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The human intestine harbors a complex bacterial community called the gut microbiota. This microbiota is specific to each individual despite the existence of several bacterial species shared by the majority of adults. The influence of the gut microbiota in human health and disease has been revealed in the recent years. Particularly, the use of germ-free animals and microbiota transplant showed that the gut microbiota may play a causal role in the development of obesity and associated metabolic disorders, and lead to identification of several mechanisms. In humans, differences in microbiota composition, functional genes and metabolic activities are observed between obese and lean individuals suggesting a contribution of the gut microbiota to these phenotypes. Finally, the evidence linking gut bacteria to host metabolism could allow the development of new therapeutic strategies based on gut microbiota modulation to treat or prevent obesity.
Gut microbiota and obesity
Philippe Ge
Received: 11 August 2015 / Revised: 29 September 2015 / Accepted: 5 October 2015 / Published online: 12 October 2015
Springer Basel 2015
Abstract The human intestine harbors a complex bacte-
rial community called the gut microbiota. This microbiota
is specific to each individual despite the existence of sev-
eral bacterial species shared by the majority of adults. The
influence of the gut microbiota in human health and disease
has been revealed in the recent years. Particularly, the use
of germ-free animals and microbiota transplant showed
that the gut microbiota may play a causal role in the
development of obesity and associated metabolic disorders,
and lead to identification of several mechanisms. In
humans, differences in microbiota composition, functional
genes and metabolic activities are observed between obese
and lean individuals suggesting a contribution of the gut
microbiota to these phenotypes. Finally, the evidence
linking gut bacteria to host metabolism could allow the
development of new therapeutic strategies based on gut
microbiota modulation to treat or prevent obesity.
Keywords Microbiome Gnotobiotic models
Metabolic syndrome Intestinal permeability Antibiotics
Probiotics Prebiotics Fecal transplant
AMPK AMP-activated protein kinase
ANGPTL4 Angiopoietin-like 4
BSH Bile salt hydrolase
DIO Diet-induced obesity
eCB Endocannabinoı
FFAR Free fatty acid receptor
FMT Fecal microbiota transplant
GF Germ-free
GI Gastro-intestinal
GLP Glucagon-like peptide
HFD High-fat diet
HGC High gene count
IBD Inflammatory bowel disease
LGC Low gene count
LPL Lipoprotein lipase
LPS Lipopolysaccharides
PYY Peptide YY
SCFA Short chain fatty acid
TLR Toll-like receptor
TMA Trimethylamine
Obesity is a major health concern, whose incidence is
increasing dramatically in both industrialized and devel-
oping countries [1]. Nowadays, more than 500 million
people are obese worldwide leading to considerable eco-
nomical costs as well as public health challenge [2].
Indeed, obesity predisposes individuals to a number of
diseases including diabetes, cardiovascular diseases, non-
alcoholic fatty liver disease, cancer, and some immune-
related disorders. Several genes have been implicated in
the determination of body weight, but this genetic sus-
ceptibility may only explain a small fraction of obesity, and
cannot explain the rise in incidence of this pathology.
Therefore, obesity arises from complex interactions
between genes and environmental factors such as diet, food
&Philippe Ge
INRA, UMR1319 MICALIS, Equipe AMIPEM, Building
442, Domaine de Vilvert, 78350 Jouy-en-Josas, France
AgroParisTech, UMR MICALIS, 78350 Jouy-en-Josas,
Cell. Mol. Life Sci. (2016) 73:147–162
DOI 10.1007/s00018-015-2061-5 Cellular and Molecular Life Sciences
components and/or way of life, and results from a long-
term positive imbalance between energy intake and
expenditure with excessive increase in body fat [3].
Overall, the complex pathways that lead to development of
overweight and its consequences are not thoroughly
understood and recent studies have suggested that the gut
microbiota (the trillions of bacteria that normally reside
within the human gastrointestinal (GI) tract) should be
factored into this equation [4]. Indeed, there is growing
evidence that the gut microbiota and its bacterial genome
(the microbiome) affect nutrient acquisition, energy regu-
lation and fat storage [5]. These findings raise the
possibility that the gut microbiota plays a role in regulating
host energy metabolism and may contribute towards the
development of obesity and associated metabolic diseases.
The objective of this review is to provide an overview of
this emerging field related to the role of the gut microbiota
in obesity and metabolic disorders.
The gut microbiota
Development and stability of the gut microbiota
Foetuses are thought to be sterile in uteri although low
levels of bacterial translocation through the placental cir-
culation may provide an elementary microbiota before
birth [6]. During birth, bacteria from the mother and the
surrounding environment colonize the infant’s gut rapidly.
The composition of this microbiota depends on various
factors including mode of birth (cesarean section or vaginal
delivery), antibiotic treatment, feeding (breastfeeding or
formula) or sanitation of the environment [7]. This
microbiota changes during the first years of life, under the
control of different factors including developmental chan-
ges in the gut environment, the host genotype, and the
introduction of solid foods, and a more complex and
stable community, close to the adult microbiota, is estab-
lished at approximately 3 years of age [7,8]. In adults, the
gut microbiota remains remarkably constant slightly fluc-
tuating around an individual core of stable colonisers.
Then, alterations occur at old age when digestive physi-
ology and diet changes [9]. Nevertheless, dietary factors or
antibiotic treatments can lead to transient changes. For
example, short-term treatment in humans with a single dose
of oral antibiotics alters the gut microbiota for as long as
4 weeks before it tends to recover its original composition
[10]. Moreover, some bacterial species are not recovered
even several months after treatment leading to a reduced
diversity following repeated antibiotic exposures [11].
Similarly, changes in diet lead to modification of the gut
microbiota composition. Diet provides nutrients for both
the host and the microbiota whose bacterial species can be
favoured or disadvantaged by dietary substrates. Therefore,
a study showed that diet changes in mice could explain
57 % of the total structural variation in gut microbiota,
whereas genetic mutation accounted for no more than 12 %
[12]. In humans, the gut microbiota in twin pairs and their
mothers has been characterized to assess the impact of
genotype and environmental exposures. It revealed that
family members share more similar microbiotas than
unrelated individuals, but that monozygotic twins have a
similar degree of variance than dizygotic twins, indicating
that early environmental exposures are key determinants of
adult gut bacterial community [13]. Interestingly, this study
also showed that if each microbiota is different in terms of
bacterial composition (no bacterial species shared by all
154 individuals), there was a wide array of shared micro-
bial genes named the ‘‘core microbiome’’, reflecting
evolutionary convergence of unrelated bacterial species.
The final composition of the microbiota is, therefore,
unique and specific to each individual [14] and a recent
study demonstrated that individuals could be uniquely
identified based on their microbiomes alone [15].
Nonetheless, the factors guiding this feature are still a
matter of debate.
Composition of the gut microbiota
In humans, the gut microbiota is a complex and dynamic
ecosystem that has coevolved with its host [16] and rep-
resents approximately 1 kg of our body weight. It is now
recognized that the communities of microbes in our gut
function as an organ with many metabolic, immunologic
and endocrine-like actions that influence human health
[17]. A large fraction of the gut bacteria still remains
impossible to culture so that our understanding of this
microbiota has been a long time limited by technical issues.
In the 1980s, Pace and co-workers introduced a new cul-
ture-independent method to identify bacteria, based on the
sequencing of the 16S rRNA gene [18]. The development
of these molecular techniques makes now possible a reli-
able assessment of the gut microbiota. Although Eukaryota
and Archaea domains are also present in the intestine,
Bacteria clearly predominate. Adult humans are colonized
by microbes from nine divisions (deep evolutionary lin-
eages) of Bacteria and at least one division of Archaea
[19]. This represents only a small fraction of the more than
70 bacterial and 13 archaeal divisions known in the bio-
sphere. Moreover, three bacterial divisions, the Firmicutes
(Gram-positive), Bacteroidetes (Gram-negative) and Acti-
nobacteria (Gram-positive), dominate the adult human gut
microbiota and account for more than 90 % of all bacteria,
whereas Methanobrevibacter smithii, a hydrogen-consum-
ing methanogen, dominates the Archaea domain [20].
These results were obtained from fecal samples which
148 P. Ge
correspond to the colonic population. However, the specific
density and type of bacteria in the GI tract are influenced
by environmental variations through the gut, such as pH,
oxygen, and nutrient availability. Hence, the bacterial
concentration is higher in the lower portion of the GI tract,
and if this gut section is largely populated by anaerobic
bacteria, aerobic bacteria dominate in the proximal gut.
Nevertheless, molecular analyses revealed that the same
bacteria are present in the different sections of the gut and
that only the relative abundance of the different species
varies [21].
Increased sequencing and bioinformatics capacities have
allowed entering into a new era, through the Human
Microbiome Project [22,23], not only giving access to the
type of bacterial species present but also to their gene
content [24]. Using these techniques, it is now estimated
that the human GI tract harbors approximately 10
microorganisms (ten times more cells than the whole
human body) and that each gut microbiota is composed of
500–1000 distinct bacterial species [20,25]. Moreover, the
MetaHit consortium has published a catalog of nearly
10 million non-redundant genes obtained from sequencing
fecal samples from 1267 individuals [26] indicating that
the human microbiome contains at least 100 times as many
genes as the human genome [2628]. Each individual hosts
on average 500–600,000 bacterial genes, about half of
which is shared by most individuals (functional core).
However, many functions are worn by the intestinal
microbiota in a fraction of humans only and could con-
tribute greatly to the metabolic diversity observed in the
human population. It was further observed that the human
population may be grouped into three distinct clusters,
based on gut microbiota composition [29]. This concept of
enterotypes is based on co-occurring of bacterial species,
with enterotypes being dominated by Bacteroides,Pre-
votella, and Ruminococcus, respectively. Although
divergences in enterotypes were first found to be inde-
pendent of geography, age, gender, or body mass index,
differences in long-term diet pattern have been associated
with these enterotypes [30]. Finally, although the concept
of enterotypes is still debated [31], it can be important for
making associations between gut microbiota and health and
defining what constitutes healthy and dysbiotic bacterial
Gut microbiota functions
The gut microbiota performs essential functions that the
human body cannot carry out, resulting in a symbiotic
relationship. The gut microbiota is, therefore, critical for
maintaining normal GI and immune functions, and efficient
digestion of nutrients [32,33]. For example, the microbiota
ferments otherwise indigestible food components,
synthesizes vitamins and other essential micronutrients,
metabolizes dietary toxins and carcinogens, converts
cholesterol and bile acids, assures the maturation of the
immune system, affects the growth and differentiation of
enterocytes, regulates intestinal angiogenesis, and protects
against enteric pathogens [34]. In the last decades, rela-
tionships between the gut microbiota and human health
have been established. Moreover, imbalances in its com-
position (i.e., dysbiosis) have been associated with immune
disorders, susceptibility to infections, and more recently to
several non-intestinal pathologies including cardiovascular
diseases, obesity, diabetes, liver or even brain diseases [35
38]. The current knowledge of the relationship between the
gut microbiota, obesity and associated diseases is presented
in the next parts of this review.
Gut microbiota and obesity
Evidences from germ-free animal models
The first evidence on the role of the gut microbiota on host
adiposity came from studies in germ-free (GF) animals,
i.e., animals devoid of bacteria and bred in sterile isolators.
In 1983, Wostmann and colleagues observed that GF
rodents require 30 % more calories to maintain their body
mass than conventional ones (possessing their own
microbiota) [39]. The potential mechanisms accounting for
this observation remained unclear until recent landmark
studies, preeminently originating from Jeffrey Gordon’s
laboratory at Washington University, Saint-Louis, MO,
USA. Indeed, they pioneered the investigation of gut
microbiota as a factor influencing fat storage and obesity.
They first found that conventionally raised mice have 42 %
more total body fat and 47 % more gonadal fat than GF
mice, although GF mice consumed more food [40]. They
next demonstrated that colonization of GF mice with a
cecum-derived microbiota from conventional mice pro-
duces a 60 % increase in body fat mass within 2 weeks.
The increase in body fat was accompanied by insulin
resistance, adipocyte hypertrophy, and increased levels of
circulating leptin and glucose [40]. This was partly
explained by the capacity of the gut microbiota to degrade
undigestible polysaccharides into monosaccharides which
could be absorbed leading to increased hepatic lipogenesis
in the host. Moreover, inoculation of a gut microbiota
suppresses the intestinal expression of angiopoietin-like 4
(ANGPTL4), a circulating inhibitor of lipoprotein lipase
(LPL). Conventionalization leads, therefore, to increased
adipocyte LPL activity and then to increased cellular
uptake of fatty acids and adipocyte triglycerides accumu-
lation [40]. The physiologic importance of ANGPTL4 was
further established by the demonstration that GF
Gut microbiota and obesity 149
mice have the same degree of adiposity as
their conventional counterparts. Finally, in contrast to
conventional mice, GF mice fed a high-fat, sugar-rich diet
are protected from diet-induced obesity (DIO) [41]. This
lean phenotype was associated with increased skeletal
muscle and liver levels of phosphorylated AMP-activated
protein kinase (AMPK) [41]. AMPK is an enzyme that is
conserved from yeast to humans and functions as a fuel
gauge that monitors cellular energy status and stimulated
fatty acid oxidation in peripheral tissue. Hence, the gut
microbiota may suppress skeletal muscle fatty acid oxida-
tion through a metabolic pathway involving
phosphorylation of AMPK. It was further observed that GF
mice receiving a high-fat diet (HFD) showed enhanced
insulin sensitivity with improved glucose tolerance and
reduced insulinemia in comparison to conventional mice.
This was associated with a reduced hypercholesterolemia, a
moderate accretion of hepatic cholesterol and an increase
in fecal cholesterol excretion suggesting an altered
cholesterol metabolism in GF mice [42]. Nevertheless, this
resistance to diet-induced obesity may depend on mice
genetic background and diet composition as C3H GF mice
were not found resistant to the obesogenic effect of a low-
sucrose, lard-based high-fat diet, while resistant to high
sucrose, palm oil-based high-fat diet [43]. Also, similar
body weights and adiposity were observed in GF and
conventional Fischer 344 rats [44]. In these rats, GF status
was associated with increased intestinal ANGPTL4 and
reduced hepatic lipogenesis as well as increased adipocyte
size suggesting that impact of a gut microbiota on fat
storage may be more complex than proposed by pioneer
Role of bacterial fermentation in host energy harvest
and appetite regulation
An important mechanism that can explain differences in
body fat between conventional and GF mice is the increase
in energy harvest from the food due to the fermentation of
the gut microbiota. Indeed, the gut microbiota is able to
process complex dietary plant polysaccharides, otherwise
inaccessible to humans, to monosaccharides and short-
chain fatty acids (SCFAs), principally acetate, propionate,
and butyrate. These SCFAs represent an important energy
source for our body as they can provide approximately
10 % of the daily energy supply in omnivores and up to
70 % in herbivores [45]. Butyrate is the preferred source of
energy for colonic epithelial cells and increases the density
of capillaries underlying the small intestine villus epithe-
lium [46]. Absorbed propionate and acetate are delivered to
hepatocytes where they can be used for gluconeogenesis
and lipogenesis, respectively. However, SCFAs act not
only as energy substrates for the host, but also as signaling
molecules, influencing energy intake and metabolism [47].
