Functional metagenomic investigations of the human
Aimee M. Moore1,2†, Christian Munck3†, Morten O.A. Sommer3* and Gautam Dantas1,4*
1Center for Genome Sciences and Systems Biology, Washington University School of Medicine, St. Louis, MO, USA
2Department of Pediatrics, Washington University School of Medicine, St. Louis, MO, USA
3Department of Systems Biology,Technical University of Denmark, Lyngby, Denmark
4Department of Pathology and Immunology, Washington University School of Medicine, St. Louis, MO, USA
Peter J.Turnbaugh, Harvard
Alain Stintzi, Ottawa Institute of
Systems Biology, Canada
Jo Handelsman,Yale University, USA
Gautam Dantas, Department of
Pathology and Immunology, Center
for Genome Science and Systems
Biology, Washington University
School of Medicine, 4444 Forest Park
Avenue, Room 6215, Campus Box
8510, St. Louis, MO 63108, USA.
Morten O. A. Sommer, Department
of Systems Biology,Technical
University of Denmark, Matematik
Torvet Building 301, DK-2800 Lyngby,
†Aimee M. Moore and Christian
Munck have contributed equally to
The human intestinal microbiota encode multiple critical functions impacting human health,
including metabolism of dietary substrate, prevention of pathogen invasion, immune sys-
tem modulation, and provision of a reservoir of antibiotic resistance genes accessible to
pathogens.The complexity of this microbial community, its recalcitrance to standard culti-
vation, and the immense diversity of its encoded genes has necessitated the development
of novel molecular, microbiological, and genomic tools. Functional metagenomics is one
such culture-independent technique, used for decades to study environmental microor-
ganisms, but relatively recently applied to the study of the human commensal microbiota.
nity, independent of identity to known genes, by subjecting the metagenome to functional
to study the functional diversity of the intestinal microbiota, and discuss how an approach
combining high-throughput sequencing, cultivation, and metagenomic functional screens
can improve our understanding of interactions between this complex community and its
Keywords: functional metagenomics, human intestinal microbiota, antibiotic resistome
A growing body of evidence indicates that human microbial com-
munities play a role in the pathogenesis of diseases as diverse
as neonatal necrotizing enterocolitis, asthma, eczema, inflamma-
tory bowel disease, obesity, atherosclerosis, insulin resistance, and
neoplasia. Because the composition of the intestinal microbiota
is highly variable in early infancy and largely stabilizes by the
end of the first year of life, understanding the determinants of
the composition of the infant enteric microbial community is
of particular interest (Vael and Desager, 2009). The decreased
rates of early childhood infections, atopic disease, diabetes, and
obesity in breastfed infants have been well-documented (Oddy,
2004; Bartok and Ventura, 2009; Duijts et al., 2009; Le Huerou-
Luron et al., 2010; Gouveri et al., 2011), as have the differences
in the composition of the intestinal microbiota between breast-
rapidly become the predominant group of organisms (Harm-
sen et al., 2000), while formula-fed infants develop a different
microbial community comprised of some Bifidobacteria and large
proportions of other potentially pathogenic organisms, including
Bacteroides, Staphylococcus, Enterobacteria, Clostridia, and Ente-
rococcus spp. (Yoshioka et al., 1983; Rubaltelli et al., 1998). Fer-
mentative metabolites generated by Bifidobacterium and other
saccharolytic species decrease stool pH, inhibiting the growth of
potential pathogens in breastfed infants (Bullen et al., 1976). Rel-
ative decreases in the proportion of Bifidobacteria and concomi-
tant increases in other enteric flora in infancy have been linked
to disease states later in life: increased numbers of Escherichia
coli and Clostridium difficile are associated with the develop-
ment of atopic disease such as asthma and eczema (Penders
et al., 2007), while lower Bifidobacterial counts and greater num-
bers of Staphylococcus aureus are associated both with overweight
mothers (Collado et al., 2010) and an increased risk of the
infant becoming overweight in early childhood (Kalliomaki et al.,
decreasing the likelihood of bacterial translocation during peri-
ods of metabolic stress (Wang et al., 2006; Ruan et al., 2007).
