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Liu R, Wang J, Zhao Y, Zhou Q, Yang X, Gao Y, Li Q, Bai M, Liu J, Liang Y, Zhu X. Study on the mechanism of modified Gegen Qinlian decoction in regulating the intestinal flora-bile acid-TGR5 axis for the treatment of type 2 diabetes mellitus based on macro genome sequencing and targeted metabonomics integration. PHYTOMEDICINE : INTERNATIONAL JOURNAL OF PHYTOTHERAPY AND PHYTOPHARMACOLOGY 2024; 132:155329. [PMID: 38853123 DOI: 10.1016/j.phymed.2023.155329] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 05/24/2023] [Revised: 12/12/2023] [Accepted: 12/30/2023] [Indexed: 06/11/2024]
Abstract
BACKGROUND Currently, there are many drugs available for the treatment of type 2 diabetes mellitus (T2DM), but most of them cause various side effects due to the need for long-term use. As a traditional Chinese medicine, Gegen Qinlian Decoction (GQD) has shown good efficacy and low side effects in the treatment of T2DM in both clinical and basic research. Based on relevant traditional Chinese medicine theories, dried ginger is innovatively added the formula of traditional GQD to create a modified GQD. This modification reduces the side effects of traditional GQD while exerting its therapeutic effect on T2DM. Previous studies have found that the modified GQD can regulate endoplasmic reticulum stress in the liver, inhibit hepatic gluconeogenesis, protect pancreatic islet β cells, and control blood sugar levels by inhibiting the FXR/neuronal ceramide signaling pathway. GQD can also regulate the intestinal microbiota to achieve therapeutic and protective effects in various gastrointestinal diseases. However, there is no research exploring whether the modified GQD achieves its therapeutic mechanism for T2DM by regulating the intestinal microbiota. PURPOSE To explore the mechanism of modified GQD in the treatment of T2DM based on multi-omics, focusing on its effect on the "intestinal flora bile acid TGR5'' axis. METHODS The T2DM model was established using db/db mice, which were randomly divided into a model group, metformin group, high-dose GQD group, medium-dose GQD group, low-dose GQD group, while m/m mice were used as blank control. The drug intervention lasted for 12 weeks, during which the general conditions, oral glucose tolerance (OGT), blood glucose, and lipid-related indexes were recorded. Additionally, the fasting insulin (FINS), c-peptide, GLP-1 in serum, and cAMP in the ileum were measured by ELISA assay. Furthermore, the composition, abundance, and function of the intestinal microbiota were determined by macro genome sequencing, while bile acid was detected by targeted metabonomics. For histological evaluation, HE staining was used to observe the pathological changes of the ileum and pancreas, and the ultrastructure of the ileum and pancreas was observed by transmission electron microscopy. Apoptosis in the ileum tissue was detected by Tunel staining. Moreover, the mRNA and protein expressions of TGR5, PKA, CREB, PC1/3, GLP-1, and their phosphorylation levels in the ileum were detected by qPCR, immunohistochemistry, and Western blot; The expression of INS in the pancreas was also evaluated using immunohistochemistry. Finally, double immunofluorescence staining was used to detect the co-localization expression of TGR5 and GLP-1, NeuroD1, and GLP-1 in the ileum. RESULTS The modified GQD was found to significantly reduce blood glucose, improve oral glucose tolerance, and blood lipid levels, as well as alleviate the injury of the ileum and pancreas in T2DM mice. Furthermore, modified GQD was found to effectively regulate intestinal flora, improve bile acid metabolism, activate the TRG5/cAMP/PKA/CREB signal pathway, and stimulate GLP-1 secretion. CONCLUSION GQD can regulate the "intestinal flora-bile acid-TGR5" axis and has a therapeutic effect on T2DM in mice.
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Affiliation(s)
- Rong Liu
- Jiangxi University of Chinese Medicine, Nanchang 330004, Jiangxi, PR China; Gansu University of Chinese Medicine, Lanzhou 730000, Gansu, PR China; Research Center of Traditional Chinese Medicine, Gansu Province, Lanzhou 730000, Gansu, PR China
| | - Jiahui Wang
- Gansu University of Chinese Medicine, Lanzhou 730000, Gansu, PR China
| | - Yikun Zhao
- Gansu University of Chinese Medicine, Lanzhou 730000, Gansu, PR China
| | - Qi Zhou
- Gansu University of Chinese Medicine, Lanzhou 730000, Gansu, PR China
| | - Xia Yang
- Gansu University of Chinese Medicine, Lanzhou 730000, Gansu, PR China
| | - Yankui Gao
- Gansu University of Chinese Medicine, Lanzhou 730000, Gansu, PR China
| | - Qin Li
- Gansu University of Chinese Medicine, Lanzhou 730000, Gansu, PR China; Gansu Health Vocational College, Gansu Province, Lanzhou 730000, Gansu, PR China
| | - Min Bai
- Gansu University of Chinese Medicine, Lanzhou 730000, Gansu, PR China
| | - Jiahui Liu
- Research Center of Traditional Chinese Medicine, Gansu Province, Lanzhou 730000, Gansu, PR China
| | - Yonglin Liang
- Gansu University of Chinese Medicine, Lanzhou 730000, Gansu, PR China; Research Center of Traditional Chinese Medicine, Gansu Province, Lanzhou 730000, Gansu, PR China.
| | - Xiangdong Zhu
- Ningxia Medical University, Yinchuan 750004, Ningxia Hui Autonomous Region, PR China.
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Gong P, Wang J, Wang S, Yang W, Yao W, Li N, Wang J, Zhao Y, Chen F, Xie J, Zhou T, Guo Y. Metabolomic analysis of the Puerarin hypoglycemic activity via AMPK-mTOR and PPARγ-NF-κB signaling pathways. PHYTOMEDICINE : INTERNATIONAL JOURNAL OF PHYTOTHERAPY AND PHYTOPHARMACOLOGY 2024; 130:155546. [PMID: 38833790 DOI: 10.1016/j.phymed.2024.155546] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 08/29/2023] [Revised: 03/11/2024] [Accepted: 03/17/2024] [Indexed: 06/06/2024]
Abstract
BACKGROUND Diabetes mellitus (DM) is a chronic metabolic disease characterized by hyperglycemia, and its increasing prevalence is a global concern. Early diagnostic markers and therapeutic targets are essential for DM prevention and treatment. Pueraria, derived from kudzu root, is used clinically for various symptoms, and its active compound, Puerarin, shows promise in improving insulin resistance and reducing inflammation. PURPOSE This study aims to evaluate the protective effects of metformin and Puerarin at different doses in an STZ-induced DM mouse model. The intricate metabolites within the serum of STZ-induced diabetic mice were subjected to thorough investigation, thus elucidating the intricate mechanism through which Puerarin demonstrates notable efficacy in the treatment of diabetes. METHODS An STZ-induced DM mouse model is established. Mice are treated with metformin and puerarin at varying doses. Physiological, biochemical, and histomorphological assessments are performed. Metabolomics analysis is carried out on serum samples from control, DM, metformin, and medium-dose Puerarin groups. Western blot and qRT-PCR technologies are used to validate the mechanisms. RESULTS The DM mouse model replicates abnormal blood glucose, insulin levels, physiological, biochemical irregularities, as well as liver and pancreas damage. Treatment with metformin and Puerarin restores these abnormalities, reduces organ injury, and modulates AMPK, PPARγ, mTOR, and NF-κB protein and mRNA expression. Puerarin activates the AMPK-mTOR and PPARγ-NF-κB signaling pathways, regulating insulin signaling, glucolipid metabolism, and mitigating inflammatory damage. CONCLUSION This study demonstrates that Puerarin has the potential to treat diabetes by modulating key signaling pathways. The focus was on the finding that Puerarin has been shown to improve insulin signaling, glucolipid metabolism and attenuate inflammatory damage through the modulation of the AMPK-mTOR and PPARγ-NF-κB pathways. The discovery of Puerarin's favorable protective effect and extremely complex mechanism highlights its prospect in the treatment of diabetes and provides theoretical support for its comprehensive development and utilization.
