Gut Microbiota and Obesity: Comparison
Please note this is a comparison between Version 3 by Ludovico Abenavoli and Version 2 by Peter Tang.

Obesity is one of the most prevalent human health problems. Research from the last 30 ydearcades has clarified the role of the imbalance between energy intake and expenditure, unhealthy lifestyle, and genetic variability in the development of obesity. The composition and metabolic functions of gut microbiota have been proposed as being able to affect obesity development.

  • metabolism
  • gut microbiota
  • dysbiosis
  • obesity

1. Introduction

Changes in dietary habits and the increased availability of high-caloric foods have made overweightness and obesity some of the most serious health issues of our era. In 2016, the World Health Organization (WHO) estimated that 39% of individuals older than 18 were overweight, and the worldwide prevalence of obesity almost tripled between 1975 and 2016. It has been reported that nearly 2.8 million deaths annually are a consequence of overweight and obesity-associated conditions: blood hypertension, dyslipidemia, and insulin resistance lead to an increased risk of coronary heart disease, ischemic stroke, type 2 diabetes mellitus, as well as cancer development [1]. Obesity is caused by an imbalance between energy intake and expenditure: increasing the intake of fattening food and other lifestyle changes pushed its prevalence to epidemic proportions. On the other hand, several works have proven a significant genetic role in determining the obesity risk [2][3][4]. On top of the genetic factors clearly contributing to determining body weight and fat mass, the drastic boost in obesity prevalence has also suggested a prominent contribution in the development and maintenance of obesity caused by environmental elements.
In recent years, changes in bacterial strains, hosted in the human intestine, were proposed to have a causative role in obesity [3][5][6]. Intriguingly, the microbiome is a fingerprint of both the environment and human heritable genetic material [7]. In fact, it has been proposed that the genetic pool of the microbiota represents an extension of the nuclear and mitochondrial genomes, leading to the definition of the meta-genome to describe such extension [8].

2. Historical and Current Perspectives

The complex interaction involving the diet, intestinal microbiota, and human host has been investigated for over a century. Acceptance of the germ theory of disease development led to an original classification of a number of human disorders as caused by microbes, including conditions that were eventually going to be reconsidered as non-infectious. The initial proponent of such theories was the immunologist Elie Metchnikoff, considered by many as the father of probiotics. In his 1907 article, ‘‘Essais optimistes’’, Metchnikoff proposed a causative link between microbes and aging mechanisms and suggested a central role in senescence progression for compounds resulting from microbial intestinal putrefaction [9]. Furthermore, he firstly noted the beneficial effect of consuming fermented food on human health. Therefore, he hypothesized that fermented foods could avoid intestinal proteins putrefaction and thus senility.
Over the past century, several studies have demonstrated the influence of gut microbiota on the pathophysiology of many extra-intestinal conditions. More specifically, the exhaustive description of human microbiota’s relationship with health and disease has become the major challenge of research in the twenty-first century [10]. In recent years, the number of annual publications on this topic has almost quadrupled, as compared to 2005, when Eckburg et al. published the first large-scale gut metagenomic study that, starting from genetic fragments, allowed the reconstruction of entire genomic germ profiles [11].
Gut microbiota is the most complex ecosystem in nature since it harbors large bacterial populations in the intestine and colon, with around 1011–1012 microorganisms/gram of the intestinal content and mostly are anaerobes (95% of the total organisms) [12]. The first studies on the composition of intestinal microbiota were based on microscopic observation and culture-based methods, and showed as predominant cultivable species Bacteroides spp., Eubacterium spp., Bifidobacterium spp., Peptostreptoccocus spp., Fusobacterium spp., Ruminococcus spp., Clostridium spp. and Lactobacillus spp. [13]. Subsequently, Gill et al. obtained the first metagenomic sequencing of the distal gut microbiome in two subjects, showing microbial genomic and genetic diversity and identifying some of the distinctive features of this subpopulation of microbiome [14].
To date, genetic tests have led to the generation of large new datasets on gut microbiota, including information on the composition and functional properties of greater numbers of microbial strains. In this frame, US National Institutes of Health (NIH), founded the Human Microbiome Project (HMP) Consortium. HMP follows into the footsteps of the Human Genome Project, being constituted by multiple projects that bring together scientific experts worldwide to explore microbial communities to characterize the composition of the normal microbiome and the relationship with human organism [15]. Characterizing the microbial genes has led to the description of a human microbiome core [16]. It is established by a set of genes shared by microbes colonizing most habitats in humans. Interestingly, core genes present in a limited habitat and in a smaller set of humans can be modified by a combination of factors, such as host genotype, immune system physiology, disease state, lifestyle, diet, and also the presence of other microorganisms. This core microbiome is not present in shared big microbial populations but is involved in several essential metabolic functions for the bugs hosted in our intestine [17].

