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Review

Gut Microbiota and Obesity: The Chicken or the Egg?

by
Daniele S. Tassoni
1,
Rodrigo C. O. Macedo
1,
Felipe M. Delpino
2 and
Heitor O. Santos
3,*
1
Department of Health Sciences, Universidade de Santa Cruz do Sul (UNISC), Av. Independência, 2293-Universitário, Santa Cruz do Sul 96815-900, Brazil
2
Postgraduate Program in Nursing, Universidade Federal de Pelotas (UFPEL), R. Gomes Carneiro, 01-Balsa, Pelotas 96010-610, Brazil
3
Postgraduate Program, Faculdade UNIGUAÇU, EXXA Building—Pres. Bernardes Street, 2009—2nd Floor—Center, Cascavel 85801-180, Brazil
*
Author to whom correspondence should be addressed.
Obesities 2023, 3(4), 296-321; https://doi.org/10.3390/obesities3040024
Submission received: 5 November 2023 / Revised: 23 November 2023 / Accepted: 23 November 2023 / Published: 27 November 2023
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Abstract

:
Although the link between gut microbiota and obesity is increasingly reported, the pathophysiological mechanisms and clinical outcomes are still under debate. This overview of human and animal data addresses several pathophysiologic mechanisms, dietary habits, exercise and probiotic and symbiotic supplementation in the fields of gut microbiota and obesity. Overall, obesity impairs gut microbiota composition due to factors that may be linked to the onset of the disease, such as excessive consumption of high-energy foods, sugars and fats, as well as a low fiber intake and physical inactivity. Conversely, low-energy diets, physical exercise, and probiotic and prebiotic supplementations can enhance gut microbiota in patients with obesity, in addition to improving cardiometabolic markers. As for perspectives, further research is warranted to ascertain proper dietary manipulation, physical exercise protocols and dosing regimens of probiotics. Regarding the latter, the effects on indicators of obesity are clinically modest, and hence skepticism must be exercised.

1. Introduction

Obesity is a disease characterized by excess body fat and is associated with an increased risk of developing type 2 diabetes mellitus (T2DM), dyslipidemia, cardiovascular diseases (CVD), respiratory disorders, joint diseases, gastrointestinal diseases and some types of cancer [1,2]. According to WHO data [3], more than 1.9 billion adults worldwide were classified as overweight in 2016, of which more than 650 million suffered from obesity. In the United States, the trends of obesity indicate that nearly one in two adults will develop obesity by 2030, such that the prevalence will exceed 50% in 29 states [4]. Globally, the number of subjects who are overweight and obese will be approximately 1.35 billion and 573 million individuals by 2030, respectively [5].
Obesity is a multicausal disease in which lifestyle, environment, genetics and social, cultural, economic, psychological and physiological factors are some triggering factors [6]. Furthermore, gut microbiota seems to contribute to adiposity and influences the development and progression of obesity, since patients with obesity have an altered microbiome compared to lean individuals [7,8].
In addition to participating in the digestive and absorptive processes, gut microbiota plays an important role in immune response, metabolism, gene expression, vitamin synthesis and energy harvest from food [9]. A symbiotic relationship between bacteria in the intestinal lumen and the host promotes the renewal of cells present in the villi, the maintenance of the absorption surface, an increase in the content of microorganisms, and a reduction in intestinal transit time [10].
Disorders in the composition of gut microbiota may influence many physiological aspects [11]. The integrity of the intestinal barrier is affected by high-fat diets and entails an elevated concentration of antigens, subsequently stimulating the immune system and developing insulin resistance [12]. A high-fiber diet—mostly from plant sources—in turn, is strongly associated with stimulating the diversity of beneficial bacteria and contributing to reducing the risk of chronic diseases [13]. Moreover, physical exercise and supplementation with probiotics and/or prebiotics can enhance gut microbiota in subjects with obesity.
Despite a myriad of research studies, further attention is needed to unify the mechanistic and clinical backgrounds of non-pharmacological strategies in the circles of obesity and gut microbiota. That said, this article aims to provide an overview of the crosstalk between obesity and gut microbiota by exploring putative mechanisms and clinical environments in an attempt to elucidate the causal relationship. Taken together, pathophysiological mechanisms, dietary habits, exercise and probiotic and symbiotic supplementation are addressed in this regard.

2. Materials and Methods

An overview of human and animal studies was carried out through a search for articles in databases Pubmed (Medline), Embase and Google Scholar with the terms (and respective entry terms) “Obesity”, “Gut microbiota/Gut microbiome” and “Microbiota/microbiome” published until the search period of November 2022. Studies with observational design (cross-sectional or cohort) or clinical trials, published in English and Portuguese and published in the last 20 years were included. Animal studies were included to improve the physiological background as well; however, in vitro studies, case reports and editorials were excluded.
We included articles that associated being obese or overweight with the principal themes of the present study, such as physical activity, sedentary habits, lifestyle, foods, dietary patterns, gut microbiota, probiotics and prebiotics.

3. Results

A total of 6915 results were found, of which 695 were observational studies, 509 were clinical trials and 2322 were studies with animals. The articles were first selected by reading the titles and/or abstracts. After that, the studies were filtered by reading the complete manuscript, with 40 human studies (observational and clinical trials) and 25 experimental studies on animals remaining.
A summary of several studies reporting the link between gut microbiota and obesity in humans can be seen in Table 1 and Table 2, and those in animals in Table 3. Collectively, weight loss induced by low-energy diets alone or combined with physical exercise or bariatric surgery is sharply associated with improved gut microbiota. Probiotic and prebiotic supplementations can also enhance gut microbiota, but their effects on indicators of obesity are modest and cannot be overrated. Weight loss strategies alone or combined with probiotics and/or prebiotics can not only improve gut microbiota but also cardiometabolic markers. However, high-fat, high-calorie diets along with a low-complex carbohydrate (CHO) pattern can be detrimental to gut microbiota. Finally, a couple of research studies shed light on the role of fecal transplantation in modulating gut microbiota.
Further physiological and clinical backgrounds can be seen in the topics below.

4. Gut Microbiota-Derived Nutrients and Nutrient Absorption

A healthy gut microbiota is of pivotal importance in enhancing nutrient absorption. In the large intestine, bacteria interact with dietary substrates that are undigested in the upper digestive tract for survival, while bacterial fermentation can yield beneficial metabolites [77]. Gut microbiota contributes to the metabolism of CHO, proteins (PTN), lipids and short-chain fatty acids (SCFAs). Apart from macronutrients, the gut microbiota modulates the metabolism of vitamins and phytochemicals, as discussed in these subsections.

4.1. Carbohydrates

CHO metabolism and transport are major catalytic functions of the gut microbiota, with important consequences for the host. Mammals can hydrolyze starch and disaccharides to monosaccharides but have a limited ability to hydrolyze other polysaccharides [78]. Humans lack the enzymes to degrade the bulk of dietary fibers (nondigestible CHO), which are fermented by the anaerobic cecal and colonic microbiota [79]. Furthermore, gut microbiota has the ability to break down plant glycoconjugates (glycans), including cellulose, chondroitin sulfate, hyaluronic acid, mucin and heparin [80].

4.2. Protein

Since there is a tendency for gut microbiota to ferment CHO over PTN, saccharolytic bacterial fermentation occurs predominantly in the proximal colon, while proteolytic fermentation is mainly performed in the distal colon. Moreover, gut microbiota PTN breakdown produces potentially toxic metabolites such as ammonia, sulfur-containing compounds and indoles [81,82]. Therefore, CHO and PTN fermentation results in multiple groups of metabolites, of which SCFAs substantially contribute to the host metabolic phenotype and hence to disease risk [83].
Undigested proteins have been considered potentially harmful to the gut microbiota [84,85]. Reaching the large intestine, proteinaceous fermentation substrates produce toxic metabolites, such as gaseous products (hydrogen sulfide, hydrogen, carbon dioxide and methane), ammonia, N-nitroso compounds, amines and phenolic and indolic compounds [85]. More importantly, the major concern of proteinaceous fermentation is linked to the excess of hydrogen sulfide levels, whose metabolite stimulates pro-inflammatory gene expression in colonocytes [86]. Figure 1 illustrates these concerns.