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Affiliation(s)
- Pin Gong
- School of Food science and Engineering, Shaanxi University of Science and Technology, Xi' an 710021, China; School of Biological and Pharmaceutical Sciences, Shaanxi University of Science and Technology, Xi' an 710021, China.
| | - Jiating Wang
- School of Food science and Engineering, Shaanxi University of Science and Technology, Xi' an 710021, China; School of Biological and Pharmaceutical Sciences, Shaanxi University of Science and Technology, Xi' an 710021, China
| | - Shuang Wang
- School of Food science and Engineering, Shaanxi University of Science and Technology, Xi' an 710021, China; School of Biological and Pharmaceutical Sciences, Shaanxi University of Science and Technology, Xi' an 710021, China
| | - Wenjuan Yang
- School of Food science and Engineering, Shaanxi University of Science and Technology, Xi' an 710021, China; School of Biological and Pharmaceutical Sciences, Shaanxi University of Science and Technology, Xi' an 710021, China
| | - Wenbo Yao
- School of Food science and Engineering, Shaanxi University of Science and Technology, Xi' an 710021, China; School of Biological and Pharmaceutical Sciences, Shaanxi University of Science and Technology, Xi' an 710021, China
| | - Nan Li
- School of Food science and Engineering, Shaanxi University of Science and Technology, Xi' an 710021, China; School of Biological and Pharmaceutical Sciences, Shaanxi University of Science and Technology, Xi' an 710021, China
| | - Jing Wang
- School of Food science and Engineering, Shaanxi University of Science and Technology, Xi' an 710021, China; School of Biological and Pharmaceutical Sciences, Shaanxi University of Science and Technology, Xi' an 710021, China
| | - Yanni Zhao
- School of Food science and Engineering, Shaanxi University of Science and Technology, Xi' an 710021, China; School of Biological and Pharmaceutical Sciences, Shaanxi University of Science and Technology, Xi' an 710021, China
| | - Fuxin Chen
- School of Chemistry and Chemical Engineering, Xi' an University of Science and Technology, Xi'an 710054, China
| | - Jianwu Xie
- School of Food science and Engineering, Shaanxi University of Science and Technology, Xi' an 710021, China; School of Biological and Pharmaceutical Sciences, Shaanxi University of Science and Technology, Xi' an 710021, China
| | - Ting Zhou
- China Certification & Inspection Group shaanxi Co, Ltd., Xi'an 710054, China
| | - Yuxi Guo
- School of Food science and Engineering, Shaanxi University of Science and Technology, Xi' an 710021, China; School of Biological and Pharmaceutical Sciences, Shaanxi University of Science and Technology, Xi' an 710021, China.
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Guo Y, Wang H, Liu Z, Chang Z. Comprehensive analysis of the microbiome and metabolome in pus from pyogenic liver abscess patients with and without diabetes mellitus. Front Microbiol 2023; 14:1211835. [PMID: 37426007 PMCID: PMC10328747 DOI: 10.3389/fmicb.2023.1211835] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/25/2023] [Accepted: 05/31/2023] [Indexed: 07/11/2023] Open
Abstract
Introduction Pyogenic liver abscess (PLA) patients combined with diabetes mellitus (DM) tend to have more severe clinical manifestations than without DM. The mechanism responsible for this phenomenon is not entirely clear. The current study therefore aimed to comprehensively analyze the microbiome composition and metabolome in pus from PLA patients with and without DM, to determine the potential reasons for these differences. Methods Clinical data from 290 PLA patients were collected retrospectively. We analyzed the pus microbiota using 16S rDNA sequencing in 62 PLA patients. In addition, the pus metabolomes of 38 pus samples were characterized by untargeted metabolomics analysis. Correlation analyses of microbiota, metabolites and laboratory findings were performed to identify significant associations. Results PLA patients with DM had more severe clinical manifestations than PLA patients without DM. There were 17 discriminating genera between the two groups at the genus level, among which Klebsiella was the most discriminating taxa. The ABC transporters was the most significant differential metabolic pathway predicted by PICRUSt2. Untargeted metabolomics analysis showed that concentrations of various metabolites were significantly different between the two groups and seven metabolites were enriched in the ABC transporters pathway. Phosphoric acid, taurine, and orthophosphate in the ABC transporters pathway were negatively correlated with the relative abundance of Klebsiella and the blood glucose level. Discussion The results showed that the relative abundance of Klebsiella in the pus cavity of PLA patients with DM was higher than those without DM, accompanied by changes of various metabolites and metabolic pathways, which may be associated with more severe clinical manifestations.
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Key Stratification of Microbiota Taxa and Metabolites in the Host Metabolic Health-Disease Balance. Int J Mol Sci 2023; 24:ijms24054519. [PMID: 36901949 PMCID: PMC10003303 DOI: 10.3390/ijms24054519] [Citation(s) in RCA: 4] [Impact Index Per Article: 4.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/31/2023] [Revised: 02/21/2023] [Accepted: 02/22/2023] [Indexed: 03/03/2023] Open
Abstract
Human gut microbiota seems to drive the interaction with host metabolism through microbial metabolites, enzymes, and bioactive compounds. These components determine the host health-disease balance. Recent metabolomics and combined metabolome-microbiome studies have helped to elucidate how these substances could differentially affect the individual host pathophysiology according to several factors and cumulative exposures, such as obesogenic xenobiotics. The present work aims to investigate and interpret newly compiled data from metabolomics and microbiota composition studies, comparing controls with patients suffering from metabolic-related diseases (diabetes, obesity, metabolic syndrome, liver and cardiovascular diseases, etc.). The results showed, first, a differential composition of the most represented genera in healthy individuals compared to patients with metabolic diseases. Second, the analysis of the metabolite counts exhibited a differential composition of bacterial genera in disease compared to health status. Third, qualitative metabolite analysis revealed relevant information about the chemical nature of metabolites related to disease and/or health status. Key microbial genera were commonly considered overrepresented in healthy individuals together with specific metabolites, e.g., Faecalibacterium and phosphatidylethanolamine; and the opposite, Escherichia and Phosphatidic Acid, which is converted into the intermediate Cytidine Diphosphate Diacylglycerol-diacylglycerol (CDP-DAG), were overrepresented in metabolic-related disease patients. However, it was not possible to associate most specific microbiota taxa and metabolites according to their increased and decreased profiles analyzed with health or disease. Interestingly, positive association of essential amino acids with the genera Bacteroides were observed in a cluster related to health, and conversely, benzene derivatives and lipidic metabolites were related to the genera Clostridium, Roseburia, Blautia, and Oscillibacter in a disease cluster. More studies are needed to elucidate the microbiota species and their corresponding metabolites that are key in promoting health or disease status. Moreover, we propose that greater attention should be paid to biliary acids and to microbiota-liver cometabolites and its detoxification enzymes and pathways.
