JECH Online First, published on September 23, 2014 as 10.1136/jech-2014-203997 Commentary
Metagenomic epidemiology: a new frontier Stephen S Francis,1 Lee W Riley2 A new frontier of basic human biology has opened up, which is changing our understanding of what constitutes the human body. This new knowledge is fuelling a paradigm shift from the dominant, 20th century view that viruses, bacteria and fungi operated independently to cause disease. Now, we are beginning to view a more complex and nuanced interpretation with increased recognition of the importance of commensalism, synergy and balance of microbiota in human health.1 In this commentary we hope to briefly summarise studies into the bacterial and viral microbiome and how this shifting paradigm affects epidemiology.
METAGENOMIC EPIDEMIOLOGY The distribution of human diseases is directly linked to how different people form groups and interact with each other and their environment box 1. This interaction defines a community structure. Community structure has been long recognised as a major determinant of the spread of traditional infectious diseases. Examples range from tuberculosis in crowded slums to the recent spread of Ebola in Africa, where the human behaviours that create community structure often dictate infectious disease spread. These diseases are very sensitive to the social network configuration of the population in which they occur.2 Moreover, social networks within these populations are also important determinants of chronic and traditionally noninfectious diseases. For example, obese individuals are more likely to have other obese individuals as contacts.3 However, even in these ‘non-infectious’ diseases, microorganisms may play a greater role than previously thought. A community is traditionally conceptualised as groups of individuals within ecosystems, which, if disrupted, can lead to disease epidemics. There is, however, another type of community that has only 1
Division of Epidemiology, University of California at Berkeley, Berkeley, California, USA; 2Division of Infectious Disease and Vaccinology, University of California—School of Public Health, Berkeley, California, USA Correspondence to Dr Stephen Francis, University of California at Berkeley—Division of Epidemiology, 101 Haviland Hall, Berkeley, CA 94720-7358, USA; [email protected]
recently come to be recognised as affecting health outcomes—the microbiome. Study of the distribution and determinants of the microbiome structures and their relationship to disease, therefore, constitutes metagenomic epidemiology. As our ability to define the microbes in and on our bodies increases, so will our ability to delineate the ‘normal’ or ‘healthy’ microbiome. This will lead to a more refined distinction between ‘good’ vs ‘bad’ microbes, where ‘good’ can be defined as a microbiome in an equilibrium state, while ‘bad’ is defined as a microbiome in a disrupted state. With diligent study, robust comparison and population level data, we will be able to better define those factors that influence health, disease and community structures. Given our new genetic technological power today, the time is ripe for metagenomic epidemiology.
METAGENOMICS It is estimated that for every human cell there are 10 bacterial cells and for every bacterial cell there are 10 viral particles.4 Such estimates have been made possible by technological spill-over from tools developed from human genome sequencing. Next generation sequencing technologies (NGS) designed to rapidly and accurately sequence the genomes of human communities are now being used to sequence microbial communities or microbiotas. While these technologies continue to improve in speed and cost, the massive amount of data generated from them have produced immense challenges for our bioinformatics capabilities. Cluster-based computing is essential for most metagenomic studies, although some tool kits (QIIME, for example) are bringing 16s rRNA-based bacterial metagenomics accessible to most researchers by streamlining analyses. This ability to sequence all nucleic acids in a given niche without amplification of the targeted region has engendered the new field of metagenomics. Prior to these technologies, culturing was required to study microorganisms. NGS studies now enable unbiased identification and quantification of all known organisms in an ecological niche, be it from the human body or the environment. As a result, a flurry of environmental microbiome studies is afoot ranging from the ocean floor to arctic ice.5 6
Metagenomics has enabled us to identify heretofore unknown microorganisms. In fact, this new technology has permitted the discovery of nucleic acid sequences in the human body and in environmental niches, which cannot be assigned to any known microbial entities—bacteria, viruses, fungi, protozoa or helminthes. We call these entities ‘dark sequences’ analogous to the ‘dark matter’ that astrophysicists hope could explain many of the mysteries of the universe. Not only are there new sequences, but their quantity is vast as well. In fact what had been recognised to exist in the microbial world until 20 years ago represents only a small microcosm of what is now known to exist today. And surely there are more to be discovered. What they are and how they affect the human body remain to be determined. We have only begun to scratch the surface.
THE HUMAN BACTERIAL MICROBIOME The Human Microbiome Project (http:// www.hmpdacc.org/) is contributing as a new basis for understanding what constitutes ‘normal’ human flora. Recent studies show that the core microbiome is essential in metabolic and regulatory processes throughout the body.7 Bacteria are required for basic functions ranging from digestion of lipids and vitamins to glucose homoeostasis. In addition, they can alter host gene expression and modify drug metabolism.8–10 Bacteria also exist as communities with structure, creating an ecosystem that serves as a barrier to microbial pathogens and synergistically interacts with the host. We are just beginning to understand the central role of bacteria in the human gut. It is now clear that our gut microbiota functions like a previously undescribed organ. Like other vital organs, it is susceptible to disease and is essential for health and life itself. Most research in this arena has primarily focused on the gut bacterial flora for three reasons. First, the gut is the most rich and interactive body compartment and second, sample ascertainment is noninvasive. Finally, conducting bacterial metagenomics through 16S rRNA sequencing is relatively straightforward due to shared genes across bacteria and archaea. In this regard, recent technological advances11 have enabled metagenomic community level descriptions for as little as $11 per sample. Such feasibility has put bacterial metagenomics into the hands of population-based epidemiological studies. Many of the diseases of the human intestine result from disruption of the steady-state microbial population structure
SS, et al. J 2014. EpidemiolProduced Community Health Vol 0 No 0 Group Ltd under licence. Copyright Article author (or theirFrancis employer) byMonth BMJ2014 Publishing
1
Commentary within the gut. A clear link exists between the microbiome and host immune response.12 For example, inflammatory bowel disease (IBD) has long been suspected to involve gut microbiota as some patients respond to antibiotics and faecal transplants.13 Indeed, IBD is associated with mutations within bacterial recognition genes.14 15 In this regard, obesity has become of keen interest. Animal studies have shown that transplantation of obese mouse microbiota to germ free mice can induce obesity in the latter,16 proving that certain microbiota aid in transfer of energy to the host and, intriguingly, that the microbiota are transmissible. Human twin studies have also provided interesting data. Discordantly obese mono and dizygotic twins demonstrate an association with diminished Bacteroidetes prevalence and lower overall diversity in the obese twin compared to the non-obese sibling.17 Transplanting faecal microbiota from an obese member of a human discordant twin pair to a germ-free mouse caused the mouse to gain significant increase in body mass and adiposity.18 Further, antibiotic use during the first 6 months of life (which can disrupt the gut microbiota) is associated with development of obesity later in life,19 suggesting a potentially intervenable target. While our gut microbiota may be central players in how we develop disease, they may also be a reservoir for agents that cause disease. For example, our gut microflora act as a reservoir for the horizontal transfer of antimicrobial resistance genes,20 a finding more likely to occur in food animals given low-dose antibiotics as growth promoters. The steady-state intestinal microbial population structure is, of course, maintained by what is introduced into the intestine as food. If an ingested food product is contaminated with a human pathogen (eg, Salmonella), most of the time, the normal gut flora will protect the host against such a pathogen. However, a large inoculum of the pathogen, or a prior exposure of the intestine to an antibiotic, can overcome this protective microbial barrier. Thus, again, it is not only the pathogen, per se, but also the disruption of the balance in the intestinal microbiota that serves as a disease-causing factor. The association of prior exposure to antibiotics and drug-resistant salmonellosis has long been recognised,21 but now, metagenomics can provide a biological explanation for this epidemiological association. Targeted study of the gut microbiome has provided an astounding and novel insight into the mechanistic underpinnings 2
of the function of the human body. In addition to the gut, other body compartments22–24 and other organisms are proving to harbour additional fascinating and unique properties.
THE HUMAN VIROME The totality of viruses within a human, the ‘virome’, is a fascinating and yet challenging (complex and expensive) part of the microbiome. The evolution of viruses has likely paralleled all cellular life since the formation of nucleic acids.25 Their diversity is staggering and it has been postulated that viruses are the most genetically diverse group of organisms on the planet.26 This diversity has not only brought forth some of the most pathogenic species in existence but has also made studying viral communities difficult, especially for those viruses that share no genetic similarity. Recent advances in metagenomics have for the first time allowed a wide classification of all known viruses in a given sample. Two key findings have emerged from these studies. First, viruses of bacteria ( phages) and viruses of humans are both abundant in humans and second, we are just beginning to understand the diversity of ‘normal’ human viral flora. While it is debated that viruses evolve towards avirulence on an evolutionary scale, there is evidence that highly evolved viruses maximise fitness not by increasing but by decreasing pathogenicity. Nevertheless, through millions of generations and unstable genomes, many viruses have ‘mistakenly’ ventured into extremely pathogenic mutations. Yet traditional pathogenicity may be the exception rather than the rule. For example, members of anelloviridae, torque teno virus (TTV), may in fact be the most common human virus, and yet remain relatively understudied because they have not been identified as causing disease in humans. Indeed, most people are likely infected with an Anellovirus, where primary infection often occurs within the first weeks of life. There is also evidence that constant transmission occurs back and forth in adults.27 28 The cloud of genotypes that make up TTV is highly diverse and poorly delineated. It is possible that, akin to oncogenic strains of largely benign human papilloma viruses, specific TTV strains may be associated with disease. In the instance of these highly diverse groups, traditional methods of identification are challenging. Yet metagenomics has opened the door of investigations. TTV is just one organism among many that is highly prevalent yet poorly understood. Strain-specific differences in
pathogenicity have been recognised, for example, between serotypes of enteroviruses or strains of papillomaviruses; some cause diarrhoea or cancer and some do not. To assess the disease-causing potential of TTV and many yet-to-be known common viruses will require population-based studies.
MICROBIAL BALANCE When we study humans we are, in fact, studying groups of microbial ecosystems that interact positively to maintain health and negatively to promote disease. An important concept when considering the human microbiome is that of neutrality. The human body consists of groups of ecosystems that have evolved over tens of thousands of years to establish a stable equilibrium state. When this equilibrium state is disrupted, diseases occur. For example, antibiotic exposure (a synthetic product) disrupts the fine balance that existed in our intestinal microbiota before the era of antibiotics. This resulting ‘dysbiosis’ can trigger diseases like Clostridium difficile colitis. C. difficile is not a ‘bad’ bacterium. Indeed, studies show ∼21% asymptomatic carriage rate.29 It is only when other microbial populations are eliminated that C. difficile becomes ‘bad’. Coprotransplantation works against C. difficile colitis because it restores the balance. A disruption of the ‘local’ intestinal microbiota can also affect body physiology as a whole. Other complex diseases may be caused by similar disruptions of this fine balance—not only in the gut with bacteria but also in other body compartments and with other organisms. The dysbiosis concept can also be extended to viruses. A primary example is that of cytomegalovirus (CMV), where prevalence in healthy adults ranges from 70% to 90%. Infection generally occurs early in life with minor symptoms and otherwise subclinical presentation. Yet lifelong latent infection ensues, a process that is the result of hundreds of thousands of years of coevolution of humans and viruses culminating in dynamic and intricate immunological evasion strategies. In a healthy balanced individual, CMV causes no harm, yet in an immune compromised individual, CMV can be lifethreatening. Dysbiosis resulting in CMV-caused morbidity can be triggered by a number of factors; some are known, such as HIV and immunosuppressive therapies, yet we suspect many others are unidentified. Little is known of the viral interaction between CMV and other common viruses. Yet striking epidemiological associations have been drawn
Francis SS, et al. J Epidemiol Community Health Month 2014 Vol 0 No 0
Commentary between CMV and a broad range of complex diseases from brain tumours to heart disease.30 31 For the first time we have the ability to examine such relationships in terms of their multifactorial biological causal pathways.
LOOKING INTO THE FUTURE The microbiome may be a critical component of the epidemiology of many diseases. Genomic changes in the microbiome are measurable. Through our growing understanding of the metagenome, it is clear that we not only transmit pathogens, but we transmit our commensal flora as well (unpublished data). Through direct or indirect contact, community structure may modify disease risk. In addition to antibiotics for bacteria, other factors could disrupt microbial balance. These may include chemicals (eg, immunotoxic products that alter host immune response and therefore microbial communities), stress (a psychologicallyinduced response that can be immunosuppressive and alter our core microbiome or
risk of dysregulation), contact (direct or indirect contact modification of microbiota occurring on a daily basis), and timing and frequency of infection (early life exposures to both commensal and pathogenic organisms that mould our immune system for the remainder of the life course) and likely many others. The combined tools of metagenomics and epidemiology will lend more insight into human health and disease. As laboratory and bioinformatics methods become streamlined, defining and quantifying known organisms, as well as the expanse of unknown organisms and how they interact, will likely become a critical aspect of this field. Challenges including intrasubject variation and temporal stability will require multiple sampling schemes. Despite these challenges, paired with detailed genetic predisposition, environmental and social exposures, metagenomic epidemiology may be the major key to untangling decades of cryptic disease associations. We are excited by this new tool in our epidemiological quiver.
10
11
12
13
14
15
16
17
18
19
Competing interests None.
Box 1 Definitions: METAGENOMIC EPIDEMIOLOGY- The study of the distribution and determinants of the microbiome structures and their relationship to disease. MICROBIOTA- A community of microorganisms (viruses, bacteria, fungi, archea) living in a defined niche MICROBIOME- The community of commensal, symbiotic, and pathogenic microorganisms (microbiota) or their genomes sharing the human body. METAGENOME- The totality of non-human nucleic acids belonging to all the microbiotas in the human body. (META)TRANSCRIPTOME- Totality of RNA expressed in a cell or population of cells at a given time. The metatranscriptome is the totality of the non-human RNA in or on the body being expressed at any given time. NEXT-GENERATION SEQUENCING- A blanket term describing advanced sequencing platforms beyond traditional Sanger sequencing providing significant advances in throughput and amount of data generated. 16s rRNA Gene- A subunit of all prokaryotic genomes. It is highly conserved yet variable enough across all species of bacteria and archaea to be used for PCR amplification and sequencing for the purpose of phylogenetic analysis.
Provenance and peer review Commissioned; externally peer reviewed. To cite Francis SS, Riley LW. J Epidemiol Community Health Published Online First: [ please include Day Month Year] doi:10.1136/jech-2014-203997
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J Epidemiol Community Health 2014;0:1–3. doi:10.1136/jech-2014-203997
REFERENCES 1
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Honda K, Littman DR. The microbiome in infectious disease and inflammation. Annu Rev Immunol 2012;30:759–95. Keeling MJ, Eames KT. Networks and epidemic models. J R Soc Interface 2005;2:295–307. Christakis NA, Fowler JH. The spread of obesity in a large social network over 32 Years. N Engl J Med 2007;357:370–9. Clemente JC, Ursell LK, Parfrey LW, et al. The impact of the gut microbiota on human health: an integrative view. Cell 2012;148:1258–70. Varin T, Lovejoy C, Jungblut AD, et al. Metagenomic analysis of stress genes in microbial mat communities from Antarctica and the High Arctic. Appl Environ Microbiol 2012;78:549–59. Yoshida M, Takaki Y, Eitoku M, et al. Metagenomic analysis of viral communities in (hado)pelagic sediments. PLoS ONE 2013;8:e57271. Aagaard K, Petrosino J, Keitel W, et al. The Human Microbiome Project strategy for comprehensive sampling of the human microbiome and why it matters. FASEB J 2013;27:1012–22. Clayton TA, Baker D, Lindon JC, et al. Pharmacometabonomic identification of a significant host-microbiome metabolic interaction affecting human drug metabolism. Proc Natl Acad Sci USA 2009;106:14728–33. Devaraj S, Hemarajata P, Versalovic J. The human gut microbiome and body metabolism: implications for obesity and diabetes. Clin Chem 2013;59:617–28.
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Jones ML, Martoni CJ, Ganopolsky JG, et al. The human microbiome and bile acid metabolism: dysbiosis, dysmetabolism, disease and intervention. Expert Opin Biol Th 2014;14:467–82. Caporaso JG, Lauber CL, Walters WA, et al. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc Natl Acad Sci USA 2011;108(Suppl 1):4516–22. Littman DR, Pamer EG. Role of the commensal microbiota in normal and pathogenic host immune responses. Cell Host Microbe 2011;10:311–23. Brown AC. Ulcerative colitis, Crohn’s disease and irritable bowel syndrome patients need fecal transplant research and treatment. J Crohns Colitis 2014;8:179. Ogura Y, Bonen DK, Inohara N, et al. A frameshift mutation in NOD2 associated with susceptibility to Crohn’s disease. Nature 2001;411:603–6. Hugot JP, Chamaillard M, Zouali H, et al. Association of NOD2 leucine-rich repeat variants with susceptibility to Crohn’s disease. Nature 2001;411:599–603. Turnbaugh PJ, Ley RE, Mahowald MA, et al. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 2006;444:1027–31. Turnbaugh PJ, Ridaura VK, Faith JJ, et al. The effect of diet on the human gut microbiome: a metagenomic analysis in humanized gnotobiotic mice. Sci Transl Med 2009;1:6ra14. Ridaura VK, Faith JJ, Rey FE, et al. Gut microbiota from twins discordant for obesity modulate metabolism in mice. Science 2013;341:1241214. Ajslev TA, Andersen CS, Gamborg M, et al. Childhood overweight after establishment of the gut microbiota: the role of delivery mode, pre-pregnancy weight and early administration of antibiotics. Int J Obesity 2011;35:522–9. Penders J, Stobberingh EE, Savelkoul PHM, et al. The human microbiome as a reservoir of antimicrobial resistance. Front Microbiol 2013;4:87. Riley LW, Cohen ML, Seals JE, et al. Importance of host factors in human salmonellosis caused by multiresistant strains of Salmonella. J Infect Dis 1984;149:878–83. Bogdanos DP, Smyk D, Shoenfeld Y. The microbiome of the lung. Isr Med Assoc J 2013;15:766–7. Chen YE, Tsao H. The skin microbiome: current perspectives and future challenges. J Am Acad Dermatol 2013;69:143–55. Ma B, Forney LJ, Ravel J. Vaginal microbiome: rethinking health and disease. Annu Rev Microbiol 2012;66:371–89. Koonin EV, Martin W. On the origin of genomes and cells within inorganic compartments. Trends Genet 2005;21:647–54. Suttle CA. Viruses in the sea. Nature 2005;437:356–61. Davidson I, Shulman LM. Unraveling the puzzle of human anellovirus infections by comparison with avian infections with the chicken anemia virus. Virus Res 2008;137:1–15. TeKippe EM, Wylie KM, Deych E, et al. Increased prevalence of anellovirus in pediatric patients with fever. PLoS ONE 2012;7:e50937. Alasmari F, Seiler SM, Hink T, et al. Prevalence and risk factors for asymptomatic Clostridium difficile Carriage. Clin Infect Dis 2014;59:216–22. Cobbs CS, Harkins L, Samanta M, et al. Human cytomegalovirus infection and expression in human malignant glioma. Cancer Res 2002;62:3347–50. Nieto FJ, Adam E, Sorlie P, et al. Cohort study of cytomegalovirus infection as a risk factor for carotid intimal-medial thickening, a measure of subclinical atherosclerosis. Circulation 1996;94:922–7.
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Metagenomic epidemiology: a new frontier Stephen S Francis,1 Lee W Riley2 A new frontier of basic human biology has opened up, which is changing our understanding of what constitutes the human body. This new knowledge is fuelling a paradigm shift from the dominant, 20th century view that viruses, bacteria and fungi operated independently to cause disease. Now, we are beginning to view a more complex and nuanced interpretation with increased recognition of the importance of commensalism, synergy and balance of microbiota in human health.1 In this commentary we hope to briefly summarise studies into the bacterial and viral microbiome and how this shifting paradigm affects epidemiology.
METAGENOMIC EPIDEMIOLOGY The distribution of human diseases is directly linked to how different people form groups and interact with each other and their environment box 1. This interaction defines a community structure. Community structure has been long recognised as a major determinant of the spread of traditional infectious diseases. Examples range from tuberculosis in crowded slums to the recent spread of Ebola in Africa, where the human behaviours that create community structure often dictate infectious disease spread. These diseases are very sensitive to the social network configuration of the population in which they occur.2 Moreover, social networks within these populations are also important determinants of chronic and traditionally noninfectious diseases. For example, obese individuals are more likely to have other obese individuals as contacts.3 However, even in these ‘non-infectious’ diseases, microorganisms may play a greater role than previously thought. A community is traditionally conceptualised as groups of individuals within ecosystems, which, if disrupted, can lead to disease epidemics. There is, however, another type of community that has only 1
Division of Epidemiology, University of California at Berkeley, Berkeley, California, USA; 2Division of Infectious Disease and Vaccinology, University of California—School of Public Health, Berkeley, California, USA Correspondence to Dr Stephen Francis, University of California at Berkeley—Division of Epidemiology, 101 Haviland Hall, Berkeley, CA 94720-7358, USA; [email protected]
recently come to be recognised as affecting health outcomes—the microbiome. Study of the distribution and determinants of the microbiome structures and their relationship to disease, therefore, constitutes metagenomic epidemiology. As our ability to define the microbes in and on our bodies increases, so will our ability to delineate the ‘normal’ or ‘healthy’ microbiome. This will lead to a more refined distinction between ‘good’ vs ‘bad’ microbes, where ‘good’ can be defined as a microbiome in an equilibrium state, while ‘bad’ is defined as a microbiome in a disrupted state. With diligent study, robust comparison and population level data, we will be able to better define those factors that influence health, disease and community structures. Given our new genetic technological power today, the time is ripe for metagenomic epidemiology.
METAGENOMICS It is estimated that for every human cell there are 10 bacterial cells and for every bacterial cell there are 10 viral particles.4 Such estimates have been made possible by technological spill-over from tools developed from human genome sequencing. Next generation sequencing technologies (NGS) designed to rapidly and accurately sequence the genomes of human communities are now being used to sequence microbial communities or microbiotas. While these technologies continue to improve in speed and cost, the massive amount of data generated from them have produced immense challenges for our bioinformatics capabilities. Cluster-based computing is essential for most metagenomic studies, although some tool kits (QIIME, for example) are bringing 16s rRNA-based bacterial metagenomics accessible to most researchers by streamlining analyses. This ability to sequence all nucleic acids in a given niche without amplification of the targeted region has engendered the new field of metagenomics. Prior to these technologies, culturing was required to study microorganisms. NGS studies now enable unbiased identification and quantification of all known organisms in an ecological niche, be it from the human body or the environment. As a result, a flurry of environmental microbiome studies is afoot ranging from the ocean floor to arctic ice.5 6
Metagenomics has enabled us to identify heretofore unknown microorganisms. In fact, this new technology has permitted the discovery of nucleic acid sequences in the human body and in environmental niches, which cannot be assigned to any known microbial entities—bacteria, viruses, fungi, protozoa or helminthes. We call these entities ‘dark sequences’ analogous to the ‘dark matter’ that astrophysicists hope could explain many of the mysteries of the universe. Not only are there new sequences, but their quantity is vast as well. In fact what had been recognised to exist in the microbial world until 20 years ago represents only a small microcosm of what is now known to exist today. And surely there are more to be discovered. What they are and how they affect the human body remain to be determined. We have only begun to scratch the surface.
THE HUMAN BACTERIAL MICROBIOME The Human Microbiome Project (http:// www.hmpdacc.org/) is contributing as a new basis for understanding what constitutes ‘normal’ human flora. Recent studies show that the core microbiome is essential in metabolic and regulatory processes throughout the body.7 Bacteria are required for basic functions ranging from digestion of lipids and vitamins to glucose homoeostasis. In addition, they can alter host gene expression and modify drug metabolism.8–10 Bacteria also exist as communities with structure, creating an ecosystem that serves as a barrier to microbial pathogens and synergistically interacts with the host. We are just beginning to understand the central role of bacteria in the human gut. It is now clear that our gut microbiota functions like a previously undescribed organ. Like other vital organs, it is susceptible to disease and is essential for health and life itself. Most research in this arena has primarily focused on the gut bacterial flora for three reasons. First, the gut is the most rich and interactive body compartment and second, sample ascertainment is noninvasive. Finally, conducting bacterial metagenomics through 16S rRNA sequencing is relatively straightforward due to shared genes across bacteria and archaea. In this regard, recent technological advances11 have enabled metagenomic community level descriptions for as little as $11 per sample. Such feasibility has put bacterial metagenomics into the hands of population-based epidemiological studies. Many of the diseases of the human intestine result from disruption of the steady-state microbial population structure
SS, et al. J 2014. EpidemiolProduced Community Health Vol 0 No 0 Group Ltd under licence. Copyright Article author (or theirFrancis employer) byMonth BMJ2014 Publishing
1
Commentary within the gut. A clear link exists between the microbiome and host immune response.12 For example, inflammatory bowel disease (IBD) has long been suspected to involve gut microbiota as some patients respond to antibiotics and faecal transplants.13 Indeed, IBD is associated with mutations within bacterial recognition genes.14 15 In this regard, obesity has become of keen interest. Animal studies have shown that transplantation of obese mouse microbiota to germ free mice can induce obesity in the latter,16 proving that certain microbiota aid in transfer of energy to the host and, intriguingly, that the microbiota are transmissible. Human twin studies have also provided interesting data. Discordantly obese mono and dizygotic twins demonstrate an association with diminished Bacteroidetes prevalence and lower overall diversity in the obese twin compared to the non-obese sibling.17 Transplanting faecal microbiota from an obese member of a human discordant twin pair to a germ-free mouse caused the mouse to gain significant increase in body mass and adiposity.18 Further, antibiotic use during the first 6 months of life (which can disrupt the gut microbiota) is associated with development of obesity later in life,19 suggesting a potentially intervenable target. While our gut microbiota may be central players in how we develop disease, they may also be a reservoir for agents that cause disease. For example, our gut microflora act as a reservoir for the horizontal transfer of antimicrobial resistance genes,20 a finding more likely to occur in food animals given low-dose antibiotics as growth promoters. The steady-state intestinal microbial population structure is, of course, maintained by what is introduced into the intestine as food. If an ingested food product is contaminated with a human pathogen (eg, Salmonella), most of the time, the normal gut flora will protect the host against such a pathogen. However, a large inoculum of the pathogen, or a prior exposure of the intestine to an antibiotic, can overcome this protective microbial barrier. Thus, again, it is not only the pathogen, per se, but also the disruption of the balance in the intestinal microbiota that serves as a disease-causing factor. The association of prior exposure to antibiotics and drug-resistant salmonellosis has long been recognised,21 but now, metagenomics can provide a biological explanation for this epidemiological association. Targeted study of the gut microbiome has provided an astounding and novel insight into the mechanistic underpinnings 2
of the function of the human body. In addition to the gut, other body compartments22–24 and other organisms are proving to harbour additional fascinating and unique properties.
THE HUMAN VIROME The totality of viruses within a human, the ‘virome’, is a fascinating and yet challenging (complex and expensive) part of the microbiome. The evolution of viruses has likely paralleled all cellular life since the formation of nucleic acids.25 Their diversity is staggering and it has been postulated that viruses are the most genetically diverse group of organisms on the planet.26 This diversity has not only brought forth some of the most pathogenic species in existence but has also made studying viral communities difficult, especially for those viruses that share no genetic similarity. Recent advances in metagenomics have for the first time allowed a wide classification of all known viruses in a given sample. Two key findings have emerged from these studies. First, viruses of bacteria ( phages) and viruses of humans are both abundant in humans and second, we are just beginning to understand the diversity of ‘normal’ human viral flora. While it is debated that viruses evolve towards avirulence on an evolutionary scale, there is evidence that highly evolved viruses maximise fitness not by increasing but by decreasing pathogenicity. Nevertheless, through millions of generations and unstable genomes, many viruses have ‘mistakenly’ ventured into extremely pathogenic mutations. Yet traditional pathogenicity may be the exception rather than the rule. For example, members of anelloviridae, torque teno virus (TTV), may in fact be the most common human virus, and yet remain relatively understudied because they have not been identified as causing disease in humans. Indeed, most people are likely infected with an Anellovirus, where primary infection often occurs within the first weeks of life. There is also evidence that constant transmission occurs back and forth in adults.27 28 The cloud of genotypes that make up TTV is highly diverse and poorly delineated. It is possible that, akin to oncogenic strains of largely benign human papilloma viruses, specific TTV strains may be associated with disease. In the instance of these highly diverse groups, traditional methods of identification are challenging. Yet metagenomics has opened the door of investigations. TTV is just one organism among many that is highly prevalent yet poorly understood. Strain-specific differences in
pathogenicity have been recognised, for example, between serotypes of enteroviruses or strains of papillomaviruses; some cause diarrhoea or cancer and some do not. To assess the disease-causing potential of TTV and many yet-to-be known common viruses will require population-based studies.
MICROBIAL BALANCE When we study humans we are, in fact, studying groups of microbial ecosystems that interact positively to maintain health and negatively to promote disease. An important concept when considering the human microbiome is that of neutrality. The human body consists of groups of ecosystems that have evolved over tens of thousands of years to establish a stable equilibrium state. When this equilibrium state is disrupted, diseases occur. For example, antibiotic exposure (a synthetic product) disrupts the fine balance that existed in our intestinal microbiota before the era of antibiotics. This resulting ‘dysbiosis’ can trigger diseases like Clostridium difficile colitis. C. difficile is not a ‘bad’ bacterium. Indeed, studies show ∼21% asymptomatic carriage rate.29 It is only when other microbial populations are eliminated that C. difficile becomes ‘bad’. Coprotransplantation works against C. difficile colitis because it restores the balance. A disruption of the ‘local’ intestinal microbiota can also affect body physiology as a whole. Other complex diseases may be caused by similar disruptions of this fine balance—not only in the gut with bacteria but also in other body compartments and with other organisms. The dysbiosis concept can also be extended to viruses. A primary example is that of cytomegalovirus (CMV), where prevalence in healthy adults ranges from 70% to 90%. Infection generally occurs early in life with minor symptoms and otherwise subclinical presentation. Yet lifelong latent infection ensues, a process that is the result of hundreds of thousands of years of coevolution of humans and viruses culminating in dynamic and intricate immunological evasion strategies. In a healthy balanced individual, CMV causes no harm, yet in an immune compromised individual, CMV can be lifethreatening. Dysbiosis resulting in CMV-caused morbidity can be triggered by a number of factors; some are known, such as HIV and immunosuppressive therapies, yet we suspect many others are unidentified. Little is known of the viral interaction between CMV and other common viruses. Yet striking epidemiological associations have been drawn
Francis SS, et al. J Epidemiol Community Health Month 2014 Vol 0 No 0
Commentary between CMV and a broad range of complex diseases from brain tumours to heart disease.30 31 For the first time we have the ability to examine such relationships in terms of their multifactorial biological causal pathways.
LOOKING INTO THE FUTURE The microbiome may be a critical component of the epidemiology of many diseases. Genomic changes in the microbiome are measurable. Through our growing understanding of the metagenome, it is clear that we not only transmit pathogens, but we transmit our commensal flora as well (unpublished data). Through direct or indirect contact, community structure may modify disease risk. In addition to antibiotics for bacteria, other factors could disrupt microbial balance. These may include chemicals (eg, immunotoxic products that alter host immune response and therefore microbial communities), stress (a psychologicallyinduced response that can be immunosuppressive and alter our core microbiome or
risk of dysregulation), contact (direct or indirect contact modification of microbiota occurring on a daily basis), and timing and frequency of infection (early life exposures to both commensal and pathogenic organisms that mould our immune system for the remainder of the life course) and likely many others. The combined tools of metagenomics and epidemiology will lend more insight into human health and disease. As laboratory and bioinformatics methods become streamlined, defining and quantifying known organisms, as well as the expanse of unknown organisms and how they interact, will likely become a critical aspect of this field. Challenges including intrasubject variation and temporal stability will require multiple sampling schemes. Despite these challenges, paired with detailed genetic predisposition, environmental and social exposures, metagenomic epidemiology may be the major key to untangling decades of cryptic disease associations. We are excited by this new tool in our epidemiological quiver.
10
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12
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14
15
16
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Competing interests None.
Box 1 Definitions: METAGENOMIC EPIDEMIOLOGY- The study of the distribution and determinants of the microbiome structures and their relationship to disease. MICROBIOTA- A community of microorganisms (viruses, bacteria, fungi, archea) living in a defined niche MICROBIOME- The community of commensal, symbiotic, and pathogenic microorganisms (microbiota) or their genomes sharing the human body. METAGENOME- The totality of non-human nucleic acids belonging to all the microbiotas in the human body. (META)TRANSCRIPTOME- Totality of RNA expressed in a cell or population of cells at a given time. The metatranscriptome is the totality of the non-human RNA in or on the body being expressed at any given time. NEXT-GENERATION SEQUENCING- A blanket term describing advanced sequencing platforms beyond traditional Sanger sequencing providing significant advances in throughput and amount of data generated. 16s rRNA Gene- A subunit of all prokaryotic genomes. It is highly conserved yet variable enough across all species of bacteria and archaea to be used for PCR amplification and sequencing for the purpose of phylogenetic analysis.
Provenance and peer review Commissioned; externally peer reviewed. To cite Francis SS, Riley LW. J Epidemiol Community Health Published Online First: [ please include Day Month Year] doi:10.1136/jech-2014-203997
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J Epidemiol Community Health 2014;0:1–3. doi:10.1136/jech-2014-203997
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