4.3. Lipids and SCFAs

Gut microbiota is also vital to bile acid pool size and thus enhances intestinal nutrient absorption and biliary secretion of lipids [88,89]. More specifically, in the gut, primary bile acids are converted by colonic bacteria to secondary bile acids, predominantly deoxycholic acid and lithocholic acid [90]. The host, in turn, generates a large, conjugated hydrophilic bile acid pool via the positive-feedback antagonism of FXR in the gut–liver axis, which is a fundamental action insofar as decreased bile acid concentrations in the gut can lead to bacterial overgrowth and inflammation [89]. Moreover, taurine-related modulation by the gut microbiota is crucial to bile acids, as taurine is an amino acid used to conjugate bile acids [91].
SCFAs, i.e., acetate, propionate and butyrate, are organic acids produced within the intestinal lumen by bacterial fermentation of undigested dietary CHO and PTN, which can be used as energy sources either by the human colonocytes or elsewhere in the body [81,92]. In humans, fermentation of 50–60 g of CHO or ~10% of the daily energy requirement (140–180 kcal) from high-vegetable and fruit diets yields 0.5–0.6 mol of SCFAs [78]. In addition to their nutritional value, SCFAs have important effects on other aspects of human physiology. SCFAs regulate the balance between fatty acid synthesis and oxidation, glucose and cholesterol metabolism via AMP-activated protein kinase (AMPK) [79]. SCFAs broadly influence host processes, which include energy uptake, host–microbe crosstalk signaling, and colonic pH control, with ensuing effects on microbiota composition, gut motility and epithelial cell proliferation [83].

4.4. Vitamins

Gut bacteria participate in vitamin K and B synthesis. Since human neonates are born with low levels of vitamin K [93], gut microbiota is essential to provide K2 (or menaquinone) [94]. Vitamin K is necessary for several blood coagulation factors (II, VII, IX and X) and some coagulation inhibitors synthetized by the liver [95]. B-vitamins are a diverse group of molecules and biosynthetic precursors of universally essential cofactors used in numerous metabolic pathways related to energy production, protein metabolism and hemopoiesis [96]. Taking into account the bacterial patterns that synthesize B-vitamins, type 1 enterotypes participate in the synthesis of biotin, riboflavin and pantothenate, while type 2 enterotypes synthesize thiamine and folate [97]. The real contribution of microbiome-produced B-vitamins to host requirements and status are unknown [96].

4.5. Phytochemicals

Gut microbiota has an extensive capacity to metabolize phytochemicals, chiefly polyphenols [98,99]. Polyphenols are secondary metabolites of plants generally involved in defense against ultraviolet radiation or aggression by pathogens. In humans, polyphenols confer antioxidant properties and may modulate the activity of a wide range of enzymes and cell receptors [100]. Although polyphenols are common in the human diet, accounting for about 820 mg/day, mainly from fruits and vegetables, they are poorly absorbed by the intestine [77,100]. It may occur because most food polyphenols are in the form of esters, glycosides or polymers that must be hydrolyzed by intestinal enzymes or by the gut microbiota before they can be absorbed [100].
Polyphenols that are not absorbed in the small intestine reach the colon, where they are hydrolyzed by the colonic microbiota, which includes Bacteroides distasonis, Bacteroides uniformis, Bacteroides ovatus, Enterococcus casseliflavus, Eubacterium cellulosolvens, Lachnospiraceae CG19-1 and Eubacterium ramulus [101,102]. Specific active metabolites are produced by the gut microbiota; for instance, (a) enterolactone and enterodiol, from lignans of linseed, and (b) equol, from daidzein of soya. Both of them have antioxidant capacities as well as phytoestrogenic and potential anti-cancer properties [103,104].

5. Gut Microbiota-Derived Metabolites and Cardiovascular Disorders

Gut microbiota under unhealthy diet patterns transforms dietary nutrients into metabolically harmful substances, of which branched-chain amino acids (BCAA), imidazole propionate and trimethylamine N-oxide (TMAO) are some examples [105,106].
The microorganisms Prevotella copri and Bacteroides vulgatus increase BCAA synthesis, while Streptococcus mutans and Eggerthella lenta are producers of imidazole propionate [7]. Since high circulating levels of BCAA are an important risk factor for insulin resistance [107], BCAA-related microbial compounds (e.g., imidazole propionate) have negative effects on insulin signaling cascades [105].
TMAO, in turn, has gained much attention due to its potential role in CVD [105,108]. Trimethylamine (TMA) is synthetized by gut microbiota from phosphatidylcholine, choline, betaine and l-carnitine, which are abundant in seafood, dairy products, egg yolks and red meat. TMA enters the portal circulation and is oxidized to TMAO in the liver by flavin-containing monooxygenase 3 [7,109]. TMAO—or its dietary precursors—accelerates arteriosclerosis via inflammation, oxidative stress, platelet aggregation and thrombosis [109,110]. Accordingly, gut dysbiosis leads to high plasma TMAO levels, which are related to CVD and all-cause mortality [105,111].
Importantly, the crosstalk between gut microbiota imbalance and obesity is inherent to inflammation induced by lipopolysaccharides (LPS). LPS are glycolipid molecules that serve as important outer membrane components of Gram-negative bacteria and have a role as bacterial toxins [112], thereby favoring cardiometabolic abnormalities. High levels of LPS can induce the expression of pro-inflammatory cytokines, thus contributing to endothelial damage and increasing the oxidation of low-density cholesterol particles and foam cell formation, ultimately accelerating atherosclerosis [113].

6. Gut Microbiota Composition in Obesity

The intestinal colon is inhabited by several microorganisms that form the gut microbiota and reach nearly trillions [114]. The predominant gut bacteria belong to the following phyla: Firmicutes, Bacteroidetes, Actinobacteria, Proteobacteria, Verrumicrobia and Fusobacteria; however, Firmicutes and Bacteroidetes occur in greater quantities among bacterial cells in the gut [115]. Seemingly, Bacteroides and Prevotella appear to be the predominant bacterial genera inside the Bacteroidetes phylum. In contrast, the genera Clostridium, Eubacterium and Ruminococcus appear to occur in greater numbers in the Firmicutes phylum [116].
In addition to the distribution by phyla, intestinal bacteria are classified as enterotypes, i.e., groups of various microorganisms that can somehow impact the health of the host. Arumugam et al. [117] define three groups: (1) type 1 enterotypes, which are apparently rich in species of Bacteroides; (2) type 2 enterotypes, with a greater presence of the genera Prevotella; and (3) type 3 enterotypes, delimited by Ruminococcus.
Individuals with obesity have a higher prevalence of Firmicutes (Fusobacteria, Proteobacteria and Lactobacillus reuteri) and a lower prevalence of Bacteroidetes (Akkermansia muciniphila, Faecalibacterium prausnitzii, Lactobacillus plantarum and Lactobacillus paracasei) compared with normal-weight individuals [118]. Furthermore, animals and humans with obesity have a higher ratio of Firmicutes/Bacteroidetes [74,118,119].
Gut microbiota plays an important role in energy uptake (the energy harvest hypothesis). Individuals with obesity show a higher energy harvest from food compared to lean individuals. This effect seems to be associated with increased CHO degradation and, consequently, the formation of SCFAs, favoring greater energy gain. In addition, microbiota has been suggested to manipulate host behaviors by changing food preferences (e.g., altered taste receptors for fat and sweets) [120]. Since obesity is a result of energy balance, a negative modification of gut microbiota can result in increased energy intake. The pathophysiological link between obesity and gut microbiota is depicted in Figure 2.