Therefore, they are ligands for at least two G-protein-
coupled receptors, free fatty acid receptor 2 (FFAR2 or
GPR43) and free fatty acid receptor 3 (FFAR3 or GPR41).
These GPCRs are mainly expressed by gut epithelial cells,
in particular enteroendocrine cells. FFAR2 is preferentially
activated by acetate, and FFAR3 by butyrate, whereas
propionate activates both receptors [48]. FFAR2
were found to resist to diet-induced obesity indicating that
FFAR2 could promote fat storage [49]. Similarly, it has
been shown that GF FFAR3
mice colonized by a
microbiota gained less fat mass than their wild-type lit-
termates [50]. The authors proposed that in the absence of
FFAR3 signaling, the plasma level of peptide YY (PYY) is
reduced leading to an increased gut motility and reduced
energy harvest from the diet. Therefore, FFAR2 and
FFAR3 would be modulators of host energy balance
through effects dependent upon the gut microbiota. These
receptors may also control eating behavior as increased
production of SCFAs due to fiber administration leads to
increased satiety and reduced food intake [5153]. These
effects are mediated by increases in the satietogenic gut
peptides PYY and glucagon-like peptide (GLP) 1 together
with decrease in orexigenic ghrelin [54]. Moreover, buty-
rate and propionate may reduce appetite via induction of
leptin expression from adipocytes [55]. Other pathways
may be involved in SCFAs outcomes as butyrate and
propionate were also shown to protect mice against diet-
induced obesity via FFAR3-independent mechanism [56].
Finally, SCFAs produced by the microbiota may constitute
a fine tune of the host metabolism by the regulation of
energy harvest, fat storage and appetite.
The influence of antibiotics on obesity
If the gut microbiota plays a role in obesity, modulation of
this bacterial community should have an impact on obesity
development. Antibiotics are known to disrupt microbiota
composition and while a rapid recovery is observed fol-
lowing short-term antibiotic treatment, pervasive effects
may be obtained after repeated antibiotic perturbations [10,
11]. Seventy years ago, it was first shown that adminis-
tration of low doses of antibiotics resulted in promotion of
growth in chicks [57]. This effect was confirmed in
mammalian livestock (cows, pigs, and sheep), and antibi-
otics have been used to promote weight gain in farm
animals for over 60 years. Moreover, antibiotics have no
growth-promoting effects in GF chicken [58] indicating
that changes in the microbiota of treated animals are
responsible for these effects. Interestingly, increases in
body mass are obtained only when antibiotic exposure
occurs early in life [59] which has been confirmed in mice
more recently [60,61]. Indeed, mice that received low-dose
150 P. Ge
penicillin treatment at birth had higher body weight gain
than their counterparts that were exposed at weaning [61].
Notably, these effects in mice lasted into adulthood weeks
after antibiotic treatment was stopped indicating that even
transient perturbations early in life can cause long-term
effects [62]. Finally, GF mice colonized with the micro-
biota from low-dose penicillin-treated mice gained more
fat mass than mice colonized with the microbiota from
control mice, demonstrating that the shifted microbiota
itself possesses the capacity to trigger obesity [61]. Nev-
ertheless, the effect of antibiotic exposure in obesity
development is dependent on the dose of antibiotics.
Indeed, high doses of antibiotics resulted in reduced fat
mass and insulin resistance in mice models of obesity [63].
It can be assumed that these high doses of antibiotics
reduce considerably the bacterial population and, therefore,
the capability of the gut microbiota to extract calories from
the diet, then mimicking the conditions observed in GF
animals. In humans, a growth-promoting effect of antibi-
otic treatments has been reported in the 1950s [64,65], but
these studies have been ignored until the recent demon-
stration of a link between the gut microbiota and obesity.
Therefore, epidemiological studies from different countries
have been recently launched to evaluate the impact of
antibiotic treatment in infancy on risk of obesity develop-
ment. The first published results seem to confirm that
exposure to antibiotics in early life is associated with an
increased body mass index [6669]. This suggests that the
massive use of antibiotics in the last decades could be
involved in the parallel increase in prevalence of obesity in
the western countries.
Gut microbiota and obesity: the dysbiosis concept
Dysbiosis is defined as the condition of having microbial
imbalances associated with a pathology. In accordance
with this definition, it has been shown, firstly in mice, that
obesity can be associated with an altered gut microbiota.
Ley et al. analyzed 5088 bacterial 16S rRNA gene
sequences from fat ob/ob, lean ob/?and wild-type mice
fed the same polysaccharide-rich diet [70]. They revealed
that obese animals have a 50 % reduction in the abundance
of Bacteroidetes and a proportional increase in Firmicutes
[70]. Ob/ob mice also harbored more methanogenic
Archaea, which may increase the efficiency of bacterial
fermentation via removal of H
. Similar differences in the
gut microbiota of lean versus obese humans were observed
in initial studies by the same team [71]. Indeed, it was
found that obese people had lower Bacteroidetes and more
Firmicutes than did lean control subjects. Moreover, the
Bacteroidetes to Firmicutes ratio approached a lean phe-
notype after 52 weeks of diet-induced weight loss.
Together, these results obtained in mice and humans
suggested that obesity alters the nature of the gut micro-
biota and raised the possibility that manipulation of the gut
microbiota towards a lower Firmicutes/Bacteroidetes ratio
could be a new strategy for treating obese people. How-
ever, if several studies confirmed an increased Firmicutes/
Bacteroidetes ratio in obese individuals [7274], others did
not report any differences in the abundance of Firmicutes
and Bacteroidetes in obese and lean subjects, or even found
an opposite relationship [7578]. Therefore, these phylum-
wide changes in the gut microbiota composition cannot be
currently considered as a biomarker for obesity. Changes in
microbiota composition at lower taxonomic levels have
also been associated with obesity and genera or even
specific bacterial species abundance may better define the
dysbiosis associated with obesity than Firmicutes/Bac-
teroidetes ratio. Moreover, if several bacterial genera have
been found increased or decreased in obese patients, bac-
terial species belonging to these genera may follow an
opposite trend suggesting a species or even strain-depen-
dent effect. As an example, if a higher level of
Lactobacillus has been found in obese patients than in
controls [72], some species belonging to this genus (L.
reuteri) have been indeed associated with obesity whereas
others (L. casei,L. plantarum) have been found associated
with weight loss in humans and animals [79]. Several
studies also reported an association between obesity and
lower populations of bifidobacteria [74,75,80], but only a
few bifidobacterial species have been proved to exert anti-
obesogenic effects in animal models [81]. Also, potential
opportunistic pathogens have been frequently associated
with obesity and a few bacterial strains have been proposed
as markers or even contributors to obesity. For instance,
Staphylococcus aureus was found more abundant in the gut
of overweight children and pregnant women [75,80,82].
Similarly, increased populations of Enterobacteriaceae
have been described in overweight pregnant women as
compared to normal weight [74]. Further, a bacterium
belonging to this family, Enterobacter cloacae strain B29,
has been isolated from the gut microbiota of an obese
human. B29 constituted almost 35 % of his gut microbiota
before dietary intervention, but became undetectable after
the volunteer lost 51.4 kg of his 174.8 kg initial weight.
Strikingly, this bacterium was shown to cause obesity when
introduced into high-fat diet-fed germ-free mice [83].
Conversely, Faecalibacterium prausnitzii, a butyrate pro-
ducer with known anti-inflammatory properties [84], has
been found decreased in morbidly obese subjects with
diabetes [73], similarly to its low abundance in patients
with inflammatory bowel disease (IBD) [85]. Moreover, it
was negatively associated with plasma levels of inflam-
matory cytokines. Similarly, Akkermansia muciniphila is
inversely related to fasting plasma glucose levels, visceral
fat accumulation, and adipocyte diameter in subcutaneous
Gut microbiota and obesity 151
adipose tissue in obese humans [86]. In addition, feeding
mice with A. muciniphila reduces body weight gain, fat
mass development, and low-grade inflammation and
restores gut barrier function [87]. Altogether these results
suggest that specific bacterial species, or a combination of
these species, may contribute directly to obesity develop-
ment or protection. However, it is still impossible to define
what an ‘‘obese’’ microbiota is due to a variety of co-
founding factors (including heterogeneity in genotype, diet,
lifestyle) that exist within the human population, and it is
likely that identical gut microbiota may have a different
influence on obesity development in the heterogeneous
human population. Also, we can hypothesize that the
contribution of the gut microbiota to obesity may rather
depend on the genes present in the microbiome and on the
metabolites produced than on taxonomic composition. The
development of high-throughput sequencing techniques
makes it now possible to get access to the whole gene
content of the gut microbiota. This could allow the iden-
tification of metabolic functions that can be
overrepresented in the microbiome of obese individuals.
Accordingly, it was first showed that the cecal microbiome
of genetically obese ob/ob mice contains more genes
involved in the hydrolysis of indigestible polysaccharides
leading to the hypothesis that the ob/ob microbiome has
increased capacity to harvest energy from the diet [88].
Consistently, fecal energy content was reduced and the
amounts of cecal SCFAs were increased in ob/ob vs wild-
type mice. In obese humans, genes involved in phospho-
transferase system, in carbohydrate metabolism and in
membrane transport, were found increased whereas genes
involved in transcription, nucleotide metabolism and
cofactors and vitamin metabolism were found depleted [13,
89]. Analysis of SCFAs also suggests that the fermentation
activity of the gut microbiota is higher in obese individuals,
propionate being the most increased SCFA [90]. Recently,
a bimodal distribution of microbial gene counts leading to
the stratification of the population as either ‘‘low gene
count’’ (LGC) or ‘‘high gene count’’ (HGC) has been
identified [91]. This microbial gene richness was associated
with body weight, fat mass, inflammation, glucose and
lipid metabolism. Strikingly, dietary restriction in over-
weight or obese patients was less efficient in LGC than in
HGC individuals in terms of body weight loss, improve-
ment of insulin sensitivity and decrease of inflammation
[92]. These results suggest that a decreased bacterial
diversity may be a feature of the ‘‘obese microbiota’’ as it
has been described for other disease states [93]. In con-
clusion, it appears that obesity is associated with a gut
microbiota differing from a lean microbiota in terms of
composition, diversity, metabolic activity, and gene con-
tents. However, the association studies described in this
paragraph do not inform whether this dysbiosis is a cause
or a consequence of obesity.
Causative role in obesity: evidences from gut
microbiota transplant experiments
If the gut microbiota plays a causal role in obesity devel-
opment, transplanting different gut microbiota to GF mice
should lead to different weight gain and adiposity. Con-
sistently, Turnbaugh et al. first transplanted cecal
microbiota from lean and ob/ob mice to GF wild-type
recipient. They found that after only 2 weeks, mice har-
boring the microbiota from obese mice gained more fat
compared to the mice inoculated with the gut microbiota
from lean donors [88], supporting a causal role of these
bacteria in the pathogenesis of obesity. They further raised
an important question. Are the differences in the compo-
sition of the gut microbiota a consequence of host genotype
or the hyperphagic state, as it is well known that ob/ob
mice consume more food than their wild-type littermates.
To further investigate this question, the same team devel-
oped a model of Western diet-induced obesity (DIO) to
study the interrelationship between gut microbiota, diet and
energy balance [94]. They showed that DIO produced a
bloom in a single uncultured clade within the Firmicutes,
named Erysipelotrichi. Moreover, this group of bacteria
was reduced following dietary manipulations that limit
weight. Similar to transplantation of the ob/ob microbiota,
transplantation of a DIO gut microbiota to GF recipients
promoted greater fat gain than transplants from lean
donors. Metagenomic sequencing also revealed that the
Western diet microbiome is enriched in pathways involved
in import and fermentation of simple sugars and host gly-
cans [94]. To determine whether human gut microbiota
may also be able to cause obesity in mice, transplantations
of adult human fecal microbiota to GF mice have been
performed. In a first study, these humanized gnotobiotic
mice were then fed a low fat or a high-fat diet. Finally, GF
recipients were colonized with cecal microbiota from
humanized donors fed either diet, and were kept on the low
fat diet. Mice colonized with the microbiota from HFD-fed
donors gained significantly more adiposity than mice col-
onized with the microbiota from low fat diet-fed donors
[95]. More recently, the same group inoculated the GF
mice with gut microbes from four pairs of female twins,
each in which one person was obese and the other had a
healthy weight. Mice that received the obese humans’
microbes gained more body fat, put on more weight, and
showed increased level of markers of metabolic disorders
[96]. Because mice are coprophagic, cohousing is widely
used to investigate the impact of sharing microbial com-
munities on the host phenotype. Strikingly, cohousing mice
152 P. Ge
associated with the human obese or lean microbiota pre-
vents increased adiposity, and it was further demonstrated
that bacteria from the lean mice were able to invade the
obese microbiota, the best colonizers among the lean
communities belonging to the Bacteroidetes phylum [96].
Whether these species were responsible for the lean-like
state remains to be proven but it indicates that bacterial
species within the human gut microbiota may have the
capacity to protect from obesity.
Interestingly, these fecal transplant experiments have
also demonstrated that the gut microbiota may play a
causal role in the development of the metabolic disorders
associated with obesity. Toll-like receptor 5 (TLR5) is
predominantly expressed basolaterally by intestinal
epithelial cells and serves to detect motile bacteria that
breach the epithelial monolayer and limit their dissemina-
tion. It was first described that TLR5
mice present
increased adiposity, elevated serum triglycerides and
cholesterol levels, as well as mild loss of glucose tolerance,
insulin resistance, hyperlipidemia and hypertension.
Remarkably, the transfer of TLR5
cecal contents into
wild-type GF mice recapitulated most aspects of the
metabolic syndrome phenotype [97]. Similarly, another
study demonstrated that gut microbiota determines devel-
opment of Non-alcoholic fatty liver disease in mice [37].
First, conventional mice were fed an HFD for 16 weeks
and two of them were selected based on their opposite
response to HFD. Although both mice were the same
weight, one displayed low fasting glycemia and weak
steatosis (Non-Responder). The other one displayed insulin
resistance and marked steatosis (Responder). Two groups
of GF mice were transplanted with the gut microbiota of
the two selected mice. After being fed an HFD, only the
mice associated with the Responder microbiota developed
fasting hyper-glycemia and hyper-insulinemia as well as
hepatic macrovesicular steatosis [37]. These experiments
demonstrating a causal role of the gut microbiota in obesity
and associated metabolic disorders raise the question
whether gut microbiota transfer in humans could be a new
way to treat obesity and metabolic syndrome as recently
shown in rats [98]. This question will be developed in the
section dedicated to the ‘Therapeutic potential of the gut
microbiota’’ .
Gut microbiota, intestinal permeability
and inflammation: the LPS hypothesis (and beyond)
Obesity is associated with a low-grade inflammation, which
has been implicated in the development of the metabolic
syndrome and insulin resistance [99]. The origin of this
inflammation is unclear and Cani et al. have proposed that
the lipopolysaccharide (LPS, a membrane component of
Gram-negative bacteria) is the triggering factor of the early
development of inflammation and metabolic diseases [100].