The gastrointestinal microbiota appear essential to the develop-
ment of the immune system (Round and Mazmanian, 2009),
can act as a reservoir for antibiotic resistance genes (van der
Waaij and Nord, 2000), and may contribute to chronic inflam-
matory states (Erridge et al.,2007; Ghanim et al.,2009). Together,
these data suggest that understanding the interactions between
pathogenesis of complex human diseases such as obesity and the
metabolic syndrome, atopic disease, and autoimmune disorders,
October 2011 | Volume 2 | Article 188 | 1
Moore et al. Functional metagenomics of human microbiota
and thereby provide a rich source for mining novel therapeutic
To understand microbial community effects on human health,
both the phylogenetic profile of human microbial communities
and the functional capacity of their members must be charac-
terized. Much progress has been made toward these ends using
direct bacterial culture, 16S sequencing, shotgun metagenomic
of microbial metabolites. These approaches have yielded incredi-
ble insights ranging from shifts in prevalent bacterial phylotypes
and altered metabolic profiles in human subjects with inflamma-
tory bowel disease, variations in the composition of the intestinal
microbiota with human diet and functional differences in the gut
the composition of the gastrointestinal microbiota during infancy
and childhood, and the genetic epidemiology of antibiotic resis-
tance in the intestinal microbiota. (Rimbara et al.,2005;Qin et al.,
2006; Turnbaugh et al., 2006; Bezabeh et al., 2009; Jansson et al.,
et al., 2011; Rigsbee et al., 2011). In this perspective, we will focus
currently used to characterize the human microbiota.
Direct culture, historically the sine qua non of microbiology,
readily provides information on the functional characteristics of
the species being investigated. The majority of gastrointestinal
Traditional estimates are that only 15–20% of the gastrointestinal
2005; Gill et al., 2006). A recent report by Goodman et al. (2011)
showed, using high-throughput 16S sequencing in combination
with extensive anaerobic culturing, that up to 56% of gastroin-
testinal microbial species are culturable. Although this represents
remains a significant proportion of unculturable organisms that
from simple PCR-based screens to large metagenomic sequenc-
ing analyses and functional metagenomic screens. Together, these
methods have expanded our knowledge about the fraction of the
GI tract microbiota that cannot be characterized by culture-based
FUNCTIONAL METAGENOMICS: AN EMERGING TECHNIQUE
FOR CHARACTERIZING UNCULTURABLE ORGANISMS
to characterize the unculturable fraction of soil microbiota (Han-
delsman et al., 1998; Rondon et al., 2000) and successfully used
for years to characterize the functional diversity of microbes in
a variety of environments (Warnecke et al., 2007; Allen et al.,
2009b; Berlemont et al., 2009; Torres-Cortes et al., 2011), has
relatively recently been adapted to characterize the functions of
human microbial communities,representing an interesting cross-
pollination between environmental microbiology and biomedical
science. The functional metagenomic screening method, based
on clone libraries containing genomic DNA from a microbial
community, does not require direct culture of fastidious organ-
isms. Instead, clone libraries are constructed by first extracting
and shearing DNA from a sample of a microbial community,
then cloning the fragmented DNA into a relevant vector, and
subsequently transforming this vector into a suitable host strain
(Figure 1). Once a library is constructed, it can be function-
ally screened by cultivation on selective media or by employing
a reporter system. Using this approach, it is possible to identify
FIGURE 1 | Schematic presentation of the processes leading from fecal
microbial sample to functional selection of antibiotic resistance genes.
Metagenomic DNA is directly extracted from any microbial community (e.g.,
from a fecal sample) and cloned into an expression system in a cultivable,
genetically tractable host strain (e.g., E. coli). Metagenomic transformants
harboring DNA fragments that encode antibiotic resistance genes are
selected by subjecting the library of clones to specific antibiotics at
concentrations which inhibit the growth of the untransformed indicator strain.