7. Unhealthy Dietary Patterns

An excessive intake of alcohol, sugars, and saturated fatty acids (SFAs) is associated with a reduction in bacterial abundance, diversity and richness in the gut and, by virtue of an augmentation of Gram-negative bacteria (dysbiosis), can raise the production of LPS and disrupt intestinal barrier integrity [121,122,123,124,125].
That said, the crosstalk between gut microbiota imbalance and obesity is related to a dietary cluster of high-energy food, fat and sugar intake, suggesting that an “obese microbiota” may not be triggered by obesity itself [126]. In this regard, the high intake of ultra-processed foods with a low nutritional profile is an unhealthy dietary pattern that plays a negative role in gut microbiota [127,128].
The triad of a high content of sodium, SFAs and sugars across ultra-processed foods leads to a higher calorie intake, as observed in a clinical trial in which participants received an ultra-processed diet for two weeks and then a healthy food-based diet for the same period [129]. In the period of the ultra-processed diet, there was an increase of 500 calories ingested daily from CHO and fats, accompanied by a body mass gain of 900 g. Conversely, in the healthy eating phase, the participants lost an average of 900 g. Thus, a diet rich in ultra-processed foods is not only harmful to the gut microbiota but also results in a higher energy intake that, in turn, can cause obesity in the long term.
Reduced microbial gene diversity is observed in low-complex CHO diets, suggesting that this type of CHO acts as a prebiotic and promotes the diversity of gut bacteria [130]. Overall, the benefits of high-complex CHO diets and gut microbiota modulation are thoroughly discussed in the topic below.

8. Healthy Dietary Patterns

A dietary pattern based on fruits, vegetables, seeds, whole grains and mono- and poly-unsaturated fatty acids has been shown to result in gut microbiota diversity, mainly because of the large supply of dietary fiber [131]. Such an eating pattern improves cardiometabolic markers mediated by the gut microbiota, as shown in Figure 3. More specifically, the low-energy, high-fiber pattern is the cornerstone of increasing microbial gene diversity, thus affording reductions in serum cholesterol levels, adiposity and inflammation in patients with obesity [132].
Both low-fat and low-CHO diets with energy restriction increase Bacteroidetes, while reducing body weight, as observed in a one-year intervention of individuals with obesity [23]. In light of this, energy restriction is imperative for modulating the gut microbiota of patients with obesity.
Lastly, public policies encouraging greater consumption of fresh or minimally processed foods and taxation of ultra-processed foods may reflect healthier habits, contributing to obesity reduction [133].

9. Probiotics and Synbiotics in Weight Loss

It is recognized that supplementation with products containing live microorganisms, known as probiotics, improves intestinal epithelial barrier function and increases mucus production [134], thereby partially reducing gastrointestinal problems such as diarrhea, abdominal pain, lactose intolerance, etc. [135]. More interestingly, probiotic supplementation has emerged as a weight loss [136] strategy by virtue of its putative anorexigenic effect by increasing SCFA production, which plays a role in fatty acid oxidation as well as the secretion of gut hormones (YY peptide and glucagon-like peptide 1) and leptin in adipocytes.
The potential effects of probiotic supplementation on weight loss could be enhanced when combined with prebiotics, a specific group of non-digestible and fermentable foods that confer more gastric volume during the meal and are substrates for microorganisms in the gut lumen [137]. Thus, the combination of probiotics and prebiotics, named synbiotics (“live microorganisms that, after ingestion in specific numbers, exert benefits for the health of the host”) [138], merits attention as to their potential in improving indicators of obesity.
Species from the Lactobacillus and Bifidobacterium genera are the components of probiotic supplements in the field of weight loss [139]; however, optimal dosing regimens and plausible clinical effects are far from discernible. A meta-analysis of randomized clinical trials (15 studies, 957 patients) of patients who were overweight or obese revealed that probiotic supplementation alone for 3 to 12 weeks significantly reduced body weight by ~0.60 kg and BMI by ~0.27 kg/m2 compared to placebos, along with a non-statistical decrease of ~0.42 kg in fat mass [140]. In addition to obesity, such a modest effect is similar in patients suffering from both obesity and its metabolic-related diseases [141]. Not only probiotics but also supplementation with symbiotics portrays a small clinical magnitude in improving anthropometric indicators of obesity [142].

10. Exercise

Exercise significantly contributes to the increased biodiversity of microbial species, modulation of the immune system, improved motility and decreased intestinal permeability. Changes in gut microbiota seem to be intensity- and volume-dependent with exercise [143]. Furthermore, exercise increases microbiota-induced SCFA synthesis in the intestinal lumen, which is related to fat oxidation and the preservation of muscle mass [144].
Aerobic exercise training improved gut microbiota and microbial-derived SCFA in previously sedentary patients with obesity without dietary modification, whereas those benefits were reversed after exercise training cessation [145].
In a recent study [26] whereby individuals who were overweight or obese underwent a Mediterranean diet with caloric restriction associated with physical activity promotion for one year, the Bacteroidetes/Firmicutes ratio increased at the end of the intervention, such that there were improvements in the indicators of obesity as well as glycemic and lipid profiles.
Regarding high-intensity interval training, it can counteract high-fat diet-induced changes in the gut by increasing the alpha diversity and Bacteroidetes/Firmicutes in rats with obesity; however, further research using this type of exercise ought to be performed in humans [53].

11. Microbiota Transplantation

Mice receiving obese microbiota transplantation increase in body mass as a result of an increase in the energy harvest without changing energy intake or expenditure, suggesting that the microbiome may favor weight gain [9]. Ridaura et al. [71] tested if gut microbiota may promote body fat increase by performing a microbiota transplant from obese discordant twins (one obese and one lean) to germ-free mice. The animals were fed a low-fat diet and a high-plant polysaccharide diet. The fecal material from mice was analyzed to identify differences between their microbial communities and the relevance of these results to metabolism and host body composition. Gut microbiota composition was modified according to the characteristics of the transplanted microbiota. Comparing results from the transplant, mice that received obese microbiota samples gained more weight than animals that received lean microbiota samples.
In humans, Vrieze et al. [31] implanted lean feces in men with metabolic syndrome and, after six weeks, identified an improvement in gut microbiota composition and insulin sensitivity. However, Yu et al. [32] performed a fecal microbiota transplant by capsules in individuals with obesity and did not find significant changes between the two groups in microbial diversity, body mass, insulin sensitivity, energy expenditure, HOMA-IR or fasting lipid profile.
There are severe limitations when comparing trials in animals and humans due to physiological, food, and microbial differences. Mice that received obese microbiota transplantation showed weight gain as a result of an increase in energy harvest without changing energy intake or expenditure, suggesting that the microbiome may favor weight gain [9].
Collectively, gut microbiota transplantation is promising; however, there are several limitations between animals and humans due to physiological, food, and microbial differences, such that there is no uniform evidence for humans.

12. Conclusions and Perspectives

A common obesity pattern can be a cause of dysbiosis due to the accumulative effects of a high intake of high-energy foods, sugars and SFAs, as well as a reduced consumption of fiber and physical inactivity.
Conversely, low-energy diets, high fiber intake and physical exercise are crucial to enhancing gut microbiota of patients with obesity. Moreover, advice to reduce the intake of ultra-processed foods with a low nutritional profile, along with increasing the intake of natural or minimally processed foods, are reasonable strategies to afford a better status of gut microbiota.
Regarding perspectives, although supplementing probiotics and synbiotics (mainly those containing Lactobacillus and/or species from the Bifidobacterium genus) can aid in the management of obesity, skepticism must be exercised due to modest clinical effects, such that more investigation is needed to better understand proper bacterial strains and dosing regimens.
Finally, microbiota transplantation is a field that deserves substantial elucidation in terms of clinical recommendations.

