Amur linden honey and its principal polyphenols alleviate obesity and regulate gut microbiota in high-fat diet-induced mice

Abstract

Obesity has emerged as a critical global health challenge in recent decades, driving increased scientific interest in honey as a sugar alternative. Despite its perceived nutritional benefits, the inherent high fructose-glucose ratio in honey continues to raise concerns regarding metabolic implications for overweight individuals. In this study, Amur linden honey (LH) was evaluated as a low-glycemic-index (GI) dietary intervention, demonstrating significant anti-obesity effects through murine model. Subsequently, nine principal polyphenols (PC) were identified by metabolomics and proven anti-obesity activity in cellular assays, suggesting their potential role in mediating the biological effects of LH. Notably, the anti-obesity effects of LH were more pronounced as compared to the equivalent amount of glucose and fructose, and this effect was further facilitated by addition of the PC. Furthermore, LH and HP (LH with the addition of PC) attenuate obesity by modulating gut microbiota, promoting production of SCFA especially acetate and propionate etc., and activating the AMPK/PI3K/AKT pathways. The present study revealed that LH, enriched with diverse bioactive compounds, presents the potential to be a healthy and safe sugar substitutes due to its positive effects on the obesity.

Graphical abstract

Amur linden honey and the addition of polyphenol complex alleviate obesity in HFD-induced mice by regulating gut microbiota, SCFAs production, and AMPK/PI3K/AKT pathways, suggesting it as a potential natural sugar substitute.

Highlights

• •Amur linden honey (LH) controls obesity in mice, especially at high-doses.
• •Identification and quantification of nine major polyphenols by metabolomics to explore their anti-obesity effects.
• •LH and HP (LH with the addition of PC) significantly alleviated obesity compared to isocaloric glucose and fructose intake.
• •LH and HP regulated gut microbiota disorders, SCFA production, and the AMPK/PI3K/AKT pathways.
• •LH could be a safe and healthy natural sugar substitute, because of its active constituents.

1. Introduction

High-sugar and high-fat diets are recognized as major contributors to glycolipid metabolism disorders, leading to obesity, insulin resistance, hypertension, hyperlipidemia, etc. (Saklayen, 2018). Consequently, there is a growing demand for sweeteners to reduce sugar intake, especially in obesity individuals (Mejia & Pearlman, 2019). Artificial sweeteners (erythritol, stevia and sucralose, etc.) in wide range of foods and beverages can be used as alternatives to added sugars in food industry. Although the chronic safety profile of artificial sweeteners remains controversial, emerging evidence have shown that long-term consumption of artificial sweeteners may lead paradoxically induce hyperglycemia and is associated with elevated risks of cardiovascular and cerebrovascular disease, inflammation, and cancer (Witkowski et al., 2023). Therefore, there is a need to develop natural sweeteners that not only align with sensory preferences but also safe and beneficial to the human.

Honey, as a functional food with dual medicinal and nutritional properties, has been recognized as the oldest sweetener and used in a wide range of applications such as food and medicine (Alvarez-Suarez, Tulipani, Romandini, Bertoli, & Battino, 2009). However, the excessive content of glucose and fructose in honey often raises concerns about whether its use as a sugar substitute is safe and effective, particularly among obese individuals monitoring carbohydrate intake (Farakla et al., 2018). This concern has not been specifically addressed in previous studies. Amur linden honey (LH), classified as a premium-grade monofloral honey with higher content of bioactive ingredients, especially polyphenols (Al-Waili et al., 2014), prompts the exploration of its potential as a healthier sugar substitute.

Bioactive components include polyphenols, flavonoids and peptides, providing various health benefits including anti-diabetic, anti-obesity, antioxidant and antibacterial effects (Wadi, 2022; Zhu, Zhao, Wang, Wu, & Cao, 2020). The AMPK and AKT signaling pathways significantly influence insulin sensitivity and energy metabolism, and their dysregulation contributes to obesity progression by affecting fatty acid oxidation and synthesis, thereby modifying lipid metabolism. (Bao et al., 2020; Day, Ford, & Steinberg, 2017; Lu et al.; Xu, Zhou, Lu, & Chang, 2021). In our previous study, honey-derived chrysin was demonstrated to alleviate diabetes and its complications by activating the AMPK signaling pathway (Zhou et al., 2021). Additionally, there are reports that natural active substances have a significant regulatory effect on intestinal flora disorders caused by obesity (Guerra-Valle, Orellana-Palma, & Petzold, 2022). Thus, those have a great potential to be the major active ingredients in the hypoglycemic effect of honey. Targeted metabolomics documents, identifies, and quantifies metabolites in various biological systems using modern analytical platforms, covering a wide range of naturally active metabolic intermediates such as polyphenols, lipids, organic acids, amino acids, etc.(S. Shen, Zhan, Yang, Fernie, & Luo, 2023). This approach, which we can utilize for the analysis of active components in honey, will further enhance its health benefits and greatly increase its use in sugar substitutes.

Now only a few studies have reported health effects of honey as sugar substitute on normal mice (Chen et al., 2022; Vijan, Mazilu, Enache, Enache, & Topala, 2023). Current studies lack standardized guidelines for honey consumption in weight management interventions (25 g/60 kg adult (World Health, 2015)), and not explore major effective substances and specific mechanism of action in depth. Given the urgent demand for healthy sugar alternatives in obesity management, honey has emerged as a potential substitute. However, its safety profile and therapeutic efficacy in obese populations remain undetermined, particularly due to its inherent high fructose content. Based on these considerations, we extra validated the effect of LH in obese mice through comparative studies with the equal amounts of fructose and glucose intake, while systematically investigating its major effective substances and specific mechanism of action in depth.

