gut microbiota and endotoxemia
TRANSCRIPT
Meghan McGillin January 15, 2016
Dysbiosis of the Gut and Obesity
The obesity pandemic
In the past thirty years the prevalence of obesity has more than doubled (W.H.O., 2015).
In 2014, over 600 million adults had a body mass index (BMI) over 31, classifying 11% of the
global adult population as obese. The World Health Organization defines obesity as excessive
accumulation of fat tissue and is a major risk factor for noncommunicable diseases like
cardiovascular disease (CVD), diabetes, musculoskeletal disorders, and some cancers (W.H.O.,
2015). Obesity is the result of an imbalanced energy homeostasis, which is the consequence of
greater intake of energy than expenditure (W.H.O., 2015). However, the doubling of global obesity rates over the past three decades suggests that the traditional equation for obesity is
incomplete. As more parts of the world transition from developing to industrial societies, a shift
in quality of life follows. These changes are most prominent in diet, where a diet high in whole foods is replaced with a more western-style diet, which is considered a diet high in refined carbohydrates, processed meats and low in dietary fiber (Carnahan, S. 2014). It is speculated that the soaring rates of obesity and metabolic syndrome are partially the consequence of the
shift from a whole to a processed food diet. Obesity is associated with a cluster of several metabolic disorders, such as insulin
resistance, hyperglycemia, hyperlipidemia, and hepatic steatosis (Chassaing,B. 2014 CT
Nathan 2008). This cluster of metabolic disorders is related to increased risk of diabetes,
cardiovascular diseases, and liver dysfunction (Cani, Patrice D 2009). The underlying cause of
obesity is complex and confounding, and involves various environmental, genetic, and lifestyle
factors. Recently, the human gut microbiota has been implicated as a major force in host
metabolism and the development of obesity.
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The human gut microbiota
The human gut microbiota refers to the trillions of microorganisms that reside in the
human gut (Qin, J., 2009). It is estimated to be home to 1000 different species (Qin, J., 2009),
and contains greater than 100 times the genes found in the human genome (Carnahan, S.,
2014). The human gut microbiota can be viewed as “a responsive intestinal endocrine organ”
(Rosenbaum, Michael, 2015), capable of secreting or modifying the production of molecules
involved in energy balance and energy stores (Rosenbaum, Michael, 2015).
The gut microbiota is intertwined with many aspects of host metabolism of nondigestible
carbohydrates, absorption of micronutrients, synthesis of essential vitamins, and mediation of
immune responses (Requena,Teresa, 2013). Recent advances in analytical methods like DNA
sequencing, metabolomics, and glycomics have lead to a series of discoveries pairing the gut
microbiota with obesity. Beginning with the discovery that the presence of a gut microbiota
increases energy harvest has fueled scientific inquiry in the gut microbiota involvement in host
metabolism (Bäckhed, F. 2004). It has lead to other fundamental findings within the field of research, such as the gut microbiota role in the regulation of fat storage. This phenomenon was
demonstrated when conventionalization of germ-free (GF) mice led to increases triglyceride
storage in adipocytes through a mechanism involving hepatic lipogenesis and fasting-induced
adipocyte factor (Fiaf) (Bäckhed, F. 2004). It has also been shown that certain interactions between the gut microbiota and the host immune system can exacerbate the development of
metabolic disorders (Cani, Patrice D 2009). Hansen touched on this concept when they reported that a dietary change in pregnant mice significantly altered the susceptibility of type I
diabetes in their offspring, despite the offspring being being fed a standard diet. It is speculated
that this finding stems from a shift towards an anti-inflammatory state following diet-induced
alterations in the gut microbiota (Hansen 2014). Altogether, these findings suggest that the gut microbiota can affect an individual’s energy harvest capacity and fat storage, and influence their
susceptibility to diseases, like diabetes and obesity (Requena,Teresa, 2013).
The vast diversity and highly individualized nature of one’s gut microbiota complicates
the already convoluted task of defining the gut microbiota exact involvement in host metabolism.
That being said, a more complete picture of the mechanisms behind the development of
metabolic disorders, like obesity, is beginning to surface. This new picture, which replaces the
old energy equation described earlier, illustrates the how such metabolic disorders might affect
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the status of one's gut microbiota and how one’s gut microbiota may affect the status of one’s
health.
Diet induced alterations in the gut microbiota represents both a contributing factor and a
ultimately a treatment for the obesity epidemic. Over the course in which one becomes obese,
abnormalities in host metabolism develop concurrently. The process is not fully understood, but
it is speculated that the dysfunctional metabolism can be attributed to disturbances in the gut
microbiome. These alterations in the gut bacteria composition can result from diet and may
further perpetuate the ill effects of diet-induced obesity (DIO) (Carnahan, S., 2014). The aim of
this review is to explore how alterations in the gut microbiota is linked to obesity and to explore
the relationship between them and diet.
Bacterial richness of the gut
The composition of the gut microbiota has been associated with obesity, as well as other
diseases and disorders such as allergies, diabetes, and irritable bowel disease (Le Chatelier, E.,
2013). The number of gut microbial genes, also referred to as the “bacterial richness” of the gut,
has the potential to identify individuals at increased risk for obesity, and other related diseases
(Le Chatelier, E., 2013).
A study to investigate the relationship between bacterial richness of the gut microbiome
and metabolic markers related to adiposity and inflammation found that variations in gut
bacterial richness can distinguish populations who may be at increased risk of developing
obesity-related diseases (Le Chatelier, E., 2013). In this study 209 subjects fell into two groups,
the subjects with less than 480,000 genes were placed in the low gene count (LGC) group and
those with more were placed in the high gene count (HGC) group (Le Chatelier, E., 2013). The
LGC group was characterized by increased adiposity, insulin resistance and inflammation (Le
Chatelier, E., 2013). The obese population was heavily represented by the LGC group. The
same was seen for other groups like individuals afflicted with inflammatory bowel disorder (IBD),
and elderly patients suffering from inflammation, all whom are most commonly associated with
low bacterial richness (Le Chatelier, E., 2013).
There were direct variations in gut microbiotas that were associated by marked differences in
bacterial gene richness. Starting at the phylum level, Proteobacteria and Bacteroidetes were
seen in greater abundance among the LGC group, the same was not observed in the HGC
group. Increased abundance of Verrucomicrobia, Actinobacteria, and Euryarchaeota were
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associated with high gene count individuals (Le Chatelier, E., 2013). Le Chatelier found 46
different genera between the two groups. The most dominant genera of the LGC subset was
Bacteroides, Parabacteroides, Ruminococcus, Campylobacter, Dialister, Porphyromonas,
Staphylococcus and Anaerostipes. In total, 36 genera were significantly associated with HGC, including Faecalibacterium, Bifidobacterium, Lactobacillus, Butyrivibrio, Alistipes, Akkermansia, Coprococcus and Methanobrevibacter (Le Chatelier, E., 2013). 73 species were identified in total from the 97 genomes analyzed. Interestingly, more than 93% of the total microbial
population belonged to just nine different species. There were significant differences in the
diversity and abundance of the nine dominant species observed between LGC and HGC
individuals. The known species that differed in abundance among the two groups are
Clostridium bolteae, Clostridium clostridioforme, Coprococcus eutactus, Clostridium ramosum, Clostridium symbiosum, Faecalibacterium prausnitzii, Methanobrevibacter smithii,
Ruminococcus gnavus, and Roseburia inulinivorans (Le Chatelier, E., 2013). This particular study found anti-inflammatory species, like Faecalibacterium prausnitzii to be associated with high bacterial richness;; whereas Bacteroides and Ruminococcus gnavus, both pro-inflammatory species associated with IBD, are more prevalent in LGC individuals.
