Next Article in Journal
DSC Phase Transition Profiles Analyzed by Control Charts to Determine Markers for the Authenticity and Deterioration of Flaxseed Oil during Storage
Previous Article in Journal
Multivariate Profiling of Metabolites and Volatile Organic Compounds in Citrus depressa Hayata Fruits from Kagoshima, Okinawa, and Taiwan
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Foods
Volume 12
Issue 15
10.3390/foods12152953
foods-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

The Role of Green Tea on the Regulation of Gut Microbes and Prevention of High-Fat Diet-Induced Metabolic Syndrome in Mice

by
Huiling Mei
1,†,
Jin Li
2,†,
Shujing Liu
3,
Anburaj Jeyaraj
3,
Jing Zhuang
3,
Yuhua Wang
3,
Xuan Chen
3,
Qijun Yuan
4 and
Xinghui Li
3,*
1
College of Resources and Environmental Sciences, Nanjing Agricultural University, Nanjing 210095, China
2
College of Tourism and Economic Management, Nanchang Normal University, Nanchang 330032, China
3
International Institute of Tea Industry Innovation for the Belt and Road, Nanjing Agricultural University, Nanjing 210095, China
4
Northern Tea Germplasm Resource Center, Rizhao 276808, China
*
Author to whom correspondence should be addressed.
†
These authors contributed equally to this work.
Foods 2023, 12(15), 2953; https://doi.org/10.3390/foods12152953
Submission received: 13 July 2023 / Revised: 1 August 2023 / Accepted: 2 August 2023 / Published: 4 August 2023
(This article belongs to the Section Plant Foods)
Browse Figures
Versions Notes

Abstract

:
Green tea is a popular non-alcoholic beverage consumed worldwide and has been shown to be beneficial for human health. However, further exploration is needed to fully understand its function in reducing obesity and regulating gut microbes. Here, we investigated the modulatory effects of green tea and its functional components on high-fat diet (HF)-induced metabolic alterations and gut microbiota in obese mice. Our results showed that 1%, 2%, and 4% of green tea promotes weight loss, with the 2% and 4% groups exhibiting distinct gut microflora clusters compared to the HF group. These results were comparable to those observed in the tea polyphenols (TPP)-treated group, suggesting the TPP in green tea plays a crucial role in body weight control and gut microbiota regulation. Additionally, 32 bacteria were identified as potential obesity markers via 16S rRNA gene sequencing. The 16SrDNA gene is a chromosomal gene present in all bacterial species, highly conserved in structure and function, that can reflect the differences between different taxa. The 16S rRNA-based analysis revealed that Akkermansia, a gut-beneficial bacteria, significantly increased in the TPP group.

1. Introduction

Obesity is a significant health issue in modern society with more than 500 million obese people and 1.4 billion overweight individuals in the world [1,2]. It is associated with various metabolic diseases, such as hyperglycemia, hyperlipidemia, and high blood pressure. Abdominal obesity and insulin resistance, accompanied by elevated blood glucose metabolism, elevated serum triglycerides, elevated blood pressure, high-density lipoprotein cholesterol, and increased low-density cholesterol, are the obesity indicators [3,4]. Mounting evidence has shown a link between intestinal microflora and obesity [5]. Obese microbiota has been found to increase dietary energy harvest and favor weight gain and fat deposition [6,7]. Disturbance of gut microbiota in high fat (HF)-induced obesity and diabetes mice leads to metabolic endotoxemia, inflammation, and associated disorders by increasing intestinal permeability [8,9]. Additionally, gut microbiota may play an active role in insulin resistance development [10]. Therefore, the intestinal microflora is closely related to the formation and development of metabolic syndrome and its related symptoms.
Green tea is a popular non-alcoholic beverage known for its functional effects on humans and animals with functional components, such as tea polyphenols (TPP), caffeine (Caf), and L-theanine (Thea) [11,12]. Two major mechanisms have been identified in the functional effects of green tea: (1) decreasing the absorption of lipids and proteins in the intestine, thereby reducing calorie uptake [13,14], and (2) activating AMP-activated protein kinase via TPP that is bioavailable in the liver, skeletal muscle, and adipose tissues [15]. Animal models and human studies have shown that green tea reduces body weight, alleviates metabolic syndrome, and prevents diabetes and cardiovascular diseases [16,17]. TPP mainly accumulates (90–95%) in the large intestinal lumen where gut microbial communities enzymatically break down the accumulated polyphenolic structures into a series of low-molecular-weight phenolic metabolites [18]. The green tea components interact and affect the gut microbe population. For example, fermented green tea extract can reduce Firmicutes to Bacteroidetes and Bacteroides to Prevotella in the large intestine of obese mice [19,20]. Polyphenols have been shown to increase the content of Akkermansia, a gut-beneficial bacterium that is negatively correlated with various excessive fat-related diseases, such as inflammatory bowel disease, obesity, type 2 diabetes, and appendicitis [21,22]. This study investigated the role of green tea and its functional components (TPP, Caf, and Thea) on the regulation of intestinal microflora and reducing obesity.

2. Materials and Methods

2.1. Preparation of Green Tea Infusion

Suchazao tea cultivar leaves were collected from Zhongshanling tea garden (Nan-jing, China) and made into green tea after deactivation of enzymes and torrefaction treatment [23,24]. With reference to the standardized concentrations for tea beverage preparation, 1, 2, and 4 g green tea were mixed with 100 mL distilled water at 100 °C, which was maintained for 30 min by using a water bath. Total TPP content was quantified by spectrophotometric method based on Folin phenol and the ninhydrin assay as described by GB/T 8313-2018, and Caf and Thea contents were detected in the brewed tea via high-performance liquid chromatography (HPLC) (Alliance 2695, Waters, America, Milford). To evaluate the effectiveness of the main components of green tea, concentration of TPP in the second experiment was set to 6 g per liter, where the concentration was equivalent to the total concentration of TPP in 4% green tea. Constitute profile of the 4% green tea is shown in Table 1.

2.2. Animal and Treatments

Healthy male C67BL/6J mice (10~12 g, 3~4 weeks old) (Permission number: 201604129) were obtained from Animal Centre, Yangzhou University, and kept in a growth chamber in the Animal Centre, Nanjing Agricultural University, in a controlled environment with a temperature range of 20~26 °C, relative humidity of 40~70%, light intensity of 250 Lux, and a photoperiod of 14 h light followed by 10 h darkness. They were given one week to acclimatize to their surroundings before starting the experiment. To investigate the effect of green tea on obesity, 35 mice were randomized into 5 groups and labeled as LF, HF, HF+1%, HF+2%, and HF+4%. The mice in the LF and HF groups were fed a low-fat (10% fat calories) and high-fat (60% fat calories) diet, respectively, while mice in HF+1%, HF+2%, and HF+4%groups were fed an HF diet with corresponding 1, 2, and 4% green tea infusions, respectively, for a period of 8 weeks. Also, to assess the effect of major components of green tea on the regulation of the gut microbiota, 35 mice were randomized into 5 equal groups and labeled HF + TPP, HF + Thea, HF + Caf, LF, and HF groups. According to the proportion of the 3 major components in green tea, mice in the HF + TPP, HF + Thea, and HF + Caf groups were fed an HF diet with 6.0 gL−1 TPP, 1.5 gL−1 Thea, and Caf, respectively. Feeding and water supply (with or without treatments) were performed ad libitum granting the mice equal opportunity and access to feed and water. The amount of water intake and the change in body weight were recorded daily. All protocols for the animal experiments complied with the Nanjing Agricultural University guideline for care and use of laboratory animals.