In the present study, commencing with the determination of the glycemic index (GI) of LH, followed by a systematic investigation of its therapeutic effects on obese mice. Comprehensive metabolomics profiling was conducted to characterize the bioactive constituents in LH, and the cell experiments were conducted to demonstrate their anti-obesity effects. Following this, in the next round of animal experiments, three improvements were made: in an effort to make it safer to use in obese patients, the dosage of LH was appropriately adjusted downward on the basis of the previous dosage (Al-Waili et al., 2014); validating the effect of LH with the addition of nine principal components (PC) on obese mice to explore whether the PC play the key role; investigating the influence of consuming glucose and fructose in amounts equal to those contained in honey to validate the health effects of LH. Furthermore, this study evaluated gut microbiota, the SCFA contents, and the AMPK/AKT signaling pathways to reveal the mechanism of LH and the addition of PC on obesity. Consequently, our study provides a theoretical basis for the use of LH as a healthy and safe sweetener for obese individuals, as well as to alleviate the nutritional development value of LH.

2. Materials and methods

2.1. Sample Preparation

Amur linden honey (Nutrient composition in Table S8) and rape honey (RH) was purchased from Shanghai sfybee Co. Ltd., Shanghai, China. LH total polyphenol extracts (PE) and the combination of nine principal polyphenols (PC) preparation were performed according to methods established in the laboratory (Zou, Tao, & Chang, 2022).

2.2. Animals and Experimental Grouping

All the specific pathogen-free (SPF) grade C57BL/6 J mice (male, 4 weeks, 10 ± 2 g) were purchased from Shanghai JieSiJie Laboratory Animal Co. Ltd. (Shanghai, China), and sheltered in a controlled environmental condition (23 ± 2 °C, 50 ± 10 % RH, and 12 h day/night cycle) with free access to food and water.

GI value measurement of LH (n = 12): Three independent feeding trials were conducted, including two times of glucose and one time of LH. Mice were given 2.0 g/kg B.W. carbohydrate in each feeding experiment, and then fasting blood glucose and postprandial blood glucose values of 15, 30, 45, 60, 90 and 120 min were detected and recorded.

Effects of LH on obese mice (four groups, n = 6): (a) Control: mice fed with standard diet (AIN-93G); (b) HFD: mice fed with high-fat diet (D12492, Research Diets Inc.); (c) HFD + HL: mice fed with high-fat diet and gavaged with low-dose LH (1.56 g/kg B.W./d); (d) HFD + HH: mice fed with high-fat diet and gavaged with high-dose LH (3.13 g/kg B.W./d); Group (a) and (b) were administered equivalent volumes of water via oral gavage during 12-week murine intervention experiment, with body weight and food intake measurements recorded at two-day intervals.

Effects of PC addition to LH on obese mice (five groups, n = 6): (a) Control: mice fed with standard diet; (b) HFD: mice fed with high-fat diet; (c) HFD + LH: mice fed with high-fat diet and gavaged with LH (2.5 g/kg B.W./d); (d) HFD + HP: mice fed with high-fat diet and gavaged with LH (2.5 g/kg B.W./d) and PC (0.675 mg/kg B.W./d); (e) HFD + GF: mice fed with high-fat diet and gavaged with a mixture of glucose (0.93 g/kg B.W./d) and fructose (1.07 g/kg B.W./d), which equaled to that found in LH (2.5 g/kg B.W./d). Group (a) and (b) were administered equivalent volumes of water via oral gavage during 12-week murine intervention experiment, with body weight and food intake measurements recorded at two-day intervals.

At the end of 12-week experiment, mice were anesthetized fasted for 12 h and then anesthetized intraperitoneally with avertin. Following euthanasia, blood samples were collected via orbital puncture, centrifuged to isolate serum, and stored at −80 °C for further assay. Tissues and organs were weighed and stored at −80 °C. Liver specimens were dissected and fixed in 4 % neutral buffered formalin for histopathological analysis.

The dosage setting in this animal experiment has taken into consideration the recommended healthy intake for humans, providing a strong theoretical basis for honey substitutes. The World Health Organization (WHO) recommends a daily intake of 25 g of free sugars for adults (based on a 60 kg individual)(World Health, 2015). Given that sugar substitutes generally administered at ≤50 % of the standard sucrose intake, the adjusted sugar intake for mice was established at 2.5 g/kg B.W./d. Based on honey's typical sugar content of 80 % (w/w), the corresponding honey dosage was calculated as 3.13 g/kg B.W./d, with a sub-therapeutic dose of 1.56 g/kg B.W./d implemented for comparative analysis.

In the ‘Effects of PC addition to LH on obese mice’ experiment, honey (primarily containing sugar components) was administered at a safety-verified dosages of 2.5 g/kg B.W./d. Each 2.5 g of honey aliquot contains 0.675 mg polyphenols. To explore whether polyphenols promote the effects of honey, we doubled the total polyphenol concentration in the honey formulation, the polyphenol extra dosage was therefore 0.675 mg/kg B.W./d.

2.3. GI Value Measurement

The standard method for the determination of human GI (ISO method 26,642:2010) has been modified for use in C57BL/6 J mice (Campbell, Belobrajdic, & Bell-Anderson, 2018).

2.4. UPLC-MS/MS analysis of metabolomics

2.4.1. Sample preparation and extraction

The sample was added proportionally to the 70 % methanol water internal standard extract (600 μL extractant per 50 mg sample) at −20 °C, vortex (15 min), and centrifuge (12,000 r/min, 4 °C, 3 min). Then, the obtained supernatant was filtered by microporous membrane (0.22 μm).