Selected DNA fragments can then be sequenced to identify the specific
Frontiers in Microbiology | Cellular and Infection Microbiology
October 2011 | Volume 2 | Article 188 | 2
Moore et al. Functional metagenomics of human microbiota
genes encoding a variety of functions such as antibiotic resis-
tance, metabolism of complex compounds, and modulation of
eukaryotic cells. Subsequent sequencing and in silico analysis of
the DNA inserts from isolated clones provides information about
the source of the genes and the putative mechanisms of action of
INTERACTIONS WITHIN MEMBERS OF THE INTESTINAL
MICROBIOTA: ANTIBIOTIC RESISTANCE
One area of early success for functional metagenomic screens is in
the discovery of new antibiotic resistance genes in the human gas-
trointestinal microbiota. Multidrug resistant bacteria are increas-
ingly prevalent in both hospitals and the community, and pose
a growing threat to human health (Boucher et al., 2009; Högberg
ciated with increased mortality and cost of treatment (Maragakis
et al.,2008),and novel antibiotic discovery has not kept pace with
the emergence of microbial resistance to existing agents (Högberg
et al., 2010). In order to develop a rational approach to curtail
the emergence of antibiotic resistance in human pathogens, a
bial communities is required. Pathogenic organisms present in
the environment may acquire resistance genes from soil or water
microbes, while commensal gastrointestinal organisms that are
continuously exposed to the outside environment via host inges-
tion of food, may also come in contact with pathogenic bacteria
made in recent years documenting genetic resistance reservoirs
and patterns of gene flow within and between environmental and
human commensal microbiota, fully characterizing the diversity
trol the emergence of ever more resistant organisms (Aminov and
Mackie, 2007; Martinez, 2008; Aminov, 2009; Allen et al., 2010).
in the detection and quantification of antibiotic resistance genes
present in the gastrointestinal microbiota. PCR assays have been
used to detect the presence of known tetracycline resistance genes
(tet) in fecal samples from antibiotic-naive infants (Gueimonde
et al., 2006). Similarly, qPCR has been used to quantify the levels
of tet and erm genes, which confer resistance to tetracycline and
macrolide, lincosamide, and streptogramin B antibiotics respec-
tively, in animal and human waste water (Smith et al., 2004;
Auerbach et al.,2007; Chen et al.,2010). The extraordinary speci-
ficity of PCR-based studies is also an important limitation of the
technique: because PCR can only be used to interrogate a sample
for known genes, it is an ineffective method for identifying novel
tifying genes by their function in an expression vector rather
than by a specific sequence used for PCR probing. Using this
approach, novel antibiotic resistance genes have been identified
in different environments including oral microbiota, soil micro-
biota, and moth gut flora (Diaz-Torres et al., 2003; Riesenfeld
et al., 2004; Allen et al., 2009a). Sommer et al. (2009) demon-
strated the power of metagenomic functional screens to iden-
tify novel antibiotic resistance genes in fecal samples from two
healthy adults. Metagenomic libraries with a total size of 9.3Gb
(gigabases) and an average insert size of 1.8kb (kilobases) were
screened for resistance against 13 different antibiotics, revealing
95 unique inserts representing a variety of known resistance genes
as well as 10 novel beta-lactamase gene families (Sommer et al.,
2009). Genes identified using metagenomic functional screens
were, on average, 61% identical to known resistance genes from
pathogenic organisms, while genes identified via aerobic cultur-
ing of isolates from the same individuals had greater than 90%
sequence identity to previously described resistance genes. One of
the novel resistance genes identified with the functional metage-
function, demonstrating the power of metagenomic functional
screens to identify novel resistance genes even in fully sequenced
and apparently well-annotated organisms. Antibiotic resistance
with high sequence identity to known genes were more likely
than novel genes to be flanked by mobile genetic elements such
as transposases, possibly indicating that the novel genes rep-
resent a potential resistance reservoir that has not yet become
widely disseminated. Recent work by Goodman et al. (2011)
demonstrated that interindividual differences in gastrointestinal