3. Gut Environment: Microbiota Evolutionary Development

The microbes detected in the human intestinal tract can be divided into three domains based on molecular phylogeny (i.e., 16S ribosomal ribonucleic acid [rRNA] sequence similarities and differences): eukarya, bacteria, and archaea. Eukarya includes organisms whose cells contain complex structures surrounded by membranes, primarily the nucleus. On the other hand, bacteria are the predominant strains of the gut microbiota (Table 1). About 90% of the fecal bacteria belong to two of the major phylogenetic lineages: Firmicutes and Bacteroidetes. However, the gastrointestinal tract of adult humans has been estimated to contain approximately 500–1000 distinct bacterial species [16]. In addition, Methanobrevibacter smithii is the dominant methanogenic archaeon species within the microbes in our digestive system [11].
Table 1. Main bacteria and Archaea in the human gut microbiota.

Domain

Phylum

Class

Order

Family

Genus

Clostridia [23]. A crucial determinant of gut microbiota development is the infant feeding. Several studies have shown different qualitative compositions of the bacterial flora in the breastfed subjects compared to the artificially fed ones. In breastfed infants, Bifidobacterium prevails (60%–90% of the fecal flora) vs. less than 1% of lactic-acid bacteria. In addition, there is a decrease in pH and inhibition of putrefactive flora growth with advantage for fermentative one development. This microbial switch improves intestinal digestive and absorptive functions of nutrients, in particular vitamins, with a consensual stimulation of immune system, namely gastrointestinal associated immune system (GALT), that reduces the risk of contracting allergies [24]. After the first six months of life, the weaning period begins with an enlarged diet composition and the introduction of the solid foods that leads to a further differentiation of microorganisms present in adults [25]. More specifically, these bugs belong to Firmicutes and Bacteroidetes (26). In the first year of life, levels of Escherichia coli and Enterococci range between 106 and 108 CFU/g of feces—there is a reduction in Clostridia and an increase in anaerobic flora, that undergoes a gradual diversification [24][25]. Interestingly, the initial colonization of the intestinal tract by microbes is important for defining the bacterial flora of the adult age. In fact, once the adult microbiota is constituted remains stable, with the exception of possible variations, following several factors such as a change in eating habits or the onset of diseases [26]. In adolescent children, a significantly higher representation of genera Bifidobacterium and Clostridium has been reported, as compared to adult levels [25][26]. A decline in the microbial abundance and species diversity, has been reported in the elderly, with lower levels of bifidobacteria and higher levels of Enterobacteriaceae [27].

