Content uploaded by David A Relman
Author content
All content in this area was uploaded by David A Relman
Content may be subject to copyright.
Nowhere in the study of human biology are basic concepts cha nging
more rapidly than with respect to the human microbiota. Micro-
organisms were first shown to cause disease in humans in the 1800s,
and after this finding, the popular and scientific views of the microbial
world became dominated by the quest to understand, prevent and cure
microbial disease. This led to millions of lives being saved through
improved hygiene, vaccinations and antibiotics. However, most inter-
actions between humans and microorganisms do not result in disease.
Beneficial host–microbe interactions have been studied for more than
a century, but it was not until the advent of molecular biology that the
pathogen-dominated view of human-associated microorganisms began
to change. Gene-sequence-based approaches have recently allowed
complex microbial communities to be characterized more compre-
hensively and have removed the constraint of being able to identify
only microorganisms that can be cultured, greatly increasing knowledge
about commensal microorganisms and mutualistic microorganisms
of humans
1–12
(that is, organisms in a relationship in which one part-
ner benefits and the other is unharmed, and organisms in a relation-
ship in which both partners benefit, respectively), as well as human
pathogens
13–18
. Researchers are now finding that host–microbe interac-
tions are essential to many aspects of normal ‘mammalian’ physiology,
ranging from metabolic activity to immune homeostasis
19–25
. With the
availability of new tools to investigate complex microbial communi-
ties and the expanded appreciation for the importance of the human
indigenous microbiota, this is an opportune time to apply ecological
and evolutionary principles to improve the current understanding of
both health and disease.
So far, the human microbiota has not been fully described, but it is
clear that microorganisms are present in site-specific communities on
the skin and mucosal surfaces and in the intestinal lumen. Each commu-
nity contains microorganisms from certain families and genera that are
found in the same habitat in many or most individuals, although at the
species and strain levels the microbiota of an individual can be as unique
as a fingerprint
3,11,26
. The microbial communities of other terrestrial ver-
tebrates mainly contain lineages that are related to, but distinct from,
those in humans
27–31
. These characteristics indicate that humans have
co-evolved with their microbial partners. In this review, we examine
evolutionary and ecological principles that are relevant to these relation-
ships, and we consider microbial pathogenesis in this context.
Evolution of mutualism
In the 1960s, evolutionary biologists rejected the idea that natural selec-
tion would generally favour the good of the species (or any group),
because individual types with the greatest reproductive success in a pop-
ulation increase in relative abundance regardless of the consequences
for the population as a whole
32
. Since then, the evolution of traits that
benefit individuals other than the trait bearer has been extensively
researched, both theoretically and empirically. Although the field has
been contentious at times, there is now general agreement about the
conditions that promote cooperation, including mutualism between
species
32–34
.
Organisms can have traits that contribute directly to their own fitness
and also incidentally benefit members of another species. When such
‘by-product benefits’ occur in both directions, the result is a no-cost
mutualism
34
. For example, plant polysaccharides that are not digestible
by humans are the main substrates for microbial growth in the colon,
whereas butyrate and other products of microbial fermentation are impor-
tant energy sources for the host
35,36
. Intestinal symbionts are selected to be
effective consumers of available resources through direct effects on their
fitness, but this also benefits the host because resource competition pro-
vides an additional barrier to colonization by potential pathogens
37–41
.
If mutualistic by-product interactions such as the example above are
possible, but not ecologically inevitable, then traits that improve the like-
lihood or stability of a relationship (for example, site-specific attachment
molecules) might evolve in one or both partners. A species might also
evolve to increase its own fitness by increasing the fitness of a mutualistic
partner
34
. For example, microbial symbionts that secrete molecules that
inhibit host pathogens (known as pathogen interference)
38–40
or detoxify
compounds that harm the host
42
can augment the lifespan and reproduc-
tive capacity of the host, thereby giving the symbionts more opportuni-
ties to spread. Evolution to increase mutualistic benefits has been called
‘partner fidelity feedback’, and it is strengthened if the same lineages of
partners interact across multiple generations
33,34
. Unlike traits that sup-
port mutualism incidentally, traits that evolve specifically to improve
1
Department of Microbiology and Immunology, Stanford University, Stanford, California 94305, USA.
2
Department of Medical Microbiology and Immunology, Symbiosis Cluster, 4835A
Medical Sciences Center, 1300 University Avenue, University of Wisconsin, Madison, Wisconsin 53706, USA.
3
Department of Medicine, Stanford University, Stanford, California 94305, USA.
4
Veterans Affairs Palo Alto Health Care System 154T, 3801 Miranda Avenue, Palo Alto, California 94304, USA.
An ecological and evolutionary perspective
on human–microbe mutualism and disease
Les Dethlefsen
1
, Margaret McFall-Ngai
2
& David A. Relman
1,3,4
The microbial communities of humans are characteristic and complex mixtures of microorganisms that have
co-evolved with their human hosts. The species that make up these communities vary between hosts as a
result of restricted migration of microorganisms between hosts and strong ecological interactions within
hosts, as well as host variability in terms of diet, genotype and colonization history. The shared evolutionary
fate of humans and their symbiotic bacteria has selected for mutualistic interactions that are essential for
human health, and ecological or genetic changes that uncouple this shared fate can result in disease. In
this way, looking to ecological and evolutionary principles might provide new strategies for restoring and
maintaining human health.
811
INSIGHT REVIEW
NATURE|Vol 449|18 October 2007|doi:10.1038/nature06245
mutualism, such as the production of compounds dedicated to pathogen
interference, can impose a direct fitness cost, although a net benefit would
be expected in the context of the evolved mutualism
34
.
Mutualism-promoting traits with a direct cost for the bearer, however,
create the potential for ‘cheating’. When organisms interact to create a
shared benefit, cheaters are organisms that obtain the benefit without
helping to create it. For example, a cheating microbial phenotype could
result from a mutation that redirects resources towards faster growth
of the microorganism itself instead of detoxification or pathogen inter-
ference. The cheater therefore increases its relative fitness in a host by
avoiding costly contributions towards host fitness while benefiting from
the improved host fitness that results from the mutualistic contributions
of its competitors
33,34
. Various evolutionary outcomes are possible, inclu-
ding the absence of costly contributions to mutualism, contributions to
mutualism that are below the level that would maximize the mutualistic
benefit, and the coexistence of mutualists and cheaters in the commu-
nity
43
. A possible example of this dynamic balance is that certain benefits
attributed to probiotic bacterial species are characteristic of only a subset
of the strains that make up the species
38,40
. For any mutualism that is not
cost free, the partners can evolve mechanisms to protect their relationship
from being exploited by cheaters
32,34,44
, and mutualism can be stronger
and more stable where ecological features limit the potential for exploita-
tion (discussed later).