Metabolic activity of HGC and LGC
There were significant differences in the metabolic activity of the LGC and HGC groups.
The metabolic activity of HGC individuals were associated with increased production of SCFA
(lactate, propionate, and butyrate), and demonstrated a higher potential for hydrogen
production. LGC individuals appeared to have an increased capacity to withstand oxidative
stress based off of the increased production of peroxides, catalase, and TCA modules. The
LGC gut microbiota had the potential to produce possible harmful metabolites, like
pro-carcinogens and ammonium and modules for degradation of aromatic amino acids and
β-glucuronide (Le Chatelier, E., 2013). Le Chatelier speculate the significant increase in potentially noxious modules may stem from the increased abundance of Bacteroides associated with the LGC.
Compared to the metabolic activity observed with HGC microbiota, the LGC had reduced
levels of butyrate-producing bacteria and a decrease in hydrogen and methane production. The
LGC group was associated with increased mucus degradation potential, as told by the reduced
ratio of Akkermansia to Ruminococcus torque and Ruminococcus gnavus (Le Chatelier, E., 2013). The weakened mucosal barrier protection, in addition to the increased presence of
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opportunistic pathogens, like Campylobacter and Shigella, and the improved oxidative stress threshold links that low bacterial richness to a pro-inflammatory gut microbiota (Le Chatelier, E.,
2013).
Phenotypes of HGC and LGC
Bacterial richness was significantly associated with biochemical and anthropometric
aspects of the host’s phenotype. As mention earlier, LGC represented a majority of the obese
subjects involved in this study. Low bacterial richness was correlated with increased adiposity,
body weight, and greater fat mass percentage. The LCG group was associated with insulin
resistance, hyperinsulinemia and inflammation (Le Chatelier, E., 2013). Le Chatelier suggested that the imbalance of pro- and anti-inflammatory bacteria that is responsible for the inflammation
and insulin resistance observed with LGC individuals. Low bacterial richness was also
associated increased levels of leptin, triglyceride, and free fatty acids. It was proposed that the
increase in free triglycerides and free fatty acids was triggered by increased expression in
fasting induced adipose factor (FIAF also known as ANGPLT4) resulting from an altered gut
microbiota. Members of the LGC group had lower serum adiponectin and HDL-cholesterol
compared to HGC individuals (Le Chatelier, E., 2013). The significant differences observed
between the two different groups suggest that the metabolic disturbances associated with low
levels of gut bacterial richness increase the risk for T2D and cardiovascular disorders (Le
Chatelier, E., 2013).
Le Chatelier found that those with low bacterial richness gained significantly more weight than their HGC counterparts over the course of nine years. Based off the differences
discussed earlier, Le Chatelier speculated that it may be the butyrate-producing bacteria found in high abundance in HGC individuals that discouraged the weight gain seen in LGC individuals.
The findings of this study demonstrated perfect stratification related to bacterial richness. The
significance of this was their ability to identify HGC and LGC based off of a few select bacteria,
like Faecalibacterium prausnitzii for HGC individuals and Bacteroides for LGC individuals (Le Chatelier, E., 2013).
Modulation of energy intake and metabolism by SCFA
A major function of the gut microbiome is the production of short chain fatty acids
(SCFA), which are the product of microbial fermentation of nondigestible polysaccharides in the
colon and small intestine (Lin,H.V. 2012). The predominant SCFA in the gut lumen of humans
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and rodents are acetate, butyrate, and propionate (Lin,H.V. 2012). SCFAs act as energy
sources for various cells in the body (Lin,H.V. 2012). Butyrate is utilized by the colonic
epithelium whereas propionate is prefered by liver cells. Acetate tends to circulate the body,
reaching it’s final destination in peripheral tissue (Lin,H.V. 2012). Acetate appeared to serve as
a substrate in cholesterol synthesis (Hartstra,A.V. 2015).
Despite providing an estimated 6-10% of the daily needed energy, SCFAs are also
directly involved in energy homeostasis by acting as signalling molecules in various host
metabolic pathways (Requena,Teresa, 2013). It’s becoming increasingly evident that SCFAs
protect against obesity by modifying host energy balance and appetite regulation.
In mice, there was an improvement in insulin sensitivity and energy expenditure after
being administered butyrate (Hartstra,A.V. 2015). Butyrate also functions as a regulator of the
production of glucose in the liver. Animal studies found propionate reduces lipogenesis in the
liver (Oh, Susan 2014). Propionate and butyrate effect gluconeogenesis in the liver. Intestinal
gluconeogenesis (IGN) releases glucose, which sends signals to the brain which result in
improved glucose metabolism and food intake (Hartstra,A.V. 2015). One study found that
butyrate was involved in initiating IGN gene expression in rats (Hartstra,A.V. 2015).
Another way in which SCFA interact with host metabolism is through regulation of gut
peptide secretion. SCFA act as signalling molecules for receptors involved in hormone
production and secretion, like G-coupled protein receptors (GPR) (Lin,H.V. 2012) (figure 1.).
Acetate has a high affinity for GPR43, whereas GPR41 is activated butyrate. Propionate is
indifferent and binds to both endogenous receptors (Lin,H.V. 2012). GPR41 activation induces
growth and stimulates the sympathetic nervous system (Rosenbaum, Michael, 2015). Activation
of GPR41 by butyrate induces the release of peptide YY (PYY), a satiety hormone (Delzenne,
N. M. 2011)]. GPR43 activation has been shown to decrease release of inflammatory cytokines
which may also increase hypothalamic sensitivity to leptin (Rosenbaum, Michael, 2015). Leptin
is a peptide released in the adipose tissue that regulates food intake (Oh, Susan 2014).
Butyrate and propionate have demonstrated a more direct effects on feeding behavior
compared to acetate (Rosenbaum, Michael, 2015).