4. Gut Microbiota Distribution and Its Relationship with Obesity

Differences in composition have been noticed in the microbial populations along the gastrointestinal tract [28]. These differences add a horizontal stratification, with the presence of diverse microbial communities in the intestinal lumen, in the layer of mucus of the intestinal crypts and directly adherent to the epithelial cells. In quantitative terms, esophagus and stomach carry the lowest bacterial load and the predominant cultivable bacteria are facultative anaerobes that derive from the oral cavity (e.g., Streptococci and Lactobacilli). Bacterial load increases progressively along the intestinal tract as the redox potential drops. Moreover, the genus Streptococcus is the most represented among the microbiota of jejunum [28]. However, a significantly higher population of bacteria (108–109/g of feces) characterizes specifically the ileo-cecal area. In fact, the small intestine is enriched by the subgroup Bacillus bacteria (phylum Firmicutes, mainly Streptococcaceae, corresponding to 23% of the genomic sequences identified compared with 5% in the colon). In addition, up to 8% of genomic sequences belong to members of the phylum Actinobacteria and, in particular, to the subgroups Actinomycinaeae and Corynebacteriaceae. In the small intestine, a small percentage Bacteroidetes and Lachnospiraceae has been identified vs. their concentration in the colon [29]. The largest number of bacteria and the vastest microbial diversity (1011–1012/mL of luminal contents) in human gut have been observed in the distal section of the ileum and the colon. The greatest portion is composed by strictly anaerobic, often non-spore-forming, mainly Gram-positive (Bacteroides and Clostridium). There are also facultative anaerobes such as Lactobacillus, Enterococcus and Enterobacteriaceae [29][30]. This substantially higher concentration of bacteria is due to a slower motility characterized by anti-peristaltic contractions that allow retention of colonic content for long periods. In addition, the intestinal pH is buffered through the secretion of bicarbonate that makes the environment more favorable to the bacterial colonization [31].
The hypothesis that the intestinal microbiota can constitute to a relevant environmental factor in the pathogenesis of obesity has led to the investigation of gut microbial communities in overweight individuals. The first evidence indicating an association between obesity and intestinal microbes was produced by studies applying DNA sequencing methods on a large scale to allow the screening of the entire gut microbiome. The first link between gut microbial environment and obesity was hypothesized by Ley et al. that analyzed the gut microbiota of leptin-deficient mice at major phyla level [32]. Results from 16S rRNA gene sequencing in mouse models indicated as the two most abundant bacterial phyla were Firmicutes (60%–80%) and Bacteroidetes (20%–40%), and showed how mice homozygous for an aberrant leptin gene ob/ob, carried a different proportion of bacteria in the ceca compared to lean wild-type (+/+) or heterozygous (ob/+) mice. In particular, the ob/ob mice had a 50% decrease in the population of Bacteroidetes and a proportional increase in Firmicutes (p < 0.05).
Similarly, Turnbaugh et al. published a study on mouse models using the newer shotgun metagenomic sequencing technique on cecal microbial DNA (ob/ob, ob/+ and +/+) [33]. This study confirmed the increased ratio of Firmicutes vs. Bacteroidetes in obese mice, as compared to lean ones. Moreover, ob/ob mice had a higher proportion of Archaea within the cecal gut microbial communities. There was also a higher representation of genes involved in energy extraction from food in the obese host microbiota compared to lean host microbes. Works in another mammalian models noticed a lower abundance of Bacteroidetes associated with obesity [34][35]. Other works have associated mouse obesity with specific bacteria, in particular Halomonas and Sphingomonas, and the reduction in the Bifidobacteria number [36]. In order to assess if microbial communities can similarly affect weight gain or loss in humans, several studies have investigated various cohorts of obese and lean individuals, but the results have not always been consistent (Table 2).
Table 2. Gut microbial population and obesity: relationship, causality and effects in human studies.

Source

Study Subjects

Comparison

No. of Subjects

Methods

Community Measured

Major Findings

Bacteria

Bacteroidetes

Ley et al. [32]

Human adults

Bacteroidia

Bacteroidales

Obese vs. controls

Bacteroidacee

12 obese, 2 normal weight

Bacteroides

16S rRNA sequencing

Bacteroidetes Firmicutes

Significantly reduced level of Bacteroidetes in obese subjects.

 

Collado et al.

 

[

   

37]

Prevotellacee

Prevotella

Pregnant women

Obese vs. lean pregnant

18 overweight, 36 normal weight pregnant women

FCM-FISH qPCR

Bacteroides Bifidobacteria Staphylococcus aureus

High numbers of Bacteroides group and S.aureus in the overweight pregnant women.

         

Xylanibacter

Zhang et al. [38]

Human adults

Obese vs. control vs. after RYGB

3 normal weight, 3 obese, 3 post-gastric bypass

16S Pyrosequencing qPCR

Firmicutes Bacteroidetes Proteobacteria Actinobacteria Fusobacteria Verrucomicrobia

More Bacteroidetes in obese subjects (not significant). Prevotellacee (phylum Bacteroidetes) and Coriobacteriacee (phylum Actinobacteria) increased in obese. Significant increase in Methanobacteriales in obese subjects.

   

Kalliomaki et al. [39]

 

Human children

Overweight/obese Normal weight

 

25 overweight: 7 obese, 24 normal weight

Rikenellacee

FISH

Rikenella

Bifidobacteria Lactobacilli Clostridia Staphylococcus aureus

Lower number of bifidobacteria and greaternumber of

S. aureus

predict Obese/overweight phenotype.

 

Duncan et al. [40]

Firmicutes

Human male

Clostridia

Obese vs. normal weight

Clostridiales

15 obese, 14 lean

Clostridiacee

Clostridium

FISH

Bacteroides Firmicutes E.rectale/C. coccoides

No differences in Bacteroides level in obese and normal weight subjects. Significant diet-dependent reduction in Eubacterium rectale/C. coccoides (phylum Firmicutes) levels in obese subjects.

