Oral Probiotic Bifidobacterium Longum Supplementation Improves Metabolic Parameters and Alters the Expression of the Renin-Angiotensin System in Obese Mice Liver
Abstract
Background:
Obesity and non-alcoholic fatty liver disease (NAFLD) have been increasing at an alarming rate worldwide. Bifidobacterium longum (BL), a common member of the human gut microbiota, has important health benefits through several mechanisms.
Objectives:
We evaluated the BL supplementation effects on body metabolism and renin-angiotensin components hepatic expression in mice fed a high-fat diet.
Methods:
Thirty-two male mice were divided into four groups: standard diet + placebo (ST), standard diet + Bifidobacterium longum (ST + BL), high-fat diet + placebo (HFD) and high-fat diet + Bifidobacterium longum (HFD + BL). Following the obesity induction period, the ST + BL and HFD + BL groups were supplemented with Bifidobacterium longum for 4 weeks. Then, body, biochemical, histological and molecular parameters were evaluated.
Results:
HFD + BL mice had a significant decrease in adipose tissue mass and blood glucose levels, as well as a significant reduction in blood glucose during an intraperitoneal glucose tolerance test. The treatment also resulted in reduced levels of total cholesterol and hepatic fat accumulation. Moreover, we observed an increase in angiotensin converting enzyme 2 (ACE2) and Mas receptor (MASR) expression levels in BL-treated obese mice.
Conclusions:
These data demonstrate that BL may have the potential to prevent obesity and NAFLD by modulating the mRNA expression of renin-angiotensin system components.
Obesity represents one of the greatest public health problems worldwide, afflicting more than 600 million people (Collaboration, 2016). The obesity etiopathogenesis is multifactorial, involving genetic and environmental factors (for example, hypercaloric diets and sedentarism), and is characterized by excessive body fat accumulation, which commonly results from an imbalance between energy intake and expenditure (Bluher, 2019). The white adipose tissue accumulation predisposes one to a low-grade systemic chronic inflammatory condition that contributes to the development of several diseases, such as diabetes mellitus, atherosclerosis, stroke, non-alcoholic fatty liver disease (NAFLD), and some types of cancer (Choquet & Meyre, 2011).
Non-alcoholic fatty liver disease is a pathological clinical entity characterized by the accumulation of triglycerides in the hepatocytes, with or without inflammation or fibrosis. One of the main risk factors for NAFLD obesity (Brunt et al., 2015; Cobbina & Akhlaghi, 2017) and 30%–40% of the individuals with obesity also have NAFLD. NAFLD is a public health problem with growing prevalence and increased potential to progress to more severe hepatic diseases (Polyzos et al., 2019). Furthermore, NAFLD is associated with several cardiometabolic abnormalities, including type 2 diabetes mellitus (T2DM), metabolic syndrome, and coronary heart disease (Brunt et al., 2015).
The link between obesity and NAFLD comprises several factors. Recently, the literature has drawn attention to the roles of the renin-angiotensin system (SRA) and gut microbiota in relation to the molecular aspects associated with obesity and NAFLD (Aron-Wisnewsky et al., 2020; Borem et al., 2018; Goh et al., 2015; Safari & Gerard, 2019). The SRA is a complex network, formed by several components that together exert important functions in body homeostasis, including hydroelectrolytic balance, arterial pressure control and body metabolism, as well as in the function of several organs, such as the liver, adipose tissue, and intestine (Miller & Arnold, 2019; Patel et al., 2017; Rein & Bader, 2017).
Our understanding of gut microbiota modulation as a possibility for the prevention/treatment of metabolic disturbances associated with obesity is growing (Karlsson et al., 2013; Lynch & Pedersen, 2016). Gut microbiota, or probiotics provide many crucial functions for the host during health and disease and are now recognized as playing key roles in obesity by regulating energy balance and inflammation (Lynch & Pedersen, 2016; Tilg et al., 2020). Probiotics are reported to improve metabolic diseases such as obesity and diabetes through modulating gut microorganisms (Bleau et al., 2015; Brusaferro et al., 2018). Bifidobacterium longum (B. longum) is a gram-positive anaerobic bacteria belonging to Bifidobacterium spp. Recent studies have shown several positive effects of Bifidobacterium longum (B. longum; An et al., 2011; In Kim et al., 2019; Krumbeck et al., 2018).
