Diet, Gut Microbiota, and Obesity: Links with Host Genetics and Epigenetics and Potential Applications

ABSTRACT

Diverse evidence suggests that the gut microbiota is involved in the development of obesity and associated comorbidities. It has been reported that the composition of the gut microbiota differs in obese and lean subjects, suggesting that microbiota dysbiosis can contribute to changes in body weight. However, the mechanisms by which the gut microbiota participates in energy homeostasis are unclear. Gut microbiota can be modulated positively or negatively by different lifestyle and dietary factors. Interestingly, complex interactions between genetic background, gut microbiota, and diet have also been reported concerning the risk of developing obesity and metabolic syndrome features. Moreover, microbial metabolites can induce epigenetic modifications (i.e., changes in DNA methylation and micro-RNA expression), with potential implications for health status and susceptibility to obesity. Also, microbial products, such as short-chain fatty acids or membrane proteins, may affect host metabolism by regulating appetite, lipogenesis, gluconeogenesis, inflammation, and other functions. Metabolomic approaches are being used to identify new postbiotics with biological activity in the host, allowing discovery of new targets and tools for incorporation into personalized therapies. This review summarizes the current understanding of the relations between the human gut microbiota and the onset and development of obesity. These scientific insights are paving the way to understanding the complex relation between obesity and microbiota. Among novel approaches, prebiotics, probiotics, postbiotics, and fecal microbiome transplantation could be useful to restore gut dysbiosis.

Introduction

Rates of obesity are rising worldwide (1), and its management is challenging because the etiology of obesity is complex, with many factors involved in its development (e.g., unbalanced diets, sedentary lifestyle, genetic causes, and social and environmental factors) (2, 3). In the early 21st century, findings on differing gut microbiota composition between lean and obese mice (which were later corroborated in human subjects) (4) suggested that this composition could affect obesity (5). Since then, a number of studies have shown a close relation between the microbiota and obesity, suggesting that gut microbiota may be crucial to the regulation of energy homeostasis (6, 7). In 2006, Turnbaugh et al. (8) suggested that the microbiota affects nutrient harvesting and contributes to the development of obesity, which is supported by more recent studies (9). However, other studies have found a lack of evidence in this area (10, 11), highlighting the need for further research.

The gut microbiota is mostly composed of 5 phyla and populates mainly the large intestine (10). Approximately 90% of bacterial species belong to the phyla Firmicutes (i.e. Bacillusspp.) and Bacteroidetes (Bacteroidesspp.), with the other important phyla being Actinobacteria (Bifidobacteriumspp.), Proteobacteria (Escherichia, Helicobacter), and Verrucomicrobia (Akkermansiaspp.) (12). However, there is a large diversity between subjects, which confers a high interindividual variability (13). To date, 3 bacterial clusters (enterotypes) driven by high proportions of 1 of 3 taxa have been described: Bacteroides (enterotype 1), Prevotella (enterotype 2), and Ruminococcus (enterotype 3) (14). The Bacteroides enterotype has been associated with a diet rich in protein and animal fat, whereas the Prevotella enterotype is related to a high-carbohydrate diet (15). This classification could contribute to a better understanding of the complex relations between gut microbiota and metabolic diseases, including obesity. However, other studies suggest that these enterotypes do not represent recurrent microbial communities across the diversity of human populations and the use of “biomarkers” is proposed as a more accurate term (16).

The gut microbiota regulates many physiological processes through interactions with the host, such as food digestion (17), nutrient uptake and metabolism (18), synthesis of vitamins and bile acids (19), as well as modulation of innate and mucosal immunity, epithelial growth, layer development (20), prevention of pathogenic micro-organism propagation (21), and even regulation of host gene expression (22). The potential of the intestinal microbiota to contribute to obesity has been attributed to energy harvest from nondigestible dietary starches (production of SCFAs) (23), inflammatory processes caused by bacterial LPS translocation and endotoxemia (24, 25), and hormonal mechanisms (activation to G protein receptors and host appetite control) (26). Genetic factors and epigenetic signatures also play an important role in the relation between gut microbiota composition and obesity predisposition, as well as postbiotics and metabolite production (27–29). Other processes are also likely to be involved in the interplay between microbiota and energy metabolism, including taste sensing (30), anaerobic resting metabolism (31), and thermogenesis (32) (Table 1). Hence, this review discusses current evidence on the impact of the gut microbiome on human obesity. These scientific insights are paving the way for the design of innovative precision strategies for the management of obesity and accompanying comorbidities by targeting the gut microbiota.

TABLE 1.

Suggested mechanisms by which gut microbiota could be involved in the onset and progression of obesity¹

Target tissue/organ	Suggested mechanism	Effect in host related to obesity	Reference
Colonic enterocytes	↑ Production of SCFAs	↑ Energy harvesting	(23)
Liver	↑ Expression of liver ChREBP/SREBP	↑ Glucose absorption	(33)
Adipose tissue, liver	↑ Expression of GPR41 and GPR43	↑ Adipogenesis and de novo hepatic lipogenesis	(23)
Colon	↑ Bile acid circulation	↑ Reverse cholesterol transport	(19)
Large intestine	↑ LPS translocation	↑ Endotoxemia	(24)
Large intestine	↑ Activation of endocannabinoid system	↑ Gut permeability	(34)
Colon	↑ Chronic low-grade inflammation	↑ Inflammation (TNF-α, NF-κB, TLR4)	(25)
White and brown adipose tissue	↑ Suppression of FIAF	↑ Lipolysis	(35)
Colonic L cells, brain	↑ Increase of PYY and GLP-1	↓ Appetite and ↑ satiety response	(36)
Colonic L cells, adipose tissue	↑ Activation of GPR41 and GPR43	↑ Appetite	(37)
Brain	↑ Production of bacteria-derived metabolites	Regulation of appetite and satiety response	(38)
Adipose tissue, colon	↑ Inhibition of histone deacetylase activity	Modulation of host gene expression (FFAR3, TLR4, and TLR2 genes)	(29)

^lChREBP, carbohydrate response element binding protein; FFAR3, free fatty acid receptor 3; FIAF, fasting-induced adipose factor; GLP-1, glucagon-like peptide 1; GPR41, G-protein–coupled receptor 41; GPR43, G-protein–coupled receptor 43; PYY, peptide YY; SREBP, sterol response element binding protein; TLR, Toll-like receptor; ↑, increased; ↓ , decreased.

Current Status of Knowledge

Microbiota, dysbiosis, and relations with obesity

The microbiota has a commensal relation with the host and plays a key role in human health and disease (39). Thus, homeostatic balance of the intestinal microbiome is extremely beneficial to the host (40). In fact, some diseases are accompanied by a change in microbial composition that causes a drastic imbalance between the beneficial and the potentially pathogenic bacteria (41). Examples of diseases associated with microbial alterations include autoimmune and allergic diseases, inflammatory bowel disease, and obesity (13). This imbalance in the microbial equilibrium is termed “dysbiosis,” which has been defined as a disturbance to microbiota homeostasis caused by disruption of the ecological equilibrium in the gut; changes in microbial gene richness, functional composition, and metabolic activities; or changes in local distribution (42, 43). Dysbiosis has been related to 3 different phenomena, which can occur at the same time: 1) loss of beneficial organisms, 2) excessive growth of potentially harmful bacteria, and 3) loss of overall microbial diversity (40, 44).

The concept of dysbiosis in the context of obesity was introduced in studies by Ley et al. (5). This research showed that the Bacteroidetes and Firmicutes phyla dominated the gut microbiota in mice (92.6%), but in ob/ob (genetically obese) mice they found 50% fewer Bacteroidetes, and correspondingly more Firmicutes, than in their lean counterparts (5). Later studies in animal models and humans confirmed that obesity was often associated with a decrease in Bacteroidetes and an increase in Firmicutes (45). However, some studies in humans have found an opposite ratio (11), suggesting that the Firmicutes-to-Bacteroidetes ratio is not determinant in human obesity. Numerous researchers have studied how diet can modulate Firmicutes-to-Bacteroidetes ratio. For example, the fecal microbiota of African children consuming a high-fiber diet showed a significant enrichment in Bacteroidetes and depletion in Firmicutes, with a particular abundance of bacteria from Prevotella and Xylanibacter (Bacteroidetes) with respect to European children consuming a Western diet. On the other hand, gram-negative bacteria such as Shigella and Escherichia were significantly underrepresented in African children (46). Cotillard et al. (47) found that dietary changes (increased fruit and vegetable intake) improved bacterial richness, suggesting that dietary habits can determine and restore gut microbiota; however, these results were not strictly confirmed (48). Duncan et al. (49) found no relation in humans between BMI or absolute weight loss and the relative populations of the major groups of human colonic bacteria, including Bacteroidetes, in stool samples from both obese and nonobese subjects. In a Korean cohort, Yun et al. (50) found a decrease in microbial diversity in obese subjects compared with lean subjects, but no changes in the Firmicutes-to-Bacteroidetes ratio. In conclusion, newer studies in humans question initial observations about the Firmicutes-to-Bacteroidetes ratio and conclude that there is no simple taxonomic signature of obesity in human gut microbiota (45, 51). Indeed, Dalby et al. (52) recently discussed whether the use of refined high-fat diets and unpurified diets was appropriate as control diets in the oldest studies. They suggested that this could have introduced confounding factors from differences in dietary composition that have a key role in shaping composition of microbiota. Thus, the choice of control diet can dissociate broad changes in microbiota composition from obesity, questioning the previously proposed relation between gut microbiota and obesity (52). In a meta-analysis, Sze et al. (53) concluded that there was support for a relation between microbiota and obesity status. However, this association was relatively weak and its detection was confounded by large interpersonal variation and insufficient sample sizes.

It remains unclear whether gut microbiota dysbiosis is a causal factor or an effect of obesity, but some experiments in germ-free mice support dysbiosis as a causal factor. In these experiments, germ-free mice and wild-type mice were fed the same high-fat diet; however, only the wild-type mice developed obesity. When the obese microbiota was transplanted into the germ-free mice, obesity was induced (54, 55), and when a lean microbiota was transferred into obese mice, the symptoms of metabolic syndrome were ameliorated (56).

In any case, dietary habits constitute a major factor influencing changes in human gut microbiota (57) (Figure 1). Some of the dietary factors that can modify microbiota composition are macronutrient composition, fiber content, and the presence of bioactive compounds (i.e., polyphenols) (Table 2). In addition to diet, other lifestyle factors, including stress or physical activity, have been reported to induce alterations in gut microbiota composition; and some of these might be associated with obesity (Table 3).

FIGURE 1.

Gut microbiota, genomic/epigenomic stability, and obesity. Diverse environmental factors may alter microbiota composition (dysbiosis). Microbially derived metabolites may induce a set of genetic and epigenetic modifications. Dysbiosis can increase the number of SCFA-producing bacteria, which can be used as an extra energy source. An increase in gram-negative bacteria can produce LPS translocation caused by an increase in gut permeability, which can trigger endotoxemia and low-grade systemic inflammation. These factors appear to increase susceptibility to obesity and metabolic disease.

TABLE 2.

Effects of different diets and fibers on gut microbiota and their impact on host health¹

Type of diet and diet composition	Study model	Effect on gut microbiota	Effect on host health	Reference
High-fiber
Normal diet supplemented with 25 g nonstarch polysaccharide and 22 g resistant starch	Healthy adults	↑ Abundance of Rominococcus bromii	High production of SCFAs with high-resistant-starch diet Increase in butyrate production (22%) R. bromii facilitates fermentation of carbohydrates (cellulose, pectin, and starch) and increases energy availability	(58)
High-fat diet supplemented with 10% inulin	Germ-free male C3H/HeOuJ mice	↑ Production of SCFAs and ↑ bacterial proliferation	No increase in body fat/weight Increased expression of genes involved in hepatic lipogenesis (Fasn, Gpam) and improvement in the ω-6-to-ω-3 ratio	(59)
500 g oat products/kg and 130 g wheat starch/kg	Wistar rats	↑ Bifidobacteria	Increase in acetate production	(60)
		↑ Production of SCFAs	High excretion of bile acids
			Decrease in LDL cholesterol
10 g fiber/d (2.26%)	Healthy children	↑ Bacteroides and ↓ Firmicutes ↓ Enterobacteriaceae ↑ Production of SCFAs ↓ Abundance of Shigella and Escherichia	Prevention of some potentially pathogenic intestinal microbes causing diarrhea (i.e., a decrease in Enterobacteriaceae such as Shigella and Escherichia)	(46)
High-fat
72% fat	Male C57BL/6J mice	↓ Lactobacillus, Bifidobacterium, and Prevotella	Increased intestinal permeability and association with inflammatory biomarkers (IL-1, TNF-α)	(61)
60% fat	C57BL/6J and TLR4-deficient C57BL/10ScNJ mice	↑ Firmicutes ↓ Bacteroides ↑ Ruminococcus and Rickenellaceae and ↓ Prevotellaceae	Increased intestinal permeability and inflammatory biomarkers (TNF-α, IL-β, and IL-6)	(62)
35% carbohydrates, 20% protein, 45% fat (36.3% saturated, 45.3% MUFAs, 18.5% PUFAs)	Sprague-Dawley rats	↑ Clostridiales	Increase of serum LPS and TLR4 activation; alteration in tight junction and occludin translocation	(63)
Western diet (13.1% protein, 60.6% fat, 26.3% carbohydrates, mainly saccharose)	Female mice C57BL/6	↑ Escherichia coli, Bacteroides, and Prevotella	Increase of gut permeability and alteration in mucus layer	(64)
60% fat (95% lard and 5% soybean oil)	Male C57BL/6J mice	↑ Sulfidogenic bacteria (Desulfobulbus species, Desulfobacter species; and Bilophila wadsworthia)	Impairment of tight junction and macrophage infiltration	(65)
High-protein diet
53% protein	Wistar male rats	↓ Clostridium coccoides, Clostridium leptum, and Faecalibacterium prausnitzii	Increased production of butyrate Increased substrate availability	(66)
29% protein, 66% fat, 5% carbohydrates	Obese humans	↓ Roseburia	Decrease in total fecal SCFAs Increase in hazardous metabolites (N-nitroso compounds)	(67)
Artificial sweetener
Chocolate with 22.8–45.6 g MTL, MTL and PDX, or MTL and resistant starch	Healthy humans	↑ Fecal Bifidobacteria, Lactobacilli, propionate and butyrate after PDX treatment	No significant change in bowel habit or intestinal symptoms	(68)
100, 300, 500, or 1000 mg Splenda/kg ("Splenda no calorie sweetener, granular", McNeil Nutritionals, LLC, Fort Washington, PA)	Sprague-Dawley rats	↓ Bifidobacteria, Lactobacilli, Bacteroides, Clostridia, and total aerobic bacteria	Reduction in beneficial fecal microbiota, increase of fecal pH	(69)

¹FASN, Fatty Acid Synthase; GPAM, Glycerol-3-Phosphate Acyltransferase; MTL, maltitol; PDX, polydextrose; TLR, Toll-like receptor; ↑, increased; ↓ , decreased.

TABLE 3.

Lifestyle factors modulating gut microbiota composition and their relation with obesity

Lifestyle factor	Study model	Mechanism of action	Effects in host related to obesity	Reference
Breastfeeding	Infants (12 mo)	↓ Diversity and ↑ enrichment of Bifidobacteriaceae and Veillonellaceae	Protection against overweight	(70)
	Infants (39–42 mo)	↑ Bifidobacteria?	Reduction in obesity risk	(71)
Undernutrition	Gnotobiotic mice, kwashiorkor and healthy children	Transplantation of gut microbiota from children with kwashiorkor	Less weight gain when mice harbored gut microbiota from malnourished children	(72)
Physical exercise	C57BL/6NTac male mice	↑Faecalibacterium prausnitzii, Clostridiumspp., and Allobaculumspp. in exercise group	Exercise manifests a unique microbiome independent of diet that reduced the intestinal inflammatory response with the high-fat diet, playing a role in gut integrity	(73)
	Athletes, healthy and obese male humans	Male athletes had higher proportions of genus Akkermansia compared with high BMI controls	Lower inflammatory status and increase in gut microbial diversity in athletes	(74)
Stress	Men and women	↑ Firmicutes phylum, ↓ Bacteroides	Increase in IL-6 and intestinal permeability	(75)
	Male Fischer rats	↓ Relative abundance of Prevotella	Stress-evoked inflammatory cytokine and chemokine production	(76)
Cesarean delivery	Children born vaginally and by cesarean delivery	↓ Abundance of Bifidobacteria	Higher level of immunoglobulin-producing cells in their peripheral blood than in those born by vaginal delivery (IgA, IgG, and IgM)	(77)
	Swiss Webster mice	↓ Bacteroides, Ruminococcaceae, Lachnospiraceae, and Clostridiales	Higher body mass gain after weaning	(78)
Antibiotics use	Healthy children	↓ Abundance of Bifidobacterium and Akkermansia	Increased risk of obesity	(79)
	Female C57BL/6J mice	↑ Firmicutes abundance	Increased adiposity and decreased caloric output in fecal samples	(80)
	Q fever endocarditis patients and healthy humans	↓ Concentrations of Bacteroidetes, Firmicutes, and Lactobacillus	Abnormal weight gain in patients treated with doxycycline and hydroxychloroquine	(81)
Sleep disturbances	ClockD19/D19 mutant and wild-type mice	↑ Disorganization in tight junction protein occludin	Increased intestinal permeability	(82)
Cold exposure	Mice	↓ Clostridiales and Porphyromonadaceae family members ↑ Abundance of Parabacteroides spp.	Increase in bile acid production which contributes to beneficial effects of beige and brown adipocytes on obesity-associated comorbidities	(83)

↑, increased; ↓ , decreased.

Diet, microbiota, and obesity

High-fiber diets and production of SCFAs

Cumulative epidemiological data suggest a protective effect of high intakes of dietary fibers (the main source of SCFAs) for maintaining a healthy body weight (84). As previously mentioned, one of the metabolic roles of gut microbiota is to harvest energy from the host diet (85); for example, some microbial species (especially Firmicutes) can generate SCFAs from nondigestible dietary starches, which play important metabolic roles in regulation of energy expenditure to maintain energy homoeostasis and could affect obesity development (86, 87) (Table 2). Several mechanisms have been proposed for how SCFAs may participate in development of obesity: 1) SCFAs provide an extra energy source [equivalent to 10% of the daily caloric intake (87)] and contribute to extra fat deposition in the body (23); 2) SCFAs are ligands for G-protein–coupled receptor (GPR) 41 and GPR43, which regulate energy expenditure (86); 3) regulation of fasting-induced adipose factor (FIAF) (35); 4) de novo lipogenesis (23); 5) regulation of glucose homeostasis (88); 6) regulation of leptin secretion via free fatty acid receptor (FFAR) 3 (37); and 7) modulation of satiety response (36, 89). Moreover, SCFAs have recently been linked to blood pressure control (90).

Riva et al. (91) reported that obese children had more SCFAs in feces than nonobese children, and this correlated positively with higher BMI z score and more Firmicutes and less Bacteroidetes in the gut. Similar conclusions were obtained by Schwiertz et al. (11) when comparing SCFA fecal concentrations in obese, overweight, and lean subjects. The obese subjects had the highest production of SCFAs, but in contrast to other studies, the authors did not find a correlation with the Firmicutes-to-Bacteroidetes ratio (11). The relation between SCFAs and weight gain observed in some studies may be related to the action of GPRs. SCFAs are ligands for GPR41 and GPR43, which are expressed in the intestinal epithelium, immune cells, and adipocytes. In adipose tissue, SCFAs can promote adipogenesis via GPR43 (92, 93). Hong et al. (94) showed that Gpr43 expression was significantly greater in the white adipose tissue of mice with high-fat-diet–induced obesity compared with normal mice fed unpurified diets. Moreover, in 3T3-L1 cells, treatment with SCFAs increased Gpr43 and Pparg (peroxisome proliferator activated receptor γ) transcript levels, whereas suppression of Gpr43 mRNA by RNA interference inhibited adipogenesis (94). SCFAs play a role in glucose and lipid homeostasis through GPR43 and GPR41 (also known as FFAR2/3, respectively) (95), but it appears that not all SCFAs have the same metabolic effects. In the liver, propionate is gluconeogenic, whereas acetate and butyrate are lipogenic (23, 96); however, results from studies in humans are inconsistent.

Some studies have suggested that the increase in fecal SCFA concentrations in overweight and obese individuals could result partially from greater SCFA production, which might also be related to increased conversion of amino acids into SCFAs (89). In accordance, obesity-associated changes in amounts of SCFAs may reflect enhanced microbial amino acid catabolism. Modulation of the gut microbiota by antibiotics has been shown to increase plasma amino acid concentrations in piglets compared with controls (97). Furthermore, there is a marked increase in the portal concentrations of several essential amino acids during high-fat-diet–induced obesity and glucose intolerance (98). It has been speculated that chronic elevations in systemic branched-chain amino acids, as usually seen in obesity, impair transport of these amino acids from the intestinal lumen into the systemic circulation, thereby contributing to persistent amino acid catabolism in the lumen and increased SCFA formation (99, 100). The potential impact of gut microbiota activity on both amino acid and SCFA perturbations in obesity warrants further investigation.

Gut hormones appear to communicate information from the gastrointestinal tract to the regulatory appetite centers within the central nervous system (30). Several studies have suggested that commensal bacteria might modulate brain biochemistry and behavior though metabolite production and modulation of the vagus nerve (101–104). This so-called gut-brain axis constitutes a major mediator of the complex neuroendocrine regulation of appetite and energy homoeostasis (101). According to this, gut dysbiosis caused by an unbalanced diet could trigger altered production of neurotransmitters, leading to overeating and weight gain (101). Modulation of gut hormone release is a potential treatment target for obesity through the use of synchronizing appetite/satiety signals and energy balance mechanisms.

Contrary to the roles of SCFAs as extra energy sources and adipogenic factors, it has been demonstrated that SCFAs may have some beneficial effects in obesity prevention, including modulation of satiety responses and lipid metabolism. In this context, the gut microbiota may modulate adiposity by regulating expression of FIAF, an inhibitor of adipose LPL, therefore exerting an effect on energy extraction and partitioning (35). In germ-free mice, increased amounts of FIAF have been reported to correlate with enhanced lipid oxidation (55). Bäckhed et al. (33) noted a 60% increase in epididymal body fat when the microbiota from germ-free mice was transferred into the distal intestine of conventionally grown mice. The authors suggested that the transferred gut microbiota suppressed FIAF expression in intestinal epithelium, which, in turn, induced higher fatty acid uptake by adipocytes via increased LPL activity. These results suggest that FIAF exerts a protective effect against obesity via increased activity of AMP-activated kinase (in the colon, liver, and skeletal muscle), thus promoting catabolic processes such as β-oxidation while inhibiting lipogenesis (105). Conversely, consumption of high-fat, high-carbohydrate diets induced a dysbiosis and enhanced TG deposition in adipose tissue, which was associated with the suppression of gut FIAF expression and increased LPL activity. Intestinal secretion of FIAF was suppressed in mice in the presence of SCFAs, thus promoting the storage of TGs (35, 106) (Figure 1).

In addition, dietary fibers and SCFAs stimulate mucus production and secretion and contribute to maintaining the normal structure and production of intestinal mucus (107). Diets with very low fiber content increase the penetrability of the inner mucus layer and are associated with increased abundance of mucin-degrading bacteria (108). Concerning the beneficial effects of the different SCFAs, butyrate seems to enhance fatty acid oxidation and thermogenesis by increasing the expression of PPAR-γ coactivator 1α and mitochondrial uncoupling protein 1 in brown adipose tissue and phosphorylation of AMP-activated kinase in muscle and liver (109). In obese subjects, it was reported that propionate significantly increased postprandial release of plasma peptide YY (PYY) and glucagon-like peptide 1 (GLP-1) from colonic L cells, which have a role in satiety and reduction of energy intake (36). Butyrate and propionate are ligands for GPR41 (also known as FFAR3), an SCFA receptor expressed in PYY and GLP-1–secreting endocrine L cells, suggesting their involvement in energy homeostasis. Interestingly, it has been proposed that increasing gut propionate production could prevent weight gain through stimulation of PYY and GLP-1 secretion from human colonic cells (36). Similarly, it has been reported that acetate may reduce appetite by shifting the expression profiles of satiety regulatory neuropeptides in the hypothalamus through activation of the citric acid cycle (110). Moreover, acetate can also activate GPR43 (also known as FFAR2), promoting GLP-1 secretion in the gut and suppressing fat accumulation in adipose tissue, leading to increased insulin sensitivity (94). Several studies reported that Ffar2- or Ffar3-knockout mice had reduced concentrations of GLP-1 and became obese even after a normal diet, whereas mice with overexpression of Ffar2 in adipose tissue remained lean after being fed a high-fat diet (111–113). In addition, SCFAs have an effect on leptin secretion from adipocytes through a GPR41/43-dependent process, further supporting their role in the satiety response (37). These findings suggest that SCFAs may contribute to control of energy intake and use via the gut-brain axis.

Together, these studies suggest that SCFAs could have a protective effect against the development of obesity. In fact, most studies associate high dietary fiber intake with lower risk of obesity, suggesting that SCFAs may have beneficial effects in terms of body-weight regulation. However, SCFAs also participate in energy harvesting and interfere with host metabolism, and further studies are warranted to elucidate this.

High-fat diets and gut permeability

The gut microbiota contributes to the regulation of integrity of the intestinal mucosal barriers (114). It has been proposed that a dysfunction in gut permeability is a primary event triggering bacterial translocation into the bloodstream and contributing to early onset of inflammation and metabolic disturbances related to obesity (115). Cani et al. (115) identified endotoxemia when they found that a high-fat diet in mice increased plasma LPS concentrations in comparison with control animals. Moreover, high-fat diets appear to be involved in a reduction in Bifidobacteriumspp. and overactivation of the endocannabinoid system (34, 115) (Figure 1). These events can unfavorably alter the normal gut microbial composition, leading to increased intestinal permeability, as evidenced by less abundant and disorganized tight junction proteins, such as zonulin and occludin in the colon (61, 63). When tight junction integrity is compromised, passive diffusion across the intestinal mucosa is affected, increasing translocation and plasma LPS concentrations. Likewise, high-fat diets boost the overgrowth of gram-negative pathogens, promoting LPS absorption across the intestinal barrier (115) (Table 2).

LPS can activate the immune pathway of NF-κB in the bloodstream. In combination with CD14 (a proinflammatory cytokine), LPS acts as a ligand for Toll-like receptor (TLR) 4 (62). This suggests that LPS translocation caused mainly by high-fat diets is related to obesity-induced low-grade systemic inflammation (116).

High-protein diets

The microbiota has a considerable proteolytic capacity (117). In particular, Bacteroides and Propionibacterium species are able to convert dietary protein intake, mucin, or host enzymes into amino acids and derivatives (118). There is emerging evidence that aromatic amino acids can be fermented to phenolic compounds, which are similar to those provided by the gut microbiota breakdown of vegetables (119). Although more investigation is needed into amino acid use and availability to the host, bacterial conversion of free amino acids into polypeptides contributes considerably to amino acid metabolism in the mammalian gut (120). On the other hand, although proteolytic fermentation produces beneficial compounds, putrefaction can generate toxic substances such as ammonia, amines, phenols, and sulfides (67, 121) (Table 2). Therefore, the health of the gut could be compromised by an increase in protein content of the diet; however, current evidence is not conclusive about possible relations with obesity.

High consumption of artificial sweeteners and emulsifiers

Some studies have found that artificial sweeteners may have deleterious effects on the composition of the gut microbiota (Table 2), which could interfere with physiological responses that regulate energy homeostasis (68). For instance, altered growth of gut bacteria was reported after administering Splenda (McNeil Nutritionals, LLC, Fort Washington, PA) to rats (69). Another study found that noncaloric artificial sweeteners, such as saccharin, impaired glucose tolerance by modulating the composition of the gut bacteria (122). Recent studies on acesulfame-potassium consumption reported a significant increase in body weight in male mice by disrupting the gut microbiota and activating bacterial energy harvesting pathways (123). The responses and complex regulations of the gut microbiome might be involved in energy metabolism of the host during consumption of artificial sweeteners. However, the specific effects of artificial sweeteners on gut microbiota and metabolism are still largely unknown and further studies are needed. In addition, emulsifiers, such as polysorbate-80 and carboxymethylcellulose, have been found to induce low-grade inflammation and obesity/metabolic syndrome and other chronic inflammatory diseases in wild-type mice, probably by disrupting mucus-bacterial interactions (124).

Genetic and epigenetic factors regulating association between gut microbiota and obesity

Host genetics, microbiota composition, and obesity predisposition

In addition to environmental factors, some studies support a key role for host genetics in shaping the gut microbiome (125). Actually, several genetic variants have accounted for substantial differences in community microbiome composition, diversity, and structure. For example, Bacteroides and Prevotella enterotypes showed a clear difference in microbial functional genes involved in amino acid and carbohydrate metabolism (126). Interestingly, complex interactions between the host genetic background, gut microbiota, and diet concerning the risk of developing obesity and metabolic syndrome have also been reported. In this context, research in animal models has shown a significant variation in obesity-related phenotypes and gut microbiota composition among genetically distinct inbred mouse strains in response to diet (127–129). Emerging evidence in humans revealed that expression of polymorphic genes related to obesity was conditional on exposure to the microbiota in primary human colonic epithelial cells (130). Furthermore, a genomewide association analysis in humans revealed an association between an obesity-related taxon (genus Akkermansia) and a variant near the phospholipase D1 (PLD1) gene (rs4894707), which has been associated with BMI (131). Likewise, a significant association was found between the abundance of Prevotella and the human variant rs878394 linked to lysophospholipase-like 1 (LYPLAL1) in humans, a gene related to body fat distribution and insulin sensitivity (126). This area of research deserves additional efforts to understand the complex interactions of the host genotype with microbiota functions.

Gut microbiota, epigenetics, and obesity

There is growing evidence on the capacity of several microbial metabolites to interact with epigenetic processes (132). These epigenetic modifications can lead to host genome reprogramming by altering the transcriptional machinery of the cell in response to environmental stimuli, with potential implications on health status and disease development (28). These epigenetic mechanisms are probably more relevant in early childhood and could be related to gut microbiota colonization and development through type of delivery, breastfeeding, introduction of solid food, infections, and antibiotic treatments. In this context, SCFAs have been found to inhibit histone deacetylase activity and subsequently modulate gene expression (85). Also, consumption of a Western-style diet prevented some of the microbiota-dependent chromatin changes seen after consumption of a polysaccharide-rich diet (133). In the same study, administration of SCFAs to germ-free mice retrieved chromatin modification states and transcriptional responses associated with microbial colonization, including regulation of global histone acetylation and methylation. Moreover, administration of propionate and butyrate to the stromal vascular fraction of porcine adipose tissue enhanced adipocyte differentiation, which could be partially mediated by their inhibitory effect on histone deacetylase activity (134). Furthermore, exposure of mouse ileal organoids to SCFAs and products generated by Akkermansia muciniphila modulated expression of histone deacetylases, transcription factors, and genes involved in cellular lipid metabolism and satiety (135). Putative mechanistic relations between gut microbiota composition and epigenetic status in human obesity have also been hypothesized (29). For example, compared with lean controls, obese patients had a reduced microbial diversity and abundance of Faecalibacterium prausnitzii as well as lower methylation levels of the FFAR3 gene (FFAR3). Also, a correlation was found between higher BMI and lower FFAR3 gene methylation (29). Similarly, differences in the proportion of Firmicutes:Bacteroidetes and lactic acid bacteria were reported among obese subjects compared with normal-weight controls, which were accompanied by lower methylation levels of the TLR genes TLR4 and TLR2. Notably, significant correlations were found between methylation levels of both TLR genes and BMI (29). In addition, deep sequencing analysis of DNA methylomes revealed a clear association between bacterial predominance and epigenetic profiles (136). Thus, genes with differentially methylated promoters in pregnant women with abundant Firmicutes were linked to lipid metabolism, inflammatory response, and risk of obesity. On the other hand, a recent report demonstrated that fecal micro-RNAs (miRNAs) can shape the composition of the gut microbiome (137), showing an interesting role for miRNAs in mediating a bidirectional host-microbiome interaction (22). Together, these pioneer insights are contributing to progress and understanding of associations between gut microbiota composition and epigenetic status in relation to body weight and metabolism regulation. According to these preliminary data, a dietary approach targeted to favor a more beneficial bacterial population and epigenetic changes underlying energy homeostasis might be effective in the prevention of obesity and related clinical manifestations.

Modulation of gut microbiota in obesity: postbiotics, prebiotics, probiotics, and fecal transplantation

The gut microbiota is not static and short-term changes can occur through dietary and lifestyle modifications (47). Evidence of the relation between intestinal microbiota and obesity makes it vital to understand the effects of microbial manipulation to prevent excessive adiposity or to contribute to body-weight regulation. It has been shown that obesity-associated microbial imbalance can be re-established through, for example, prebiotics/probiotics and balanced dietary therapy, where decreased Firmicutes-to-Bacteroidetes ratio correlated with body-weight loss (138–140).

Postbiotics and other metabolites identified in metabolomic approaches

Postbiotics are nonviable bacterial products or metabolic byproducts from probiotic micro-organisms that have biological activity in the host (141). It has been proposed that these compounds could also be useful in the manipulation of gut microbiota and modulation of related diseases (142). As an example, Cavallari et al. (143) found that bacterial cell wall–derived muramyl dipeptide acts as an insulin-sensitizing postbiotic and can reduce insulin resistance in a model of hyperphagic obesity in mice. In this context, metabolomic approaches aimed at characterization of metabolites in biological fluids and tissues provide the potential to identify biomarkers and to discover new targets and tools to be incorporated into personalized therapies (144, 145). For instance, in humans, a metabolomic analysis of urinary samples detected gut microbiota–derived metabolites (i.e., hippuric acid, trigonelline, 2-hydroxyisobutyrate, and xanthine) associated with a morbidly obese phenotype that differed from lean controls (146). Also, dietary treatment with prebiotics (inulin-type fructans) in obese women decreased Bacteroides intestinalis, Bacteroides vulgatus, and Propionibacterium, associated with a slight decrease in fat mass and with plasma lactate and phosphatidylcholine concentrations, 2 key metabolites implicated in obesity (147). In animal models, it has been reported that lean and obese rats show specific metabolic phenotypes that are linked to their individual microbiomes (148). For example, obese rats had relative abundances of Halomonas and Sphingomonas microbial species as well as different concentrations of urinary (hippurate, creatinine, isoleucine, leucine, and acetate) and plasmatic (LDL and VLDL) metabolites from lean rats. Furthermore, marked associations between bacterial species (Clostridium genus) and the amounts of some metabolites (uridine 3′-monophosphate and 2,4-dioxotetrahydropyrimidine d-ribonucleotide) have been identified in feces from Wistar rats fed a high-fat sucrose diet supplemented with trans-resveratrol and quercetin, which confirms the usefulness of metabolomics to evaluate the physiological effect of food constituents and postbiotics with potential antiobesity properties (149).

Prebiotics, probiotics, and fecal microbiome transplantation in the management of obesity

Prebiotics and probiotics are potential modulators of obesity and its comorbidities. The beneficial effects of prebiotics are generally attributed to the following: 1) stimulation of beneficial bacteria and SCFA production and, consequently, improved barrier function and resistance to inflammatory stimuli (150); 2) increasing levels of some beneficial species (such as Bifidobacterium) that could contribute to restore gut dysbiosis (151); and 3) modulation of lipid metabolism, possibly by inhibition of lipogenic enzymes, and subsequently decreased synthesis of lipoproteins and TGs (152). Well-known effective prebiotics include nondigestible starches, such as inulin or oligofructose. Animal studies have provided strong evidence that prebiotics can modulate the gut microbiota composition, reducing metabolic endotoxemia and inflammation (116). However, in humans, this relation is more controversial. Dewulf et al. (147) showed that inulin-type fructans selectively changed the gut microbiota in obese women, leading to modest changes in host metabolism. Studies analyzing the effects of inulin have proposed that this compound could be effective in reducing cardiometabolic risk (153) and concluded that dietary prebiotics may help to delay or prevent comorbidities associated with obesity (154). Vulevic et al. (155) did not observe changes in obesity parameters but noticed increased levels of Bifidobacteria after 12 wk of galactooligosaccharide mixture supplementation in adults. Nichenametla et al. (156) observed a reduction in waist circumference and fat mass in subjects without metabolic syndrome (but not with metabolic syndrome) supplemented with resistant starch type 4. However, current results from clinical trials are too scarce to propose any recommendations for the general population (157).

Some probiotics, generally Lactobacillus and Bifidobacterium, have shown an amelioration of obesity status and associated metabolic disorders in high-fat-diet–fed mice (158). It has been reported that Bifidobacterium supplementation may exert beneficial metabolic effects in rodents fed a high-fat diet, mainly by improving gut barrier integrity, bacterial LPS translocation, endotoxemia, and inflammation (159–161). Similarly, recent studies have suggested that Lactobacillus gasseri may decrease abdominal adiposity and postprandial lipid responses in Japanese overweight, hypertriacylglycerolemic subjects (162). Osterberg et al. (163) showed that supplementation with probiotics provided protection from body and fat mass gain with a high-fat diet in healthy young males. However, a pilot study in underweight and normal-weight children showed that administration of Enterococcus faecium IS-27526 with milk had a significant positive effect on immune humoral response but resulted in increased body weight of children with normal body weight (164, 165). However, most studies testing probiotics in humans have not reported antiobesity effects. Zarrati et al. (166) reported that probiotic treatment (Lactobacillus and Bifidobacterium) had no effects on BMI, body fat, and waist-to-hip ratio in obese and overweight people.

There are some species that are being exhaustively studied, such as A. muciniphila, which has been associated with restored gut barrier function and reduction of endotoxemia. In obese mice, oral administration of A. muciniphila reduced fat mass gain and adipose tissue inflammation and enhanced the gut barrier function. In humans, a high abundance of A. muciniphila is also associated with a healthier metabolic status and blood cholesterol concentrations (167). A specific protein isolated from the outer membrane of this bacteria, Amuc_1100, interacts with TLR2, is able to improve the gut barrier, and partly recapitulates the beneficial effects of the bacterium (168). In summary, although some studies have shown that probiotics may play a role in the regulation of body weight, information from human intervention trials is extremely limited and there are no conclusive data to support that probiotic intake may contribute to a decrease in body weight (169, 170).

Fecal microbiome transplantation (FMT) is a radical procedure that has been performed with remarkable success in the treatment of patients with recurrent and refractory Clostridium difficile infections. Although many studies in rodents have demonstrated that FMT can help reverse obesity, there is no evidence in humans (44). Vrieze et al. (56) found that FMT from lean donors to patients with metabolic syndrome tended to increase insulin sensitivity 6 wk after infusion, without concomitant changes in body weight and adiposity measurements (171). This study contributes to the knowledge on FMT as a new tool for microbiota modulation in obesity-related diseases, although further studies in humans are needed to clarify the effect of FMT on body weight.

Conclusions

It is widely accepted that the gut microbiota has intricate relations and associations with the onset and development of obesity. When diet and lifestyle change, the gut microbiota rapidly responds to these modifications. The close interactions between the gut microbiota and the host mean that microbiota alterations trigger modifications in the host health, potentially contributing to increase the risk of obesity and associated diseases. In fact, modulation of the gut microbiome through diet, changes in lifestyle, prebiotics, probiotics, or fecal transplantation potentially could be useful for the microbiota homeostasis and management of obesity and accompanying comorbidities. However, although some of these strategies have shown promising results in animal models, there is not enough evidence in humans. Results in humans are still inconsistent and further investigation is mandatory.

The response of the human gut microbiota to dietary changes is highly individualized. A better understanding of diet-microbiota and host gene-microbiota interactions would help in designing new personalized nutrition approaches to prevent and reduce more efficiently the incidence of obesity and other chronic diseases related to inflammation. However, because of the intricate relation between diet, microbiota, and the host metabolism, more studies are needed because some mechanisms are controversial and still not well known in humans. Improving knowledge of the interactions between diet, gut microbiota, and host genetics and epigenetics is vital for the design and implementation of new personalized strategies to prevent and manage obesity and its comorbidities.

Notes

Published in a supplement to Advances in Nutrition. Presented at the International Union of Nutritional Sciences (IUNS) 21st International Congress of Nutrition (ICN) held in Buenos Aires, Argentina, October 15 -20, 2017. The International Union of Nutritional Sciences (IUNS) thanks Mead Johnson Nutrition and Herbalife Nutrition for generously providing grants to support the publication and distribution of the present supplement from the 21st International Union of Nutritional Sciences. The contents of this supplement are solely the responsibility of the authors and do not necessarily represent official views of the IUNS. The supplement coordinators were Angel Gil and Alfredo Martinez. The supplement coordinators had no conflicts of interest to disclose.

Supported by CIBERobn, Mineco (Nutrigenio AGL2013-45554-R project), Aditech (Obekit PT024 and Microbiota PI035 projects), and CONACYT-Mexico (to OR-L).

Author disclosures: AC-S, OR-L, JIR-B, FIM, and JAM, no conflicts of interest.

Publication costs for this supplement were defrayed in part by the payment of page charges. This publication must therefore be hereby marked “advertisement” in accordance with 18 USC section 1734 solely to indicate this fact. The opinions expressed in this publication are those of the authors and are not attributable to the sponsors or the publisher, Editor, or Editorial Board of Advances in Nutrition.

Abbreviations used: FASN, Fatty Acid Synthase; FFAR, free fatty acid receptor; FIAF, fasting-induced adipose factor; FMT, fecal microbiome transplantation; GLP, glucagon-like peptide; GPAM, Glycerol-3-Phosphate Acyltransferase; GPR: G-protein–coupled receptor; PYY, peptide YY; TLR, Toll-like receptor.