This hypothesis is based on the following points: (1) LPS
triggers the secretion of proinflammatory cytokines when it
binds to the complex of CD14 and TLR4 at the surface of
immune cells [101], (2) LPS is continuously produced
within the gut through lysis of Gram-negative bacteria and is
physiologically carried into intestinal capillaries though a
TLR4-dependent mechanism [102], (3) LPS is transported
from the intestine by a mechanism facilitated by chylomi-
crons freshly synthesized from epithelial intestinal cells in
response to fat feeding [103]. Cani et al. first demonstrated
that mice fed an HFD for 2–4 weeks exhibited a significant
increase in plasma LPS that they named metabolic endo-
toxemia [100]. Interestingly, it has been also reported that
patients with type 2 diabetes and patients with non-alcoholic
fatty liver disease had higher LPS levels than control
humans [104,105]. It should be noted that these levels of
LPS are 10–50 times lower than values seen in septicemia or
other infections. Cani et al. also showed that continuous
subcutaneous low-rate infusion of LPS mimicked the HFD
phenotype including excessive weight gain, hyperglycemia,
steatosis, adipose tissue macrophages infiltration and insulin
resistance in mice. Finally, to demonstrate the causal link
between LPS and the development of metabolic diseases,
they challenged LPS receptor (CD14) knock out mice with
an HFD or LPS infusion [100]. CD-14 deficient mice were
protected from metabolic disease induced by both high-fat
feeding and LPS infusion. These results were corroborated
by studies showing that TLR4-deficient mice are resistant to
the development of DIO [106,107]. They also suggest that
GF mice could be protected from DIO through the lack of
LPS in their gut. To further assess the contribution of the gut
microbiota in the development of these metabolic disorders,
they used intestinal-focused antibiotic treatment in high-fat
fed or genetically obese ob/ob mice. Drastic changes in the
gut microbiota through antibiotic treatment completely
blunted the metabolic endotoxemia, and the related meta-
bolic disorders (e.g., macrophages infiltration, glucose
intolerance and insulin resistance) [63,108]. They also
showed that high-fat feeding increased gut permeability and
changed gut microbiota composition with a reduction of
Bacteroides,Clostridium coccoides group and bifidobacteria
[108]. Interestingly, bifidobacteria have been shown to
reduce intestinal LPS levels and to improve gut barrier
function in mice [109,110]. To determine if the metabolic
disorders observed during high-fat feeding can be attributed
to the decrease of bifidobacteria, they used prebiotic dietary
fibers to specifically increase the gut bifidobacteria in high-
fat fed mice. They confirmed that mice fed an HFD exhibit a
higher endotoxemia, a phenomenon completely abolished
through dietary supplementation with the prebiotic fibers
[111]. Moreover, in prebiotic-treated mice, bifidobacteria
positively correlated with improved glucose tolerance and
Gut microbiota and obesity 153
negatively correlated with metabolic endotoxemia and body
weight gain [111]. More recently, they deciphered one of the
mechanisms explaining how these specific changes in the
gut microbiota improved metabolic endotoxemia. They
found that the modulation of gut microbiota controls and
increases endogenous production of the intestinotrophic
peptides GLP-2, and consequently improves tight junction
integrity and gut barrier functions by a GLP-2-dependent
mechanism [112]. They also identified the endocannabinoid
(eCB) system as determinant of gut barrier function. More
specifically, they proposed that the eCB system mediates
communication between adipose tissue and the gut micro-
biota. Accordingly, modulating the gut microbiota of obese
and diabetic mice profoundly affected the tone of the
intestinal and adipose tissue eCB system and improved
adipose tissue metabolism [113,114]. Finally, they further
showed that MyD88 (myeloid differentiation primary
response gene 88), a central adaptor molecule of most of the
TLRs, acts as a sensor involved in the interaction between
nutrients, gut microbes and the host during DIO [115].
Indeed, they first revealed that inducible intestinal epithelial
cell-specific deletion of MyD88 partially protects against
DIO, diabetes and inflammation. Remarkably, the gut
microbiota of these MyD88-deleted mice protected GF
recipients after fecal transplant. Finally, it appears that the
gut barrier function may be important in the crosstalk
between gut bacteria and host metabolism, and lps are
probably only one of the players linking the gut microbiota,
the gut permeability and metabolic disorders. Accordingly, it
was also shown that HFD leads to increased bacterial DNA
in ileal mucosa, blood and mesenteric adipose tissue in mice
[116]. Then, a 9-year longitudinal study revealed that blood
bacterial DNA at baseline was higher among participants
who presented with abdominal adiposity and developed
diabetes during the 9-year period than among those who did
not [117] suggesting that translocation of entire bacteria and
the existence of a tissue microbiota could be another con-
tributor to metabolic syndrome [118].
Influence of the gut microbiota on plasma lipids
Dyslipidemia is commonly associated with obesity and
metabolic syndrome and besides its influence on weight
gain and metabolic disorders, it has been shown for a long
time that the gut microbiota impacts the lipid metabolism
of the host. As an example, pioneer studies by Wostmann
et al. in the 1960s demonstrated that GF animals absorb
dietary cholesterol more efficiently than conventional
controls, but display reduced plasma cholesterol [119,
120]. Nevertheless, this topic was not studied thoroughly
until recently when comparison of GF and conventional
mice fed an HFD showed that GF mice display increased
fecal lipid excretion and reduced plasma free fatty acid and
liver triglyceride levels [42]. Interestingly, this study also
revealed that GF mice have reduced cholesterolemia, an
increase in fecal cholesterol excretion, and a moderate
accretion of hepatic cholesterol confirmed by an up-regu-
lation of cholesterol biosynthesis genes in the liver,
suggesting that the gut microbiota alters cholesterol
metabolism in the host [42]. This influence of the gut
microbiota on cholesterol metabolism was further con-
firmed using MS-based lipidomics of serum, white adipose
tissue, and liver of GF and conventional mice [121]. This
impaired cholesterol metabolism could be related to the
lack of cholesterol conversion by the intestinal bacteria.
Indeed, even if only a few cholesterol-reducing bacteria
have been isolated from human or animal gut [122,123],
the conversion of cholesterol to the saturated product
coprostanol by intestinal microorganisms was established
during the 1930s. Coprostanol is poorly absorbed by the
human intestine and an inverse relationship has been
observed between serum cholesterol levels and the
coprostanol-to-cholesterol ratio in human feces [124].
Hence, conversion of cholesterol to coprostanol by the gut
may lead to decreased cholesterol absorption and then
cholesterolemia [125]. Besides cholesterol, comparison of
GF and conventional mice also showed that the gut
microbiota modified a number of lipid species in the serum,
adipose tissue, and liver, with its greatest effect on
triglyceride and phosphatidylcholine species [121]. The
latter is of importance regarding the role of the gut
microbiota in cardiovascular diseases. Indeed, dietary
choline and phosphatidylcholine are converted to
trimethylamine (TMA) by gut microbes. Then, the absor-
bed TMA is metabolized to trimethylamine-N-oxide, a
proatherosclerotic metabolite, by hepatic flavin monooxy-
genases [126,127]. Gut microbiota could also regulate
serum lipids by taking part in bile acid metabolism. Bile
salts are highly effective detergents that promote solubi-
lization and absorption of dietary lipids throughout the
intestine. The bile acids that escape the enterohepatic cir-
culation undergo bacterial metabolism in the colon leading
to over twenty different secondary bile acids in human
feces [128]. Also, deconjugation of bile acids through the
enzyme bile salt hydrolase (BSH) may alter plasma
cholesterol levels. Briefly, glycine or taurine is liberated
from the steroid moiety of the molecule, resulting in the
formation of free bile acids which are less efficiently
reabsorbed than their conjugated counterparts. Hence,
deconjugated bile acids are more readily excreted within
the feces than conjugated bile acids. Cholesterol, being a
precursor of bile acids, is broken down to replace the
processed bile salts leading to a reduction in serum
cholesterol [129].
154 P. Ge
Therapeutic potential of the gut microbiota
Probiotics and prebiotics
Probiotics are defined by the Food and Agricultural
Organization and the World Health Organization as ‘‘live
microorganisms which when administered in adequate
amounts, confer a beneficial health effect on the host’’.
Whereas probiotics are used for decades in agriculture for
their growth-promoting effects, several studies have
demonstrated that probiotics may ameliorate obesity and
associated metabolic disorders both in animal models and
in humans. In particular, probiotics containing Bifidobac-
terium were shown to exert beneficial effects in HFD fed
mice and rats [81,130135], mainly through increased gut
barrier function, leading to reduced bacterial translocation
and endotoxemia, and improvement of inflammation,
insulin sensitivity, fat accumulation as well as cholesterol
and triglyceride serum levels. Similarly, probiotics con-
taining Lactobacillus strains have been shown to be
effective in reducing body fat mass and improving lipid
profiles and glucose homeostasis in animal models of
obesity [136147]. Proposed mechanisms include conju-
gated linoleic acid production, BSH activity, stimulation of
fatty acids oxidation, or inhibition of lipoprotein lipase
activity. Well-controlled studies in humans are scarce but
recent studies suggested that Lactobacillus gasseri may
decrease body weight and abdominal adiposity and
improve postprandial serum lipid responses in overweight
human subjects [148150]. Finally, a meta-analysis based
on 17 randomized clinical trials in humans, 51 studies on
farm animals and 14 experimental models highlighted the
strain-dependent effect of Lactobacillus containing probi-
otics on weight management. Therefore, Lactobacillus
acidophilus administration resulted in a significant weight
gain in humans and in animals. Lactobacillus fermentum
and Lactobacillus ingluviei were associated with weight
gain in animals. Conversely, Lactobacillus plantarum was
associated with weight loss in animals and Lactobacillus
gasseri was associated with weight loss both in obese
humans and in animals [79]. In conclusion, although
encouraging results emerge from rodents experiments, the
efficacy of probiotics remains highly debatable and their
therapeutic used for obesity management has not yet been
recommended [151].
Prebiotics are defined as non-digestible polysaccharides
that promote ‘‘the selective stimulation of growth and/or
activity(ies) of one or a limited number of microbial gen-
us(era)/species in the gut microbiota that confer(s) health
benefit to the host’’ [152]. The most studied prebiotics are
the inulin and various types of fructo-oligosaccharides and
galactooligosaccharides and numerous studies in animal
models showed that they modify gut microbial composi-
tion, enhancing the growth of beneficial Bifidobacteria and
Lactobacillus [111,153155]. However, more recent
studies revealed that prebiotics affect many more bacterial
taxa than previously thought [156,157]. Interestingly, this
microbiota modulation is commonly associated with a
reduction in body weight, body fat and adipocyte size.
These effects are mediated through decreased food intake
and appetite, as well as reduced fatty acid storage [154,
155,158160]. Furthermore, the improvement of gut bar-
rier integrity [112,154] leads to better glucose tolerance
and insulin sensitivity. In humans, beneficial effects of
prebiotics on glycemia and insulinemia have been largely
confirmed whereas impacts on body weight, fat mass and
satiety have not been consistently observed and are still
matter of debate [161165].
Fecal microbiota transplant
Fecal microbiota transplant (FMT) refers to infusion of a
fecal suspension from a healthy individual into the GI tract
of another person to cure a specific disease. Transplantation
of stool for the treatment of GI disease was first reported in
the fourth century in China by Ge Hong, who described the
use of human fecal suspension by mouth for patients who
had food poisoning or severe diarrhea [166]. Sixteen cen-
turies later, its first clinical use was for the treatment of
pseudomembranous colitis and was reported in 1958 in a
four-patient case series [167]. In the recent years, FMT has
gained an increasing interest as an effective treatment
strategy for severe recurrent Clostridium difficile infection
with global success rate over 80 % [168]. Moreover, early
experience suggests that FMT could be used for other GI
and non-GI diseases associated with microbial dysbiosis
and whose aetiologies are uncertain, including IBD, irri-
table bowel syndrome or metabolic diseases. Indeed, as
metabolic phenotypes can be transmitted to GF mice via
gut microbiota transplant, it can be postulated that FMT
may be effective to improve lipid and glucose homeostasis.
In a first pilot study, intestinal microbiota was transferred
from lean human donors to recipients with metabolic
syndrome via a postpyloric enteral feeding tube. Patients
who received microbiota from lean donors had an increase
in peripheral insulin sensitivity 6 weeks after FMT in
comparison with peripheral insulin sensitivity prior to
FMT, although the body weights and adiposity were not
modified. This was associated with increased gut bacterial
diversity, as well as increase in the amount of the butyrate
producer Eubacterium hallii [169]. Therefore, if the legal
framework and the standardization of the FMT are needed
and if more well-designed randomized controlled trials in
the context of metabolic diseases should be performed, this
Gut microbiota and obesity 155
study suggests that FMT might be a new way to improve
obesity and associated metabolic disorders in the future.
Conclusions and future challenges
Gut microbiota is now viewed as a novel factor involved in
body weight management. The gut microbiota may,
therefore, participate to energy metabolism through energy
harvest from the diet, regulation of fat storage, regulation
of lipogenesis, or regulation of fatty acid oxidation. Fur-
ther, differences in the composition of gut microbiota in
obese humans and mice suggest that different microbes or
community may influence body weight differently.
Although the cause–effect relationships of the gut micro-
biota with obesity remain unclear, the rapid developments
in high-throughput techniques may make it possible to
unravel the real impact of the gut microbiota on host’s
metabolism. Multidisciplinary research in this field will be
helpful to provide evidence-based data and to shed light on
the roles of specific sets of microbes. The next step will be
the discovery of pharmacological, dietary or fecal trans-
plant interventions to modify the gut microbiota in such a
way that prevents or treats metabolic disorders and/or
1. Ng M, Fleming T, Robinson M, Thomson B, Graetz N, Margono
C, Mullany EC, Biryukov S, Abbafati C, Abera SF, Abraham JP,
Abu-Rmeileh NM, Achoki T, AlBuhairan FS, Alemu ZA,
Alfonso R, Ali MK, Ali R, Guzman NA, Ammar W, Anwari P,
Banerjee A, Barquera S, Basu S, Bennett DA, Bhutta Z, Blore J,
Cabral N, Nonato IC, Chang JC, Chowdhury R, Courville KJ,
Criqui MH, Cundiff DK, Dabhadkar KC, Dandona L, Davis A,
Dayama A, Dharmaratne SD, Ding EL, Durrani AM, Estegha-
mati A, Farzadfar F, Fay DF, Feigin VL, Flaxman A,
Forouzanfar MH, Goto A, Green MA, Gupta R, Hafezi-Nejad N,
Hankey GJ, Harewood HC, Havmoeller R, Hay S, Hernandez L,
Husseini A, Idrisov BT, Ikeda N, Islami F, Jahangir E, Jassal
SK, Jee SH, Jeffreys M, Jonas JB, Kabagambe EK, Khalifa SE,
Kengne AP, Khader YS, Khang YH, Kim D, Kimokoti RW,
Kinge JM, Kokubo Y, Kosen S, Kwan G, Lai T, Leinsalu M, Li
Y, Liang X, Liu S, Logroscino G, Lotufo PA, Lu Y, Ma J,
Mainoo NK, Mensah GA, Merriman TR, Mokdad AH,
Moschandreas J, Naghavi M, Naheed A, Nand D, Narayan KM,
Nelson EL, Neuhouser ML, Nisar MI, Ohkubo T, Oti SO,
Pedroza A, Prabhakaran D, Roy N, Sampson U, Seo H,
Sepanlou SG, Shibuya K, Shiri R, Shiue I, Singh GM, Singh JA,
Skirbekk V, Stapelberg NJ, Sturua L, Sykes BL, Tobias M, Tran
BX, Trasande L, Toyoshima H, van de Vijver S, Vasankari TJ,
Veerman JL, Velasquez-Melendez G, Vlassov VV, Vollset SE,
Vos T, Wang C, Wang X, Weiderpass E, Werdecker A, Wright
JL, Yang YC, Yatsuya H, Yoon J, Yoon SJ, Zhao Y, Zhou M,
Zhu S, Lopez AD, Murray CJ, Gakidou E (2014) Global,
regional, and national prevalence of overweight and obesity in
children and adults during 1980–2013: a systematic analysis for
the Global Burden of Disease Study 2013. Lancet
384(9945):766–781. doi:10.1016/S0140-6736(14)60460-8
2. Swinburn BA, Sacks G, Hall KD, McPherson K, Finegood DT,
Moodie ML, Gortmaker SL (2011) The global obesity pan-
demic: shaped by global drivers and local environments. Lancet
378(9793):804–814. doi:10.1016/S0140-6736(11)60813-1
3. Hill JO (2006) Understanding and addressing the epidemic of
obesity: an energy balance perspective. Endocr Rev
4. Clavel T, Desmarchelier C, Haller D, Gerard P, Rohn S, Lepage
P, Daniel H (2014) Intestinal microbiota in metabolic diseases:
from bacterial community structure and functions to species of
pathophysiological relevance. Gut Microbes 5(4):544–551.
