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===Studies in humans===
===Studies in humans===
*Community sequencing of total gut microbiota taken from obese and lean twins show substantial differences in their compositions. Total population sequences were analyzed to determine the levels of enzymes involved in carbohydrate, lipid, and amino acid metabolism. Obesity is associated with phylum-level differences in the microbiota, a significantly reduced bacterial diversity, and an increase in the population expression of enzymes which result in an increased efficiency of calorie harvest in the diets of the obese twins.<ref>{{cite journal
*Community sequencing of total gut microbiota taken from obese and lean twins show substantial differences in their compositions. Total population sequences were analyzed to determine the levels of enzymes involved in carbohydrate, lipid, and amino acid metabolism. Obesity is associated with phylum-level differences in the microbiota, a significantly reduced bacterial diversity, and an increase in the population expression of enzymes which result in an increased efficiency of calorie harvest in the diets of the obese twins.<ref name=TurnHamaYat2009>{{cite journal
|author=Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, Duncan A, Ley RE, Sogin ML, Jones WJ, Roe BA, Affourtit JP, Egholm M, Henrissat B, Heath AC, Knight R, Gordon1 JI
|author=Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, Duncan A, Ley RE, Sogin ML, Jones WJ, Roe BA, Affourtit JP, Egholm M, Henrissat B, Heath AC, Knight R, Gordon1 JI
|title=A core gut microbiome in obese and lean twins
|title=A core gut microbiome in obese and lean twins
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''For the members of the human microbiome, see [[human microbiome]]''
''For the members of the human microbiome, see [[human microbiome]]''


The human microbiome consists of about 100 trillion microbial cells, outnumbering human cells 10 to 1.<ref>Savage DC (1977) Microbial ecology of the gastrointestinal tract. Annu Rev Microbiol 31:107–133.</ref> Thus it can significantly affect human physiology. For example, in healthy individuals the microbiota provide a wide range of metabolic functions that humans lack.<ref>Gill SR,Pop M, Deboy RT, Eckburg PB, Turnbaugh PJ, Samuel BS, Gordon JI, Relman DA, Fraser-Liggett CM, Nelson KE (2006) Metagenomic analysis of the human distal gut microbiome. Science 312:1355–1359.</ref> In diseased inviduals altered microbiota are associated with diseases such as [[inflammatory bowel disease]]<ref>Aas, J., Gessert, C. E. & Bakken, J. S. Recurrent Clostridium difficile colitis: case series involving 18 patients treated with donor stool administered via a nasogastric tube. Clin. Infect. Dis. 36, 580–585 (2003).</ref> and [[vaginosis]]<ref>Ravel, J. et al. Vaginal microbiome of reproductive-age women. Proc. Natl Acad. Sci. USA 108 (Suppl. 1), 4680–4687 (2011).</ref>. Thus studying the human microbiome is an important task that has been undertaken by initiatives such as the Human Microbiome Project<ref>Peterson, J. et al. The NIH Human Microbiome Project. Genome Res. 19, 2317–2323 (2009).</ref> and MetaHIT<ref name=Qin2010>Qin, J. et al. A human gut microbial gene catalogue established by metagenomic sequencing. Nature 464, 59–65 (2010).</ref>.
The human microbiome consists of about 100 trillion microbial cells, outnumbering human cells 10 to 1.<ref name=Savage1977>{{cite doi|10.1146/annurev.mi.31.100177.000543|noedit}}</ref> Thus it can significantly affect human physiology. For example, in healthy individuals the microbiota provide a wide range of metabolic functions that humans lack.<ref name="GillPop2006">{{Cite pmid|16741115|noedit}}</ref> In diseased inviduals altered microbiota are associated with diseases such as [[inflammatory bowel disease]]<ref name="AasGess2003">{{Cite pmid|12594638|noedit}}</ref> and [[vaginosis]].<ref name="RavelGajer2011">{{Cite pmid|20534435|noedit}}</ref> Thus studying the human microbiome is an important task that has been undertaken by initiatives such as the Human Microbiome Project<ref>Peterson, J. et al. The NIH Human Microbiome Project. Genome Res. 19, 2317–2323 (2009).</ref> and MetaHIT.<ref name="Qin2010">{{Cite pmid|20203603|noedit}}</ref>


===Studying the human microbiome===
===Studying the human microbiome===
[[File:Microbiome_analysis_flowchart.png|thumb|right|Flowchart illustrating how the human microbiome is studied on the DNA level.]]
[[File:Microbiome_analysis_flowchart.png|thumb|right|Flowchart illustrating how the human microbiome is studied on the DNA level.]]


