Human Microbiome Project Explained

Abbreviation:HMP
Owner:US National Institutes of Health

The Human Microbiome Project (HMP) was a United States National Institutes of Health (NIH) research initiative to improve understanding of the microbiota involved in human health and disease. Launched in 2007,[1] the first phase (HMP1) focused on identifying and characterizing human microbiota. The second phase, known as the Integrative Human Microbiome Project (iHMP) launched in 2014 with the aim of generating resources to characterize the microbiome and elucidating the roles of microbes in health and disease states. The program received $170 million in funding by the NIH Common Fund from 2007 to 2016.[2]

Important components of the HMP were culture-independent methods of microbial community characterization, such as metagenomics (which provides a broad genetic perspective on a single microbial community), as well as extensive whole genome sequencing (which provides a "deep" genetic perspective on certain aspects of a given microbial community, i.e. of individual bacterial species). The latter served as reference genomic sequences — 3000 such sequences of individual bacterial isolates are currently planned — for comparison purposes during subsequent metagenomic analysis. The project also financed deep sequencing of bacterial 16S rRNA sequences amplified by polymerase chain reaction from human subjects.[3]

Introduction

Prior to the HMP launch, it was often reported in popular media and scientific literature that there are about 10 times as many microbial cells and 100 times as many microbial genes in the human body as there are human cells; this figure was based on estimates that the human microbiome includes around 100 trillion bacterial cells and an adult human typically has around 10 trillion human cells.[4] In 2014 the American Academy of Microbiology published a FAQ that emphasized that the number of microbial cells and the number of human cells are both estimates, and noted that recent research had arrived at a new estimate of the number of human cells at around 37 trillion cells, meaning that the ratio of microbial to human cells is probably about 3:1.[4] [5] In 2016 another group published a new estimate of ratio as being roughly 1:1 (1.3:1, with "an uncertainty of 25% and a variation of 53% over the population of standard 70 kg males").[6] [7]

Despite the staggering number of microbes in and on the human body, little was known about their roles in human health and disease. Many of the organisms that make up the microbiome have not been successfully cultured, identified, or otherwise characterized. Organisms thought to be found in the human microbiome, however, may generally be categorized as bacteria, members of domain Archaea, yeasts, and single-celled eukaryotes as well as various helminth parasites and viruses, the latter including viruses that infect the cellular microbiome organisms (e.g., bacteriophages). The HMP set out to discover and characterize the human microbiome, emphasizing oral, skin, vaginal, gastrointestinal, and respiratory sites.

The HMP will address some of the most inspiring, vexing and fundamental scientific questions today. Importantly, it also has the potential to break down the artificial barriers between medical microbiology and environmental microbiology. It is hoped that the HMP will not only identify new ways to determine health and predisposition to diseases but also define the parameters needed to design, implement and monitor strategies for intentionally manipulating the human microbiota, to optimize its performance in the context of an individual's physiology.[8]

The HMP has been described as "a logical conceptual and experimental extension of the Human Genome Project."[8] In 2007 the HMP was listed on the NIH Roadmap for Medical Research[9] as one of the New Pathways to Discovery. Organized characterization of the human microbiome is also being done internationally under the auspices of the International Human Microbiome Consortium.[10] The Canadian Institutes of Health Research, through the CIHR Institute of Infection and Immunity, is leading the Canadian Microbiome Initiative to develop a coordinated and focused research effort to analyze and characterize the microbes that colonize the human body and their potential alteration during chronic disease states.[11]

Contributing Institutions

The HMP involved participation from many research institutions, including Stanford University, the Broad Institute, Virginia Commonwealth University, Washington University, Northeastern University, MIT, the Baylor College of Medicine, and many others. Contributions included data evaluation, construction of reference sequence data sets, ethical and legal studies, technology development, and more.