Therefore, we hypothesized that supplementation of probiotic B. longum for obese animals would modulate the renin-angiotensin system in the liver and improve systemic metabolic parameters. Thus, the objective of this study was to evaluate the effect of B. longum supplementation on body metabolism and the renin-angiotensin system’s expression in the livers of high-fat fed mice.
Methods
Study Design
All experimental procedures were approved by the Ethics Committee of the State University of Montes Claros and were conducted by following the regulations described in the Committee Guiding Principles Manual (Protocol number 103/2016). The experiment was conducted with 4-week-old male Swiss mice divided into four groups (n = 8 animals/group): standard diet + placebo (ST), standard diet + Bifidobacterium longum (ST + BL), high-fat diet + placebo (HFD) and high-fat diet + Bifidobacterium longum (HFD + BL). The animals were kept in propylen cages (41 × 34 × 18 cm) with four animals each, with 12 h light/dark cycle, temperature 22 °C ± 2 °C, and free access to food and water during treatment. The study was divided into two phases: phase 1) obesity induction: the animals were fed for 8 weeks with the respective diets (ST or HFD); phase 2) treatment: the groups ST and HFD maintained their diets and received placebo for 4 weeks, while the ST + BL and HFL + BL groups received B. longum probiotic for the same period (Figure 1).
Diets and Drugs
The standard diet is composed of approximately 50% carbohydrates, 32% proteins, and 18% lipids, presenting 2.2 Kcal/g (Ração Labina Presence®, Brazil), and the high-fat diet is composed by 24.5% carbohydrate, 14.5% protein and 61% fat, presenting a total of 5.28 Kcal/g diet (Haslam & James, 2005; Rocha & Libby, 2009). The B. longum probiotic was administered by gavage at a dose of 50 billion bacteria/kg body weight/daily (Rashid et al., 2014). ST and HFD groups received vehicle daily—sterile water as placebo.
Measurements of Body Weight and Food/Energy Intake
The body weight (in grams), food intake (diet in grams/animal/day), and energy intake (Kcal/animal/day) were measured three times a week at fixed times and days during all experimental procedures. Mice were fasted overnight (10 hours) and killed by decapitation. Samples of blood, adipose tissues (epididymal, mesenteric, and retroperitoneal), and liver were collected, weighed, immediately frozen in liquid nitrogen and stored at −80 °C for subsequent analyses. The tissue weights were corrected by the animal’s body weight (tissue weight (g) ÷ animal body weight (g). Visceral adiposity (g) was calculated by the sum of all adipose tissues (∑ epididymal, mesenteric and retroperitoneal adipose tissues weight (g) ÷ animal body weight (g). For the food intake analysis, the mean food intake of each animal (g and Kcal) was also adjusted by the body weight.
Histology Staining
Liver samples were fixed in 10% neutral-buffered formalin at 4 °C overnight, dehydrated by escalating grades of alcohol, xylene, and paraffin, and then embedded in paraffin. Sections of 5 micrometers were prepared for Hematoxylin & Eosin staining. The slides were analyzed in an FSX100 Inverted Microscope (Olympus®, Japan).
Glucose Tolerance and Insulin Sensitivity Tests
For the glucose tolerance test (IPGTT), a 50% weight/volume hypertonic glucose solution (2 g/kg animal) was intraperitoneally administered after a 10-hour overnight fast. Blood glucose levels were measured in blood samples taken from the caudal vein, in the times 0 (baseline), 15, 30, 60, and 120 minutes after injection. The insulin sensitivity test (IPITT) was performed with the animals in the fed state, being administered an injection of insulin (0.75 U/Kg body weight); tail blood samples were taken at the time points 0 (baseline), 15, 30, and 60 minutes after injection for the measurement of blood glucose levels. The glucometer Accu-Chek Active (Roche®, Suíça) was used for both tests.
Determination of Blood Measurements
Serum was obtained by centrifugation (3,200 rpm for 10 minutes at 4 °C) of the blood samples obtained when the animals were killed. Fasting glucose, total cholesterol, high-density lipoprotein (HDL), low-density lipoprotein (LDL) and triglycerides levels were assessed using enzymatic kits (Wiener®, Argentina). Measurements were performed on a Wiener BT-3000 plus ChemistryAnalyzer (Wiener®, Argentina).
Reverse Transcription and qRT-PCR
Total RNA extracted from the liver was prepared using TRIzol reagent (Invitrogen Corp.®, USA), treated with DNAse and reverse transcribed with M-MLV (Invitrogen Corp.®, USA). The endogenous glyceraldehyde 3-phosphate dehydrogenase (GAPDH), angiotensin-converting enzyme (ACE), angiotensin-converting enzyme 2 (ACE2), and Mas receptor (MASR) were assessed using specific primers and SYBR green reagent (AppliedBiosystems®, USA) in a Plus-One Platform (Applied Biosystems®). Relative comparative CT method was applied to compare gene expression levels between groups, using the 2−ΔΔCT equation (Livak & Schmittgen, 2001). Sequences of primers are shown in Table 1.
| Primer target | Primer sequences (5’-3’) | |
|---|---|---|
| ACE | F R | CTC CTG GGA CTT CTA CAAC CTC CAT GTT CAC AGA GGT ACA CT |
| ACE2 | F R | GGA TAC CTA CCC TTC CTA CAT CAG C CAT CCC CAC ATA TCA CCA AGCA |
| MASR | F R | ACT GCC GGG CGG TCA TCA TC GGT GGA GAA AAG CAA GGA GA |
Note. ACE = angiotensin-converting enzyme; ACE2 = angiotensin-converting enzyme 2; MASR = Mas receptor; F = forward; R = reverse.
Statistical Analysis
Data were expressed as means ± standard error of mean (SEM) and analyzed using GraphPad Prism version 5.0 (GraphPad Software, United States). All data were analyzed for normality of distribution using the Kolmogorov-Smirnov test and were found to be normal. Multiple comparisons were performed using one-way ANOVA with Tukey post-hoc analysis. IPGTT and IPITT were analyzed by two-way ANOVA test. Statistical significance was set at p < 0.05.
Results
Food/energy Intake and Adiposity
As expected, after 8 weeks (phase 1: obesity induction period) the mice fed on high fat-diet gained more weight than did the ST fed mice (gain weight: ST, 79%; ST + BL, 89%; HFD, 109%; and HFD + ST, 106%; Figure 2A). During the second phase (treatment period), no significant differences were observed in mice body weight; mice treated with B. longum displayed a slightly higher weight loss than that of respective control mice (ST, 0.53%; ST + BL, −1.3%; HFD, 0.18; HFD + BL, −1.7%; Figure 2B). Furthermore, B. longum had no significant effect on food intake (Figure 2C).
The results evidenced an important reduction in visceral adiposity between HFD and HFD + BL mice (HFD, 0.047 ± 0.005; HFD + BL, 0.028 ± 0.004; reduction in approximately 42.5% in HFD + BL; Figure 3D). Similar results were observed to epididymal adipose tissue (HFD, 0.029 ± 0.007; HFD + BL, 0.017 ± 0.003), retroperitoneal adipose tissue (HFD, 0.01075 ± 0.001; HFD + BL, 0.005 ± 0.001), mesenteric adipose tissue (HFD, 0.007 ± 0.002; HFD + BL, 0.005 ± 0.001) weights (Figure 3A–C).
IPGTT, IPITT and Plasmatic Analyses
Upon glucose challenge, blood glucose levels in HFD + BL mice were significantly lower than those of the HFD group in the IPGTT test (AUC: HFD, 40.543 ± 5.215 vs. HFD + BL, 26.178 ± 2.882; Figure 4A–B), similarly to the tendency observed in fasting glucose levels (HFD, 143.8 mg/dL ± 12.24 vs. HFD + BL, 77.00 mg/dL ± 13.8; Figure 4E). No differences were found between groups in the IPITT test (Figure 4C-D).
When serum lipid parameters were analyzed, a decrease in total cholesterol was observed HFD + BL versus HFD mice (HFD, 156.7 mg/dL ± 23.73 vs. HFD + BL, 105.7 mg/dL ± 5.78; Figure 4F). However, the levels of HLD-c, LDL-c and triglycerides did not differ between the experimental groups and their respective controls (Figure 4G–I).
Histological and qRT-PCR liver analysis
No statistically significant differences were found regarding the liver weight of the mice (Figure 5A). Hence, we performed a histological analysis to examine the effect of BL on the development of intrahepatic fat deposition. Large hepatic lipid droplets were diffusely present in the liver of the HFD group mice as compared with the other groups (Figure 5B).
qRT-PCR analysis showed increased mRNA expression of ACE2 (HFD, 3.143 ± 1.244 vs. HFD + BL, 7.158 ± 1.315) and MASR (HFD, 1.597 ± 0,584 vs. HFD + BL, 3.137 ± BL, 0.186) in HFD + BL versus HFD mice (Figure 5D–E). No significant differences in the ACE mRNA expression were observed between groups and their respective controls (Figure 5C).
Discussion
The present findings indicate the potential beneficial effects of B. longum in mice fed a high-fat diet: reduction of the body adiposity, improvement in the glycemic/lipid profiles, and the hepatic histological pattern of fat deposition. Furthermore, increased mRNA expression of ACE2 and MASR, were observed. Therefore, even in a preliminary way, B. longum may modulate the renin-angiotensin system components in the liver and by consequence lead to improvements in the metabolic profile, thus supporting our hypothesis.
Experimental and clinical studies have shown that supplementation with probiotics has different metabolic effects and that these effects are strain-dependent (Dong et al., 2012; Million et al., 2012). There are several mechanisms by which bacterial strains perform their functions (Firouzi et al., 2013; Parvaneh et al., 2015). In particular, the genus Bifidobacterium spp. consists of anti-obesity microorganisms and comprises a group of gram-positive bacteria, representing the most common genus in the human gastrointestinal tract, exerting a key role in the promotion of beneficial health effects (An et al., 2011; In Kim et al., 2019; Le et al., 2014). B. longum, one species found in this group, deserves special attention. These therapeutic options are especially important considering the common gastrointestinal and metabolic abnormalities founding in daily nursing practice.
Our study demonstrated an important reduction in the body adiposity of mice fed a high-fat diet supplemented with B. longum, despite the absence of differences in energy intake. The B. longum capacity to decrease body adiposity without affecting food intake might be linked to the modulation of genes involved in the processes of adipogenesis, lipolysis, and lipogenesis. Karimi et al. found that B. longum bacteria supplementation displayed better results than other bacterial species in obese mice in terms of modulating fat mass and adipocyte size (Karimi et al., 2017). An et al. (2011) corroborated these same findings, providing evidence for the B. longum’s ability to decrease body adiposity. Furthermore, in the elderly, B. longum was capable of reducing body mass index (Inoue et al., 2018). Accordingly, strong evidence exists for the renin-angiotensin system’s role in white adipose tissue modulation. Studies suggest that the activation of the Ang-(1-7)/ACE2/MASR axis may lead to decreased body adiposity (de Macedo et al., 2015; Oliveira Andrade et al., 2014). Supporting these findings, Santos et al. (2008) observed increased adipocytes size in MASR knockout mice.
Improvement in glucose tolerance and reduction in serum glucose levels of obese animals that received B. longum correspond to the results of other studies (Backhed et al., 2007; Cani et al., 2007; Chen et al., 2011; Ley et al., 2005) and may be directly associated with particularities of the interaction of this microorganism with the intestinal microbiota of the host (Mazloom et al., 2019). The increase in the Bifidobacterium population is directly related to the lean phenotype and metabolic improvement (Backhed et al., 2005; Ley et al., 2006). Microorganisms colonizing the intestinal microbiota have the ability to degrade polysaccharides and dietary fiber, producing short-chain fatty acids (SCFAs). In the intestine, SCFAs bind to the short-chain fatty acid receptor (GPR43) leading to secretion of anorexigenic peptides, including glucagon-like peptide-1 (GLP-1) and YY peptide (PYY), resulting in improved glucose tolerance and increased energy use, which may explain the decrease in body adiposity (Mazloom et al., 2019).
Recent studies have found that bacteria producing lactic acid, including Bifidobacterium longum have hypocholesterolemic effects in rats and humans (Xiao et al., 2003). Possible mechanisms have been suggested. For example, fermentation products of lactic acid bacteria might inhibit enzymes involved in the synthesis of cholesterol, thus reducing their production. Alternatively, lactic acid bacteria could facilitate the elimination of cholesterol in feces, or bacteria may inhibit the absorption of cholesterol back into the body by binding to cholesterol. In addition, bacteria might interfere with the process of recycling bile salt (a metabolic product of cholesterol) and facilitate its elimination, which increases the demand for bile salt produced from cholesterol, resulting in the consumption of body cholesterol (Beena & Prasad, 1997; Fukushima & Nakano, 1995; Kim et al., 2017).
Obese animals that received B. longum had a lower deposition of liver fat. Recently, Xu et al. demonstrated that B. longum supplementation attenuated the accumulation of hepatic fat in a model of non-alcoholic fatty liver disease (Xu et al., 2012). Furthermore, supplementation with VSL#3, a preparation composed of a mixture of four strains of Lactobacillus and Bifidobacterium, including B. longum improved the fat-induced dietary hepatic steatosis and insulin resistance in mice by modulating hepatic natural killer T cells (NKT cells), suppressing the TNF-alpha/IKK signaling pathway, and reducing the inflammatory signaling (Ma et al., 2008). Some studies have also suggested that B. longum can mitigate hepatic injuries caused by endotoxin-induced activation of macrophages (Fuller, 1991; Liu et al., 2004).
Increased hepatic ACE2 and MASR expression observed in obese animals treated with B. longum describes, for the first time, a modulation of the ACE2/Ang-(1-7)/MASR axis by a probiotic strain. In addition, the metabolic improvement observed in treated animals is associated with RAS since the increased expression of ACE2 and MASR is directly related to the increase in Ang-(1-7) (Santos & Simoes e Silva, 2014). The first study showing the metabolic potential of Ang-(1-7)/MASR, demonstrated a worsening of metabolic efficiency, as well as dyslipidemia, insulin resistance, and decreased expression of adiponectin and GLUT-4 in transgenic mice with MASR suppression (Santos et al., 2008).
Regarding hepatic homeostasis, an oral administration of Ang-(1-7) may decrease gluconeogenesis in the liver, improving glucose and lipid metabolism (Bilman et al., 2012). In addition, Ang-(1-7) decreased inflammatory marker levels by down-regulation of the resistin/TLR4/NF-KB pathway in obese rats (Santos et al., 2013). Another remarkable finding was that obese mice treated with an oral formulation of Ang-(1-7) had a significant reduction in levels of TNF-alpha and IL-6, as well as decreased markers related to adipogenesis, such as ACC, PPAR-Y, and SREBP-1c (Feltenberger et al., 2013).
In summary, we conclude that oral supplementation with B. longum may improve important metabolic parameters, especially in the liver, of mice fed a high-fat diet. Furthermore, the beneficial effects observed by the use of B. longum may be attributed, even partially, to the modulation of the renin-angiotensin system ACE2/Ang-(1-7)/MASR axis. Although further studies are necessary for firmer conclusions, the present study provides important perspectives in the comprehension of the B. longum anti-obesity effects.
Abbreviations
- ACE
- angiotensin-converting enzyme
- ACE2
- angiotensin-converting enzyme 2
- B. longum
- Bifidobacterium longum
- GAPDH
- glyceraldehyde 3-phosphate dehydrogenase
- GLP-1
- glucagon-like peptide-1
- GPR43
- short chain fatty acid receptor
- GLUT-4
- glucose transporter type 4
- HDL
- high-density lipoprotein
- HFD
- high-fat diet
- IKK-β
- IκB kinase beta
- LPS
- lipopolysaccharides
- Mas
- Mas Receptor
- NAFLD
- non-alcoholic fatty liver disease
- NF-KB
- factor nuclear kappa B
- NKT
- natural killer cells
- qRT-PCR
- quantitative real time-PCR
- PYY
- peptide YY
- SCFAs
- short-chain fatty acids
- SCFAs
- short chain fatty acid
- SEM
- standard error
- ST
- standard diet
- TNF-α
- tumor necrosis factor alpha
- TRL4
- toll-like receptor 4.
Declaration of Conflicting Interests
The author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.
Funding
The author(s) disclosed receipt of the following financial support for the research, authorship, and/or publication of this article: This work was partially supported by the Coordenadoria de Aperfeiçoamento de Pessoal de Nível Superior - Coordination of Superior Level Staff Improvement (CAPES), Conselho Nacional de Desenvolvimento Científico e Tecnológico - Brazilian Council for Scientific and Technological Development (CNPq) and Fundação de Amparo à Pesquisa do Estado de Minas Gerais - Minas Gerais Research Foundation (FAPEMIG).
ORCID iDs
André L. S. Guimarães https://orcid.org/0000-0002-3162-3206
Sérgio H. S. Santos https://orcid.org/0000-0002-7788-5447
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Article first published online: July 23, 2020
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