2.3. Tissue Preparation and Biomarker Assessments

Oral glucose tolerance test (OGTT) was performed to determine the glucose tolerance level of the mice. After 12 h starve treatment, the blood serum of mice was collected from the tail to detect the fast blood glucose (FBG) level. The glucose was then given to the mice by oral gavage (2 g/kg, 10% solution) for OGTT. Thereafter, the mice were fasted for 12 h, anesthetized, and sacrificed by cervical dislocation after peripheral blood collection from the ophthalmic vein. Histological studies were conducted on the liver and small intestine. Tissues were fixed with 0.04 g/mL−1 paraformaldehyde in 0.01 M phosphate buffer for 24 h and then processed for paraffin inclusion. Serial paraffin sections (4 mm) were stained with haematoxilin-eosin (HE) followed by light microscopy examination (KingMed Diagnostics, Nanjing, China). The number of goblet cells per small intestinal villus was counted [24]. Alanine aminotransferase (ALT) (C009), aspartate aminotransferase (AST) (C010), triglyceride (TG) (A110), total cholesterol (TC) (A111), LDL (low-density lipoprotein) (A113), HDL (high-density lipoprotein) (A112), and free fatty acids (FFA) (A045) (Njjcbio, Nanjing, China) in serum were determined by using commercially available kits according to the manufacturer’s instructions. Serum contents of mono-cytechemo attractant protein-1 (MCP-1) (60224M), insulin (INS) (60207M) (Rigor, Beijing, China), tumornecrosisfactor-α (TNF-α) (E21030M), and LPS (Lipopolysaccharide) (E21618M) (Aogene, Nanjing, China) were detected using ELISA kits.

2.4. Gut Microbiota Classification by Next Generation Sequencing (NGS)

Total DNA was extracted from 0.2 g of fresh fecal samples collected from each mouse following the manufacturer’s instructions for DNA extraction kit (MoBio, Carlsbad, CA, USA). The DNA amplification was performed in 25 µL reaction volumes using primer sequences (520F/802R) targeting the V4 region of the 16S rRNA gene [25]. The purified amplicons were pooled in equimolar concentrations and employed for library construction using the NEBNext®UltraTM DNA Library Prep Kit for Illumina (New England Biolabs, Hitchin, UK). The final quality and concentration of the libraries were assessed using Agilent 2100 Bioanalyzer Instruments (Agilent Technologies, Santa Clara, CA, USA) and determined with KAPA Library Quantification Kits (Kapa Biosystems, Wilmington, MA, USA). All library preparations for sequencing were performed on the Illumina MiSeq platform. Sequencing reads were assigned to each sample according to their unique barcodes. Sequences were analyzed with QIIME 1 (Quantitative Insights into Microbial Ecology) software package and UPARSE pipeline [26]. The reads were filtered with QIIME quality filter [27]. The sequences retained for each sample, referred to as clean paired sequences, were analyzed following the UPARSE pipeline to pick up operational taxonomic units (OTUs) through the creation of OTU table. Sequences with quality scores lower than 0.5, lengths shorter than 200 nt, and singletons were discarded, and then retained sequences were assigned to OTUs at 97% similarity. Chimeras were filtered. Representative sequence was selected for each OTU, and using Ribosomal Database Project (RDP) classifier [28], the taxonomic data were assigned to each representative sequence. To reveal distinct clustering of microbiota composition for each treatment group, UniFrac-based principal coordinate analysis (PCoA) was performed using Rlanguage (Version 3.3.1). Resultant Venn diagram was then drawn using Bioinformatics and Evolutionary Genomics (http://bioinformatics.psb.ugent.be/webtools/Venn/, accessed on 1 May 2023).

2.5. Statistical Analysis

Data are shown as mean ± SEM. Differences were analyzed for statistical significance using one-way analysis of variance (ANOVA) with Turkey’s multiple comparison test to compare samples (Graph Pad Prism, San Francisco, CA, USA). Differences in body weight were assessed using two-way ANOVA. Values of p < 0.5 were considered significant. Next-generation sequencing analysis was assessed using PERMANOVA to check significant differences between microbial assemblages, and packages of DESeq2 were used for the identification of differentially abundant microbial features.

3. Results

3.1. Effect of Green Tea on Body Weight- and Fat-Associated Biochemical Indices of HF-Induced Obese Mice

After 8 weeks of feeding, compared to the LF group, the weight, subcutaneous, epididymal, and abdominal fat of the HF group mice significantly increased, indicating the successful construction of a high-fat diet-induced obesity model. However, there was no significant difference in diet and water intake between the HF group and the LF group (Figure 1). To assess the impact of green tea on obesity, we fed the mice with LF, HF, HF with 1% green tea (HF+1%), HF with 2% green tea (HF+2%), and HF with 4% green tea (HF+4%) diets. We found that the body weight, hypodermic, epididymal, and abdominal fat were significantly higher in the HF group compared to the LF group mice, whereas the HF diet combined with green tea reduced the mice’s body weight and fat accumulation (Figure 1A–D). The water intake of the mice in all the groups had no significant difference (Figure 1E). The HF+4%group had the highest food intake compared to the LF and other HF groups (Figure 1F), suggesting the water or food intake did not affect the body weight or fat accumulation. Generally, the biochemical indices were higher in the LF group, and fat accumulation was higher in the HF group, but these biochemical indices were decreased in the tea-consumed mice (Table 2). A histological investigation of the liver and small intestine showed that swelling cells with mild lymphocytes were in the portal area of the liver cells in the HF group mice, while dense and regularly arranged cells without the hydroncus phenomenon were in the green tea-treated mouse liver cells (Figure 2A). Additionally, ALT and AST were decreased in the groups treated with HF together with green tea (Table 2), suggesting that green tea has the potential to repair liver damage caused by obesity. In the small intestine, HF-induced shortening and loss of villus and swelling on the intestinal glands were alleviated in the green tea treatment groups. (Figure 2B.) The inflammatory biomarkers TNF-α and MCP-1 were significantly altered in the HF group and the 2% and 4% green tea-treated groups (Table 2).