The immune system is the most conspicuous set of anti-exploitation
adaptations involved in human–microbial symbiosis. The gastrointestinal
mucosa is intimately associated with the most abundant and diverse
microbial communities in the human body, but the gut-associated
immune system neither controls the composition of the gut microbiota
nor remains ignorant of it. Instead, specialized tissues and cells actively
sample the intestinal contents and initiate local immune responses that
help to confine the microbiota to the gut, avoiding a damaging systemic
inflammatory response to the microorganisms present in the healthy
gut
45
. However, if host tissue is damaged
46
or if micro organisms spread
to normally sterile sites
45
, then there is a vigorous systemic response to
clear the infection. Therefore, microorganisms are free to compete for
resources in the gut, generating a robust and disease-resistant commu-
nity
37,41
, but are prevented (usually) from exploiting the host to obtain
additional resources. Recent work has also shown that the normal
development and activity of the ‘host’ immune system is itself a result of
mutualistic interactions
20–22,24,25
(see page 819).
Humans and their collective microbiota are segmented into many
local communities, each comprising an individual human with his or her
symbionts. This ecological pattern, characterized by strong interactions
within distinct local communities and limited interactions or migra-
tion between them, is described as a metacommunity. Another level of
metacommunity organization exists because individual humans belong
to social groups that tend to share a similar microbiota
47,48
. At both lev-
els, the metacommunity structure allows selection to occur between the
local units (that is, between individuals or between social groups), which
promotes mutualism and restrains cheating within the human–microbe
symbiosis
32,49
. Such selection occurs when a local symbiotic community
succeeds or fails together, with more successful communities increasing
in abundance or prevalence relative to less successful communities
32
. For
example, a human individual or social group that carries a microbiota
with strong defences against an abundant pathogen is likely to leave more
progeny than those lacking such defences. If the progeny tend to carry the
parental microbiota, then mutualistic microorganisms that make costly
contributions to pathogen defence are favoured by selection between
distinct local symbiotic communities. This community-level selection
opposes the tendency for cheating non-defenders to increase in rela-
tive abundance within each local symbiotic community
32
. The greater
similarity of the microbiota within a human family than between human
families
12
(and within, rather than between, chimpanzee social groups
30
)
shows that there is, indeed, a shared evolutionary fate. The individualized
microbiota of each person has a stake in his or her fitness.
Human–microbe mutualism often involves more than two partners,
although the same principles apply. For example, the colonic degrada-
tion of polysaccharides that provides butyrate for the host is a coopera-
tive microbial process
35,36
. Extracellular enzymes from multiple species
are required for complete hydrolysis of the polymers. In addition, some
of the resultant sugars are consumed by strains that do not produce
extracellular enzymes but provide growth factors to strains that do
35
.
Some fermenters such as Bifidobacterium spp. release lactate as waste.
Their fermentation efficiency is increased by lactate fermenters, such
as Eubacterium hallii, that release butyrate as waste, and this butyrate
is then used by the host
36
. Sugar-fermenting lactobacilli that produce
neither hydrolytic enzymes nor growth factors could be considered
cheaters from the perspective of polysaccharide degradation, but they
could be considered mutualists of the entire symbiotic community if
they interfere with the colonization of pathogens
40
. The butyrate-pro-
ducing consortium as a whole is a mutualist of the host and would be
favoured by community-level selection over consortia producing less-
desirable fermentation products
36
. However, selection for mutualistic
functional traits such as butyrate production cannot entirely determine
the composition of the microbiota, because communities of different
composition can have similar functional characteristics in a given con-
text. Not only selection on community-level traits but also competi-
tion within the community and chance colonization events affect the
structure of the microbiota
50
.
Human microbial communities and health
The distribution of microorganisms in and on the human body reflects
adaptations to life on land, which were made about 400 million years ago.
Terrestrial vertebrates developed skin, lungs, internal fertilization, and
protective membranes around the embryo. The skin became relatively
impermeable, and mucous membranes were confined to protected sites.
Because microorganisms generally thrive only in moist environments,
these adaptations to a mostly dry environment have shaped the abun-
dance, location and phenotypes of human-associated microorganisms
and have limited the exchange of microorganisms between individuals.
Table 1 | Model systems for animal–microbe symbioses
Type of symbiosis Specific system (Host/symbiont species) Host phylogenetic affiliation Host tissue colonized Reference
Highly complex consortia (10
2
–10
3
)* Mus musculus (mouse) Vertebrate chordate Intestine 19
Danio rerio (zebrafish) Vertebrate chordate Intestine 86
Microcerotermes spp. and Reticulitermes spp. (termites) Insect arthropod Hindgut 87
Relatively simple consortia (~2–25)* Hirudo medicinalis (leech) Oligochaete annelid Intestine 88
Lymantria dispar (gypsy moth) Insect arthropod Larval midgut 89
Drosophila melanogaster (fruitfly) Insect arthropod Intestine 90
Hydra oligactis and Hydra vulgaris Hydrozoan cnidarian Not determined 91
Monospecific (1)* Euprymna scolopes (sepiolid squid)/Vibrio fischeri Cephalopod mollusc Light organ 92
Eisenia fetida (earthworm)/Acidovorax spp. Oligochaete annelid Excretory tissues 93
Steinernema spp./Xenorhabdus spp.
and Heterorhabditis spp./Photorhabdus spp.
Entomopathogenic
nematodes
Gut-associated
vesicle or region
94
*Number of bacterial-symbiont phylotypes found reproducibly.
812
NATURE|Vol 449|18 October 2007
INSIGHT REVIEW
The current understanding of the human microbiota relies heavily
on cultivation-based approaches and therefore is biased and incom-
plete. Although imperfect, molecular approaches that identify micro-
organisms from small-subunit (16S) ribosomal RNA gene sequences
offer advantages over cultivation. The 16S rRNA gene is typically chosen
because it is present universally and can provide a taxonomic identifica-
tion ranging from the domain and phylum level to approximately the
species level. However, these methods have been used to study human
microbial ecology for only a decade, and the available data are limited.
There are few deep surveys of microbial-community membership in
any human habitat and even fewer assessments of functional potential
or activity. In general, 16S rRNA gene-sequence data have been col-
lected from one site in a few humans at one time, representing a nar-
row range of health and disease states
2,5–7
, although there are studies
that include several temporal or spatial samples per individual
1,3,4,51
.
Sequence-dependent approaches that are less labour-intensive but yield
lower-resolution data have been applied to a larger number of individu-
als, at various time points and under various conditions
8,9,11,12,52
. Even
so, the microbial communities associated with only a small proportion
of the diversity of human genotypes, lifestyles, diets and diseases have
been investigated. One high-throughput method for obtaining infor-
mation about bacterial communities is to use phylogenetic microarrays,
which yield high-resolution data, but this method also depends on
adequate 16S rRNA gene-sequence databases
10
. Like these microarray
studies, metagenomic and proteomic analyses are just beginning to be
published
53,54
. Technical and ethical constraints restrict sampling from
humans; therefore, model systems will continue to be important, and
examples of these are listed in Table 1.