2.4.2. UPLC-MS/MS conditions

The sample extracts were analyzed using an UPLC-ESI-MS/MS system (UPLC, ExionLC™ AD) and Tandem mass spectrometry system. After obtaining the metabolite profiling data of different samples, peak area integration was performed for all the substance chromatographic peaks and the integration was corrected for the mass spectrometry peaks of the same metabolite in different samples among them (Fraga, Clowers, Moore, & Zink, 2010). In all the elements analyzed in this metabolomics, two main approaches were taken to process the data during the analysis, which were calculated as follows:

$${log}_2\mathrm{FC}={log}_2\mathrm{RH}\left(\text{Fold Change}\right)-{log}_2\mathrm{LH}\left(\text{Fold Change}\right)$$

$$\mid \mathrm{RH}-\mathrm{LH}\mid =\text{Absolute value}\left(\mathrm{RH}-\mathrm{LH}\right)$$

$$\text{Compound ratio}=\frac{\text{Compound}}{\text{Total amount of the Compounds corresponding to Class}\mathrm{I}}$$

$$\text{Average ratio}=\frac{\left(\text{Compound ratio in}\mathrm{LH}\right)+\left(\text{Compound ratio in}\mathrm{LH}\right)}{2}$$

2.5. Determination of antioxidant activity of LH in vitro

2.5.1. Determination of total reducing power:

0.1 M PBS buffer (pH = 6.6), 0.1 % (w/v) FeCl₃ solution, 1 % (w/v) K₃[Fe(CN)₆] solution, and 10 % (w/v) trifluoroacetic acid solution was prepared. Each concentration of LH solution or Vc solution was mixed with dH₂O as solvent. The reaction conditions are 50 °C for 20 mins in a thermostatic water bath, measured absorbance at 700 nm.

2.5.2. DPPH free radical scavenging capacity assay

DPPH working solution: DPPH radical solution 0.2 mg/mL was prepared by dissolving in anhydrous ethanol was diluted to 0.1 mg/mL with dH₂O. Each concentration of sample solution or Vc solution was mixed with DPPH working solution. React for 30 min at room temperature away from light. The absorbance A_s was measured at 525 nm.

2.5.3. 2.5.3 Determination of ·OH radical scavenging ability:

FeSO₄ solution (6 mmol/L) and H₂O₂ solution (6 mmol/L) were prepared in dH₂O. 6 mmol/L salicylic acid solution was prepared in 70 % ethanol. Incubate the mixture for 30 min at room temperature away from light. The absorbance A_s was measured at 510 nm.

2.5.4. 2.5.4 Determination of ABTS·⁺ radical scavenging ability:

Prepare an ABTS reservoir solution and dilute it into a working solution(Zou et al., 2022). Incubate the mixture for 20 min at room temperature away from light. The absorbance A_s was measured at 734 nm.

2.6. The effects of PE and PC on the lipid accumulation model of HepG2 cells

HepG2 cells cultured in DMEM medium for 12 h. The control, modelling and experimental groups were replaced with DMEM medium and DMEM medium with different concentrations of PE and PC for 24 h, followed by oleic acid (OA) challenge for 24 h. After modelling, intracellular lipid accumulation of different groups was quantified through Oil Red O staining. Subsequently, cells were lysed and total protein content was determined using the BCA assay kit, the cellular total cholesterol (TC), triglyceride (TG) contents were determined according to the procedure in the kit. All biochemical parameters expressed as the concentration per unit weight of protein.

2.7. The effects of PE and PC on the insulin resistance model of HepG2 cells

HepG2 cells were initially cultured in low-glucose (LG) DMEM medium for 12 h. The control, modelling and experimental groups were replaced with LG medium, high glucose (HG) medium, HG medium with different concentrations of PE and PC for 24 h, followed by induction with oleic acid (OA) solution. After PBS washing (×2), the cells were treated with 3 mL of 2-NBDG incubation solution and incubated for 30 min at 37 °C. Fluorescence intensity was determined by flow cytometry and fluorescence microscope.

2.8. Histological Analysis

Liver tissues were fixed in 4 % formalin solution at room temperature for 24 h, followed by paraffin embedding to prepare tissue sections (5 μm thickness).The sections were stained with hematoxylin and eosin (H&E) (Servicebio, WH, China) and imaged using an optical microscope.

2.9. Detection of glucose homeostasis in blood

Oral glucose tolerance test (OGTT) was performed at the 11th week of the intervention experiment. After 12 h fasting, glucose solution (2 g/kg B.W.) was administered via oral gavage. Blood samples were collected through tail vein puncture at 0, 15, 30, 60, 90, and 120 min post-administration for blood glucose level detection. The area under the time-blood glucose curve (AUC) was calculated. The homeostasis model assessment-insulin resistance (HOMA-IR) score was calculated as follows:

$$\text{HOMA}-\mathrm{IR}=\frac{\text{fasting glucose}\left(\text{mmol}/\mathrm{L}\right)\times \text{fasting insulin}\left(\mathrm{\mu U}/\mathrm{mL}\right)}{22.5}$$

2.10. Detection of blood lipid and serum biochemical analysis

Levels of insulin (INS) in mice serum were measured using an ELISA kit (Jining, SH, China); Blood glucose levels were detected using a portable blood glucose meter (Johnson & Johnson, New Jersey, USA) from a tail prick; The concentrations of TC, TG, high density lipoprotein cholesterol (HDL-c), low density lipoprotein cholesterol (LDL-c), aminotransferase (AST) and alanine aminotransferase (ALT) were performed with biochemical assay kits (Nanjingjiancheng, NJ, China).

2.11. 16S rRNA sequencing and gut Microbiota analysis

Paired end sequencing was employed utilizing the Illumina NovaSeq platform. After reads splicing filtering, clustering or noise reduction methods generate representative sequences, which can be used for species annotation and abundance analysis. Sample preparation (n = 6) for the metabonomic analysis and data analysis was performed using the Metware Cloud (Metware, WH, China), a free online platform for data analysis (https://cloud.metware.cn).

2.12. SCFA profile analysis

Fecal SCFA concentrations were quantified by GC. To fully extract SCFA from the samples, cecal contents were homogenized thoroughly in H₂SO₄ solution, and diethyl ether containing 2-ethylbutyric acid (8 mM, internal standard) were added. The extracted SCFA were centrifuged to acquire the supernatant after ice bath shaker, repeat the addition of ether twice. The SCFA in the supernatant, comprising acetate, propionate, and butyrate, were quantified using GC (Shimadzu, Japan) equipped with an SH-Stabilwax-DA capillary column (30 m × 0.25 mm × 0.25 μm). The internal standard method was used to quantify the contents of SCFA.