3.2. Effect of Green Tea on HF-Induced Gut Dysbiosis

To determine the effect of green tea on mice gut microbiota, we examined the composition of intestinal microbiota via NGS. After the removal of low-quality reads, a total of 2,028,825 bacterial 16S rRNA gene sequences were obtained in all the samples. The number of retained bacterial 16S rRNA gene sequences per sample varied between 21,062 and 77,969. A total of 32 bacterial phyla were identified in all samples of these, with Firmicutes (10.30–81.42%) and Bacteroidetes (8.65–65.96%) being dominant and Thermotogae (0–0.01%) and Chloroflexi (0–0.01%) being the least. Additionally, five more minuscule phyla were noticed in most samples (Figure 3A). The clusters of intestinal microflorae were identified in different groups of mice (Figure 3B). PCoA including PCoA1 and PCoA2 were calculated as 26.63 and 11.35%, respectively (Figure 3B). The HF+1% green tea group showed mild separation from the HF group, while the HF+2% and HF+4%green tea groups showed significant separation and were significantly separated from the HF group (Figure 3B). A Venn diagram presented the specific bacterial microorganisms that were altered by HF and green tea intake (Figure 3C). The total number of OTUs of the LF, HF, HF+1%, HF+2%, and HF+4% groups were 672, 782, 769, 711, and 712, respectively. When comparing with the HF group, the HF groups with 1%, 2%, and 4% green tea altered 212 (99 newly appeared and 113 disappeared), 213 (70 newly appeared and 143 disappeared), and 263 (96 newly appeared and 167 disappeared) OTUs, respectively. The OTUs HF+1%, HF+2%, and HF+4% shared with HF mice were 670, 641, and 616, respectively (Figure 3C). The results indicated that the intake of HF with 4% green tea drastically altered the population of intestinal microflora compared to the HF group.

3.3. Influence of TPP, Thea, and Caf on Intestinal Bacteria and Obesity-Related Indices of HF-Induced Obese Mice

After 8 weeks of treatment, the TPP and Thea-treated group showed significant reductions in body weight and fat accumulation compared to the HF group (Figure 4A–D). There was no significant impact on water intake among the mice in all the groups (Figure 4E). The HF + Thea group had the highest food intake and reduced body weight (Figure 4F). TPP treatment significantly reduced the FFA, fat ratio, TG, HDL, and LDL levels (Table 3). The results suggest that TPP plays a critical role in reducing obesity. Morphological analysis of the liver under various tea component treatments were shown in Figure 5A. Swelling and inflammation were observed in the liver cells of HF group mice, and these were relatively less in the Thea, Caf, and TPP groups. The observation in the TPP group can be attributed to the fact that the cells were closely arranged, partially accounting for the reduction in swelling and inflammation (Figure 5A). The HF group had a relatively short and excised villi surface area compared to the LF group. However, the TPP, Caf, and Thea treatments increased the intestinal villi length and surface area (Figure 5B). The villus height, crypt depth, and goblet cell count were significantly higher in the TPP, Thea, and Caf groups compared to the HF and LF groups (Table 4).

3.4. Influence of TPP, Thea, and Caf on Gut Dysbiosis of HF-Induced Mice

The TPP significantly increased Verrucomicrobia and decreased the Firmicutes population in the gut microbiota, respectively. But no significant impact was noticed in HF, Thea, and Caf groups (Figure 6A). The PCoA analysis revealed five distinct groups in the gut microbiota (Figure 6B). The principal coordinates PCoA1 and PCoA were 21.36% and 17.17%, respectively. The clustering of the Thea and Caf groups was partly separated from the HF group, but the TPP cluster was completely separated from HF and closer to the LF cluster (Figure 6B). The OTU of the functional components was investigated to determine their impact on reducing obesity. The total OTUs of the HF + TPP, HF + Thea, and HF + Caf groups were 621, 792, and 821, respectively. The TPP, Thea, and Caf treatments altered 332 (85 newly appeared and 247 disappeared), 221 (115 newly appeared and 106 disappeared), and 232 (135 newly appeared and 97 disappeared) OTUs, respectively. The OTUs of the HF + TPP, HF + Thea, and HF + Caf groups were 536, 677, and 686, respectively (Figure 6C), and the largest number of OTUs was altered by TPP. Among the LF and HF groups, the Student’s t-test revealed 32 significantly different genera of microbiota that were associated with obesity. The effects of TPP, Thea, and Caf on these microbiotas were evaluated, and each functional component significantly altered 10 genera (Figure 7). Overall, the results indicate that green tea intake has a positive correlation with anti-obesity by altering some genera of microbiota.

4. Discussion

In this work, we investigated the effect of 1%, 2%, and 4% green tea on body weight and gut microflora dysbiosis and found that green tea with such concentrations contributed to weight loss in HF mice. However, 4% of green tea had the most remarkable effect on controlling body weight, regulating gut microflora, and performing without hepatotoxicity (Table 2). It is worth noting that the high concentration of EGCG (1500 mg/kg) used in the previous study resulted in hepatotoxicity in mice [29,30], which is much higher than our concentration. Therefore, intake of 4% green tea is recommended for the regulation of intestinal microflora.
A large proportion of TPP is converted into simple compounds and metabolites by colon and intestinal microbial enzymes [31,32]. The Bacteroidetes and Firmicutes are the main groups of biomarkers involved in the metabolisms of undigested food remnants, including dietary fiber and polyphenols [33]. Firmicutes were significantly higher in the HF mice compared to the LF mice; in contrast, the Firmicutes/Bacteroidetes ratio decreased in the TPP-treated mice, which is supported by many studies showing that TPP significantly decreases the Firmicutes/Bacteroidetes ratio [34,35,36]. Suppression of Firmicutes by TPP and their metabolites favors Bacteroidetes in the gut of mice, indicating that TPP has a modulatory effect on the composition of the intestinal microbiota. This result is closely associated with previous reports conducted by Higdon and Frei, [32]. But Janssens et al. [37] reported that long-term intake of tea EGCG and Caf does not affect the human gut microbiota. This controversial report may be due to differences in the concentration of the functional components used in these two studies.
A total of 32 obesity-associated biomarkers were identified, including Firmicutes (20 genera) and Bacteroidetes (5 genera). Liu et al. [38] identified 30 key microorganisms that respond to tea, including Alistipes, Akkermansia, Bacteroides, and Allobaculum. Our study found that the addition of TPP increased Akkermansia abundance in HF mice, which is consistent with previous research indicating that TPP, cranberry, chlorogenic acid, and grape also increase the colonization of Akkermansia in the gut [39,40,41,42]. We observed a significant increase in small intestinal goblet cells in TPP-treated mice, which secrete mucins, a food source for Akkermansia development [43]. Polyphenols increase intestinal mucus secretion which is the food source of Akkermansia and TPP does not alter mucingene (Muc2) expression in the jejunum, suggesting that Akkermansia is not simply due to increased host’s mucin production [44,45]. Therefore, the potential mechanism of TPP to increase Akkermansia needs further investigation.
L-theanine treatment also altered several genera of biomarkers, including disappearing Saccharofermentans, like the effect of TPP. Thea with tannins in goat fodder reduces the amount of Saccharofermentans in the goats’ rumen [46]. The Thea treatment also altered populations of Acetatifactor, Bacteroides, and Alistipes, with Acetatifactor being higher in the Thea group and lower in the TPP group. Additionally, Caf altered the population of the Allobaculum genera, which was significantly decreased in the HF mice, and its population density was positively correlated with plasma HDL concentrations of hamsters [47,48]. Mice with barriers to a natural immune response showed a dysbiosis microbiota, reflected by the increase in some Bacteroidetes species, including Alistipes and Bacteroides [49]. Alistipes and Bacteroides were also overrepresented in carcinoma patients [50,51]. In this study, both Alistipes and Bacteroides had a positive correlation with body weight, which is significantly increased in the HF group and decreased in the Thea or Caf treatments.
We assessed the effects of three different functional components on the regulation of the intestinal bacterial population and found that TPP played a significant role in specific bacterial population regulation compared to Thea and Caf. At present, the main mechanisms of tea polyphenols in reducing fat and weight loss are as follows: inhibiting the activity of enzymes related to fat synthesis, promoting fatty acid oxidation, and increasing energy consumption in the body while inhibiting appetite and reducing nutrient absorption [52]. Green tea catechins mixed with caffeine have been proposed as adjuvants for maintaining or enhancing energy expenditure and for increasing fat oxidation in the context of the prevention and treatment of obesity [53]. Caf regulated the obesity-associated biomarkers, including Allobaculum, Psychrosinus, and Flavonifractor, while both Thea and Caf regulated Bacteroides, Alistipes, Coprococcus, and Roseburia. These components play a complementary role with TPP in maintaining the intestinal flora population and improving the effect of high-fat-induced obesity.
A combination of green tea extract with isomalto-oligosaccharides and tea powder extract can enhance the relative abundance of some probiotics, such as Bifidobacteriaceae and Lactobacillus, respectively [39]. However, our findings indicate that green tea and its functional components did not support probiotic proliferation. Chen et al. [54] also reported that Fuzhuan brick tea could not enhance Lactobacillus.
In summary, we observed a distinct clustering pattern of gut microbiota in mice fed an HF and green tea infusion diet. A 4% green tea infusion significantly increased intestinal microflora in obese mice and reduced high-fat diet-induced metabolic alterations by preventing metabolic disorders associated with the disrupted microflora. Additionally, we identified 32 genera, including Akkermansia, Saccharofermentans, Acetatifactor, Bacteroides, Alistipes, Allobaculum, and Falsiporphyromonas, as HF-associated biomarkers. Among these, TPP significantly increased Akkermansia and played the most important role in restoring the bacterial community essential for anti-obesity stimulation. Our study suggests that green tea intake is an effective alternative for HF-induced disorders with manipulation of gut microbial communities.