Despite the limited data available, analyses of the human microbiota
have revealed intriguing features. Most of the phylogenetic diversity is
found in shallow, wide radiations in a small subset of the known deep
lineages
26
. Specifically, there are more than 50 bacterial phyla on Earth,
but human-associated communities are dominated by only 4 phyla
(Firmicutes, Bacteroidetes, Actinobacteria and Proteobacteria), with
9 other phyla (Chlamydiae, Cyanobacteria, Deferribacteres, Deinococcus–
Thermus, Fusobacteria, Spirochaetes, Verrucomicrobia, and the candi-
date phyla TM7 and SR1) found in some sites and individuals (Fig. 1). In
contrast to the paucity of phyla represented, the human microbiota
contains an abundance of species and strains. Uniform probabilities
of speciation and extinction over time would result in an exponential
increase in the number of lineages throughout evolution. However, in
humans, there is a marked excess of phylotype diversity at the species
and strain level compared with the trends in more inclusive taxa (Fig. 2);
there are similar patterns in other vertebrate hosts
26
. This finding might
reflect a long history of stability in the types of microbial niche associ-
ated with terrestrial animals, together with factors (such as host hetero-
geneity and metacommunity structure) that promote diversification
among organisms in similar niches. In contrast to the remarkable diver-
sity of bacterial species, a striking but unexplained finding is that the only
Archaea found frequently in humans are several species of methanogens.
Methanobrevibacter smithii is abundant in the colon of some humans
3,53
.
Also, Methanobrevibacter oralis and close relatives can be found within
the subgingival crevice in the human mouth but only in the setting of
moderate to severe disease
55
. Overall, the human microbiota is similar
to that of other mammals at the phylum level, but most bacterial families
and genera seem to be distinct (Fig. 3).
Multiple samples of the microbiota that are taken separated in time
or space from a single body habitat within one individual are gener-
ally more similar to each other than they are to samples from the same
habitat in another individual
3,9,11
, although temporal variation in the
skin microbiota of an individual is as great as the variation between
individuals
4
. In addition, the bacterial communities at a given site are
more similar between human family members than between unrelated
individuals
12
, but more studies are necessary to distinguish the effects
of genetic relatedness and a shared early environment
50
. Antibiotics can
markedly affect the composition of the microbiota in the short term,
with most (but not all) families and genera of gut micro organisms
returning to typical levels within weeks of exposure
51,56
. However,
pathogens can exploit the reduced competitiveness of a community
disturbed by antibiotics, thereby establishing themselves in the host
39,57
.
The degree to which the unique bacterial communities of an individual
are re-established after antibiotic treatment is unclear, but particular
antibiotic-resistant strains that colonize or evolve during treatment can
persist for years
58,59
.
Firmicutes
Bacteroidetes
Actinobacteria
Proteobacteria
Other phyla
Mouth (56)
Skin (48)
Colon (195)
Vagina (5)
Stomach (25)
Oesophagus (43)
Figure 1 | Site-specific distributions of bacterial
phyla in healthy humans.
The area of the chart
for each site represents the average number of
distinct phylotypes (approximate species-level
taxa, based on 16S rRNA gene-sequence analysis)
per individual. (The mean number of phylotypes
per individual is shown in parentheses; 3–11
individuals were studied per habitat.) The coloured
wedges represent the proportion of phylotypes
belonging to different phyla. More than 50 bacteria
phyla exist, but human microbial communities
are overwhelmingly dominated by the 4 that are
shown. The relative abundance of these phyla at
most sites tends to be consistent across individuals:
for example, in almost all humans studied so far,
Bacteroidetes and Firmicutes predominate in the
colon. By contrast, the composition of the vaginal
microbiota is more variable; most women have
a preponderance of Firmicutes with few other
representatives, whereas a minority of women have
a preponderance of Actinobacteria with few other
representatives. An estimated 20–80% of human-
associated phylotypes (depending on habitat) are
thought to have eluded cultivation so far. Data
taken from refs 1–7.
813
NATURE|Vol 449|18 October 2007
INSIGHT REVIEW
A human infant acquires its microbiota from the environment. In
humans, symbionts are not vertically transmitted (that is, transmit-
ted through the germ line), as they are in some invertebrate animals.
Colonization, succession and diversification occur within characteristic
windows of time in the various microbial habitats in the body, ranging
over the first weeks, months or years of life
10,60,61
. The composition of
faecal communities in early infancy, for example, is dynamic and reflects
opportunistic environmental exposures, especially to the mother. The
introduction of solid foods then begins the transition to an individual-
ized, adult-like microbiota
10
. The assembly of bacterial communities
on tooth surfaces also follows a consistent pattern as teeth emerge
62
, as
well as after the removal of pre-existing biomass (that is, plaque)
52,60
.
The horizontal transfer of microorganisms to every human genera-
tion favours strains that are locally abundant at that time (for example,
those present in parents and kin), but colonization remains somewhat
stochastic
50
. The mixing of lineages from different sources that occurs
during community assembly is analogous to the reassortment of paren-
tal alleles during sexual reproduction
49
, and it promotes the adaptation
of community composition to local conditions and the rapid spread of
beneficial strains. However, strains that become locally abundant by
cheating can also spread.
Competition for niches within the human microbiota is ubiquitous
and occurs together with the selective forces that promote mutualism
in the community as a whole. Microorganisms can even compete and
cooperate simultaneously. For example, Bacteroides thetaiotaomicron
and M. smithii facilitate each other’s growth by complementary energy
metabolism, while competing for nitrogen
63
. Cooperatively crosslinked
biofilms containing multiple species promote the colonization of tooth
surfaces, even while the constituent species compete with each other for
individual binding sites
64
. Symbionts that are highly prevalent and abun-
dant probably have effective mechanisms for competing for resources:
for example, B. thetaiotaomicron
65
and Bifidobacterium longum
66
have a
wide variety of inducible genes encoding factors involved in the bind-
ing, uptake and degradation of plant- and host-derived polysaccharides.
Competition within the human microbiota involves not only resources
but also interference; that is, the direct inhibition of one strain by another
in a resource-independent manner. In some cases, the metabolic by-
products of one species (such as lactate or short-chain fatty acids) inhibit
other microorganisms. In other cases, dedicated compounds are gener-
ated solely because of their inhibitory effect: for example, reactive oxy-
gen species and the peptide antibiotics known as bacteriocins
39,40
. The
immediate fitness costs and context-dependent benefits of dedicated
interference compounds result in selection for diversity: for example,
the capacity to produce and resist bacteriocins evolves rapidly among
closely related strains
67,68
. Both resource competition and interference
competition contribute to the resistance of the intact microbiota to colo-
nization by pathogens
37–40
.