     

Turnbaugh et al. [33]

Human twins

 

Obese and normal twins, mothers

Ruminococcae

154 subjects: 31 monozygotic twin pairs, 23 dizygotic twin pairs, 46 mothers

Faecalibacterium

16S pyrosequencing V2 and V6 variable region

Bacteroidetes Firmicutes Proteobacteria Actinobacteria

Significantly reduced levels of Bacteroidetes in obese and increased level of Actinobacteria. Nearly half of the lean-enriched genes are from Bacteroidetes.

     

Armougom et al. [41]

 

Human adults

Anorexic, normal weight and obese

 

Ruminococcus

20 normal weight, 20 obese, 9 anorexic

qPCR

Lactobacillus M. smithii Bacteroidetes Firmicutes

Significantly reduced levels of Bacteroidetes in obese subjects versus healthy subjects (p < 0.01). Firmicutes data are similar in the three categories. Significantly higher levels of Lactobacillus. Increase of M. smithii in anorexic subjects (p < 0.05).

       

Mai et al. [42]

Human adults

Peptostreptococcae

Peptostreptococcus

African American and Caucasian American

98 subjects

FISH qPCR

Bacteroidetes Clostridia cluster XIV (Firmicutes)

No significant difference in Bacteroidetes numbers between obese and normal-weight subjects.

     

Nadal et al. [

 

43

 

Fusibacter

]

Human adolescents

Before and after 10 weeks of calorie-restricted diet

39 overweight adolescents

FISH

Bacteroidetes/Prevotella Bifidobacterium C. histolyticum E. rectale/C. coccoides Lactobacillus/En-terococcus

Greater weight loss after a multidisciplinary treatment program associated with: significant reduction of Eubacterium rectale, Clostridium coccoides and C. histolyticum; significant increase in Bacteroides/Prevotella.

       

Santacruz et al. [44]

Human adolescents

Eubacteriacee

Eubacterium

Before and after diet and exercise for 10 weeks

36 obese adolescents

qPCR

Bacteroides fragilis Lactobacillus C. coccoides C. leptum Bifidobacterium Escherichia coli

After an obese group submitted to a weight program lost >4 Kg: significant reduction in C.coccoides; increase in the Bacteroides fragilis and Lactobacillus group.

     

Schwiertz et al. [45]

Human adults

 

Obese vs. overweight vs.normal weight

98 subjects: 30 lean, 35 overweight, 33 obese subjects

Veillonellacee

qPCR

Veillonella

Firmicutes Bacteroidetes

Bifidobacteria

Significantly increased level of Bacteroidetes in obese subjects and decreased level of Firmicutes. Significant decrease in

Bifidobacteria and Methanobrevibacter spp. in obese subjects.

 

Balamurugan et al. [46

     

]

Human children

Lachnospiraceae

Obese vs. non obese

15 obese, 13 normal weight

qPCR

Roseburia

Bacteroidetes

Bifidobacterium Lactobacillus acidophilus E. rectale F. prausntzi

No significant difference in

Bacteroides/Prevotella and Bifidobacterium spp. Significant increase of Fecalibacterium prausntzi levels (Firmicutes species) in obese subjects.

   

Santacruz et al. [

Bacilli

47]

Bacillales

Bacillaceae

Bacillus

Pregnant women

Overweight/obese pregnant women vs. normal weight women

16 overweight pregnant, 34 normal weight pregnant women

qPCR

Bifidobacterium Lactobacilli Bacteroidetes Escherichia coli Staphilococcus

Significant reduction of Bifidobacterium and Bacteroides numbers in obese pregnant women. Increased levels of Staphilococcus and E. coli in overweight women.

     

Abdallah Ismail et al. [48]

 

Human children and adults

Obese vs. normal weight

Lysteriaceae

Lysteria

79 subjects: 51 obese, 28 normal weight

qPCR

Bacteroidetes Firmicutes

Significantly increased distribution of Bacteroidetes and Firmicutes in the obese group.

       

Staphylococcaceae

Furet et al. [49]

Obese after RYGB

Obese subjects enrolled in a bariatric-surgery program

30 obese after RYGB, 13 lean

qPCR

Staphylococcus

Bacteroides/Prevotella E. Coli F. Prausnitzii Bifidobacterium Lactobacilli

Bacteroides

/

Prevotella group was lower in obese subjects than in control subjects and increased after 3 months. Escherichia coli species after 3 months and inversely correlated with fat mass and leptin levels. F. prausnitzii species was lower in subjects with diabetes and associated negatively with inflammatory markers.