Author Contributions

Conceptualization, H.M., J.L. and X.L.; Methodology, H.M. and J.L; Formal analysis, H.M. and J.L.; Data curation, H.M. and J.L.; Writing—original draft, H.M. and J.L.; Revision, H.M., J.L., S.L. and A.J.; Writing—Review and editing, H.M., J.L., A.J., S.L., J.Z., Y.W., X.C. and X.L.; Funding acquisition, X.L. and Q.Y. All authors have read and agreed to the published version of the manuscript.

Funding

This work was supported financially by Expert Workstation of Yunnan Province (202305AF150198), Key Research and Development Program of Sichuan Province (202105AF150045, 2023YFN0010), and the National Key Research and Development Program of China (2022YFD1601800).

Institutional Review Board Statement

This animal experiment was approved by the Animal Care and Use Committee of Nanjing Agricultural University [SYXK (SU) 2021-0086].

Informed Consent Statement

Not applicable.

Data Availability Statement

Data are contained within the article.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Moustafa, J.; Froguel, P. From obesity genetics to the future of personalized obesity therapy. Nat. Rev. Endocrinol. 2013, 9, 402–413. [Google Scholar]
  2. Lee, H.; Jenner, A.; Low, C.; Lee, Y. Effect of tea phenolics and their aromatic fecal bacterial metabolites on intestinal microbiota. Res. Microbiol. 2006, 157, 876–884. [Google Scholar] [CrossRef]
  3. Kahn, R.; Buse, J.; Ferrannini, E.; Stern, M. The metabolic syndrome. Lancet 2005, 366, 1921–1922. [Google Scholar] [CrossRef]
  4. Ford, E.S. Prevalence of the metabolic syndrome defined by the international diabetes federation among adults in the U.S. Diabetes Care 2005, 28, 2745–2749. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  5. Feng, L.; Zhou, J.; Zhang, L.; Liu, P.; Zheng, P.; Gao, S.; Song, C.; Yu, Y.; Gong, Z.; Wan, X. Gut microbiota-mediated improvement of metabolic disorders by qingzhuan tea in high fat diet-fed mice. J. Funct. Foods 2021, 78, 104366. [Google Scholar]
  6. Compare, D.; Rocco, A.; Zamparelli, M.; Nardone, G. The gut bacteria-driven obesity development. Dig. Dis. 2016, 34, 221–229. [Google Scholar] [CrossRef] [PubMed]
  7. Turnbaugh, P.; Ley, R.; Mahowald, M.; Magrini, V.; Mardis, E.; Gordon, J. An obesity-associated gut microbiome with increased capacity for energy harvest. Nature 2006, 444, 1027–1031. [Google Scholar] [CrossRef]
  8. Cani, P.; Bibiloni, R.; Knauf, C.; Neyrinck, A.; Neyrinck, A.; Delzenne, N.; Bu-rcelin, R. Changes in gut microbiota control metabolic endotoxemia-induced inflammation in high-fat diet-induced obesity and diabetes in mice. Diabetes 2008, 57, 1470–1481. [Google Scholar] [CrossRef] [Green Version]
  9. Hu, S.; Chen, Y.; Zhao, S.; Sun, K.; Luo, L.; Zeng, L. Ripened Pu-Erh tea improved the enterohepatic circulation in a circadian rhythm disorder mice model. J. Agric. Food Chem. 2021, 69, 13533–13545. [Google Scholar] [CrossRef]
  10. Dumas, M.; Barton, R.; Toye, A.; Cloarec, O.; Blancher, C.; Rothwell, A.; Fearnside, J.; Tatoud, R.; Blanc, V.; Lindon, J.; et al. Metabolic profiling reveals a contribution of gut microbiota to fatty liver phenotype in insulin-resistant mice. Proc. Natl. Acad. Sci. USA 2006, 103, 12511–12516. [Google Scholar]
  11. Hua, F.; Zhou, P.; Liu, P.; Bao, G. Rat plasma protein binding of kaempferol-3-O-rutinoside from Lu’an GuaPian tea and its anti-inflammatory mechanism for cardiovascular protection. J. Food Biochem. 2021, 45, e13749. [Google Scholar] [CrossRef] [PubMed]
  12. Wan, C.C.; Hu, X.; Li, M.; Rengasamy, K.R.R.; Cai, Y.; Liu, Z. Potential protective function of green tea polyphenol EGCG against high glucose-induced cardiac injury and aging. J. Funct. Foods 2023, 104, 105506. [Google Scholar] [CrossRef]
  13. Bose, M.; Lambert, J.; Ju, J.; Reuhl, K.; Shapses, S.; Yang, C. The major green tea polyphenol, (-)-Epigallocatechin-3-Gallate, inhibits obesity, metabolic syndrome, and fatty liver disease in high-fat-fed mice. J. Nutr. 2008, 138, 1677–1683. [Google Scholar] [CrossRef] [Green Version]
  14. Sae-tan, S.; Grove, K.; Lambert, J. Weight control and prevention of metabolic syndrome by green tea. Pharmacol. Res. 2011, 64, 146–154. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  15. Serisier, S.; Leray, V.; Poudroux, W.; Magot, T.; Ouguerram, K.; Nguyen, P. Effects of green tea on insulin sensitivity, lipid profile and expression of P-PARα and PPARγ and their target genes in obese dogs. Br. J. Nutr. 2008, 99, 1208–1216. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  16. Yang, C.; Zhang, J.; Zhang, L.; Huang, J.; Wang, Y. Mechanisms of body weight reduction and metabolic syndrome alleviation by tea. Mol. Nutr. Food Res. 2016, 60, 160–174. [Google Scholar] [CrossRef] [Green Version]
  17. Wan, C.; Ouyang, J.; Li, M.; Rengasamy, K.; Liu, Z. Effects of green tea polyphenol extract and epigallocatechin-3-o-gallate on diabetes mellitus and diabetic complications: Recent advances. Crit. Rev. Food Sci. Nutr. 2022, 1–29. [Google Scholar] [CrossRef]