Phase One (2007-2014)

The HMP1 included research efforts from many institutions.[12] The HMP1 set the following goals:[13]

Phase Two (2014-2016)

In 2014, the NIH launched the second phase of the project, known as the Integrative Human Microbiome Project (iHMP). The goal of the iHMP was to produce resources to create a complete characterization of the human microbiome, with a focus on understanding the presence of microbiota in health and disease states.[14] The project mission, as stated by the NIH, was as follows:

The iHMP will create integrated longitudinal datasets of biological properties from both the microbiome and host from three different cohort studies of microbiome-associated conditions using multiple "omics" technologies.
The project encompassed three sub-projects carried out at multiple institutions. Study methods included 16S rRNA gene profiling, whole metagenome shotgun sequencing, whole genome sequencing, metatranscriptomics, metabolomics/lipidomics, and immunoproteomics. The key findings of the iHMP were published in 2019.[15]

Pregnancy & Preterm Birth

The Vaginal Microbiome Consortium team at Virginia Commonwealth University led research on the Pregnancy & Preterm Birth project with a goal of understanding how the microbiome changes during the gestational period and influences the neonatal microbiome. The project was also concerned with the role of the microbiome in the occurrence of preterm births, which, according to the CDC, account for nearly 10% of all births[16] and constitutes the second leading cause of neonatal death.[17] The project received $7.44 million in NIH funding.[18]

Onset of Inflammatory Bowel Disease (IBD)

The Inflammatory Bowel Disease Multi'omics Data (IBDMDB) team was a multi-institution group of researchers focused on understanding how the gut microbiome changes longitudinally in adults and children suffering from IBD. IBD is an inflammatory autoimmune disorder that manifests as either Crohn's disease or ulcerative colitis and affects about one million Americans.[19] Research participants included cohorts from Massachusetts General Hospital, Emory University Hospital/Cincinnati Children's Hospital, and Cedars-Sinai Medical Center.[20]

Onset of Type 2 Diabetes (T2D)

Researchers from Stanford University and the Jackson Laboratory of Genomic Medicine worked together to perform a longitudinal analysis on the biological processes that occur in the microbiome of patients at risk for Type 2 Diabetes. T2D affects nearly 20 million Americans with at least 79 million pre-diabetic patients,[21] and is partially characterized by marked shifts in the microbiome compared to healthy individuals. The project aimed to identify molecules and signaling pathways that play a role in the etiology of the disease.[22]

Achievements

The impact to date of the HMP may be partially assessed by examination of research sponsored by the HMP. Over 650 peer-reviewed publications were listed on the HMP website from June 2009 to the end of 2017, and had been cited over 70,000 times.[23] At this point the website was archived and is no longer updated, although datasets do continue to be available.[24]

Major categories of work funded by HMP included:

Developments funded by HMP included:

Milestones

Reference database established

On 13 June 2012, a major milestone of the HMP was announced by the NIH director Francis Collins.[51] The announcement was accompanied with a series of coordinated articles published in Nature[52] [53] and several journals including the Public Library of Science (PLoS) on the same day.[54] [55] [56] By mapping the normal microbial make-up of healthy humans using genome sequencing techniques, the researchers of the HMP have created a reference database and the boundaries of normal microbial variation in humans.[57]

From 242 healthy U.S. volunteers, more than 5,000 samples were collected from tissues from 15 (men) to 18 (women) body sites such as mouth, nose, skin, lower intestine (stool) and vagina. All the DNA, human and microbial, were analyzed with DNA sequencing machines. The microbial genome data were extracted by identifying the bacterial specific ribosomal RNA, 16S rRNA. The researchers calculated that more than 10,000 microbial species occupy the human ecosystem and they have identified 81 – 99% of the genera. In addition to establishing the human microbiome reference database, the HMP project also discovered several "surprises", which include:

Clinical application

Among the first clinical applications utilizing the HMP data, as reported in several PLoS papers, the researchers found a shift to less species diversity in vaginal microbiome of pregnant women in preparation for birth, and high viral DNA load in the nasal microbiome of children with unexplained fevers. Other studies using the HMP data and techniques include role of microbiome in various diseases in the digestive tract, skin, reproductive organs and childhood disorders.[51]

Pharmaceutical application

Pharmaceutical microbiologists have considered the implications of the HMP data in relation to the presence / absence of 'objectionable' microorganisms in non-sterile pharmaceutical products and in relation to the monitoring of microorganisms within the controlled environments in which products are manufactured. The latter also has implications for media selection and disinfectant efficacy studies.[58]

External links

Notes and References

  1. Web site: Human Microbiome Project: Diversity of Human Microbes Greater Than Previously Predicted. ScienceDaily. 8 March 2012.
  2. Web site: Human Microbiome Project - Home NIH Common Fund. commonfund.nih.gov. 28 June 2013. en. 2018-04-15.
  3. Web site: Human Microbiome Project. The NIH Common Fund. 8 March 2012.
  4. American Academy of Microbiology FAQ: Human Microbiome January 2014
  5. Judah L. Rosner for Microbe Magazine, Feb 2014. Ten Times More Microbial Cells than Body Cells in Humans?
  6. Alison Abbott for Nature News. Jan 8 2016 Scientists bust myth that our bodies have more bacteria than human cells
  7. Sender R, Fuchs S, Milo R . Are We Really Vastly Outnumbered? Revisiting the Ratio of Bacterial to Host Cells in Humans . Cell . 164 . 3 . 337–40 . January 2016 . 26824647 . 10.1016/j.cell.2016.01.013 . free .
  8. Turnbaugh PJ, Ley RE, Hamady M, Fraser-Liggett CM, Knight R, Gordon JI . The human microbiome project . Nature . 449 . 7164 . 804–10 . October 2007 . 17943116 . 3709439 . 10.1038/nature06244 . 2007Natur.449..804T .
  9. Web site: About the NIH Roadmap . The NIH Common Fund . 8 March 2012 . dead . https://web.archive.org/web/20130217072814/https://commonfund.nih.gov/aboutroadmap.aspx . 17 February 2013 .
  10. Web site: The International Human Microbiome Consortium. 8 March 2012.
  11. Web site: Canadian Microbiome Initiative. 13 August 2009. Canadian Institutes of Health Research. 8 March 2012.
  12. Web site: Human Microbiome Project / Funded Research. The NIH Common Fund. 8 March 2012.
  13. Web site: Human Microbiome Project / Program Initiatives. The NIH Common Fund. 8 March 2012.
  14. Web site: NIH Human Microbiome Project - About the Human Microbiome. hmpdacc.org. en. 2018-03-30.
  15. NIH Human Microbiome Portfolio Analysis Team. 2019. A review of 10 years of human microbiome research activities at the US National Institutes of Health, Fiscal Years 2007-2016. Microbiome. en. 7. 1. 31. 10.1186/s40168-019-0620-y. 30808411. 2049-2618. 6391833 . free .
  16. Ferré C, Callaghan W, Olson C, Sharma A, Barfield W . Effects of Maternal Age and Age-Specific Preterm Birth Rates on Overall Preterm Birth Rates - United States, 2007 and 2014 . en-us . MMWR. Morbidity and Mortality Weekly Report . 65 . 43 . 1181–1184 . November 2016 . 27811841 . 10.15585/mmwr.mm6543a1 . free .
