RESEARCH ARTICLE

# Preventive effects of a nutraceutical mixture of berberine, citrus and apple extracts on metabolic disturbances in Zucker fatty rats

Mohamed Siliman Misha<sup>1*</sup>, Sandrine Destrumelle<sup>1</sup>, Dylan Le Jan<sup>1</sup>, Nahla M. Mansour<sup>1,2</sup>, Lionel Fizanne<sup>3</sup>, Khadija Ouguerram<sup>4</sup>, Jean-Claude Desfontis<sup>1</sup>, Mohamed-Yassine Mallem<sup>1</sup>

1. Nutrition, Pathophysiology and Pharmacology (NP3) Unit, Oniris, Nantes Atlantic College of Veterinary Medicine, Food Science and Engineering, Nantes, France, 2. Department of Chemistry of Natural and Microbial Products, Division of Pharmaceutical Industries, National Research Centre, Giza, Egypt, 3. Laboratoire HIFIH UPRES EA 3859, SFR ICAT 4208, Université d'Angers, Angers, France, 4. INRAE, UMR 1280, Physiopathology of Nutritional Adaptations, Nantes, France

* m.silimanmisha@gmail.com

<figure><img src="image_1.png" /></figure>

## Abstract

<figure><img src="image_2.png" /></figure>

**OPEN ACCESS**

**Citation:** Siliman Misha M, Destrumelle S, Le Jan D, Mansour NM, Fizanne L, Ouguerram K, et al. (2024) Preventive effects of a nutraceutical mixture of berberine, citrus and apple extracts on metabolic disturbances in Zucker fatty rats. PLoS ONE 19(7): e0306783. https://doi.org/10.1371/journal.pone.0306783

**Editor:** Joseph L Roberts, Arizona State University, UNITED STATES OF AMERICA

**Received:** November 6, 2023

**Accepted:** June 20, 2024

**Published:** July 26, 2024

**Copyright:** © 2024 Siliman Misha et al. This is an open access article distributed under the terms of the [Creative Commons Attribution License](https://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.

**Data Availability Statement:** All relevant data are within the manuscript and its [Supporting information files](#).

**Funding:** Région Pays de la Loire.

**Competing interests:** The authors have declared that no competing interests exist.

**Abbreviations:** Ach, Acetylcholine; ALAT, Alanine aminotransferase; ASAT, Aspartate aminotransferase; AUC, Area under the curve; AVS,

### Background

The prevention of obesity represents a major health and socio-economic challenge. Nutra-ceuticals are regularly highlighted for their beneficial effects in preventing the metabolic dis-turbances associated with obesity. However, few studies have described the combined action of nutraceutical mixtures combining polyphenols with alkaloids.

### Objective

The aim of this study was to evaluate the effects of long-term dietary supplementation with a mixture of Berberine, Citrus and Apple extracts (BCA) in the primary prevention of obesity and its metabolic and vascular complications in the obese Zucker rat, a spontaneous model of genetic obesity and insulin resistance.

### Methods

Sixteen 8-week-old obese Zucker male rats were randomly divided into two groups: all rats received oral gavage daily either with water, untreated obese (U-ObZ) or BCA (BCA-ObZ) mixture for thirteen weeks. Morphological and metabolic parameters were measured along the study. Cumulative concentration-response curves to insulin, acetylcholine and phenyl-ephrine were determined on isolated thoracic aorta. Colon permeability measurements were performed using the Ussing chamber technique. Fecal samples collected at the beginning and the end of the protocol were used as a template for amplification of the V3-V4 region of the 16S rDNA genes.

### Results

BCA supplementation reduced weight gain (p<0.05) and food intake (p<0.05) in the BCA-ObZ group rats compared to the U-ObZ group rats. It also improved glucose tolerance
Amplicon variant sequences; BCA, Berberine, Citrus and Apple; BCA-ObZ, BCA-Treated Obese Zucker; BMI, Body Mass Index; CCRCs, Cumulative concentration-response curves; HDL, High-density lipoprotein cholesterol; HOMA, Homeostasis model assessment; Ins, Insulin; IR, Insulin resistance; L-Arg, L-arginine; LDL, Low-density lipoprotein cholesterol; LME, Linear mixed-effects; NLME, Nonlinear mixed-effects; NO, Nitric oxide; OGTT, Oral Glucose Tolerance Test; Phe, Phenylephrine; SCFA, Short-chain fatty acids; SEM, Standard error of the mean; U-ObZ, Untreated Obese Zucker.

(p<0.001) and decreased fasting insulin and Homeostasis model assessment index (p<0.05). Through *ex vivo* experiments, the BCA mixture enhanced significantly aortic insulin relaxation (p<0.01), reduced α₁-adrenoceptor-mediated vasoconstriction (p<0.01), and decreased distal colon permeability. Moreover, short-chain fatty acid producers such as *Bacteroides*, *Blautia*, and *Akkermansia* were found to be increased by the BCA mixture supplementation.

## Conclusion

The results showed that a 13-week-supplementation with BCA mixture prevented weight gain and improved glucose metabolism in obese Zucker rats. We also demonstrated that BCA supplementation improved vascular function, colonic barrier permeability and gut microbiota profile.

# 1. Introduction

Obesity is a multifactorial disease. These include genetics, psychological factors (stress, depression), medical factors (the use of certain medications such as beta-blockers, corticoids and antidepressants), as well as lifestyle factors including a sedentary lifestyle and excessive diet [1-3]. Particularly ultra-processed products, resulting in excessive and dysfunctional accumulation of body fat [2,4,5]. Its prevalence is estimated to reach 13% (2023) and 15.9% (2022) worldwide and in the European population respectively [3,6,7]. The pathological feature of obesity is mainly an increase of visceral fat associated with an increased risk of developing metabolic syndrome [7-9], including the obesity-linked meta-inflammation [10], being an important contributor to insulin resistance and alteration of carbohydrate and lipid homeostasis [10-12]. Assuming the multifactorial nature of obesity, the complexity and multiplicity of mechanisms and mediators involved (i.e. oxidative stress, inflammation, arterial hypertension) [12-14], public health organizations and scientific journals agree that multi-component and/or multi-disciplinary interventions are the best option for treating obesity [15-17]. Therefore, therapeutic strategies focused on multi-ingredient-based interventions, including mixtures of nutraceuticals, can be considered more appropriate, due to the cumulative efficacy targeting multiple pathways simultaneously (targeting multiple pathways simultaneously) of such products to overcome the obesity [18].

Nutraceuticals are foods or food-derived products that have health benefits on the main components of the metabolic syndrome [11,18,19]; they have been shown to inhibit lipogenesis and promote lipolysis in the adipose tissue [20-22], to improve insulin sensitivity [18,23,24] and reduce appetite [25,26]. In this study, a nutraceutical blend of Berberine and hydro-alcoholic extracts of Citrus and Apple (BCA) was selected to explore its activity against obesity and obesity-related disorders. The individual pharmacological activities of these ingredients have been previously described. Berberine, an isoquinoline plant alkaloid [19,27] has been paid more attention due to its anti-obesity activities like insulin sensitizing [28,29] and anti-inflammatory [30-32] effects, and its ability to increase energy expenditure by lipolytic and thermogenic actions [21]. Citrus flavonoids have been reported to exert anti-obesity effects due to reduction of appetite, regulation of metabolism and fat storage by mechanisms involving in part a role of hesperidin [21,33,34]. They also have shown anti-inflammatory and antioxidant properties [20,33]. Previously studies have also proven that apple extracts exhibit a
favorable effect on metabolic health thanks to the various components of the skin and apple pulp (pectins, phenolic compounds, flavonoids: quercetin, phlorizin [22,35,36]. The metabolic protection of (via the effects of nutraceuticals) comprises the activation of satietogen mechanisms, the limitation of the gut absorption of carbohydrates and lipids and the decrease of ectopic fat accumulation [34–36].

This study investigated the possible synergistic effects of BCA in terms of primary prevention of obesity and its metabolic and vascular complications in the obese Zucker rat, a spontaneous model of genetic obesity and insulin resistance [37,38]. We hypothesize that long-term supplementation with BCA mixture can prevent obesity and related metabolic and vascular issues through the combined effects of its main ingredients, implying on the one hand, an action on effectors acting directly on weight loss, and on the other hand, the implementation of anti-inflammatory and regulatory actions of metabolism.