  18. Cardona, F.; Andres-Lacueva, C.; Tulipani, S.; Tinahones, F.; Queipo-Ortuno, M. Benefits of polyphenols on gut microbiota and implications in human health. J. Nutr. Biochem. 2013, 24, 1415–1422. [Google Scholar] [CrossRef] [Green Version]
  19. Seo, D.; Jeong, H.; Cho, D.; Lee, B.; Lee, J.; Choi, J.; Bae, I.; Lee, S. Fermented green tea extract alleviates obesity and related complications and alters gut microbiota composition in diet-induced obese mice. J. Med. Food 2015, 18, 549–556. [Google Scholar] [CrossRef] [Green Version]
  20. Liu, Y.; Luo, L.; Luo, Y.; Zhang, J.; Wang, X.; Sun, K.; Zeng, L. Prebiotic properties of green and dark tea contribute to protective effects in chemical-induced colitis in mice: A fecal microbiota transplantation study. J. Agric. Food Chem. 2020, 68, 6368–6380. [Google Scholar] [CrossRef]
  21. Derrien, M.; Belzer, C.; de Vos, W. Akkermansia muciniphila and its role in regulating host functions. Microb. Pathog. 2017, 106, 171–181. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  22. Everard, A.; Belzer, C.; Geurts, L.; Ouwerkerk, J.; Druart, C.; Bindels, L.; Guiot, Y.; Derrien, M.; Muccioli, G.; Delzenne, N.; et al. Cross-talk between Akkermansia muciniphila and intestinal epithelium controls diet-induced obesity. Proc. Natl. Acad. Sci. USA 2013, 110, 9066–9071. [Google Scholar] [CrossRef] [PubMed]
  23. Huang, Y.; Sheng, J.; Yang, F.; Hu, Q. Effect of enzyme inactivation by microwave and oven heating on preservation quality of green tea. J. Food Eng. 2007, 78, 687–692. [Google Scholar] [CrossRef]
  24. Walk, C.; Cowieson, A.; Remus, J.; Novak, C.; McElroy, A. Effects of dietary enzymes on performance and intestinal goblet cell number of broilers exposed to a live coccidia oocyst vaccine. Poult. Sci. 2011, 90, 91–98. [Google Scholar] [CrossRef]
  25. Milani, C.; Hevia, A.; Foroni, E.; Duranti, S.; Turroni, F.; Lugli, G.; Sanchez, B.; Martin, R.; Gueimonde, M.; van Sinderen, D.; et al. Assessing the fecal microbiota: An optimized ion torrent 16S rRNA gene-based analysis protocol. PLoS ONE 2013, 8, e68739. [Google Scholar] [CrossRef] [PubMed]
  26. Edgar, R.C. UPARSE: Highly accurate OTU sequences from microbial amplicon reads. Nat. Methods 2013, 10, 996–998. [Google Scholar] [CrossRef] [PubMed]
  27. Sun, J.; Zhang, Q.; Zhou, J.; Wei, Q. Illumina amplicon sequencing of 16S rRNA tag reveals bacterial community development in the rhizosphere of apple nurseries at a replant disease site and a new planting site. PLoS ONE 2014, 9, e111744. [Google Scholar] [CrossRef] [Green Version]
  28. Caporaso, J.; Lauber, C.; Walters, W.; Berg-Lyons, D.; Lozupone, C.; Turnbaugh, P.; Fierer, N.; Knight, R. Global patterns of 16S rRNA diversity at a depth of millions of sequences per sample. Proc. Natl. Acad. Sci. USA 2011, 108, 4516–4522. [Google Scholar] [CrossRef]
  29. Saleh, I.; Ali, Z.; Abe, N.; Wilson, F.; Hamada, F.; Abd-Ellah, M.; Walker, L.; Khan, I.; Ashfaq, M. Effect of green tea and its polyphenols on mouse liver. Fitoterapia 2013, 90, 151–159. [Google Scholar] [CrossRef]
  30. Saleh, I.A.; Hamada, F.M.; Abd-Ellah, M.F.; Khan, I.A.; Walker, L.A.; Ashfaq, M.K. Consumption of EGCG can become hepatotoxic under inflammatory condition. Planta Med. 2013, 79, P95. [Google Scholar] [CrossRef]
  31. van Duynhoven, J.; Vaughan, E.; Jacobs, D.; Kemperman, R.; van Velzen, E.; Gross, G.; Roger, L.; Possemiers, S.; Smilde, A.; Dore, J.; et al. Metabolic fate of polyphenols in the human superorganism. Proc. Natl. Acad. Sci. USA 2011, 108, 4531–4538. [Google Scholar] [CrossRef] [PubMed]
  32. Higdon, J.; Frei, B. Tea catechins and polyphenols: Health effects, metabolism, and antioxidant functions. Crit. Rev. Food Sci. Nutr. 2003, 43, 89–143. [Google Scholar] [CrossRef] [PubMed]
  33. Candela, M.; Maccaferri, S.; Turroni, S.; Carnevali, P.; Brigidi, P. Functional intestinal microbiome, new frontiers in prebiotic design. Int. J. Food Microbiol. 2010, 140, 93–101. [Google Scholar] [CrossRef]
  34. Cheng, M.; Zhang, X.; Miao, Y.; Cao, J.; Wu, Z.; Weng, P. The modulatory effect of (-)-epigallocatechin 3-O-(3-O-methyl) gallate (EGCG3″Me) on intestinal microbiota of high fat diet-induced obesity mice model. Food Res. Int. 2017, 92, 9–16. [Google Scholar] [CrossRef] [PubMed]
  35. Guo, X.; Cheng, M.; Zhang, X.; Cao, J.; Wu, Z.; Weng, P. Green tea polyphenols reduce obesity in high-fat diet-induced mice by modulating intestinal microbiota composition. Int. J. Food Sci. Technol. 2017, 52, 1723–1730. [Google Scholar] [CrossRef]
  36. Henning, S.; Yang, J.; Hsu, M.; Lee, R.; Grojean, E.; Ly, A.; Tseng, C.; Heber, D.; Li, Z. Decaffeinated green and black tea polyphenols decrease weight gain and alter microbiome populations and function in diet-induced obese mice. Eur. J. Nutr. 2018, 57, 2759–2769. [Google Scholar] [CrossRef]
  37. Janssens, P.L.H.R.; Penders, J.; Hursel, R.; Budding, A.E.; Savelkoul, P.H.M.; Westerterp-Plantenga, M.S. Long-term green tea supplementation does not change the human gut microbiota. PLoS ONE 2016, 11, e0153134. [Google Scholar] [CrossRef]