  17. Web site: Infant Mortality Maternal and Infant Health Reproductive Health CDC. 2018-01-02. www.cdc.gov. en-us. 2018-04-03.
  18. Web site: Vaginal Microbiome Consortium. Consortium. VCU, Vaginal Microbiome. vmc.vcu.edu. en. 2018-04-05.
  19. Web site: CDC - Epidemiology of the IBD - Inflammatory Bowel Disease. www.cdc.gov. en-us. 2018-04-15. https://web.archive.org/web/20170223213840/https://www.cdc.gov/ibd/ibd-epidemiology.htm. 2017-02-23. dead.
  20. Web site: Team. ibdmdb.org. en. 2018-04-05.
  21. Web site: National Diabetes Statistics Report Data & Statistics Diabetes CDC. 2018-03-09. www.cdc.gov. en-us. 2018-04-15.
  22. Web site: Integrated Personal Omics Profiling Integrated Personal Omics Profiling Stanford Medicine. med.stanford.edu. en. 2018-04-05.
  23. Web site: Human Microbiome Project - Home NIH Common Fund. commonfund.nih.gov. 28 June 2013. 2019-04-18.
  24. Web site: Human Microbiome Project Data Portal. portal.hmpdacc.org. 2019-04-18.
  25. Markowitz VM, Chen IM, Palaniappan K, Chu K, Szeto E, Grechkin Y, Ratner A, Jacob B, Huang J, Williams P, Huntemann M, Anderson I, Mavromatis K, Ivanova NN, Kyrpides NC . IMG: the Integrated Microbial Genomes database and comparative analysis system . Nucleic Acids Research . 40 . Database issue . D115–22 . January 2012 . 22194640 . 3245086 . 10.1093/nar/gkr1044 .
  26. Markowitz VM, Chen IM, Chu K, Szeto E, Palaniappan K, Grechkin Y, Ratner A, Jacob B, Pati A, Huntemann M, Liolios K, Pagani I, Anderson I, Mavromatis K, Ivanova NN, Kyrpides NC . IMG/M: the integrated metagenome data management and comparative analysis system . Nucleic Acids Research . 40 . Database issue . D123–9 . January 2012 . 22086953 . 3245048 . 10.1093/nar/gkr975 .
  27. Madupu R, Richter A, Dodson RJ, Brinkac L, Harkins D, Durkin S, Shrivastava S, Sutton G, Haft D . CharProtDB: a database of experimentally characterized protein annotations . Nucleic Acids Research . 40 . Database issue . D237–41 . January 2012 . 22140108 . 3245046 . 10.1093/nar/gkr1133 .
  28. Pagani I, Liolios K, Jansson J, Chen IM, Smirnova T, Nosrat B, Markowitz VM, Kyrpides NC . The Genomes OnLine Database (GOLD) v.4: status of genomic and metagenomic projects and their associated metadata . Nucleic Acids Research . 40 . Database issue . D571–9 . January 2012 . 22135293 . 3245063 . 10.1093/nar/gkr1100 .
  29. Zhao Y, Tang H, Ye Y . RAPSearch2: a fast and memory-efficient protein similarity search tool for next-generation sequencing data . Bioinformatics . 28 . 1 . 125–6 . January 2012 . 22039206 . 3244761 . 10.1093/bioinformatics/btr595 .
  30. Stombaugh J, Widmann J, McDonald D, Knight R . Boulder ALignment Editor (ALE): a web-based RNA alignment tool . Bioinformatics . 27 . 12 . 1706–7 . June 2011 . 21546392 . 3106197 . 10.1093/bioinformatics/btr258 .
  31. Wu S, Zhu Z, Fu L, Niu B, Li W . WebMGA: a customizable web server for fast metagenomic sequence analysis . BMC Genomics . 12 . 444 . September 2011 . 21899761 . 3180703 . 10.1186/1471-2164-12-444 . free .
  32. Ghodsi M, Liu B, Pop M . DNACLUST: accurate and efficient clustering of phylogenetic marker genes . BMC Bioinformatics . 12 . 271 . June 2011 . 21718538 . 3213679 . 10.1186/1471-2105-12-271 . free .