Microbial evolution and human disease
Microbial symbionts occupy a complex adaptive landscape. Many traits
affect fitness, and many different trait combinations can generate a local
optimum fitness (that is, a fitness peak). Natural selection generally
acts on subtle phenotypic differences to move microorganisms ‘uphill’
towards a fitness peak, but larger changes can move an organism onto
the slope of a different fitness peak (Fig. 4). The fitness of a symbiont
depends on environmental features that can change, such as the coexist-
ing microbiota, the diet of the host, and which species and even particu-
lar individual is the host. Thus, the adaptive landscape is dynamic.
Changes in the genotype or environment of a non-pathogenic
symbiont can result in the invasion of host tissue. The usual outcome is
then an immune response that eliminates the infection. This high rate of
microbial mortality imposes a strong selective pressure: the rare changes
that enable a symbiont to survive such a challenge would involve avoid-
ing immune recognition or circumventing immune control, at least until
some progeny have been transmitted to a new host. Alternatively, changes
that increase the opportunities for a non-pathogen to be transmitted to
a new host reduce the dependence of the microorganism on the fate of
the current host. In this case, the selective pressures on the fitness of the
symbiont are less constrained by the need to preserve host fitness as well.
In either case, the microorganism can begin adapting towards a fitness
peak as a pathogen.
All human microbial symbionts must be able to establish themselves in
new hosts. The adaptations of mutualistic or commensal microorganisms
towards this end can facilitate a pathogenic lifestyle as well. For example,
the biochemical mechanisms for sensing host environments, interacting
with host surfaces and even communicating with the host are often the
same in human pathogens, commensal microorganisms and mutualistic
microorganisms
15,69–71
. Not surprisingly, many common human pathogens
are closely related to non-pathogenic symbionts: examples are found in
1
10
100
1,000
10,000
00.10.20.30.40.50.6
Genetic distance between lineages (percentage difference)
Skin
Mouth
Oesophagus
Stomach
Colon
Number of lineages
Genus
Species
Strain
Genus
Family
Species
Strain
0.1 0.05 0
10
100
1,000
10,000
a
b
Figure 2 | Patterns of human-associated microbial diversity. a, Lineage-by-
distance analysis of 16S rRNA gene-sequence data from human microbial
communities in specific habitats. The x axis shows the percentage difference
threshold (Olsen correction), over 1,241 unambiguously aligned positions
of near full-length 16S rRNA gene sequences, for delineating separate
lineages. The y axis shows the number of distinct lineages that exist at
the distance threshold. If speciation and extinction occur with constant
probabilities as 16S rRNA gene sequences diverge, this would result in an
exponentially increasing number of lineages with diminishing evolutionary
distances between them (a straight line on a semi logarithmic plot). Such
a pattern seems to hold from the phylum level (largest distances between
lineages) to approximately the species level. However, relative to this trend,
all sites have an excess of recently diverged lineages. The excess lineages
accumulate in the range of 16S rRNA gene divergence that is typically
associated with species and strains. The inset depicts a portion of the same
data at a larger scale. Samples were taken from 3–11 individuals, depending
on the site. Data taken from refs 1–5. b, When displayed as a dendrogram,
16S rRNA gene-based patterns of microbial diversity in soil and aquatic
environments generally resemble the tree shape on the left, with new
branches arising at all distances from the root. Patterns of diversity in
vertebrate-associated communities resemble the tree shape on the right,
with few branches arising close to the root and many branches arising close
to the branch tips.
814
NATURE|Vol 449|18 October 2007
INSIGHT REVIEW
the genera Staphylococcus, Streptococcus, Neisseria and Enterococcus, and
in the family Enterobacteriaceae
13–18
. It is not coincidental that these taxa
tolerate the aerobic environment between hosts, whereas the more abun-
dant, but less aerotolerant, taxa of the colon have fewer known pathogens
as close relatives. The greater ability of aerotolerant taxa to be transmitted
to a new host weakens the selection for mutualism in the current host
33,34
.
In general, the pathogenic phenotypes in taxa that contain abundant non-
pathogenic symbionts have multiple evolutionary origins
13–18
, empha-
sizing that pathogenicity is not necessarily a considerable evolutionary
barrier for microorganisms. By contrast, other pathogens have originated
only once
72,73
, but the continued emergence of new diseases is a reminder
that there might be many unoccupied pathogen fitness peaks at present.
The evolution of pathogen virulence has received considerable
attention, largely centred on the paradox that pathogens both harm
and depend on their hosts
74
. The view that highly virulent pathogens
originated recently, with selection inevitably reducing virulence over
time, has been supplanted by the realization that there is an optimal
level of virulence (for the pathogen) that depends on the biology of its
host interactions
74,75
. For example, if pathogen transmission is inher-
ently damaging to the host (as occurs with Salmonella enterica serovar
Typhimurium
76
), then selective pressure on the pathogen balances the
benefit of higher transmission against the loss of host viability as a result
of higher virulence. By contrast, pathogens with environmental reser-
voirs (for example, Vibrio cholerae), transmission vectors (for example,
Plasmodium falciparum) or environmentally resistant propagules (such
as spores; for example, Clostridium tetani) might be able to afford a
higher level of virulence than those that depend on direct transmission
77
.
For pathogens that depend on normal host activity for trans mission,
such as sexually transmitted pathogens (for example, Chlamydia
trachomatis and Treponema pallidum), low virulence and/or long latency
can promote the spread of pathogen. In host populations with a reduced
potential for pathogens to encounter new hosts, the optimal virulence
is reduced to allow the host to survive long enough to ensure pathogen
transmission
78
.
The observed level of virulence for a pathogen, however, does not
necessarily correspond to its evolutionary optimum. Many pathogens
are zoonotic (that is, transmitted from animals to humans)
79
and can
be adapted to a low-virulence niche in their primary host; an example is
enterohaemorrhagic Escherichia coli in cattle
80
. Unless transmission by
humans contributes to the evolutionary success of the pathogen, exces-
sive (or suboptimal) virulence in humans exerts no selective pressure on
the microorganism. Competition between different strains of a pathogen
(as a result of co-infection, as occurs with Plasmodium spp., or in-host
evolution, as occurs with human immunodeficiency virus) can affect
virulence, because an optimally virulent pathogen (as measured by trans-
mission success) might not be the best competitor during mixed infec-
tions in a single host
81
. A rapidly replicating, excessively virulent strain
might kill the host or provoke a successful immune response before
transmission of a co-infecting, less virulent strain, even if the latter strain
is optimally virulent when infecting a host alone
81
. Competition between
pathogens can also decrease virulence. The production of extracellular
iron-scavenging molecules (known as siderophores) contributes to the
virulence of many bacterial pathogens, but cheating lineages that con-
sume siderophores without producing them reduce virulence, thereby
benefiting the host
82
. The diverse biology of host–pathogen and patho-
gen–pathogen interactions precludes simple predictions about the effect
of interpathogen competition on virulence
81,83
.
The importance of opportunity for the origin of pathogens is empha-
sized by a recent analysis of the 25 infectious diseases that cause the most
human death and disability
84
. The preferred host of a pathogen is thought
to change most easily to a species closely related to the current host
85
.
Indeed, although primates constitute only a small proportion of all animal
species on Earth, they are the origin of a large proportion of these serious
human diseases. However, an even larger proportion of these diseases
originated from domestic animals, reflecting greater opportunities for the
symbionts of domesticated species to be transmitted to humans
84
. With
the advent of agriculture, changes in human populations simultaneously
Human Mouse
Cattle Pig
a
b
Lactobacillaceae
Mollicutes
IV
XIVa
Firmicutes
Other phyla
Proteobacteria
Bacteroidetes
Figure 3 | Relationships between bacterial 16S rRNA gene sequences
from the intestinal microbiota of animals. A set of aligned, high-quality,
full-length sequences was obtained from Greengenes
95
. Sequences derived
from one human stool sample and caecal samples from one mouse family
were chosen to obtain approximately the same number of sequences as
obtained from multiple studies of the bovine rumen and pig caecum and
colon (range 617–748 sequences per host species). a, A neighbour-joining
tree was created from 1,241 unambiguously aligned positions in all 2,735
sequences, with selected taxa indicated. Mollicutes, Lactobacillaceae and
Clostridium clusters IV and XIVa are within the Firmicutes
96
. b, Host-
specific trees were created with the same topology as the entire tree, shown
in part a, but they depict only the sequences derived from the indicated host
species. Branches shared with at least one other host species are shown in
black, and branches specific to a single species are coloured. The same phyla
and classes predominate in these animals (evident from the overlapping
tree topologies and shared branches), although their relative abundances
vary. By contrast, most genera and many families are specific to a single
host species (coloured branches).
815
NATURE|Vol 449|18 October 2007
INSIGHT REVIEW
created a new niche for deadly pathogens. Ten of these 25 major infectious
diseases could have arisen only after urbanization, because they depend
on human–human transmission and quickly kill infected individuals or
leave them with lifelong immunity
84
. Such ‘crowd’ diseases could not have
survived in the small dispersed human societies present before agriculture.
Common pathogens derived from human mutualistic microorganisms
have also exploited these changes in the human population, with many
clonal lineages being disseminated globally
13–18
.
Urbanization and global travel have eroded some of the barriers to
microbial transmission between social groups that contribute to the
metacommunity structure of the human–microbe symbiosis. The
diminished fidelity of host and symbiont lineages to each other (both
within and between generations) and reduced opportunities for com-
munity-level selection between human social groups have reduced the
strength of selection for mutualism. Microbial cheaters that allocate
resources to their own growth and dissemination instead of pathogen
interference or other costly contributions to host fitness can now spread
globally, instead of merely within a tribe. Symbionts that colonize an
infant who resides in an urban area include many microorganisms that
are not derived from the infant’s relatives, much less from an extended
Fitness in context AFitness in context B
?
?
Phenotypic
variation
Figure 4 | Adaptive landscapes. The plane is a conceptual representation
of the multidimensional phenotypes that are available to a microorganism.
The height of the surface above the plane represents the fitness of the
corresponding phenotypes in a given ecological context, including biotic
and abiotic components of the environment. In a given environment
(context A, upper panel), for mutations that have a small effect,
a phenotype (circle) under natural selection will tend to evolve along
the steepest path uphill towards higher fitness (solid arrow), eventually
moving the mean phenotype of a population to a local fitness maximum.
Mutations that have a large effect, such as horizontal gene transfer, can
shift a phenotype to the slope of a different fitness peak (dashed arrow).
This can markedly alter the outcome for the host; for example, it can result
in pathogenesis instead of mutualism. The valley separating the peaks
represents phenotypes of low fitness, such as those that are likely to elicit
an immune response but lack the adaptations necessary to survive it. For
a given phenotype, a change in context (for example, a change in host diet,
alterations in coexisting microbial populations, or transfer to a different
host or host species; context B, lower panel) can have subtle or marked
effects on fitness. A phenotype near a fitness peak in context A might
be in a valley of low fitness in context B. If the microorganism survives,
the subsequent course of evolution might depend on the direction of
phenotypic change caused by the next mutation.
816
NATURE|Vol 449|18 October 2007
INSIGHT REVIEW
kin group with a consistent lifestyle and geographic range over genera-
tions. This disruption of co-evolved mutualism between humans and
human microbiota, as a result of changes in human ecology, contrib-
utes to the increasing prevalence of chronic and degenerative disease in
industrialized countries
21,47
.
Paths forward
Researchers have only just begun to describe the microbial communi-
ties that are associated with humans and the extent of the interactions
between host and microbiota. Understanding this symbiotic ‘landscape’
will require research that spans the biological hierarchy from molecules
to communities and is informed by ecological and evolutionary theory.
Only with an integrated approach will it be possible to comprehend the
complex ecology of human health and the many ways in which interac-
tions between humans and microorganisms can go awry.
The first step in improving our understanding is to describe the com-
position of microbial communities in each habitat of the human body
and how this varies over time, among individuals and with respect to
variables such as diet, host genotype and health status. This project is
now in its early stages, with the first successful forays having laid the
groundwork for more ambitious studies, such as the Human Microbiome
Project (see page 804).
Several recent studies highlight remarkable examples of how a
co-evolved microbiota can markedly affect host biology at the molecu-
lar level
19–25
, and these findings call for a complete re-examination of
human physiology and immunology
44
. Attributes that were assumed
to be human traits have been shown to result from human–microbe
interactions.
Although human studies are essential, the technical and ethical limita-
tions of carrying out experiments and obtaining samples from humans
mean that experimental model systems also need to be used. These two
approaches offer complementary information. The relevance of human
studies is clear. But experimental model systems have two main advan-
tages: they highlight evolutionarily conserved features that are likely
to be crucial for function, and they show diversity (how a single ‘goal’
is accomplished differently), thereby exposing the essence of a charac-
teristic. Models for the study of symbioses range from binary relation-
ships between an invertebrate and one microbial species to complex
vertebrate systems involving consortia of microorganisms (Table 1).
For models with complex consortia, gnotobiotic techniques are used
to manipulate the symbiosis experimentally. By contrast, using simpler
consortia facilitates the molecular dissection of interactions in the intact
natural setting. The genetic tools available for some model hosts allow
the identification of genes and proteins that control host responses and
manage the consortia.
From the microbial perspective, the host is a simply a complex environ-
ment — the distinction between human health and disease is important
only as far as it affects microbial fitness. To think that we can intervene
effectively in human–microbe relationships without considering microbial
ecology and evolution is folly, as demonstrated by the spread of anti biotic-
resistant microorganisms
13,14,16,17,58,59
and by the connections between
some modern diseases and alterations in the human microbiota
21,47
. The
principles and mechanisms that underlie microbial community struc-
ture and host–symbiont relationships must become incorporated into
our definitions of human health. It will be crucial to consider the role
of microbial communities, and not just individual species, as pathogens
and mutualists
55
. Moreover, one of the goals of medical intervention
during disease should be minimizing damage to the health-associated
homeostasis between humans and their microbiota. Medical and general
educational curricula will need to be modified accordingly. ■
1. Aas, J. A., Paster, B. J., Stokes, L. N., Olsen, I. & Dewhirst, F. E. Defining the normal bacterial
flora of the oral cavity. J. Clin. Microbiol. 43, 5721–5732 (2005).
2. Bik, E. M. et al. Molecular analysis of the bacterial microbiota in the human stomach.
Proc. Natl Acad. Sci. USA 103, 732–737 (2006).
3. Eckburg, P. B. et al. Diversity of the human intestinal microbial flora. Science 308,
1635–1638 (2005).
4. Gao, Z., Tseng, C. H., Pei, Z. & Blaser, M. J. Molecular analysis of human forearm superficial
skin bacterial biota. Proc. Natl Acad. Sci. USA 104, 2927–2932 (2007).
5. Pei, Z. et al. Bacterial biota in the human distal esophagus. Proc. Natl Acad. Sci. USA 101,
4250–4255 (2004).
6. Verhelst, R. et al. Cloning of 16S rRNA genes amplified from normal and disturbed vaginal
microflora suggests a strong association between Atopobium vaginae, Gardnerella vaginalis
and bacterial vaginosis. BMC Microbiol. 4, 16 (2004).
7. Zhou, X. et al. Characterization of vaginal microbial communities in adult healthy women
using cultivation-independent methods. Microbiology 150, 2565–2573 (2004).
8. Lay, C. et al. Colonic microbiota signatures across five northern European countries.
Appl. Environ. Microbiol. 71, 4153–4155 (2005).
9. Matsuki, T., Watanabe, K., Fujimoto, J., Takada, T. & Tanaka, R. Use of 16S rRNA gene-
targeted group-specific primers for real-time PCR analysis of predominant bacteria in
human feces. Appl. Environ. Microbiol. 70, 7220–7228 (2004).
10. Palmer, C., Bik, E. M., DiGiulio, D. B., Relman, D. A. & Brown, P. O. Development of the
human infant intestinal microbiota. PLoS Biol. 5, e177 (2007).
11. Vanhoutte, T., Huys, G., De Brandt, E. & Swings, J. Temporal stability analysis of the
microbiota in human feces by denaturing gradient gel electrophoresis using universal and
group-specific 16S rRNA gene primers. FEMS Microbiol. Ecol. 48, 437–446 (2004).
12. Zoetendal, E. G., Akkermans, A. D. L., Akkermans-van Vliet, W. M.,
de Visser, J. A. G. M. & de Vos, W. M. The host genotype affects the bacterial community
in the human gastrointestinal tract. Microb. Ecol. Health Dis. 13, 129–134 (2001).
13. Leavis, H. L., Bonten, M. J. & Willems, R. J. Identification of high-risk enterococcal clonal
complexes: global dispersion and antibiotic resistance. Curr. Opin. Microbiol. 9, 454–460
(2006).
14. Miragaia, M., Thomas, J. C., Couto, I., Enright, M. C. & de Lencastre, H. Inferring a
population structure for Staphylococcus epidermidis from multilocus sequence typing data.
J. Bacteriol. 189,
2540–2552 (2007).
15. Callaghan, M. J., Jolley, K. A. & Maiden, M. C. Opacity-associated adhesin repertoire in
hyperinvasive Neisseria meningitidis. Infect. Immun. 74, 5085–5094 (2006).
16. Robinson, D. A. & Enright, M. C. Multilocus sequence typing and the evolution of
methicillin-resistant Staphylococcus aureus. Clin. Microbiol. Infect. 10, 92–97 (2004).
17. Robinson, D. A., Sutcliffe, J. A., Tewodros, W., Manoharan, A. & Bessen, D. E. Evolution
and global dissemination of macrolide-resistant group A streptococci. Antimicrob. Agents
Chemother. 50, 2903–2911 (2006).
18. Wirth, T. et al. Sex and virulence in Escherichia coli: an evolutionary perspective.
Mol. Microbiol. 60, 1136–1151 (2006).
19. Bäckhed, F. et al. The gut microbiota as an environmental factor that regulates fat storage.
Proc. Natl Acad. Sci. USA 101, 15718–15723 (2004).
20. Cash, H. L., Whitham, C. V., Behrendt, C. L. & Hooper, L. V. Symbiotic bacteria direct
expression of an intestinal bactericidal lectin. Science 313, 1126–1130 (2006).
21. Guarner, F. et al. Mechanisms of disease: the hygiene hypothesis revisited. Nature Clin.
Pract. Gastroenterol. Hepatol. 3, 275–284 (2006).
22. Kelly, D. et al. Commensal anaerobic gut bacteria attenuate inflammation by regulating
nuclear–cytoplasmic shuttling of PPAR-γ and RelA. Nature Immunol. 5, 104–112
(2004).
23. Martin, F. P. et al. A top-down systems biology view of microbiome–mammalian metabolic
interactions in a mouse model. Mol. Syst. Biol. 3, 112 (2007).
24. Mazmanian, S. K., Liu, C. H., Tzianabos, A. O. & Kasper, D. L. An immunomodulatory
molecule of symbiotic bacteria directs maturation of the host immune system. Cell 122,
107–118 (2005).
25. Rakoff-Nahoum, S., Paglino, J., Eslami-Varzaneh, F., Edberg, S. & Medzhitov, R. Recognition
of commensal microflora by Toll-like receptors is required for intestinal homeostasis. Cell
118, 229–241 (2004).
26. Ley, R. E., Peterson, D. A. & Gordon, J. I. Ecological and evolutionary forces shaping
microbial diversity in the human intestine. Cell 124, 837–848 (2006).
27. Gong, J. et al. 16S rRNA gene-based analysis of mucosa-associated bacterial community
and phylogeny in the chicken gastrointestinal tracts: from crops to ceca. FEMS Microbiol.
Ecol. 59, 147–157 (2007).
28. Mackie, R. I., Rycyk, M., Ruemmler, R. L., Aminov, R. I. & Wikelski, M. Biochemical and
microbiological evidence for fermentative digestion in free-living land iguanas (Conolophus
pallidus) and marine iguanas (Amblyrhynchus cristatus) on the Galapagos archipelago.
Physiol. Biochem. Zool. 77, 127–138 (2004).
29. Nelson, K. E. et al. Phylogenetic analysis of the microbial populations in the wild herbivore
gastrointestinal tract: insights into an unexplored niche. Environ. Microbiol. 5, 1212–1220
(2003).
30. Uenishi, G. et al. Molecular analyses of the intestinal microbiota of chimpanzees in the wild
and in captivity. Am. J. Primatol. 69, 367–376 (2007).
31. Wilson, K. H., Brown, R. S., Andersen, G. L., Tsang, J. & Sartor, B. Comparison of fecal biota
from specific pathogen free and feral mice. Anaerobe 12, 249–253 (2006).
32. Wilson, D. S. Biological communities as functionally organized units. Ecology 78,
2018–2024 (1997).
33. Foster, K. R. & Wenseleers, T. A general model for the evolution of mutualisms. J. Evol. Biol.
19, 1283–1293 (2006).
34. Sachs, J. L., Mueller, U. G., Wilcox, T. P. & Bull, J. J. The evolution of cooperation. Q. Rev. Biol.
79, 135–160 (2004).
35. Flint, H. J. Polysaccharide breakdown by anaerobic microorganisms inhabiting the
mammalian gut. Adv. Appl. Microbiol. 56, 89–120 (2004).
36. Flint, H. J., Duncan, S. H., Scott, K. P. & Louis, P. Interactions and competition within the
microbial community of the human colon: links between diet and health. Environ. Microbiol.
9, 1101-1111 (2007).
37. Fons, M., Gomez, A. & Karjalainen, T. Mechanisms of colonisation and colonisation
resistance of the digestive tract. Part 2: bacteria/bacteria interactions. Microb. Ecol. Health
Dis. 12, 240–246 (2000).
38. Reid, G. & Bruce, A. W. Probiotics to prevent urinary tract infections: the rationale and
evidence. World J. Urol. 24, 28–32 (2006).
39. Brook, I. The role of bacterial interference in otitis, sinusitis and tonsillitis. Otolaryngol. Head
Neck Surg. 133, 139–146 (2005).
40. Servin, A. L. Antagonistic activities of lactobacilli and bifidobacteria against microbial
pathogens. FEMS Microbiol. Rev. 28, 405–440 (2004).
817
NATURE|Vol 449|18 October 2007
INSIGHT REVIEW
41. Tilman, D. Niche tradeoffs, neutrality, and community structure: a stochastic theory of
resource competition, invasion, and community assembly. Proc. Natl Acad. Sci. USA 101,
10854–10861 (2004).
42. Pool-Zobel, B., Veeriah, S. & Bohmer, F. D. Modulation of xenobiotic metabolising enzymes
by anticarcinogens — focus on glutathione S-transferases and their role as targets of
dietary chemoprevention in colorectal carcinogenesis. Mutat. Res. 591, 74–92 (2005).
43. Doebeli, M., Hauert, C. & Killingback, T. The evolutionary origin of cooperators and
defectors. Science 306, 859–862 (2004).
44. McFall-Ngai, M. Adaptive immunity: care for the community. Nature 445, 153 (2007).
45. Macpherson, A. J., Geuking, M. B. & McCoy, K. D. Immune responses that adapt the
intestinal mucosa to commensal intestinal bacteria. Immunology 115, 153–162 (2005).
46. Matzinger, P. The danger model: a renewed sense of self. Science 296, 301–305 (2002).
47. O’Keefe, S. J. et al. Why do African Americans get more colon cancer than Native Africans?
J. Nutr. 137, 175S–182S (2007).
48. Moore, W. E. & Moore, L. H. Intestinal floras of populations that have a high risk of colon
cancer. Appl. Environ. Microbiol. 61, 3202–3207 (1995).
49. Swenson, W., Wilson, D. S. & Elias, R. Artificial ecosystem selection. Proc. Natl Acad. Sci.
USA 97, 9110–9114 (2000).
50. Dethlefsen, L., Eckburg, P. B., Bik, E. M. & Relman, D. A. Assembly of the human intestinal
microbiota. Trends Ecol. Evol. 21, 517–523 (2006).
51. Young, V. B. & Schmidt, T. M. Antibiotic-associated diarrhea accompanied by large-scale
alterations in the composition of the fecal microbiota. J. Clin. Microbiol. 42, 1203–1206
(2004).
52. Li, J. et al. Identification of early microbial colonizers in human dental biofilm. J. Appl.
Microbiol. 97, 1311–1318 (2004).
53. Gill, S. R. et al. Metagenomic analysis of the human distal gut microbiome. Science 312,
1355–1359 (2006).
54. Klaassens, E. S., de Vos, W. M. & Vaughan, E. E. Metaproteomics approach to study the
functionality of the microbiota in the human infant gastrointestinal tract. Appl. Environ.
Microbiol. 73, 1388–1392 (2007).
55. Lepp, P. W. et al. Methanogenic Archaea and human periodontal disease. Proc. Natl Acad.
Sci. USA 101, 6176–6181 (2004).
56. Jernberg, C., Sullivan, A., Edlund, C. & Jansson, J. K. Monitoring of antibiotic-induced
alterations in the human intestinal microflora and detection of probiotic strains by use of
terminal restriction fragment length polymorphism. Appl. Environ. Microbiol. 71, 501–506
(2005).
57. Pepin, J. et al. Emergence of fluoroquinolones as the predominant risk factor for Clostridium
difficile-associated diarrhea: a cohort study during an epidemic in Quebec. Clin. Infect. Dis.
41, 1254–1260 (2005).
58. Lofmark, S., Jernberg, C., Jansson, J. K. & Edlund, C. Clindamycin-induced enrichment and
long-term persistence of resistant Bacteroides spp. and resistance genes. J. Antimicrob.
Chemother. 58, 1160–1167 (2006).
59. Sjolund, M., Tano, E., Blaser, M. J., Andersson, D. I. & Engstrand, L. Persistence of resistant
Staphylococcus epidermidis after single course of clarithromycin. Emerg. Infect. Dis. 11,
1389–1393 (2005).
60. Kolenbrander, P. E. et al. Bacterial interactions and successions during plaque development.
Periodontol. 2000 42, 47–79 (2006).
61. Savage, D. C. in Mucosal Immunology (eds Mestecky, J. et al.) 19-34 (Elsevier, Boston,
2005).
62. Caufield, P. W. et al. Natural history of Streptococcus sanguinis in the oral cavity of infants:
evidence for a discrete window of infectivity. Infect. Immun. 68, 4018–4023 (2000).
63. Samuel, B. S. & Gordon, J. I. A humanized gnotobiotic mouse model of host–Archaeal-
bacterial mutualism. Proc. Natl Acad. Sci. USA 103, 10011–10016 (2006).