  38. Liu, Z.; Chen, Z.; Guo, H.; He, D.; Zhao, H.; Wang, Z.; Zhang, W.; Liao, L.; Zhang, C.; Ni, L. The modulatory effect of infusions of green tea, oolong tea, and black tea on gut microbiota in high-fat-induced obese mice. Food Funct. 2016, 7, 4869–4879. [Google Scholar] [CrossRef]
  39. Singh, D.; Singh, J.; Boparai, R.; Zhu, J.; Mantri, S.; Khare, P.; Khardori, R.; Kondepudi, K.; Chopra, K.; Bishnoi, M. Isomalto-oligosaccharides, a prebiotic, functionally augment green tea effects against high fat diet-induced metabolic alterations via preventing gut dysbacteriosis in mice. Pharmacol. Res. 2017, 123, 103–113. [Google Scholar] [CrossRef]
  40. Anhe, F.; Roy, D.; Pilon, G.; Dudonne, S.; Matamoros, S.; Varin, T.; Garofalo, C.; Moine, Q.; Desjardins, Y.; Levy, E.; et al. A polyphenol-rich cranberry extract protects from diet-induced obesity, insulin resistance and intestinal inflammation in association with increased Akkermansia spp. population in the gut microbiota of mice. Gut 2015, 64, 872–883. [Google Scholar] [CrossRef] [Green Version]
  41. Kemperman, R.; Gross, G.; Mondot, S.; Possemiers, S.; Marzorati, M.; Van de Wiele, T.; Dore, J.; Vaughan, E. Impact of polyphenols from black tea and red wine/grape juice on a gut model microbiome. Food Res. Int. 2013, 53, 659–669. [Google Scholar] [CrossRef]
  42. Zhang, Z.; Wu, X.; Cao, S.; Cromie, M.; Shen, Y.; Feng, Y.; Yang, H.; Li, L. Chlorogenic acid ameliorates experimental colitis by promoting growth of Akkermansia in mice. Nutrients 2017, 9, 677. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  43. Yang, G.; Xue, Y.; Zhang, H.; Du, M.; Zhu, M. Favourable effects of grape seed extract on intestinal epithelial differentiation and barrier function in IL10-deficient mice. Br. J. Nutr. 2015, 114, 15–23. [Google Scholar] [CrossRef] [Green Version]
  44. Martin, A.R.; La Casa, C.; Villegas, I.; Herrerias, J.M.; Alarcon de la Lastra, C. Resveratrol, a polyphenol found in grapes, suppresses oxidative damage and stimulates apoptosis during early colonic inflammation in rats. Biochem. Pharmacol. 2004, 67, 1399–1410. [Google Scholar]
  45. Roopchand, D.; Carmody, R.; Kuhn, P.; Moskal, K.; Rojas-Silva, P.; Turnbaugh, P.; Raskin, I. Dietary polyphenols promote growth of the gut bacterium Akkermansia muciniphila and attenuate high-fat diet-induced metabolic syndrome. Diabetes 2015, 64, 2847–2858. [Google Scholar] [CrossRef] [Green Version]
  46. Min, B.R.; Perkins, D.; Wright, C.; Dawod, A.; Min, B.J.; Terrill, T.H. Effects of feeding two different tannin-containing diets on ruminal fermentation profiles and microbial community changes in meat goats. Agric. Food Anal. Bacteriol. 2015, 5, 153–165. [Google Scholar]
  47. Ravussin, Y.; Koren, O.; Spor, A.; LeDuc, C.; Gutman, R.; Stombaugh, J.; Knight, R.; Ley, R.; Leibel, R. Responses of gut microbiota to diet composition and weight loss in lean and obese mice. Obesity 2012, 20, 738–747. [Google Scholar] [CrossRef] [PubMed]
  48. Martinez, I.; Wallace, G.; Zhang, C.; Legge, R.; Benson, A.; Carr, T.; Moriyama, E.; Walter, J. Diet-induced metabolic improvements in a hamster model of hypercholesterolemia are strongly linked to alterations of the gut microbiota. Appl. Environ. Microbiol. 2009, 75, 4175–4184. [Google Scholar] [CrossRef] [Green Version]
  49. Rehman, A.; Sina, C.; Gavrilova, O.; Hasler, R.; Ott, S.; Baines, J.; Schreiber, S.; Rosenstiel, P. Nod2 is essential for temporal development of intestinal microbial communities. Gut 2011, 60, 1354–1362. [Google Scholar] [CrossRef]
  50. Feng, Q.; Liang, S.; Jia, H.; Stadlmayr, A.; Tang, L.; Lan, Z.; Zhang, D.; Xia, H.; Xu, X.; Jie, Z.; et al. Gut microbiome development along the colorectal adenoma-carcinoma sequence. Nat. Commun. 2015, 6, 6528. [Google Scholar] [CrossRef] [Green Version]
  51. Xie, G.; Wang, X.; Liu, P.; Wei, R.; Chen, W.; Rajani, C.; Hernandez, B.; Alegado, R.; Dong, B.; Li, D.; et al. Distinctly altered gut microbiota in the progression of liver disease. Oncotarget 2016, 7, 19355–19366. [Google Scholar] [CrossRef] [PubMed] [Green Version]
  52. Li, Q.; Huang, J.; Fu, D.; Li, Y.; Liu, Z. Tea loses weight and its preventive effect on metabolic syndrome in the human body. Chinatea 2019, 5, 7–13. [Google Scholar]
  53. Janssens, P.L.H.R.; Hursel, R.; Westerterp-Plantenga, M.S. Nutraceuticals for body-weight management: The role of green tea catechins. Physiol. Behav. 2016, 162, 83–87. [Google Scholar] [CrossRef] [PubMed]
  54. Chen, G.; Xie, M.; Dai, Z.; Wan, P.; Ye, H.; Zeng, X.; Sun, Y. Kudingcha and Fuzhuan brick tea prevent obesity and modulate gut microbiota in high-fat diet fed mice. Mol. Nutr. Food Res. 2018, 62, 1700485. [Google Scholar] [CrossRef] [PubMed]
Foods 12 02953 g001
Figure 1. Green tea prevents HF-induced obesity in mice. Image of hypodermic fat in different groups of mice (A). The body weight (B), epididymal fat (C), and abdominal epididymal fat (D) in the different groups of mice. Water (E) and food (F) intake in different groups of mice. LF represents low-fat-fed mice and HF represents high-fat-fed mice. * p < 0.05; ** p < 0.01; *** p < 0.001.