  33. Yao G, Ye L, Gao H, Minx P, Warren WC, Weinstock GM . Graph accordance of next-generation sequence assemblies . Bioinformatics . 28 . 1 . 13–6 . January 2012 . 22025481 . 3244760 . 10.1093/bioinformatics/btr588 .
  34. Book: Treangen TJ, Sommer DD, Angly FE, Koren S, Pop M . Next generation sequence assembly with AMOS . Current Protocols in Bioinformatics . Chapter 11 . Unit 11.8 . March 2011 . 21400694 . 3072823 . 10.1002/0471250953.bi1108s33 . 978-0471250951 .
  35. Koren S, Miller JR, Walenz BP, Sutton G . An algorithm for automated closure during assembly . BMC Bioinformatics . 11 . 457 . September 2010 . 20831800 . 2945939 . 10.1186/1471-2105-11-457 . free .
  36. Web site: Human Microbiome Project / Reference Genomes Data . Data Analysis and Coordination Center (DACC) for the National Institutes of Health (NIH). 8 March 2012.
  37. Web site: Data Analysis and Coordination Center (DACC). National Institutes of Health (NIH) Common Fund. 11 March 2012.
  38. Schwab AP, Frank L, Gligorov N . Saying privacy, meaning confidentiality . The American Journal of Bioethics . 11 . 11 . 44–5 . November 2011 . 22047127 . 10.1080/15265161.2011.608243 . 34313782 .
  39. Rhodes R, Azzouni J, Baumrin SB, Benkov K, Blaser MJ, Brenner B, Dauben JW, Earle WJ, Frank L, Gligorov N, Goldfarb J, Hirschhorn K, Hirschhorn R, Holzman I, Indyk D, Jabs EW, Lackey DP, Moros DA, Philpott S, Rhodes ME, Richardson LD, Sacks HS, Schwab A, Sperling R, Trusko B, Zweig A . De minimis risk: a proposal for a new category of research risk . The American Journal of Bioethics . 11 . 11 . 1–7 . November 2011 . 22047112 . 10.1080/15265161.2011.615588 . 205859554 .
  40. McGuire AL, Lupski JR . Personal genome research : what should the participant be told? . Trends in Genetics . 26 . 5 . 199–201 . May 2010 . 20381895 . 2868334 . 10.1016/j.tig.2009.12.007 .
  41. Sharp RR, Achkar JP, Brinich MA, Farrell RM . Helping patients make informed choices about probiotics: a need for research . The American Journal of Gastroenterology . 104 . 4 . 809–13 . April 2009 . 19343022 . 2746707 . 10.1038/ajg.2008.68 .
  42. Cuellar-Partida G, Buske FA, McLeay RC, Whitington T, Noble WS, Bailey TL . Epigenetic priors for identifying active transcription factor binding sites . Bioinformatics . 28 . 1 . 56–62 . January 2012 . 22072382 . 3244768 . 10.1093/bioinformatics/btr614 .
  43. Haft DH . Bioinformatic evidence for a widely distributed, ribosomally produced electron carrier precursor, its maturation proteins, and its nicotinoprotein redox partners . BMC Genomics . 12 . 21 . January 2011 . 21223593 . 3023750 . 10.1186/1471-2164-12-21 . free .
  44. Caporaso JG, Lauber CL, Costello EK, Berg-Lyons D, Gonzalez A, Stombaugh J, Knights D, Gajer P, Ravel J, Fierer N, Gordon JI, Knight R . Moving pictures of the human microbiome . Genome Biology . 12 . 5 . R50 . 2011 . 21624126 . 3271711 . 10.1186/gb-2011-12-5-r50 . free .
  45. Sczesnak A, Segata N, Qin X, Gevers D, Petrosino JF, Huttenhower C, Littman DR, Ivanov II . The genome of th17 cell-inducing segmented filamentous bacteria reveals extensive auxotrophy and adaptations to the intestinal environment . Cell Host & Microbe . 10 . 3 . 260–72 . September 2011 . 21925113 . 3209701 . 10.1016/j.chom.2011.08.005 .
