Difference between revisions of "Microbiome"
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* Computational systems biology of in silico metabolic models proved extremely useful in studying microbial metabolism. | * Computational systems biology of in silico metabolic models proved extremely useful in studying microbial metabolism. | ||
− | * Two fundamentally different approaches can be used to model microbiome metabolism: genome-based multi-species models and metagenomics-based supra-organism models. | + | * Two fundamentally different approaches can be used to model microbiome metabolism: genome-based multi-species models and [[metagenomics]]-based supra-organism models. |
* Preliminary studies of these modeling approaches demonstrate tremendous potential but several challenges should be addressed before a comprehensive modeling framework can be introduced. | * Preliminary studies of these modeling approaches demonstrate tremendous potential but several challenges should be addressed before a comprehensive modeling framework can be introduced. | ||
Line 135: | Line 135: | ||
==See also== | ==See also== | ||
+ | * [[Metagenomics]] | ||
+ | * [[Genomes OnLine Database]] (GOLD) | ||
* [[KEGG]] | * [[KEGG]] | ||
* [[MetaCyc]] | * [[MetaCyc]] | ||
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* functional equivalent pathogroups — a kind of "microbial guild" | * functional equivalent pathogroups — a kind of "microbial guild" | ||
* [[wikipedia:Enterotype]] — a classification of living organisms based on its bacteriological ecosystem in the human gut microbiome. | * [[wikipedia:Enterotype]] — a classification of living organisms based on its bacteriological ecosystem in the human gut microbiome. | ||
+ | **Research has indicated that each human has one of only three gut ecosystems.<ref name=Nature>Arumugam M, Raes J, ''et al.'' (April 2011). "[http://www.nature.com/nature/journal/vaop/ncurrent/full/nature09944.html Enterotypes of the human gut microbiome]". ''Nature'', '''473'''(7346): 174–80. PMID 21508958. {{doi|10.1038/nature09944}}.</ref> The following reflect the species that dominate in each: | ||
+ | *#''[[wikipedia:Bacteroides|Bacteroides]]''; | ||
+ | *#''[[wikipedia:Prevotella]]''; and | ||
+ | *#''[[wikipedia:Ruminococcus]]''. | ||
+ | **People with a bacteriode ecosystem have a bias towards bacteria that get most of their energy from carbohydrates and proteins. Prevotellas specialise in digesting sugar-covered proteins in mucin, the mixture of viscous proteins in the gut – an ability shared by people with a ruminococcus ecosystem.<ref name="Wired">Keim, Brandon (20 April 2011). "[http://www.wired.com/wiredscience/2011/04/gut-bacteria-types/ Gut-Bacteria Mapping Finds Three Global Varieties]". ''Wired Magazine''.</ref><ref name="NewScientist">Coghlan, Andy (20 April 2011). "[http://www.newscientist.com/article/dn20401-each-human-has-one-of-only-three-gut-ecosystems.html Each human has one of only three gut ecosystems]". ''New Scientist''.</ref> | ||
==Glossary== | ==Glossary== | ||
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;prebiotics : oligosaccharides or complex saccharides that stimulate the growth or activity of the beneficial commensal bacteria that already are present in the host. | ;prebiotics : oligosaccharides or complex saccharides that stimulate the growth or activity of the beneficial commensal bacteria that already are present in the host. | ||
;microbial guilds : groups of microbial species sharing a common ecological niche. On this view, different combinations of species could fulfil the same functional roles in different hosts (Tschop et al., 2009). | ;microbial guilds : groups of microbial species sharing a common ecological niche. On this view, different combinations of species could fulfil the same functional roles in different hosts (Tschop et al., 2009). | ||
− | ;metagenomics : wholesale (random) shotgun sequencing of DNA extracted from mixed bacterial communities, in the hope of characterising the physiology and ecology of the mostly uncultured members of these communities (Streit and Schmitz, 2004; Mongodin et al., 2005; | + | ;metagenomics : wholesale (random) shotgun sequencing of DNA extracted from mixed bacterial communities, in the hope of characterising the physiology and ecology of the mostly uncultured members of these communities (Streit and Schmitz, 2004; Mongodin et al., 2005; Tringe and Rubin, 2005). |