The problem of elucidating the human microbiome is essentially identifying the members of a microbial community which includes bacteria, eukaryotes and viruses. This is done primarily using DNA-based studies, though RNA, protein and metabolite based studies have also been performed.<ref name=Kucz2012>Kuczynski et al. Experimental and analytical tools for studying the human microbiome. Nature Reviews Genetics 13:47–58 (2012).</ref>
The problem of elucidating the human microbiome is essentially identifying the members of a microbial community which includes bacteria, eukaryotes and viruses. This is done primarily using DNA-based studies, though RNA, protein and metabolite based studies have also been performed.<ref name="Kucz2012">{{Cite pmid|22179717|noedit}}</ref> DNA-based microbiome studies typically can be categorized as either targeted amplicon studies or more recently shotgun metagenomic studies. The former focuses on specific known marker genes and is primarily informative taxonomically, while the latter is an entire metagenomic approach which can also be used to study the functional potential of the community. One of the challenges that is present in human microbiome studies but not in other metagenomic studies is to avoid including the host DNA in the study.<ref name="Vest2008">{{Cite pmid|18638418|noedit}}</ref>
DNA-based microbiome studies typically can be categorized as either targeted amplicon studies or more recently shotgun metagenomic studies. The former focuses on specific known marker genes and is primarily informative taxonomically, while the latter is an entire metagenomic approach which can also be used to study the functional potential of the community. One of the challenges that is present in human microbiome studies but not in other metagenomic studies is to avoid including the host DNA in the study.<ref name=Vest2008>Vestheim, H. & Jarman, S. N. Blocking primers to enhance PCR amplification of rare sequences in mixed samples — a case study on prey DNA in Antarctic krill stomachs. Front. Zool. 5, 12 (2008).</ref>


===Presence of a core microbiome===
===Presence of a core microbiome===
Aside from simply elucidating the composition of the human microbiome, one of the major questions involving the human microbiome is whether there is a “core”, that is, whether there is a subset of the community that is shared between most humans<ref name=HK2009>Hamady, M and Knight, R Microbial community profiling for human microbiome projects: Tools, techniques, and challenges. Genome Res. 19: 1141–1152 (2009)</ref>. If there is a core, then it would be possible to associate certain community compositions with disease states, which is one of the goals of the Human Microbiome Project. It is known that the human microbiome is highly variable both within a single subject and between different individuals. For example, the gut microbiota of humans is markedly dissimilar between individuals, a phenomenon which is also observed in mice.<ref>Ley RE et al. (2005) Obesity alters gut microbial ecology. Proc Natl Acad Sci 102:11070–11075.</ref> Hamady and Knight show that one can rule out the possibility that any species is found in more than 0.9% of human guts or on 2% of human hands.<ref name=HK2009/> Although there is very little species level conservation between individuals, it has been shown that this may be a result of functional redundancy as different communities tend to converge on the same functional state.<ref>Turnbaugh PJ et al. A core gut microbiome in obese and lean twins. Nature 457:480–484 (2009).</ref>
Aside from simply elucidating the composition of the human microbiome, one of the major questions involving the human microbiome is whether there is a “core”, that is, whether there is a subset of the community that is shared between most humans.<ref name="HK2009">{{Cite pmid|19383763|noedit}}</ref> If there is a core, then it would be possible to associate certain community compositions with disease states, which is one of the goals of the Human Microbiome Project. It is known that the human microbiome is highly variable both within a single subject and between different individuals. For example, the gut microbiota of humans is markedly dissimilar between individuals, a phenomenon which is also observed in mice.<ref name="LeyBack2005">{{Cite pmid|16033867|noedit}}</ref> Hamady and Knight show that one can rule out the possibility that any species is found in more than 0.9% of human guts or on 2% of human hands.<ref name=HK2009/> Although there is very little species level conservation between individuals, it has been shown that this may be a result of functional redundancy as different communities tend to converge on the same functional state.<ref name="TurnHamady2009">{{Cite pmid|19043404|noedit}}</ref>


==Hologenome theory of evolution==
==Hologenome theory of evolution==
Line 172: Line 171:
Targeted amplicon sequencing relies on having some expectations about the composition of the community that is being studied. In target amplicon sequencing a phylogenetically informative marker is targeted for sequencing. Such a marker should be present in ideally all the expected organisms. It should also evolve in such a way that it is conserved enough that primers can target genes from a wide range of organisms while evolving quickly enough to allow for finer resolution at the taxonomic level. A common marker for human microbiome studies is the 16S rRNA gene (the sequence of rDNA which encodes for the rRNA molecule).<ref name=Kucz2012/> Since ribosomes are present in all living organisms, using the 16S rDNA allows for DNA to be amplified from many more organisms than if another marker were used. The 16S rDNA gene contains both slowly evolving regions and fast evolving regions; the former can be used to design broad primers while the latter allow for finer taxonomic distinction. However, species level resolution is not typically possible using the 16S rDNA. Primer selection is an important step, as anything that cannot be targeted by the primer will not be amplified and thus will not be detected. Different sets of primers have been shown to amplify different taxonomic groups due to sequence variation.
Targeted amplicon sequencing relies on having some expectations about the composition of the community that is being studied. In target amplicon sequencing a phylogenetically informative marker is targeted for sequencing. Such a marker should be present in ideally all the expected organisms. It should also evolve in such a way that it is conserved enough that primers can target genes from a wide range of organisms while evolving quickly enough to allow for finer resolution at the taxonomic level. A common marker for human microbiome studies is the 16S rRNA gene (the sequence of rDNA which encodes for the rRNA molecule).<ref name=Kucz2012/> Since ribosomes are present in all living organisms, using the 16S rDNA allows for DNA to be amplified from many more organisms than if another marker were used. The 16S rDNA gene contains both slowly evolving regions and fast evolving regions; the former can be used to design broad primers while the latter allow for finer taxonomic distinction. However, species level resolution is not typically possible using the 16S rDNA. Primer selection is an important step, as anything that cannot be targeted by the primer will not be amplified and thus will not be detected. Different sets of primers have been shown to amplify different taxonomic groups due to sequence variation.


Targeted studies of eukaryotic and viral communities are limited<ref>Marchesi, J. R. Prokaryotic and eukaryotic diversity of the human gut. Adv. Appl. Microbiol. 72, 43–62 (2010).</ref> and subject to the challenge of excluding host DNA from amplification and the reduced eukaryotic and viral biomass in the human microbiome.<ref name=Vest2008/>
Targeted studies of eukaryotic and viral communities are limited<ref name="Marchesi2010">{{Cite pmid|20602987|noedit}}</ref> and subject to the challenge of excluding host DNA from amplification and the reduced eukaryotic and viral biomass in the human microbiome.<ref name=Vest2008/>


After the amplicons are sequenced, phylogeny is then used to infer the composition of the microbial community. This is done by clustering the amplicons into operational taxonomic units (OTUs) and inferring phylogenetic relationships between the sequences. An important point is that the scale of data is extensive, and further approaches must be taken to identify patterns from the available information. Tools used to analyze the data include VAMPS, QIIME<ref>Caporaso, J. G. et al. QIIME allows analysis of high-throughput community sequencing data. Nature Methods 7, 335–336 (2010).</ref> and mothur<ref>Schloss, P. D. et al. Introducing mothur: open-source, platform-independent, community-supported software for describing and comparing microbial communities. Appl. Environ. Microbiol. 75, 7537–7541 (2009).</ref>.
After the amplicons are sequenced, phylogeny is then used to infer the composition of the microbial community. This is done by clustering the amplicons into operational taxonomic units (OTUs) and inferring phylogenetic relationships between the sequences. An important point is that the scale of data is extensive, and further approaches must be taken to identify patterns from the available information. Tools used to analyze the data include VAMPS, QIIME<ref name="CapoKucz2010">{{Cite pmid|20383131|noedit}}</ref> and mothur.<ref name="SchlossWest2009">{{Cite pmid|19801464|noedit}}</ref>


===Metagenomic sequencing===
===Metagenomic sequencing===
Metagenomics is also used extensively for studying microbial communities<ref name=Qin2010/><ref>Turnbaugh, P. J. et al. A core gut microbiome in obese and lean twins. Nature 457, 480–484 (2009).</ref><ref>Tringe, S. G. et al. Comparative metagenomics of microbial communities. Science 308, 554–557 (2005).</ref>. In metagenomic sequencing DNA is recovered directly from environmental samples in an untargeted manner with the goal of obtaining an unbiased sample from all genes from all members of the community. Recent studies use shotgun Sanger sequencing or pyrosequencing to recover the sequences of the reads. The reads can then be assembled into contigs. To determine the phylogenetic identity of a sequence, it is compared to available full genome sequences using methods such as BLAST. One drawback of this approach is that many members of microbial communities do not have a representative sequenced genome.<ref name=Kucz2012/>
Metagenomics is also used extensively for studying microbial communities<ref name=Qin2010/><ref name=TurnHamaYat2009/><ref>Tringe, S. G. et al. Comparative metagenomics of microbial communities. Science 308, 554–557 (2005).</ref>. In metagenomic sequencing DNA is recovered directly from environmental samples in an untargeted manner with the goal of obtaining an unbiased sample from all genes from all members of the community. Recent studies use shotgun Sanger sequencing or pyrosequencing to recover the sequences of the reads. The reads can then be assembled into contigs. To determine the phylogenetic identity of a sequence, it is compared to available full genome sequences using methods such as BLAST. One drawback of this approach is that many members of microbial communities do not have a representative sequenced genome.<ref name=Kucz2012/>


Despite the fact that metagenomics is limited by the availability of reference sequences, one significant advantage of metagenomics over targeted amplicon sequencing is that metagenomics data can elucidate the functional potential of the community DNA.<ref>Muller, J. et al. eggNOG v2.0: extending the evolutionary genealogy of genes with enhanced non-supervised orthologous groups, species and functional annotations. Nucleic Acids Res. 38, D190–D195 (2010).</ref><ref>Kanehisa, M., Goto, S., Furumichi, M., Tanabe, M. & Hirakawa, M. KEGG for representation and analysis of molecular networks involving diseases and drugs. Nucleic Acids Res. 38, D355–D360 (2010).</ref> Targeted gene surveys cannot do this as they only reveal the phylogenetic relationship between the same gene from different organisms. Functional analysis is done by comparing the recovered sequences to databases of metagenomic annotations such as KEGG. The metabolic pathways that these genes are involved in can then be predicted with tools such as MG-RAST<ref>Meyer, F. et al. The metagenomics RAST server — a public resource for the automatic phylogenetic and functional analysis of metagenomes. BMC Bioinformatics 9, 386 (2008).</ref>, CAMERA<ref>Sun, S. et al. Community Cyberinfrastructure for Advanced Microbial Ecology Research and Analysis: the CAMERA resource. Nucleic Acids Res. 39, D546–D551 (2011).</ref> and IMG/M<ref>Markowitz, V. M. et al. IMG/M: a data management and analysis system for metagenomes. Nucleic Acids Res. 36, D534–D538 (2008).</ref>.
Despite the fact that metagenomics is limited by the availability of reference sequences, one significant advantage of metagenomics over targeted amplicon sequencing is that metagenomics data can elucidate the functional potential of the community DNA.<ref name="MullerSzkl2010">{{Cite pmid|19900971|noedit}}</ref><ref name="KanehisaGoto2010">{{Cite pmid|19880382|noedit}}</ref> Targeted gene surveys cannot do this as they only reveal the phylogenetic relationship between the same gene from different organisms. Functional analysis is done by comparing the recovered sequences to databases of metagenomic annotations such as KEGG. The metabolic pathways that these genes are involved in can then be predicted with tools such as MG-RAST,<ref name="MeyerPaar2008">{{Cite pmid|18803844|noedit}}</ref> CAMERA<ref name="SunChen2011">{{Cite pmid|21045053|noedit}}</ref> and IMG/M.<ref name="MarkowitzIvan2008">{{Cite pmid|17932063|noedit}}</ref>


===RNA and protein-based approaches===
===RNA and protein-based approaches===
Metatranscriptomics studies have been performed to study the gene expression of microbial communities through methods such as the pyrosequencing of extracted RNA<ref>Shi, Y., Tyson, G. W. & DeLong, E. F. Metatranscriptomics reveals unique microbial small RNAs in the ocean’s water column. Nature 459, 266–269 (2009)</ref>. Structure based studies have also identified ncRNAs such as ribozymes from microbiota<ref>Jimenez et al. Structure-based search reveals hammerhead ribozymes in the human microbiome. Journal of Biological Chemistry.286, 7737–7743. (2011).</ref>. Metaproteomics is a new approach that studies the proteins expressed by microbiota, giving insight into its functional potential <ref>Maron, P. A., Ranjard, L., Mougel, C. & Lemanceau, P. Metaproteomics: a new approach for studying functional microbial ecology. Microb. Ecol. 53, 486–493 (2007).</ref>
Metatranscriptomics studies have been performed to study the gene expression of microbial communities through methods such as the pyrosequencing of extracted RNA.<ref name="ShiTyson2009">{{Cite pmid|19444216|noedit}}</ref> Structure based studies have also identified ncRNAs such as ribozymes from microbiota.<ref name="JimenezDel2011">{{Cite pmid|21257745|noedit}}</ref> Metaproteomics is a new approach that studies the proteins expressed by microbiota, giving insight into its functional potential.<ref name="MaronRan2007">{{Cite pmid|17431707|noedit}}</ref>


==Projects==
==Projects==
The [[Human Microbiome Project]] (HMP) is a United States [[National Institutes of Health]] initiative with the goal of identifying and characterizing the microorganisms which are found in association with both healthy and diseased humans (their microbial flora). Launched in 2008, it is a five-year project, best characterized as a feasibility study, and has a total budget of $115 million. The ultimate goal of this and similar NIH-sponsored microbiome projects is to test if changes in the human microbiome are associated with human health or disease.
The [[Human Microbiome Project]] (HMP) is a United States [[National Institutes of Health]] initiative with the goal of identifying and characterizing the microorganisms which are found in association with both healthy and diseased humans (their microbial flora). Launched in 2008, it is a five-year project, best characterized as a feasibility study, and has a total budget of $115 million. The ultimate goal of this and similar NIH-sponsored microbiome projects is to test if changes in the human microbiome are associated with human health or disease.


The [[Earth Microbiome Project]] (EMP) is an initiative to collect natural samples and analyze the microbial community around the globe. Microbes are highly abundant and diverse. Experts have estimated that there are 1.3 x 10^28 archaeal cells, 3.1 x 10^28 bacterial cells and 1x10^30 virus particles in the ocean.<ref>Suttle, C. a. (2007). Marine viruses--major players in the global ecosystem. Nature reviews. Microbiology, 5(10), 801–12. doi:10.1038/nrmicro1750</ref><ref name=CSS2002>Curtis, T. P., Sloan, W. T., & Scannell, J. W. (2002). Estimating prokaryotic diversity and its limits. Proceedings of the National Academy of Sciences of the United States of America, 99(16), 10494–9. doi:10.1073/pnas.142680199</ref> Not only rich in abundance, microbes pose great diversity that is largely unknown. The number of bacteria has roughly been estimated to 160 per ml in ocean water, 6,400-38,000 per g in soil, and 70 per ml sewage works<ref name=CSS2002/>. These microbes work together and act as an important role in the ecological system such as nutrient recycling. However, only 1% of the genetic variation has been characterized<ref>Liu, W.-tso, Marsh, T. L., & Cheng, H. (1997). Characterization of microbial diversity by determining terminal restriction fragment length polymorphisms of genes encoding 16S Characterization of Microbial Diversity by Determining Terminal Restriction Fragment Length Polymorphisms of Genes Encoding 16S. Microbiology. </ref>. Therefore, the specific interactions between microbes are largely unknown. The EMP aims to process as many as 200,000 samples and set up an inventory of microbial diversity in different biomes. In other words, we need a complete database of microbes on earth in order characterize environments and ecosystems by microbial composition and interaction. Using these data, we could perhaps propose new ecological and evolutionary theories.
The [[Earth Microbiome Project]] (EMP) is an initiative to collect natural samples and analyze the microbial community around the globe. Microbes are highly abundant and diverse. Experts have estimated that there are 1.3 x 10^28 archaeal cells, 3.1 x 10^28 bacterial cells and 1x10^30 virus particles in the ocean.<ref name="Suttle2007">{{Cite pmid|17853907|noedit}}</ref><ref name="CSS2002">{{Cite pmid|12097644|noedit}}</ref> Not only rich in abundance, microbes pose great diversity that is largely unknown. The number of bacteria has roughly been estimated to 160 per ml in ocean water, 6,400-38,000 per g in soil, and 70 per ml sewage works<ref name=CSS2002/>. These microbes work together and act as an important role in the ecological system such as nutrient recycling. However, only 1% of the genetic variation has been characterized.<ref name="LiuMarsh1977">{{Cite pmid|9361437|noedit}}</ref> Therefore, the specific interactions between microbes are largely unknown. The EMP aims to process as many as 200,000 samples and set up an inventory of microbial diversity in different biomes. In other words, we need a complete database of microbes on earth in order characterize environments and ecosystems by microbial composition and interaction. Using these data, we could perhaps propose new ecological and evolutionary theories.


==Conclusion==
==Conclusion==

Revision as of 04:53, 6 March 2012

Depiction of the human body and bacteria that predominate

A microbiome is the totality of microbes, their genetic elements (genomes), and environmental interactions in a particular environment. The term "microbiome" was coined by Joshua Lederberg, who argued that microorganisms inhabiting the human body should be included as part of the human genome, because of their influence on human physiology. The human body contains over 10 times more microbial cells than human cells.[1] [2]

Microbiomes are being characterized in many other environments as well, including soil, seawater and freshwater systems.

Introduction

All plants and animals, from protists to humans, live in close association with microbial organisms. Up until relatively recently, however, the interactions of plants and animals with the microbial world have been defined mostly in the context of disease states and a relatively small number of symbiotic case studies. Organisms do not live in isolation, but have evolved in the context of complex communities. A number of advances have driven a change in this perception, which include, notably, the current ease of performing genomic and gene expression analyses of single cells and even entire microbial communities in the new disciplines of metagenomics and metatranscriptonomics, along with massive databases enabling this information to be accessible to researchers across multiple disciplines, and methods of mathematical analysis that enable sense to be made of complex data sets. It has become increasingly appreciated that microbes play an important part of an organism's phenotype far beyond the occasional symbiotic case study.[3]

Indeed, an organism's complement of microbial inhabitants can be considered as a forgotten organ.

Case studies

The following sections present various case studies which illustrate this concept. There is a strengthening consensus among evolutionary biologists that one should not separate an organism's genes from the context of its resident microbes.

Studies in humans

  • Community sequencing of total gut microbiota taken from obese and lean twins show substantial differences in their compositions. Total population sequences were analyzed to determine the levels of enzymes involved in carbohydrate, lipid, and amino acid metabolism. Obesity is associated with phylum-level differences in the microbiota, a significantly reduced bacterial diversity, and an increase in the population expression of enzymes which result in an increased efficiency of calorie harvest in the diets of the obese twins.[4]
  • Type I diabetes is an autoimmune disease that is correlated with a multiplicity of predisposing factors, including an aberrant intestinal microbiota, a leaky intestinal mucosal barrier, and intrinsic differences in immune responsiveness. Various animal models for diabetes have shown a role for bacteria in the onset of the disease. Community DNA sequencing of intestinal flora comparing healthy and autoimmune children showed that autoimmune children had relatively unstable gut biomes with significantly decreased levels of species diversity, and the populations showed large scale replacement of Firmicutes species with Bacteroidetes species.[5]
  • Human skin represents the most extensive organ of the human body, whose functions include protecting the body from pathogens, preventing loss of moisture, and participating in the regulation of body temperature. Considered as an ecosystem, the skin supports a range of microbial communities that live in distinct niches. Hair-covered scalp lies but a few inches from exposed neck, which in turn lies inches away from moist hairy underarms, but these niches are, at a microbial level, as distinct as a temperate forest would be compared with savanna and tropical rain forest. Studies characterizing the microbiota that inhabit these different niches are beginning to provide insights into the balance between skin health and disease.[6]
  • Prevention of urogenital diseases in women depends on healthy vaginal microbiomes, but what is meant by "healthy" has not been understood. Community population studies using advanced sequencing methodologies (including pyrosequencing) are yielding insights into the range of microbial diversity in the human vagina. An unexpected finding was the prevalance of Prevotella species, which are known to positively affect the growth of Gardnerella vaginalis and Peptostreptococcus anaerobius, two species linked to bacterial vaginosis, by providing these disease-associated bacteria with key nutrients.[7]
  • A proposal has been made to classify people by enterotype, based on the composition of the gut microbiome. By combining 22 newly sequenced fecal metagenomes of individuals from four countries with previously published data sets, three robust clusters were identified that are not nation or continent specific.[8][9]
  • The traditional view of the immune system is that it is a complex assembly of organs, tissues, cells and molecules that work together to eliminate pathogens. Modifications to this traditional view, that the immune system has evolved to control microbes, have come from the discovery that in certain cases, microbes control the immune system. It is well known that germ-free animals possess an underdeveloped immune system. The biology of the recently discovered T helper 17 cells (Th17) has generated great interest in recent years due to their key role in inflammatory processes. Excessive amounts of the cell are thought to play a key role in autoimmune diseases such as multiple sclerosis, psoriasis, juvenile diabetes, rheumatoid arthritis, Crohn's disease, and autoimmune uveitis. It has been discovered that specific microbiota direct the differentiation of Th17 cells in the mucosa of the small intestine.[10]

Animal studies

  • A massive, worldwide decline in amphibian populations has been well-publicised. Habitat loss and over-exploitation account for part of the problem, but many other processes seem to be at work. The spread of the virulent fungal disease chytridiomycosis represents an enigma.[11] The ability of some species to coexist with the causative agent Batrachochytrium dendrobatidis appears to be due to the expression of antimicrobial skin peptides along with the presence of symbiotic microbes that benefit the host by resisting pathogen colonization or inhibiting their growth while being themselves resistant to high concentrations of antimicrobial skin peptides.[12]
  • The bovine rumen harbors a complex microbiome that converts plant cell wall biomass into proteins, short chain fatty acids, and gases. Multiple species are involved in this conversion. Traditional methods of characterizing the microbial population, based on culture analysis, missed many of the participants in this process. Comparative metagenomic studies yielded the surprising result that individual steer had markedly different community structures, predicted phenotype, and metabolic potentials,[13] even though they were fed identical diets, were housed together, and were apparently functionally identical in their utilization of plant cell wall resouces.
  • Leaf-cutter ants form huge underground colonies with millions of workers, each colony harvesting hundreds of kilograms of leaves each year. Unable to digest the cellulose in the leaves directly, they maintain fungus gardens that are the colony's primary food source. The fungus itself does not digest cellulose. Instead, a microbial community containing a diversity of bacteria is responsible for cellulose digestion. Analysis of the microbial population's genomic content by community metagenome sequencing methods revealed the presence of many genes with a role in cellulose digestion. This microbiome's predicted carbohydrate-degrading enzyme profile is similar to that of the bovine rumen, but the species composition is almost entirely different.[14]

Plant studies

  • Plants exhibit a broad range of relationships with symbiotic microorganisms, ranging from parasitism, in which the association is disadvantageous to the host organism, to mutualism, in which the association is beneficial to both, to commensalism, in which the symbiont benefits while the host is not affected. Exchange of nutrients between symbiotic partners is an important part of the relationship: it may be bidirectional or unidirectional, and it may be context dependent. The strategies for nutrient exchange are highly diverse. Oomycetes and fungi have, through convergent evolution, developed similar morphology and occupy similar ecological niches. They develop hyphae, filamentous structures that penetrate the host cell. In those cases where the association is mutualistic, the plant exchanges hexose sugars for inorganic phosphate from the fungal symbiont. It is speculated that such associations, which are very ancient, may have aided plants when they first colonized land.[15][16]
  • A huge range of bacterial symbionts colonize plants. Many of these are pathogenic, but others known as plant-growth promoting bacteria (PGPB) provide the host with essential services such as nitrogen fixation, solubilization of minerals such as phosphorus, synthesis of plant hormones, direct enhancement of mineral uptake, and protection from pathogens.[17][18] PGPBs may protect plants from pathogens by competing with the pathogen for an ecological niche or a substrate, producing inhibitory allelochemicals, or inducing systemic resistance in host plants to the pathogen[19]

Human microbiome

For the members of the human microbiome, see human microbiome

The human microbiome consists of about 100 trillion microbial cells, outnumbering human cells 10 to 1.[20] Thus it can significantly affect human physiology. For example, in healthy individuals the microbiota provide a wide range of metabolic functions that humans lack.[21] In diseased inviduals altered microbiota are associated with diseases such as inflammatory bowel disease[22] and vaginosis.[23] Thus studying the human microbiome is an important task that has been undertaken by initiatives such as the Human Microbiome Project[24] and MetaHIT.[25]

Studying the human microbiome

Flowchart illustrating how the human microbiome is studied on the DNA level.

The problem of elucidating the human microbiome is essentially identifying the members of a microbial community which includes bacteria, eukaryotes and viruses. This is done primarily using DNA-based studies, though RNA, protein and metabolite based studies have also been performed.[26] DNA-based microbiome studies typically can be categorized as either targeted amplicon studies or more recently shotgun metagenomic studies. The former focuses on specific known marker genes and is primarily informative taxonomically, while the latter is an entire metagenomic approach which can also be used to study the functional potential of the community. One of the challenges that is present in human microbiome studies but not in other metagenomic studies is to avoid including the host DNA in the study.[27]

Presence of a core microbiome

Aside from simply elucidating the composition of the human microbiome, one of the major questions involving the human microbiome is whether there is a “core”, that is, whether there is a subset of the community that is shared between most humans.[28] If there is a core, then it would be possible to associate certain community compositions with disease states, which is one of the goals of the Human Microbiome Project. It is known that the human microbiome is highly variable both within a single subject and between different individuals. For example, the gut microbiota of humans is markedly dissimilar between individuals, a phenomenon which is also observed in mice.[29] Hamady and Knight show that one can rule out the possibility that any species is found in more than 0.9% of human guts or on 2% of human hands.[28] Although there is very little species level conservation between individuals, it has been shown that this may be a result of functional redundancy as different communities tend to converge on the same functional state.[30]

Hologenome theory of evolution

Main article: Hologenome theory of evolution

The hologenome theory proposes that the object of natural selection is not the individual organism, but the organism together with its associated microbial communities.

The hologenome theory originated in studies on coral reefs. Coral reefs are the largest structures created by living organisms, and contain abundant and highly complex microbial communities. Over the past several decades, major declines in coral populations have occurred. Climate change, water pollution and over-fishing are three stress factors that have been described as leading to disease susceptibility. Over twenty different coral diseases have been described, but of these, only a handful have had their causative agents isolated and characterized. Coral bleaching is the most serious of these diseases. In the Mediterranean Sea, the bleaching of Oculina patagonica was first described in 1994 and shortly determined to be due to infection by Vibrio shiloi. From 1994 to 2002, bacterial bleaching of O. patagonica occurred every summer in the eastern Mediterranean. Surprisingly, however, after 2003, O. patagonica in the eastern Mediterranean has been resistant to V. shiloi infection, although other diseases still cause bleaching. The surprise stems from the knowledge that corals are long lived, with lifespans on the order of decades,[31] and do not have adaptive immune systems. Their innate immune systems do not produce antibodies, and they should seemingly not be able to respond to new challenges except over evolutionary time scales. The puzzle of how corals managed to acquire resistance to a specific pathogen led Eugene Rosenberg and Ilana Zilber-Rosenburg to propose the Coral Probiotic Hypothesis. This hypothesis proposes that a dynamic relationship exists between corals and their symbiotic microbial communities. By altering its composition, this "holobiont" can adapt to changing environmental conditions far more rapidly than by genetic mutation and selection alone. Extrapolating this hypothesis of adaptation and evolution to other organisms, including higher plants and animals, led to the proposal of the Hologenome Theory of Evolution.[32]

The hologenome theory is still being debated.[33] A major criticism has been the claim that V. shiloi was misidentified as the causative agent of coral bleaching, and that its presence in bleached O. patagonica was simply that of opportunistic colonization.[34] If this is true, the basic observation leading to the theory would be invalid. Nevertheless, the theory has gained significant popularity as a way of explaining rapid changes in adaptation that cannot otherwise be explained by traditional mechanisms of natural selection. For those who accept the hologenome theory, the holobiont has become the principal unit of natural selection.

Research methods

Targeted amplicon sequencing

Targeted amplicon sequencing relies on having some expectations about the composition of the community that is being studied. In target amplicon sequencing a phylogenetically informative marker is targeted for sequencing. Such a marker should be present in ideally all the expected organisms. It should also evolve in such a way that it is conserved enough that primers can target genes from a wide range of organisms while evolving quickly enough to allow for finer resolution at the taxonomic level. A common marker for human microbiome studies is the 16S rRNA gene (the sequence of rDNA which encodes for the rRNA molecule).[26] Since ribosomes are present in all living organisms, using the 16S rDNA allows for DNA to be amplified from many more organisms than if another marker were used. The 16S rDNA gene contains both slowly evolving regions and fast evolving regions; the former can be used to design broad primers while the latter allow for finer taxonomic distinction. However, species level resolution is not typically possible using the 16S rDNA. Primer selection is an important step, as anything that cannot be targeted by the primer will not be amplified and thus will not be detected. Different sets of primers have been shown to amplify different taxonomic groups due to sequence variation.

Targeted studies of eukaryotic and viral communities are limited[35] and subject to the challenge of excluding host DNA from amplification and the reduced eukaryotic and viral biomass in the human microbiome.[27]

After the amplicons are sequenced, phylogeny is then used to infer the composition of the microbial community. This is done by clustering the amplicons into operational taxonomic units (OTUs) and inferring phylogenetic relationships between the sequences. An important point is that the scale of data is extensive, and further approaches must be taken to identify patterns from the available information. Tools used to analyze the data include VAMPS, QIIME[36] and mothur.[37]

Metagenomic sequencing

Metagenomics is also used extensively for studying microbial communities[25][4][38]. In metagenomic sequencing DNA is recovered directly from environmental samples in an untargeted manner with the goal of obtaining an unbiased sample from all genes from all members of the community. Recent studies use shotgun Sanger sequencing or pyrosequencing to recover the sequences of the reads. The reads can then be assembled into contigs. To determine the phylogenetic identity of a sequence, it is compared to available full genome sequences using methods such as BLAST. One drawback of this approach is that many members of microbial communities do not have a representative sequenced genome.[26]

Despite the fact that metagenomics is limited by the availability of reference sequences, one significant advantage of metagenomics over targeted amplicon sequencing is that metagenomics data can elucidate the functional potential of the community DNA.[39][40] Targeted gene surveys cannot do this as they only reveal the phylogenetic relationship between the same gene from different organisms. Functional analysis is done by comparing the recovered sequences to databases of metagenomic annotations such as KEGG. The metabolic pathways that these genes are involved in can then be predicted with tools such as MG-RAST,[41] CAMERA[42] and IMG/M.[43]

RNA and protein-based approaches

Metatranscriptomics studies have been performed to study the gene expression of microbial communities through methods such as the pyrosequencing of extracted RNA.[44] Structure based studies have also identified ncRNAs such as ribozymes from microbiota.[45] Metaproteomics is a new approach that studies the proteins expressed by microbiota, giving insight into its functional potential.[46]

Projects

The Human Microbiome Project (HMP) is a United States National Institutes of Health initiative with the goal of identifying and characterizing the microorganisms which are found in association with both healthy and diseased humans (their microbial flora). Launched in 2008, it is a five-year project, best characterized as a feasibility study, and has a total budget of $115 million. The ultimate goal of this and similar NIH-sponsored microbiome projects is to test if changes in the human microbiome are associated with human health or disease.

The Earth Microbiome Project (EMP) is an initiative to collect natural samples and analyze the microbial community around the globe. Microbes are highly abundant and diverse. Experts have estimated that there are 1.3 x 10^28 archaeal cells, 3.1 x 10^28 bacterial cells and 1x10^30 virus particles in the ocean.[47][48] Not only rich in abundance, microbes pose great diversity that is largely unknown. The number of bacteria has roughly been estimated to 160 per ml in ocean water, 6,400-38,000 per g in soil, and 70 per ml sewage works[48]. These microbes work together and act as an important role in the ecological system such as nutrient recycling. However, only 1% of the genetic variation has been characterized.[49] Therefore, the specific interactions between microbes are largely unknown. The EMP aims to process as many as 200,000 samples and set up an inventory of microbial diversity in different biomes. In other words, we need a complete database of microbes on earth in order characterize environments and ecosystems by microbial composition and interaction. Using these data, we could perhaps propose new ecological and evolutionary theories.

Conclusion

Many more case studies exist than the few presented in this article, which illustrate the diverse interactions that been shown to exist between macro organisms and their microbial inhabitants. Elucidation of these interactions has required new technologies and an interdisciplinary approach. Genomics and ecology, once separate disciplines, are showing rapid convergence, and may together allow us to understand the molecular basis underlying the adaptations and interactions of the communities of life.[3]

Notes

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See also

External links

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