5. Rosenbaum M, Knight R, Leibel RL (2015) The gut microbiota
in human energy homeostasis and obesity. Trends Endocrinol
Metab 26(9):493–501. doi:10.1016/j.tem.2015.07.002
6. Aagaard K, Ma J, Antony KM, Ganu R, Petrosino J, Versalovic
J (2014) The placenta harbors a unique microbiome. Sci Transl
Med 6(237):237ra265. doi:10.1126/scitranslmed.3008599
7. Palmer C, Bik EM, DiGiulio DB, Relman DA, Brown PO
(2007) Development of the human infant intestinal microbiota.
PLoS Biol 5(7):e177
8. Koenig JE, Spor A, Scalfone N, Fricker AD, Stombaugh J,
Knight R, Angenent LT, Ley RE (2011) Succession of microbial
consortia in the developing infant gut microbiome. Proc Natl
Acad Sci USA 108(Suppl 1):4578–4585. doi:10.1073/pnas.
9. Faith JJ, Guruge JL, Charbonneau M, Subramanian S, Seedorf
H, Goodman AL, Clemente JC, Knight R, Heath AC, Leibel RL,
Rosenbaum M, Gordon JI (2013) The long-term stability of the
human gut microbiota. Science 341(6141):1237439. doi:10.
10. Dethlefsen L, Huse S, Sogin ML, Relman DA (2008) The per-
vasive effects of an antibiotic on the human gut microbiota, as
revealed by deep 16S rRNA sequencing. PLoS Biol 6(11):e280.
11. Dethlefsen L, Relman DA (2011) Incomplete recovery and
individualized responses of the human distal gut microbiota to
repeated antibiotic perturbation. Proc Natl Acad Sci USA
108(Suppl 1):4554–4561. doi:10.1073/pnas.1000087107
12. Zhang C, Zhang M, Wang S, Han R, Cao Y, Hua W, Mao Y,
Zhang X, Pang X, Wei C, Zhao G, Chen Y, Zhao L (2010)
Interactions between gut microbiota, host genetics and diet
relevant to development of metabolic syndromes in mice. ISME
J 4(2):232–241. doi:10.1038/ismej.2009.112
13. Turnbaugh PJ, Hamady M, Yatsunenko T, Cantarel BL, Duncan
A, Ley RE, Sogin ML, Jones WJ, Roe BA, Affourtit JP, Egholm
M, Henrissat B, Heath AC, Knight R, Gordon JI (2009) A core
gut microbiome in obese and lean twins. Nature
14. Lozupone CA, Stombaugh JI, Gordon JI, Jansson JK, Knight R
(2012) Diversity, stability and resilience of the human gut
microbiota. Nature 489(7415):220–230. doi:10.1038/
15. Franzosa EA, Huang K, Meadow JF, Gevers D, Lemon KP,
Bohannan BJ, Huttenhower C (2015) Identifying personal
microbiomes using metagenomic codes. Proc Natl Acad Sci
USA 112(22):E2930–2938. doi:10.1073/pnas.1423854112
16. Ley RE, Hamady M, Lozupone C, Turnbaugh PJ, Ramey RR,
Bircher JS, Schlegel ML, Tucker TA, Schrenzel MD, Knight R,
Gordon JI (2008) Evolution of mammals and their gut microbes.
Science 320(5883):1647–1651
17. O’Hara AM, Shanahan F (2006) The gut flora as a forgotten
organ. EMBO Rep 7(7):688–693. doi:10.1038/sj.embor.
156 P. Ge
18. Olsen GJ, Lane DJ, Giovannoni SJ, Pace NR, Stahl DA (1986)
Microbial ecology and evolution: a ribosomal RNA approach.
Annu Rev Microbiol 40:337–365
19. Ge
´rard P (2011) Le microbiote intestinal: composition et fonc-
tions. Phytothe
´rapie 9(2):72–75
20. Eckburg PB, Bik EM, Bernstein CN, Purdom E, Dethlefsen L,
Sargent M, Gill SR, Nelson KE, Relman DA (2005) Diversity of
the human intestinal microbial flora. Science
21. Frank DN, St Amand AL, Feldman RA, Boedeker EC, Harpaz
N, Pace NR (2007) Molecular-phylogenetic characterization of
microbial community imbalances in human inflammatory bowel
diseases. Proc Natl Acad Sci USA 104(34):13780–13785
22. Hsiao WW, Fraser-Liggett CM (2009) Human Microbiome
Project–paving the way to a better understanding of ourselves
and our microbes. Drug Discov Today 14(7–8):331–333
23. Turnbaugh PJ, Ley RE, Hamady M, Fraser-Liggett CM, Knight
R, Gordon JI (2007) The human microbiome project. Nature
24. Frank DN, Pace NR (2008) Gastrointestinal microbiology enters
the metagenomics era. Curr Opin Gastroenterol 24(1):4–10
25. Gill SR, Pop M, Deboy RT, Eckburg PB, Turnbaugh PJ, Samuel
BS, Gordon JI, Relman DA, Fraser-Liggett CM, Nelson KE
(2006) Metagenomic analysis of the human distal gut micro-
biome. Science 312(5778):1355–1359
26. Li J, Jia H, Cai X, Zhong H, Feng Q, Sunagawa S, Arumugam
M, Kultima JR, Prifti E, Nielsen T, Juncker AS, Manichanh C,
Chen B, Zhang W, Levenez F, Wang J, Xu X, Xiao L, Liang S,
Zhang D, Zhang Z, Chen W, Zhao H, Al-Aama JY, Edris S,
Yang H, Wang J, Hansen T, Nielsen HB, Brunak S, Kristiansen
K, Guarner F, Pedersen O, Dore J, Ehrlich SD, Meta HITC,
Bork P, Wang J, Meta HITC (2014) An integrated catalog of
reference genes in the human gut microbiome. Nat Biotechnol
32(8):834–841. doi:10.1038/nbt.2942
27. Dethlefsen L, McFall-Ngai M, Relman DA (2007) An ecologi-
cal and evolutionary perspective on human-microbe mutualism
and disease. Nature 449(7164):811–818
28. Qin J, Li R, Raes J, Arumugam M, Burgdorf KS, Manichanh C,
Nielsen T, Pons N, Levenez F, Yamada T, Mende DR, Li J, Xu
J, Li S, Li D, Cao J, Wang B, Liang H, Zheng H, Xie Y, Tap J,
Lepage P, Bertalan M, Batto JM, Hansen T, Le Paslier D,
Linneberg A, Nielsen HB, Pelletier E, Renault P, Sicheritz-
Ponten T, Turner K, Zhu H, Yu C, Li S, Jian M, Zhou Y, Li Y,
Zhang X, Li S, Qin N, Yang H, Wang J, Brunak S, Dore J,
Guarner F, Kristiansen K, Pedersen O, Parkhill J, Weissenbach
J, Bork P, Ehrlich SD, Wang J (2010) A human gut microbial
gene catalogue established by metagenomic sequencing. Nature
29. Arumugam M, Raes J, Pelletier E, Le Paslier D, Yamada T,
Mende DR, Fernandes GR, Tap J, Bruls T, Batto JM, Bertalan
M, Borruel N, Casellas F, Fernandez L, Gautier L, Hansen T,
Hattori M, Hayashi T, Kleerebezem M, Kurokawa K, Leclerc
M, Levenez F, Manichanh C, Nielsen HB, Nielsen T, Pons N,
Poulain J, Qin J, Sicheritz-Ponten T, Tims S, Torrents D, Ugarte
E, Zoetendal EG, Wang J, Guarner F, Pedersen O, de Vos WM,
Brunak S, Dore J, Antolin M, Artiguenave F, Blottiere HM,
Almeida M, Brechot C, Cara C, Chervaux C, Cultrone A,
Delorme C, Denariaz G, Dervyn R, Foerstner KU, Friss C, van
de Guchte M, Guedon E, Haimet F, Huber W, van Hylckama-
Vlieg J, Jamet A, Juste C, Kaci G, Knol J, Lakhdari O, Layec S,
Le Roux K, Maguin E, Merieux A, Melo Minardi R, M’Rini C,
Muller J, Oozeer R, Parkhill J, Renault P, Rescigno M, Sanchez
N, Sunagawa S, Torrejon A, Turner K, Vandemeulebrouck G,
Varela E, Winogradsky Y, Zeller G, Weissenbach J, Ehrlich SD,
Bork P (2011) Enterotypes of the human gut microbiome.
Nature 473(7346):174–180. doi:10.1038/nature09944
30. Wu GD, Chen J, Hoffmann C, Bittinger K, Chen YY, Keilbaugh
SA, Bewtra M, Knights D, Walters WA, Knight R, Sinha R,
Gilroy E, Gupta K, Baldassano R, Nessel L, Li H, Bushman FD,
Lewis JD (2011) Linking long-term dietary patterns with gut
microbial enterotypes. Science 334(6052):105–108. doi:10.
31. Knights D, Ward TL, McKinlay CE, Miller H, Gonzalez A,
McDonald D, Knight R (2014) Rethinking ‘‘enterotypes’’. Cell
Host Microbe 16(4):433–437. doi:10.1016/j.chom.2014.09.013
32. Backhed F, Ley RE, Sonnenburg JL, Peterson DA, Gordon JI
(2005) Host-bacterial mutualism in the human intestine. Science
33. Hooper LV, Midtvedt T, Gordon JI (2002) How host-microbial
interactions shape the nutrient environment of the mammalian
intestine. Annu Rev Nutr 22:283–307
34. Ge
´rard P, Bernalier-Donadille A (2007) Les fonctions majeures
du microbiote intestinal. Cahiers de Nutrition et de Die
35. Backhed F, Fraser CM, Ringel Y, Sanders ME, Sartor RB,
Sherman PM, Versalovic J, Young V, Finlay BB (2012)
Defining a healthy human gut microbiome: current concepts,
future directions, and clinical applications. Cell Host Microbe
12(5):611–622. doi:10.1016/j.chom.2012.10.012
36. Duca F, Gerard P, Covasa M, Lepage P (2014) Metabolic
interplay between gut bacteria and their host. Front Horm Res
42:73–82. doi:10.1159/000358315
37. Le Roy T, Llopis M, Lepage P, Bruneau A, Rabot S, Bevilacqua
C, Martin P, Philippe C, Walker F, Bado A, Perlemuter G,
Cassard-Doulcier A, Ge
´rard P (2013) Intestinal microbiota
determines development of nonalcoholic fatty liver disease in
mice. Gut 62(12):1787–1794
38. Mayer EA, Tillisch K, Gupta A (2015) Gut/brain axis and the
microbiota. J Clin Invest 125(3):926–938. doi:10.1172/
39. Wostmann BS, Larkin C, Moriarty A, Bruckner-Kardoss E
(1983) Dietary intake, energy metabolism, and excretory losses
of adult male germfree Wistar rats. Lab Anim Sci 33(1):46–50
40. Backhed F, Ding H, Wang T, Hooper LV, Koh GY, Nagy A,
Semenkovich CF, Gordon JI (2004) The gut microbiota as an
environmental factor that regulates fat storage. Proc Natl Acad
Sci USA 101(44):15718–15723
41. Backhed F, Manchester JK, Semenkovich CF, Gordon JI (2007)
Mechanisms underlying the resistance to diet-induced obesity in
germ-free mice. Proc Natl Acad Sci USA 104(3):979–984
42. Rabot S, Membrez M, Bruneau A, Ge
´rard P, Harach T, Moser
M, Raymond F, Mansourian R, Chou CJ (2010) Germ-free
C57BL/6J mice are resistant to high-fat-diet-induced insulin
resistance and have altered cholesterol metabolism. FASEB J
43. Fleissner CK, Huebel N, Abd El-Bary MM, Loh G, Klaus S,
Blaut M (2010) Absence of intestinal microbiota does not pro-
tect mice from diet-induced obesity. Br J Nutr 104(6):919–929.
44. Swartz TD, Sakar Y, Duca FA, Covasa M (2013) Preserved
adiposity in the Fischer 344 rat devoid of gut microbiota.