## 2. Material & methods

### 2.1. Animals

Sixteen 8-week-old male obese Zucker (fa/fa) rats (weight range: 349.20±5.09 g) included in this study were purchased from Janvier Labs® (Le Genest-Saint-Isle, France). Rats were acclimatized for one week before being randomly assigned to 2 groups: Untreated Obese Zucker (U-ObZ) receiving vehicle (water) and the BCA-Treated Obese Zucker (BCA-ObZ) group receiving the orally administered Berberine and hydro-alcoholic extracts of Citrus and Apple (BCA) mixture (200 mg/kg/day, the dose comprises 100 mg berberine, 50 mg citrus extract and 50 mg apple extract.) for 13 weeks. The environment of their housing room was controlled according to the requirements of the European standard ETS 123, relating to the housing of animals in experimental animal facilities. Thus, the light is regulated with a 12-hour day/night cycle, the temperature is 22 ±2°C, the hygrometry is around 50%, ventilation and noise pollution are reduced to a minimum. Standard rodent food (Serlab®, Montataire, France) and drinking water were provided *ad libitum*. Ethical approval of the project was obtained beforehand and all experiments were performed in accordance with the institutional guidelines of the Ethics Committee of Pays de la Loire, France (ministerial authorization, APAFIS#27136-2020090716464179 v2).

### 2.2. Apple and citrus extracts and drugs

Apple extract (Appl'In®) was provided by Diana Naturals (Antrain, France). This is a fine powder of a polyphenolic extract obtained by hydro-ethanolic extraction method from apple (Malus domestica Borkh) standardised for its content in phloridzin (at least 5%). The specific batch (SD01290004) used in the study contained 5.33% of phlorizin, with a total polyphenols content (hydroxycinnamic acids, flavonols, flavanols) of 87.6% of the final product expressed as catechin equivalents.

Citrus extract (Citrus aurantium L) was supplied by Naturex (Caronno Pertusella, VA, Italy). The extract is a granulated powder obtained by water extraction from Citrus aurantium pericarps (100 mg of extract are equivalent to an average of 290 mg of dry citrus aurantium pericarps). The specific batch used in the study (EC834725) contained around 35% bioflavonoids, including rutin, hesperidin, quercetin and amentoflavone, with hesperidin as the main component (around 37%).

Berberine chloride (100 mM stock solutions of berberine chloride in warm distilled water [39]) was obtained Sigma Aldrich Chimie® (Saint Quentin-Fallavier, France).

Sodium pentobarbital solution was purchased from CEVA Santé Animale (Libourne, France); phenylephrine hydrochloride, acetylcholine chloride, insulin (prepared in 0.01 M
hydrochloric acid solution at a concentration of 20 mg/mL) and berberine chloride were supplied by Sigma Aldrich Chimie® (Saint Quentin-Fallavier, France).

All drugs were prepared as stock solutions in distilled water, with the exception of berberine chloride which was dissolved in warm distilled water [39].

## 2.3. Physiological parameters

Body weight, abdominal circumference, total length and food and water consumption of all rats were monitored weekly. The BMI was calculated according to the following formula: $BMI = \frac{body weight (g)}{length^2 (cm^2)}$. The adiposity index was calculated as $(\text{total body fat/final body weight}) \times 100$.

Before and at the end of the protocol, blood collection was performed after a 4-h physiological fasting. Plasma sampling were stored at -80°C for subsequent determination of plasma levels of total cholesterol (TC), triglycerides (TG) and high-density lipoprotein cholesterol (HDL-C) by Nantes Hospital Center. Moreover, plasma levels of insulin were quantified by Nantes Laboniris laboratory.

## 2.4 Glucose tolerance test and biochemical measurements

An oral glucose tolerance test was performed (2 g/kg body weight, *per os*) in 4-hour fasted rats at baseline, 6, 9 and 13 weeks. Blood was collected from the tail vein at T0, 15, 30, 45, 60, 90 and 120 minutes and then glucose concentration was determined with a calibrated rodent blood glucose meter (StatStrip, Nova Biomedical®). The area under the curve (AUC) was calculated using GraphPad PRISM® software (version 9.3.0) using the trapezoidal method.

Homeostasis Model Assessment of Insulin Resistance (HOMA-IR) was calculated using the following equation: $\frac{[(\text{fasting blood glucose (mmol/l)} \times \text{fasting plasma insulin (μU/ml)})]}{22.5}$ at the beginning and end of the protocol [40].

## 2.5. Vascular reactivity experiments

After the sacrifice (pentobarbital overdose) of the rat, the thoracic aorta was removed, cleaned of fat and connective tissue, and placed in cold Krebs solution. The artery was cut into 3-4-mm rings that were mounted on triangular wire supports and suspended in 10-mL organ baths containing Krebs solution, maintained at 37°C and gassed with carbogen (95% $O_2$ and 5% $CO_2$) [21]. The isometric tension was measured continuously with an automated isometric transducer system (EMKAbath4, EMKA technologies, France) and recorded using data acquisition software (iox version 2.9.10.25. EMKA technologies, France).

As previously described [41], the aorta rings were stretched at a resting tension of 2 g in 0.5 g steps and allowed to equilibrate for 15 min per step. Then, Cumulative Concentration-Response Curves (CCRCs) to phenylephrine (Phe), an $\alpha_1$-adrenoceptor agonist ($10^{-9}$ to $3.10^{-5}$ M), acetylcholine (Ach), a muscarinic receptor agonist ($10^{-9}$ to $3.10^{-5}$ M), and insulin (Ins) ($10^{-9}$ to $10^{-5}$ M) were performed. Ach and Ins CCRCs were constructed in Phe-precontracted rings. Contractile responses to Phe were measured as the increase in tension expressed as a percentage of the peak rise in tension caused by 80 mM KCl. The relaxant responses to Ach and Ins were calculated as the percentage change in the maximal tension of vessel rings after addition of phenylephrine.

## 2.6. Colonic reactivity experiments

After the sacrifice, the colon is removed and placed in cold Krebs solution previously carbonized ($95\% O_2$, 5% $CO_2$). After being dissected, fat-free and its contents rinsed with cold
Krebs, the colon was cut into 0.5 to 1 cm longitudinal segments (2 proximal segments approximately 3 cm from the cecum and 2 distal segments approximately 2 cm from the rectum), segments were mounted in 10-mL organ baths containing Krebs solution, maintained at 37°C and gassed with carbogen. The isometric tension was measured continuously with an automated isometric transducer system (EMKAbath4, EMKA technologies, France) and recorded in a data acquisition software (iox version 2.9.10.25. EMKA technologies, France).

Once the system is set up, a stabilization period (60 minutes) is necessary before performing the non-cumulative concentration-response curves (CCRCs). During this time the segments are stretched at a resting tension of 1 g, including a systematic flush every 15 minutes and a return to basal tension. The segment was evaluated stable after obtaining two reproducible responses to KCl (80 mM).

Then, to evaluate the colonic reactivity, non-cumulative curves are performed with KCl and Carbachol with or without prior incubation with short-chain fatty acids (SCFA): Butyrate (5mM) and propionate (5mM).

## 2.7. Colonic paracellular permeability

Following the same sampling and dissection protocol as for colonic reactivity, the segments were opened in half and placed on sliders (Area = 0.031 cm²) and finally mounted in Ussing chambers (Physiologic Instruments, San Diego, CA, USA) in 3 mL of Krebs maintained at 37°C with carbogen (95% O₂ and 5% CO₂). After 30 min of equilibration, a volume of Krebs (100 µL), from the mucosal side was collected and then replaced with 100 µL FITC-Sulfonic Acid (FSA, 400 Da). In order to evaluate the paracellular permeability, a volume of Krebs (150 µL) was taken from the serous side and replaced with fresh Krebs every half hour for 3 hours. Permeability was determined by the fluorescence slope related to time.

## 2.8. Gut microbiota analysis

**Library preparation and sequencing.** The polymerase chain reaction (PCR) technique was used to amplify regions V3-V4 of the gene coding for 16S ribosomal RNA using primers 341F and 785R [42]. Magnetic AMPure XP beads (Beckman Coulter, France) were used to clean the amplicons before adding double indexes and sequencing adapters using Illumina's Nextera XT index kit (Illumina, USA). Each library was cleaned and quantified by fluorimetry (Qubit® 2.0 Fluorometer), normalized and pooled. The pooled library was denatured prior to sequencing (2x250 pair-end, chemistry v2) using an Illumina MiSeq (Illumina, USA).

**Data processing.** A bioinformatics pipeline developed by Biofortis and based on Dadaist2 software [43] was used for sequence analysis. Basically, after demultiplexing indexed reads, single-read sequences were matched for each sample into longer fragments and cleaned up. Amplicon variant sequences (AVSs) were obtained after quality filtering and modeling of sequencing errors. In order to determine bacterial community profiles, a taxonomic assignment of these AVSs was carried out.

## 2.9 Histological analyses

Two liver lobes were sliced and fixed in 4% paraformaldehyde for 24 hours, then embedded in paraffin. Staining of the 5 µm-thick sections was then performed with hematoxylin-eosin-safron (HES) solution or 0.1% picrosirius red (steatosis and fibrosis zone). These samples were then analyzed with an automatic threshold technique using an algorithm developed in the HIFIH laboratory (EA 3859, Angers, France) as previously described [44].
## 2.10. Statistical analysis

Results were expressed as the mean ± standard error of the mean (SEM) of “n” experiments with “n” corresponding to the number of rats studied. The influence of BCA treatment on morphometric, metabolic and microbiota parameters was evaluated with Two-Way ANOVA, unpaired t test or Mann-Whitney test.