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Al‐Emran HM, Rahman S, Hasan MS, Ul Alam R, Islam OK, Anwar A, Jahid MIK, Hossain A. Microbiome analysis revealing microbial interactions and secondary bacterial infections in COVID-19 patients comorbidly affected by Type 2 diabetes. J Med Virol 2023; 95:e28234. [PMID: 36258280 PMCID: PMC9874868 DOI: 10.1002/jmv.28234] [Citation(s) in RCA: 7] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 07/26/2022] [Revised: 09/03/2022] [Accepted: 10/13/2022] [Indexed: 01/27/2023]
Abstract
The mortality of coronavirus disease 2019 (COVID-19) disease is very high among the elderly or individuals having comorbidities such as obesity, cardiovascular diseases, lung infections, hypertension, and/or diabetes. Our study characterizes the metagenomic features in severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2)-infected patients with or without type 2 diabetes, to identify the microbial interactions associated with its fatal consequences.This study compared the baseline nasopharyngeal microbiome of SARS-CoV-2-infected diabetic and nondiabetic patients with controls adjusted for age and gender. The metagenomics based on next-generation sequencing was performed using Ion GeneStudio S5 Series and the data were analyzed by the Vegan-package in R. All three groups possessed significant bacterial diversity and dissimilarity indexes (p < 0.05). Spearman's correlation coefficient network analysis illustrated 183 significant positive correlations and 13 negative correlations of pathogenic bacteria (r = 0.6-1.0, p < 0.05), and 109 positive correlations between normal flora and probiotic bacteria (r > 0.6, p < 0.05). The SARS-CoV-2 diabetic group exhibited a significant increase in pathogens and secondary infection-causing bacteria (p < 0.05) with a simultaneous decrease of normal flora (p < 0.05). The dysbiosis of the bacterial community might be linked with severe consequences of COVID-19-infected diabetic patients, although a few probiotic strains inhibited numerous pathogens in the same pathological niches. This study suggested that the promotion of normal flora and probiotics through dietary supplementation and excessive inflammation reduction by preventing secondary infections might lead to a better outcome for those comorbid patients.
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Affiliation(s)
- Hassan M. Al‐Emran
- Department of Biomedical EngineeringJashore University of Science and TechnologyJashoreBangladesh
| | - Shaminur Rahman
- Department of MicrobiologyJashore University of Science and TechnologyJashoreBangladesh
| | - Md. Shazid Hasan
- Department of MicrobiologyJashore University of Science and TechnologyJashoreBangladesh
| | - Rubayet Ul Alam
- Department of MicrobiologyJashore University of Science and TechnologyJashoreBangladesh
| | - Ovinu Kibria Islam
- Department of MicrobiologyJashore University of Science and TechnologyJashoreBangladesh
| | - Ajwad Anwar
- Department of MicrobiologyUniversity of DhakaDhakaBangladesh
| | - Md. Iqbal K. Jahid
- Department of MicrobiologyJashore University of Science and TechnologyJashoreBangladesh,Genome CenterJashore University of Science and TechnologyJashoreBangladesh
| | - Anwar Hossain
- Genome CenterJashore University of Science and TechnologyJashoreBangladesh,Department of MicrobiologyUniversity of DhakaDhakaBangladesh
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Wang Y, Zhao Y, Nan X, Wang Y, Cai M, Jiang L, Luo Q, Xiong B. Rumen-protected glucose supplementation alters fecal microbiota and its metabolic profiles in early lactation dairy cows. Front Microbiol 2022; 13:1034675. [PMID: 36532465 PMCID: PMC9755595 DOI: 10.3389/fmicb.2022.1034675] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Grants] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 09/01/2022] [Accepted: 11/21/2022] [Indexed: 02/19/2024] Open
Abstract
INTRODUCTION Negative energy balance (NEB) is the pathological basis of metabolic disorders in early lactation dairy cows. Rumen-protected glucose (RPG) is a feed additive to relieve NEB of cows in early lactation. The aims of the current study were to evaluate the impact of different doses of RPG supply on fecal microbiota and metabolome in early lactation dairy cows, and their correlation with each other. METHODS A total of 24 multiparous Holstein dairy cows in early lactation were randomly assigned to one of four treatments for the first 35 days of the early lactation period, as follows: control group, a basal diet without RPG (CON); low RPG, a basal diet plus 200 g/d RPG (LRPG); medium RPG, a basal diet plus 350 g/d RPG (MRPG); or HRPG, high RPG, a basal diet plus 500 g/d RPG (HRPG). After 35 days, fecal samples were obtained from cows in all groups individually and using 16S rRNA gene sequencing to evaluate their microbiotas, while their metabolites were evaluated through metabolomics. RESULTS As expected, Firmicutes and Bacteroidetes were the core bacteria phyla. After RPG supplementation, there were an increase in Firmicutes and a decrease in Bacteroidetes. MRPG increased the relative abundance of cellulolytic bacteria, including Ruminococcaceae_UCG-005, Lachnospiraceae_UCG-008, Lachnospiraceae_FCS020_group, and Ruminiclostridium_9, while it decreased the relative abundance of Alistipes, Prevotellaceae_UCG-003, and Dorea. RPG supplementation could regulate the carbohydrate metabolism and amino acid metabolism pathway significantly and relieve lipolysis in dairy cows. Correlation analysis of fecal microbiome and metabolome showed that some major differential bacteria were the crucial contributors to differential metabolites. CONCLUSION In conclusion, RPG supplementation can affect the fecal microbial components and microbial metabolism, and 350 g RPG might be the ideal dose as a daily supplement.
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Affiliation(s)
- Yapin Wang
- State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yiguang Zhao
- State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Xuemei Nan
- State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Yue Wang
- State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Meng Cai
- State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Linshu Jiang
- Beijing Key Laboratory for Dairy Cow Nutrition, Beijing University of Agriculture, Beijing, China
| | - Qingyao Luo
- State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
| | - Benhai Xiong
- State Key Laboratory of Animal Nutrition, Institute of Animal Science, Chinese Academy of Agricultural Sciences, Beijing, China
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Fecal microbiota and metabolomics revealed the effect of long-term consumption of gallic acid on canine lipid metabolism and gut health. Food Chem X 2022; 15:100377. [PMID: 36211749 PMCID: PMC9532725 DOI: 10.1016/j.fochx.2022.100377] [Citation(s) in RCA: 12] [Impact Index Per Article: 6.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 05/06/2022] [Revised: 06/15/2022] [Accepted: 06/22/2022] [Indexed: 12/03/2022] Open
Abstract
Long-term consumption of 0.02%∼0.08% GA had no negative effect on canine body condition. GA intervention improved anti-oxidative and anti-inflammatory capacities. 0.08% GA regulated lipid metabolism in serum. 0.08% GA increased the relative abundance of SCFAs-producing bacteria. 0.08% GA regulated carbohydrate metabolism in fece.