Author Contributions

D.S.T. and R.C.O.M. were responsible for conceiving the review. D.S.T. and F.M.D. searched and organized the results. All authors participated in the analysis and interpretation of the data and manuscript writing. H.O.S. wrote and contributed to the revision of the manuscript. All authors have read and agreed to the published version of the manuscript.

Funding

This research did not receive any specific grants from funding agencies in the public, commercial or not-for-profit sectors.

Conflicts of Interest

The authors declare no conflict of interest.

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Figure 1. High-protein diets and gut microbiota imbalance. Legend: High-protein diets can increase the undigested protein amount, which, after colonic microbial protein fermentation (putrefaction) through microbiota passage, produces several colon gases from amino acid metabolism (i.e., H2, CO2, CH4, mercaptans and H2S) [87]. These byproducts are excreted as flatus, which may lead to abdominal pain and increase the malodorous components of human flatus. A major concern is the H2S implications in the colonocytes, where it triggers an increased expression of pro-inflammatory genes [84,86]. CO2: carbon dioxide; CH4: methane; H2: hydrogen; H2S: hydrogen sulfide.
Figure 1. High-protein diets and gut microbiota imbalance. Legend: High-protein diets can increase the undigested protein amount, which, after colonic microbial protein fermentation (putrefaction) through microbiota passage, produces several colon gases from amino acid metabolism (i.e., H2, CO2, CH4, mercaptans and H2S) [87]. These byproducts are excreted as flatus, which may lead to abdominal pain and increase the malodorous components of human flatus. A major concern is the H2S implications in the colonocytes, where it triggers an increased expression of pro-inflammatory genes [84,86]. CO2: carbon dioxide; CH4: methane; H2: hydrogen; H2S: hydrogen sulfide.
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Figure 2. Pathophysiological relationship between obesity and gut microbiota. Legend: Obesity is a disease characterized by being overweight and has triggering factors such as excessive calorie consumption and a sedentary lifestyle. Individuals with obesity suffer alterations in gut microbiota and gastrointestinal tracts, such as increased energy uptake and intestinal permeability, decreased microbial diversity and gene richness, and an increased Firmicutes/Bacteroidetes ratio.
Figure 2. Pathophysiological relationship between obesity and gut microbiota. Legend: Obesity is a disease characterized by being overweight and has triggering factors such as excessive calorie consumption and a sedentary lifestyle. Individuals with obesity suffer alterations in gut microbiota and gastrointestinal tracts, such as increased energy uptake and intestinal permeability, decreased microbial diversity and gene richness, and an increased Firmicutes/Bacteroidetes ratio.
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Figure 3. Influence of diet on gut microbiota and accompanied systemic consequences. Legend: (A) A metabolically healthy microbiota may be achieved through a diet high in fiber and low in animal fat and protein, as well as a low sugar intake. Fermentation of nondigestible CHO results in short-chain fatty acids (acetate, butyrate and propionate), whose elements improve cardiometabolism. (B) Gut dysbiosis may be induced by a diet low in fiber and high in animal fat and protein, as well as by high intake of sugar and alcohol. An unhealthy diet is associated with a reduction in bacterial abundance, diversity and richness in the gut, transforming dietary nutrients into metabolically harmful metabolites, i.e., branched-chain amino acids (BCAA), imidazole propionate and trimethylamine N-oxide (TMAO), and thus increasing the production of lipopolysaccharides (LPS) and/or disrupting the intestinal barrier integrity. Finally, such a background can induce the expression of pro-inflammatory cytokines and hence contribute to insulin resistance and related cardiometabolic disorders (e.g., atherosclerosis).
Figure 3. Influence of diet on gut microbiota and accompanied systemic consequences. Legend: (A) A metabolically healthy microbiota may be achieved through a diet high in fiber and low in animal fat and protein, as well as a low sugar intake. Fermentation of nondigestible CHO results in short-chain fatty acids (acetate, butyrate and propionate), whose elements improve cardiometabolism. (B) Gut dysbiosis may be induced by a diet low in fiber and high in animal fat and protein, as well as by high intake of sugar and alcohol. An unhealthy diet is associated with a reduction in bacterial abundance, diversity and richness in the gut, transforming dietary nutrients into metabolically harmful metabolites, i.e., branched-chain amino acids (BCAA), imidazole propionate and trimethylamine N-oxide (TMAO), and thus increasing the production of lipopolysaccharides (LPS) and/or disrupting the intestinal barrier integrity. Finally, such a background can induce the expression of pro-inflammatory cytokines and hence contribute to insulin resistance and related cardiometabolic disorders (e.g., atherosclerosis).
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Table 1. Clinical trials that evaluated gut microbiota and obesity in humans.
Table 1. Clinical trials that evaluated gut microbiota and obesity in humans.
Author (Year)Type of StudyPopulationNInterventionControlTime (Weeks)Results
Crovesy, El-Bacha and Rosado [14]Clinical trial, randomized,
double-blind		Obese women32Hypocaloric diet + probiotic or symbiotic supplementationPlacebo supplementation8No differences in anthropometry between groups of intervention
After the dietary intervention, all groups showed changes in the metabolic profile associated with the reduction in inflammation
Dong et al. [15]Clinical trial, randomizedOverweight or obese adults and older adults80Hypoproteic diet, initially normocaloric and after with caloric reduction Diet with normal content of PTN8No significant differences between weight loss in all groups
Differences in microbiota composition between individuals according to higher or lower fiber consumption
↑ α diversity and abundance of 6 genera of bacteria in the intervention group
Gøbel et al. [16]Clinical trial, randomized,
double-blind		Obese adolescents 50Probiotic supplementation with Lactobacillus salivarius Ls-33Placebo supplementation12No changes in inflammatory markers after intervention (fasting glucose, insulin, HOMA-IR, C-peptide)
↓ fasting insulin, HOMA-IR and C-peptide in the placebo group
Gomes, Hoffmann and Mota [17]Clinical trial, randomized,
double-blind		Overweight or obese women32Probiotic supplementationPlacebo supplementation12Best lipid profile showed ↑ Prevotella, Collinsella, Paraprevotella Enterococcus, Clostridiaceaee Veillonella, while the worst lipid profile showed ↑ phylum TM7, Lachnospiraceae and Roseburia
Alterations in microbial composition in the intervention group: ↑ Firmicutes and ↓ Bacteroidetes
Haro, Borrego
et al. [18]		Clinical trial, randomizedObese men20Mediterranean dietLow-lipid
high-complex CHO diet 		48↑ insulin sensitivity in all groups
↑ genera Prevotella and F. prausnitzii + ↓ Roseburia in low-lipid high-complex CHO diet
↑ genera Roseburia and Oscillospira in Mediterranean diet
Both diets promoted changes in abundance of T2DM-related bacterial abundance, promoting a protective effect
Jian et al. [19]Clinical trial, randomizedOverweight or obese individuals38
(1)
Hypocaloric high-saturated-fat diet
(2)
Hypocaloric high-unsaturated-fat diet
(3)
Hypocaloric high-sugar diet
-3↑ phylum Proteobacteria in high-saturated-fat diet
↑ Lactococcus and Escherichia coli in a high-sugar diet
↑ butyrate producers in high-unsaturated-fat diet
↑ proportion of Firmicute to Bacteroidetes in non-alcoholic fatty liver disease
↑ BMI in all groups
No differences between the richness of microbial genes and α diversity, comparing all groups