Ach and Phe CCRCs are drawn using GraphPad PRISM® software (version 9.3) and analyzed by a nonlinear mixed-effects model (NLME) using R software (RStudio 2022.12.0+353).

Data from insulin CCRCs are analyzed by a linear mixed-effects model (LME) using R software [45].

For each statistical test, a value of P<0.05 was considered to be significant.

# 3. Results

## 3.1 Effect of BCA treatment on body weight and metabolic parameters

The administration of the BCA mixture significantly reduced weight gain after 8 weeks of treatment compared to U-ObZ rats (p<0.05) (Fig 1A). Furthermore, after 13 weeks of supplementation, the weight gain reduction was accompanied by significant decreases in abdominal circumference (p<0.05), in BMI (Body Mass Index) (p<0.05, Table 1), and in adiposity index

<figure><img src="image_3.png" /><figcaption>**Fig 1.** Effect of BCA mix on body weight (A), adiposity index (B), food intake (C) and water intake (D). Data were expressed as mean ± SEM. A Mann-Whitney test or Two-way ANOVA test were used for statistical analysis. n = 8 for each group. \* p<0.05; \*\* p<0.01 BCA-ObZ vs. U-ObZ. U-ObZ: Untreated Obese Zucker; BCA-ObZ: BCA-Treated Obese Zucker.</figcaption></figure>

https://doi.org/10.1371/journal.pone.0306783.g001
<table><caption>Table 1. Effect of BCA supplementation on weight, abdominal circumference, fasting glycaemia, insulin, plasma lipids and hepatic transaminases.</caption><thead><tr><th rowspan="2"></th><th colspan="2">U-ObZ</th><th colspan="2">BCA-ObZ</th><th colspan="2">p-value<br>(between groups)</th></tr><tr><th>Baseline</th><th>13<sup>th</sup> week</th><th>Baseline</th><th>13<sup>th</sup> week</th><th>Baseline</th><th>13<sup>th</sup> week</th></tr></thead><tbody><tr><td>Weight (g)</td><td>349.20 ± 6.50</td><td>545.90 ± 5.70</td><td>349.30 ± 8.27</td><td>516.70 ± 8.15</td><td>ns</td><td>*0.0281</td></tr><tr><td>Abdominal circumference (cm)</td><td>15.41 ± 0.20</td><td>20.45 ± 0.18</td><td>15.33 ± 0.17</td><td>19.70 ± 0.27</td><td>ns</td><td>*0.034</td></tr><tr><td>BMI</td><td>0.7539 ± 0.01</td><td>0.86 ± 0.01</td><td>0.75 ± 0.01</td><td>0.82 ± 0.01</td><td>ns</td><td>*0.0499</td></tr><tr><td>Fasting glycaemia (mg/dL)</td><td>95.38 ± 2.22</td><td>109.6 ± 2.88</td><td>94.25 ± 3.519</td><td>103.0 ± 3.09</td><td>ns</td><td>ns</td></tr><tr><td>Fasting insulinemia (ng/mL)</td><td>4.806 ± 0.58</td><td>9.301 ± 1.21</td><td>4.93 ± 0.54</td><td>6.252 ± 0.73</td><td>ns</td><td>*0.0379</td></tr><tr><td>Triglycerides (g/L)</td><td>2.563 ± 0.19</td><td>3.961 ± 0.38</td><td>1.80 ± 0.19</td><td>4.65 ± 0.38</td><td>**0.0064</td><td>ns</td></tr><tr><td>Total cholesterol (g/L)</td><td>3.63 ± 0.08</td><td>5.874 ± 0.27</td><td>3.5 ± 0.15</td><td>5.194 ± 0.26</td><td>ns</td><td>ns</td></tr><tr><td>HDL-C (g/L)</td><td>2.885 ± 0.05</td><td>3.923 ± 0.19</td><td>2.838 ± 0.12</td><td>3.59 ± 0.074</td><td>ns</td><td>ns</td></tr><tr><td>ASAT (IU/L)</td><td>89.93 ± 4.15</td><td>89.53 ± 10.67</td><td>99.23 ± 7.02</td><td>107.7 ± 15.87</td><td>ns</td><td>ns</td></tr><tr><td>ALAT (IU/L)</td><td>140.8 ± 7.18</td><td>94.67 ± 13.24</td><td>154.4 ± 10.37</td><td>118.8 ± 28.46</td><td>ns</td><td>ns</td></tr><tr><td>ASAT/ALAT</td><td>0.65 ± 0.02</td><td>0.96 ± 0.04</td><td>0.65 ± 0.04</td><td>1.11 ± 0.19</td><td>ns</td><td>ns</td></tr></tbody></table>

ns: Not significant;

* p<0.05;

** p<0.01 BCA-ObZ vs. U-ObZ.

U-ObZ: U-ObZ: Untreated Obese Zucker; BCA-ObZ: BCA-Treated Obese Zucker; BMI: Body Mass Index; HDL-C = high-density lipoprotein, ASAT = aspartate aminotransferase; ALAT = alanine aminotransferase.

https://doi.org/10.1371/journal.pone.0306783.t001

(p<0.05) in BCA-ObZ rats (Fig 1B). These reductions were also associated with a decrease in food intake (p<0.05) while the water consumption was not affected (Fig 1C & 1D).

We found an increase in total cholesterol (TC) and high-density lipoprotein cholesterol (HDL-C) in both groups between baseline and week 13 in the U-ObZ rats (p<0.05) and BCA-ObZ rats (p<0.05) groups. Nevertheless, no significant differences emerged between the groups at week 13 (Table 1).

## 3.2. Effect of BCA treatment on glucose and insulin levels

The basal levels (baseline) showed no significant difference between groups in OGTT AUC and blood glucose levels over a 2-hour period after testing (Fig 2A & 2B). In addition, no difference was observed in fasting blood glucose levels. After 13 weeks, fasting blood glucose levels, AUC, and 2-hour post-OGTT blood glucose levels increased for both groups. However, the BCA mixture group had significantly lowered AUC and HOMA-IR index compared to the control group (Fig 2C & 2D).

## 3.3 Effect of BCA treatment on hepatic metabolic parameters

There was no significant change in ASAT levels from baseline to the end in either the untreated or BCA-treated group. However, the ALAT level decreased significantly in the untreated group (p = 0.0331), and decreased non-significantly in the BCA-treated group compared to baseline values. There was no significant difference observed between the two groups for the ASAT/ALAT ratio (Table 1).

Furthermore, there was no significant difference observed between the untreated and BCA-treated groups for the weighted fibrosis area (S1A Fig). While there was a trend towards a decrease in the steatosis area in the BCA-ObZ group, this difference was not significant (S1B Fig).
<figure><img src="image_4.png" /></figure>

<figure><img src="image_5.png" /></figure>

<figure><img src="image_6.png" /></figure>

<figure><img src="image_7.png" /></figure>

**Fig 2.** Effect of BCA blend on glucose and insulin metabolism. Glucose metabolism was assessed by oral glucose tolerance test (OGTT), performed at the beginning and end of the protocol. After a glucose bolus, plasma glucose was measured at baseline (A) and at week 13 of the protocol (B). The area under the curve (AUC) of OGTT was calculated at baseline and at week 13 of the protocol (C). Insulin metabolism was assessed by calculating the insulin resistance assessment model (HOMA-IR) (D). Data were expressed as mean ± SEM. A Mann-Whitney test or Unpaired t test were used for statistical analysis. n = 8 * p<0.05; *** p<0.001 BCA-ObZ vs. U-ObZ. U-ObZ: Untreated Obese Zucker; BCA-ObZ: BCA-Treated Obese Zucker.

https://doi.org/10.1371/journal.pone.0306783.g002

**3.4. Vascular reactivity**

The maximal contractile response to Phe in aortic rings from BCA-treated group was significantly lower (Emax = 78.23±7.49) than that in the U-ObZ group (Emax = 105.8±8.5) (p<0.01) (Fig 3A). In the present study, we evaluated the effects of long-term treatment with BCA on endothelium-dependent aortic relaxation using Ach and Ins. Our results showed that Ach-induced relaxation was similar in aortic rings from control (Emax = 99.2±0.8; pD2 = 7.6±0.1) and BCA group (Emax = 99.2±0.8; pD2 = 7.6±0.1) (Fig 3B). However, we found that the maximal relaxant response to Ins in aortic rings from the BCA-ObZ group (maximal response to the higher concentration was 38.6±9.5) was significantly higher than that in the control group (maximal response to the higher concentration was 22.9±6.2) (p<0.01) (Fig 3C). The treatment with the eNOS cofactors BH4 and L-Arg also enhanced the response to Ins in both
<figure><img src="image_8.png" /><figcaption>**Fig 3. Effect of BCA treatment on aortic vasoreactivity.** CCRCs were constructed to assess aortic contractile responses using phenylephrine (Phe, 10⁻⁹ to 3.10⁻⁵ M (A) and relaxation responses using acetylcholine (Ach, 10⁻⁹ to 3.10⁻⁵ M) (B), insulin (Ins, 10⁻⁹ to 10⁻⁵ M) (C) and insulin (Ins, 10⁻⁹ to 10⁻⁵ M) with or not incubated BH4 (10⁻⁵ M) and L-Arg (10⁻³ M) (D). Percentages of contraction and relaxation calculated are relative to maximal changes from pre-contraction produced by KCl and Phe, respectively. Data are expressed as mean ± SEM and determined using NLME for Phe and Ach and LME for Ins. n = 6–8 each group. **p<0.01 BCA-ObZ vs. U-ObZ. ## p<0.01 U-ObZ+BH4+Larg vs. U-ObZ. U-ObZ: Untreated Obese Zucker; BCA-ObZ: BCA-Treated Obese Zucker; BH4: Tetrahydrobiopterin; L-Arg: L-arginine; NLME Non-linear Mixed Effect; LME: Linear Mixed effect.</figcaption></figure>

https://doi.org/10.1371/journal.pone.0306783.g003

untreated (maximal response to the higher concentration was 39.9±11.5; p<0.05) and BCA-treated groups (maximal response to the higher concentration was 45.2±10.8) (Fig 3D).

### 3.5. Colonic reactivity

In the U-ObZ group, Carbachol (1 mM-100 mM) induced a contractile response of the isolated distal colonic segments that was slightly, although not significantly decreased at the higher concentrations (10 mM and 100 mM) by BCA treatment (Fig 4A). Distal colonic segments seem to exhibit a higher contractile response to Carbachol after treatment with Butyrate only in the BCA-ObZ group (Fig 4A). A similar pattern of Carbachol-induced response was seen in the BCA-ObZ group when the distal colonic segments were pretreated with propionate (Fig 4B).
A

<figure><img src="image_9.png" /></figure>

B

<figure><img src="image_10.png" /><figcaption>Fig 4. Effect of BCA mixture on carbachol-induced contraction in isolated segments of distal colon from control and BCA-treated groups. The responses were obtained after pretreatment with sodium butyrate (A) or propionate (B). Data are expressed as mean ± SEM. LME was used for statistical analysis. n = 8 for each group. U-ObZ: Untreated Obese Zucker; BCA-ObZ: BCA-Treated Obese Zucker; LME: Linear Mixed effect.</figcaption></figure>

https://doi.org/10.1371/journal.pone.0306783.g004
A

<figure><img src="image_11.png" /><figcaption>**Fig 5.** Permeability to fluorescein sulfonic acid was measured using Ussing chambers in the proximal colon (A) and in the distal colon (B). Data are expressed as mean ± SEM. The Mann-Whitney test was used for statistical analysis. n = 8 for each group. ns: Not significant; \* p<0.05 BCA-ObZ vs. U-ObZ. U-ObZ: Untreated Obese Zucker; BCA-ObZ: BCA-Treated Obese Zucker.</figcaption></figure>

B

<figure><img src="image_12.png" /></figure>

https://doi.org/10.1371/journal.pone.0306783.g005

## 3.6. Colonic paracellular permeability

The paracellular permeability of the proximal colon segments was studied in the Ussing chamber, with results indicating no significant difference in permeability when assessed over 3 hours (Fig 5A). However, in the distal colon segment, the addition of the BCA mixture resulted in a 51% reduction in FD4 flow compared with the U-ObZ group (Fig 5B).

## 3.7. Cecum morphometric parameter

We compared the morphometry of the cecum and the *ratio* of cecal weight to body weight between the BCA-ObZ and U-ObZ groups. Regarding morphological differences, our observations revealed a significant disparity, as depicted in S2A Fig. Furthermore, the cecal weights were notably greater in the BCA-ObZ group compared to the U-ObZ group (p<0.001; S2B Fig).

## 3.8 Microbiome analysis

A total of thirty-two fecal samples were collected from the two rat groups. Fecal samples were collected at the beginning and at the end of the experiment to find out the effect of the treatment using the BCA mixture on the microbiota composition. Thus, the DNA was extracted from the fecal samples from each rat at the start Week 0 and at the end week 13 and used in the amplification of V3-V4 variable region of 16S rRNA genes.

The raw sequence reads in fastq files were quality filtered and pre-processed before assessment and classification using specific software and database as mentioned in the materials and
<figure><img src="image_13.png" /><figcaption>Fig 6. The panels represent the alpha diversity measures where; A) presents the observed library (total number of AVS observed); B) presents Chao1 index is the richness estimators (estimate the total number of AVS present in a community); C) presents Simpson is microbial indexes of diversity. Boxes span the first to third quartiles; the horizontal line inside the boxes represents the median. U-ObZ: Untreated Obese Zucker; BCA-ObZ: BCA-Treated Obese Zucker.</figcaption></figure>

https://doi.org/10.1371/journal.pone.0306783.g006

methods section. The results showed library size extended from 31,702 to 47,345 reads across the sequence samples, and this consider an adequate reads per sample for taxonomic analysis. Total number of AVS's observed ranged from 123 to 414 which fit with richness estimation by Chao1 and ACE. The taxonomic levels include 11 phyla, 20 classes, 33 orders, 65 families, and 199 genera (Fig 6).

Alpha-diversity was implemented towards investigate the species complexity according to Fisher, Gini_Simpson, InvSimpson, PD, Pielou, Shannon and Simpson. The Shannon alpha-diversity index extended from 2.85 to 4.59; detected richness extended from 20.32 to 62.74 and Pielou's evenness extended from 0.59 to 0.76 (Fig 6).

At phylum level, 11 phyla were initially identified. The most represented phyla were Bacteroidetes and Firmicutes, representing an equal average relative abundance of around 45% of all samples at the start of the experiment, followed by Akkermansiaceae representing 4%, Proteobacteria 3.5% and Actinobacteria 2.5% (Fig 7).

More specifically, at the start of the experiment (baseline the U-ObZ group showed an average relative abundance for the following five phyla: Bacteroidetes 45%, Firmicutes 44.81%, Akkermansiaceae 4.26%, Proteobacteria 3.77% and Actinobacteria 2.58%. At the end of the experiment (13 weeks), this group presented 31.09% Bacteroidetes, 54.11% Firmicutes, 7.99% Akkermansiaceae, 4.77% Proteobacteria and 2.61% Actinobacteria. Similarly, at the start of the experiment, the BCA-ObZ group showed 45.81% Bacteroidetes, 42.95% Firmicutes, 5.69% Akkermansiaceae, 3.94% Proteobacteria and 1.60% Actinobacteria (S3 Fig). At the end of the experiment, this BCA-ObZ group contained 30.71% Bacteroidetes, 47.82% Firmicutes, 16.72% Akkermansiaceae, 4.30% Proteobacteria and 0.43% Actinobacteria (S3 Fig). As the results show, at the end of the experiment, the groups treated an increase in Akkermansiaceae (16.72%), followed by Firmicutes, while Actinobacteria decreased by only 0.43%.

Bacteria identified by microbiome analysis are shown in Krona plots, representing relative abundance of microbial species detected in BCA-ObZ week 0 and week 13 (S3 Fig).

At 0 week (baseline), the fecal microbiome consists of *Prevotellaceae* 28% (*Prevotella copri* 89%), *Clostridia* 28% (Romboutsia timonensis 14%), *Lactobacillales* 7% (*Lactobacillus*
<figure><img src="image_14.png" /><figcaption>**Fig 7.** The phylum composition of microbiome after the 13th week of experimentation. U-ObZ: Untreated Obese Zucker; BCA-ObZ: BCA-Treated Obese Zucker.</figcaption></figure>

https://doi.org/10.1371/journal.pone.0306783.g007

*johnsonii* 48%), *Akkermansiaceae* 6% (*Akkermansia muciniphila*), *Acidaminococcaceae* 4% (*Phascolarctobacterium faecium*), *Erysipelotrichales* 4% (*Turicibacter sanguinis* 92%), *Sutterellaceae* 3% (*Parasutterella excrementihominis*), *Ruminococcaceae* 3%.

The composition of microbiome showed changes after the 13 weeks as follows; *Prevotella-ceae* 23%, *Erysipelotrichaceae* 14% (*Turicibacter sanguinis*), *Lachnospiraceae* 12%, *Lactobacil-lales* 10% (*Ligilactobacillus apodemi* 42%, *Limosilactobacillus reuteri* 25%, *Lactobacillus johnsonii* 18%, *Lactobacillus gasseri* 15%) *Akkermansia muciniphila* 8%, *Ruminococcaceae* 6% (S3 Fig).

**4. Discussion**

In the present study we evaluated the potential effectiveness of a nutraceutical supplementa-
tion, comprising a combination of berberine and extracts of citrus and apple, in mitigating the
metabolic and functional disorders associated with obesity. To this end, we used the Zucker
rat as a genetic model of obesity and insulin resistance. The untreated obese (fa/fa) Zucker rats
showed a significant increase in weight from week 0 to week 13 that is clearly linked to features
of the metabolic syndrome (insulin resistance, dyslipidemia) as previously described
[37,46,47]. Collectively all the studies cited above have explored the individual activities of ber-
berine, apple extract or citrus extract, and have shown that these natural products exhibited
anti-obesity properties that involved multi-targets and pathways (ie reducing fat mass, improv-
ing insulin sensitivity, and increasing thermogenesis and energy expenditure and lipid break-
down). However, to the best of our knowledge, little is known about the effects due to their
combination and their long-term combined use on obesity and obesity-related metabolic and
functional alterations. Whether the potential complementary actions on the lipid/glucide
metabolism regulation, reduction of energy absorption or increase in its expenditure, or appe-
tite suppression, attributed to berberine, citrus extract and apple extract respectively, may
achieve a greater nutraceutical effect in obese Zucker rat is still unknown and remains to be
determined.

In this study we aimed to evaluate whether polyphenols from apple and citrus extracts com-
bined with the alkaloid berberine, when consumed together, could target synergistically the
obesity and related disorders in obese Zucker rat. One of the main findings of the present
study is that long-term supplementation with BCA mixture reduced weight gain, abdominal
circumference and adiposity index in treated rats compared to the untreated obese Zucker
rats. These effects may be attributed at least in part to the reduction of food intake as observed
in the treated group, and are in line with our initial hypothesis that postulated a potential sati-
ety-inducing effect of the BCA mixture. However, we cannot totally rule out the possibility
that increase energy expenditure could have been involved in the limitation of weight gain and
change of morphological parameters following BCA supplementation. The ability of berberine,
citrus, and apple extracts to potentially increase thermogenic mechanisms, such as mitochon-
drial biogenesis and UCP-1 expression, is well-documented in the literature [21,22,48,49], For
example, citrus polymethoxyflavones have been shown to enhance thermogenesis in brown
adipose tissue (BAT) and inguinal white adipose tissue (iWAT) by activating AMPK/PGC1α
signaling [17]. Similarly, apple polyphenols have been demonstrated to induce thermogenic
adaptations in iWAT, possibly through the activation of the peripheral catecholamine synthe-
sis-FGF21-PGC-1α cascade [18]. Moreover, berberine has been found to increase energy
expenditure and limit weight gain in obese mice by promoting the expression of UCP1 and
enhancing mitochondrial biogenesis [44]. While it's plausible that the observed reduction in
weight gain in the treated group could be attributed, at least in part, to increased energy expen-
diture mediated by these mechanisms, it's essential to acknowledge that our study did not
directly measure energy expenditure. Furthermore, previous studies have highlighted the
potential of berberine, citrus, and apple extracts to mitigate weight gain through various meta-
bolic pathways, including modulation of adipose tissue mass and lipid metabolism
[17,18,44,45]. To sum up, while increased energy expenditure could be a plausible mechanism
underlying the observed benefits on weight gain, our study design and existing literature sup-
port the view that the BCA supplementation exert beneficial effects through multiple metabolic
pathways. Ideally energy expenditure should have been measured in order to accurately assess
whether BCA may increase energy expenditure in addition to reduced food intake.

We next investigated the effects of BCA on whole-body metabolic homeostasis. As
expected, Zucker rats exhibited increased fasting insulin levels as well as HOMA-IR when
compared to the BCA-supplemented Zucker rats. Furthermore, untreated Zucker rats showed
impaired glucose homeostasis as assessed by *per os* glucose tolerance tests. BCA attenuated this
impairment only after 13 weeks supplementation indicating likely that this beneficial effect
may be secondary to the reduction of body weight gain as the later was observed from the 8th
week supplementation. In contrast, although the relationship still needs to be clarified, our
study failed to find any evidence that BCA-induced reduction of weight gain is linked with
change of fasting total cholesterol and fasting triglycerides. The mild inhibition in weight gain
observed in our study may be one possibility that could explain why nutraceutical supplemen-
tation did not limit the lipid disturbances occurring in treated-Zucker rats. Therefore, these
findings suggested a specific positive effect of BCA on glucose tolerance and insulin resistance
that could have been due to the large polyphenols content of BCA. However, they are at vari-
ance with the statement that apple and citrus polyphenols and berberine possess antilipidemic
properties [36,49,50]. Whether dose of BCA up to 200 mg/kg and/or a long-term
supplementation (>13 weeks) may significantly improve the lipid profile is unknown. Moreover, it is not unreasonable to postulate that antagonistic effects between the BCA ingredients could have been limited its delipidating ability at the used doses.

The functional alterations at the gut level associated with obesity, such as inflammation, permeability impairment and change of smooth muscle contractility have been poorly explored in both diet-induced obesity and specifically in obese Zucker rats. Our *in vitro* experiments revealed that colonic contractile effect following cholinergic stimulation (at the higher concentrations) was, although not significant, decreased in treated-Zucker rats. Some compounds present in BCA, notably polyphenols have been reported as signaling molecules that depress intestinal contractility [51]. Thus, although it is not necessarily valid to correlate the decreased colonic contraction of the BCA-supplemented rats with modulation of whole-animal gut transit, the potential decrease of colonic peristalsis that may occur under *in vivo* conditions supports the hypothesis that BCA supplementation may modulate, through cholinergic mechanism, the progress of the food bolus and likely the absorption of nutrients. However, it could be also suggested that the BCA-induced inhibition of colonic contractility may involve a role of gut microbiota via SCFA production. We evaluated the effect of butyrate and propionate on contractility of colonic segments obtained from untreated and BCA-treated Zucker rats. We found that carbachol-mediated contraction was increased after preincubation with propionate or butyrate. Studies investigating the effects of SCFA on intestinal contractility have shown different results depending on the muscle type studied [52,53]. The mechanism by which propionate or butyrate produces a relative potentiation of colonic response to carbachol is not readily apparent, but could involve specific local effects that may modify muscarinic receptor mechanisms or ion channels that involve calcium handling within the colonic smooth muscle cells linked to electrical coupling and contraction.

One of the objectives of the current research was also to investigate the potential benefit of BCA on the intestinal damage by exploring the change in colonic permeability using Ussing chambers. Under our experimental conditions, BCA supplementation significantly decreased the permeability of the distal colon supporting the hypothesis of a possible anti-inflammatory action of BCA that would likely result from an improvement of intestinal barrier function. In agreement with these results, berberine as apple or citrus ingredients and more broadly polyphenols have been shown to increase the expression of tight junction proteins in epithelial intestinal cells [54–56].

Metabolic syndrome and obesity are prominent risk factors contributing to the development of cardiovascular disease and are involved in the onset of endothelial dysfunction [57,58]. Obese Zucker rat is also characterized by the presence of endothelial dysfunction in addition to metabolic alterations (i.e. insulin resistance, dyslipidemia) [59–62]. However, our findings showed a great relaxant response to Ach in endothelium-intact aortic rings from control group (with a near 100% relaxation rate) which was comparable to that observed in the BCA-supplemented group. This is in line with our experience where the maximal relaxation in response to Ach in aorta from lean (Wistar) rats under the same conditions is typically in the range of 80–100%, excluding therefore the presence of endothelial dysfunction in response to muscarinic stimulation in 21-week-old obese Zucker rats. This finding aligns with previous literature reporting superior relaxation in obese Zucker rats compared to lean Zucker rats at 16-week-old [63] and in 32-week-old obese rats [60]. One of the hypotheses proposed to explain this unexpected result could be the intervention of adaptative mechanisms involving an increase in inducible nitric oxide synthase (iNOS) expression and/or in the cyclooxygenase (COX) pathway [63]. These putative mechanisms could have likely masked the beneficial effect of BCA mixture on endothelial function and could account for the decrease in maximal contraction to Phe observed in the BCA-ObZ group.
Conversely to the effect on the Ach-mediated relaxation, supplementation with BCA signif-
icantly enhanced insulin-mediated vasorelaxation, known to involve endothelial NO through
the PI3K-Akt pathway, emphasizing specific action of BCA on this signaling. We also found
that incubation of endothelium-intact aortic rings with eNOS cofactors (BH4 and L-arginine)
improved relaxation only in untreated obese rats. The reason to account for this difference is
not readily apparent. The fact that only aortic rings from control group were sensitive to cofac-
tors supplementation supports the hypothesis that insulin signaling is impaired in obese
Zucker rat. This impairment could have been attenuated under BCA supplementation and
might explain why co-factor pretreatment failed to add any improvement in insulin relaxation
in BCA-ObZ group.

Available research evidences have documented that the beneficial effects of citrus flavo-
noids, apple polyphenols and/or berberine on obesity and related disturbances could be medi-
ated by mechanisms involving gut microbiota [34,64,65]. However, their combinatory effect
on gut flora in obese Zucker rats is still unknown. We pursued this line of investigation to test
the hypothesis that the potential anti-obesity effect of BCA might partially involve a positive
modulatory effect of the gut microbiota in obese Zucker rats. We found that The BCA mixture
reduced the proportion of Firmicutes and Actinobacteria, two phylum that promote energy
absorption, letting us hypothesize that inhibition of energy absorption could be considered as
another mechanism accounting for the reduction of weight gain observed in the treated
Zucker rats. In addition, the significant increase of some genus such as *Akkermansia*, *Blautia*,
*Lactobacillus* and *Muribaculum*, known to be important producers of SCFA [66] supports the
theory that SCFA may be the link between gut microbiota and beneficial effect of BCA supple-
mentation. SCFA have been shown to play an important role in the regulation of glucose and
lipid metabolism [65,67,68] by mechanisms involving at least maintenance of the integrity of
intestinal barrier and reduction of inflammation. However, in order to confirm that BCA mix-
ture-induced reduction of colonic permeability can contribute to some of the metabolic
improvement (i.e. decrease of insulin resistance) further studies are required.

There are some limitations to the present study. Firstly, the absence of the lean Zucker rat
in the present study might be viewed as a limitation. However, we have considered that little
information would be gained by including it because the experimental design has been con-
ceived to evaluate the effects of BCA directly in the obese Zucker rats, and additional experi-
ments with their lean counterparts are not essential to the message of the present paper.
Secondly, we studied a nutraceutical mixture of berberine and plant extracts containing sev-
eral ingredients at different concentrations acting alone or in synergy and/or antagonism.
Further works would be required to assess in our experimental conditions the individual
contribution of each component of the mixture to the global activity. Thirdly, whether a pro-
longed supplementation (>13 weeks) may induce a more powerful and lasting effect on obe-
sity and related disorders in obese Zucker rat, therefore, the results must be interpreted with
caution.

Our data provide the first evidence to our knowledge for a beneficial effect of nutraceutical
mixture with berberine and extracts of apple and citrus for preventing weight gain, improving
glycemic control and insulin sensitivity in obese Zucker rat. Both aortic and colonic findings
support the hypothesis that long-term BCA supplementation has vascular and gut protective
potential that warrants further investigation. As a significant increase of SCFA-producing spe-
cies (*Akkermansia municipiphila*, *Blautia*, *Lactobacillus* and *Muribaculum*) was observed after
BCA supplementation, it is tempting to suggest that the metabolic and functional improve-
ments observed could be explained, at least in part by a positive modulatory effect of BCA on
gut microbiota. Finally, we believe that long-term BCA supplementation has the potential of a
promising therapeutic option in metabolic and vascular pathology linked to the obesity,
nevertheless further research is needed for better understanding the health-promoting effects
of BCA used as a dietary supplement.

**Supporting information**

S1 Fig. Effect of BCA mixture on liver in obese Zucker rats, quantification of area of steatosis (A) and area of fibrosis (B).

(DOCX)

S2 Fig. Effect of BCA mixture on cecum size in obese Zucker rats, representative photograph (A) and Cecum weight as a percentage of body weight (B).

(DOCX)

S3 Fig. Evolution in gut microbiota composition between week 0 (A&B) and week 13 (C&D).

(DOCX)

**Acknowledgments**

The authors would like to thank Pr Chantal THORIN for access to her nonlinear mixed-effect model for the study of aortic relaxation.

The authors would also like to thank Pr Karine PICHAVANT and Aline AMERAND for their help in setting up the inflammatory study and the realization of the PCRs.

**Author Contributions**

**Conceptualization:** Khadija Ouguerram, Jean-Claude Desfontis, Mohamed-Yassine Mallem.

**Data curation:** Sandrine Destrumelle, Nahla M. Mansour, Lionel Fizanne.

**Formal analysis:** Mohamed Siliman Misha, Nahla M. Mansour, Lionel Fizanne.

**Funding acquisition:** Khadija Ouguerram, Jean-Claude Desfontis, Mohamed-Yassine Mallem.

**Investigation:** Mohamed Siliman Misha, Sandrine Destrumelle, Dylan Le Jan, Lionel Fizanne.

**Methodology:** Mohamed Siliman Misha, Sandrine Destrumelle, Dylan Le Jan, Nahla M. Mansour, Lionel Fizanne, Jean-Claude Desfontis, Mohamed-Yassine Mallem.

**Project administration:** Mohamed Siliman Misha, Dylan Le Jan, Mohamed-Yassine Mallem.

**Software:** Sandrine Destrumelle, Nahla M. Mansour, Lionel Fizanne.

**Supervision:** Khadija Ouguerram, Jean-Claude Desfontis, Mohamed-Yassine Mallem.

**Validation:** Mohamed Siliman Misha, Sandrine Destrumelle, Khadija Ouguerram, Jean-Claude Desfontis.

**Writing – original draft:** Mohamed Siliman Misha, Khadija Ouguerram, Jean-Claude Desfontis, Mohamed-Yassine Mallem.

**Writing – review & editing:** Mohamed Siliman Misha, Sandrine Destrumelle, Dylan Le Jan, Nahla M. Mansour, Khadija Ouguerram, Jean-Claude Desfontis, Mohamed-Yassine Mallem.
References

1. Chalk MB. Obesity: addressing a multifactorial disease. Case Manag. 1 nov 2004; 15(6):47-9. https://doi.org/10.1016/j.casemgr.2004.09.001 PMID: 15557992

2. Harb AA, Shechter A, Koch PA, St-Onge MP. Ultra-processed foods and the development of obesity in adults. Eur J Clin Nutr. 1 juin 2023; 77(6):619-27. https://doi.org/10.1038/s41430-022-01225-z PMID: 36280730

3. Lin X, Li H. Obesity: Epidemiology, Pathophysiology, and Therapeutics. Front Endocrinol. 6 sept 2021; 12:706978. https://doi.org/10.3389/fendo.2021.706978 PMID: 34552557

4. Romieu I, Dossus L, Barquera S, Blottière HM, Franks PW, et al. On behalf of the IARC working group on Energy Balance and Obesity, Energy balance and obesity: what are the main drivers? Cancer Causes Control. mars 2017; 28(3):247-58.

5. Longo M, Zatterale F, Naderi J, Parrillo L, Formisano P, Raciti GA, et al. Adipose Tissue Dysfunction as Determinant of Obesity-Associated Metabolic Complications. Int J Mol Sci. 13 mai 2019; 20(9):2358. https://doi.org/10.3390/ijms20092358 PMID: 31085992

6. Hruby A, Hu FB. The Epidemiology of Obesity: A Big Picture. PharmacoEconomics. juill 2015; 33 (7):673-89. https://doi.org/10.1007/s40273-014-0243-x PMID: 25471927

7. Abarca-Gómez L, Abdeen ZA, Hamid ZA, Abu-Rmeileh NM, Acosta-Cazares B, Acuin C, et al. World-wide trends in body-mass index, underweight, overweight, and obesity from 1975 to 2016: a pooled analysis of 2416 population-based measurement studies in 128.9 million children, adolescents, and adults. The Lancet. déc 2017; 390(10113):2627-42.

8. Aleixandre De Artiñano A, Miguel Castro M. Experimental rat models to study the metabolic syndrome. Br J Nutr. 14 nov 2009; 102(9):1246-53. https://doi.org/10.1017/S0007114509990729 PMID: 19631025

9. Grundy SM. Obesity, Metabolic Syndrome, and Cardiovascular Disease. J Clin Endocrinol Metab. juin 2004; 89(6):2595-600. https://doi.org/10.1210/jc.2004-0372 PMID: 15181029

10. Wu H, Ballantyne CM. Metabolic Inflammation and Insulin Resistance in Obesity. Circ Res. 22 mai 2020; 126(11):1549-64. https://doi.org/10.1161/CIRCRESAHA.119.315896 PMID: 32437299

11. Han TS, Lean ME. A clinical perspective of obesity, metabolic syndrome and cardiovascular disease. JRSM Cardiovasc Dis. 1 janv 2016; 5:204800401663337. https://doi.org/10.1177/2048004016633371 PMID: 26998259

12. Vekic J, Zeljkovic A, Stefanovic A, Jelic-Ivanovic Z, Spasojevic-Kalimanovska V. Obesity and dyslipidemia. Metabolism. mars 2019; 92:71-81. https://doi.org/10.1016/j.metabol.2018.11.005 PMID: 30447223

13. Wondmkun YT. Obesity, Insulin Resistance, and Type 2 Diabetes: Associations and Therapeutic Implications. Diabetes Metab Syndr Obes Targets Ther. oct 2020; Volume 13:3611-6. https://doi.org/10.2147/DMSO.S275898 PMID: 33116712

14. Leggio M, Lombardi M, Caldarone E, Severi P, D'Emidio S, Armeni M, et al. The relationship between obesity and hypertension: an updated comprehensive overview on vicious twins. Hypertens Res. déc 2017; 40(12):947-63. https://doi.org/10.1038/hr.2017.75 PMID: 28978986

15. Woldemariam S, Dorner TE, Wiesinger T, Stein KV. Multi-omics approaches for precision obesity management. Wien Klin Wochenschr. 2023; 135(5-6):113-24.

16. Clinical Practice Guidelines for the management of overweight and obesity | NHMRC [Internet]. [cité 20 mars 2024]. Disponible sur: https://www.nhmrc.gov.au/about-us/publications/clinical-practice-guidelines-management-overweight-and-obesity.

17. NHANES—National Health and Nutrition Examination Survey Homepage [Internet]. [cité 25 janv 2024]. Disponible sur: https://www.cdc.gov/nchs/nhanes/index.htm.

18. Ammendola S, Scotto d'Abusco A. Nutraceuticals and the Network of Obesity Modulators. Nutrients. 1 déc 2022; 14(23):5099. https://doi.org/10.3390/nu14235099 PMID: 36501129

19. Och A, Och M, Nowak R, Podgórska D, Podgórski R. Berberine, a Herbal Metabolite in the Metabolic Syndrome: The Risk Factors, Course, and Consequences of the Disease. Molecules. 17 févr 2022; 27 (4):1351. https://doi.org/10.3390/molecules27041351 PMID: 35209140

20. Jack BU, Malherbe CJ, Mamushi M, Muller CJF, Joubert E, Louw J, et al. Adipose tissue as a possible therapeutic target for polyphenols: A case for Cyclopia extracts as anti-obesity nutraceuticals. Biomed Pharmacother. déc 2019; 120:109439. https://doi.org/10.1016/j.biopha.2019.109439 PMID: 31590126

21. Kou G, Hu Y, Jiang Z, Li Z, Li P, Song H, et al. Citrus aurantium L. polymethoxyflavones promote thermogenesis of brown and white adipose tissue in high-fat diet induced C57BL/6J mice. J Funct Foods. avr 2020; 67:103860.
22. Tamura Y, Tomiya S, Takegaki J, Kouzaki K, Tsutaki A, Nakazato K. Apple polyphenols induce brow-
ning of white adipose tissue. J Nutr Biochem. mars 2020; 77:108299. https://doi.org/10.1016/j.jnutbio.
2019.108299 PMID: 31841959

23. Garza-Juárez A, Pérez-Carrillo E, Arredondo-Espinoza EU, Islas JF, Benítez-Chao DF, Escamilla-García E. Nutraceuticals and Their Contribution to Preventing Noncommunicable Diseases. Foods. 30 août 2023; 12(17):3262. https://doi.org/10.3390/foods12173262 PMID: 37685194

24. Kim YC, Ki SW, Kim H, Kang S, Kim H, Go G woong. Recent Advances in Nutraceuticals for the Treatment of Sarcopenic Obesity. Nutrients. 4 sept 2023; 15(17):3854. https://doi.org/10.3390/nu15173854 PMID: 37686886

25. Stuby J, Gravestock I, Wolfram E, Pichierri G, Steurer J, Burgstaller JM. Appetite-Suppressing and Satiety-Increasing Bioactive Phytochemicals: A Systematic Review. Nutrients. 17 sept 2019; 11(9):2238. https://doi.org/10.3390/nu11092238 PMID: 31533291

26. Bertuccioli A, Cardinali M, Biagi M, Moricoli S, Morganti I, Zonzini GB, et al. Nutraceuticals and Herbal Food Supplements for Weight Loss: Is There a Prebiotic Role in the Mechanism of Action? Microorganisms. 25 nov 2021; 9(12):2427. https://doi.org/10.3390/microorganisms9122427 PMID: 34946029

27. Dong C, Yu J, Yang Y, Zhang F, Su W, Fan Q, et al. Berberine, a potential prebiotic to indirectly promote Akkermansia growth through stimulating gut mucin secretion. Biomed Pharmacother. juill 2021; 139:111595. https://doi.org/10.1016/j.biopha.2021.111595 PMID: 33862492

28. Fong C, Alesi S, Mousa A, Moran LJ, Deed G, Grant S, et al. Efficacy and Safety of Nutrient Supplements for Glycaemic Control and Insulin Resistance in Type 2 Diabetes: An Umbrella Review and Hierarchical Evidence Synthesis. Nutrients. 30 mai 2022; 14(11):2295. https://doi.org/10.3390/nu14112295 PMID: 35684094

29. Affuso F. A nutraceutical combination improves insulin sensitivity in patients with metabolic syndrome. World J Cardiol. 2012; 4(3):77. https://doi.org/10.4330/wjc.v4.i3.77 PMID: 22451856

30. Howes MJR. Phytochemicals as Anti-inflammatory Nutraceuticals and Phytopharmaceuticals. In: Immunity and Inflammation in Health and Disease [Internet]. Elsevier; 2018 [cité 13 sept 2023]. p. 363–88. https://linkinghub.elsevier.com/retrieve/pii/B9780128054178000287

31. Takechi R, Pallebage-Gamarallage MM, Lam V, Giles C, Mamo JC. Nutraceutical agents with anti-inflammatory properties prevent dietary saturated-fat induced disturbances in blood-brain barrier function in wild-type mice. J Neuroinflammation. déc 2013; 10(1):842. https://doi.org/10.1186/1742-2094-10-73 PMID: 23782872

32. Caponio G, Lippolis T, Tutino V, Gigante I, De Nunzio V, Milella R, et al. Nutraceuticals: Focus on Anti-Inflammatory, Anti-Cancer, Antioxidant Properties in Gastrointestinal Tract. Antioxidants. 28 juin 2022; 11(7):1274. https://doi.org/10.3390/antiox11071274 PMID: 35883765

33. Xiong H, Wang J, Ran Q, Lou G, Peng C, Gan Q, et al. Hesperidin: A Therapeutic Agent For Obesity. Drug Des Devel Ther. nov 2019;Volume 13:3855–66. https://doi.org/10.2147/DDDT.S227499 PMID: 32009777

34. Tung YC, Chang WT, Li S, Wu JC, Badmeav V, Ho CT, et al. Citrus peel extracts attenuated obesity and modulated gut microbiota in mice with high-fat diet-induced obesity. Food Funct. 2018; 9(6):3363–73. https://doi.org/10.1039/c7fo02066j PMID: 29855643

35. Jiang T, Gao X, Wu C, Tian F, Lei Q, Bi J, et al. Apple-Derived Pectin Modulates Gut Microbiota, Improves Gut Barrier Function, and Attenuates Metabolic Endotoxemia in Rats with Diet-Induced Obesity. Nutrients. 29 févr 2016; 8(3):126. https://doi.org/10.3390/nu8030126 PMID: 26938554

36. Susilowati R, Jannah J, Maghfuroh Z, Kusuma M. Antihyperlipidemic effects of apple peel extract in high-fat diet-induced hyperlipidemic rats. J Adv Pharm Technol Res. 2020; 11(3):128. https://doi.org/10.4103/japtr.JAPTR_28_20 PMID: 33102196

37. Durham HA, Truett GE. Development of insulin resistance and hyperphagia in Zucker fatty rats. Am J Physiol-Regul Integr Comp Physiol. mars 2006; 290(3):R652–8. https://doi.org/10.1152/ajpregu.00428. 2004 PMID: 16223850

38. Leonard BL, Watson RN, Loomes KM, Phillips ARJ, Cooper GJ. Insulin resistance in the Zucker diabetic fatty rat: a metabolic characterisation of obese and lean phenotypes. Acta Diabetol. déc 2005; 42 (4):162–70. https://doi.org/10.1007/s00592-005-0197-8 PMID: 16382303

39. Chiou WF, Chen J, Chen CF. Relaxation of corpus cavernosum and raised intracavernous pressure by berberine in rabbit: Berberine relaxes corpus cavernosum. Br J Pharmacol. déc 1998; 125(8):1677–84.

40. Antunes LC, Elkfury JL, Jornada MN, Foletto KC, Bertoluci MC. Validation of HOMA-IR in a model of insulin-resistance induced by a high-fat diet in Wistar rats. Arch Endocrinol Metab. avr 2016; 60(2):138–42. https://doi.org/10.1590/2359-3997000000169 PMID: 27191048
41. Doghri Y, Chetaneau F, Rhimi M, Kriaa A, Lalanne V, Thorin C, et al. Sildenafil citrate long-term treatment effects on cardiovascular reactivity in a SHR experimental model of metabolic syndrome. PLoS ONE. 7 nov 2019; 14(11):e0223914. https://doi.org/10.1371/journal.pone.0223914 PMID: 31697707

42. Klindworth A, Pruesse E, Schweer T, Peplies J, Quast C, Horn M, et al. Evaluation of general 16S ribosomal RNA gene PCR primers for classical and next-generation sequencing-based diversity studies. Nucleic Acids Res. 1 janv 2013; 41(1):e1-e1. https://doi.org/10.1093/nar/gks808 PMID: 22933715

43. Ansorge R, Birolo G, James SA, Telatin A. Dadaist2: A Toolkit to Automate and Simplify Statistical Analysis and Plotting of Metabarcoding Experiments. Int J Mol Sci. 18 mai 2021; 22(10):5309. https://doi.org/10.3390/ijms22105309 PMID: 34069990

44. Coué M, Tesse A, Falewée J, Aguesse A, Croyal M, Fizanne L, et al. Spirulina Liquid Extract Protects against Fibrosis Related to Non-Alcoholic Steatohepatitis and Increases Ursodeoxycholic Acid. Nutrients. 18 janv 2019; 11(1):194. https://doi.org/10.3390/nu11010194 PMID: 30669332

45. Thorin C, Mallem MY, Noireaud J, Gogny M, Desfontis JC. Nonlinear mixed effects models applied to cumulative concentration-response curves. J Pharm Pharmacol. 25 mars 2010; 62(3):339-45. https://doi.org/10.1211/jpp.62.03.0008 PMID: 20487217

46. Saito T, Toriniwa Y, Ishii Y, Uemura A, Miyajima K, Uno K, et al. Hepatic lesions induced by feeding Western diets to Zucker fatty rats, an insulin-resistant model. J Toxicol Pathol. 2018; 31(4):283-91. https://doi.org/10.1293/tox.2018-0016 PMID: 30393432

47. Garcés-Rimón M, González C, Vera G, Uranga JA, López-Fandiño R, López-Miranda V, et al. Pepsin Egg White Hydrolysate Improves Glucose Metabolism Complications Related to Metabolic Syndrome in Zucker Fatty Rats. Nutrients. 3 avr 2018; 10(4):441. https://doi.org/10.3390/nu10040441 PMID: 29614007

48. Wang Q, Xu X, Jiang X, Yin F. Berberine regulates UCP1 expression by reshaping the conformation of quadruplex formed by the element of the UCP1 gene promoter. Acta Biochim Biophys Sin. 1 nov 2022; 54(11):1757-60.

49. Mallick N, Khan RA. Antihyperlipidemic effects of Citrus sinensis, Citrus paradisi, and their combinations. J Pharm Bioallied Sci. 2016; 8(2):112-8. https://doi.org/10.4103/0975-7406.171727 PMID: 27134462

50. Wu M, Yang S, Wang S, Cao Y, Zhao R, Li X, et al. Effect of Berberine on Atherosclerosis and Gut Microbiota Modulation and Their Correlation in High-Fat Diet-Fed ApoE-/- Mice. Front Pharmacol. 13 mars 2020; 11:223. https://doi.org/10.3389/fphar.2020.00223 PMID: 32231564

51. Curci F, Corbo F, Clodoveo ML, Salvagno L, Rosato A, Corazza I, et al. Polyphenols from Olive-Mill Wastewater and Biological Activity: Focus on Irritable Bowel Syndrome. Nutrients. 16 mars 2022; 14 (6):1264. https://doi.org/10.3390/nu14061264 PMID: 35334922

52. Ono S, Karaki S ichiro, Kuwahara A. Short-Chain Fatty Acids Decrease the Frequency of Spontaneous Contractions of Longitudinal Muscle via Enteric Nerves in Rat Distal Colon. Jpn J Physiol. 2004; 54 (5):483-93. https://doi.org/10.2170/jjphysiol.54.483 PMID: 15667672

53. Shaidullov IF, Sorokina DM, Sitdikov FG, Hermann A, Abdulkhakov SR, Sitdikova GF. Short chain fatty acids and colon motility in a mouse model of irritable bowel syndrome. BMC Gastroenterol. déc 2021; 21(1):37. https://doi.org/10.1186/s12876-021-01613-y PMID: 33499840

54. Nunes C, Freitas V, Almeida L, Laranjinha J. Red wine extract preserves tight junctions in intestinal epithelial cells under inflammatory conditions: implications for intestinal inflammation. Food Funct. 2019; 10(3):1364-74. https://doi.org/10.1039/c8fo02469c PMID: 30735221

55. Bernardi S, Del Bo' C, Marino M, Gargari G, Cherubini A, Andrés-Lacueva C, et al. Polyphenols and Intestinal Permeability: Rationale and Future Perspectives. J Agric Food Chem. 19 févr 2020; 68 (7):1816-29. https://doi.org/10.1021/acs.jafc.9b02283 PMID: 31265272

56. Wang K, Jin X, Chen Y, Song Z, Jiang X, Hu F, et al. Polyphenol-Rich Propolis Extracts Strengthen Intestinal Barrier Function by Activating AMPK and ERK Signaling. Nutrients. 7 mai 2016; 8(5):272. https://doi.org/10.3390/nu8050272 PMID: 27164138

57. Kajikawa M, Higashi Y. Obesity and Endothelial Function. Biomedicines. 19 juill 2022; 10(7):1745. https://doi.org/10.3390/biomedicines10071745 PMID: 35885049

58. Lobato NS, Filgueira FP, Akamine EH, Tostes RC, Carvalho MHC, Fortes ZB. Mechanisms of endothelial dysfunction in obesity-associated hypertension. Braz J Med Biol Res. mai 2012; 45(5):392-400. https://doi.org/10.1590/s0100-879x2012007500058 PMID: 22488221

59. Chinen I, Shimabukuro M, Yamakawa K, Higa N, Matsuzaki T, Noguchi K, et al. Vascular Lipotoxicity: Endothelial Dysfunction via Fatty-Acid-Induced Reactive Oxygen Species Overproduction in Obese Zucker Diabetic Fatty Rats. Endocrinology. 1 janv 2007; 148(1):160-5. https://doi.org/10.1210/en.2006-1132 PMID: 17023526
60. Subramanian R, MacLeod KM. Age-dependent changes in blood pressure and arterial reactivity in obese Zucker rats. Eur J Pharmacol. sept 2003; 477(2):143-52. https://doi.org/10.1016/j.ejphar.2003.08.003 PMID: 14519418

61. Eringa EC, Stehouwer CDA, Roos MH, Westerhof N, Sipkema P. Selective resistance to vasoactive effects of insulin in muscle resistance arteries of obese Zucker (fa/fa) rats. Am J Physiol-Endocrinol Metab. nov 2007; 293(5):E1134-9.

62. Tran V, De Silva TM, Sobey CG, Lim K, Drummond GR, Vinh A, et al. The Vascular Consequences of Metabolic Syndrome: Rodent Models, Endothelial Dysfunction, and Current Therapies. Front Pharma- col. 4 mars 2020; 11:148. https://doi.org/10.3389/fphar.2020.00148 PMID: 32194403

63. Vendrame S, Kristo AS, Schuschke DA, Klimis-Zacas D. Wild blueberry consumption affects aortic vascular function in the obese Zucker rat. Appl Physiol Nutr Metab. févr 2014; 39(2):255-61. https://doi.org/10.1139/apnm-2013-0249 PMID: 24476483

64. Zhang W, Xu JH, Yu T, Chen QK. Effects of berberine and metformin on intestinal inflammation and gut microbiome composition in db/db mice. Biomed Pharmacother. oct 2019; 118:109131. https://doi.org/10.1016/j.biopha.2019.109131 PMID: 31545226

65. Balderas C, De Ancos B, Sánchez-Moreno C. Bile Acids and Short-Chain Fatty Acids Are Modulated after Onion and Apple Consumption in Obese Zucker Rats. Nutrients. 5 juill 2023; 15(13):3035. https://doi.org/10.3390/nu15133035 PMID: 37447361

66. Liu MJ, Yang JY, Yan ZH, Hu S, Li JQ, Xu ZX, et al. Recent findings in Akkermansia muciniphila-regulated metabolism and its role in intestinal diseases. Clin Nutr. oct 2022; 41(10):2333-44. https://doi.org/10.1016/j.clnu.2022.08.029 PMID: 36113229

67. Cheng Y, Liu J, Ling Z. Short-chain fatty acids-producing probiotics: A novel source of psychobiotics. Crit Rev Food Sci Nutr. 3 oct 2022; 62(28):7929-59. https://doi.org/10.1080/10408398.2021.1920884 PMID: 33955288

68. Nogal A, Valdes AM, Menni C. The role of short-chain fatty acids in the interplay between gut microbiota and diet in cardio-metabolic health. Gut Microbes. 1 janv 2021; 13(1):1897212. https://doi.org/10.1080/19490976.2021.1897212 PMID: 33764858