FASEB J 27(4):1701–1710. doi:10.1096/fj.12-221689
45. Flint HJ, Bayer EA, Rincon MT, Lamed R, White BA (2008)
Polysaccharide utilization by gut bacteria: potential for new
insights from genomic analysis. Nat Rev Microbiol 6(2):121–131
46. Stappenbeck TS, Hooper LV, Gordon JI (2002) Developmental
regulation of intestinal angiogenesis by indigenous microbes via
Paneth cells. Proc Natl Acad Sci USA 99(24):15451–15455
47. Conterno L, Fava F, Viola R, Tuohy KM (2011) Obesity and the
gut microbiota: does up-regulating colonic fermentation protect
against obesity and metabolic disease? Genes Nutr
6(3):241–260. doi:10.1007/s12263-011-0230-1
Gut microbiota and obesity 157
48. Brown AJ, Goldsworthy SM, Barnes AA, Eilert MM, Tcheang
L, Daniels D, Muir AI, Wigglesworth MJ, Kinghorn I, Fraser
NJ, Pike NB, Strum JC, Steplewski KM, Murdock PR, Holder
JC, Marshall FH, Szekeres PG, Wilson S, Ignar DM, Foord SM,
Wise A, Dowell SJ (2003) The Orphan G protein-coupled
receptors GPR41 and GPR43 are activated by propionate and
other short chain carboxylic acids. J Biol Chem
278(13):11312–11319. doi:10.1074/jbc.M211609200
49. Bjursell M, Admyre T, Goransson M, Marley AE, Smith DM,
Oscarsson J, Bohlooly YM (2011) Improved glucose control and
reduced body fat mass in free fatty acid receptor 2-deficient
mice fed a high-fat diet. Am J Physiol Endocrinol Metab
300(1):E211–220. doi:10.1152/ajpendo.00229.2010
50. Samuel BS, Shaito A, Motoike T, Rey FE, Backhed F,
Manchester JK, Hammer RE, Williams SC, Crowley J, Yanag-
isawa M, Gordon JI (2008) Effects of the gut microbiota on host
adiposity are modulated by the short-chain fatty-acid binding G
protein-coupled receptor, Gpr41. Proc Natl Acad Sci USA
51. Cani PD, Dewever C, Delzenne NM (2004) Inulin-type fructans
modulate gastrointestinal peptides involved in appetite regula-
tion (glucagon-like peptide-1 and ghrelin) in rats. Br J Nutr
52. Cani PD, Lecourt E, Dewulf EM, Sohet FM, Pachikian BD,
Naslain D, De Backer F, Neyrinck AM, Delzenne NM (2009)
Gut microbiota fermentation of prebiotics increases satietogenic
and incretin gut peptide production with consequences for
appetite sensation and glucose response after a meal. Am J Clin
Nutr 90(5):1236–1243. doi:10.3945/ajcn.2009.28095
53. Tarini J, Wolever TM (2010) The fermentable fibre inulin
increases postprandial serum short-chain fatty acids and reduces
free-fatty acids and ghrelin in healthy subjects. Appl Physiol
Nutr Metab 35(1):9–16. doi:10.1139/H09-119
54. Delzenne NM, Neyrinck AM, Cani PD (2011) Modulation of the
gut microbiota by nutrients with prebiotic properties: conse-
quences for host health in the context of obesity and metabolic
syndrome. Microb Cell Fact 10(Suppl 1):S10. doi:10.1186/
55. Soliman MM, Ahmed MM, Salah-Eldin AE, Abdel-Aal AA
(2011) Butyrate regulates leptin expression through different
signaling pathways in adipocytes. J Vet Sci 12(4):319–323
56. Lin HV, Frassetto A, Kowalik EJ Jr, Nawrocki AR, Lu MM,
Kosinski JR, Hubert JA, Szeto D, Yao X, Forrest G, Marsh DJ
(2012) Butyrate and propionate protect against diet-induced
obesity and regulate gut hormones via free fatty acid receptor
3-independent mechanisms. PLoS One 7(4):e35240. doi:10.
57. Moore PR, Evenson A et al (1946) Use of sulfasuxidine,
streptothricin, and streptomycin in nutritional studies with the
chick. J Biol Chem 165(2):437–441
58. Coates ME, Fuller R, Harrison GF, Lev M, Suffolk SF (1963) A
comparison of the growth of chicks in the Gustafsson germ-free
apparatus and in a conventional environment, with and without
dietary supplements of penicillin. Br J Nutr 17:141–150
59. Gaskins HR, Collier CT, Anderson DB (2002) Antibiotics as
growth promotants: mode of action. Anim Biotechnol
13(1):29–42. doi:10.1081/ABIO-120005768
60. Cho I, Yamanishi S, Cox L, Methe BA, Zavadil J, Li K, Gao Z,
Mahana D, Raju K, Teitler I, Li H, Alekseyenko AV, Blaser MJ
(2012) Antibiotics in early life alter the murine colonic microbiome
and adiposity. Nature 488(7413):621–626. doi:10.1038/nature11400
61. Cox LM, Yamanishi S, Sohn J, Alekseyenko AV, Leung JM,
Cho I, Kim SG, Li H, Gao Z, Mahana D, Zarate Rodriguez JG,
Rogers AB, Robine N, Loke P, Blaser MJ (2014) Altering the
intestinal microbiota during a critical developmental window
has lasting metabolic consequences. Cell 158(4):705–721.
62. Cox LM, Blaser MJ (2015) Antibiotics in early life and obesity.
Nat Rev Endocrinol 11(3):182–190. doi:10.1038/nrendo.2014.
63. Membrez M, Blancher F, Jaquet M, Bibiloni R, Cani PD, Bur-
celin RG, Corthesy I, Mace K, Chou CJ (2008) Gut microbiota
modulation with norfloxacin and ampicillin enhances glucose
tolerance in mice. FASEB J 22(7):2416–2426
64. Haight TH, Pierce WE (1955) Effect of prolonged antibiotic
administration of the weight of healthy young males. J Nutr
65. Ozawa E (1955) Studies on growth promotion by antibiotics. II.
Results of aurofac administration to infants. J Antibiot
66. Ajslev TA, Andersen CS, Gamborg M, Sorensen TI, Jess T
(2011) Childhood overweight after establishment of the gut
microbiota: the role of delivery mode, pre-pregnancy weight and
early administration of antibiotics. Int J Obes (Lond)
35(4):522–529. doi:10.1038/ijo.2011.27
67. Bailey LC, Forrest CB, Zhang P, Richards TM, Livshits A,
DeRusso PA (2014) Association of antibiotics in infancy with
early childhood obesity. JAMA Pediatr 168(11):1063–1069.
68. Murphy R, Stewart AW, Braithwaite I, Beasley R, Hancox RJ,
Mitchell EA, Group IPTS (2014) Antibiotic treatment during
infancy and increased body mass index in boys: an international
cross-sectional study. Int J Obes (Lond) 38(8):1115–1119.
69. Trasande L, Blustein J, Liu M, Corwin E, Cox LM, Blaser MJ
(2013) Infant antibiotic exposures and early-life body mass. Int J
Obes (Lond) 37(1):16–23. doi:10.1038/ijo.2012.132
70. Ley RE, Backhed F, Turnbaugh P, Lozupone CA, Knight RD,
Gordon JI (2005) Obesity alters gut microbial ecology. Proc
Natl Acad Sci USA 102(31):11070–11075
71. Ley RE, Turnbaugh PJ, Klein S, Gordon JI (2006) Microbial
ecology: human gut microbes associated with obesity. Nature
72. Armougom F, Henry M, Vialettes B, Raccah D, Raoult D (2009)
Monitoring bacterial community of human gut microbiota
reveals an increase in Lactobacillus in obese patients and
methanogens in anorexic patients. PLoS One 4(9):e7125. doi:10.
73. Furet JP, Kong LC, Tap J, Poitou C, Basdevant A, Bouillot JL,
Mariat D, Corthier G, Dore J, Henegar C, Rizkalla S, Clement K
(2010) Differential adaptation of human gut microbiota to bar-
iatric surgery-induced weight loss: links with metabolic and
low-grade inflammation markers. Diabetes 59(12):3049–3057.
74. Santacruz A, Collado MC, Garcia-Valdes L, Segura MT, Mar-
tin-Lagos JA, Anjos T, Marti-Romero M, Lopez RM, Florido J,
Campoy C, Sanz Y (2010) Gut microbiota composition is
associated with body weight, weight gain and biochemical
parameters in pregnant women. Br J Nutr 104(1):83–92. doi:10.
75. Collado MC, Isolauri E, Laitinen K, Salminen S (2008) Distinct
composition of gut microbiota during pregnancy in overweight
and normal-weight women. Am J Clin Nutr 88(4):894–899
76. Duncan SH, Lobley GE, Holtrop G, Ince J, Johnstone AM,
Louis P, Flint HJ (2008) Human colonic microbiota associated
with diet, obesity and weight loss. Int J Obes (Lond)
77. Jumpertz R, Le DS, Turnbaugh PJ, Trinidad C, Bogardus C,
Gordon JI, Krakoff J (2011) Energy-balance studies reveal
associations between gut microbes, caloric load, and nutrient
158 P. Ge
absorption in humans. Am J Clin Nutr 94(1):58–65. doi:10.
78. Schwiertz A, Taras D, Schafer K, Beijer S, Bos NA, Donus C,
Hardt PD (2010) Microbiota and SCFA in lean and overweight
healthy subjects. Obesity (Silver Spring) 18(1):190–195
79. Million M, Angelakis E, Paul M, Armougom F, Leibovici L,
Raoult D (2012) Comparative meta-analysis of the effect of
Lactobacillus species on weight gain in humans and animals.
Microb Pathog 53(2):100–108. doi:10.1016/j.micpath.2012.05.
80. Kalliomaki M, Collado MC, Salminen S, Isolauri E (2008) Early
differences in fecal microbiota composition in children may
predict overweight. Am J Clin Nutr 87(3):534–538
81. Yin YN, Yu QF, Fu N, Liu XW, Lu FG (2010) Effects of four
Bifidobacteria on obesity in high-fat diet induced rats. World J
Gastroenterol 16(27):3394–3401
82. Kozyrskyj AL, Kalu R, Koleva PT, Bridgman SL (2015) Fetal
programming of overweight through the microbiome: boys are
disproportionately affected. J Dev Orig Health Dis. doi:10.1017/
83. Fei N, Zhao L (2013) An opportunistic pathogen isolated from
the gut of an obese human causes obesity in germfree mice.
ISME J 7(4):880–884. doi:10.1038/ismej.2012.153
84. Sokol H, Pigneur B, Watterlot L, Lakhdari O, Bermudez-Hu-
maran LG, Gratadoux JJ, Blugeon S, Bridonneau C, Furet JP,
Corthier G, Grangette C, Vasquez N, Pochart P, Trugnan G,
Thomas G, Blottiere HM, Dore J, Marteau P, Seksik P, Langella
P (2008) Faecalibacterium prausnitzii is an anti-inflammatory
commensal bacterium identified by gut microbiota analysis of
Crohn disease patients. Proc Natl Acad Sci USA
85. Cao Y, Shen J, Ran ZH (2014) Association between Faecal-
ibacterium prausnitzii reduction and inflammatory bowel
disease: a meta-analysis and systematic review of the literature.
Gastroenterol Res Pract 2014:872725. doi:10.1155/2014/872725
86. Dao MC, Everard A, Aron-Wisnewsky J, Sokolovska N, Prifti
E, Verger EO, Kayser BD, Levenez F, Chilloux J, Hoyles L,
Consortium MI-O, Dumas ME, Rizkalla SW, Dore J, Cani PD,
Clement K (2015) Akkermansia muciniphila and improved
metabolic health during a dietary intervention in obesity: rela-
tionship with gut microbiome richness and ecology. Gut. doi:10.
87. Everard A, Belzer C, Geurts L, Ouwerkerk JP, Druart C, Bindels
LB, Guiot Y, Derrien M, Muccioli GG, Delzenne NM, de Vos
WM, Cani PD (2013) Cross-talk between Akkermansia muci-
niphila and intestinal epithelium controls diet-induced obesity.
Proc Natl Acad Sci USA 110(22):9066–9071. doi:10.1073/pnas.
88. Turnbaugh PJ, Ley RE, Mahowald MA, Magrini V, Mardis ER,
Gordon JI (2006) An obesity-associated gut microbiome with
increased capacity for energy harvest. Nature
89. Greenblum S, Turnbaugh PJ, Borenstein E (2012) Metagenomic
systems biology of the human gut microbiome reveals topo-
logical shifts associated with obesity and inflammatory bowel
disease. Proc Natl Acad Sci USA 109(2):594–599. doi:10.1073/
90. Schwiertz A, Taras D, Schafer K, Beijer S, Bos NA, Donus C,
Hardt PD (2010) Microbiota and SCFA in lean and overweight
healthy subjects. Obesity (Silver Spring) 18(1):190–195. doi:10.
91. Le Chatelier E, Nielsen T, Qin J, Prifti E, Hildebrand F, Falony
G, Almeida M, Arumugam M, Batto JM, Kennedy S, Leonard P,
Li J, Burgdorf K, Grarup N, Jorgensen T, Brandslund I, Nielsen
HB, Juncker AS, Bertalan M, Levenez F, Pons N, Rasmussen S,
Sunagawa S, Tap J, Tims S, Zoetendal EG, Brunak S, Clement
K, Dore J, Kleerebezem M, Kristiansen K, Renault P, Sicheritz-
Ponten T, de Vos WM, Zucker JD, Raes J, Hansen T, Bork P,
Wang J, Ehrlich SD, Pedersen O, Guedon E, Delorme C, Layec
S, Khaci G, van de Guchte M, Vandemeulebrouck G, Jamet A,
Dervyn R, Sanchez N, Maguin E, Haimet F, Winogradski Y,
Cultrone A, Leclerc M, Juste C, Blottiere H, Pelletier E,
LePaslier D, Artiguenave F, Bruls T, Weissenbach J, Turner K,
Parkhill J, Antolin M, Manichanh C, Casellas F, Boruel N,
Varela E, Torrejon A, Guarner F, Denariaz G, Derrien M, van
Hylckama Vlieg JE, Veiga P, Oozeer R, Knol J, Rescigno M,
Brechot C, M’Rini C, Merieux A, Yamada T (2013) Richness of
human gut microbiome correlates with metabolic markers.
Nature 500(7464):541–546. doi:10.1038/nature12506
92. Cotillard A, Kennedy SP, Kong LC, Prifti E, Pons N, Le
Chatelier E, Almeida M, Quinquis B, Levenez F, Galleron N,
Gougis S, Rizkalla S, Batto JM, Renault P, Dore J, Zucker JD,
Clement K, Ehrlich SD, Blottiere H, Leclerc M, Juste C, de
Wouters T, Lepage P, Fouqueray C, Basdevant A, Henegar C,
Godard C, Fondacci M, Rohia A, Hajduch F, Weissenbach J,
Pelletier E, Le Paslier D, Gauchi JP, Gibrat JF, Loux V, Carre
W, Maguin E, van de Guchte M, Jamet A, Boumezbeur F, Layec
S (2013) Dietary intervention impact on gut microbial gene
richness. Nature 500(7464):585–588. doi:10.1038/nature12480
93. Mondot S, de Wouters T, Dore J, Lepage P (2013) The human
gut microbiome and its dysfunctions. Dig Dis 31(3–4):278–285.