Gallic acid (GA) is a natural polyphenolic compound with many health benefits. To assess the potential risk of long-term consumption of GA to gut health, healthy dogs were fed a basal diet supplemented with GA (0%, 0.02%, 0.04%, and 0.08%) for 45 d, and fecal microbiota and metabolomics were evaluated. This study demonstrated that GA supplementation regulated serum lipid metabolism by reducing serum triglyceride, fat digestibility, and Bacteroidetes/Firmicutes ratio. In addition, the relative abundance of Parasutterella was significantly lower, and the SCFAs-producing bacteria were increased along with fecal acetate and total SCFAs contents accumulation in the 0.08% GA group. Metabolomics data further elucidated that 0.08% GA significantly affected carbohydrate metabolism by downregulating succinic acid in fece, thereby alleviating inflammation and oxidative stress. Overall, this study confirmed the beneficial effects of long-term consumption of GA on lipid metabolism and gut health, and the optimal level of GA supplementation was 0.08%.
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Ren W, Yu B, Yu J, Zheng P, Huang Z, Luo J, Mao X, He J, Yan H, Wu J, Chen D, Luo Y. Lower abundance of Bacteroides and metabolic dysfunction are highly associated with the post-weaning diarrhea in piglets. SCIENCE CHINA. LIFE SCIENCES 2022; 65:2062-2075. [PMID: 35467318 DOI: 10.1007/s11427-021-2068-6] [Citation(s) in RCA: 22] [Impact Index Per Article: 11.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Track Full Text] [Subscribe] [Scholar Register] [Received: 12/30/2021] [Accepted: 01/12/2022] [Indexed: 06/14/2023]
Abstract
Growing evidences show a direct link between diarrhea and disorders of gut microbiota in pigs. However, whether there are microbial markers associated with post-weaning diarrhea remains unknown. In the current study, we compared the microbial community, functions and metabolites between healthy weaned piglets (group H, n=7) and piglets with post-weaning diarrhea (group D, n=7), in order to find out diarrhea associated microbial markers. Each of 7 fecal samples was collected from H and D piglets (weaned at 21 d and sampled at 26 d). The metagenomic and untargeted metabolomic analysis revealed that the microbial composition, function and metabolic profile in D pigs was considerably reshaped, including the reduced abundance and number of Bacteroides, which significantly correlated with the diarrhea status of host. The carbohydrate metabolism, biosynthesis and metabolism, lipid metabolism, amino acid metabolism, and the activity of glycan and carbohydrates digestion related enzymes showed extensively down-regulated in D pigs compared with H pigs. Diarrhea significantly changed the metabolic profiles of fecal microbiota, and most of the altered metabolites were negatively or positively correlated with the change in the abundance of Bacteroides. In conclusion, the lower abundance of Bacteroides and its associated metabolic dysfunction may be regarded as microbial markers of physiological post-weaning diarrhea in piglets.
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Affiliation(s)
- Wen Ren
- Key Laboratory for Animal Disease-Resistance Nutrition of Ministry of Education of China, Key Laboratory for Animal Disease-Resistance Nutrition and Feed of Ministry of Agriculture of China, Key Laboratory of Animal Disease-resistant Nutrition of Sichuan Province, and Animal Nutrition Institute, Sichuan Agricultural University, Chengdu, 611130, China
- DSM (China) Animal Nutrition Research Center Co., Ltd, Bazhou, 065799, China
| | - Bing Yu
- Key Laboratory for Animal Disease-Resistance Nutrition of Ministry of Education of China, Key Laboratory for Animal Disease-Resistance Nutrition and Feed of Ministry of Agriculture of China, Key Laboratory of Animal Disease-resistant Nutrition of Sichuan Province, and Animal Nutrition Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Jie Yu
- Key Laboratory for Animal Disease-Resistance Nutrition of Ministry of Education of China, Key Laboratory for Animal Disease-Resistance Nutrition and Feed of Ministry of Agriculture of China, Key Laboratory of Animal Disease-resistant Nutrition of Sichuan Province, and Animal Nutrition Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Ping Zheng
- Key Laboratory for Animal Disease-Resistance Nutrition of Ministry of Education of China, Key Laboratory for Animal Disease-Resistance Nutrition and Feed of Ministry of Agriculture of China, Key Laboratory of Animal Disease-resistant Nutrition of Sichuan Province, and Animal Nutrition Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Zhiqing Huang
- Key Laboratory for Animal Disease-Resistance Nutrition of Ministry of Education of China, Key Laboratory for Animal Disease-Resistance Nutrition and Feed of Ministry of Agriculture of China, Key Laboratory of Animal Disease-resistant Nutrition of Sichuan Province, and Animal Nutrition Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Junqiu Luo
- Key Laboratory for Animal Disease-Resistance Nutrition of Ministry of Education of China, Key Laboratory for Animal Disease-Resistance Nutrition and Feed of Ministry of Agriculture of China, Key Laboratory of Animal Disease-resistant Nutrition of Sichuan Province, and Animal Nutrition Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Xiangbing Mao
- Key Laboratory for Animal Disease-Resistance Nutrition of Ministry of Education of China, Key Laboratory for Animal Disease-Resistance Nutrition and Feed of Ministry of Agriculture of China, Key Laboratory of Animal Disease-resistant Nutrition of Sichuan Province, and Animal Nutrition Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Jun He
- Key Laboratory for Animal Disease-Resistance Nutrition of Ministry of Education of China, Key Laboratory for Animal Disease-Resistance Nutrition and Feed of Ministry of Agriculture of China, Key Laboratory of Animal Disease-resistant Nutrition of Sichuan Province, and Animal Nutrition Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Hui Yan
- Key Laboratory for Animal Disease-Resistance Nutrition of Ministry of Education of China, Key Laboratory for Animal Disease-Resistance Nutrition and Feed of Ministry of Agriculture of China, Key Laboratory of Animal Disease-resistant Nutrition of Sichuan Province, and Animal Nutrition Institute, Sichuan Agricultural University, Chengdu, 611130, China
| | - Jinlong Wu
- DSM (China) Animal Nutrition Research Center Co., Ltd, Bazhou, 065799, China
| | - Daiwen Chen
- Key Laboratory for Animal Disease-Resistance Nutrition of Ministry of Education of China, Key Laboratory for Animal Disease-Resistance Nutrition and Feed of Ministry of Agriculture of China, Key Laboratory of Animal Disease-resistant Nutrition of Sichuan Province, and Animal Nutrition Institute, Sichuan Agricultural University, Chengdu, 611130, China.
| | - Yuheng Luo
- Key Laboratory for Animal Disease-Resistance Nutrition of Ministry of Education of China, Key Laboratory for Animal Disease-Resistance Nutrition and Feed of Ministry of Agriculture of China, Key Laboratory of Animal Disease-resistant Nutrition of Sichuan Province, and Animal Nutrition Institute, Sichuan Agricultural University, Chengdu, 611130, China.