− | Tringe and Rubin, 2005). | + | |
==Keywords== | ==Keywords== | ||
Line 172: | Line 178: | ||
==List of people involved with microbiome research== | ==List of people involved with microbiome research== | ||
− | Elhanan Borenstein | + | Elhanan Borenstein (UW); Jonathan H. Badger; Pauline C. Ng; J. Craig Venter; Mark J. Pallen; Karen E. Nelson; Julie Segre (NIH) |
==Source== | ==Source== | ||
Line 179: | Line 185: | ||
==References== | ==References== | ||
<references/> | <references/> | ||
+ | |||
+ | ===To read=== | ||
+ | *Li K, Bihan M, Yooseph S, Methé BA (2012). "Analyses of the Microbial Diversity across the Human Microbiome". ''PLoS ONE'' '''7'''(6): e32118. {{doi|10.1371/journal.pone.0032118}}. | ||
==External links== | ==External links== | ||
− | *[[wikipedia:Human Microbiome Project]] (HMP) — launched in 2007 as an international collaboration with the aim of collecting and collating genomic information from many diverse human microbiomes (Peterson, 2009). ("the largest international life-science project of all time." --Davies, 2009) | + | *[http://commonfund.nih.gov/hmp/ Human Microbiome Project] — aims to characterize the microbial communities found at several different sites on the human body, including nasal passages, oral cavities, skin, gastrointestinal tract, and urogenital tract, and to analyze the role of these microbes in human health and disease. |
+ | **[http://hmpdacc.org/ HMPDACC.org] — Data Analysis and Coordination Center (DACC) for the National Institutes of Health (NIH) Common Fund supported Human Microbiome Project (HMP) | ||
+ | **[[wikipedia:Human Microbiome Project]] (HMP) — launched in 2007 as an international collaboration with the aim of collecting and collating genomic information from many diverse human microbiomes (Peterson, 2009). ("the largest international life-science project of all time." --Davies, 2009) | ||
+ | |||
+ | ===Tutorials / courses / howtos=== | ||
+ | *[http://www.cbs.dtu.dk/courses/27626/index.php Next Generation Sequencing Analysis] — June 2012 (#27626) at CBS | ||
[[Category:Bioinformatics]] | [[Category:Bioinformatics]] |
Latest revision as of 20:12, 31 July 2012
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][3]
Microbiomes are being characterized in many other environments as well, including soil, seawater and freshwater systems.
Contents
Overview of human microbiome
- The human microbiome is a complex biological system — interactions between numerous genes and between the various species comprising the microbiome markedly affect its function, dynamics and impact on the host.
- Studying the human microbiome calls for a systems-based research and for system-level modeling, ultimately leading to a better and more profound understanding of the microbiome.
- Computational systems biology of in silico metabolic models proved extremely useful in studying microbial metabolism.
- Two fundamentally different approaches can be used to model microbiome metabolism: genome-based multi-species models and metagenomics-based supra-organism models.
- Preliminary studies of these modeling approaches demonstrate tremendous potential but several challenges should be addressed before a comprehensive modeling framework can be introduced.
Individual human genomes have been sequenced, and there are approximately 3 million to 4 million variations with respect to the reference genome (Frazer et al., 2009). It is thought that some of these variants will cause phenotypic differences that can lead to disease or apparent physical traits. It is estimated that 3–8% of the human genome is functional (Siepel et al., 2005), so it is unlikely that all the variation in the 3 Gb human genome will lead to phenotypic differences. Rather, functional variants may be localized to the 90–240 Mb of human genome that contains transcribed coding genes, regulatory elements, RNA genes, and other functional elements.
...
