes5040957 25271953

28. Simonyan V, Chumakov K, Dingerdissen H, Faison W, Goldweber S, Golikov A, et al. High-performance integrated virtual environment (HIVE): a robust infrastructure for next-generation sequence data analysis. Database (Oxford). 2016;2016. doi: 10.1093/database/baw022 26989153

29. Huttenhower C, Fah Sathirapongsasuti J, Segata N, Gevers D, Earl AM, Fitzgerald MG, et al. Structure, function and diversity of the healthy human microbiome. Nature. 2012;486: 207–214. doi: 10.1038/nature11234 22699609

30. Shamsaddini A, Pan Y, Johnson W, Krampis K, Shcheglovitova M, Simonyan V, et al. Census-based rapid and accurate metagenome taxonomic profiling. BMC Genomics. 2014;15: 918. doi: 10.1186/1471-2164-15-918 25336203

31. Santana-Quintero L, Dingerdissen H, Thierry-Mieg J, Mazumder R, Simonyan V. HIVE-hexagon: High-performance, parallelized sequence alignment for next-generation sequencing data analysis. PLoS One. 2014;9. doi: 10.1371/journal.pone.0099033 24918764

32. Peng Y, Leung HCM, Yiu SM, Chin FYL. IDBA-UD: a de novo assembler for single-cell and metagenomic sequencing data with highly uneven depth. Bioinformatics. 2012;28: 1420–1428. doi: 10.1093/bioinformatics/bts174 22495754

33. Altschul SF, Gish W, Miller W, Myers EW, Lipman DJ. Basic local alignment search tool. J Mol Biol. 1990;215: 403–410. doi: 10.1016/S0022-2836(05)80360-2 2231712

34. Chen C, Natale DA, Finn RD, Huang H, Zhang J, Wu CH, et al. Representative Proteomesz: A Stable, Scalable and Unbiased proteome set for sequence analysis and functional annotation. Hoheisel JD, editor. PLoS One. 2011;6: e18910. doi: 10.1371/journal.pone.0018910 21556138

35. Bateman A, Martin MJ, O’Donovan C, Magrane M, Alpi E, Antunes R, et al. UniProt: The universal protein knowledgebase. Nucleic Acids Res. 2017;45: D158–D169. doi: 10.1093/nar/gkw1099 27899622

36. Whitman WB, Rainey F, Kämpfer P, Trujillo M, Chun J, DeVos P, et al., editors. Bergey’s Manual of Systematics of Archaea and Bacteria [Internet]. Bergey’s Manual of Systematics of Archaea and Bacteria. Wiley; 2015. doi: 10.1002/9781118960608

37. Santana-Quintero L, Dingerdissen H, Thierry-Mieg J, Mazumder R, Simonyan V. HIVE-hexagon: High-performance, parallelized sequence alignment for next-generation sequencing data analysis. PLoS One. 2014;9: e99033. doi: 10.1371/journal.pone.0099033 24918764

38. Morgan XC, Tickle TL, Sokol H, Gevers D, Devaney KL, Ward DV, et al. Dysfunction of the intestinal microbiome in inflammatory bowel disease and treatment. Genome Biol. 2012;13: R79. doi: 10.1186/gb-2012-13-9-r79 23013615

39. Okuda S, Tsuchiya Y, Kiriyama C, Itoh M, Morisaki H. Virtual metagenome reconstruction from 16S rRNA gene sequences. Nat Commun. 2012;3: 1203. doi: 10.1038/ncomms2203 23149747

40. Drell T, Larionova A, Voor T, Simm J, Julge K, Heilman K, et al. Differences in Gut Microbiota Between Atopic and Healthy Children. Curr Microbiol. 2015;71: 177–183. doi: 10.1007/s00284-015-0815-9 25869237

41. Schloissnig S, Arumugam M, Sunagawa S, Mitreva M, Tap J, Zhu A, et al. Genomic variation landscape of the human gut microbiome. Nature. 2013;493: 45–50. doi: 10.1038/nature11711 23222524

42. Zhou W, Gay N, Oh J. ReprDB and panDB: minimalist databases with maximal microbial representation. Microbiome. 2018;6: 15. doi: 10.1186/s40168-018-0399-2 29347966

43. Qin J, Li R, Raes J, Arumugam M, Burgdorf KS, Manichanh C, et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature. 2010;464: 59–65. doi: 10.1038/nature08821 20203603

44. Li J, Jia H, Cai X, Zhong H, Feng Q, Sunagawa S, et al. An integrated catalog of reference genes in the human gut microbiome. Nat Biotechnol. 2014;32: 834–841. doi: 10.1038/nbt.2942 24997786

45. Yatsunenko T, Rey FE, Manary MJ, Trehan I, Dominguez-Bello MG, Contreras M, et al. Human gut microbiome viewed across age and geography. Nature. 2012;486: 222–227. doi: 10.1038/nature11053 22699611

46. Nishijima S, Suda W, Oshima K, Kim S-W, Hirose Y, Morita H, et al. The gut microbiome of healthy Japanese and its microbial and functional uniqueness. DNA Res. 2016;23: 125–133. doi: 10.1093/dnares/dsw002 26951067

47. Qin N, Yang F, Li A, Prifti E, Chen Y, Shao L, et al. Alterations of the human gut microbiome in liver cirrhosis. Nature. 2014;513: 59–64. doi: 10.1038/nature13568 25079328

48. Gal-Mor O, Boyle EC, Grassl GA. Same species, different diseases: How and why typhoidal and non-typhoidal Salmonella enterica serovars differ [Internet]. Frontiers in Microbiology. Frontiers; 2014. p. 391. doi: 10.3389/fmicb.2014.00391 25136336

49. Strauss J, Kaplan GG, Beck PL, Rioux K, Panaccione R, DeVinney R, et al. Invasive potential of gut mucosa-derived fusobacterium nucleatum positively correlates with IBD status of the host. Inflamm Bowel Dis. 2011;17: 1971–1978. doi: 10.1002/ibd.21606 21830275

50. Bourne PE, Bonazzi V, Dunn M, Green ED, Guyer M, Komatsoulis G, et al. The NIH Big Data to Knowledge (BD2K) initiative. J Am Med Inform Assoc. 2015;22: 1114. doi: 10.1093/jamia/ocv136 26555016

51. Arumugam M, Raes J, Pelletier E, Le Paslier D, Yamada T, Mende DR, et al. Enterotypes of the human gut microbiome. Nature. 2011;473: 174–180. doi: 10.1038/nature09944 21508958

52. Wexler HM. Bacteroides: the good, the bad, and the nitty-gritty. Clin Microbiol Rev. 2007;20: 593–621. doi: 10.1128/CMR.00008-07 17934076

53. Mazmanian SK, Round JL, Kasper DL. A microbial symbiosis factor prevents intestinal inflammatory disease. Nature. 2008;453: 620–625. doi: 10.1038/nature07008 18509436

54. Coyne MJ, Comstock LE. Niche-Specific Features of the Intestinal Bacteroidales. J Bacteriol. 2008;190: 736. doi: 10.1128/JB.01559-07 17993536

55. O’Callaghan A, van Sinderen D. Bifidobacteria and Their Role as Members of the Human Gut Microbiota. Front Microbiol. 2016;7: 925. doi: 10.3389/fmicb.2016.00925 27379055

56. Xiao M, Xu P, Zhao J, Wang Z, Zuo F, Zhang J, et al. Oxidative stress-related responses of Bifidobacterium longum subsp. longum BBMN68 at the proteomic level after exposure to oxygen. Microbiology. 2011;157: 1573–1588. doi: 10.1099/mic.0.044297-0 21349974

57. Fukuda S, Toh H, Hase K, Oshima K, Nakanishi Y, Yoshimura K, et al. Bifidobacteria can protect from enteropathogenic infection through production of acetate. Nature. 2011;469: 543–547. doi: 10.1038/nature09646 21270894

58. Hao Y, Huang D, Guo H, Xiao M, An H, Zhao L, et al. Complete genome sequence of bifidobacterium longum subsp. longum BBMN68, a new strain from a healthy Chinese centenarian. J Bacteriol. 2011;193: 787–788. doi: 10.1128/JB.01213-10 21097614

59. Kim N, Kunisawa J, Kweon M-N, Eog Ji G, Kiyono H. Oral feeding of Bifidobacterium bifidum (BGN4) prevents CD4+ CD45RBhigh T cell-mediated inflammatory bowel disease by inhibition of disordered T cell activation. Clin Immunol. 2007;123: 30–39. doi: 10.1016/j.clim.2006.11.005 17218154

60. Shelburne SA, Sahasrabhojane P, Saldana M, Yao H, Su X, Horstmann N, et al. Streptococcus mitis strains causing severe clinical disease in cancer patients. Emerg Infect Dis. 2014;20: 762–771. doi: 10.3201/eid2005.130953 24750901

61. Palmer C, Bik EM, DiGiulio DB, Relman DA, Brown PO. Development of the Human Infant Intestinal Microbiota. Ruan Y, editor. PLoS Biol. 2007;5: e177. doi: 10.1371/journal.pbio.0050177 17594176

62. Miquel S, Peyretaillade E, Claret L, de Vallée A, Dossat C, Vacherie B, et al. Complete Genome Sequence of Crohn’s Disease-Associated Adherent-Invasive E. coli Strain LF82. Ahmed N, editor. PLoS One. 2010;5: e12714. doi: 10.1371/journal.pone.0012714 20862302

63. Feng Q, Liang S, Jia H, Stadlmayr A, Tang L, Lan Z, et al. Gut microbiome development along the colorectal adenoma–carcinoma sequence. Nat Commun. 2015;6: 6528. doi: 10.1038/ncomms7528 25758642

64. Howe A, Chain PSG. Challenges and opportunities in understanding microbial communities with metagenome assembly (accompanied by IPython Notebook tutorial). Front Microbiol. 2015;6: 678. doi: 10.3389/fmicb.2015.00678 26217314

65. Land M, Hauser L, Jun S-R, Nookaew I, Leuze MR, Ahn T-H, et al. Insights from 20 years of bacterial genome sequencing. Funct Integr Genomics. 2015;15: 141–61. doi: 10.1007/s10142-015-0433-4 25722247

66. Zackular JP, Rogers MaM, Ruffin MT, Schloss PD. The Human Gut Microbiome as a Screening Tool for Colorectal Cancer. Cancer Prev Res. 2014;7: 1940–6207. CAPR-14-0129-. doi: 10.1158/1940-6207.CAPR-14-0129 25104642

67. Silverman E, Niehaus A. NHGRI Genomic Medicine IX: NHGRI’s Genomic Medicine Portfolio–Bedside to Bench. https://www.genome.gov/Multimedia/Slides/GM9/gm9_summary_final_GM9full_SilvermanE.pdf

68. Donaldson GP, Lee SM, Mazmanian SK. Gut biogeography of the bacterial microbiota. Nat Rev Microbiol. 2016;14: 20–32. doi: 10.1038/nrmicro3552 26499895

69. Dao MC, Everard A, Aron-Wisnewsky J, Sokolovska N, Prifti E, Verger EO, et al. Akkermansia muciniphila and improved metabolic health during a dietary intervention in obesity: relationship with gut microbiome richness and ecology. Gut. 2016;65: 426–36. doi: 10.1136/gutjnl-2014-308778 26100928

70. Bloom SM, Bijanki VN, Nava GM, Sun L, Malvin NP, Donermeyer DL, et al. Commensal Bacteroides species induce colitis in host-genotype-specific fashion in a mouse model of inflammatory bowel disease. Cell Host Microbe. 2011;9: 390–403. doi: 10.1016/j.chom.2011.04.009 21575910

71. Rubinstien EM, Klevjer-Anderson P, Smith CA, Drouin MT, Patterson JE. Enterobacter taylorae, a new opportunistic pathogen: report of four cases. J Clin Microbiol. 1993;31: 249–54. Available: http://www.ncbi.nlm.nih.gov/pubmed/8381808 8381808

72. Flint HJ, Scott KP, Duncan SH, Louis P, Forano E. Microbial degradation of complex carbohydrates in the gut. Gut Microbes. 2012;3: 289–306. doi: 10.4161/gmic.19897 22572875


Článek vyšel v časopise

PLOS One


2019 Číslo 9

Nejčtenější v tomto čísle

Tomuto tématu se dále věnují…


Kurzy

Zvyšte si kvalifikaci online z pohodlí domova

Výhody léčby pacientů s DM 2. typu GLP-1 agonisty
nový kurz
Autoři: prof. MUDr. Martin Haluzík, DrSc.

Syndrom suchého oka – diagnostika, komplikace a léčba
Autoři: MUDr. Petr Výborný, CSc., FEBO

Systémová léčba psoriázy
Autoři: MUDr. Jiří Horažďovský, Ph.D

Klinická farmakokinetika betablokátorů
Autoři:

Současné možnosti terapie osteoartrózy
Autoři: MUDr. Jakub Holešovský

Všechny kurzy
Kurzy Doporučená témata