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Bai J, Wan Z, Zhang Y, Wang T, Xue Y, Peng Q. Composition and diversity of gut microbiota in diabetic retinopathy. Front Microbiol 2022; 13:926926. [PMID: 36081798 PMCID: PMC9445585 DOI: 10.3389/fmicb.2022.926926] [Citation(s) in RCA: 14] [Impact Index Per Article: 7.0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/23/2022] [Accepted: 08/05/2022] [Indexed: 11/13/2022] Open
Abstract
ObjectiveDiabetic retinopathy (DR) is one of the most common complications of type 2 diabetes mellitus. The current study investigates the composition, structure, and function of gut microbiota in DR patients and explores the correlation between gut microbiota and clinical characteristics of DR.MethodsA total of 50 stool samples were collected from 50 participants, including 25 DR patients and 25 healthy controls (HCs). 16S ribosomal RNA gene sequencing was used to analyze the gut microbial composition in these two groups. DNA was extracted from the fecal samples using the MiSeq platform.ResultsThe microbial structure and composition of DR patients were different from that of HCs. The microbial richness of gut microbiota in DR was higher than that of normal individuals. The alterations of microbiome of DR patients were associated with disrupted Firmicutes, Bacteroidetes, Synergistota, and Desulfobacterota phyla. In addition, increased levels of Bacteroides, Megamonas, Ruminococcus_torques_group, Lachnoclostridium, and Alistipes, and decreased levels of Blautia, Eubacterium_ hallii_group, Collinsella, Dorea, Romboutsia, Anaerostipes, and Fusicatenibacter genera were observed in the DR groups. Additionally, a stochastic forest model was developed to identify a set of biomarkers with seven bacterial genera that can differentiate patients with DR from those HC. The microbial communities exhibited varied functions in these two groups because of the alterations of the above-mentioned bacterial genera.ConclusionThe altered composition and function of gut microbiota in DR patients indicated that gut microbiome could be used as non-invasive biomarkers, improve clinical diagnostic methods, and identify putative therapeutic targets for DR.
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Yang K, Jian S, Wen C, Guo D, Liao P, Wen J, Kuang T, Han S, Liu Q, Deng B. Gallnut Tannic Acid Exerts Anti-stress Effects on Stress-Induced Inflammatory Response, Dysbiotic Gut Microbiota, and Alterations of Serum Metabolic Profile in Beagle Dogs. Front Nutr 2022; 9:847966. [PMID: 35571952 PMCID: PMC9094144 DOI: 10.3389/fnut.2022.847966] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.5] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/03/2022] [Accepted: 03/07/2022] [Indexed: 01/16/2023] Open
Abstract
Stress exposure is a potential threat to humans who live or work in extreme environments, often leading to oxidative stress, inflammatory response, intestinal dysbiosis, and metabolic disorders. Gallnut tannic acid (TA), a naturally occurring polyphenolic compound, has become a compelling source due to its favorable anti-diarrheal, anti-oxidative, anti-inflammatory, and anti-microbial activities. Thus, this study aimed to evaluate the anti-stress effects of gallnut TA on the stress-induced inflammatory response, dysbiotic gut microbiota, and alterations of serum metabolic profile using beagle models. A total of 13 beagle dogs were randomly divided into the stress (ST) and ST + TA groups. Dietary supplementation with TA at 2.5 g/kg was individually fed to each dog in the ST + TA group for 14 consecutive days. On day 7, all dogs were transported for 3 h from a stressful environment (days 1–7) to a livable site (days 8–14). In our results, TA relieved environmental stress-induced diarrheal symptoms in dogs and were shown to protect from myocardial injury and help improve immunity by serum biochemistry and hematology analysis. Also, TA inhibited the secretion of serum hormones [cortisol (COR), glucocorticoid (GC), and adrenocorticotropic hormone (ACTH)] and the expression of heat shock protein (HSP) 70 to protect dogs from stress-induced injury, thereby relieving oxidative stress and inflammatory response. Fecal 16S rRNA gene sequencing revealed that TA stimulated the growth of beneficial bacteria (Allobaculum, Dubosiella, Coriobacteriaceae_UCG-002, and Faecalibaculum) and suppressed the growth of pathogenic bacteria (Escherichia-Shigella and Streptococcus), thereby increasing fecal butyrate levels. Serum metabolomics further showed that phytosphingosine, indoleacetic acid, arachidonic acid, and biotin, related to the metabolism of sphingolipid, tryptophan, arachidonic acid, and biotin, respectively, could serve as potential biomarkers of stress exposure. Furthermore, Spearman’s correlation analysis showed strong relationships between the four potential serum biomarkers and differential bacteria. Overall, gallnut TA may be a potential prebiotic for the prevention and treatment of stress-induced metabolic disorders by targeting intestinal microbiota.
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Affiliation(s)
- Kang Yang
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Shiyan Jian
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Chaoyu Wen
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Dan Guo
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Pinfeng Liao
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Jiawei Wen
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Tao Kuang
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Sufang Han
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Qingshen Liu
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Baichuan Deng
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, China
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11
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Lisitsyna A, Moritz F, Liu Y, Al Sadat L, Hauner H, Claussnitzer M, Schmitt-Kopplin P, Forcisi S. Feature Selection Pipelines with Classification for Non-targeted Metabolomics Combining the Neural Network and Genetic Algorithm. Anal Chem 2022; 94:5474-5482. [PMID: 35344349 DOI: 10.1021/acs.analchem.1c03237] [Citation(s) in RCA: 0] [Impact Index Per Article: 0] [Reference Citation Analysis] [Abstract] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Indexed: 11/29/2022]
Abstract
Non-targeted metabolomics via high-resolution mass spectrometry methods, such as direct infusion Fourier transform-ion cyclotron resonance mass spectrometry (DI-FT-ICR MS), produces data sets with thousands of features. By contrast, the number of samples is in general substantially lower. This disparity presents challenges when analyzing non-targeted metabolomics data sets and often requires custom methods to uncover information not always accessible via classical statistical techniques. In this work, we present a pipeline that combines a convolutional neural network with traditional statistical approaches and an adaptation of a genetic algorithm. The developed method was applied to a lifestyle intervention cohort data set, where subjects at risk of type 2 diabetes underwent an oral glucose tolerance test. Feature selection is the final result of the pipeline, achieved through classification of the data set via a neural network, with a precision-recall score of over 0.9 on the test set. The features most relevant for the described classification were then chosen via a genetic algorithm. The output of the developed pipeline encompasses approximately 200 features with high predictive scores, providing a fingerprint of the metabolic changes in the prediabetic class on the data set. Our framework presents a new approach which allows to apply complex modeling based on convolutional neural networks for the analysis of high-resolution mass spectrometric data.