  46. Ballal SA, Gallini CA, Segata N, Huttenhower C, Garrett WS . Host and gut microbiota symbiotic factors: lessons from inflammatory bowel disease and successful symbionts . Cellular Microbiology . 13 . 4 . 508–17 . April 2011 . 21314883 . 10.1111/j.1462-5822.2011.01572.x . 205529660 .
  47. Bergmann GT, Bates ST, Eilers KG, Lauber CL, Caporaso JG, Walters WA, Knight R, Fierer N . The under-recognized dominance of Verrucomicrobia in soil bacterial communities . Soil Biology & Biochemistry . 43 . 7 . 1450–1455 . July 2011 . 22267877 . 3260529 . 10.1016/j.soilbio.2011.03.012 .
  48. Yeoman CJ, Yildirim S, Thomas SM, Durkin AS, Torralba M, Sutton G, Buhay CJ, Ding Y, Dugan-Rocha SP, Muzny DM, Qin X, Gibbs RA, Leigh SR, Stumpf R, White BA, Highlander SK, Nelson KE, Wilson BA . Comparative genomics of Gardnerella vaginalis strains reveals substantial differences in metabolic and virulence potential . PLOS ONE . 5 . 8 . e12411 . August 2010 . 20865041 . 2928729 . 10.1371/journal.pone.0012411 . 2010PLoSO...512411Y . Li . Wenjun . free .
  49. Koren O, Spor A, Felin J, Fåk F, Stombaugh J, Tremaroli V, Behre CJ, Knight R, Fagerberg B, Ley RE, Bäckhed F . Human oral, gut, and plaque microbiota in patients with atherosclerosis . Proceedings of the National Academy of Sciences of the United States of America . 108 Suppl 1 . Supplement_1 . 4592–8 . March 2011 . 20937873 . 3063583 . 10.1073/pnas.1011383107 . 2011PNAS..108.4592K . free .
  50. Marri PR, Paniscus M, Weyand NJ, Rendón MA, Calton CM, Hernández DR, Higashi DL, Sodergren E, Weinstock GM, Rounsley SD, So M . Genome sequencing reveals widespread virulence gene exchange among human Neisseria species . PLOS ONE . 5 . 7 . e11835 . July 2010 . 20676376 . 2911385 . 10.1371/journal.pone.0011835 . 2010PLoSO...511835M . Ahmed . Niyaz . free .
  51. Web site: NIH Human Microbiome Project defines normal bacterial makeup of the body . NIH News . 13 June 2012.
  52. A framework for human microbiome research . Nature . 486 . 7402 . 215–21 . June 2012 . 22699610 . 3377744 . 10.1038/nature11209 . Human Microbiome Project Consortium . 2012Natur.486..215T .
  53. Structure, function and diversity of the healthy human microbiome . Nature . 486 . 7402 . 207–14 . June 2012 . 22699609 . 3564958 . 10.1038/nature11234 . Human Microbiome Project Consortium . 2012Natur.486..207T .
  54. Cantarel BL, Lombard V, Henrissat B . Complex carbohydrate utilization by the healthy human microbiome . PLOS ONE . 7 . 6 . e28742 . 2012 . 22719820 . 3374616 . 10.1371/journal.pone.0028742 . 2012PLoSO...728742C . free .
  55. Wu YW, Rho M, Doak TG, Ye Y . Oral spirochetes implicated in dental diseases are widespread in normal human subjects and carry extremely diverse integron gene cassettes . Applied and Environmental Microbiology . 78 . 15 . 5288–96 . August 2012 . 22635997 . 3416431 . 10.1128/AEM.00564-12 . 2012ApEnM..78.5288W .
  56. Web site: PLOS Collections: Article collections published by the Public Library of Science. collections.plos.org. en. 2018-04-15.
  57. Web site: Manuscript Summaries.
  58. Wilder, C, Sandle T, Sutton S . Implications of the Human Microbiome on Pharmaceutical Microbiology . American Pharmaceutical Review. June 2013 .