antibiotic resistance genes can be detected by subjecting both
uncultured fecal samples as well as pools of phylogenetically rep-
resentative fecal culture collections to metagenomic functional
screens. Notably, the presence or absence of specific resistance
genes (e.g., those encoding amikacin resistance) in uncultured
samples, as determined by functional metagenomics, correlated
with the fraction of cultured isolates phenotypically resistant to
those compounds, and the presence of the exact genes identified
in phenotypically resistant cultured strains. These authors also
found that the nearest genome-sequenced phylogenetic neigh-
bors of the resistant strains isolated from the the gastrointesti-
nal microbiota of the sampled individuals lacked similar resis-
tance genes, further highlighting the diversity and individualized
nature of antibiotic resistomes. Together, these studies indicate
that the gastrointestinal microbiota are likely to harbor many
more resistance genes that will continue to be revealed by further
Functional metagenomic screens have also been used to mine
the resistance reservoir in the intestinal microbiota of farm ani-
tions and promote growth, and mounting evidence indicates that
these practices lead to increased antibiotic resistance not only in
the microbiota of the treated animals but also in their human
caregivers (Sorum et al.,2006). The scope of this problem is high-
tetracycline resistance genes in fecal samples from organically
farmed pigs that had not been exposed to antibiotics. Most of
explaining their persistence in an environment without any obvi-
resistance genes present in the intestinal microbiota must be fur-
fitness costs or benefits associated with their expression,as well as
by demonstrating the potential for direct transfer of the resistance
gene to pathogenic organisms.
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Moore et al. Functional metagenomics of human microbiota
FUNCTIONAL METAGENOMICS FOR UNDERSTANDING THE
GENETIC DETERMINANTS OF METABOLIC FUNCTION IN THE
As previously noted, specific variations in the composition of
the gastrointestinal microbial community have been linked to
important states of human health and disease. Recent advances
in understanding the interactions between bacterial metabolites
and the host cellular machinery have begun to illuminate the
physiologic basis of microbial contributions to human pathology.
species may provide a mechanistic explanation for the observed
2004), modulate tumorigenesis in animal models (Kelley et al.,
2007),and are being investigated for a role in modulating inflam-
Coakley et al.,2009). Short-chain fatty acids (SCFAs) are bacterial
metabolites that have wide-ranging effects on human physiol-
ogy. In animal models of prematurity, some SCFAs (acetic and
butyric acid) directly injure colonic mucosa in a dose-dependent
fashion in the most immature age groups (Lin et al., 2002), an
effect that disappears with increasing postnatal age (Nafday et al.,
2005). This suggests a possible role for bacterial metabolites in
the complex pathogenesis of necrotizing enterocolitis, a necroin-
flammatory disease commonly seen in preterm infants but non
existent in older age groups. Butyrate,a SCFA that is produced by
fermentation of dietary fiber, has a variety of effects modulating
(downregulated in cancer cells), and is protective against colon
cancer in animal models. It also inhibits histone deacetylase and
inhibits TNF-κB activation, which may explain its role in mod-
ulating inflammation. Acetate and propionate, two other SCFAs,
have opposing effects on cholesterol biosynthesis (Wong et al.,
sity via interaction with fasting-induced adipocyte factor (Fiaf),
storage in adipocytes, fatty acid oxidation, gastrointestinal motil-
ity, and nutrient absorption (Backhed et al., 2007; Samuel et al.,
Functional metagenomic screens offer a powerful means for
et al. (2008) employed a functional screen using a large-insert
metagenomic library to identify bile salt hydrolases within the
playing bile salt hydrolase activity revealed a broad phylogenetic
distribution of bile salt hydrolase enzymes suggesting that this
metabolic capacity is a conserved trait among bacteria adapted
to life in the human gastrointestinal tract. Since bile salts play
important roles in the processing and uptake of dietary fats in the
intestines, microbial catabolism of these compounds may affect
the amount of energy extracted from the diet.