64. Kolenbrander, P. E. et al. Communication among oral bacteria. Microbiol. Mol. Biol. Rev. 66,
486–505 (2002).
65. Xu, J. et al. A genomic view of the human–Bacteroides thetaiotaomicron symbiosis. Science
299, 2074–2076 (2003).
66. Schell, M. A. et al. The genome sequence of Bifidobacterium longum reflects its adaptation
to the human gastrointestinal tract. Proc. Natl Acad. Sci. USA 99, 14422–14427 (2002).
67. Czárán, T. L., Hoekstra, R. F. & Pagie, L. Chemical warfare between microbes promotes
biodiversity. Proc. Natl Acad. Sci. USA 99, 786–790 (2002).
68. Gordon, D. M., Riley, M. A. & Pinou, T. Temporal changes in the frequency of colicinogeny in
Escherichia coli from house mice. Microbiology
144, 2233–2240 (1998).
69. Sperandio, V., Torres, A. G., Jarvis, B., Nataro, J. P. & Kaper, J. B. Bacteria–host
communication: the language of hormones. Proc. Natl Acad. Sci. USA 100, 8951–8956
(2003).
70. Shiner, E. K., Rumbaugh, K. P. & Williams, S. C. Inter-kingdom signaling: deciphering the
language of acyl homoserine lactones. FEMS Microbiol. Rev. 29, 935–947 (2005).
71. Rendon, M. A. et al. Commensal and pathogenic Escherichia coli use a common pilus
adherence factor for epithelial cell colonization. Proc. Natl Acad. Sci. USA 104, 10637–10642
(2007).
72. Wren, B. W. The yersiniae — a model genus to study the rapid evolution of bacterial
pathogens. Nature Rev. Microbiol. 1, 55–64 (2003).
73. Monot, M. et al. On the origin of leprosy. Science 308, 1040–1042 (2005).
74. Brown, N. F., Wickham, M. E., Coombes, B. K. & Finlay, B. B. Crossing the line: selection and
evolution of virulence traits. PLoS Pathog. 2, e42 (2006).
75. Woolhouse, M. E., Webster, J. P., Domingo, E., Charlesworth, B. & Levin, B. R. Biological and
biomedical implications of the co-evolution of pathogens and their hosts. Nature Genet. 32,
569–577 (2002).
76. Wickham, M. E., Brown, N. F., Boyle, E. C., Coombes, B. K. & Finlay, B. B. Virulence is
positively selected by transmission success between mammalian hosts. Curr. Biol. 17,
783–788 (2007).
77. Walther, B. A. & Ewald, P. W. Pathogen survival in the external environment and the
evolution of virulence. Biol. Rev. Camb. Philos. Soc. 79, 849–869 (2004).
78. Boots, M. & Mealor, M. Local interactions select for lower pathogen infectivity. Science 315,
1284–1286 (2007).
79. Taylor, L. H., Latham, S. M. & Woolhouse, M. E. Risk factors for human disease emergence.
Phil. Trans. R. Soc. Lond. B 356, 983–989 (2001).
80. Naylor, S. W., Gally, D. L. & Low, J. C. Enterohaemorrhagic E. coli in veterinary medicine.
Int. J. Med. Microbiol. 295, 419–441 (2005).
81. Read, A. F. & Taylor, L. H. The ecology of genetically diverse infections. Science 292,
1099–1102 (2001).
82. West, S. A. & Buckling, A. Cooperation, virulence and siderophore production in bacterial
parasites. Proc. R. Soc. Lond B 270, 37–44 (2003).
83. Gardner, A., West, S. A. & Buckling, A. Bacteriocins, spite and virulence. Proc. R. Soc. Lond B
271, 1529–1535 (2004).
84. Wolfe, N. D., Dunavan, C. P. & Diamond, J. Origins of major human infectious diseases.
Nature 447, 279–283 (2007).
85. Woolhouse, M. E., Taylor, L. H. & Haydon, D. T. Population biology of multihost pathogens.
Science 292, 1109–1112 (2001).
86. Cheesman, S. E. & Guillemin, K. We know you are in there: conversing with the indigenous
gut microbiota. Res. Microbiol. 158, 2–9 (2007).
87. Hongoh, Y. et al. Intra- and interspecific comparisons of bacterial diversity and community
structure support coevolution of gut microbiota and termite host. Appl. Environ. Microbiol.
71, 6590–6599 (2005).
88. Kikuchi, Y. & Graf, J. Spatial and temporal population dynamics of a naturally occurring
two-species microbial community inside the digestive tract of the medicinal leech.
Appl. Environ. Microbiol. 73, 1984–1991 (2007).
89. Broderick, N. A., Raffa, K. F. & Handelsman, J. Midgut bacteria required for Bacillus
thuringiensis insecticidal activity. Proc. Natl Acad. Sci. USA 103, 15196–15199 (2006).
90. Cox, C. R. & Gilmore, M. S. Native microbial colonization of Drosophila melanogaster and its
use as a model of Enterococcus faecalis pathogenesis. Infect. Immun. 75, 1565–1576 (2007).
91. Fraune, I. & Bosch, T. Long-term maintenance of species-specific bacterial microbiota in
the basal metazoan Hydra. Proc. Natl Acad. Sci. USA 104, 13146–13151
92. Nyholm, S. V. & McFall-Ngai, M. J. The winnowing: establishing the squid–Vibrio symbiosis.
Nature Rev. Microbiol. 2, 632–642 (2004).
93. Davidson, S. K. & Stahl, D. A. Transmission of nephridial bacteria of the earthworm Eisenia
fetida. Appl. Environ Microbiol. 72, 769–775 (2006).
94. Goodrich-Blair, H. & Clarke, D. J. Mutualism and pathogenesis in Xenorhabdus and
Photorhabdus: two roads to the same destination. Mol. Microbiol. 64, 260–268 (2007).
95. DeSantis, T. Z. et al. Greengenes, a chimera-checked 16S rRNA gene database and
workbench compatible with ARB. Appl. Environ. Microbiol. 72, 5069–5072 (2006).
96. Collins, M. D. et al. The phylogeny of the genus Clostridium: proposal of five new genera and
eleven new species combinations. Int. J. Syst. Bacteriol. 44, 812–826 (1994).
Acknowledgements Research in the laboratory of D.A.R. is supported by funds from
the Doris Duke Charitable Foundation, the Horn Foundation, the Office of Naval
Research and the National Institutes of Health (NIH). Research in the laboratory
of M.M.-N. is supported by the NIH and the National Science Foundation. D.A.R.
is a recipient of an NIH Director’s Pioneer Award and a Doris Duke Distinguished
Clinical Scientist Award.
Author Information Reprints and permissions information is available at
npg.nature.com/reprints. Correspondence should be addressed to D.A.R.
(relman@stanford.edu).
818
NATURE|Vol 449|18 October 2007
INSIGHT REVIEW