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Affiliation(s)
- Anna Lisitsyna
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Neuherberg 85764, Germany.,German Center for Diabetes Research (DZD), Neuherberg 85764, Germany
| | - Franco Moritz
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Neuherberg 85764, Germany
| | - Youzhong Liu
- Analytical Development, Small Molecule Development, Janssen Pharmaceutical Companies of Johnson and Johnson, Beerse 2340, Belgium
| | - Loubna Al Sadat
- Institute for Nutritional Medicine, School of Medicine, Technical University of Munich, Munich 80686, Germany
| | - Hans Hauner
- Institute for Nutritional Medicine, School of Medicine, Technical University of Munich, Munich 80686, Germany.,Else Kröner-Fresenius-Centre for Nutritional Medicine, School of Life Sciences, Technical University of Munich, Freising 85354, Germany
| | - Melina Claussnitzer
- Broad Institute of MIT and Harvard, Cambridge 02141-2023 Massachusetts, United States.,Division of Gerontology, Department of Medicine, Beth Israel Deaconess Medical Center, Boston, Massachusetts 02108, United States.,Harvard Medical School, Harvard University, Boston, Massachusetts 02108, United States
| | - Philippe Schmitt-Kopplin
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Neuherberg 85764, Germany.,Chair of Analytical Food Chemistry, TUM School of Life Sciences, Technical University Munich, Munich 80686, Germany
| | - Sara Forcisi
- Research Unit Analytical BioGeoChemistry, Helmholtz Zentrum München, Neuherberg 85764, Germany.,German Center for Diabetes Research (DZD), Neuherberg 85764, Germany
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12
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Yang K, Deng X, Jian S, Zhang M, Wen C, Xin Z, Zhang L, Tong A, Ye S, Liao P, Xiao Z, He S, Zhang F, Deng J, Zhang L, Deng B. Gallic Acid Alleviates Gut Dysfunction and Boosts Immune and Antioxidant Activities in Puppies Under Environmental Stress Based on Microbiome-Metabolomics Analysis. Front Immunol 2022; 12:813890. [PMID: 35095912 PMCID: PMC8795593 DOI: 10.3389/fimmu.2021.813890] [Citation(s) in RCA: 20] [Impact Index Per Article: 10.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 11/12/2021] [Accepted: 12/21/2021] [Indexed: 12/12/2022] Open
Abstract
Early-life exposure to environmental stress disrupts the gut barrier and leads to inflammatory responses and changes in gut microbiota composition. Gallic acid (GA), a natural plant polyphenol, has received significant interest for its antioxidant, anti-inflammatory, and antimicrobial properties that support the maintenance of intestinal health. To assess whether dietary supplementation of GA alleviates environmental stress, a total of 19 puppies were randomly allocated to the following three dietary treatments for 2 weeks: 1) basal diet (control (CON)); 2) basal diet + transportation (TS); and 3) basal diet with the addition of 500 mg/kg of GA + transportation (TS+GA). After a 1-week supplementation period, puppies in the TS and TS+GA groups were transported from a stressful environment to another livable location, and puppies in the CON group were then left in the stressful environment. Results indicated that GA markedly reduced the diarrhea rate in puppies throughout the trial period and caused a moderate decline of serum cortisol and HSP-70 levels after transportation. Also, GA alleviated the oxidative stress and inflammatory response caused by multiple environmental stressors. Meanwhile, puppies fed GA had a higher abundance of fecal Firmicutes and Lactobacillus and lower Proteobacteria, Escherichia–Shigella, and Clostridium_sensu_stricto_1 after transportation. As a result, the TS+GA group had the highest total short-chain fatty acids and acetic acid. Also, the fecal and serum metabolomics analyses revealed that GA markedly reversed the abnormalities of amino acid metabolism, lipid metabolism, carbohydrate metabolism, and nucleotide metabolism caused by stresses. Finally, Spearman’s correlation analysis was carried out to explore the comprehensive microbiota and metabolite relationships. Overall, dietary supplementation of GA alleviates oxidative stress and inflammatory response in stressed puppies by causing beneficial shifts on gut microbiota and metabolites that may support gut and host health.
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Affiliation(s)
- Kang Yang
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Xiaolin Deng
- Department of Urology, Ganzhou People's Hospital, Ganzhou, China
| | - Shiyan Jian
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Meiyu Zhang
- College of Animal Science and Technology, Guangdong Polytechnic of Science and Trade, Guangzhou, China
| | - Chaoyu Wen
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Zhongquan Xin
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Limeng Zhang
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Aorigeile Tong
- Research Center of Pet Nutrition, Guangzhou Qingke Biotechnology Co., Ltd., Guangzhou, China
| | - Shibin Ye
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Pinfeng Liao
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Zaili Xiao
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Shansong He
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Fan Zhang
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Jinping Deng
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Lingna Zhang
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, China
| | - Baichuan Deng
- Guangdong Laboratory for Lingnan Modern Agriculture, Guangdong Provincial Key Laboratory of Animal Nutrition Control, National Engineering Research Center for Breeding Swine Industry, College of Animal Science, South China Agricultural University, Guangzhou, China
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13
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Du Y, Li DX, Lu DY, Zhang R, Zheng XX, Xu BJ, Zhao YL, Ji S, Guo MZ, Wang L, Tang DQ. Morus alba L. water extract changes gut microbiota and fecal metabolome in mice induced by high-fat and high-sucrose diet plus low-dose streptozotocin. Phytother Res 2022; 36:1241-1257. [PMID: 35129235 DOI: 10.1002/ptr.7343] [Citation(s) in RCA: 16] [Impact Index Per Article: 8.0] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Journal Information] [Subscribe] [Scholar Register] [Received: 08/13/2021] [Revised: 10/22/2021] [Accepted: 11/10/2021] [Indexed: 12/12/2022]
Abstract
Gut microbiota plays a key role in the pathophysiology of type 2 diabetes mellitus (T2D). Mulberry leaf has a hypoglycemic effect, but the potential mechanism is not fully understood. This study aimed to explore the influences and potential mechanisms of mulberry leaf water extract (MLWE) intervention on mice with T2D induced through a high-fat and high-sucrose diet combined with streptozotocin by the combination of fecal metabolomics and gut microbiota analysis. Results showed that MLWE could decrease fasting blood glucose and body weight while ameliorating lipid profiles, insulin resistance, liver inflammation, and the accumulation of lipid droplets in T2D mice. MLWE could reverse the abundances of the phyla Actinobacteria and Bacteroidetes and the ratio of Firmicutes/Bacteroidetes, and increase the abundances of the phyla Cyanobacteria and Epsilonbacteraeota in the feces of T2D mice. The abundances of genera Alloprevotella, Parabacteroides, Muribaculaceae, and Romboutsia in the feces of T2D mice could be reversed, while Oscillatoriales_cyanobacterium and Gastranaerophilales could be reinforced by MLWE supplementation. The levels of nine metabolites in the feces of T2D mice were improved, among which glycine, Phe-Pro, urocanic acid, phylloquinone, and lactate were correlated with Romboutsia and Gastranaerophilales. Taken together, we conclude that MLWE can effectively alleviate T2D by mediating the host-microbial metabolic axis.