Catabolism of fibers indigestible by the human host, another
significant activity of the human intestinal microbiota, has been
investigated using successive rounds of functional screens to
enrich the metagenomic library with carbohydrate-metabolizing
enzymes followed by high-throughput sequencing to identify
genetic determinants of carbohydrate metabolism within the
human gastrointestinal microbiota (Tasse et al.,2010). They iden-
tified 73 carbohydrate-metabolizing enzymes from the enriched
library, representing a fivefold increase in active genes identi-
fied compared to metagenomic sequencing without enrichment.
This highlights the strong potential of serial functional screens
combined with high-throughput sequencing to identify novel
genes and yield increasingly comprehensive information on the
metabolic potential of a given microbial community.
INTEGRATING FUNCTIONAL SCREENS WITH SHOT-GUN
METAGENOMIC SEQUENCING ANALYSIS
The advent of convenient applications for metagenomic data
analysis such as MG-RAST and MEGAN have simplified annota-
together with the declining cost of high-throughput sequencing,
offer an efficient complement to functional screens (Huson et al.,
2007; Meyer et al., 2008). Several studies have used this approach
tify pathways, such as metabolism of sugars, amino acids, and
nucleotides, that are enriched in the gastrointestinal microbiota
relative to representative genome-sequenced strains (Gill et al.,
2006; Kurokawa et al., 2007; Turnbaugh et al., 2009; Arumugam
ing to their frequencies,a minimal gut genome and a minimal gut
metagenome have been described (Qin et al., 2010). The former
reflects the minimal set of genes required by a single member of
the gastrointestinal microbiota,while the latter indicates the min-
imal set of genes required to sustain the aggregate gastrointestinal
microbiota. The minimal gut genome includes genes essential to
all bacteria (e.g., replication, transcription, translation) as well as
for metabolism of complex sugars, underscoring the importance
of coupled metabolism in sustaining the GI tract microbiota. The
importance of confirming gene function in vitro and in vivo to
ensure reliable annotation is illustrated by Hess et al. (2011), who
used metagenomic sequencing to identify >20,000 carbohydrate
active genes from the cow rumen microbiota. From this gene
set,they selected 90 in silico predicted carbohydrate-metabolizing
genes, expressed them, subjected them to functional assays, and
found that 51 genes were enzymatically active in vitro (Hess et al.,
2011). These studies exemplify how metagenomic sequencing,
automated annotation of large data sets,and functional screening
comprise a powerful toolkit capable of characterizing functional
networks in highly complex environments such as the GI tract
FUNCTIONAL MAPPING OF INTERACTIONS BETWEEN
HUMANS AND THEIR INTESTINAL MICROBIOTA
Functional metagenomic screens may also illuminate the genetic
nal microbiota have long been known to modulate intestinal
epithelia, for instance, by stimulating intestinal cell differentia-
tion (Bry et al., 1996). In order to identify specific bacterial gene
Frontiers in Microbiology | Cellular and Infection Microbiology
October 2011 | Volume 2 | Article 188 | 4
Moore et al. Functional metagenomics of human microbiota
(2007) used cell lysate from individual clones in a gastrointestinal
metagenomic library to screen for modulation of cell growth in
CV-1 kidney fibroblast and HT-29 human colonic tumor cells.
Using this approach, they identified 30 growth-stimulating and
20 growth-inhibiting clones, with Bacteroidetes as the dominant
phylum among both sets. Using transposon mutagenesis on these
sets of clones, they identified seven candidate genes with putative
growth modulation effects.
Functional metagenomic screens have also been designed to
investigate the immune-modulatory capacity of the gastrointesti-
nal microbiota. To identify clones modifying the host immune
response, Lakhdari et al. (2010) constructed an NF-κB activated
reporter system from a human colorectal carcinoma cell line.
By screening metagenomic libraries of GI tract microbiota from
patients with Crohn’s disease, in which NF-κB activity is fre-
quently elevated (Ellis et al., 1998), they identified several clones
either inducing or inhibiting NF-κB activity. Together,these stud-
ies demonstrate the potential for functional metagenomic screens
to illuminate the genetic mechanisms for microbial community
contribution to the development of the human immune sys-
tem and the pathogenesis of atopic, autoimmune, and neoplastic
disease, which may provide novel therapeutic targets for these
In addition to interacting with human cells,commensal bacte-
ria can also use quorum-sensing to convey signals over distances
and thereby coordinate community gene expression. Guan et al.
(2007) used a metabolite regulated expression(METREX) screen
based on a quorum-sensing inducible promoter fused to gfp to
identify genes encoding a new class of quorum-sensing inducing
molecules in moth gut microbiota, demonstrating the power of
functional metagenomics for characterizing the determinants of
community behavior in uncultured organisms.
FUNCTIONAL METAGENOMICS FOR REFINING PRE- AND
Increased understanding of the effects of gastrointestinal micro-
biota on human health has generated interest in targeting these
communities for therapeutic intervention (Cani and Delzenne,
2011). Short-chain carbohydrates that are indigestible by humans
but are fermentable by some microbes have demonstrable efficacy
in increasing the populations of Lactobacilli and Bifidobacteria
in the human gastrointestinal tract (Wang and Gibson, 1993).
Investigations of galactose oligosaccharides (GOS) and fructose
strated increased Bifidobacterial populations, decreased stool pH,
breastfed infants,and reduced populations of potential pathogens
such as Clostridia spp., Bacteroides spp., and E. coli (Fanaro et al.,
2005; Knol et al., 2005; Costalos et al., 2008; Magne et al., 2008;
may promote blooms of beneficial bacteria more effectively than
direct administration of pro-biotic organisms: a study directly
comparing infant formula containing Bifidobacterium animalis
with GOS/FOS-supplemented formula revealed a significantly
greater proportion of Bifidobacterial species in the infants fed
(Bakker-Zierikzee et al., 2005). Administration of prebiotics such
as inulin and oligosaccharides in adult humans have shown some
effect on hunger and satiety mechanisms (Whelan et al., 2006;
gies such as atopy and inflammatory bowel disease (Guarner,
2005; Roberfroid et al., 2010). Functional metagenomics has the
potential to refine current prebiotic therapies by more completely
defining the genetic determinants of metabolism for given con-
stituents of a microbial community, providing a rational basis
for more precise design of prebiotic agents intended to promote
blooming of a specific subset of organisms.
TOWARD A COMPLETE FUNCTIONAL REPRESENTATION OF
THE GASTROINTESTINAL MICROBIOTA
Functional metagenomic screens have been successful in eluci-
important limitations. First, the DNA insert must be compatible
with the host’s expression machinery and the gene product must
Uchiyama and Miyazaki, 2009). Second, the host must be suited
for the screen: when screening for antibiotic resistance genes, a
host sensitive to the antibiotic of interest must be chosen. Third,
the insert size may restrict the diversity of functions portrayed
in a screen; a small insert library cannot reveal the function of
genes organized in large operons such as many metabolic path-
ways or some efflux pumps associated with antibiotic resistance.
Finally, the expression level of the insert can significantly affect
the result of a functional screen. Using a high-copy plasmid as
vector or a strong synthetic promoter can result in an overesti-
mation of functionality. Conversely, overexpression of potentially
lethal proteins may cause underestimation of functional genes,
(e.g., cell lysis due to overexpression of efflux pumps). Despite
these limitations, multiple studies demonstrate the potential for
culture, 16S sequencing, shotgun metagenomic sequencing, and
metabolomic analysis to offer new insight into the complex inter-
actions between microbial communities and their human hosts.
Used in concert, these techniques promise to expand our under-
standing of microbial community function, its impact on human
health, and to provide novel targets for therapeutic development
in the coming years.
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Conflict of Interest Statement: The
authors declare that the research was
conducted in the absence of any
commercial or financial relationships
that could be construed as a potential
conflict of interest.
Received: 01 April 2011; paper pend-
ing published: 31 May 2011; accepted:
23 August 2011; published online:
Citation: Moore AM, Munck C, Sommer
MOA and Dantas G (2011) Functional
intestinal microbiota. Front. Microbio.
2:188. doi: 10.3389/fmicb.2011.00188
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