Kanazawa
et al. [20]		Clinical trial, randomizedObese and DM2 individuals88Symbiotic supplementationNo type of symbiotic, probiotic or prebiotic supplementation24↑ fasting glucose and HbA1c in the symbiotic group, followed by normalization
No differences in HbA1c, BMI, lipid profile and IL-6 between all groups at the end of the study
↑ Bifidobacterium, cluster Atopobium, total lactobacilli and Lactobacillus, Lacticaseibacillus and Limosilactobacillus in symbiotic group at the end of the study
Leber et al. [21]Clinical trial, randomizedIndividuals with metabolic syndrome or healthy 38Supplementation with probiotic
fermented milk (Lactobacillus casei Shirota)		No type of supplementation12Individuals with metabolic syndrome showed greater intestinal permeability in comparison to healthy individuals
The probiotic showed no changes in the parameters tested in the study
Leong et al. [22]Clinical trial, randomized,
double-blind		Obese adolescents (14–18 years)87Fecal microbiota transplantation of eutrophic individuals by oral capsulesPlacebo capsules26↑ microbial diversity six weeks post-intervention in women. No differences were found in men
↓ android/gnoid fat ratio, particularly in women
Resolution of metabolic syndrome in most individuals after intervention
Ley et al. [23]Clinical trial, randomizedObese individuals 12
(1)
Hypocaloric low-fat diet
(2)
Hypocaloric low-sugar diet
-48Before intervention: ↑ Firmicutes and ↓ Bacteroidetes
After intervention: ↑ Bacteroidetes and ↓ Firmicutes
↑ Bacteroidetes was associated with weight loss
Marungruang et al. [24]Clinical trial, randomizedOlder individuals (50–73 years) with BMI between
25 and 33 kg/m2		47Diet with biomarkers related to cardiometabolic risk (foods with anti-inflammatory potential, antioxidants and anti- anti-hypercholesterolemic, like omega-3, polyphenols, dietary fiber)Conventional diet without biomarkers8Weight loss in both diets
Improvement in lipid profile in the intervention group
No differences in diversity α and taxonomic levels of phyla and genera in the microbiome between the groups
↑ ratio Prevotella/Bacteroides after intervention in multifunctional diet
Meslier et al. [25]Clinical trial, randomizedOverweight or obese individuals 82Mediterranean diet without energy restrictionHabitual diet8↓ plasma cholesterol and HDL cholesterol
↓ fecal bile acids
Changes in the composition of microbiota in the first week of intervention
Greater microbial gene richnesses observed at low levels of PCR
Muralidharan et al. [26]Clinical trial, randomizedOverweight or obese individuals343Mediterranean diet with energy restriction and physical activity promotionMediterranean diet without energy restriction48↓ weight, ↑ Bacteroidetes and ↓ Firmicutes in the intervention group
No significant differences in α and β diversity in all groups
↓ BMI, waist circumference, TG levels, glucose and HbA1c in the intervention group
Neyrinck
et al. [27]		Clinical trial, randomized,
double-blind		Obese individuals24Inulin prebiotic supplementation + hypocaloric dietPlacebo supplementation12No changes between the groups in zonulin
↓ marker for intestinal inflammation after intervention
↑ SCFAs in both groups, but not significant
Modification in β diversity, ↑ Actinobacteria, families Bifidobacteriaceae and
Lachnospiraceae, Lactobacillaceae and genera Bifidobacterium
after intervention
Nicolucci
et al. [28]		Clinical trial, randomized,
double-blind		Overweight or obese children
(7–12 years) 		38Prebiotic supplementation with inulin enriched with oligofructosePlacebo supplementation16↓ weight gain and % body fat in the intervention group
Four individuals with insulin resistance were no longer classified as such after prebiotic intervention
↑ fecal bile acids in the placebo group
↑ Bifidobacterium spp. in the intervention group
Sergeev
et al. [29]		Clinical trialOverweight or obese individual 20Hypocaloric diet + symbiotic supplementationHypocaloric diet + placebo supplementation12No significant differences between the groups in body composition
↓ HbA1C, ↑ relative abundance of gut bacteria and ↓ microbial genera associated with inflammation in the intervention group
Van Son et al. [30]CohortOverweight or obese men and post-menopause women107--284A positive correlation was found between PLm and diastolic BP
No significant differences in Plm between insulin-resistant and -sensitive individuals
Vrieze et al. [31]Clinical trial, randomized,
double-blind		Adult men with metabolic syndrome18Fecal transplantation of microbiota by duodenal tubeFecal transplantation of own feces collected and processed6No significant changes were found in energy expenditure at rest
↑ gut microbiota diversity
↓ fecal SCFAs
↑ peripheral insulin sensitivity
Tendency to improve hepatic sensitivity
Yu et al. [32]Clinical trial, randomized,
double-blind		Obese adults with
insulin resistance		24Fecal transplantation by capsulesPlacebo
supplementation		12Comparing the intervention group and the control group, no differences were found in HOMA-IR, weight, fasting lipids or energy expenditure at rest
A modest reduction in HbA1c in the intervention group
BMI: body mass index; HbA1c: glycated hemoglobin; PTN: proteins; CHO: carbohydrates; LIP: lipids; SCFA: short-chain fatty acids; BP: blood pressure; PCR: C-reactive protein; T2DM: type 2 diabetes mellitus; IL-6: interleukin 6; LPS: lipopolysaccharides; TG: triglycerides; ImP: imidazole propionate; ObMH: obese metabolically healthy; ObMUH: metabolically unhealthy; EuMH: eutrophic metabolically healthy; OvMH: overweight metabolically healthy; MH: metabolically healthy; MUH: metabolically unhealthy; SIBO: small intestine bacterial overgrowth; rRNA: ribosomal RNA; qPCR: real-time quantitative PCR; Ob/Ov: obesity/overweight.
Table 2. Observational studies that associated gut microbiota and obesity in humans.
Table 2. Observational studies that associated gut microbiota and obesity in humans.
Author (Year)Type of StudyPopulationnTime (Weeks)Results
Bervoets et al. [33]Cross-sectionalChildren and adolescents53-↑ Firmicutes/Bacteroidetes ratio in obese children compared to control
↑ Staphylococcus spp. was associated with ↑ energy consumption
↓ Bacteroides vulgatus in obese subjects
Lactobacillus spp. concentrations were associated with CRP levels
Cho [34]CohortChildren and adolescents3648Pre-dietary intervention:
↓ Bacteroidetes in the weight-gain group, in comparison to control
↓ richness of microbial genes
Post-dietary intervention:
↑ Firmicutes, ↓ Bacteroidetes, ↓ richness of genes in the fat-loss group
↓ Firmicutes, ↑ Actinobacteria, ↓ class Clostridia in the weight-gain group
Romboutsia, Ruminococcaeceae _UCG_013, Eubacterium coprostanollgenes-group and Parabacteroides are important to microbial changes in the weight-gain group
Romboutsia genera, Eubacterium_halli_ group and Clostridium_sensu_stricto are important in microbial changes and interaction in the fat gain group
Haro, Borrego
et al. [35]		Clinical trial, randomizedObese men2048↑ insulin sensitivity in all groups
↑ genera Prevotella and F. prausnitzii + ↓ Roseburia in low-lipid high-complex CHO diet
↑ genera Roseburia and Oscillospira in Mediterranean diet
Both diets promoted changes in abundance of T2DM-related bacterial abundance, promoting a protective effect
Haro, Zúñiga et al. [18]CohortAdults75240Microbiota composition seems to be different according to sex and seems to be influenced by BMI
↑ Firmicutes in women independent of BMI
↑ Firmicutes in men with BMI > 33 kg/m2
↓ Bacteroides in men with a BMI of 33 kg/m2
Jumpertz et al. [36]CohortLean or obese adults 21-Firmicutes → associated with increasing nutrient absorption
Bacteroidetes → associated with a decrease in nutrient absorption (−150 kcal)
No differences in caloric excretion in feces of eutrophic or obese with 2.400 kcal/d diet
Eutrophic individuals lost less energy in feces with 3.400 kcal/d diet
No differences in caloric excretion in feces of obese subjects between two diets
Kim et al. [37]CohortOverweight or obese individuals 74716↓ diversity α in MUH
No differences in α diversity between the healthy control group and MH
↑ genera Oscillospira and Clostridium, ↑ family Coriobacteriaceae and Leuconostocaceae in MH
↑ Fusobacteria in MUH
No differences in ratio Firmicutes/Bacteroidetes between MUH and MH
Kong et al. [38]Cross-sectionalLean, overweight or obese individuals 45-↓ Clostridia leptum, Clostridia coccoides and Bacteroides/Prevotella in individuals that were overweight or obese
↑ richness and diversity of microbial genes in individuals with higher consumption of fruits, yogurts, soups and lower consumption of sugar and sugary drinks
The worst food pattern was associated with alterations in lipid profile
Menni et al. [39]Cross-sectionalHealthy women 1.632-↓ α diversity in weight-gain group
Dietary fiber intake was related to microbiota diversity and lower weight gain
Firmicutes were related to a lower risk of weight gain
Bacteroides was related to an increased risk of weight gain
Navarro
et al. [40]		Cross-sectionalAdults, healthy68336↑ acetate concentrations, ↓ Bacteroides in obese subjects
Lactobacillus was related as a risk factor for obesity
Olivares
et al. [41]		Cross-sectionalAdults109-↓ microbial diversity and ↓ ratio Firmicutes/Bacteroidetes in ObMUH
↑ Bifidobacterium in eutrophic EuMH
↑ family Prevotellaceae and genera Eubacterium rectale and Faecalibacterium in people ObMH and OvMH compared to EuMH
↑ Coprococcus and Ruminococcus in OvMH
Orsso et al. [42]Cross-sectionalObese children2180Increased HOMA-IR was associated with ↓ richness of microbial genes, ↓ species richness of Firmicutes and ↓ diversity of Proteobacteria
↓ α diversity was associated with ↑ PCR in obese subjects
Peters et al. [43]Cross-sectionalLean, overweight or obese individuals599-↓ richness of microbial genes in obese compared to eutrophic
No differences in α diversity between overweight and eutrophic
↑ families Streptococcaceae, Lactobacillaceae, Veillonellaceae Gemellaceae and ↓ Christensenellaceae, Clostridiaceae, Dehalobacteriaceae in obese
↑ Lactobacillaceae, Streptococcaceae and ↓ Christensenellaceae, Clostridiaceae, Dehalobacteriaceae in overweight subjects
Roland et al. [44]Cohort prospectiveIndividuals with suspicion of SIBO3024Obese people showed a prevalence of SIBO
↑ small intestine transit time and ↑ gastric and small intestine pH in SIBO
↓ α diversity, ↓ genera Parabacteriodes, Oscillospira and families Bacteroidaceae, Lachnospiraceae in obese with SIBO compared to eutrophic with SIBO
↑ Firmicutes ↓ Bacteroidetes in obese
Stefura et al. [45]Cohort prospectiveLean or grade III obese individuals9648Eutrophic and obese showed phylum Firmucutes elevated compared Bacteroidetes
↑ genera Bacteroides, Odoribacter, Blautia in obese
↑ Ruminococcus, Christensenella, Faecalibacterium in eutrophic
↑ Romboutsia, Lactobacillus, Flavonifractor in BMI ≥ 50 kg/m2
Shen et al. [46]CohortPost-bariatric surgery individuals 2648No differences in ratio Firmicutes/Bacteroidetes pre- and post-surgery
Post-bariatric surgery: ↑ α diversity, improvement in microbial metabolites and markers related to insulin resistance and DCV
Several aspects of microbiota have been modified (composition, diversity) quickly (3–6 months) after the procedure. However, there was a reduction 12 m after surgery
Silva, Monteil and Davis [47]CohortChildren51-↓ family Bifidobacteriaceae and phylum Bifidobacterium, ↑ Lactobacillus and Firmicutes in overweight/obese children compared to eutrophic
↓ phylogenetic diversity in Ob/Ov
Van Son
et al. [30]		CohortOverweight or obese men and post-menopause women107284A positive correlation was found between PLm and diastolic BP
No significant differences in Plm between insulin-resistant and -sensitive individuals
Yun et al. [48]Cross-sectionalAdults127416↓ α diversity in obese
No differences in ratio Firmicutes/Bacteroidetes between obese, overweight and eutrophic
Depletion in lipid metabolism, biodegradation of xenobiotics, ↑ gene-related to purine metabolism and oxidative phosphorylation, alterations in the immune response, ↓ metabolism of CHO, pyruvate and some amino acids in obese individuals
In a taxonomic analysis separated by BMI, bacteria from obese individuals were not influenced by the dietary confounder
Yuan et al. [49]CohortObese children and adolescents8628↑ α and β diversity in ObMH and the control group
↑ genera Anaerostipes, Oscillospir, Odoribacter, Gemmiger, Parabacteroides, Alistipes in ObMH and the control group
↑ genera Bacteroides in ObMH
↑ Fusobacterium in ObMUH
Zeng et al. [50]Cohort
retrospective		Lean, overweight or obese adults1.914-↑ bacterial diversity in obese subjects without metabolic alterations compared to eutrophic
Gradual changes in the microbiota with the aggravation of obesity
Zeng et al. [51]CohortObese individuals 383-↑ microbial diversity and gene count, ↓ ratio Firmicutes/Bacteroidetes in ObMH compared to ObMUH
↑ Alistipes, Bifidobacterium, Eubacterium, Faecalibacterium, Ruminococcus, Subdoligranulum and ↓ phylum Fusobacteria in ObMH
↑ Escherichia, Clostridium, Fusobacterium and Megamonas in ObMUH
↑ microbial genes associated with LPS biosynthesis in ObMUH
BMI: body mass index; HbA1c: glycated hemoglobin; PTN: proteins; CHO: carbohydrates; LIP: lipids; SCFA: short-chain fatty acids; BP: blood pressure; PCR: C-reactive protein; T2DM: type 2 diabetes mellitus; IL-6: interleukin 6; LPS: lipopolysaccharides; TG: triglycerides; ImP: imidazole propionate; ObMH: obese metabolically healthy; ObMUH: metabolically unhealthy; EuMH: eutrophic metabolically healthy; OvMH: overweight metabolically healthy; MH: metabolically healthy; MUH: metabolically unhealthy; SIBO: small intestine bacterial overgrowth; rRNA: ribosomal RNA; qPCR: real-time quantitative PCR; Ob/Ov: obesity/overweight.
Table 3. Studies that evaluated gut microbiota and obesity in animals.
Table 3. Studies that evaluated gut microbiota and obesity in animals.
Author
(Year)		Type of StudyPopulationnInterventionControlTime (Weeks)Results
Bo et al. [52]EXPC57BL/6J mice36
(1)
High-fat diet (HFD)
(2)
High-fat diet + Bifidobacterium pseudolongum supplementation
Standard diet8↓ glucose toleration and ↑ lipid profile markers in HFD
↓ visceral fat, ↑ Bacteroidetes,
↓ Firmicutes, ↑ Butyricimonas, Bifidobacterium and Odoribacter in obese mice using B. pseudolongum
No differences between the groups in α and β diversity
Denou et al. [53]EXPMice16
(1)
Normal diet + physical activity HIIT
(2)
HFD + physical activity HIIT
Without physical activity12↓ ratio Bacteroidetes/Firmicutes and ↓ α diversity in Ob/HFD
↑ α diversity, ↑ ratio Bacteroidetes/Firmicutes after HIIT in Ob/HFD
Ob/HFD mice showed insulin and glucose intolerance
No reduction in body mass or fasting glucose, but improved insulin sensitivity after HIIT in Ob/HFD
Evans et al. [54]EXPMale
C57BL/6
mice		48
(1)
Low-fat diet (LFD) sedentary
(2)
High-fat diet (HFD) sedentary
(3)
LFD + physical activity in hamster wheel
(4)
HFD + physical activity
-14↑ weight and body fat, change in glucose metabolism in group 2
↓ Firmicules ↑ Bacteroidetes, ↑ families Lachnospiraceae Ruminococcaceae and S24-7, ↓ Lactobacillaceae and Turicibacteraceae in physical activity independent of diet
↑ Actinobacteria in group 1
↑ families Clostridiaceae, Lachnospiraceae and Ruminococcaceae, ↓ Turicibacteraceae and S24-7, tendency ↑ Proteobacteria in HFD
Everard et al. [55]EXPC57BL/6J mice40
(1)
Control diet + PREB oligofructose
(2)
High-fat diet (HFD) to diet-induced obesity
(3)
HFD + PREB oligofructose
Control diet8HFD + PREB: ↓ ratio Firmicutes/Bacteroidetes, ↓ proportion of Tenericutes, Cianobactérias and Verrucomicrobia, ↓ Bilophila, Butyrivibrio, LE30 and Oribacterium, ↑ Allobacullum and Prevotella, ↓ hepatic LBP, ↓ inflammatory markers
↑ SCFA and ↓ insulin resistance in using PREB in both diets
PREB had a greater impact on HFD than the control diet
Fjære et al. [56]EXPMale
C57BL/6J
mice		70
(1)
High-fat sucrose diet (HFSD)
(2)
Low-fat, high-protein diet (LFPD)—salmon and casein
(3)
Low-fat, high-protein diet (LFPD)—spare ribs and casein
 
All animals had diet-induced obesity by HFD previously
-16No differences in α diversity between the groups
↑ phylum Verrucomicrobia and ↓ Proteobacteria, ↓ families Rikenellaceae, Desulfovibrionaceae and Clostridiaceae in LFD
↑ bacterial genes related to bile acids biosynthesis in sedentary animals in HFSD
↑ gene related to the transport of sugar in animals authorized to exercise voluntarily in HFSD
Gu et al. [57]EXPMale
C57BL/6J
mice		22High-fat diet (HFD)Standard diet8↑ Firmicutes, Bacteroidetes and Proteobacteria in the control groups and obesity-resistant mice
↑ Bacteroidetes ↓ Firmicutes in obesity-prone mice
Metabolic profile and gut microbiota profile were different between obesity-resistant and obesity-prone mice
Guirro et al. [58]EXPMale mice8
(1)
High-fat diet (HFD)
(2)
Low-fat diet (LFD)
-14↑ ratio Bacteroidetes/Firmicutes in HFD compared to LFD
Differences were identified between the families of microorganisms that colonize the microbiome in both diets
In tests with antibiotics, the cecal microbial content was reduced. In a later test with fecal microbiota transplantation, the biodiversity of the microbiome was restored
Hussain et al. [59]EXPMale
C57BL/6J
mice with diet-induced obesity		18
(1)
High-fat diet (HFD)
(2)
HFD + simvastatin
(3)
HFD + Lactobacillus plantarum LB818 supplementation
Normal diet16↓ body weight using LB818
↓ body weight in group 2, compared to group 1
↓ TG, LDL, fasting glucose and fat deposition in the liver, ↑ HDL in groups 2 and 3
↑ Firmicutes in HFD compared to control
↑ species Akkermanasia and Bifidobacteria and ↓ Firmicutes using LB818
↑ ratio Bacteroidetes/Firmicutes in groups 2 and 3
Ji et al. [60]EXPMale
C57BL/6
mice		48High-fat diet (HFD) + coarse cereal mix (millet, corn, oats, soybeans and purple potatoes)Feed + coarse cereal mix8↓ weight gain and fat accumulation, ↑ SCFA in HFD + cereal mix
↑ glucose tolerance and improvement in lipid profile, ↑ diversity and microbial richness of microbiome, ↓ liberation of pro-inflammatory cytokines using cereal mix
↑ phylum Bacteroidetes and Actinobacterias, ↑ genera Bifidobacterium, Lactobacillus,
Holdemanella, Barnesiella, Okibacterium and Streptophyta, ↓ ratio Firmicutes/Bacteroidetes using cereal mix
Joung et al. [61]EXPMale
C57BL/6J
mice		40
(1)
High-fat diet (HFD)
(2)
HFD + Lactobacillus rhamnosus GG (LGG)
(3)
HFD + Lactobacillus plantarum K50 (LK50)
Normal diet12↓ weight gain, fat accumulation, and slight improvement in intestinal permeability induced by HFD using LK50
↓ TG, fasting glucose, ALT, AST, ↑ HDL, insulin improvement, ↓ ratio Firmicutes/Bacteroidetes, ↑ α and β diversity, ↓ liberation of pro-inflammatory cytokines using LK50
↓ Actinobacteria and
Erysipelotrichia, ↑ Lactobacillus using LK50
Ke et al. [62]EXPGerm-free male C57BL/6J mice60
(1)
Normal diet
(2)
High-fat diet (HFD) + PROB (Bifidobacterium animalis subsp. lactis and Lactobacillus paracasei subsp. paracasei DSM 46331)
(3)
HFD + PREB (oat β-glucan)
(4)
HFD + symbiotic (mix of 2 and 3)
(1)
Normal diet + placebo
(2)
HFD + placebo
12PREB/symbiotic results after changes caused by HFD:
↓ weight gain, ↓ fasting insulin and cholesterol and improvement in HOMA-IR.
PROB results: ↓ fasting insulin and slight weight reduction
Symbiotic results: more efficient in ↓ fasting glucose
↑ microbial richness and ↑ SFCA using supplements
↓ bile acids and improvement in functional activities of the intestinal ecosystem from symbiotics
Kiilerich et al. [63]EXPFemales C57BL/6JBomTac mice150
(1)
Low-fat diet (LFD)
(2)
High-fat and sucrose diet (HFSD)
(3)
High-fat and protein diet (HFPD)
Low-fat diet (LFD)72PTN and sucrose helped reduce weight gain, but HFPD showed greater weight gain
↓ survival of animals fed with HFSD
Obesity was associated with mortality
↑ Lactobacillus in HFSD and HFPD
↓ ratio Bacteroidetes/Firmicutes according to animals’ age in HFPD and LFD
Kübeck et al. [64]EXPGerm-free mice (GFM)
and pathogen-free male C57BL/6 mice (PFM)		60In both types of animals:
(1)
High-fat diet (HFD) palm oil-based
(2)
HFD pork lard-based
Control diet8GFM on diet 2 showed no weight gain, suggesting resistance to diet-induced obesity
Reduced intestinal fat absorption and higher basal metabolic rate (↑ energy expenditure) in GFM on diet 2
PFM was obese compared to GFM, suggesting that microbial composition exerts some influence on the loss of lean phenotype
↑ Clostridiales spp. and Bacteroidales in HFD
Dietary cholesterol may have a protective effect against diet-induced obesity
Lai et al. [65]EXPMale C57BL/6JNarl
mice		47
(1)
High-fat diet (HFD)
(2)
HFD with exercise (HFDE)
(3)
Normal-fat diet (NFD)
(4)
NFD with exercise (NFDE)
(5)
HFD with DGE microbiota transplantation
(6)
HFD with NFDE microbiota transplantation
(7)
NFD with NFDE microbiota transplantation
-24Diet influenced more the composition of the microbiota and α diversity than exercise
NFDE group microbiota transplantation transfers effects similar to physical exercise for weight loss and LIP on HFD diet
↑ genera Turicibacter, Sutterella, Prevotella, AF12 and Helicobacter in NFD and NFDE
↑ Odoribacter, AF12, Helicobacter and Akkermansia in HFDE and NFDE
↑ Odoribacter, Helicobacter and AF12 in the groups of microbiota transplantation
Use of antibiotics that preceded transplantation ↑ obesity development risks
Li et al. [66]EXPMale Sprague Dawley mice20
(1)
Low-fat diet (LFD) followed by diet rich in FOS
(2)
High-fat diet (HFD) followed by diet rich in FOS
-19↑ weight gain, ↑ Bacteroidetes,
↓ Proteobacteria, ↑ abundance of bacterial species in lean mice in group 1
↑ ratio Firmicutes/Bacteroidetes in lean mice compared to obese mice
↓ ratio Firmicutes/Bacteroidetes after intervention in lean mice
Weight gain was associated with increase in Bacteroidetes
Few changes in microbiome community of obese animals:
↓ Desulfovibrionaceae and
Lactobacillaceae, ↑ Ruminococcaceae
Lu et al. [67]EXPMale
C57BL/6J
mice		60
(1)
High-fat diet (HFD) for diet-induced obesity
(2)
HFD + acetate
(3)
HFD + propionate
(4)
HFD + butyrate
(5)
HFD + mixture of three SFCA
Low-fat diet (LFD)16The SCFA from groups 2, 3, 4 and 5 prevented weight gain, promoted a partial improvement in the composition of the microbiota and reduced the increase in TG and cholesterol caused
by an HFD
No differences between the groups in microbial diversity
↓ microbial richness, ↑ ratio Firmicutes/Bacteroidetes in HFD
↓ Firmicutes ↑ Bacteroidetes in groups 2 and 3
Moreira Júnior et al. [68]EXPPathogen-free C57BL/6 mice24
(1)
Standard diet
(2)
High-sugar and butter diet
-12↑ weight and adiposity, development of hepatic steatosis, ↑ Firmicutes and Actinobacteria ↓ Bacteroidetes in group 2
↑ relative abundance of Lachnoclostridium, Bifidobacterium, Parvibacter, Ruminiclostridium
and Blautia in group 2
Diet of group 2 was associated with impulsivity and an anxiolytic effect
Moretti et al. [69]EXPGerm-free and conventional mice (normal microbiome)16Western dietRegular diet16↑ weight, ↑ fat mass, ↓ lean mass, ↑ fasting glucose, adipose tissue inflammation, development of obesity in both animal groups with a western diet
Oh et al. [70]EXPMale
mice with diet-induced obesity		36
(1)
Normal diet
(2)
HFD + PREB Cudrania tricuspidata
(3)
HFD + PROB Lactobacillus gasseri 505
(4)
HFD + PROB Lactobacillus gasseri 505 + PREB Cudrania tricuspidata
High-fat diet (HFD)10Less weight loss in group 4
↑ microbial richness in group 2, but ↓ in group 3
↑ microbial diversity in combined use or not of PROB and PREB
↑ ratio Firmicutes/Bacteroidetes in HFD and no changes using the supplement
↓ Proteobacteria and ↓ taxa associated with obesity using PROB and/or PREB
Weight gain was positively associated with phylum Verrucomicrobia and negatively associated with Bacteroidetes and Firmicutes
Ridaura et al. [71]EXPGerm-free mice12 a 16Fecal microbiota transplantation from obese discordant human twins to germ-free miceMice transplanted with microbiota from lean twins1–4↑ body mass in obese microbiota sample
↑ fermentation of butyrate and propionate, digestion of polysaccharides in the lean microbiota sample
By housing an obese microbiota mouse with a lean one, the increase in adiposity in the obese animal was reduced, and similar characteristics to the lean animal were transferred
Saiyasit et al. [72]EXPMale Wistar mice140
(1)
Normal diet
(2)
High-fat diet (HFD)
-40In HFD: cognitive impairment, ↑ weight, LPS, LDL, cholesterol, HOMA-IR, ↓ HDL
↑ ratio Firmicutes/Bacteroidetes and ↑ ratio Enterobacteriaceae/Eubacteria
HFD promoted dysbiosis in animal microbiota from the first week of the study
Shang et al. [73]EXPMale
C57BL/6J
mice		12
(1)
High-fat diet (HFD)
(2)
HFD followed by control diet
Low-fat diet (LFD)7Higher α diversity in groups 1 and 2 compared to control
Higher metabolism capacity of LIP, CH, starch and sucrose, ↓ S24-7, ↑ Lachnospiraceae in HFD
↑ ratio Bacteroidetes/Firmicutes, ↓ Proteobacteria in the control group
LFD partially re-established diversity and composition of gut microbiota after HFD
Turnbaugh
et al. [74]		EXPObese and lean mice22---↑ Firmicutes in Ob animals
↓ Firmicutes ↑ Bacteroidetes in lean animals
↑ final products of butyrate and acetate fermentation, ↓ residual energy of feces (compared to lean microbiome) in Ob mice
In a fecal transplantation test of Ob and lean mice to germ-free mice, the characteristics of the obese microbiome were transmitted, promoting body fat gain
Turnbaugh
et al. [75]		EXPGerm-free male C57BL/6J mice15Fecal microbiota transplantation from human adults
+
(1)
Low-fat diet (LFD) and high content of plant polysaccharides
(2)
Western, high-fat and high-sugar diet
Low-fat diet (LFD) and high content of plant polysaccharides12Fecal microbiota transplantation from human adults was successful
Diet of group 1: ↑ Bacteroidetes
Diet of group 2: ↑ Firmicutes (class Erysipelotrichi and Bacilli) and
↓ Bacteroidetes
• In fecal microbiota transplantation from transplanted animals to germ-free mice, human gut microbiota were transmitted from generation to generation and hence maintained its diversity. However, the composition of the gut microbiome is directly influenced by the recipient’s diet
The transplanted microbiota was similar to human microbiota after 7 days, while microbiome changes were observed by 1 day of the western diet
Welly et al. [76]EXPObesity-prone male mice30
(1)
HFD + hamster wheel volunteer exercise
(2)
HFD with weight similar to group 2
HFD and sedentary-↑ weight in the sedentary group
No differences in α diversity, relative abundance of ratio Firmicutes/Bacteroidetes and phylum-level changes between groups
↓ Bacteroidetes in groups 2 and 3 compared to control
Group 2: ↑ family Streptococcaceae and ↓ Rikenellaceae
Group 3: ↓ Streptococcus compared to other groups
BMI: body mass index; HbA1c: glycated hemoglobin; PTN: proteins; CHO: carbohydrates; LIP: lipids; SCFA: short-chain fatty acids; BP: blood pressure; PCR: C-reactive protein; T2DM: type 2 diabetes mellitus; IL-6: interleukin 6; LPS: lipopolysaccharides; TG: triglycerides; ImP: imidazole propionate; ObMH: obese metabolically healthy; ObMUH: metabolically unhealthy; EuMH: eutrophic metabolically healthy; OvMH: overweight metabolically healthy; MH: metabolically healthy; MUH: metabolically unhealthy; SIBO: small intestine bacterial overgrowth; rRNA: ribosomal RNA; qPCR: real-time quantitative PCR; Ob/Ov: obesity/overweight.
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Tassoni, D.S.; Macedo, R.C.O.; Delpino, F.M.; Santos, H.O. Gut Microbiota and Obesity: The Chicken or the Egg? Obesities 2023, 3, 296-321. https://doi.org/10.3390/obesities3040024

AMA Style

Tassoni DS, Macedo RCO, Delpino FM, Santos HO. Gut Microbiota and Obesity: The Chicken or the Egg? Obesities. 2023; 3(4):296-321. https://doi.org/10.3390/obesities3040024

Chicago/Turabian Style

Tassoni, Daniele S., Rodrigo C. O. Macedo, Felipe M. Delpino, and Heitor O. Santos. 2023. "Gut Microbiota and Obesity: The Chicken or the Egg?" Obesities 3, no. 4: 296-321. https://doi.org/10.3390/obesities3040024

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