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Affiliation(s)
- Yan Du
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China
| | - Ding-Xiang Li
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China
| | - Dong-Yu Lu
- Department of Pharmacy, Suining People's Hospital Affiliated to Xuzhou Medical University, Suining, China
| | - Ran Zhang
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China
| | - Xiao-Xiao Zheng
- Department of Pharmacy, Xuzhou Municipal Hospital Affiliated to Xuzhou Medical University, Xuzhou, China
| | - Bing-Ju Xu
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China
| | - Yan-Lin Zhao
- Department of Pharmacy, Suining People's Hospital Affiliated to Xuzhou Medical University, Suining, China
| | - Shuai Ji
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China.,Department of Pharmaceutical Analysis, Xuzhou Medical University, Xuzhou, China
| | - Meng-Zhe Guo
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China.,Department of Pharmaceutical Analysis, Xuzhou Medical University, Xuzhou, China
| | - Liang Wang
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China.,Department of Bioinformatics, School of Medical Informatics and Engineering, Xuzhou Medical University, Xuzhou, China
| | - Dao-Quan Tang
- Jiangsu Key Laboratory of New Drug Research and Clinical Pharmacy, Xuzhou Medical University, Xuzhou, China.,Department of Pharmacy, Suining People's Hospital Affiliated to Xuzhou Medical University, Suining, China.,Department of Pharmaceutical Analysis, Xuzhou Medical University, Xuzhou, China
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14
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Abstract
PURPOSE OF REVIEW Patients with diabetes mellitus (DM) are at increased risk of developing osteopathogenesis and skeletal fragility. The role of the gut microbiota in both DM and osteopathy is not fully explored and may be involved in the pathology of both diseases. RECENT FINDINGS Gut microbiota alterations have been observed in DM and osteopathogenic disorders as compared with healthy controls, such as significantly lower abundance of Prevotella and higher abundance of Lactobacillus, with a diminished bacterial diversity. Other overlapping gastro-intestinal features include the loss of intestinal barrier function with translocation of bacterial metabolites to the blood stream, induction of immunological deficits and changes in hormonal and endocrinal signalling, which may lead to the development of diabetic osteopathy. Signalling pathways involved in both DM and osteopathy are affected by gut bacteria and their metabolites. Future studies should focus on gut microbiota involvement in both diseases.
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Affiliation(s)
- Julie Kristine Knudsen
- Centre for Clinical Research, North Denmark Regional Hospital, Bispensgade 37, 9800, Hjørring, Denmark.
- Department of Clinical Medicine, Aalborg University, Søndre Skovvej 15, Aalborg, Denmark.
| | - Peter Leutscher
- Centre for Clinical Research, North Denmark Regional Hospital, Bispensgade 37, 9800, Hjørring, Denmark
- Department of Clinical Medicine, Aalborg University, Søndre Skovvej 15, Aalborg, Denmark
- Steno Diabetes Center North Jutland, Mølleparkvej 4, Aalborg, Denmark
| | - Suzette Sørensen
- Centre for Clinical Research, North Denmark Regional Hospital, Bispensgade 37, 9800, Hjørring, Denmark
- Department of Clinical Medicine, Aalborg University, Søndre Skovvej 15, Aalborg, Denmark
- Steno Diabetes Center North Jutland, Mølleparkvej 4, Aalborg, Denmark
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15
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Jiang H, Lou P, Chen X, Wu C, Shao S. Deregulation of lncRNA HIST1H2AG-6 and AIM1-3 in peripheral blood mononuclear cells is associated with newly diagnosed type 2 diabetes. BMC Med Genomics 2021; 14:149. [PMID: 34092238 PMCID: PMC8182924 DOI: 10.1186/s12920-021-00994-z] [Citation(s) in RCA: 1] [Impact Index Per Article: 0.3] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 04/29/2020] [Accepted: 05/31/2021] [Indexed: 12/11/2022] Open
Abstract
BACKGROUND Type 2 diabetes mellitus (T2DM) is mainly affected by genetic and environmental factors; however, the correlation of long noncoding RNAs (lncRNAs) with T2DM remains largely unknown. METHODS Microarray analysis was performed to identify the differentially expressed lncRNAs and messenger RNAs (mRNAs) in patients with T2DM and healthy controls, and the expression of two candidate lncRNAs (lnc-HIST1H2AG-6 and lnc-AIM1-3) were further validated using quantitative real-time polymerase chain reaction (qRT-PCR). Spearman's rank correlation coefficient was used to measure the degree of association between the two candidate lncRNAs and differentially expressed mRNAs. Furthermore, the KEGG (Kyoto Encyclopedia of Genes and Genomes) pathway and GO (Gene Ontology) enrichment analysis were used to reveal the biological functions of the two candidate lncRNAs. Additionally, multivariate logistic regression analysis and receiver operating characteristic (ROC) curve analysis were performed. RESULTS The microarray analysis revealed that there were 55 lncRNAs and 36 mRNAs differentially expressed in patients with T2DM compared with healthy controls. Notably, lnc-HIST1H2AG-6 was significantly upregulated and lnc-AIM1-3 was significantly downregulated in patients with T2DM, which was validated in a large-scale qRT-PCR examination (90 controls and 100 patients with T2DM). Spearman's rank correlation coefficient revealed that both lncRNAs were correlated with 36 differentially expressed mRNAs. Furthermore, functional enrichment (KEGG and GO) analysis demonstrated that the two lncRNA-related mRNAs might be involved in multiple biological functions, including cell programmed death, negative regulation of insulin receptor signal, and starch and sucrose metabolism. Multivariate logistic regression analysis revealed that lnc-HIST1H2AG-6 and lnc-AIM1-3 were significantly correlated with T2DM (OR = 5.791 and 0.071, respectively, both P = 0.000). Furthermore, the ROC curve showed that the expression of lnc-HIST1H2AG-6 and lnc-AIM1-3 might be used to differentiate patients with T2DM from healthy controls (area under the ROC curve = 0.664 and 0.769, respectively). CONCLUSION The profiles of lncRNA and mRNA were significantly changed in patients with T2DM. The expression levels of lnc-HIST1H2AG-6 and lnc-AIM1-3 genes were significantly correlated with some features of T2DM, which may be used to distinguish patients with T2DM from healthy controls and may serve as potential novel biomarkers for diagnosis in the future.
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Affiliation(s)
- Hui Jiang
- Department of Endocrinology, Affiliated People's Hospital of Jiangsu University, Zhenjiang, 212002, China
| | - Peian Lou
- Xuzhou Center for Disease Control Prevention, Xuzhou, 221000, China
| | - Xiaoluo Chen
- Department of Endocrinology, Affiliated People's Hospital of Jiangsu University, Zhenjiang, 212002, China
| | - Chenguang Wu
- Department of Endocrinology, Affiliated People's Hospital of Jiangsu University, Zhenjiang, 212002, China
| | - Shihe Shao
- School of Medicine, Jiangsu University, 301 Xuefu Road, Zhenjiang, 212013, Jiangsu Province, China.