By contrast, the human microbiome has extensive diversity. Each location (skin, mouth, intestine, etc) has its own metagenome. Recent studies have suggested that healthy individuals have up to 15,000 species-level phylotypes in their gastrointestinal tracts as determined by 16S rRNA sequencing (>97% identity) (Peterson et al., 2008) (Fig. 1.1 of this chapter), and that the two major phylogenetic groups present are the Firmicutes and Bacteriodetes. The average genome size of sequenced organisms from these groups is 3.4 Mb (Liolios et al., 2008), and the percentage of these genomes that codes for protein-coding genes is approximately 92%. Therefore, the functional part of the gastrointestinal microbiome can be estimated to be approximately 47,000 Mb (15,000 × 3.4 × 0.92), which is more than two orders of magnitude greater than the above-mentioned estimate of the functional part of the human genome.
...
The microbiome is an ecosystem in which the various members maintain equilibrium. So far, it appears that many diseases are associated with an abnormal proportion of the same taxonomic groups that are present in healthy individuals. For example, patients with Crohn’s disease show a lower than normal frequency of bacteria from the phylum Bacteriodetes in their gastrointestinal tract (e.g., Gophna et al., 2006), whereas patients suffering from active celiac disease have a higher than normal frequency of Bacteriodetes (e.g., Nadal et al., 2007). Biodiversity also plays a role in the microbiome.
...
The human body is home to a microbiota as rich and stunning in complexity as the flora and fauna of a rain forest or coral reef. The superlative metaphors used to describe this complex microbial community veer towards cliché: a community of bacterial cells ten-fold more numerous than the eukaryotic cells of its human host; an additional multi-cellular organ, as complex as the liver, encoded by a microbiome or "third genome", with >100 times more genes than the human nuclear genome; humans viewed as "superorganisms", built from human and microbial cells (Shanahan, 2002; Gill et al., 2006; Foxman et al., 2008; Carroll et al., 2009) or seen as "large, highly complex microbial communities attached to some relatively uninteresting organic matter" (Davies, 2009).
...
In the 1980s, Woese pioneered the use of 16S (also called small subunit or SSU) ribosomal RNA (rRNA) to study bacterial phylogenetics and evolution (Woese, 1987). Subsequently application of the polymerase chain reaction (PCR) to DNA sequences encoding 16S rRNA genes (16S rDNA sequences), twinned with electrophoretic or sequencing approaches, found widespread use in cataloguing uncharacterised and uncultured organisms in mixed microbial populations—an approach sometimes called "phylogenetic profiling" (Theron and Cloete, 2000). The Ribosomal Database Project now holds >400,000 16S rRNA gene sequences, illustrating the rich microbial diversity of our planet and hinting at what remains to be discovered.
...
Frank et al. (2007) estimated that the bacterial component of the human gut microbiome consists of ≥1,800 genera and an astonishing 15,000–36,000 species, depending on whether species are classified conservatively or liberally!
- Source: Metagenomics of the Human Body[4]
Human microbiome composition
Anatomic regions of the gut
- Over 100 trillion organisms (1014</sup>)
- 100 fold more genes in our gut then in us
- Upper GI tract: 102 – 104 cells/ml
- Lactobacilli, streptococci, H pylori
- Ileum: 106-1012 cells /ml, upper bacteria plus
- Faculative anaerobes: Enterobacteriaceae
- Obligate anaerobes: Bacteroides, Veillonella, Fusobacterium, and Clostridium species
- Colon: distal human colon is the most biodense natural ecosystem known (1010-1012 cells/ml)
- Complex and diverse
- Comprise most of our bacterial biomass
- Firmicutes, bacteroidetes, actinobacteria, proteobacteria, and others.
Gut flora and metabolism
Source: Hooper, et al. Annu Rev Nutr, 2002.
- Microbial genomes enhance our metabolic activity
- May indirectly or directly effect our metabolism
- The colon is very active metabolically
- 20-70 gms of carbos and 5-20 gms of protein/day
- Over 100 kcal per day!