   
 

Zuo et al. [50]

 

Human adults

Obese vs. normal weight

Pasteuriaceae

Pasteuria

52 obese, 52 normal weight

Culture

Bacteroides Clostridium perfringens

Significantly reduced levels of Clostridium perfringens and Bacteroides in obese population.

 

Payne et al. [

 

51]

Human children

 

Obese vs. normal weight children

Lactobacillales

Lactobacillaceae

30 subjects: 15 obese, 15 normal weight

qPCR TGGE

Lactobacillus

Bacteroides Firmicutes

Roseburia/E.rectale Lactobacillus Bifidobacterium Enterobacteriacee F. prausnitzii

No significant differences for any population tested between obese and normal weight children.

       

Vael et al. [52]

Enterococcaceae

Enterococcus

Human children

Children at 3, 26 and 52 weeks of age

138 subjects

Culture

Bacteroides fragilis Bifidobacterium Lactobacillus Enterobacteriacea Staphylococcus Clostridium

High intestinal Bacteroides fragilis and low Staphylococcus concentrations in infants between the age of 3 weeks and 1 year are associated with a higher risk of obesity later in life.

       

Patil et al. [53]

Streptococcaceae

Human adults

Lean, normal, obese and surgically-treated obese subjects

20 subjects: 5 lean, 5 normal, 5 obese, 5 surgically treated

qPCR

Streptococcus

Bacteroidetes Firmicutes

Bacteroides

are prominent among the obese subjects.

 

Zupancic et al. [54

Actinobacteria

]

Actinobacteria

Human adults

Stratified by BMI

Bifidobacteriales

Bifidobacteriaceae

Bifidobacterium

310 adult subjects

16S rRNA pyrosequencing V1-V3

Bacteroidetes spp. Firmicutes spp.

Bacteroidetes/ Firmicutes ratio is not associated with BMI or metabolic syndrome traits.

         

Xu et al. [55]

Human children

Normal, overweight and obese subjects

175 children: 91 normal, 62 overweight, 22 obese

qPCR

Gardnerella

Bacteroidetes Firmicutes

Reduction of Bacteroidetes level in obese group (

p

= 0.002).No differences in Firmicutes level between lean and obese children (p = 0.628).

     

Actinomycetales

Actinomycetaceae

Actynomices

Munukka et al. [56]

Premenopausal women

Overweight/obese women with and without metabolic disorders

85 premenopausal women

FISH

Bacteroidetes Bifidobacterium spp. Enterobacteriacee E. rectale/C. coccoides F. prausnitzii

Proportion of E. rectale/C. coccoides is higher in MDG women compared to NMDG and NWG women. Certain members of E. rectale/C. coccoides are associated with obesity related metabolic disease, not obesity per se.

 

Proteobacteria

Million et al. [57]

Human adults

Deltaproteobacteria

Obese vs. normal weight

Desulfobacteriales

Desulfobulbaceae

115 subjects: 68 obese, 47 controls

Desulfovibrio

Culture (

Lactobacillus

spp.) qPCR

Lactobacillus spp. Bacteroidetes Firmicutes M. smithii

L. paracasei is significantly associated with lean status. L. reuteri, L. gasseri are significantly associated with obesity. M. smithii is less abundant in human obesity. Bacteroidetes are lower in obeses (not significant, p = 0.25)

   

Gammaproteobacteria

Enterobacteriales

Simões et al. [58]

Human twins

Enterobacteriaceae

Obese, overweight, normal weight

20 twin pairs

qPCR DGGE

Escherichia

Eubacterium rectale group Clostridium leptum group Lactobacillus group Bacteroides

spp.

The abundance and diversity of the bacterial groups not differ between normal weight, overweight and obese individuals. Diet plays an important role in the modulation of the stool microbiota, in particular Bacteroides spp. and Bifidobacteria

         

Ferrer et al. [59]

Human adolescents

Enterobacter

         

Klebsiella

Lean and obese subjects

         

Proteus

1 obese, 1 lean individual

qPCR

Bacteroidetes Firmicutes Actinobacteria Proteobacteria

Lower Bacteroidetes abundance and greater frequencies of Clostridia (Firmicutes spp.) in obese subjects.