Figure 1. Green tea prevents HF-induced obesity in mice. Image of hypodermic fat in different groups of mice (A). The body weight (B), epididymal fat (C), and abdominal epididymal fat (D) in the different groups of mice. Water (E) and food (F) intake in different groups of mice. LF represents low-fat-fed mice and HF represents high-fat-fed mice. * p < 0.05; ** p < 0.01; *** p < 0.001.
Foods 12 02953 g001
Foods 12 02953 g002
Figure 2. Green tea improves obesity-caused hepatic dysfunction and intestinal barrier integrity. The liver cell (A) and intestinal villus (B) in different groups of mice with HE staining (100×).
Figure 2. Green tea improves obesity-caused hepatic dysfunction and intestinal barrier integrity. The liver cell (A) and intestinal villus (B) in different groups of mice with HE staining (100×).
Foods 12 02953 g002
Foods 12 02953 g003
Figure 3. Green tea prevents fat-induced gut dysbiosis. The gut microbiota composition by Illumina MiSeq platform-based analysis of V4 region (A). PCoA separation between LF and HF, HF and HF+2%, as well as HF and HF+4%tea treatment groups. Rvegan package was used with 999 per mutation (B). Venn diagrams showing the specific bacterial amount (C).
Figure 3. Green tea prevents fat-induced gut dysbiosis. The gut microbiota composition by Illumina MiSeq platform-based analysis of V4 region (A). PCoA separation between LF and HF, HF and HF+2%, as well as HF and HF+4%tea treatment groups. Rvegan package was used with 999 per mutation (B). Venn diagrams showing the specific bacterial amount (C).
Foods 12 02953 g003
Foods 12 02953 g004
Figure 4. Components of green tea reduce obesity. Image of abdominal fat in mice (A). The body weight changes of mice during the 8-week intervention of TPP, caffeine, and L-theanine (B). Epididymal fat in green tea-treated mice (C) and in the HF mice (D). Water (E) and food (F) intake in different groups of mice. All the other treatments are compared with HF group (n = 7). * p < 0.05; ** p < 0.01; *** p < 0.001.
Figure 4. Components of green tea reduce obesity. Image of abdominal fat in mice (A). The body weight changes of mice during the 8-week intervention of TPP, caffeine, and L-theanine (B). Epididymal fat in green tea-treated mice (C) and in the HF mice (D). Water (E) and food (F) intake in different groups of mice. All the other treatments are compared with HF group (n = 7). * p < 0.05; ** p < 0.01; *** p < 0.001.
Foods 12 02953 g004
Foods 12 02953 g005
Figure 5. Components of green tea improve obesity-caused hepatic dysfunction and intestinal barrier integrity. The liver cell (A) and intestinal villus (B) in mice via HE staining (100×). Arrows indicate goblet cells.
Figure 5. Components of green tea improve obesity-caused hepatic dysfunction and intestinal barrier integrity. The liver cell (A) and intestinal villus (B) in mice via HE staining (100×). Arrows indicate goblet cells.
Foods 12 02953 g005
Foods 12 02953 g006
Figure 6. Components of green tea reduce obesity by modulating disrupted microbiota. Relative abundance of bacterial taxa (A). PCoA showing the distinct clustering of different components of tea groups (B). Venn diagrams showing the specific bacterial amount (C). All the other treatments are compared with HF group (n = 7).
Figure 6. Components of green tea reduce obesity by modulating disrupted microbiota. Relative abundance of bacterial taxa (A). PCoA showing the distinct clustering of different components of tea groups (B). Venn diagrams showing the specific bacterial amount (C). All the other treatments are compared with HF group (n = 7).
Foods 12 02953 g006
Foods 12 02953 g007
Figure 7. Biomarkers of gut microbes with significant differences between LF and HF groups. The colored part indicates a significant difference from the HF group, while the color depth indicates the relative content of gut microbes. Act-Actinobacteria; Bac-Bacteroidetes; Fir-Firmicutes; Ver-Verrucomicrobia. Aqu-Aquificae; Cre-Crenarchaeota; Cya-Cyanobacteria; Chl-Chloroplast; Par-Parvarchaeota; The-Thermotogae.
Figure 7. Biomarkers of gut microbes with significant differences between LF and HF groups. The colored part indicates a significant difference from the HF group, while the color depth indicates the relative content of gut microbes. Act-Actinobacteria; Bac-Bacteroidetes; Fir-Firmicutes; Ver-Verrucomicrobia. Aqu-Aquificae; Cre-Crenarchaeota; Cya-Cyanobacteria; Chl-Chloroplast; Par-Parvarchaeota; The-Thermotogae.
Foods 12 02953 g007
Table 1. Constitute profile of green tea and TPP.
Table 1. Constitute profile of green tea and TPP.
Component (gL−1)ECEGCECGEGCGCGCGCGCGTPPCafThea
4% green tea0.230.610.691.910.070.340.310.186.071.521.50
6 gL−1 TPP0.150.010.552.350.010.220.360.146.00--
Note: EC, (-)-epicatechin; EGC, (-)-epigallocatechin; ECG, (-)-epicatechin gallate; EGCG, (-)-epigallocatechin gallate; C, (-)-catechin; GC, (-)-gallocatechin; GCG, (-)-gallocatechin gallate; CG, (-)-catechin gallate; TPP, total tea polyphenols; Caf, caffeine; Thea, L-theamine; -, not detected.
Table 2. Biochemical levels in mice serum and liver by green tea.