94. Turnbaugh PJ, Backhed F, Fulton L, Gordon JI (2008) Diet-
induced obesity is linked to marked but reversible alterations in
the mouse distal gut microbiome. Cell Host Microbe
95. Turnbaugh PJ, Ridaura VK, Faith JJ, Rey FE, Knight R, Gordon
JI (2009) The effect of diet on the human gut microbiome: a
metagenomic analysis in humanized gnotobiotic mice. Sci
Transl Med 1 (6):6ra14
96. Ridaura VK, Faith JJ, Rey FE, Cheng J, Duncan AE, Kau AL,
Griffin NW, Lombard V, Henrissat B, Bain JR, Muehlbauer MJ,
Ilkayeva O, Semenkovich CF, Funai K, Hayashi DK, Lyle BJ,
Martini MC, Ursell LK, Clemente JC, Van Treuren W, Walters
WA, Knight R, Newgard CB, Heath AC, Gordon JI (2013) Gut
microbiota from twins discordant for obesity modulate meta-
bolism in mice. Science 341(6150):1241214. doi:10.1126/
97. Vijay-Kumar M, Aitken JD, Carvalho FA, Cullender TC,
Mwangi S, Srinivasan S, Sitaraman SV, Knight R, Ley RE,
Gewirtz AT (2010) Metabolic syndrome and altered gut
microbiota in mice lacking Toll-like receptor 5. Science
98. Di Luccia B, Crescenzo R, Mazzoli A, Cigliano L, Venditti P,
Walser JC, Widmer A, Baccigalupi L, Ricca E, Iossa S (2015)
Rescue of fructose-induced metabolic syndrome by antibiotics
or faecal transplantation in a rat model of obesity. PLoS One
10(8):e0134893. doi:10.1371/journal.pone.0134893
99. Hotamisligil GS (2006) Inflammation and metabolic disorders.
Nature 444(7121):860–867
100. Cani PD, Amar J, Iglesias MA, Poggi M, Knauf C, Bastelica D,
Neyrinck AM, Fava F, Tuohy KM, Chabo C, Waget A, Delmee
E, Cousin B, Sulpice T, Chamontin B, Ferrieres J, Tanti JF,
Gibson GR, Casteilla L, Delzenne NM, Alessi MC, Burcelin R
(2007) Metabolic endotoxemia initiates obesity and insulin
resistance. Diabetes 56(7):1761–1772
101. Wright SD, Ramos RA, Tobias PS, Ulevitch RJ, Mathison JC
(1990) CD14, a receptor for complexes of lipopolysaccharide
(LPS) and LPS binding protein. Science 249(4975):1431–1433
102. Neal MD, Leaphart C, Levy R, Prince J, Billiar TR, Watkins S,
Li J, Cetin S, Ford H, Schreiber A, Hackam DJ (2006) Ente-
rocyte TLR4 mediates phagocytosis and translocation of
Gut microbiota and obesity 159
bacteria across the intestinal barrier. J Immunol
103. Vreugdenhil AC, Rousseau CH, Hartung T, Greve JW, van ‘t
Veer C, Buurman WA (2003) Lipopolysaccharide (LPS)-bind-
ing protein mediates LPS detoxification by chylomicrons.
J Immunol 170(3):1399–1405
104. Creely SJ, McTernan PG, Kusminski CM, Fisher M, Da Silva
NF, Khanolkar M, Evans M, Harte AL, Kumar S (2007)
Lipopolysaccharide activates an innate immune system response
in human adipose tissue in obesity and type 2 diabetes. Am J
Physiol Endocrinol Metab 292(3):E740–747
105. Harte AL, da Silva NF, Creely SJ, McGee KC, Billyard T,
Youssef-Elabd EM, Tripathi G, Ashour E, Abdalla MS, Sharada
HM, Amin AI, Burt AD, Kumar S, Day CP, McTernan PG
(2010) Elevated endotoxin levels in non-alcoholic fatty liver
disease. J Inflamm (Lond) 7:15
106. Davis JE, Gabler NK, Walker-Daniels J, Spurlock ME (2008)
Tlr-4 deficiency selectively protects against obesity induced by
diets high in saturated fat. Obesity (Silver Spring)
107. Tsukumo DM, Carvalho-Filho MA, Carvalheira JB, Prada PO,
Hirabara SM, Schenka AA, Araujo EP, Vassallo J, Curi R,
Velloso LA, Saad MJ (2007) Loss-of-function mutation in Toll-
like receptor 4 prevents diet-induced obesity and insulin resis-
tance. Diabetes 56(8):1986–1998
108. Cani PD, Bibiloni R, Knauf C, Waget A, Neyrinck AM, Delz-
enne NM, Burcelin R (2008) Changes in gut microbiota control
metabolic endotoxemia-induced inflammation in high-fat diet-
induced obesity and diabetes in mice. Diabetes 57(6):1470–1481
109. Wang Z, Xiao G, Yao Y, Guo S, Lu K, Sheng Z (2006) The role
of bifidobacteria in gut barrier function after thermal injury in
rats. J Trauma 61(3):650–657
110. Griffiths EA, Duffy LC, Schanbacher FL, Qiao H, Dryja D,
Leavens A, Rossman J, Rich G, Dirienzo D, Ogra PL (2004)
In vivo effects of bifidobacteria and lactoferrin on gut endotoxin
concentration and mucosal immunity in Balb/c mice. Dig Dis
Sci 49(4):579–589
111. Cani PD, Neyrinck AM, Fava F, Knauf C, Burcelin RG, Tuohy
KM, Gibson GR, Delzenne NM (2007) Selective increases of
bifidobacteria in gut microflora improve high-fat-diet-induced
diabetes in mice through a mechanism associated with endo-
toxaemia. Diabetologia 50(11):2374–2383
112. Cani PD, Possemiers S, Van de Wiele T, Guiot Y, Everard A,
Rottier O, Geurts L, Naslain D, Neyrinck A, Lambert DM,
Muccioli GG, Delzenne NM (2009) Changes in gut microbiota
control inflammation in obese mice through a mechanism
involving GLP-2-driven improvement of gut permeability. Gut
58(8):1091–1103. doi:10.1136/gut.2008.165886
113. Geurts L, Lazarevic V, Derrien M, Everard A, Van Roye M,
Knauf C, Valet P, Girard M, Muccioli GG, Francois P, de Vos
WM, Schrenzel J, Delzenne NM, Cani PD (2011) Altered gut
microbiota and endocannabinoid system tone in obese and dia-
betic leptin-resistant mice: impact on apelin regulation in
adipose tissue. Front Microbiol 2:149. doi:10.3389/fmicb.2011.
114. Muccioli GG, Naslain D, Backhed F, Reigstad CS, Lambert
DM, Delzenne NM, Cani PD (2010) The endocannabinoid
system links gut microbiota to adipogenesis. Mol Syst Biol
6:392. doi:10.1038/msb.2010.46
115. Everard A, Geurts L, Caesar R, Van Hul M, Matamoros S,
Duparc T, Denis RG, Cochez P, Pierard F, Castel J, Bindels LB,
Plovier H, Robine S, Muccioli GG, Renauld JC, Dumoutier L,
Delzenne NM, Luquet S, Backhed F, Cani PD (2014) Intestinal
epithelial MyD88 is a sensor switching host metabolism towards
obesity according to nutritional status. Nat Commun 5:5648.
116. Amar J, Chabo C, Waget A, Klopp P, Vachoux C, Bermudez-
Humaran LG, Smirnova N, Berge M, Sulpice T, Lahtinen S,
Ouwehand A, Langella P, Rautonen N, Sansonetti PJ, Burcelin
R (2011) Intestinal mucosal adherence and translocation of
commensal bacteria at the early onset of type 2 diabetes:
molecular mechanisms and probiotic treatment. EMBO Mol
Med 3(9):559–572. doi:10.1002/emmm.201100159
117. Amar J, Serino M, Lange C, Chabo C, Iacovoni J, Mondot S,
Lepage P, Klopp C, Mariette J, Bouchez O, Perez L, Courtney
M, Marre M, Klopp P, Lantieri O, Dore J, Charles M, Balkau B,
Burcelin R, Group DESIRS (2011) Involvement of tissue bac-
teria in the onset of diabetes in humans: evidence for a concept.
Diabetologia 54(12):3055–3061. doi:10.1007/s00125-011-2329-
118. Burcelin R, Serino M, Chabo C, Garidou L, Pomie C, Courtney
M, Amar J, Bouloumie A (2013) Metagenome and metabolism:
the tissue microbiota hypothesis. Diabetes Obes Metab 15(Suppl
3):61–70. doi:10.1111/dom.12157
119. Wostmann BS (1973) Intestinal bile acids and cholesterol
absorption in the germfree rat. J Nutr 103(7):982–990
120. Wostmann BS, Wiech NL (1961) Total serum and liver
cholesterol in germfree and conventional male rats. Am J
Physiol 201:1027–1029
121. Velagapudi VR, Hezaveh R, Reigstad CS, Gopalacharyulu P,
Yetukuri L, Islam S, Felin J, Perkins R, Boren J, Oresic M,
Backhed F (2010) The gut microbiota modulates host energy
and lipid metabolism in mice. J Lipid Res 51(5):1101–1112.
122. Ge
´rard P, Lepercq P, Leclerc M, Gavini F, Raibaud P, Juste C
(2007) Bacteroides sp. strain D8, the first cholesterol-reducing
bacterium isolated from human feces. Appl Environ Microbiol
123. Parmentier G, Eyssen H (1974) Mechanism of biohydrogenation
of cholesterol to coprostanol by Eubacterium ATCC 21408.
Biochim Biophys Acta 348(2):279–284
124. Sekimoto H, Shimada O, Makanishi M, Nakano T, Katayama O
(1983) Interrelationship between serum and fecal sterols. Jpn J
Med 22(1):14–20
125. Ge
´rard P (2009) GI tract: microbial metabolism of steroids. In:
Timmis KN (ed) Microbiology of hydrocarbons, oils, lipids, and
derived compounds, vol 4. Springer, Heidelberg, pp 3133–3140
126. Wang Z, Klipfell E, Bennett BJ, Koeth R, Levison BS, Dugar B,
Feldstein AE, Britt EB, Fu X, Chung YM, Wu Y, Schauer P,
Smith JD, Allayee H, Tang WH, DiDonato JA, Lusis AJ, Hazen
SL (2011) Gut flora metabolism of phosphatidylcholine pro-
motes cardiovascular disease. Nature 472(7341):57–63
127. Tang WH, Wang Z, Levison BS, Koeth RA, Britt EB, Fu X, Wu
Y, Hazen SL (2013) Intestinal microbial metabolism of phos-
phatidylcholine and cardiovascular risk. N Engl J Med
368(17):1575–1584. doi:10.1056/NEJMoa1109400
128. Ge
´rard P (2014) Metabolism of cholesterol and bile acids by the
gut microbiota. Pathogens 3(1):14–24. doi:10.3390/
129. Joyce SA, Shanahan F, Hill C, Gahan CG (2014) Bacterial bile
salt hydrolase in host metabolism: potential for influencing
gastrointestinal microbe-host crosstalk. Gut Microbes
5(5):669–674. doi:10.4161/19490976.2014.969986
130. Kondo S, Xiao JZ, Satoh T, Odamaki T, Takahashi S, Sugahara
H, Yaeshima T, Iwatsuki K, Kamei A, Abe K (2010) Antiobe-
sity effects of Bifidobacterium breve strain B-3 supplementation
in a mouse model with high-fat diet-induced obesity. Biosci
Biotechnol Biochem 74(8):1656–1661. doi:10.1271/bbb.100267
131. An HM, Park SY, Lee do K, Kim JR, Cha MK, Lee SW, Lim
HT, Kim KJ, Ha NJ (2011) Antiobesity and lipid-lowering
effects of Bifidobacterium spp. in high fat diet-induced obese
rats. Lipids Health Dis 10:116. doi:10.1186/1476-511X-10-116
160 P. Ge
132. Chen J, Wang R, Li XF, Wang RL (2012) Bifidobacterium
adolescentis supplementation ameliorates visceral fat accumu-
lation and insulin sensitivity in an experimental model of the
metabolic syndrome. Br J Nutr 107(10):1429–1434. doi:10.
133. Chen JJ, Wang R, Li XF, Wang RL (2011) Bifidobacterium
longum supplementation improved high-fat-fed-induced meta-
bolic syndrome and promoted intestinal Reg I gene expression.
Exp Biol Med 236(7):823–831. doi:10.1258/ebm.2011.010399
134. Cano PG, Santacruz A, Trejo FM, Sanz Y (2013) Bifidobac-
terium CECT 7765 improves metabolic and immunological
alterations associated with obesity in high-fat diet-fed mice.
Obesity (Silver Spring) 21(11):2310–2321. doi:10.1002/oby.
135. Moya-Perez A, Neef A, Sanz Y (2015) Bifidobacterium pseu-
docatenulatum CECT 7765 reduces obesity-associated
inflammation by restoring the lymphocyte-macrophage balance
and gut microbiota structure in high-fat diet-fed mice. PLoS One
10(7):e0126976. doi:10.1371/journal.pone.0126976
136. Lee HY, Park JH, Seok SH, Baek MW, Kim DJ, Lee KE, Paek
KS, Lee Y, Park JH (2006) Human originated bacteria, Lacto-
bacillus rhamnosus PL60, produce conjugated linoleic acid and
show anti-obesity effects in diet-induced obese mice. Biochim
Biophys Acta 1761(7):736–744. doi:10.1016/j.bbalip.2006.05.
137. Lee K, Paek K, Lee HY, Park JH, Lee Y (2007) Antiobesity
effect of trans-10, cis-12-conjugated linoleic acid-producing
Lactobacillus plantarum PL62 on diet-induced obese mice.
J Appl Microbiol 103(4):1140–1146. doi:10.1111/j.1365-2672.
138. Hamad EM, Sato M, Uzu K, Yoshida T, Higashi S, Kawakami
H, Kadooka Y, Matsuyama H, Abd El-Gawad IA, Imaizumi K
(2009) Milk fermented by Lactobacillus gasseri SBT2055
influences adipocyte size via inhibition of dietary fat absorption
in Zucker rats. Br J Nutr 101(5):716–724. doi:10.1017/
139. Aronsson L, Huang Y, Parini P, Korach-Andre M, Hakansson J,
Gustafsson JA, Pettersson S, Arulampalam V, Rafter J (2010)
Decreased fat storage by Lactobacillus paracasei is associated
with increased levels of angiopoietin-like 4 protein
(ANGPTL4). PLoS One 5(9). doi:10.1371/journal.pone.
140. Okubo T, Takemura N, Yoshida A, Sonoyama K (2013) KK/Ta
mice administered Lactobacillus plantarum strain no. 14 have
lower adiposity and higher insulin sensitivity. Biosci Microbiota
Food Health 32(3):93–100. doi:10.12938/bmfh.32.93
141. Fak F, Backhed F (2012) Lactobacillus reuteri prevents diet-
induced obesity, but not atherosclerosis, in a strain dependent
fashion in Apoe
mice. PLoS One 7(10):e46837. doi:10.1371/
142. Kim SW, Park KY, Kim B, Kim E, Hyun CK (2013) Lacto-
bacillus rhamnosus GG improves insulin sensitivity and reduces
adiposity in high-fat diet-fed mice through enhancement of
adiponectin production. Biochem Biophys Res Commun
431(2):258–263. doi:10.1016/j.bbrc.2012.12.121
143. Wang LX, Liu K, Gao DW, Hao JK (2013) Protective effects of
two Lactobacillus plantarum strains in hyperlipidemic mice.
World J Gastroenterol 19(20):3150–3156. doi:10.3748/wjg.v19.
144. Tomaro-Duchesneau C, Saha S, Malhotra M, Jones ML, Labbe
A, Rodes L, Kahouli I, Prakash S (2014) Effect of orally
administered L. fermentum NCIMB 5221 on markers of meta-
bolic syndrome: an in vivo analysis using ZDF rats. Appl
Microbiol Biotechnol 98(1):115–126. doi:10.1007/s00253-013-
145. Park KY, Kim B, Hyun CK (2015) Lactobacillus rhamnosus GG
reverses insulin resistance but does not block its onset in diet-
induced obese mice. J Microbiol Biotechnol 25(5):753–757
146. Martin FP, Wang Y, Sprenger N, Yap IK, Lundstedt T, Lek P,
Rezzi S, Ramadan Z, van Bladeren P, Fay LB, Kochhar S,
Lindon JC, Holmes E, Nicholson JK (2008) Probiotic modula-
tion of symbiotic gut microbial-host metabolic interactions in a
humanized microbiome mouse model. Mol Syst Biol 4:157.
147. Park YH, Kim JG, Shin YW, Kim SH, Whang KY (2007) Effect
of dietary inclusion of Lactobacillus acidophilus ATCC 43121
on cholesterol metabolism in rats. J Microbiol Biotechnol
148. Kadooka Y, Sato M, Imaizumi K, Ogawa A, Ikuyama K, Akai
Y, Okano M, Kagoshima M, Tsuchida T (2010) Regulation of
abdominal adiposity by probiotics (Lactobacillus gasseri
SBT2055) in adults with obese tendencies in a randomized
controlled trial. Eur J Clin Nutr 64(6):636–643. doi:10.1038/
149. Kadooka Y, Sato M, Ogawa A, Miyoshi M, Uenishi H, Ogawa
H, Ikuyama K, Kagoshima M, Tsuchida T (2013) Effect of
Lactobacillus gasseri SBT2055 in fermented milk on abdominal
adiposity in adults in a randomised controlled trial. Br J Nutr
110(9):1696–1703. doi:10.1017/S0007114513001037
150. Ogawa A, Kadooka Y, Kato K, Shirouchi B, Sato M (2014)
Lactobacillus gasseri SBT2055 reduces postprandial and fasting
serum non-esterified fatty acid levels in Japanese hypertriacyl-
glycerolemic subjects. Lipids Health Dis 13:36. doi:10.1186/
151. Floch MH (2014) Recommendations for probiotic use in
humans—a 2014 update. Pharmaceuticals 7(10):999–1007.
152. Roberfroid M, Gibson GR, Hoyles L, McCartney AL, Rastall R,
Rowland I, Wolvers D, Watzl B, Szajewska H, Stahl B, Guarner
F, Respondek F, Whelan K, Coxam V, Davicco MJ, Leotoing L,
Wittrant Y, Delzenne NM, Cani PD, Neyrinck AM, Meheust A
(2010) Prebiotic effects: metabolic and health benefits. Br J Nutr
104(Suppl 2):S1–63. doi:10.1017/S0007114510003363
153. Everard A, Lazarevic V, Derrien M, Girard M, Muccioli GG,
Neyrinck AM, Possemiers S, Van Holle A, Francois P, de Vos
WM, Delzenne NM, Schrenzel J, Cani PD (2011) Responses of
gut microbiota and glucose and lipid metabolism to prebiotics in
genetic obese and diet-induced leptin-resistant mice. Diabetes
60(11):2775–2786. doi:10.2337/db11-0227
154. Neyrinck AM, Possemiers S, Druart C, Van de Wiele T, De
Backer F, Cani PD, Larondelle Y, Delzenne NM (2011) Prebi-
otic effects of wheat arabinoxylan related to the increase in
bifidobacteria, Roseburia and Bacteroides/Prevotella in diet-in-
duced obese mice. PLoS One 6(6):e20944. doi:10.1371/journal.
155. Parnell JA, Reimer RA (2012) Prebiotic fibres dose-dependently
increase satiety hormones and alter Bacteroidetes and Firmi-
cutes in lean and obese JCR:LA-cp rats. Br J Nutr
107(4):601–613. doi:10.1017/S0007114511003163
156. Everard A, Lazarevic V, Gaia N, Johansson M, Stahlman M,
Backhed F, Delzenne NM, Schrenzel J, Francois P, Cani PD
(2014) Microbiome of prebiotic-treated mice reveals novel tar-
gets involved in host response during obesity. ISME J
8(10):2116–2130. doi:10.1038/ismej.2014.45
157. Respondek F, Gerard P, Bossis M, Boschat L, Bruneau A,
Rabot S, Wagner A, Martin JC (2013) Short-chain fructo-
oligosaccharides modulate intestinal microbiota and metabolic
parameters of humanized gnotobiotic diet induced obesity
mice. PLoS One 8(8):e71026. doi:10.1371/journal.pone.
Gut microbiota and obesity 161
158. Cani PD, Daubioul CA, Reusens B, Remacle C, Catillon G,
Delzenne NM (2005) Involvement of endogenous glucagon-like
peptide-1(7-36) amide on glycaemia-lowering effect of
oligofructose in streptozotocin-treated rats. J Endocrinol
185(3):457–465. doi:10.1677/joe.1.06100
159. Cani PD, Neyrinck AM, Maton N, Delzenne NM (2005)
Oligofructose promotes satiety in rats fed a high-fat diet:
involvement of glucagon-like peptide-1. Obes Res
13(6):1000–1007. doi:10.1038/oby.2005.117
160. Chassaing B, Miles-Brown JP, Pellizzon M, Ulman E, Ricci M,
Zhang L, Patterson AD, Vijay-Kumar M, Gewirtz AT (2015)
Lack of soluble fiber drives diet-induced adiposity in mice. Am J
Physiol Gastrointest Liver Physiol 00172:02015. doi:10.1152/
161. Cani PD, Joly E, Horsmans Y, Delzenne NM (2006)
Oligofructose promotes satiety in healthy human: a pilot study.
Eur J Clin Nutr 60(5):567–572. doi:10.1038/sj.ejcn.1602350
162. Dewulf EM, Cani PD, Claus SP, Fuentes S, Puylaert PG,
Neyrinck AM, Bindels LB, de Vos WM, Gibson GR, Thissen
JP, Delzenne NM (2013) Insight into the prebiotic concept:
lessons from an exploratory, double blind intervention study
with inulin-type fructans in obese women. Gut
62(8):1112–1121. doi:10.1136/gutjnl-2012-303304
163. Genta S, Cabrera W, Habib N, Pons J, Carillo IM, Grau A,
Sanchez S (2009) Yacon syrup: beneficial effects on obesity and
insulin resistance in humans. Clin Nutr 28(2):182–187. doi:10.
164. Kellow NJ, Coughlan MT, Reid CM (2014) Metabolic benefits
of dietary prebiotics in human subjects: a systematic review of
randomised controlled trials. Br J Nutr 111(7):1147–1161.
165. Parnell JA, Reimer RA (2009) Weight loss during oligofructose
supplementation is associated with decreased ghrelin and
increased peptide YY in overweight and obese adults. Am J Clin
Nutr 89(6):1751–1759. doi:10.3945/ajcn.2009.27465
166. Aroniadis OC, Brandt LJ (2013) Fecal microbiota transplanta-
tion: past, present and future. Curr Opin Gastroenterol
29(1):79–84. doi:10.1097/MOG.0b013e32835a4b3e
167. Eiseman B, Silen W, Bascom GS, Kauvar AJ (1958) Fecal
enema as an adjunct in the treatment of pseudomembranous
enterocolitis. Surgery 44(5):854–859
168. Kassam Z, Lee CH, Yuan Y, Hunt RH (2013) Fecal microbiota
transplantation for Clostridium difficile infection: systematic
review and meta-analysis. Am J Gastroenterol 108(4):500–508.
169. Vrieze A, Van Nood E, Holleman F, Salojarvi J, Kootte RS,
Bartelsman JF, Dallinga-Thie GM, Ackermans MT, Serlie MJ,
Oozeer R, Derrien M, Druesne A, Van Hylckama Vlieg JE,
Bloks VW, Groen AK, Heilig HG, Zoetendal EG, Stroes ES, de
Vos WM, Hoekstra JB, Nieuwdorp M (2012) Transfer of
intestinal microbiota from lean donors increases insulin sensi-
tivity in individuals with metabolic syndrome. Gastroenterology
143(4):913–916 e917. doi:10.1053/j.gastro.2012.06.031
162 P. Ge
... Numerous studies indicated that dietary nutrient intake, as a key environmental factor impacting gut microbiota composition, can induce "dysbiosis" which is defined as an altered microbial community including richness, diversity and composition. The dysbiosis can accelerate the homeostatic imbalance which contributes to multiple disease states [4][5][6][7][8][9], including obesity, diabetes, liver diseases, cancer, brain disorders, as well as cardiovascular disease (CVD) which remains the leading cause of morbidity and mortality worldwide [10,11]. ...
... X. Zhang and P. Gérard / Computational and Structural Biotechnology Journal xxx (xxxx) [1][2][3][4][5][6][7][8][9][10][11][12] circulating TMAO levels, an increase of macrophage foam cell formation and enhancement of aortic atherosclerotic plaque development (Fig. 1) [33,86]. On the contrary, the capacity to TMAO production, and choline or carnitine diet related atherosclerotic plaque burden were respectively eliminated or suppressed in GF or antibiotic treated ApoE −/− mice (C57BL/6 strain) [33,86]. ...
Cardiovascular diseases (CVD) are a group of disorders of the heart and blood vessels and remain the leading cause of morbidity and mortality worldwide. Over the past decades, accumulating studies indicated that the gut microbiota, an indispensable “invisible organ”, plays a vital role in human metabolism and disease states including CVD. Among many endogenous and exogenous factors that can impact gut microbial communities, the dietary nutrients emerge as an essential component of host-microbiota relationships that can be involved in CVD susceptibility. In this review, we summarize the major concepts of dietary modulation of the gut microbiota and the chief principles of the involvement of this microbiota in CVD development. We also discuss the mechanisms of diet-microbiota crosstalk that regulate CVD progression, including endotoxemia, inflammation, gut barrier dysfunction and lipid metabolism dysfunction. In addition, we describe how metabolites produced by the microbiota, including trimethylamine-N-oxide (TMAO), secondary bile acids (BAs), short chain fatty acids (SCFAs) as well as aromatic amino acids (AAAs) derived metabolites play a role in CVD pathogenesis. Finally, we present the potential dietary interventions which interacted with gut microbiota as novel preventive and therapeutic strategies for CVD management.
... Although the structure of the microorganism is relatively stable, factors including infection, diet, or genetics can also affect the intestinal flora, resulting in the growth of pathogenic bacteria, the loss of normal commensal bacteria, and the decline in diversity (Levy et al., 2017), which is called dysbiosis, and can further lead to diseases such as obesity (Gérard, 2016), autoimmune disease (Knip and Siljander, 2016), neurological disorders (Tremlett et al., 2017), and inflammatory bowel disease (Wlodarska et al., 2015). A study showed that using mass spectrometry to detect chemicals in the peripheral circulation in germ-free (GF) mice found that the synthesis of most substances depends on the gut microbiome (Wikoff et al., 2009). ...
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Epilepsy is a common chronic brain disease. There are many clinical methods to control epileptic seizures, such as anti-seizure medications (ASMs) or surgical removal of epileptogenic lesions. However, the pathophysiology of epilepsy is still unknown, making it difficult to control or prevent it. The host’s immune system monitors gut microbes, interacts with microbes through pattern recognition receptors such as Toll-like receptors (TLRs) and NOD-like receptors (NLRs) expressed by innate immune cells, and activates immune responses in the body to kill pathogens and balance the relationship between microbes and host. In addition, inflammatory responses induced by the innate immune system are seen in animal models of epilepsy and temporal lobe epilepsy brain tissue to combat pathogens or injuries. This review summarizes the potential relationship between gut microbes, innate immunity, and epilepsy based on recent research to provide more hints for researchers to explore this field further.
... The gastrointestinal tract is colonized by microbial communities called gut microbiota [6], which play a relevant role in regulating the innate and adaptive immune system, gut motility, gut barrier homeostasis, nutrient absorption and fat distribution [7]. Dysbiosis, defined as an imbalance in microbial communities [8], can be induced by multiple factors, such as an unhealthy diet [9] or the use of antibiotics and other drugs [10,11], and is related to obesity and non-communicable chronic diseases [12]. Dysbiosis induces gut barrier dysfunction, which leads to the translocation from the gut into the bloodstream of Gram-negative bacterial components, such as lipopolysaccharide [13]. ...
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Objective: To investigate the association of plasma levels of endocannabinoids with fecal microbiota. Methods: Plasma levels of endocannabinoids, anandamide (AEA) and 2-arachidonoylglycerol (2-AG), as well as their eleven analogues, and arachidonic acid (AA), were measured using liquid chromatography-tandem mass spectrometry in 92 young adults. DNA extracted from stool samples was analyzed using 16S rRNA gene sequencing. Lipopolysaccharide levels were measured in plasma samples. Results: Plasma levels of endocannabinoids and their analogues were not related to beta or alpha diversity indexes. Plasma levels of AEA and related N-acylethanolamines correlated positively with the relative abundance of Faecalibacterium genus (all rho ≥ 0.26, p ≤ 0.012) and Akkermansia genus (all rho ≥ 0.22, p ≤ 0.036), and negatively with the relative abundance of Bilophila genus (all rho ≤ -0.23, p ≤ 0.031). Moreover, plasma levels of 2-AG and other acylglycerols correlated positively with the relative abundance of Parasutterella (all rho ≥ 0.24, p ≤ 0.020) and Odoribacter genera (all rho ≥ 0.27, p ≤ 0.011), and negatively with the relative abundance of Prevotella genus (all rho ≤ -0.24, p ≤ 0.023). In participants with high lipopolysaccharide values, the plasma levels of AEA and related N-acylethanolamines, as well as AA and 2-AG, were negatively correlated with plasma levels of lipopolysaccharide (all rho ≤ -0.24, p ≤ 0.020). Conclusion: Plasma levels of endocannabinoids and their analogues are correlated to specific fecal bacterial genera involved in maintaining gut barrier integrity in young adults. This suggests that plasma levels of endocannabinoids and their analogues may play a role in the gut barrier integrity in young adults.
... 20 Saturated fatty acids (SFAs) could activate the toll-like receptors (TLRs), especially TLR2 and TLR4, 21 then activate nuclear factor kappa B (NF-κB), resulting in inflammatory responses. 22 By contrast, monounsaturated fatty acids (MUFAs) and polyunsaturated fatty acids (PUFAs) could reduce the concentration of interleukin-6 (IL-6) and tumor necrosis factor-α (TNF-α), and relived inflammatory reaction. 18,23,24 However, the role of n-6 PUFAs played in was still controversies. ...
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Purpose: To verify the mediating role of inflammatory factors in plasma fatty acid-induced changes in cognitive function in patients with type 2 diabetes mellitus (T2DM). Patients and methods: In this study, we evaluated the cognitive function of 372 Chinese patients (the average age was 58.00 (52.50, 63.00) years) with T2DM by using the Mini-Mental State Examination (MMSE) and the Montreal Cognitive Assessment (MoCA), with plasma fatty acids measured by gas chromatography analysis and inflammatory cytokines determined by immune turbidimetric analysis and enzyme-linked immunosorbent assay (ELISA) to investigate whether there was a correlation between the plasma fatty acids, inflammatory cytokine levels and cognitive test scores in Chinese patients with T2DM. Results: We found that the increase of waist circumference and hip circumference might lead to cognitive impairment and induce the inflammatory response. Higher saturated fatty acids (SFAs) levels in plasma were linked to cognitive decline, while higher monounsaturated fatty acids (MUFAs) intake might be a protective factor for cognitive function. In addition, higher levels of plasma n-6 polyunsaturated fatty acids (n-6 PUFAs) stood out as having association with lower cognitive function scores, while higher level of plasma C22:6 n-3 could be a predictor of better cognitive function. In our study, higher SFAs led to higher proinflammatory factor levels. Apart from that, MUFAs and stearoyl-CoA desaturase-18 (SCD-18) were positively related to hypersensitive C-reactive protein (hs-CRP). Meanwhile, higher level of plasma C20:0 could lead to better MMSE delayed recall by reduce the expression of hs-CRP. Conclusion: Levels of plasma SFAs, C18:3 n-6, and C20:3 n-6 could be a predictor for worse cognitive function, while MUFAs and C22:6 n-3 could be a predictor for better cognitive function. The level of hs-CRP could be a mediator of C20:0 induced the change of cognitive function.
... An imbalance of the intestinal flora may lead to bacterial translocation by increasing intestinal permeability and inducing mucosal immune dysfunction [9]. Microbiota dysbiosis can lead to various diseases, including diabetes and obesity [10][11][12]. ...
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Sepsis is defined as a life-threatening organ dysfunction, which is caused by a dysregulated host response to infection. The composition of the intestinal microbiota is significantly different between patients with sepsis and healthy individuals. Intestinal microbial imbalance plays an important role in the occurrence and development of sepsis. Our review mainly introduces the mechanism of intestinal microbiota involvement in sepsis, the effects of microbiota dysbiosis on the damage of multiple organs and concisely discusses the prospects for microbe-specific treatment of sepsis in the future.
... The gut microbiota functions as an organ with many metabolism, immunology, and endocrine-like effects that are crucial for human health. 10,11 The pathogenesis of gut microbiota involved in the lipid accumulation may be through its influence on energy balance, nutrient absorption, inflammatory pathway, and the gut-brain axis. 12 However, the effects of early STA administration and its subsequent withdrawal on gut microbiota and bacterial metabolites are poorly understood. ...
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Background: This study aims to evaluate the effects of sub-therapeutic antibiotic (STA) administration and its subsequent withdrawal on body tissue deposition, gut microbiota and metabolite profiles of piglets. The STA piglets were fed with STA (30 mg kg-1 bacitracin methylene disalicylate, 75 mg kg-1 chlortetracycline, 300 mg kg-1 calcium oxytetracycline) for 14d and the target BW of the withdrawal period is 25 kg. Results: The results showed that STA did not improve piglets' growth performance during the two periods. Piglets treated with STA had lower body water deposition during the withdrawal period and tended to increase body lipid deposition during the withdrawal period and the whole period than CON group. It was found that STA markedly altered the colonic microbiota and their metabolites of piglets. STA was initially effective in decreasing the abundance of pathogenic bacteria during the administration period; however, STA could not continue the effect during the withdrawal period, leading to the rebound of pathogenic bacteria such as Alloprevotella and the increased abundance of other pathogenic bacteria like Oscillibacter. Remarkably, STA treatment decreased Blautia abundance which plays a potential protective role against obesity either during the two periods. Metabolomic analysis indicated that STA mainly altered amino acid metabolism, lipid metabolism, and carbohydrate metabolism during the two periods. Furthermore, Spearman's correlation analysis showed that the gut microbiota was highly correlated with microbial metabolites changes. Conclusion: These results suggest that early STA administration may alter body tissue deposition later in life through reshaping the gut microbiota and their metabolite profiles. This article is protected by copyright. All rights reserved.
The gut microbiota is the community of microbes (bacteria, viruses, fungi) that live in the gastrointestinal tract and are critical for normal nutrient absorption, digestion, and immune system development. These microbes communicate with the central nervous system (CNS) through interactions with the immune system, production of neuroactive metabolites/neurotransmitters, and activation of the vagus nerve. Spinal cord injury (SCI) disrupts the autonomic nervous system (ANS) and impairs communication with organ systems throughout the body, resulting in dysautonomia. This dysautonomia contributes to the pronounced immunosuppression and gastrointestinal dysfunction seen after SCI. Combined with frequent antibiotic use, physical and psychosocial stress, and altered GI motility, SCI-induced dysautonomia likely also causes an imbalance in the composition of the gut microbiome, i.e., gut dysbiosis. Pre-clincal and clinical studies indicate that SCI-induced gut dysbiosis triggers intestinal inflammation, impairs gut motility, and alters the composition of serum metabolites. SCI not only affects the abundance of various gut microbes but also the functional potential of the gut microbiome. As gut dysbiosis develops and the metabolites produced by gut microbiota change, these changes can influence the progress or severity of various SCI-associated comorbidities including metabolic syndrome, cardiovascular disease, liver dysfunction, and depression/anxiety disorders. Therefore, the development of novel therapeutic targets to prevent and treat these comorbidities requires a better understanding of how SCI affects the emergence or reduction in key gut microbial species.
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Background: Dysbiosis of intestinal microbiota may be linked to pathogenesis of obesity and metabolic disorders. Objective: This study compared the gut microbiome of obese Thai children with that of healthy controls and examined their relationships with host lifestyle, adiposity, and metabolic profiles. Methods: This cross-sectional study enrolled obese children aged 7-15. Body composition was evaluated using bioelectrical impedance analysis. Stool samples were analyzed by 16S rRNA sequencing using the Illumina MiSeq platform. Relative abundance and alpha- and beta-diversity were compared with normal-weight Thai children from a previous publication using Wilcoxon rank-sum test and ANOSIM. Relationships of gut microbiota with lifestyle activity, body composition, and metabolic profiles were assessed by canonical correlation analysis (CCA) and Spearman correlation. Results: The study enrolled 164 obese children with a male percentage of 59%. Mean age was 10.4 ± 2.2 years with a BMI z-score of 3.2 ± 1. The abundance of Bacteroidetes and Actinobacteria were found to be lower in obese children compared to nonobese children. Alpha-diversity indices showed no differences between groups, while beta-diversity revealed significant differences in the family and genus levels. CCA revealed significant correlations of the relative abundance of gut microbial phyla with sedentary lifestyle and certain metabolic markers. Univariate analysis revealed that Actinobacteria and Bifidobacterium were positively correlated with HDL-C and negatively correlated with body weight and screen time. Additionally, Actinobacteria was also negatively associated with fasting insulin and HOMA-IR. Lactobacillus showed positive correlation with acanthosis nigricans and adiposity. Cooccurrence analysis revealed 90 significant bacterial copresence and mutual exclusion interactions among 43 genera in obese children, whereas only 2 significant cooccurrences were found in nonobese children. Conclusions: The composition and diversity of gut microbiota in obese Thai children were different from those of their normal-weight peers. Specific gut microbiota were associated with lifestyle, adiposity, and metabolic features in obese children. An interventional study is needed to support causality between specific gut microbiota and obesity.
Background Browning of white adipose tissue (WAT) is currently considered a potential therapeutic approach to treat or prevent diet-induced obesity. Synbiotics have protective effects against diet-induced obesity; however, its role in adipose tissue browning has been less investigated. Aim of the work to study the possible effect of synbiotics intake on browning of WAT in obese rats. Material and methods Twenty-four adult male Wistar rats were randomly divided into four groups; normal diet (ND) control group, high fat diet (HFD) group, ND group receiving synbiotics, and HFD group receiving synbiotics. After eight weeks, all rats were sacrificed; and samples (blood, WAT, brown adipose tissue, and liver) were collected. Lipid profile, liver enzymes, fasting glucose, and fasting insulin levels were measured. The expression of browning-related genes: uncoupler protein-1 (UCP-1), peroxisome proliferator-activated receptor gamma coactivator 1-alpha (PGC1α), and peroxisome proliferator-activated receptors gamma (PPARγ) were measured by real-time polymerase chain reaction (PCR) in adipose tissues. Fibroblast growth factor 21 (FGF21) protein level was measured in serum, adipose and liver tissues, and FGF21 receptor expression was performed by real-time PCR in adipose tissues. Results synbiotics intake was associated with improvement in lipid profile, liver enzymes, and insulin sensitivity in HFD rats. Moreover, the intake was associated with higher gene expression of brown adipocyte-specific markers. As for the FGF21 and its receptor, intriguing results were obtained that needs further in-depth studies. Conclusion synbiotics might protect against diet-induced obesity through induction of thermogenic genes resulting in brown-like adipocyte phenotype in WAT.
Gut microbes share a symbiotic relationship with humans and perform several metabolic and physiological functions essential for human survival. It has been established in several scientific studies that obesity and other metabolic complications are always associated with disturbed gut microbiota profile, also called gut dysbiosis. In recent years, bariatric surgery has become a treatment of choice for weight loss, and it forms an important part of obesity management strategies across the globe. Interestingly, bariatric surgery has been shown to alter gut microbiota profile and synthesize short-chain fatty acids by gut microbes. In other words, gut microbes play a crucial role in better clinical outcomes associated with bariatric surgery. In addition, gut microbes are important in reducing weight and lowering the adverse events post-bariatric surgery. Therefore, several prebiotics, probiotics and postbiotics are recommended for patients who underwent bariatric surgery procedures for better clinical outcomes. The present review aims to understand the possible association between gut microbes and bariatric surgery and present scientific evidence showing the beneficial role of gut microbes in improving therapeutic outcomes of bariatric surgery.
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Obesity is associated with alteration of the gut microbiota. In order to clarify the effect of Lactobacillus-containing probiotics (LCP) on weight we performed a meta-analysis of clinical studies and experimental models. We intended to assess effects by Lactobacillus species. A broad search with no date or language restriction was performed. We included randomized controlled trials (RCTs) and comparative clinical studies in humans and animals or experimental models assessing the effect of Lactobacillus-containing probiotics on weight. We primarily attempted to extract and use change from baseline values. Data were extracted independently by two authors. Results were pooled by host and by Lactobacillus species and are summarized in a meta-analysis of standardized difference in means (SMDs). We identified and included 17 RCTs in humans, 51 studies on farm animals and 14 experimental models. Lactobacillus acidophilus administration resulted in significant weight gain in humans and in animals (SMD 0.15; 95% confidence intervals 0.05-0.25). Results were consistent in humans and animals. Lactobacillus fermentum and Lactobacillus ingluviei were associated with weight gain in animals. Lactobacillus plantarum was associated with weight loss in animals and Lactobacillus gasseri was associated with weight loss both in obese humans and in animals. Different Lactobacillus species are associated different effects on weight change that are host-specific. Further studies are needed to clarify the role of Lactobacillus species in the human energy harvest and weight regulation. Attention should be drawn to the potential effects of commonly marketed lactobacillus-containing probiotics on weight gain.
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Recent studies showed that germ-free (GF) mice are resistant to obesity when consuming a high-fat, high-carbohydrate Western diet. However, it remains unclear what mechanisms are involved in the antiobesity phenotype and whether GF mice develop insulin resistance and dyslipidemia with high-fat (HF) feeding. In the present study, we compared the metabolic consequences of HF feeding on GF and conventional (conv) C57BL/6J mice. GF mice consumed fewer calories, excreted more fecal lipids, and weighed significantly less than conv mice. GF/HF animals also showed enhanced insulin sensitivity with improved glucose tolerance, reduced fasting and nonfasting insulinemia, and increased phospho-Akt((Ser-473)) in adipose tissue. In association with enhanced insulin sensitivity, GF/HF mice had reduced plasma TNF-α and total serum amyloid A concentrations. Reduced hypercholesterolemia, a moderate accretion of hepatic cholesterol, and an increase in fecal cholesterol excretion suggest an altered cholesterol metabolism in GF/HF mice. Pronounced nucleus SREBP2 proteins and up-regulation of cholesterol biosynthesis genes indicate that enhanced cholesterol biosynthesis contributed to the cholesterol homeostasis in GF/HF mice. Our results demonstrate that fewer calorie consumption and increased lipid excretion contributed to the obesity-resistant phenotype of GF/HF mice and reveal that insulin sensitivity and cholesterol metabolism are metabolic targets influenced by the gut microbiota.
The trillions of bacterial cells that colonize the mammalian digestive tract influence both host physiology and the fate of dietary compounds. Gnotobionts and fecal transplantation have been instrumental in revealing the causal role of intestinal bacteria in energy homeostasis and metabolic dysfunctions such as type-2 diabetes. However, the exact contribution of gut bacterial metabolism to host energy balance is still unclear and knowledge about underlying molecular mechanisms is scant. We have previously characterized cecal bacterial community functions and host responses in diet-induced obese mice using omics approaches. Based on these studies, we here discuss issues on the relevance of mouse models, give evidence that the metabolism of cholesterol-derived compounds by gut bacteria is of particular importance in the context of metabolic disorders and that dominant species of the family Coriobacteriaceae are good models to study these functions.
Objective. Individuals with obesity and type 2 diabetes differ from lean and healthy individuals in their abundance of certain gut microbial species and microbial gene richness. Abundance of Akkermansia muciniphila, a mucin-degrading bacterium, has been inversely associated with body fat mass and glucose intolerance in mice, but more evidence is needed in humans. The impact of diet and weight loss on this bacterial species is unknown. Our objective was to evaluate the association between faecal A. muciniphila abundance, faecal microbiome gene richness, diet, host characteristics, and their changes after calorie restriction (CR). Design. The intervention consisted of a 6-week CR period followed by a 6-week weight stabilisation diet in overweight and obese adults (N=49, including 41 women). Faecal A. muciniphila abundance, faecal microbial gene richness, diet and bioclinical parameters were measured at baseline and after CR and weight stabilisation. Results. At baseline A. muciniphila was inversely related to fasting glucose, waist-to-hip ratio and subcutaneous adipocyte diameter. Subjects with higher gene richness and A. muciniphila abundance exhibited the healthiest metabolic status, particularly in fasting plasma glucose, plasma triglycerides and body fat distribution. Individuals with higher baseline A. muciniphila displayed greater improvement in insulin sensitivity markers and other clinical parameters after CR. These participants also experienced a reduction in A. muciniphila abundance, but it remained significantly higher than in individuals with lower baseline abundance. A. muciniphila was associated with microbial species known to be related to health. Conclusions. A. muciniphila is associated with a healthier metabolic status and better clinical outcomes after CR in overweight/obese adults. The interaction between gut microbiota ecology and A. muciniphila warrants further investigation.
Diabetes and obesity are two metabolic diseases characterized by insulin resistance and a low-grade inflammation. Seeking an inflammatory factor causative of the onset of insulin resistance, obesity, and diabetes, we have identified bacterial lipopolysaccharide (LPS) as a triggering factor. We found that normal endotoxemia increased or decreased during the fed or fasted state, respectively, on a nutritional basis and that a 4-week high-fat diet chronically increased plasma LPS concentration two to three times, a threshold that we have defined as metabolic endotoxemia. Importantly , a high-fat diet increased the proportion of an LPS-containing microbiota in the gut. When metabolic endotoxemia was induced for 4 weeks in mice through continuous subcutaneous infusion of LPS, fasted glycemia and insulinemia and whole-body, liver, and adipose tissue weight gain were increased to a similar extent as in high-fat–fed mice. In addition, adipose tissue F4/80-positive cells and markers of inflammation, and liver triglyceride content, were increased. Furthermore, liver, but not whole-body, insulin resistance was detected in LPS-infused mice. CD14 mutant mice resisted most of the LPS and high-fat diet–induced features of metabolic diseases. This new finding demonstrates that metabolic endotoxemia dysregulates the inflammatory tone and triggers body weight gain and diabetes. We conclude that the LPS/CD14 system sets the tone of insulin sensitivity and the onset of diabetes and obesity. Lowering plasma LPS concentration could be a potent strategy for the control of metabolic diseases.