Million et al. [45]

Humans adults

Obese, overweight, lean and anorexic subjects

263 individuals: 134 obese, 38 overweight, 76 lean, 15 anorexic

qPCR

Bacteroidetes Firmicutes, M. smithii Lactobacillus spp. E.coli

L. reuterii was positively correlated with BMI. M. smithii was negatively associated with BMI. Bacteroidetes was not correlated with BMI.

Bervoets et al. [60]

Human children

Obese, overweight and morbidly obese (O/O group) and normal-weight, thinness (C group)

26 overweight/obese, 27 lean

qPCR Mass spectrometry

Bacteroides Bifidobacterium Clostridium Staphylococcus Lactobacillus

Higher concentration of Lactobacillus spp. in obese microbiota. Increased concentration of Firmicutes and decreased concentration of Bacteroidetes in obese children.

   

Epsilonproteobacteria

Tims et al. [61]

Campylobacteriales

Campylobacteriaceae

Campylobacter

Human twins

Concordant and discordant BMI twin pairs

40 subjects: 20 discordant BMI 20 concordant BMI twin pairs

HITChip phylogenetic microarrays

Bacteroidetes Firmicutes Actinobacteria at phylotype level

MZ twins have more similar GI microbiota compared with unrelated subject. Inverse correlation between Clostridium cluster IV diversity and BMI; positive correllation between

       

Helycobacteriaceae

Helycobacter

 

Fusobacteria

Fusobacteria

Fusobacteriales

Fusobacteriaceae

Fusobacterium

 

Verrucomicrobia

Verrucomicrobiae

Verrucomicrobiales

Verrucomicrobiaceae

Verrucomicrobium

 

Synergistetes

Synergistia

Synergistales

Synergistaceae

Synergistes

 

Spirochaetes

Spirochaetes

Spirochaetales

Spirochaetaceae

Spirochaeta

         

Treponema

 

Cyanobacteria

Cyanobacteria

     

Archaea

Euryarchaeota

Methanobacteria

Methanobacteriales

Methanobacteriaceae

Methanobrevibacter

         

Methanobacterium

         

Methanosphaera

More specifically, the subclass distribution of gut microbiota are composed by: Bacteroidetes (23%) that comprise the genus Bacteroides, Firmicutes (64%) that includes Bacilli, Clostridia and Mollicutes (the majority of microorganisms in this phylum are closely related to genus Streptococcus and Clostridium); Proteobacteria (8%), Gram-negative bacteria such as Escherichia coli and Helicobacter pylori; Fusobacteria, Verrucomicrobia and Actinobacteria (3%) that include species such as Bifidobacterium [18][19][20]. Over 20 genera of Bacteroidetes have been described, with Bacteroidales being the most studied one, in particular the genus Bacteroides. Firmicutes are Gram-positive bacteria, divided into three classes: Clostridia, Bacilli, and Mollicutes (Table 1).
Childhood is characterized by the microbial plasticity that resembles the physiologic process of progressive gut colonization by microbes over time. The colonization of the digestive apparatus begins at birth and is different from individual to individual [21]. This process recognizes three steps: from birth to weaning, from weaning to a normal diet assumption that is characteristic of adulthood, and elderly. More particularly, at birth, the human gut is essentially free from bacteria, but, immediately after delivery, the intestine begins to be populated by a series of microorganisms—this process is influenced by exogenous and endogenous factors (e.g., mother’s vaginal and fecal microbiota, environment, skin bacterial flora) [22]. During the first 12–24 h of extra-uterine life, gut colonists are especially facultative anaerobic bacteria such as Escherichia coli, Enterococci and Streptococci [22]. Subsequently, from the second to the third day, these bacteria generate an anaerobic environment promoting the growth of obligate anaerobes (Lactobacilli and mainly Bifidobacteria), perhaps through reduction of the redox environment potential (low oxygen concentration). Within two weeks, this bacterial population expands from 108 to 1010 per gram of feces and establishes itself as species Bacteroides and

Eubacterium ventriosum/Roseburia intestinalis

and BMI. No consistent Bacteroidetes/Firmicutes ratio were observed in pair-wise comparison of lower- and higher-BMI siblings.