Butyrate and propionate, specifically, have accumulated interest in regards to their
possible anti-obesity effects. Both have shown to stimulate gut hormone secretion and to reduce
appetite in humans resulting in decreased food intake (Shen, Jian, 2013). The observed
decrease in appetite and consumption is speculated to be the result of increased secretion by
endocrine cells of two gut peptide hormones, glucagon-like peptide-1 (GLP-1) and PYY. The
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expression of GLP-1 and PYY showed to decrease significantly in plasma levels of DIO mice
(Lin,H.V. 2012). It was also shown that these signalling molecules interfered with ghrelin
secretion, which provides further explanation for the observed increase in satiety and decrease
in energy intake (Shen, Jian, 2013). Consumption of dietary fiber has been correlated with
increased production of GLP-1 and PYY, and a decrease in ghrelin levels (Requena,Teresa,
2013). These findings offer an explanation to the observed increase in satiety, and decreased
energy intake associated with diets high in fiber.
Obesity-induced changes in composition and function
Gut microbial profiles of obese rodents
One of the first discoveries highlighting the collaboration between the gut microbiota and
human energy homeostasis was when Bäckhed found that germ-free (GF) mice were protected
from diet induced weight gain. When GF mice were colonized with gut bacteria, weight gain and
increased fat mass followed (Bäckhed, 2004). Perhaps the most important finding from this
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discovery was the significance of the microbial type on the mice’s weight gain outcome
(Rosenbaum, Michael, 2015 CT Turnbaugh 2006).
Obesity showed a positive relationship to increases in the Firmicutes to Bacteriodetes
ratio populating the gut of rodents (Rosenbaum, Michael, 2015). This was also observed along
side an overall decrease in gut diversity resulting from both weight and diet composition
(Rosenbaum, Michael, 2015). When fecal transplants from obese subjects were introduced to
GF mice, they developed the obese phenotype following no significant change in daily chow
consumption (Rosenbaum, Michael, 2015) (figure 2.).
A study conducted on obese mice fed a HF diet found that those HF-DIO mice placed on
a calorie-restricted HF diet had greater microbial diversity in their gut than compared to when
they were at their maximal weight (Rosenbaum, Michael, 2015). The significance of this finding
was that it demonstrated that changes in energy intake, independent of diet, can alter gut
bacterial diversity of obese mice.
Shortcomings in translating mice to human gut microbiota studies
There are several anatomic, physiological, and behavioral factors that should be
accounted for when applying mouse based models to humans. The diet composition typical of
mice is higher in carbohydrate content, and lower in fat content compared to humans, which can
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demonstrate much more variety. Additionally, mice show significant differences in
thermogenesis by brown and beige adipose tissue (<50%) compared to humans (<5%)
(Rosenbaum, Michael, 2015).
Obesity and diversity in the human gut
Phylum-wide change
The link between the gut microbiota composition and obesity has yet to be defined. The
dominant phyla in the human gut are Bacteroidetes, Firmicutes, Proteobacteria, and
Actinobacteria (Rosenbaum, Michael, 2015). Collectively, these four phyla make up 97% of the
total microbial population (Rosenbaum, Michael, 2015). It is important to consider the high
degree of taxonomic variability in the human gut when using averages to describe phylum
representation. That being said, Firmicutes, make up around 60 to 65% of the gut microbiota,
and are associated with the fermentation of fiber to butyrate (Rosenbaum, Michael, 2015).
Bacteroidetes, which make up around 20 to 25% of the total gut microbiota, are associated with
polysaccharide degradation, and involve some butyrate producing species by fermentation of
fiber (Rosenbaum, Michael, 2015). Proteobacteria compose of approximately 5 to 10% of the
gut microbiota and its function in host metabolism is not known (Rosenbaum, Michael, 2015).
Actinobacteria represent approximately 3% of the gut microbiota and are associated with
vitamin biosynthesis (Rosenbaum, Michael, 2015). It’s being explored the significance of the ratio of Firmicutes to Bacteroidetes in the gut.
Firmicutes and Bacteroidetes are the dominant phyla responsible for the production of SCFAs
(Rosenbaum, Michael, 2015). A negative correlation between Bacteroidetes and obesity was
one of the first reported gut microbial alterations associated with host metabolism. In rodent
studies, and in some human, an increase in relative abundance of Firmicutes to Bacteroidetes
has been associated with obesity (Rosenbaum, Michael, 2015). However, whether this finding
translates to the human gut microbiota is unclear. There have been studies exploring the human
gut microbiota relationship between obesity and F/B ratio, some have produced results that
question, and in some cases, contradict the previous positive association between obesity and
the relative increase in Firmicutes at the expense of the Bacteroidetes (Rosenbaum, Michael,
2015). Different studies in both humans and rodents found that no difference in relative
abundance of Firmicutes and/or Bacteroidetes in obese vs lean individuals (Duncan, Sylvia, H.,
2008), others reported no effect of weight loss on the F/B ratio (Duncan, Sylvia, H., 2008), and
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some reported even greater relative abundance of Bacteroidetes in obese individuals
(Collado,M.C. 2008). The only fair conclusion one can make in regards to the relative
abundance of Firmicutes to Bacteroidetes is that it is uncertain whether that is an effective
predictor for obesity (Shen, Jian, 2013). The controversy arising from attempts to determine the
microbial profiles of obese human guts compared to their lean counterparts suggests
differences of the gut microbiota at the phylum level between obese and lean individuals might
not be so easily typecast.
Finer grain changes
One study set out on better defining the influence of obesity on the gut microbiota
composition, focusing members of the Lactobacillus genus (Million, M., 2012). Million et. al. compared the Lactobacillus population at the species level between obese and lean humans. They found an increase in Lactobacillus reuteri abundance and reduced levels of L.casei/paracasei and L. plantarum in obese patients. They also found that Methanobrevibacter smithii , a member of Archaea domain, was significantly less abundant in obese patient, in general (Million, M., 2012). Methanobrevibacter was also one of the dominant genera seen with individuals with high gene count, discussed earlier. This finding appears to contradict previous
studies, which reported increased levels of Methanobrevibacter smithii in obese patients (Zhang,H. 2009), and speculated that their increased capacity to ferment dietary
polysaccharides was their link to the observed increase in adipose tissue(Requena,Teresa,
2013). Methanobrevibacter smithii role in host metabolism remains unclear, but it does appear to be a key member of the gut.
Functional changes in the gut microbiota of obese individuals Gut dysbiosis has been characterized by a shift from SCFA producing microbes to
opportunistic pathogens (Qin, Junjie 2012). There were noted increases in potential
opportunistic pathogens associated with obesity. One study found that overweight and obese
pregnant women and their infants who later in childhood became overweight had a higher
abundance of Staphylococcus aureus (Santacruz, Arlette 2010). One study found that members belonging to the gram negative Enterobacter genus comprised a staggering 35% of a morbidly
obese patient (Fei, Na 2013).
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In addition to the increase in the prevalence of pathogenic microorganism in the obese
gut microbiota, there was an observed decrease in SCFA producing bacteria. SCFA producing
bacteria, like Bifidobacteria were in lower abundance in obese subjects (den Besten,G. 2013).
Role of gut microbiota in metabolic syndrome
The gut microbiota and metabolic enterotoxaemia, inflammation and gut permeability
It has been established that conventionalization of GF mice with a microbiota from a
diseased donor partially transfers aspects of the affected phenotype. This phenomenon
highlights the impact an impaired microbiota has in the establishment and manifestation of
noncommunicable disease (Chassaing,B. 2014).
Low-grade inflammation
Changes in the gut microbiota can promote low-grade inflammation (Chassaing,B.
2014). Obesity is considered as a state chronic low grade inflammation and is a major
contributor to the metabolic disturbances and disorders associated with increased BMI (Shen,
Jian, 2013). Low grade inflammation can be assessed by measuring levels of lipocalin-2 (Lcn2)
in fecal samples (Chassaing,B. 2014 CT Chassaing 2012). The production of pro-inflammatory cytokines responsible for the inflamed response is associated with increased adipose tissue
(Cani, P.D., , 2007). These cytokines, such as IL-1, IL-6 and TNF-α, can disrupt insulin
sensitivity and promote hyperinsulinemia and lipid storage in adipose and liver tissue (Cani,
P.D., , 2007). Inflammation results from the activation of toll-like receptors (TLR) by lipotoxic
substances, like saturated fatty acids, produced by the gut microbiota (Carnahan, S., 2014).
The relationship between the gut microbiota and low-grade inflammation was first
reported when studying colitis, which is inflammation in the colon. In this study, they found mice
lacking gene expression for TLR5, a receptor that detects bacterial flagellin, were more
susceptible to developing colitis. However, less than 30% of the TLR5 deficient mice actually
developed colitis, the majority of them failed to show any histopathological characteristics
associated with colitis. What they found in those mice was mild increases in expression of
proinflammatory genes, leading to what was eventually called, low-grade inflammation
(Chassaing,B. 2014 CT Vijay-Kumar 2007). Interestingly, the phenotype of the non colitis TLR5
deficient mice paralleled that of metabolic syndrome seen in humans. Specifically, increased
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body mass (mostly fat mass), followed by increased macrophage infiltration in adipose tissue,
which lead to a deposit of proinflammatory cytokines to the adipose tissue. The non colitis TLR5
deficient mice also developed hypertension and were more susceptible to insulin resistance and
impaired glucose tolerance. The mechanism behind the development of metabolic syndrome in
TLR5 deficient mice was hypothesized to be driven by the increased levels of proinflammatory
cytokines brought on by the inflamed state which was caused initially by alterations in the gut
microbiota.
Low bacterial diversity in the gut microbiota has been associated with low-grade
inflammation. When considering overall bacterial diversity in the gut, individuals with LGC or
less bacterial richness were characterized by pro-inflammatory bacteria, Bacteroides and Ruminococcus gnavus (Le Chatelier, E., 2013). Whereas individuals with HGC or greater
bacterial richness in the gut was associated with an increased abundance of anti-inflammatory
species, such as Faecalibacterium prausnitzii (Le Chatelier, E., 2013). The gut microbiota from children living in rural Burkina Faso who consumed a diet high in fiber and plant-based
polysaccharides also were enriched with SCFA producing bacteria, like Faecalibacterium prausnitzii , and also exhibited a lower prevalence of inflammation (De Filippo, C. 2010).
Metabolic Endotoxemia
Increased plasma levels of lipopolysaccharide (LPS), a cell wall component derived from
gram negative bacteria, is closely tied to the development of obesity (Carnahan, S., 2014)
(Shen, Jian, 2013) (Cani, P.D., , 2007). Elevated levels of circulating LPS is known as
metabolic endotoxaemia and is associated with many negative health effects, such as insulin
resistance, glucose intolerance, fasting insulinaemia, increased adipose tissue and body weight
gain (Cani, P.D., , 2007)(Carnahan, S., 2014). LPS is a product of the gut microbiota and its
plasma concentration is a major driver in inflammation and an indicator for reduced gut barrier
integrity (Pendyala, Swaroop 2012). The inflamed state observed with metabolic endotoxaemia
is characterized by increased pro-inflammatory cytokines (Carnahan, S., 2014). The
mechanism involves LPS binding to CD14, a coreceptor found on the membrane of host cells.
The endotoxin is then transferred to TLR4, resulting in the activation NF-kβ pathway (Thomson
Reuters). The NF-kβ complex is involved in the production of cytokines, which, when released
into circulation, assists in the infiltration of macrophages in adipose tissue. This influx of
macrophages further induces the NF-kβ expression of cytokines, which leads to an acceleration
in the inflammatory response (Carnahan, S., 2014).
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Reduced levels of Bifidobacteria has been associated with metabolic endotoxemia in
multiple studies (Cani, P.D., , 2007). The relative abundance of circulating LPS is associated
with alterations in the gut microbiota brought on by other factors like diet and BMI.
Gut barrier integrity
Increased levels of circulating LPS appear to be the common denominator between
obesity, inflammation and the gut microbiome. The mechanism in which metabolic endotoxemia
develops is speculated to be the result of impaired gut barrier integrity (Cani, P. D. 2009). In
healthy individuals, the intestinal epithelium acts as a continuous barrier to prevent LPS from
entering circulation;; yet this protective function can be compromised by changes in the gut
microbiota. Such changes include the reduced levels of bifidobacteria, a commensal gut
bacteria that is negatively correlated with plasma LPS and associated with enhanced gut
integrity (Cani, P. D. 2009).
The onset of metabolic endotoxemia seen with obese and diabetic mice was in
accordance with reduced abundance of tight-junction proteins (Cani, P. D. 2009). The proposed
mechanism behind this observation involves increased production of plasma cytokines, like
TNF-α, IL-1α, IL-1β and IL-6. It was proposed that this influx in pro-inflammatory cytokines
further propagated the inflammatory response, which in turn, induced modifications of both
tight-junctional proteins (Cani, P. D. 2009). In this study they found that modifications in the gut
microbiota influenced GLP-2 production, which was strongly associated with altered gut barrier
functions in a mechanism based off of GLP-2 gut peptide (Cani, P. D. 2009). This suggests that obesity promotes metabolic endotoxemia and low-grade inflammation through disruption of
tight-junction proteins involved in gut barrier function.
The gut microbiota and insulin sensitivity and glucose homeostasis
Insulin plays a major role in glucose homeostasis, for it is the only hormone in humans
capable of lowering blood glucose levels (Oh, Susan 2014). Diabetes mellitus is a metabolic
disease described by abnormally high levels of glucose in the blood (Oh, Susan 2014). The
development of type two diabetes (T2D) is closely associated to obesity and inflammation. T2D
is characterized by insulin resistance and impaired β-cell function, resulting in diminished
sensitivity of insulin in peripheral tissue, and inadequate insulin release (Oh, Susan 2014).
There were marked alterations in the gut microbiome of individuals inflicted with T2DM
compared to healthy individuals. One study found reduced levels of butyrate-producing bacteria
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Roseburia and Faecalibacterium prausnitzii in T2DM patients compared to healthy subjects (Qin, J., 2009). There was an increase in abundance of opportunistic pathogens, like
Clostridium hathewayi and Clostridium ramosum in type two diabetics (Shen, Jian, 2013 CT Qin , 2012).
Obesity is associated with insulin resistance, and has been shown to disrupt epithelial
barrier function resulting in the activation of toll-like-receptor 4 (TLR4) by a LPS-dependent
mechanism (Chassaing,B. 2014). The activation of TLR4 by LPS induces the release of
cytokines that promote insulin resistance (Chassaing,B. 2014 CT Cani 2007). The signaling of
TLR4 prompts the upregulation of inflammatory pathways, like nuclear factor-κB (NF-κB), that
are involved in the development of insulin resistance (Caricilli, Andrea M 2013).
Diet-induced changes in gut microbiota composition, function, and
metabolism
Diet and microbial diversity in the human gut
The influence of diet on the composition and activity of the gut microbiota has gained a
lot of interest as the incidences of obesity and other metabolic diseases continue to increase.
The extent of diet’s influence on composition is not fully known. Comparison of human gut
metagenomes have found that the gut microbiota can be distinguished by distinct bacterial
clusters, or enterotypes, which demonstrate high association to certain diets. These enterotypes
can be distinguished by the dominant phyla in the individual's gut microbiota (Wu, G.D., , 2011),
and recent studies suggest enterotypes could be potential indicators for disease.
Plant-based and animal-based diets
Several studies have examined the alterations in the gut microbiota brought on by
animal-based and plant-based diets. An animal-based diet is characterized as being high in fat
and protein, whereas a plant-based diet is one high in carbohydrates and fiber. Clusters of
specific gut bacteria demonstrate a strong associations with these two contrasting diets. Wu
found that these enterotypes could be distinguished by the relative abundance of Bacteroides
and Prevotella (Wu, G.D., , 2011). Bacteroidetes and Actinobacteria were associated with fat,
and carbohydrates and fiber were associated with Firmicutes and Prevotella (Wu, G.D., , 2011).
There were six different genera that differed between the two enterotypes examined in the
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study. The Prevotella enterotype included Paraprevotella, a genus within the Bacteroidetes, and Catenibacterium, a genus within Firmicutes. The Bacteroides enterotype included Alistipes and Parabacteroides, all of the Bacteroidetes phylum(Wu, G.D., , 2011). Greater consumption of
animal-based products, as seen in the western diet, was associated with the Bacteroides enterotype. This enterotype is highly associated with animal protein, various amino acids, and
saturated fat. The opposite was seen for the Prevotella enterotype, which demonstrated a high affinity for carbohydrates and simple sugars. This enterotype demonstrated a strong association
to carbohydrate-based diets, typical of plant-based diets (Wu, G.D., , 2011).
One study analyzed the gut microbiota of children living in Europe (EU) compared to
children living in a rural African village in Burkina Faso (BF), and discovered distinct differences
in enterotypes of the two populations (De Filippo, C. 2010). The european subjects consumed a
typical western diet, one high in animal protein, sugar, fat, and low in fiber. The BF subjects ate
a diet resembling that of Neolithic subsistence farmers, which unlike the European diet, was low
in fat and animal protein, and high in fiber and other plant polysaccharides (De Filippo, C. 2010).
Actinobacteria and Bacteroidetes were the dominant phyla in the BF children’s microbiota,
whereas Firmicutes and Proteobacteria were greater represented in the EU children’s
microbiota. The ratio between Firmicutes and Bacteroidetes showed that the Firmicutes were
twice as abundant in the microbiota of EU children compared to their BF peers.
Contrary to the enterotype observed in European children, the enterotype observed in
African children was characterized by the Prevotella genus (De Filippo, C. 2010). Two genera within Bacteroidetes;; Prevotella and Xylanibacter, and Treponema of the Spirochaetes were absent from the microbiota of the EU children, but present in the microbiota of the BF children.
This particular bacterial community seen exclusively in BF children are SCFA-producers. It was
speculated that the BF diet, which was rich in plant polysaccharides and low in sugar and fat,
could selectively promote the growth of SCFA-producing bacteria. The greater abundance in
SCFA-producers observed in the BF children could possibly protect them from the colonization
of potentially pathogenic microbes, like Enterobacteriaceae, Shigella, and Escherichia. Interestingly, there potential pathogens which were much more abundant in the gut microbiota
of EU children than in BF children (De Filippo, C., 2010).
Interestingly, there was a major divergence in gut microbiota composition of the two
populations that occurred when the diet shifted from breast milk to solid foods. This observation
continued to diverge ultimately leading to two different gut microbiota profiles. The BF children’s
gut microbiota was comprised of more gram negative bacteria (Bacteroidetes), whereas the EU
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Meghan McGillin January 15, 2016
children were much more abundant in gram positive bacteria (Firmicutes). This observation
nicely depicts the impact of the dietary and environmental influences that alter the
Firmicutes/Bacteroidetes (F/B) ratio (De Filippo, C. 2010). The overall bacterial diversity was
less in the microbiomes of EU children compared to BF children. De Filippo believed that the
reduced microbial diversity demonstrated the impact of a HF/HS diet on the “adaptive potential”
of the gut microbiota of children in developed societies (De Filippo, C. 2010).
There was another study that examined the short-term changes in the human gut
microbiota brought on by the animal-based and plant-based diets. It was discovered that the
animal-based diet had a greater effect on the overall gut microbial diversity than the plant-based
diet. Alterations in the subject’s gut microbiota became detectable in just 24 hours on the
selected diets, and became more prominent over time (David, A. L., 2014). The animal-based diet lead to significant changes in the relative abundance of 22 clusters after five days, whereas
only 3 clusters significantly altered in their abundance after five days on the plant-based diet
(David, A. L., 2014). They found that the animal-based diet promoted the growth of bile-tolerant
bacteria, like Alistipes, Bilophila and Bacteroides and discouraged the growth of Firmicutes involved in plant polysaccharide fermentation, like Roseburia, Eubacterium rectale, and Ruminococcus bromii .
There was an observed differences in gene expression followed the taxonomic shifts
seen with the animal-based diet compared to the plant-based diet. The animal-based diet was
associated with the increased expression of β-lactamase and genes involved in vitamin
biosynthesis and polycyclic aromatic hydrocarbons degradation, which are carcinogenic
compounds produced during the charring of meat (David, A. L., 2014). Another study examined
the short-term change induced by the two diets and found that the differences in the gut
microbiota activity reflected the diet type (David, A. L., 2014). Analysis of fecal SCFA indicated
alterations in microbial activity resulting from the different diets. Compared to the plant-based
diet, the animal-based diet produced significantly lower levels of fermented carbohydrate-based
metabolites, compensating the loss of SCFA with increased amino acids fermentation (David, A.
L., 2014).
When comparing the metagenomes of the western diet to rural African diets, it was
discovered that the westernized diet was enriched in genes associated in enzymes involved in
the degradation of amino acids and simple sugars (Hannelore, D., 2014 CT Yatsunenko
2012). Mice fed a typical diet high in sugar and fat (HF/HS) were enriched in genes associated
with glutamate metabolic pathways. It was suggested that the HF/HS microbiota has increased
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Meghan McGillin January 15, 2016
fitness for the transport and conversion of simple sugars and glycoproteins. This is based off of
the occurrence of four enzymes;; 2-dehydro-3-deoxygluconokinase, 6-phosphofructokinase,
N-acetylglucosamine-6-phosphate deacetylase and two sugar-binding proteins, that were all
present in the gut microbiome of mice fed a western diet (Hannelore, D., 2014 CT Turnbaugh ,
2008].
The high fat diet
Several studies have explored alterations in the gut microbiota brought on by a high fat
diet. Hannelore found that in addition to increased body weight gain, fasting hyperglycemia, and reduced cecal mass, mice fed a HF diet for 12-weeks also underwent significant changes in
their gut microbial composition (Hannelore, D., 2014). The Firmicutes were the dominant
phylum, making up approximately 71-98% of the total sequences. That being said, there was a
significant decrease in Ruminococcaceae of the Firmicute phylum. This decrease in Ruminococcaceae is expected as they are a major utilizer of plant polysaccharides;; a food component lacking in the experiment being described. There was an increase in Rikenellaceae, of the Bacteroidetes phylum in HF mice. Overall, there was no reported decrease in
Bacteroidetes after HF feeding. Mice fed a HF diet, in general, showed no significant change in abundance of lactobacilli compared to the control group (Hannelore, D., 2014). The HF-diet altered 19 distinct species. There was an increase in 2 Alistipes species (Hannelore, D., 2014). The majority of the analyzed species that decreased after HF feeding belonged to the
Clostridiales order (Hannelore, D., 2014). HF feeding appeared to promote two Clostridium species, and one species belonging to the Clostridium cluster XIVa (Hannelore, D., 2014).
When analyzing cecal samples of the mice fed a HF diet, it was reported that the HF diet
altered the biochemical environment and microbial activity of the gut. This study found that the
HF-diet induced changes in the biochemical fingerprints of the bacteria belonging to the
Bacteroidetes and Lachnospiraceae (Hannelore, D., 2014). The HF diet impact on the gut metaproteome activity was also analyzed. Interestingly, they reported that the majority of
proteins in the metaproteome was involved in carbohydrate metabolism. As a consequence of
this, it appeared that the gut microbiota is not equipped for adequate energy harvest for diets
where dietary fat exceeds 60% of calories needed for dietary energy intake. The gut bacteria
responded to the HF diet by reducing the expression of protein associated with carbohydrate
metabolism, and shifting the focus to amino acid metabolism (Hannelore, D., 2014). These
findings are consistent with the increased protein to carbohydrate ratio observed in HF diets
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Meghan McGillin January 15, 2016
compared to CARB diets (1:1 vs 1:3). This is also in accordance with the increased production
of branched-chain FA from leucine, isoleucine, and valine. The focus on amino acid
fermentation is consistent with previously made associations between HF feeding in humans
and protein fermentation in vitro (Hannelore, D., 2014 CT MacFarlane , 1992;; Russell , 2011).
Similar to the LGC microbiome, HF feeding led to alterations that increased oxidative stress
tolerance by increasing the activity of three enzymes;; glutaredoxin, alkyl hydroperoxide and
thioredoxin reductase (Hannelore, D., 2014 CT Xiao , 2010).
The effects of a diet high in saturated fat the development of metabolic endotoxemia was determined by comparing the LPS levels of western diet to a prudent diet (Pendyala, Swaroop
2012). The prudent diet was low in fat and high in fiber, and of equal calories to the western
diet. There were significant differences in plasma LPS levels of the eight healthy subjects over
the duration of four weeks (Pendyala, Swaroop 2012). The western-diet lead to significant
increases (71%) in plasma endotoxin levels, whereas the prudent diet resulted in a 38%
decrease in endotoxin activity. The prudent-diet also showed significant decreases in the level
of pro-inflammatory chemokines and cytokines, like TNF-α, IL-8 and in the protein MCP-1
(Pendyala, Swaroop 2012). There are striking similarities between the inflammatory response induced by the HF-diet
compared to LPS. This observation is in accordance with the belief that elevated plasma LPS
may be the molecular link between HF feeding, microbiota, and inflammation (Cani, P.D., , 2007). It’s been established that feeding mice a high fat diet can trigger an inflammatory
response (Cani, P.D., , 2007). One study found that HF feeding of mice increased levels of
pro-inflammatory cytokines, specifically, plasma IL-1α, IL-1β, and IL-6 concentrations (Cani,
P.D., , 2007). They also found increases in adipose tissue mRNA concentrations of
proinflammatory cytokines, TNF-α, and PAI-1 after HF feeding, further supporting the
association between a high fat diet and low-grade inflammation (Cani, P.D., , 2007).
The gut microbiota impact on gut integrity has been tested in previous studies. The HF
diet demonstrated diminished gut barrier function in obese and diabetic mice (Cani, P. D.
2009). It was also associated with increased plasma LPS levels and low-grade inflammation
(Cani, P. D. 2009). The increase in intestinal permeability followed alterations in the gut
microbial composition brought on by the HF-diet. Specifically the decrease in bifidobacteria, a
group of bacteria associated with reduced LPS levels and improved mucosal barrier function
(Cani, P. D. 2009). The compromised gut barrier function may be due to decreased activity of
ZO-1 and occludin, two tight-junction proteins found on the plasma membranes of host cells
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Meghan McGillin January 15, 2016
(Cani, P. D. 2009). Immunofluorescence assay performed on the intestines of
chow-fed-wild-type mice found a greater abundance localized network of ZO-1 and occludin
proteins (Cani, P. D. 2009 CT Brun P, Castagliuolo I, Leo VD, , 2007). This starkly contrasted
the reduced and discontinuous ZO-1 and occludin protein network observed in the obese
control group tissue (Cani, P. D. 2009). Tight-junction proteins mRNA was negatively correlated
with gut permeability biomarkers used in the immunofluorescence assays (Cani, P. D. 2009).
This suggest that the HF-diet promotes metabolic endotoxemia by way of increasing gut
permeability, resulting in elevated plasma LPS and low-grade inflammation.
Dietary fat type
There were significant alterations in the composition of the gut microbiota based off of
the dietary lipid type. Mice fed fish oil had increased Lactobacillus character. This particular genera is an established probiotic, marketed towards reducing inflammation and treating IBD
(Caesar, Robert 2015). There was also an observed increase in Akkermansia muciniphila, a bacterial species associated with improved gut barrier function and glucose metabolism
(Caesar, Robert 2015). Akkermansia muciniphila was negatively correlated with fat mass gain and WAT macrophage infiltration in obese mice (Caesar, Robert 2015). A similar decrease in
Akkermansia genus was observed individuals with LGC, as discussed in a previous section. The mice fed a diet high in saturated fat displayed an increase in Bilophila, as seen with the animal-based diet. Previous studies have associated Bilophila wadsworth with increased colitis (Caesar, Robert 2015). These changes demonstrate the significance of dietary fat type on the
community structure of the intestinal microbiota. This study highlighted the impact of dietary fat
on both composition and diversity of the gut microbiota (Caesar, Robert 2015).
When discussing the manifestation of metabolic diseases, the type of dietary fat appears
to significantly influence the susceptibility and development of the disease. Although the
association between fat and metabolic endotoxemia is well established, it does not consider the
effects of the type of fat being consumed. One study comparing the influence of different dietary
lipids found that mice fed a lard-based diet had higher serum levels of LPS than compared to
mice fed fish-oil, highlighting the impact of saturated fats on metabolic endotoxemia (Caesar,
Robert 2015).
Similar distinct effects of fat type appear when applying the same criticalness to
development of inflammation. One study demonstrated that lard-fed mice had increased
expression of TNF-α in both adipocytes and macrophages compared to mice fed a fish-oil-diet
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Meghan McGillin January 15, 2016
(Caesar, Robert 2015). Mice fed lard showed increased TLR4 activity (Caesar, Robert 2015).
It’s speculated that TLR4 signalling, which is associated with inflammation and insulin
resistance, is activated by saturated FA found in greater quantity in lard compared to fish oil
(Caesar, Robert 2015). The lard-based-diet showed significantly higher CCL2 levels when
compared to fish-oil diet. CCL2 is a chemokine that undergoes secretion when activated by TLR
ligands. The overexpression of CCL2 resulted in white adipose tissue (WAT) inflammation and
insulin resistance (Caesar, Robert 2015). In this particular study, Caeser demonstrated CCL2 vitalness in WAT macrophage infiltration, thus fortifying the link between the gut microbiota to
WAT inflammation (Caesar, Robert 2015). All of these finding highlight the impact of fat type on the gut microbiota and the development of low-grade inflammation.
HF-feeding reported significant increase in fasting insulinaemia and glucose intolerance
in mice (Cani, P.D., 2007). Diabetic individuals fed a HF-diet were enriched with Alistipes (Hannelore, D., 2014 CT Qin , 2012). This is consistent with previous studies that Alistipes with HF diets. The HF diet appeared to interfere with glucose-induced insulin secretion, which was
severely reduced in mice fed a HF diet. Cani et al. noted a positive correlation with insulin resistance and plasma endotoxin levels (Cani, P.D., , 2007). Similarly, there were significantly
higher plasma endotoxins levels and inflammatory markers, like TNF-α, in obese and diabetic
mice (Cani, P.D., , 2007 CT Brun ). The cytokine, TNF-α, disrupts insulin sensitivity by
phosphorylating serine residue substrate (IRS-1) from the insulin receptor, leading to its
inactivation (Cani, Patrice D 2009). The HF-diet was associated with greater levels of ceramide
(N-acylsphingosine) in cecal samples of mice. Ceramide is a fatty acid component of cell
membrane and have been associated in diet-induced insulin resistance (Hannelore, D., 2014
CT Longato , 2011).
Potential treatments
Prebiotics
Prebiotics are nondigestible carbohydrates that are fermented by the gut microbiota
(Carnahan, S., 2014). The criteria for prebiotics requires them to tolerate gastric acidity,
withstand host enzymes, and avoid absorption in the upper gastrointestinal tract while
selectively promoting the growth of beneficial gut bacteria (Carnahan, S., 2014). For example,
insulin and fructooligosaccharides (FOS) are two well studied inulin-type-fructan (ITF) prebiotics,
20
Meghan McGillin January 15, 2016
that are effective in stimulating growth of health-promoting genera like Bifidobacterium and Lactobacillus (Cani, Patrice D 2009). The majority of studies conducted on prebiotics focus on enriching the bifidobacterium genus which are considered beneficial to human health (Hildebrandt, Marie A 2009). Prebiotics counter-acted diet induced metabolic endotoxemia by
promoting the Bifidobacteria (Cani, Patrice D 2009). Prebiotic treatment normalized low-grade
inflammation by decreasing metabolic endotoxemia through reduced plasma LPS. This
decreased the amount of proinflammatory cytokines in circulation and in the tissue. There was
an improvement in insulin sensitivity and steatosis from the prebiotic treatment (Cani, Patrice D
2009).
Recently, a lot of interest in treatment and prevention of disease through targeted
modification in the gut microbiota by prebiotic supplements.The treatment potential of
dietary-fiber prebiotics include improved gut barrier function and host immunity, reduced
pathogenic bacteria, and enhanced SCFA production (Slavin, J., 2013). Growing evidence is
depicting prebiotics as potential treatment for metabolic syndrome and metabolic endotoxemia.
Prebiotics and gut microbial composition
Prebiotics can alter the gut microbiota by selectively promoting the growth of a specific
bacteria, altering the composition and diversity of the gut. There were significant differences in
the bacterial profile of the gut of obese mice fed a dietary fiber prebiotic compared the obese
microbiome standard fed a standard chow diet (Geurts, L, , 2013). The effects of the HF diet
appear to be blunted by probiotics. The HF-diet showed to significantly decrease the
bifidobacteria content in the gut of humans and mice(Cani, P.D., , 2007). Supplementation of
the prebiotic oligofructose [OFS] to a HF-diet restored the quantities of bifidobacteria in mice (Turnbaugh, P. J. 2009)]. Inulin-type-fructans (ITF) and arabinoxylan oligosaccharides (AXOS) also increased bifidobacteria levels (Schwiertz, A., , 2010). The increase in bifidobacteria observed with ITF treatment appeared to be at the expense of the Bacteroides (Geurts, L, , 2013).
ITF showed to increase Firmicutes and Actinobacteria (Dewulf, E.M. 2012). The increase
in Firmicutes attributed to increases in Bacilli and Clostridium clusters IV and XVI. Bacilli are negatively associated with LPS levels (Dewulf, E.M. 2012). ITF supplementation lead to
reductions in two bacteria involved in fat metabolism, Propionibacterium and Bacteroides vulgatus (Geurts, L, , 2013) (Wu, G.D., , 2011). ITF increased Faecalibacterium prausnitzii , a bacteria that is negatively correlated with metabolic endotoxemia (Schwiertz, A., , 2010).
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Meghan McGillin January 15, 2016
Prebiotics effects on metabolic endotoxemia
Prebiotics counter-acted diet induced metabolic endotoxemia by promoting bacteria that
is negatively associated with circulating LPS (Cani, Patrice D 2009). ITF-treatment increased
Faecalibacterium prausnitzii , a bacteria that is counteracts metabolic endotoxemia. Supplementation of OFS to HF diet normalized plasma LPS
levels (Cani, P.D., , 2007). The prebiotic treatment
counteracted metabolic endotoxemia by reducing the level of
circulating endotoxins. This reduced the amount of
proinflammatory cytokines in circulation and was followed by
improved insulin sensitivity and reduced inflammation (Cani,
Patrice D 2009).
Prebiotics effects on gut permeability
Prebiotic feeding improved the tight-junction integrity of the
epithelial cells lining the intestines (Cani, P. D. 2009)]. Obese
mice treated with prebiotics had greater abundance of ZO-1
and occludin proteins localized along the host cell membrane
compared to obese mice (Cani, P. D. 2009). Prebiotic-fed
mice had lower level of TNF-α, IL-1β, IL-1α and IL-6, all
cytokines known to promote tight-junction disruption (Cani, P.
D. 2009).
One possible mechanism behind prebiotics protective
effect on gut barrier permeability is by the promotion of
Bifidobacterium species (Cani, P. D. 2009). Unlike other bacteria, Bifidobacterium doesn’t degrade intestinal mucus
glycoproteins, and improve gut barrier integrity (Cani, P. D. 2009). Bifidobacterium promote healthy microvilli and are associated with thick mucosal layer in the intestine
(Cani, P. D. 2009).
Obese mice administered a dietary-fiber prebiotic had increased proglucagon mRNA in
their intestine (Cani, P. D. 2009). The prebiotic treatment induced alterations in the gut
microbiota composition, a shift that promoted GLP-1 and GLP-2 synthesis. Gut peptide
hormones, GLP-1 and GLP-2 are associated with increased satiety and improved mucosal
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Meghan McGillin January 15, 2016
barrier function, respectively (Cani, P. D. 2009). The improved gut barrier observed with
prebiotic treat was correlated to the lower portal plasma LPS levels and inflammation (Cani, P.
D. 2009) (Figure 3.).
Prebiotics effects on inflammation
Prebiotic supplementation has been shown to effectively abate inflammation through
activation of G-coupled protein receptor GPR43. Prebiotics increase levels of short chain
carboxylic acids in the colon and circulating in the plasma, which activates GPR43. Activation of
GPR43 results in a decrease in lipolysis and free fatty acids in plasma. The reduction of free
fatty acids decrease their interaction with membrane TLR, which subdue the inflammatory
response.
Supplementation of AXOS is believed to discouraged metabolic endotoxemia through
increased production of anti-inflammatory cytokine in serum ( Neyrinck, AM., , 2012). It is
speculated that the prebiotic increases expression of IL-10 and reduces macrophage infiltration
in adipose tissue ( Neyrinck, AM., , 2012).
Another study found that treatment of OFS to mice restored the increased levels of
pro-inflammatory cytokines IL-1α and IL-6 that resulted from a HF feeding (Cani, P.D., , 2007).
The increased mRNA concentrations of TNF-α, and PAI-1(Serpine1) in adipose tissue reported with HF feeding was normalized after OFS supplementation (Cani, P.D., , 2007).
Prebiotics and insulin sensitivity
Supplementation of OFS to the HF-diet appeared to reverse the glucose intolerance
brought on by the HF-diet in mice. Additionally, glucose-induced insulin secretion and normal
fasting plasma insulin levels also improved after administration of the OFS prebiotic to the
HF-diet (Cani, P.D., , 2007). AXOS supplementation demonstrated improved
fasting-hyperinsulinemia and HOMA-IR brought on by a HF diet ( Neyrinck, AM., , 2012).
Prebiotics effects on satiety and energy intake
Studies comparing lean and obese mice establish the gut microbiota influence on host
energy balance. Promoting weight loss through directed changes in the gut microbiota brought
on through prebiotic treatment is appearing as an attractive method for the treatment of obesity.
One study found that fructooligosaccharides (FOS) supplementation reduced energy intake and body weight in overweight and obese subjects by suppressing ghrelin levels and
23
Meghan McGillin January 15, 2016
enhancing PYY levels (Slavin, J., 2013). Similar results were found with supplementation of
AXOS to a high fat diet, which increased activity in satieogenic peptides GLP-1 and PYY and
blunted body weight gain, fat mass development as a result ( Neyrinck, AM., , 2012).
The 2.5-fold increase in body weight gain and 3- to 4-fold in fat mass after HF-feeding in
mice was significantly reduced following OFS supplementation (Cani, P.D., , 2007). Additionally,
HF-OFS mice resulted in decreased energy intake. OFS prebiotic also appeared to stimulate
GLP-1 production (Cani, P.D., , 2007).
Conclusion
Obesity is a disease associated with a cluster of several metabolic disorders like insulin
resistance, hyperglycemia, and hyperlipidemia (Chassaing,B. 2014). This cluster of metabolic
disorders is known as metabolic syndrome and is related to increased risk of diabetes,
cardiovascular diseases, and liver dysfunction (Cani, Patrice D 2009). The gut microbiota has
an established role in the development of obesity. Obesity is associated with changes in the gut
microbiota and is shown to reduced bacterial diversity and altered metabolic pathways (Slavin,
J., 2013). Gut dysbiosis has been characterized by a shift from SCFA producing microbes, like
bifidobacteria, to opportunistic pathogens (Qin, Junjie 2012). Reduced levels of bifidobacteria
has been associated with metabolic endotoxemia in multiple studies (Cani, P.D. 2007).
Elevated levels of circulating LPS is known as metabolic endotoxaemia and is
associated with many negative health effects, such as insulin resistance, fasting insulinaemia,
increased adipose tissue and body weight gain (Cani, P.D., , 2007, Carnahan, S., 2014). LPS is
a product of the gut microbiota and its plasma concentration is a major driver in inflammation
and an indicator for reduced gut barrier integrity (Pendyala, S. 2012). The inflamed state
observed with metabolic endotoxaemia is characterized by increased pro-inflammatory
cytokines (Pendyala, Swaroop 2012). It was proposed that the HF-diet promotes metabolic
endotoxemia by way of increasing gut permeability, resulting in elevated plasma LPS and
low-grade inflammation.
Prebiotic intervention appeared to improve gut barrier function, reduce metabolic
endotoxemia and promote beneficial gut bacteria. It appears that alterations in the gut
microbiota with prebiotics may participate in the control of the development of metabolic
diseases associated with obesity (Cani, Patrice D 2009). For this reason, it would be useful to
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Meghan McGillin January 15, 2016
further explore the potential of alterations in the gut microbiota that discourage the harmful
effect of the high-fat or obesity-induced metabolic diseases.
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Meghan McGillin January 15, 2016
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