- Mass of colonic microbiome = single kidney
- Metabolically as active as the liver
- Energy salvage: esp via the short-chain fatty acids
- Acetate, butyrate, propionate (SCFAs)
- Absorbed into body and used by liver and others organs
- Acetate and propionate modulate glucose metabolism in the liver and adipocytes (glycemic index)
- 50-70% of colonic cell energy derived from butyrate
- Mice and humans have different gut flora but the two largest divisions are shared in common:
- Bacteroidetes (Gram -)
- Firmicutes (Gram +)
- These flora change in response to diet and obesity of host
Regulators
- Archae: 1-2 % of mouse and human flora
- Represent a major microbial group in gut flora Increased in obese mice
- Many are methanogenic : Methanobacter smithii
- Converts CO2 and H2 gas to methane
- By decreasing the partial pressure of H2 gas these bacteria can drive bacterial metabolism
- The flora of obese mice are more efficient at extracting energy: "The Energy Harvest".
Research questions
Systems biology research has already revolutionized genomics and could similarly transform metagenomic research and particularly research of the human microbiome.
Systems based research represents a unique opportunity for addressing several of the most pressing questions concerning the human microbiome:
- What determines the assembly of the microbiome and what role do interspecific interactions play in its composition?
- Which factors govern the response of the microbiome to various perturbations?
- How does the microbiome, as a whole, interact with the human host and how does it impact human health?
Online resources for the human microbiome
The following are a list of useful online resources for systems biology and modeling of the human microbiome:
- Microbial genomic data and analysis
- IMG
- DACC
- GOLD
- Microbes online
- RAST
- Metagenomic data and analysis
- IMG/M
- MG-RAST
- METAREP
- Metabolic databases
- KEGG
- MetaCyc
- Brenda
- Metabolic model reconstruction, visualization, and analysis
- The Model Seed
- Systems Biology Research Group
- iPath
- Pathway Tools
- Cytoscape
- Cobra
- Reverse ecology software
- NetSeed
See also
Concepts
- wikipedia:Directed graph
- flux balance analysis (FBA)
- wikipedia:linkage disequilibrium
- wikipedia:List of human flora
- wikipedia:Koch's postulates
- wikipedia:Dysbiosis — (also called dysbacteriosis) refers to a condition with microbial imbalances on or within the body.
- wikipedia:Hygiene hypothesis
- wikipedia:Amplicon — a piece of DNA formed as the product of natural or artificial amplification events.
- wikipedia:Xenobiotic — a chemical which is found in an organism but which is not normally produced or expected to be present in it.
- wikipedia:Resistome — the collection of all the antibiotic resistance genes and their precursors in both pathogenic and non-pathogenic bacteria.
- wikipedia:Bacteriocin — proteinaceous toxins produced by bacteria to inhibit the growth of similar or closely related bacterial strain(s).
- functional equivalent pathogroups — a kind of "microbial guild"
- wikipedia:Enterotype — a classification of living organisms based on its bacteriological ecosystem in the human gut microbiome.
- Research has indicated that each human has one of only three gut ecosystems.[5] The following reflect the species that dominate in each:
- People with a bacteriode ecosystem have a bias towards bacteria that get most of their energy from carbohydrates and proteins. Prevotellas specialise in digesting sugar-covered proteins in mucin, the mixture of viscous proteins in the gut – an ability shared by people with a ruminococcus ecosystem.[6][7]
Glossary
- metatran-scriptomic
- meta-metabolomic
- auxotrophy
- (Gr. αὐξάνω "to increase"; τροφή "nourishment") is most commonly defined as the inability of an organism to synthesize a particular organic compound required for its growth (as defined by IUPAC). An auxotroph is an organism that displays this characteristic; auxotrophic is the corresponding adjective.
- bacteriotherapy
- the modulation of one's microbiota via antibiotics and probiotics or the transplantation of a complete microbiota into a recipient. (see: Clostridium difficile)
- ecosystomics
- a high-throughput systematic study of all realizable ecosystems in a given environment.