5. MFuture Pechanism Linking the Microbiota to Obrspectivesity

Thes debate shreds of evidence altogether have confirmed a statistical associon the significance of the correlation between obesity and gut microbiota peculiar composition. A number of mechanisms has been proposed forimbalance and obesity is one of the hottest topics in medicine. Although several molecular pathways have widened the view on the causative association between gut microbiota causative action inalterations and obesity physiopathology. In fact, gut commensal bacteria interact with our metabolism at several points: it helps to convert ingested complex nutrients to SCFAs, transforms mucins and dietary fibers into simple sugars ready for absorption, stimulatesdevelopment, this linkage remains very complex. On the other hand, the obesity pandemic asks for a solid response able to restore the significant gut microbial imbalance present in these patients. Thus, these findings imply the possibility and need for therapeutic manipulation of intestinal epithelial proliferation, favors nutrients absorption and microbiota to prevent or treat obesity and its metabolism, it is the main actor in the shaping of gut crucial defense barrierc manifestations. The correlation between Firmicutes/Bacteroidetes ratio and obesity constituted by systemic and mucosal immune system, and it activates bio-inactive compounds [62]s strong evidence arising from three decades of research in this filed. NHowevertheless, gut microbiota plays an important role in human adipose tissue formation and de, several recent studies have highlighted the complexity of the altered composition. Indeed, our of intestinal bacteria are able to maintain the human body energy balance mainly because of their amicrobiota in obese patients compared with lean subjects. Therefore, each study has linked obesity to species- or genus-specific composition profiles. The extreme variability to share otherwise indigestible components of mammalians dieof the results can be attributed to the different [63].
Gexperim-free (GF) mice have provided a complementary approach for characterizing the properties of human guental designs, microbiota fingerprinting, and genome analyses. We must also mention the different populations or sub-populations studied.

Part microbiota in the frameularly, the heterogeneity of metabolic processes. Backhed et al. have suggested thathods used to quantify the levels of gut microbiota may regulate energy storage through host signaling pathways, analyzing GF and conventionalized micedoes not allow a proper comparison of the results generated by different studies, as every technique is biased by accuracy, sensitivity or specificity issues. Thus, there is the need for [64].a Colostandardization of adult GF mice with a normaltechniques to be used to detect and classify gut microbiota harvested from the cecucomposition in obese subjects.

In m of conventionally raised animals produced a 57% increase in total body fat content and 61% increase of epididymal fat pads weight, despite reduced food intake. Moreover, the presence of microbiota increased serum levels of glucose and SCFAs that induced triglyceride production in the liver,re recent years, the attention of researchers has focused on the understanding of the specific metabolic patterns linked to the obesity physiopathology. Intestinal bacteria are an important part of these integrated functional networks. It has derived an increased adiposity, and reduced glucose tolerance. The authors observed also that the presenceing interest of investigators for the impact of gut microbes promoted an increased monosaccharide uptake from the gut, and an increased ability to degradeiota modulation by the diet in these metabolic processes.

In pcolysaccharides.
Lemnclusion, further investigations et al. analyzed the relationship between human milk hormones, namely leptin and insulin, and both the taxonomic organiz using standardized next-generation sequencing technologies should be conducted on the real association and metabolic properties of the infant of gut microbiota [65]. The aucomposithiors found increased levels of lipoprotein lipase (LPL) in epididymal fat pads of conventionalized mice. LPL, a key regulator of fatty acid release from triglyceride-rich lipoproteins, lead to the increased cellular uptake of fatty acids and adipocyte triglyceride accumn and specific obesity-related phenotypes. Moreover, the complex interaction of intestinal bacteria with the host has to be unraveled, as well as the possible effect of variables such as diet, age, gender or physical activity. Future evidences can help, using the modulation. Another study consolidated evidence showing that of these variables in order to re-shape gut microbiota is able to influence an important gut-derived host lipid metabolism factor, namely fasting-induced adipose factor (Fiaf), a circulating lipoprotein lipase inhibitor whose gene expression is normally selectively suppressed in the gut epithelium only by microbes although it is produced in liver and adipose tissuen a healthier profile. Indeed, it remains possible to directly modulate gut microbiota with probiotics, prebiotics, antibiotics, or other therapeutic interventions. Although several randomized clinical trials on probiotics in obesity setting have been carried out [66]. Iandeed, GF mice showed increased gut expression of Fiaf, but administration of microbes from a normal mouse decreases such expression and leads to larger deposits of triglycerides in adipose tissuetheir results are not yet convincing. Thus, more randomized placebo-controlled are lacking in this topic.
 
 

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