2.13. Quantitative real-time polymerase chain reaction (qRT-PCR) analysis of liver mRNA expression

Total RNA was extracted from the liver tissue using the SteadyPure Quick RNA Extraction Kit and cDNA synthesis with Evo M-MLV RT Mix Kit. The qRT-PCR analyses were conducted using the SYBR Green Premix Pro Taq HS qPCR Kit. All operations experimental procedures strictly followed the manufacturer's protocols (Accurate Biology, HN, China). The sequences of the gene expression primers used for amplification are listed in Table S10 (Supplementary Materials). The reaction was performed using a CFX96 system (Bio-Rad, CA, USA). Relative mRNA expression levels was calculated using the 2^−ΔΔCt method, with normalization to β-actin mRNA serving as the endogenous control.

2.14. Western blot analysis

Total proteins were extracted from mouse tissues using an ice-cold RIPA reagent (Beyotime, SH China). Protein concentrations were determined using a BCA assay kit (Epizyme, SH, China), with equal amounts (40 μg) subjected to 10 % SDS-PAGE and transferred onto PVDF membranes (Millipore, NJ, USA). After blocking, the PVDF membranes were incubated overnight at 4 °C with the following primary antibodies: p-AKT (Ser 473), AKT, p-AMPK (Thr172), AMPK (Epizyme, SH, China), and GAPDH (CST, MA, USA). The membranes were incubated with the HRP secondary anti-rabbit antibody (CST, MA, USA) for 2 h, stained with an ECL reagent (Beyotime, SH, China) and visualized with a Tannon imaging system (Tannon-4200, SH, China). Band intensities were normalized to GAPDH levels for comparative analysis.

2.15. Statistical analysis

All statistical analysis was performed by the SPSS 27.0.1.0 software (SPSS Inc., IL, USA). Group differences were assessed through one-way ANOVA with Tukey's HSD post-hoc test for multiple comparisons. The statistical are shown as means ± SEM. Statistical significance was determined at p < 0.05. Each experimental condition included three technical replicates to ensure measurement consistency.

3. Results

3.1. GI value measurement and the effects of LH on obesity in mice

Due to the high content of glucose and fructose in honey, concerns persist regarding its potential impact on glucolipid metabolism homeostasis (Sadeghi, Akhlaghi, & Salehi, 2020).The GI provides a more accurate indicator of honey's effect on blood glucose regulation, as low-GI dietary patterns have demonstrated efficacy in promoting weight management and glycemic control (Jenkins et al., 1981). Hence, we initially examined the changes in blood glucose within 2 h postprandial period with the consumption of LH (Table S1), rape honey (Table S2)and glucose in healthy mice (Fig. 1A). The GI value of LH was calculated as 51.94 (Table S3), demonstrating a statistically significant reduction compared to RH (GI = 63.01, Table S4), as calculated through the glycemic response curves (Supplementary Table S1–4). The experiment results demonstrate that consuming LH exerts a milder impact on postprandial blood glucose, thereby enhancing blood glucose management.

Fig. 1.

Glycemic index value measurement and the effects of amur linden honey on obese mice. (A) Effect of LH and RH on postprandial blood glucose on healthy mice (n = 12); (B) 12 weeks body weight; (C) the 12th week body weight; (D) BAT weight/WAT weight; (E) Blood glucose levels of OGTT; (F) AUC of OGTT; (G) The 12th week blood glucose level; (H) Fasting serum-insulin levels; (I) HOMA-IR; (J) Serum TC level; (K) Serum TG level; (L) LDL-c level; (M) HDL-c level; (N) LDL-c/HDL-c. Data are presented by the mean ± SEM (n = 6). Different letters correspond to significant differences at p < 0.05.

To further demonstrate the impact of honey on obese individuals, we conducted animal experiments. As shown in Fig. 1B-D, the weight gain of 12-week obese mice (27.70 ± 3.74 g) was 27.00 % higher than that of control mice (21.81 ± 1.12 g; p < 0.05), confirming successful metabolic dysfunction modelling. In addition, no significant differences were observed between the HFD and HL groups regarding body weight or fat mass measurements (p > 0.05). Notably, high-dose honey administration (HH group) significantly reduced body weight (vs. HFD group) and elevated the BAT/WAT ratio in obese mice. Besides, the OGTT and AUC illustrated that the HL and HH groups were significantly lower than those of the HFD group (Fig. 1E-G). Consistently, serum insulin levels and HOMA-IR in the HFD group were markedly elevated compared with the Control group. (Fig. 1H-I) However, LH administration demonstrated a dose-dependent reduction in these parameters, suggesting that honey may enhance blood glucose regulation capacity in obese mice through insulin sensitivity modulation.

Furthermore, high-fat diet remarkably increased the serum TC, TG, and LDL-c levels in obese mice, while LH intervention can dose-dependently reverse these negative effects (Fig. 1J-L). Importantly, LH administration increased HDL-c level and reduced the LDL-c/HDL-c ratio in obese mice (Fig. 1M-N). In conclusion, LH consumption not only alleviate obesity in mice but also significantly demonstrates efficacy in mitigating overweight conditions and glycolipid metabolism disorders, especially at high-doses LH. These findings provide compelling evidence supporting the potential of LH as a health-promoting sugar alternative or even as an adjuvant for obese patients. The dose-dependent efficacy observed (particularly with high-dose LH regimens) indicates that specific bioactive constituents in honey, such as polyphenols, may mediate these beneficial effects. This warrants further investigation to isolate and characterize the exact mechanisms of action.

3.2. Metabolomics and antioxidant determination of LH and RH

The significantly lower GI value of LH compared to RH (p < 0.05) substantiates its potential in obesity intervention, as evidenced by our experimental models. Therefore, UPLC-MS/MS-based metabolomics analyses allowed to peep into the metabolite changes in LH and RH, to screen the metabolites that differed between the two honeys and to identify the principal compounds exerting anti-obesity effects. The metabolomic profiling revealed 869 metabolites in both LH and RH samples (Fig. 2A), which were systematically categorized into distinct chemical classes. Notably, polyphenols emerged as the predominant phytochemical group, accounting for 25.1 % of the total identified metabolites. The two honey types exhibited marked differences in metabolite composition, with the LH group demonstrating significantly higher concentrations of more phenolic acids (38 compounds, p < 0.05), alkaloids, alcohols, lignans and coumarins compared to RH (Fig. 2B). Notably, quantitative analysis revealed that phenolic acids constituted the most prominent differential component category between the two honey varieties.

Fig. 2.

Antioxidant activity and metabolomics determination of amur linden honey and rape honey. (A) Plot of total metabolite Class I and its corresponding Class II share for all samples; (B) Total relative content of each metabolite in the Class II. The bottom heat map shows the number of differential metabolites with increased or decreased levels in RH compared to LH under this substance class. Red and blue indicate quantitative differences only; (C) Compounds with significant differences in the relative contents of Phenolic acids and Flavonoids; (D) Determination of total reducing power; (E) OH· free radical scavenging assay; (F) DPPH· free radical scavenging assay; (G) ABTS⁺ free radical scavenging assay. Data are presented by the mean ± SEM (n = 6). (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

Volcano plotting was employed to visualize differential metabolites of phenolic acids and flavonoids according to the set values (FC ≥ 2 or ≤ 0.5, |RH-LH| × 10⁻⁵). In the visualization, metabolites were colour-coded as: red (significantly increased), green (significantly decreased), and grey (no significant change). The plot effectively distinguished compounds exhibiting substantial content variations between experimental groups (Fig. 2C). Simultaneously, based on the differential analysis of phenolic acid and flavonoid differential metabolites between RH and LH (Table S5), combined with the percentage distribution of differential metabolites in these two categories (Table S6), and the nine metabolites with higher relative content and significantly enriched in RH were obtained, 2,4-Dihydroxybenzoic acid, 2,3-Dihydroxybenzoic Acid, 3,4-Dihydroxybenzoic acid (Protocatechuic acid), 2,5-Dihydroxybenzoic acid (Gentisic Acid), p-Coumaric acid, 3-Hydroxycinnamic Acid, 3-O-Methylquercetin, 3-(4-Hydroxyphenyl)-propionic acid and Caffeic acid (Fig. 2C and Table S7).

Based on these findings, further experiments were conducted to determine and compare the total polyphenol and flavonoid contents of LH and RH. The results demonstrated that the total polyphenol and flavonoid contents of LH were markedly superior to those of RH, with 27.1 (mg/100 g honey) of total phenols and 1.2 (mg/100 g honey) of total flavonoids for LH and 19.9 (mg/100 g honey) of total phenols and 0.8 (mg/100 g honey) of total flavonoids for RH, thereby corroborating the reliability of the metabolomics analysis. Similarly, the total reducing power of LH per 100 g was 44.37 ± 4.90 mg Vc, DPPH radical scavenging activity was 8.28 ± 0.16 mg Vc, OH radical scavenging capacity was 97.13 ± 2.11 mg Vc, and ABTS+ radical scavenging capacity was 29.25 ± 0.21 mg Vc per 100 g of LH, while the antioxidant capacity of LH exhibited significantly stronger than that of RH at all equivalent test concentrations (p < 0.05) (Fig. 2D-G). These results demonstrated that the LH contains a higher amount of polyphenolic active substances and superior antioxidant activity compared to RH.

3.3. Comparing PE and PC effects on glycolipid metabolism disorder cell model

Based on the metabolomic profiling data, it is speculated that polyphenols in LH play the primary contributors in anti-obesity activity. To further clarify the key components, we compared the effects of LH total polyphenol extracts (PE) and the combination of nine principal polyphenols (PC) on alleviating glycolipid metabolic disorders in cellular experiments.

The results showed that both PE and PC could significantly alleviate the glycolipid metabolism disorder in HepG2 cells, exhibiting consistent therapeutic effects at equivalent dosage. In the lipid accumulation model, PE and PC treatment resulted in a significant dose-dependent reduction in lipid droplet accumulation and the content of TC and TG within HepG2 cells, with no statistically significant disparity (p > 0.05) between the lipid-lowering efficacies of PE and PC at equivalent doses (Fig. 3A-D). In the insulin resistance (IR) model, both doses of PE and PC treatment significantly enhanced glucose consumption (Fig. 3E) and 2-NBDG uptake (Fig. 3F-G). Similarly, PE and PC exhibited equivalent effects at identical dosages. These findings indicate that the polyphenol composition and proportion of PC constitute the key to mechanism underlying the anti-obesity efficacy of LH.

Fig. 3.

The ameliorative effects of total polyphenol extracts and nine principal components treatment on glycolipid metabolism disorders in HepG2 cells. (A) Oil Red O staining results; (B) Lipid droplet content; (C) Contents of TC; (D) Contents of TG; (E) Glucose consumption; (F) Fluorescent images of 2-NBDG uptake under various treatments; (G) Median fluorescence absorbance. Data are presented by the mean ± SEM (n = 6). Different letters correspond to significant differences at p < 0.05. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

3.4. Effects of adding PC to LH on overweight and glucose metabolism disorders in obese mice based on WHO recommended sugar intake

Given that the initial LH dosage exceeded the WHO-recommended daily free sugar intake threshold (50 g for adults), the experimental protocol was revised to restrict LH quantities within 25–50 g/day, aligning with the organization's phased reduction guidelines. Moreover, the considerable amounts of glucose and fructose in honey raise notable health concerns for obese individuals. To investigate this, a group of mice that received equivalent amounts of glucose and fructose mixtures to those found in LH was introduced.

Initial experiments revealed significant increases in final body weight, Lee's index, and liver weight in the HFD groups compared to the control group (p < 0.01), which could be significantly alleviated with the LH and HP intervention (Fig. 4A-C). Moreover, LH and HP markedly increased the BAT/WAT ratio related to the obese mice (Fig. 4D). Building upon prior findings, both LH and HP alleviated the OGTT, hyperglycemia and insulin resistance, and the effect of LH was superior with the addition of PC. It is worth noting that glucose and fructose mixtures exacerbated overweight and glucose metabolism disorders in obese mice. These results collectively demonstrate the safety profile and health-promoting potential of LH supplementation.

Fig. 4.

Amur linden honey and nine principal components added to Amur linden honey alleviate overweight and glucose metabolism disorders on obese mice. (A) Body weight; (B) Lee's index; (C) Liver weight; (D) BAT weight/WAT weight; (E) Blood glucose levels of OGTT; (F) AUC of OGTT; (G) The 12th week blood glucose level; (H) Fasting serum-insulin levels; (I) HOMA-IR score. Data are presented by the mean ± SEM (n = 6). Different letters correspond to significant differences at p < 0.05.

3.5. Effects on lipid metabolism disorders and liver injury in obese mice

The amelioration of honey on lipid metabolism disorders in obese mice aligns with previous results. Compared to the HFD group, the serum TC level was remarkably increased in the HFD + GF group, suggesting that glucose and fructose exacerbated the production of TC, while LH and HP counteract these negative effects (Fig. 5A). Moreover, serum levels of TG and LDL-c, along with the LDL-c/HDL-c ratio showed consistent results (Fig. 5B-E). The results of H&E staining (Fig. 5H) revealed severe hepatic steatosis, mononuclear inflammatory cells infiltration, and apoptosis of hepatocytes in obese mice. Notably, glucose and fructose supplementation exacerbated these hepatic lesions, whereas administration of LH and HP significantly attenuated the observed tissue damage. Similarly, the decrease of ALT and AST levels by LH and HP treatments further supported their positive effects in attenuating liver damage (Fig. 5F-G). In summary, the findings confirm that LH and HP exert beneficial effects on obesity-related metabolic disorders and hepatic injury mitigation. Moreover, the incorporation of polyphenols significantly amplifies honey's therapeutic efficacy compared to conventional sweeteners such as glucose and fructose.

Fig. 5.

Effects on lipid metabolism disorders and liver injury on obese mice. (A) Serum TC levels; (B) Serum TG levels; (C) LDL-c levels; (D) HDL-c levels; (E) LDL-c/HDL-c ratio; (F) Serum AST levels; (G) Serum ALT levels; (H) Representative liver H&E staining (scale bar = 50 μm), and the black, red, and blue arrow indicate the vesicular degeneration, hepatic steatosis and local inflammatory cell infiltration, respectively. Data are presented by the mean ± SEM (n = 6). Different lowercase letters correspond to significant differences at p < 0.05. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of this article.)

3.6. Regulation on the gut microbiota composition and the level of SCFA in obese mice

The gut microbiota exhibits a profound association with obesity development (K. Hou et al., 2022). As illustrated in Venn diagram (Fig. 6A), analysis of 2090 total OTUs revealed distinct microbial signatures: 183 OTUs (8.6 %) were unique to HFD + LH group, while 204 OTUs (9.8 %) were unique to HFD + HP group, which indicated that LH and HP have a greater effect on the gut microbiota of obese mice. In addition, the diversity of the gut microbiota was significantly reduced in obese mice, with glucose and fructose supplementation causing a further reduction in microbial richness (Fig. 6B). Moreover, both HFD + LH and HFD + HP groups were significantly different from that of the HFD group (Fig. 6C). At the phylum level, the taxonomic composition patterns aligned with these findings (Fig. 6D). At the genus level, LH and HP significantly increased the abundance of Akkermansia, Enterorhabdus, Enterococcus and Mucispirillum, and decreased the abundance of Desulfovibrio, Blautia, Colidextribacter, Oscillibacter and Bilophila in obese mice (Fig. 6E). Moreover, LH increased Lactobacillus, Roseburia and Terrisporobacter abundance suggested that there is a slight difference between LH and HP in the regulation of gut microbiota.

Fig. 6.

Regulation on the gut microbiota composition and the level of SCFA on obese mice. (A) Venn Graph Based on OTU; (B) α diversity analysis of Chao1 index; (C) β diversity analysis of PCoA analysis; (D) Gut microbiota composition at the phylum level; (E) Heatmap at the genus level; (G-I) GC analysis of the content of short fatty acids. Data are presented by the mean ± SEM (n = 6). Different letters correspond to significant differences at p < 0.05.

SCFA, derived from the fermentation of dietary fibers by gut microbiota, play crucial roles in regulating host energy metabolism and inflammation. Dysregulation of SCFAs is strongly linked to obesity development through altered microbial composition and metabolic pathways. Therefore, the SCFA concentrations in feces were measured in each group. As illustrated in Fig. 6G-I and Table S9, the contents of acetic, and propionic acids were markedly decreased in obese mice (p < 0.05), while butyric, isovaleric and ethyl butyric acid did not show significant differences. Compared to the HFD group, LH treatment statistically increased the levels of acetic acid and propionic acid, and also elevated the contents of butyric acid and isovaleric acid. However, the HP treatment did not have such an effect. This is closely related to the different gut microbiota structures regulated by the two treatments. It also further indicates that the addition of PC has a more pronounced impact on the microbiota.

The above results suggested that both LH and HP alleviated the disorders of gut microbiota in obese mice, with LH exhibiting superior capacity to augment short-chain fatty acid biosynthesis, which mechanistically underpins its anti-obesity properties. However, the gut microbiota regulated by HP did not promote SCFA production and might function through other pathways.

3.7. Effects on glycolipid metabolism signaling pathway in obese mice

To further clarify the effects of LH and HP on glycolipid metabolism, we analyzed the transcript levels of PI3K/AKT and AMPK-related genes in liver. Comparative analysis revealed significant downregulation of phosphoinositide 3-kinase (PI3K) and protein kinase B (AKT) transcripts in both HFD and HFD + GF groups relative to the control group (p < 0.05). Notably, these diet-induced transcriptional alterations were effectively ameliorated by LH and HP interventions (Fig. 7A-B). Similarly, both LH and HP significantly reduced the transcript levels of glucose-6-phosphatase (G6Pase) in obese mice (Fig. 7C). Moreover, HP exhibited a statistically significant increase the AMP-activated protein kinase (AMPK) transcript level compared to the LH group, whereas glucose-fructose (GF) supplementation resulted in marked reduction of AMPK expression in obese mice (Fig. 7D). Consistently, the transcript levels of 3-hydroxy-3-methylglutaryl coenzyme A reductase (HMGCR), fatty acid synthase (FAS), and peroxisome proliferator-activated receptor (PPAR-γ) showed parallel trends (Fig. 7E-G). Notably, the addition of LH and HP significantly attenuated the phosphorylation levels of AMPK and AKT (Fig. 7I-K). Compared to HFD-induced conditions, GF further aggravated metabolic dysregulation. In contrast, both LH and HP can significantly regulate PI3K/AKT and AMPK signaling pathway to alleviate glycolipid metabolism disorders. Notably, HP exhibited superior therapeutic efficacy over LH (p < 0.05), which strongly evidenced the ability of LH to improve glycolipid metabolism disorders, whereas the addition of PC enhanced the ameliorative effect of LH.

Fig. 7.

Effects on glycolipid metabolism signaling pathway on obese mice. The relative mRNA expression of (A) PI3K, (B) AKT, (C) G6pase, (D) AMPK, (E) HMGCR, (F) FAS, (G) PPAR-γ, (H) PI3K/AKT/AMPK pathway, (I) Western blotting of p-AMPK (Thr172), AMPK, p-AKT (Ser473), AKT and GAPDH. The relative protein expression of (J) p-AMPK/AMPK, (K) p-AKT/AKT. Data are presented by the mean ± SEM (n ≥ 3). Different letters correspond to significant differences at p < 0.05.

4. Discussion

It has been found that sweetness is prioritized over addictive substances such as caffeine in the sequencing of neural pathways (Ludwig, 2009; Suez et al., 2022). Therefore, the sweet taste needs of sub - healthy populations, especially those who are obese, should not be overlooked. Artificial sweeteners have potential long - term safety issues and can cause distorted sweetness. Given these concerns, it is crucial to investigate the effects of natural sweeteners such as honey on obesity.

The GI measurement in mice revealed that LH has a value of 51.94, categorizing it as a low-GI food (GI < 55). Given that low-GI foods are clinically recommended for obese populations due to their attenuated postprandial glycemic response (Thomas & Elliott, 2010), LH holds significant potential for health applications. This finding addresses the growing concern among suboptimal health groups, particularly obese individuals seeking sugar reduction strategies while maintaining natural sweetener intake. We hypothesized that LH might exhibit better amelioration in obese individuals. To validate this, we conducted a dose-response study administering two LH concentrations (low-dose: 1.56 g/kg B.W./d; high-dose: 3.13 g/kg B.W./d) to diet-induced obese mice over 12 weeks. While the low-dose LH did not exacerbate the overweight and showed some amelioration in glycolipid metabolism disorders, illustrating the safety and potential benefits of LH as a sugar substitute in obese individuals. It is worth noting that, the high dose LH not only alleviated overweight but also showed a higher efficacy in alleviating glycolipid metabolism disorders in obese mice. Notably, although the high-dose regimen introduced elevated glucose and fructose intake, its enhanced therapeutic outcomes suggest that bioactive components in LH play a critical regulatory role.

Based on previous findings suggesting the potential anti-obesity properties of LH components, we employed untargeted metabolomics to identify bioactive compounds with significantly higher concentrations in LH compared to RH. Polyphenols in honey accounted for a significant proportion of all metabolites detected, highlighting their critical role in LH's biochemical composition. Further comparative analysis helped to identify 9 potential key active substances in LH. To investigate the therapeutic potential of LH-derived active components, two in vitro models of glycolipid metabolic dysregulation were established. The results revealed that the 9 substances, when administered at equivalent concentrations, exhibited comparable corrective effects on lipid accumulation (vs. Control group) and glucose uptake, identifying them as core bioactive constituents in LH. As a result, in subsequent experiments, we anticipate exploring whether direct addition of PC to the LH matrix would demonstrate better anti-obesity effects compared to current approaches involving PE supplementation or polyphenol enrichment, which would prove more straightforward and cost-effective in terms of practical application and production significance.

We investigated the effects of equicaloric intake of glucose and fructose under the same HFD-induced obesity model, aiming to further explore the health benefits and safety profiles of LH. As expected, the consumption of GF aggravated weight gain, induced glucose metabolism disorders, and exacerbated hepatic injury in obese mice. It is worth noting that the ameliorations in the HFD + LH group compared to the HFD + GF group were more pronounced than those observed compared to the HFD group. This study reveals that although the high content of glucose and fructose in honey can indeed further exacerbate obesity, the bioactive compounds not only counteract this influence but also further alleviate obesity induced by HFD. This also explains why LH has a significant effect in alleviating obesity and is a low GI food. Although HP demonstrated a stronger trend in obesity reduction compared to LH, no statistically significant intergroup differences were observed in their mean values. This may indicate that the amelioration of LH has reached a plateau. Perhaps PC could be applied to other common honeys with low polyphenol content to enhance their health benefits.

The gut microbiota has been well-established as a critical modulator in obesity pathogenesis, with dysbiosis directly linked to metabolic syndrome progression (J. Shen, Obin, & Zhao, 2013). Our study revealed that both LH and HP significantly altered the gut microbiota of HFD mice. The Akkermansia and Enterorhabdus, which have been reported to be negatively correlated with obesity and inflammation (Rodrigues et al., 2022; Zuo et al., 2023), showed significant enrichment in the HFD + LH and HP intervention groups compared to the HFD control group. Additionally, Desulfovibrio, Colidextribacter, and Bilophila, which were significantly reduced in both HFD + LH and HP groups, have been reported to exacerbate obesity by affecting lipid absorption and fat synthesis (Duan et al., 2021; Hong et al., 2021; Natividad et al., 2018). Furthermore, the gut microbiota of HFD mice exhibited marked compositional alterations after GF intervention, consistent with previous reports that high glucose and fructose diets disrupt the gut microbiota in mice (Arnone et al., 2022). The marked alterations in gut microbiota between the HFD + LH and HFD + GF groups indicated that active ingredients in LH play a significant role in modulating the gut microbiota.

Moreover, LH treatment increased the levels of acetic acid, propionic acid, and butyric acid, and isovaleric acid levels in obese mice. Emerging evidences have demonstrated that propionic acid and butyric acid enhance mitochondrial β-oxidation and inhibit fat synthase activity by regulating the intestinal flora-metabolism axis (Solar et al., 2023; Zhang et al., 2024). Acetic acid exerts insulin-sensitizing effects through GPR43-dependent inhibition of the PI3K/Akt signaling axis (Kimura et al., 2013). Concurrently, isovaleric acid modulates hepatic lipid homeostasis via dual activation of GPR41 and GPR109A receptors, demonstrating bidirectional regulation of fatty acid oxidation and cholesterol biosynthesis pathways (Chi et al., 2024). Notably, HP did not upregulate the levels of SCFA. This aligns with the finding that LH can increase the abundance of certain SCFA-producing bacterial genera, while HP does not. For example, Lactobacillus is a genus of bacteria known for its role in producing and absorbing SCFA (G. Hou et al., 2022). The Roseburia is an important butyrate-producing bacterium that can utilize fermentable dietary carbohydrates to produce butyrate in large amounts (Zhao et al., 2022). Moreover, Terrisporobacter is identified as an acetic acid-producing bacterium (Gerritsen et al., 2014). They were all promoted only by LH in obese mice. These results suggest that LH has a beneficial effect in modulating gut microbiota dysbiosis and promoting the production of SCFA. Although HP did not demonstrate a promoting effect on SCFA, it also significantly regulated the gut microbiota structure and promoted the proliferation of beneficial bacteria. On the one hand, this indicates that the addition of PC has a significant impact on the gut microbiota, which is consistent with previous reports that polyphenols can markedly regulate the gut microbiota (Guerra-Valle et al., 2022). On the other hand, it suggests that the benefits of HP-regulated gut microbiota for obesity may be achieved through other aspects.

The PI3K/AKT and AMPK pathways are two crucial signaling pathways involved in glycolipid metabolism (Mackenzie & Elliott, 2014). Consistent with previous findings, HFD mice also showed suppressed expression of PI3K, AKT, and AMPK, which play important roles in metabolic disorders (Canbolat & Cakiroglu, 2023). Following LH and HP interventions, marked upregulation of these proteins triggered sequential activation of the PI3K/AKT signaling pathway, as evidenced by phosphorylation level alterations. This includes decreased expression of G6Pase, which is the rate-limiting enzyme in glycogen conversion to glucose (Hundal et al., 2000), as well as decreased expression of HMGCR, FAS, and PPAR-γ, which are positively associated with cholesterol and lipid synthesis (Guo et al., 2022; Latasa, Griffin, Moon, Kang, & Sul, 2003; Medina-Gomez, Gray, & Vidal-Puig, 2007). These findings align with the anti-obesity effects of LH and HP. Interestingly, HP exhibited significantly stronger activation of AKT and AMPK pathways than LH. This disparity implies PC play a pivotal role in mediating these metabolic signaling cascades. However, such mechanistic advantages did not translate into discernible phenotypic improvements in adipocyte differentiation indices. Although the precise mechanisms warrant further elucidation, our findings suggest that PC supplementation significantly enhances the anti-obesity efficacy of LH. Building upon prior hypotheses regarding polyphenol synergism, the additional of PC in low doses LH or regular honey with low polyphenol content may result in better effects.

5. Conclusion

Through in vivo experiments, the lower GI LH has more potential to be a sugar substitute than regular RH. On this basis, it was found that LH exhibited dose-dependent ameliorative effects on obese mice, and it is noteworthy that the effect was more pronounced at higher doses of LH. This phenomenon may be attributed to bioactive compounds in LH, which showed positive correlation with metabolic regulation in subsequent analysis. Therefore, PC in LH were identified by widely-targeted metabolomics. Subsequent cellular experiments demonstrated its anti-obesity activity equal to its counterpart extracted from LH through cellular experiments. Moreover, LH administration at WHO-recommended dosages significantly alleviated obesity in mice while mitigating metabolic damage induced by isocaloric glucose and fructose exposure. Furthermore, our study demonstrated that the addition of PC enhanced the anti-obesity effects of LH, by modulating gut microbiota, promoting SCFA, and activating the AMPK/PI3K/AKT pathways. In conclusion, our findings highlight LH's dual functionality as both a natural sweetener and metabolic regulator, particularly demonstrating therapeutic potential for obese populations by simultaneously addressing gut dysbiosis and insulin resistance.

Ethics statement

Animal experiments were approved by the Animal Ethics Committee of the East China University of Science and Technology. All animal experiments comply with the ARRIVE guidelines and are conducted in accordance with the UK Animals (Scientific Procedures) Act 1986 and associated guidelines, the EU Directive on animal experimentation 2010/63/EU, or the National Research Council's Guidelines for the Care and Use of Laboratory Animals.

CRediT authorship contribution statement

Zitian Chen: Writing – review & editing, Writing – original draft, Investigation, Formal analysis. Heng Tao: Investigation, Formal analysis. Yuke Peng: Writing – original draft, Investigation. Jiayi Huang: Supervision. Yanzhe Cheng: Writing – review & editing. Wenxuan Tian: Resources. Yaning Chang: Writing – review & editing, Funding acquisition. Yingjun Zhou: Writing – review & editing, Conceptualization.

Declaration of competing interest

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.

Appendix A. Supplementary material

Supplementary Table.

Supplementary material (Results of UPLC-MS/MS-base metabolomics test in LH and RH).

Data availability

Data will be made available on request.