- operational taxonomic units (OTUs)
- given the number of sequences collected and a pairwise sequence identity (ID%) cutoff. A 99% ID level correlates with accepted strain classifications, likewise 97% with species and 95% with genus.[4]
- A low value will group highly diverse organisms together, underestimating biodiversity, but a high value may overestimate biodiversity, particularly in the case of next-generation sequencing methods, as they often have a higher rate of sequencing error than the traditional Sanger method.
- probiotics
- (from the Greek "pro bios", meaning "for, or promoting, life") are foods or supplements containing live bacteria thought to promote health.
- While yogurt and other fermented products have traditionally been considered "health food", studies of the human microbiome promise to understand what effect they have on the composition of the microbiome and ultimately health. Studies have shown that probiotics can manipulate the microbiome, as well as affect the intestinal barrier (Zyrek et al., 2007) and the immune system (Fitzpatrick et al., 2007).[4]
- prebiotics
- oligosaccharides or complex saccharides that stimulate the growth or activity of the beneficial commensal bacteria that already are present in the host.
- microbial guilds
- groups of microbial species sharing a common ecological niche. On this view, different combinations of species could fulfil the same functional roles in different hosts (Tschop et al., 2009).
- metagenomics
- wholesale (random) shotgun sequencing of DNA extracted from mixed bacterial communities, in the hope of characterising the physiology and ecology of the mostly uncultured members of these communities (Streit and Schmitz, 2004; Mongodin et al., 2005; Tringe and Rubin, 2005).
Keywords
systems biology; metabolic models; human microbiome; metagenomics; reverse ecology; ecosystomics; 16S rRNA; bacteriotherapy
List of people involved with microbiome research
Elhanan Borenstein (UW); Jonathan H. Badger; Pauline C. Ng; J. Craig Venter; Mark J. Pallen; Karen E. Nelson; Julie Segre (NIH)
Source
References
- ↑ Zimmer, Carl (13 July 2010). "How Microbes Defend and Define Us". New York Times.
- ↑ Because bacteria are 10-100 times smaller than human cells, the entire microbiome weighs about 200 grams.
- ↑ Coyle WJ. "The Human Microbiome: The Undiscovered Country".
- ↑ 4.0 4.1 4.2 Jonathan H. Badger, Pauline C. Ng, and J. Craig Venter (2011). "Chapter 1: The Human Genome, Microbiomes, and Disease" in Metagenomics of the Human Body. Karen E. Nelson (ed.). C Springer Science+Business Media, LLC 2011. DOI:10.1007/978-1-4419-7089-3_1 .
- ↑ Arumugam M, Raes J, et al. (April 2011). "Enterotypes of the human gut microbiome". Nature, 473(7346): 174–80. PMID 21508958. DOI:10.1038/nature09944 .
- ↑ Keim, Brandon (20 April 2011). "Gut-Bacteria Mapping Finds Three Global Varieties". Wired Magazine.
- ↑ Coghlan, Andy (20 April 2011). "Each human has one of only three gut ecosystems". New Scientist.
To read
- Li K, Bihan M, Yooseph S, Methé BA (2012). "Analyses of the Microbial Diversity across the Human Microbiome". PLoS ONE 7(6): e32118. DOI:10.1371/journal.pone.0032118 .
External links
- Human Microbiome Project — aims to characterize the microbial communities found at several different sites on the human body, including nasal passages, oral cavities, skin, gastrointestinal tract, and urogenital tract, and to analyze the role of these microbes in human health and disease.
- HMPDACC.org — Data Analysis and Coordination Center (DACC) for the National Institutes of Health (NIH) Common Fund supported Human Microbiome Project (HMP)
- wikipedia:Human Microbiome Project (HMP) — launched in 2007 as an international collaboration with the aim of collecting and collating genomic information from many diverse human microbiomes (Peterson, 2009). ("the largest international life-science project of all time." --Davies, 2009)
Tutorials / courses / howtos
- Next Generation Sequencing Analysis — June 2012 (#27626) at CBS