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16
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Huang Y, Wang Z, Ma H, Ji S, Chen Z, Cui Z, Chen J, Tang S. Dysbiosis and Implication of the Gut Microbiota in Diabetic Retinopathy. Front Cell Infect Microbiol 2021; 11:646348. [PMID: 33816351 PMCID: PMC8017229 DOI: 10.3389/fcimb.2021.646348] [Citation(s) in RCA: 58] [Impact Index Per Article: 19.3] [Reference Citation Analysis] [Abstract] [Key Words] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 01/07/2021] [Accepted: 03/02/2021] [Indexed: 12/16/2022] Open
Abstract
The pathogenesis of type 2 diabetes mellitus (T2DM) is commonly associated with altered gut bacteria. However, whether the microbial dysbiosis that exists in human diabetic patients with or without retinopathy is different remains largely unknown. Here, we collected clinical information and fecal samples from 75 participants, including 25 diabetic patients without retinopathy (DM), 25 diabetic patients with retinopathy (DR), and 25 healthy controls (HC). The gut microbial composition in the three groups was analyzed using 16S ribosomal RNA (rRNA) gene sequencing. Microbial structure and composition differed in the three groups. The α and β diversities in both the DM and DR groups were reduced compared with those in the HC group. Blautia was the most abundant genus, especially in the DM group. In addition, increased levels of Bifidobacterium and Lactobacillus and decreased levels of Escherichia-Shigella, Faecalibacterium, Eubacterium_hallii_group and Clostridium genera were observed in the DM and DR groups compared with the HC group. Furthermore, a biomarker set of 25 bacterial families, which could distinguish patients in the DR group from those in the DM and HC groups was identified, with the area under the curve values ranging from 0.69 to 0.85. Of note, Pasteurellaceae, which was increased in DM and decreased in DR compared with HC, generated a high AUC (0.74) as an individual predictive biomarker. Moreover, 14 family biomarkers were associated with fasting blood glucose levels or diabetes, with most of them being negatively correlated. In summary, our study establishes compositional alterations of gut microbiota in DM and DR, suggesting the potential use of gut microbiota as a non-invasive biomarker for clinical and differential diagnosis, as well as identifying potential therapeutic targets of diabetic retinopathy.
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Affiliation(s)
- Yinhua Huang
- Aier School of Ophthalmology, Central South University, Changsha, China.,Aier Eye Institute, Changsha, China
| | - Zhijie Wang
- Aier School of Ophthalmology, Central South University, Changsha, China.,Aier Eye Institute, Changsha, China
| | | | | | | | | | - Jiansu Chen
- Aier School of Ophthalmology, Central South University, Changsha, China.,Aier Eye Institute, Changsha, China.,Key Laboratory for Regenerative Medicine, Ministry of Education, Jinan University, Guangzhou, China.,Institute of Ophthalmology, Medical College, Jinan University, Guangzhou, China
| | - Shibo Tang
- Aier School of Ophthalmology, Central South University, Changsha, China.,Aier Eye Institute, Changsha, China.,CAS Center for Excellence in Brain Science and Intelligence Technology, Chinese Academy of Sciences, Shanghai, China
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17
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Gradisteanu Pircalabioru G, Corcionivoschi N, Gundogdu O, Chifiriuc MC, Marutescu LG, Ispas B, Savu O. Dysbiosis in the Development of Type I Diabetes and Associated Complications: From Mechanisms to Targeted Gut Microbes Manipulation Therapies. Int J Mol Sci 2021; 22:2763. [PMID: 33803255 PMCID: PMC7967220 DOI: 10.3390/ijms22052763] [Citation(s) in RCA: 6] [Impact Index Per Article: 2.0] [Reference Citation Analysis] [Abstract] [Key Words] [MESH Headings] [Grants] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 02/10/2021] [Revised: 03/06/2021] [Accepted: 03/08/2021] [Indexed: 12/12/2022] Open
Abstract
Globally, we are facing a worrying increase in type 1 diabetes mellitus (T1DM) incidence, with onset at younger age shedding light on the need to better understand the mechanisms of disease and step-up prevention. Given its implication in immune system development and regulation of metabolism, there is no surprise that the gut microbiota is a possible culprit behind T1DM pathogenesis. Additionally, microbiota manipulation by probiotics, prebiotics, dietary factors and microbiota transplantation can all modulate early host-microbiota interactions by enabling beneficial microbes with protective potential for individuals with T1DM or at high risk of developing T1DM. In this review, we discuss the challenges and perspectives of translating microbiome data into clinical practice. Nevertheless, this progress will only be possible if we focus our interest on developing numerous longitudinal, multicenter, interventional and double-blind randomized clinical trials to confirm their efficacy and safety of these therapeutic approaches.
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Affiliation(s)
| | - Nicolae Corcionivoschi
- Bacteriology Branch, Veterinary Sciences Division, Agri-Food and Biosciences Institute, Belfast BT9 5PX, UK;
| | - Ozan Gundogdu
- Faculty of Infectious & Tropical Diseases, London School of Hygiene and Tropical Medicine, Keppel Street, London WC1E 7HT, UK;
| | - Mariana-Carmen Chifiriuc
- Research Institute of University of Bucharest (ICUB), 300645 Bucharest, Romania; (G.G.P.); (L.G.M.); (B.I.)
- Academy of Romanian Scientists, 050045 Bucharest, Romania
| | | | - Bogdan Ispas
- Research Institute of University of Bucharest (ICUB), 300645 Bucharest, Romania; (G.G.P.); (L.G.M.); (B.I.)
| | - Octavian Savu
- “N.C. Paulescu” National Institute of Diabetes, Nutrition and Metabolic Diseases, 2nd District, 020042 Bucharest, Romania;
- Department of Doctoral School, “Carol Davila” University of Medicine and Pharmacy, 5th District, 050474 Bucharest, Romania
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18
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Abstract
Aging is characterized by the functional decline of tissues and organs and increased risk of aging-associated disorders, which pose major societal challenges and are a public health priority. Despite extensive human genetics studies, limited progress has been made linking genetics with aging. There is a growing realization that the altered assembly, structure and dynamics of the gut microbiota actively participate in the aging process. Age-related microbial dysbiosis is involved in reshaping immune responses during aging, which manifest as immunosenescence (insufficiency) and inflammaging (over-reaction) that accompany many age-associated enteric and extraenteric diseases. The gut microbiota can be regulated, suggesting a potential target for aging interventions. This review summarizes recent findings on the physiological succession of gut microbiota across the life-cycle, the roles and mechanisms of gut microbiota in healthy aging, alterations of gut microbiota and aging-associated diseases, and the gut microbiota-targeted anti-aging strategies.
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Affiliation(s)
- Zongxin Ling
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Xia Liu
- Department of Intensive Care Unit, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Yiwen Cheng
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
| | - Xiumei Yan
- Department of Geriatrics, Lishui Second People's Hospital, Lishui, Zhejiang, China
| | - Shaochang Wu
- Collaborative Innovation Center for Diagnosis and Treatment of Infectious Diseases, State Key Laboratory for Diagnosis and Treatment of Infectious Diseases, National Clinical Research Center for Infectious Diseases, the First Affiliated Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China
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