Table 2. Biochemical levels in mice serum and liver by green tea.
TreatmentLFHFHF+1%HF+2%HF+4%
TC (mmol/L)3.76 ± 0.14 ***6.05 ± 0.345.77 ± 0.306.18 ± 0.144.85 ± 0.17 **
HDL (mmol/L)2.00 ± 0.271.73 ± 0.182.50 ± 0.21 *2.08 ± 0.102.25 ± 0.01
LDL (mmol/L)0.84 ± 0.12 ***2.16 ± 0.251.66 ± 0.08 *1.93 ± 0.081.49 ± 0.06 **
FBG (mmol/L)4.87 ± 0.19 ***7.67 ± 0.206.44 ± 0.38 *4.17 ± 0.30 ***7.01 ± 0.46
INS (mIU/L)11.62 ± 1.359.69 ± 1.1816.07 ± 2.39 *17.18 ± 1.40 *13.18 ± 0.83
ALT (Kar U)4.83 ± 1.67 *11.92 ± 2.434.89 ± 1.38 *2.83 ± 1.01 **1.95 ± 1.00 **
AST (Kar U)148.00 ± 12.21148.20 ± 4.5490.22 ± 8.09 **120.30 ± 18.39111.20 ± 12.99 *
LPS (μg/L)207.90 ± 12.38245.90 ± 12.84239.10 ± 21.94234.00 ± 11.44237.90 ± 8.12
TNF-α (ng/L)243.60 ± 23.51 *309.10 ± 17.32299.50 ± 8.29309.00 ± 19.94275.80 ± 6.95 *
MCP-1 (ng/L)254.60 ± 33.97 *193.90 ± 15.58222.50 ± 37.57294.50 ± 42.64 **186.10 ± 48.32
TG (mmol/g pro)0.13 ± 0.01 **0.23 ± 0.020.20 ± 0.020.13 ± 0.01 **0.18 ± 0.02
FFA (mmol/g pro)0.10 ± 0.010.11 ± 0.010.07 ± 0.01*0.06 ± 0.02 **0.06 ± 0.01 *
Note: All the other treatments are compared with HF group. Data obtained from three replicate experiments are shown as mean ± SEMs. * p < 0.05; ** p < 0.01; *** p < 0.001. LF, low-fat diet; HF, high-fat diet; HF+1%, high-fat diet with 1% green tea infusion; HF+2%, high-fat diet with 2% green tea infusion; HF+4%represent, high-fat diet with 4% green tea infusion.
Table 3. Biochemical levels of mice in serum and liver by functional components.
Table 3. Biochemical levels of mice in serum and liver by functional components.
TreatmentLFHFHF + TPPHF + TheaHF + Caf
TC (mmol/L)3.76 ± 0.14 ***6.05 ± 0.345.09 ± 0.394.54 ± 0.32 **5.59 ± 0.30
HDL (mmol/L)2.00 ± 0.271.73 ± 0.182.75 ± 0.16 **2.35 ± 0.192.36 ± 0.18
LDL (mmol/L)0.84 ± 0.12 ***2.16 ± 0.251.56 ± 0.10 *1.53 ± 0.07 *1.61 ± 0.27 *
FBG (mmol/L)4.87 ± 0.19 ***7.67 ± 0.207.93 ± 0.248.02 ± 0.368.10 ± 0.21
INS (mIU/L)11.62 ± 1.359.69 ± 1.1810.17 ± 0.9010.07 ± 2.0712.79 ± 1.29
ALT (Kar U)4.83 ± 1.67 *11.92 ± 2.4312.55 ± 1.3913.80 ± 0.8211.30 ± 1.15
AST (Kar U)148.00 ± 12.21148.20 ± 4.5470.55 ± 9.18 ***84.82 ± 9.73 ***103.1 ± 10.39 *
LPS (μg/L)207.90 ± 12.38245.90 ± 12.84186.00 ± 8.61 *241.34 ± 15.66224.36 ± 16.95
TNF-α (ng/L)243.60 ± 23.51 *309.10 ± 17.32250.97 ± 11.29 *284.53 ± 21.73292.21 ± 16.61
MCP-1 (ng/L)254.60 ± 33.97 *193.90 ± 15.58197.21 ± 19.30270.79 ± 42.42247.65 ± 36.67
TG (mmol/g pro)0.13 ± 0.01 **0.23 ± 0.020.14 ± 0.01 **0.17 ± 0.020.19 ± 0.03
FFA (mmol/g pro)0.10 ± 0.010.11 ± 0.010.06 ± 0.01 **0.09 ± 0.010.06 ± 0.01 **
Note: All the other treatments are compared with HF group. Data obtained from three replicate experiments are shown as mean ± SEMs. * p < 0.05; ** p < 0.01; *** p < 0.001. LF, low-fat diet; HF, high-fat diet; HF, high-fat diet; HF+TPP, high-fat diet with 6g/L TPP infusions; HF+Thea, high-fat diet with 1.5 g/L Thea infusions; HF+Caf, high-fat diet with 1.5 g/L Caf infusions.
Table 4. Biochemical levels in functional components of treated mice.
Table 4. Biochemical levels in functional components of treated mice.
TreatmentLFHFHF + TPPHF + TheaHF + Caf
Goblet cell/villus5.36 ± 1.512.80 ± 0.3327.67 ± 4.59 ***24.29 ± 7.08 ***10.44 ± 3.00
Villus height (μm)347.50 ± 29.07289.60 ± 29.71390.50 ± 33.02 *411.30 ± 22.99 *248.70 ± 14.56
Crypt depth (μm)134.40 ± 4.65 ***90.55 ± 5.64133.40 ± 11.19 ***118.30 ± 4.52 *119.80 ± 4.78 **
Note: All the other treatments are compared with HF group. Data obtained from three replicate experiments are shown as mean ± SEMs. * p < 0.05; ** p < 0.01; *** p < 0.001. LF, low-fat diet; HF, high-fat diet; HF+TPP, high-fat diet with 6g/L TPP infusions; HF + Thea, high-fat diet with 1.5 g/L Thea infusions; HF+Caf, high-fat diet with 1.5 g/L Caf infusions.
Disclaimer/Publisher’s Note: The statements, opinions and data contained in all publications are solely those of the individual author(s) and contributor(s) and not of MDPI and/or the editor(s). MDPI and/or the editor(s) disclaim responsibility for any injury to people or property resulting from any ideas, methods, instructions or products referred to in the content.

Share and Cite

MDPI and ACS Style

Mei, H.; Li, J.; Liu, S.; Jeyaraj, A.; Zhuang, J.; Wang, Y.; Chen, X.; Yuan, Q.; Li, X. The Role of Green Tea on the Regulation of Gut Microbes and Prevention of High-Fat Diet-Induced Metabolic Syndrome in Mice. Foods 2023, 12, 2953. https://doi.org/10.3390/foods12152953

AMA Style

Mei H, Li J, Liu S, Jeyaraj A, Zhuang J, Wang Y, Chen X, Yuan Q, Li X. The Role of Green Tea on the Regulation of Gut Microbes and Prevention of High-Fat Diet-Induced Metabolic Syndrome in Mice. Foods. 2023; 12(15):2953. https://doi.org/10.3390/foods12152953

Chicago/Turabian Style

Mei, Huiling, Jin Li, Shujing Liu, Anburaj Jeyaraj, Jing Zhuang, Yuhua Wang, Xuan Chen, Qijun Yuan, and Xinghui Li. 2023. "The Role of Green Tea on the Regulation of Gut Microbes and Prevention of High-Fat Diet-Induced Metabolic Syndrome in Mice" Foods 12, no. 15: 2953. https://doi.org/10.3390/foods12152953

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop