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Changes in Intestinal Microbiota of Type 2 Diabetes in Mice in Response to Dietary Supplementation With Instant Tea or Matcha

      Abstract

      Objective

      Gut microbiota plays a key role in metabolism and health in diabetes patients with gastrointestinal microbiota dysbiosis. Thus, regulating the ecological balance of gut microbiota may provide a pathway toward improvement for these patients. Our previous study showed that functional ingredients in tea may inhibit cornstarch digestion in vitro.

      Methods

      A cornstarch–tea diet was developed, and in this study we investigated the effects of such a diet on blood glucose and gut microbiota in diabetic mice.

      Results

      Diabetes resulted in significant weight loss, hyperphagia and hyperglycemia. 16S rDNA sequencing revealed that in diabetes there is significantly increased Bacteroidaceae, Helicobacteraceae, Ruminococcaceae, Enterobacteriaceae, Rikenellaceae and Saccharibacteria_genera_incertae_sedis, and significantly decreased Lactobacillaceae, Prevotellaceae, Coriobacteriaceae, Verrucomicrobiaceae and Bifidobacteriaceae. The cornstarch‒tea diet resulted in a trend toward reduced blood glucose, with particularly increased levels of Coriobacteriaceae, Lactobacillaceae, Prevotellaceae and Bifidobacteriaceae, and decreased Bacteroidaceae, Ruminococcaceae, Helicobacteraceae and Enterobacteriaceae.

      Conclusions

      Instant tea and matcha supplementation had beneficial effects on regulation of blood glucose and gut microbiota, reversing the changes in microbiota caused by alloxan injection. The cornstarch‒tea regulation pathway is involved in bacterium group regulation rather than single-species regulation, which suggests that cornstarch combined with tea may be used as a functional food supplement for diabetes patients.

      Résumé

      Objectif

      Le microbiote intestinal joue un rôle déterminant dans le métabolisme et la santé des patients diabétiques ayant une dysbiose (déséquilibre du microbiote gastro-intestinal). Par conséquent, le maintien de l'équilibre écologique du microbiote intestinal de ces patients peut ouvrir une voie vers l'amélioration. La présente étude nous montre que les ingrédients fonctionnels du thé peuvent inhiber la digestion de l'amidon de maïs in vitro.

      Méthodes

      Nous avons élaboré un régime à base d'un thé contenant de l'amidon de maïs et, dans cette étude, nous avons examiné les effets de ce régime sur la glycémie et le microbiote intestinal de souris diabétiques.

      Résultats

      Le diabète a entraîné une perte de poids importante, une hyperphagie et une hyperglycémie. Le séquençage du gène ARNr 16S a révélé qu'en présence de diabète les Bacteroidaceae, les Helicobacteraceae, les Ruminococcaceae, les Enterobacteriaceae, les Rikenellaceae et les Saccharibacteria_genera_incertae_sedis augmentaient de manière significative, et que les Lactobacillaceae, les Prevotellaceae, les Coriobacteriaceae, les Verrucomicrobiaceae et les Bifidobacteriaceae diminuaient de manière significative. Le régime à base de thé contenant de l'amidon de maïs avait tendance à réduire la glycémie, et notamment d'augmenter le nombre de Coriobacteriaceae, de Lactobacillaceae, de Prevotellaceae et de Bifidobacteriaceae, et de diminuer le nombre de Bacteroidaceae, de Ruminococcaceae, de Helicobacteraceae et d'Enterobacteriaceae.

      Conclusions

      La supplémentation en thé soluble et en matcha a eu des effets bénéfiques sur la régulation de la glycémie et du microbiote intestinal, puis a annulé les changements causés par l'injection d'alloxane dans le microbiote. Puisque la voie de régulation du thé contenant de l'amidon de maïs est impliquée dans la régulation d'un groupe de bactéries plutôt que dans la régulation monospécifique, cela montre que les patients diabétiques peuvent utiliser un thé contenant de l'amidon de maïs comme supplément alimentaire fonctionnel.

      Keywords

      Mots clés

      • Diabetes resulted in significant weight loss, hyperphagia, hyperglycemia and microbiota dysbiosis of the intestinal tract.
      • Tea improved the growth performance, and reversed the changes in gut microbiota of diabetes compared to controls.
      • The tea regulation pathway is involved in bacterium group regulation rather than single-species regulation.

      Introduction

      Diabetes is a medical problem worldwide, with hyperglycemia leading to complications like cardiovascular disease and diabetic nephropathy (
      • Livesey G.
      • Taylor R.T.
      • Howlett J.
      Glycemic response and health—a systematic review and meta-analysis: Relations between dietary glycemic properties and health outcomes.
      ,
      • Manzano S.
      • Williamson G.
      Polyphenols and phenolic acids from strawberry and apple decrease glucose uptake and transport by human intestinal caco-2 cells.
      ). Diabetes is currently not curable, and its complications cause significant distress. Diet has a strong influence on health and is involved in the development of some diseases (
      • Blaut M.
      • Klaus S.
      Intestinal microbiota and obesity.
      ,
      • Dapito D.H.
      • Mencin A.
      • Gwak G.Y.
      • et al.
      Promotion of hepatocellular carcinoma by the intestinal microbiota and TLR4.
      ), including diabetes (
      • Abuelheiga L.
      • Oh W.
      • Kordari P.
      • Wakil S.J.
      Acetyl-CoA carboxylase 2 mutant mice are protected against obesity and diabetes induced by high-fat/high-carbohydrate diets.
      ,
      • Sandu O.
      • Song K.
      • Cai W.
      • Zheng F.
      • Uribarri J.
      • Vlassara H.
      Insulin resistance and type 2 diabetes in high-fat-fed mice are linked to high glycotoxin intake.
      ). In particular, digestion and absorption of carbohydrates leads directly to a rapid increase in blood glucose, and thus diabetes patients must strictly control their diet in addition to receiving drug therapy. In our previous study (
      • Zhang H.
      • Jiang Y.
      • Pan J.
      • et al.
      Effect of tea products on the in vitro enzymatic digestibility of starch.
      ), we found that cornstarch contains a high level of resistant starch (>50%), which is beneficial in diabetes. In addition, functional ingredients in tea, such as tea polyphenols and Epigallocatechin gallate (EGCG), were shown to greatly inhibit cornstarch digestion in vitro, suggesting cornstarch combined with tea's functional ingredients could be used as a basic formulation in the functional diet of diabetes patients (
      • Zhang H.
      • Jiang Y.
      • Pan J.
      • et al.
      Effect of tea products on the in vitro enzymatic digestibility of starch.
      ). It is well known that tea has a long history in China, and is consumed worldwide as a healthy beverage. The active ingredients in tea have many benefits, and EGCG can inhibit gluconeogenesis (
      • Nakai M.
      • Fukui Y.
      • Asami S.
      • et al.
      Inhibitory effects of oolong tea polyphenols on pancreatic lipase in vitro.
      ), inhibit lipid absorption (
      • Lin C.L.
      • Lin J.K.
      Epigallocatechin gallate (EGCG) attenuates high glucose-induced insulin signaling blockade in human hepG2 hepatoma cells.
      ) and reduce insulin resistance (
      • Mujico J.R.
      • Baccan G.C.
      • Gheorghe A.
      • Díaz L.E.
      • Marcos A.
      Changes in gut microbiota due to supplemented fatty acids in diet-induced obese mice.
      ), etc.
      Most importantly, the gastrointestinal tract is a place for digestion and absorption of one's diet, and it contains many complex microbes that play significant roles in digestion and metabolism with profound effects on nutrition and health of the host. Recent studies have suggested that diabetes patients have gastrointestinal microbiota dysbiosis (
      • Wu X.
      • Ma C.
      • Han L.
      • et al.
      Molecular characterisation of the faecal microbiota in patients with type ii diabetes.
      ,
      • He C.
      • Shan Y.
      • Song W.
      Targeting gut microbiota as a possible therapy for diabetes.
      ), which leads to dietary metabolic disturbance and worsened hyperglycemia. Thus, regulating the gastrointestinal microecology balance may serve as a pathway to improvement in diabetes patients. Interestingly, studies have shown that tea has beneficial effects on the intestinal microbiota by elevating good bacteria and reducing pathogenic bacteria, among other advantages (
      • Kelder T.
      • Stroeve J.H.
      • Bijlsma S.
      • Radonjic M.
      • Roeselers G.
      Correlation network analysis reveals relationships between diet-induced changes in human gut microbiota and metabolic health.
      ,
      • Thomas D.V.
      • Molan A.L.
      • Ravindran V.
      The ability of green tea to positively modify the gut microflora in broiler chickens.
      ,
      • Sabu M.C.
      • Smitha K.
      • Kuttan R.
      Anti-diabetic activity of green tea polyphenols and their role in reducing oxidative stress in experimental diabetes.
      ). Therefore, matcha and instant tea (2 common tea active ingredients) were selected and used to establish a cornstarch‒tea diet for diabetes patients. In this study, we investigated the effects of the cornstarch‒tea diet on body weight, food intake and blood glucose, and then assessed the regulation mechanism of cornstarch‒tea diet intervention on gut microbiota. To do this, we used a mouse model of diabetes, and aimed to present some basic information for intervening and preventing diabetes through regulation of gut microbiota.

      Methods

      Materials

      Cornstarch (CAS No. 9005-25-8) and dextrin (CAS No. 9005-65-6) were purchased from Qinhuangdao Lihua Starch (Qinghuangdao, China). Butter was provided by Fonterra Brands (Auckland, New Zealand). Cake flour was purchased from Shangdong Luzhong Kite Flour (Luzhong, China). Meringue powder was purchased from Guangdong Changxing Biotechnology (Changxing, China). Eggs were purchased from the Hangzhou Lianhua supermarket (Hangzhou, China). Potassium dihydrogen phosphate (CAS No. 7778-77-0) and calcium carbonate (CAS No. 471-34-1) were purchased from Lianyungang Youjin Food Additive Technology Development (Lianyungang, China).
      Matcha containing 14% tea polyphenols, 4.5% EGCG, 1.0% (-)-epicatechin gallate (ECG) and 2.3% caffeine and instant tea (from Chinese green tea), containing 22.7% tea polyphenols, 4.8% caffeine, 2.3% ECG and 8.4% EGCG, was made in our laboratory.

      Animals and ethics approval

      Female Kunming mice weighing 20±3 g were provided by the Experimental Animal Holding of Jilin University (Changchun, China). All mice were maintained under the same environmental conditions at the Zhejiang Academy of Medical Sciences, and housed in a temperature-controlled room at 24±1°C and 50±5% relative humidity on a 12-h light/dark cycle. The study was approved by the ethics committee of Zhejiang University (Hangzhou, China), and all experimental procedures were approved by the institutional animal care and use committee at Zhejiang University (
      • National Research Council (US)
      Committee for the Update of the Guide for the Care and Use of Laboratory Animals: Guide for the Care and Use of Laboratory Animals.
      ).

      Diabetes model and control and experimental diets

      The diabetes mouse model was established by intravenous injection of alloxan 45 mg/kg; control mice were given physiological saline. Mice with a fasting blood glucose of 10 to 25 mmol/L after 1 week were randomly assigned into 1 of 3 groups (n=8 or n=10): DM-C (tea-free cornstarch diet), DM-IT (cornstarch‒instant tea diet) or DM-M (a cornstarch‒matcha diet). Normal mice (n=10) given a tea-free cornstarch diet served as the control group (N-C).
      The cornstarch‒tea diet contained 20.59% cornstarch and 0.1% instant tea or matcha, and the tea-free cornstarch diet contained 20.69% cornstarch. The other diet ingredients included 25.33% butter, 8.66% dextrin, 20.69% cake flour, 16.68% meringue powder, 4.86% egg yolk, 1.82% potassium dihydrogen phosphate and 1.27% calcium carbonate. The experimental diet contained 22.1% fat, 40.94% carbohydrate and 20.93% protein, and had an energy content of 19.18 kJ/g. Nutrition levels of the 3 diets met the 2010 National Standards of the People's Republic of China (

      National Standards of the People's Republic of China. Laboratory animals—nutrients for formula feeds GB/T 14924.3-2010a. Ministry of Health, People's Republic of China [in Chinese].

      ).
      All mice were fed ad libitum under the same conditions for 30 days with free access to water. Amount of food consumed and body weight were recorded daily, and the average daily food intake and body weight were calculated at the end of the study. Random blood glucose concentration was monitored 3 or 4 times per day, except on fasting days. Feces reflect the ultimate result of interaction of entire gut microbiota and host; thus, fecal samples were collected, immediately frozen in liquid nitrogen and stored at −80°C in a freezer until use.

      16S rDNA sequencing, quality control and data analysis

      The V4 region of the prokaryotic small-submit (16S) rRNA gene was amplified with modified 515F (5′-GTGYCAGCMGCCGCGGTAA-3′) and 806R (5′-GGACTACNVGGGTWTCTAAT-3′) primers. The 5′ ends of the primers were barcode-tagged adjacent to the specific primers. Polymerase chain reaction (PCR) amplification was performed with 25 μL of reaction mixture aliquots containing 50 ng of template DNA, 12.5 μL of Phusion Host Start Flex 2X Master Mix (New England BioLabs, Ipswitch, Massachusetts, United States), 2.5 μL of forward primer, 2.5 μL of reverse primer and PCR-grade water to adjust the volume. PCR conditions for amplification of the prokaryotic 16S fragments consisted of initial denaturation at 98°C for 30 s, 35 cycles of denaturation at 98°C for 10 s, annealing at 54°C for 30 s, extension at 72°C for 45 s and final extension at 72°C for 10 min. The PCR products were separated by 2% agarose gel electrophoresis, purified by AMPure XT breads (Beckman Coulter Genomics, Danvers, Massachusetts, United States) and quantified fluorometrically by Qubit (Invitrogen, Waltham, Massachusetts, United States).
      The amplicon pools were sequenced with an Agilent 2100 bioanalyzer (Agilent, Santa Clara, California, United States) and size and quality of the amplicon library were determined with a Library Quantification Kit for Illumina sequencing (Kapa Biosciences, Woburn, Massachusetts, United States). The PhiX Control Library v3 (Illumina) and the amplicon library were combined, except for a 30% PhiX spike-in. The libraries were sequenced on 250PF MiSeq runs, and 1 library was sequenced with both protocols using Illumina standard sequencing primers, eliminating the need for a third (or fourth) index read. Samples were sequenced on an Illumina MiSeq platform following the manufacturer's recommendations. Paired-end reads were assigned to samples based on their unique barcode and truncated by cutting off the barcode and primer sequence. Paired-end reads were merged using Fast Length Adjustment of SHort reads (FLASH) software (https://ccb.jhu.edu/software/FLASH) (
      • Magoc T.
      • Salzberg S.L.
      FLASH: Fast Length Adjustment of SHort reads to improve genome assemblies.
      ).
      Quality filtering of the raw tags was performed under conditions that allowed us to obtain high-quality clean tags using FastQC version 0.10.0 (Babraham Bioinformatics; https://www.bioinformatics.babraham.ac.uk/projects/fastqc). Chimeric sequences were filtered using Vsearch software version 2.3.4 (https://github.com/torognes/vsearch) (
      • Rognes T.
      • Flouri T.
      • Nichols B.
      • Quince C.
      • Mahe F.
      VSEARCH: A versatile open source tool for metagenomics.
      ), and sequences with ≥97% similarity were assigned to the same operation taxonomic units (OTUs). Representative sequences were chosen for each OTU, and taxonomic data were then assigned to each representative sequence using the Ribosomal Database Project (RDP) classifier (https://rdp.cme.msu.edu/classifier/classifier.jsp;jsessionid=6EAF5285A39E3DC70FAEB431CBCEC920.radiant). Differences in the dominant species in the diet groups, phylogenetic relationships of different OTUs and multiple sequence alignments were evaluated using the Python Nearest Alignment Space Termination tool (http://biocore.github.io/pynast). OTU abundance was normalized using a standard corresponding to the sample with the smallest number of sequences.
      Alpha diversity, or mean species diversity, was used to describe the complexity of a microbiota sample. The Chao1, Shannon, Simpson and the observed species indexes were calculated with Quantitative Insights Into Microbial Ecology (QIIME) version 1.8.0 software (http://qiime.org/1.7.0) (
      • Caporaso J.G.
      • Kuczynski J.
      • Stombaugh J.
      • et al.
      QIIME allows analysis of high-throughput community sequencing data.
      ). Beta-diversity analysis was used to evaluate differences in species complexity of microbiota samples and was determined by principle coordinates analysis (PCoA) and cluster analysis using QIIME software.

      Statistical analysis

      Data were subjected to statistical analysis using SPSS version 24.0 (IBM SPSS, Armonk, New York, United States). Differences vs controls were evaluated by Wilcoxon rank sum test. A p<0.05 significance level was chosen for the statistical tests.

      Results and Discussion

      Effects of cornstarch‒tea diet on diabetes

      Food intake and body weight performance:

      The average body weights for the DM-C, DM-M and DM-IT mice were much lower than for the N-C mice. The average daily food intake in the DM-C, DM-M and DM-IT mice was much higher than that in the N-C mice. The DM-C mice had the lowest average body weight (22 to 28 g), but had the highest average daily food intake (6 to 16 g/mouse/day) compared with the other groups. The average body weight and daily food intake in the DM-IT and DM-M mice were not clearly different. From the highest to lowest performance, the average body weights in the study groups were ranked in the following order: N-C > DM-IT > DM-M > DM-C; and the average daily food intakes were: DM-C > DM-IT > DM-M > N-C (Figure 1).
      Figure thumbnail gr1
      Figure 1Effects of cornstarch tea diet on body weight, food intake and random blood glucose in diabetes. (A) Body weight. (B) Food intake. (C) Random blood glucose. DM-C, DM-IT and DM-M, diabetic mice fed a tea-free cornstarch diet, cornstarch instant tea diet and cornstarch matcha diet, respectively; N-C, normal mice fed a tea-free cornstarch diet.
      The diabetic mice had significant weight loss and hyperphagia compared with the control mice. These findings are consistent with significant hyperphagia and weight loss in diabetes. The diabetic mice fed the cornstarch‒tea diet showed higher body weight, but lower food intake, compared with the diabetic mice with the tea-free cornstarch diet. Instant tea and matcha contains polyphenols, caffeine, theaflavin, polysaccharides, etc. Tea polyphenols like EGCG are known to have antihyperglycemic activity, to reduce insulin resistance (
      • Lin C.L.
      • Lin J.K.
      Epigallocatechin gallate (EGCG) attenuates high glucose-induced insulin signaling blockade in human hepG2 hepatoma cells.
      ) and to inhibit lipid absorption (
      • Nakai M.
      • Fukui Y.
      • Asami S.
      • et al.
      Inhibitory effects of oolong tea polyphenols on pancreatic lipase in vitro.
      ). EGCG can regulate metabolism by activating the AMPK signalling pathway to reduce IRS-1 Ser307 phosphorylation and attenuate the insulin signaling blockade to improve glucose metabolism (
      • Lin C.L.
      • Lin J.K.
      Epigallocatechin gallate (EGCG) attenuates high glucose-induced insulin signaling blockade in human hepG2 hepatoma cells.
      ). Also, it was shown to protect pancreatic islets in a streptozotocin-induced diabetes model by downregulating expression of nitric oxide synthase through inhibition of nuclear factor kappaB activation (
      • Song K.
      • Hur H.
      • Han M.K.
      Epigallocatechin gallate prevents autoimmune diabetes induced by multiple low doses of streptozotocin in mice.
      ). Therefore, the benefits of tea's functional ingredients may increase utilization and conversion rate of the diet.

      Blood glucose regulation

      Random blood glucose in N-C mice ranged from 0 to 10 mmol/L or 10 to 25 mmol/L. The glucose concentrations in DM-C, DM-IT and DM-M mice ranged from 10 to 34 mmol/L, with some values >34 mmol/L. The percentage of random blood glucose levels >34 mmol/L decreased with the increase in feeding time. The proportion of random blood glucose concentrations between 10 and 25 mmol/L in the DM-IT mice and between 25 and 34 mmol/L in the DM-M mice became much higher than in the DM-C group with increased time on the experimental diet (Figure 1).
      Consumption of a tea-free cornstarch diet or cornstarch‒tea diet affected blood glucose control, with a time-dependent trend in reduction. These findings may be related to the high content of resistant starch, active functions of tea or both. Cornstarch has a content of about 50% resistant starch, which has lower kinetic constants and slower digestion than other types of starch, leading to a sustained slow release of glucose (
      • Zhang H.
      • Jiang Y.
      • Pan J.
      • et al.
      Effect of tea products on the in vitro enzymatic digestibility of starch.
      ). The reduced digestion of starch may have resulted in a reduction in the absorption of blood glucose from the small intestine of the diabetic mice. Instant tea and matcha contains many functional ingredients. In particular, EGCG is a well-known catechin and has many functions, such as reducing digestion and absorption of lipid by inhibiting pancreatic lipase activity (
      • Nakai M.
      • Fukui Y.
      • Asami S.
      • et al.
      Inhibitory effects of oolong tea polyphenols on pancreatic lipase in vitro.
      ), reducing glucose absorption by downregulating expression of sodium-dependent glucose cotransporter 1 (
      • Hossain S.J.
      • Kato H.
      • Aoshima H.
      • Yokoyama T.
      • Yamada M.
      • Hara Y.
      Polyphenol-induced inhibition of the response of Na(+)/glucose cotransporter expressed in Xenopus oocytes.
      ) and improving glucose utilization by promoting synthesis of insulin (
      • Yuskavage J.K.
      Epigallocatechin gallate in the regulation of insulin secretion.
      ). Therefore, the trend in reduction of blood glucose by feeding with a cornstarch‒tea diet may be due to the decreased digestion and absorption of energy from the gastrointestinal tract.

      Effects of cornstarch‒tea diet on gut microbiota in diabetes

      Alpha diversity, OTU clustering and beta diversity:

      The median values of the observed species, and Chao1, Shannon, and Simpson indexes in group DM-C were all higher than those of group N-C, but the differences were not statistically significant (p>0.05). The indexes in groups DM-IT and DM-M were all lower than those of group DM-C, but not to a significant extent (p>0.05). The difference in OTUs present in groups N-C and DM-C was 26.9%; 23.8% of the OTUs in groups DM-C and DM-IT and 23.8% of the OTUs in groups DM-C and DM-M were different. The differences in OTUs observed among the samples obtained from mice in the different experimental groups reflect the differences in fecal microbiota. In the PCoA, the unweighted quantitative UniFrac and weighted qualitative UniFrac showed that the microbiota of groups DM-C and N-C were obviously different. Effects of the other 2 treatments were intermediate (Figure 2). The PCoA results reconfirm that the experimental treatment changed the composition of the fecal microbiota.
      Figure thumbnail gr2
      Figure 2Effects of cornstarch tea diet on alpha diversity, OTU clustering and beta diversity in diabetes. (A) Alpha diversity. Boxplots depict microbiota diversity differences according to the observed species, Chao1, Shannon index and Simpson index among treatments. Dash represents median value, and the upper and lower ranges of the box represent the 75% and 25% quartiles, respectively. (B) OTU clustering. (C) Beta diversity (left: unweighted UniFrac [qualitative]; right: weighted UniFrac [qualitative]). Each symbol represents a sample; the variance explained by the principle coordinates is indicated in parentheses on the axes. DM-C, DM-IT and DM-M, diabetic mice fed a tea-free cornstarch diet, cornstarch instant tea diet and cornstarch-matched diet; N-C, normal mice fed a tea-free cornstarch diet; OTU, operation taxonomic unit.

      Bacterial taxonomic differences at phylum levels

      Analysis of the microbiota in fecal samples confirmed changes involving 10 phyla, with Bacteroidetes, Firmicutes, Proteobacteria and Actinobacteria being highly abundant and prevalent. These 4 phyla accounted for 98.36% of the reads in group DM-C, 98.88% in DM-M, 99.19% in DM-IT and 98.66% in N-C (Figure 3).
      Figure thumbnail gr3
      Figure 3Effects of cornstarch tea diet on gut microbiota at the phylum level. (A) Comparison of abundances of bacterial phylum of each sample. (B) Comparison of average abundance of each bacterial phylum in treatment groups, respectively. (C) Differences among the abundances of discriminatory phylum among 4 treatments. Dash represents median value, and the upper and lower ranges of the box represent the 75% and 25% quartiles, respectively. The p values were calculated using the Wilcoxon rank sum test. Asterisk represents significant difference (p<0.05) vs N-C. Pound sign represents significant difference (p<0.05) vs DM-C. DM-C, DM-IT and DM-M, diabetic mice fed a tea-free cornstarch diet, cornstarch instant tea diet and cornstarch matcha diet, respectively; N-C, normal mice fed with tea-free cornstarch diet.
      Compared with group N-C, levels of Proteobacteria, Candidatus saccharibacteria and Cyanobacteria in group DM-C were all significantly increased (p<0.05), and levels of Deferribacteres and Tenericutes increased by 58.33% and 600%, respectively, but the difference was not significant (p>0.05). Levels of both Actinobacteria and Verrucomicrobia decreased significantly (p<0.05) (Figure 3).
      Most importantly, the level of Actinobacteria in group DM-M and DM-IT was increased significantly (p<0.05) compared with group DM-C; levels of Proteobacteria were decreased by 58.43% (p<0.05) and 56.59% (p>0.05), respectively; and levels of Cyanobacteria were decreased by 62.50% (p>0.05) and 87.50% (p<0.05), respectively (Figure 3).

      Bacterial taxonomic differences at family levels

      Twenty families demonstrated microbiota changes. The 10 most prominent were Porphyromonadaceae, Lachnospiraceae, Lactobacillaceae, Bacteroidaceae, Prevotellaceae, unclassified Bacteroidales, Helicobacteraceae, Ruminococcaceae, Erysipelotrichaceae and Enterobacteriaceae (92.66%, 93.76%, 92.54% and 94.72% of the reads in DM-C, DM-M, DM-IT and N-C mice, respectively; Figure 4).
      Figure thumbnail gr4
      Figure 4Effects of the cornstarch tea diet on gut microbiota at the family level. (A) Comparison of bacterial family levels for each sample. (B) Comparison of the average level of each bacterial family in each treatment group. (C) Differences among the levels of each discriminatory family for the 4 treatments. Dash represents median value, and the upper and lower ranges of the box represent the 75% and 25% quartiles, respectively. The p values were calculated using the Wilcoxon rank sum test. Asterisk represents significant difference (p<0.05) vs group N-C; pound sign represents significant difference (p<0.05) vs group DM-C. (d) Heat maps of the top 20 microbial changes at the family level among treatments. (E) Heat maps of the top 20 microbial changes at genus levels among treatments. For each group, the columns show the relative abundance data of discriminatory microbiota at the genus level, as listed to the right of the figure. The abundances of each family were clustered using unsupervised hierarchical clustering (blue = low abundance; red = high abundance). DM-C, DM-IT and DM-M, diabetic mice fed a tea-free cornstarch diet, cornstarch instant tea diet and cornstarch‒matcha diet, respectively; N-C, normal mice fed with tea-free cornstarch diet.
      When compared with group N-C, levels of Lactobacillaceae, Prevotellaceae, Coriobacteriaceae, Verrucomicrobiaceae and Bifidobacteriaceae in group DM-C were all decreased significantly (p<0.05); levels of Bacteroidaceae, Helicobacteraceae, Ruminococcaceae, Enterobacteriaceae, Rikenellaceae and Saccharibacteria_genera_incertae_sedis were all increased significantly (p<0.05) (Figure 4).
      Moreover, levels of both Bacteroidaceae and Ruminococcaceae in groups DM-M and DM-IT decreased significantly (p<0.05); levels of Helicobacteraceae decreased by 55.68% and 74.91%, respectively, but this difference was not significant (p>0.05); levels of Enterobacteriaceae decreased by 78.07% and 32.89%, respectively, but again this was not significant (p>0.05). Beyond that, Coriobacteriaceae increased significantly (p<0.05); Lactobacillaceae increased by 101.81% and 27.21%, respectively (p>0.05, not significant); levels of Prevotellaceae increased by 80.72% and 68.64%, respectively (p>0.05, not significant) and levels of Bifidobacteriaceae increased by 155.56% and 311.11% (p>0.05, not significant) when compared with group DM-C (Figure 4). Comparative analysis results show that diabetes disturbed the composition of the intestinal microbiota, and that instant green tea and matcha dietary supplements reversed the changes in levels at the bacterial family level.
      Diabetes is a serious problem worldwide, with long-term hyperglycemia leading to increased oxidative stress, metabolic disorders and adverse changes in the gut microbiota (
      • Qin J.
      • Li Y.
      • Cai Z.
      • et al.
      A metagenome-wide association study of gut microbiota in type 2 diabetes.
      ). Our results suggest diabetic mice have major changes in bacterial abundance at the family and phylum levels compared with healthy controls. PCoA analysis confirmed the presence of differences in the microbiota. A total of 334 discriminatory OTUs were detected between the diabetic and normal mice, involving the families Bacteroidaceae, Helicobacteraceae, Ruminococcaceae, Enterobacteriaceae, Rikenellaceae, Saccharibacteria_genera_incertae_sedis, Lactobacillaceae, Prevotellaceae, Coriobacteriaceae, Verrucomicrobiaceae and Bifidobacteriaceae, with the phyla Proteobacteria, Candidatus Saccharibacteria, Cyanobacteria, Actinobacteria and Verrucomicrobia also involved (Figures 3 and 4).
      Diabetic mice showed significantly increased levels of Bacteroidaceae, Helicobacteraceae, Ruminococcaceae, Enterobacteriaceae, Rikenellaceae and Saccharibacteria_genera_incertae_sedis, and significantly decreased Lactobacillaceae, Prevotellaceae, Coriobacteriaceae, Verrucomicrobiaceae and Bifidobacteriaceae (Figure 4). It is well known that gut microbiota are closely related to digestion and absorption of chyme as well as body health. Intestinal microbiota dysbiosis leads to metabolism and physiological dysfunction. Results suggest that diabetes was significantly associated with changes in bacterial abundance at the family and phylum levels. Bifidobacteriaceae are anaerobic Gram-positive bacteria that belong to the phylum Actinobacteria and are abundant in the gastrointestinal microbiota of humans and animals (
      • Trovatelli L.D.
      • Crociani F.
      • Pedinotti M.
      • Scardovi V.
      Bifidobacterium pullorum, sp. nov.: A new species isolated from chicken feces and a related group of Bifidobacteria isolated from rabbit feces.
      ). Bifidobacteriaceae regulate the balance of intestinal microbiota (
      • Scardovi V.
      • Trovatelli L.D.
      Fructose-6-phosphate shunt as peculiar pattern of hexose degradation in the genus Bifidobacterium.
      ), reduce serum cholesterol and improve lactose tolerance (
      • Kimura N.
      • Yoshikane M.
      • Kobayash A.
      • Mitsuoka T.
      An application of dried Bifidobacteria preparation to scouring animals.
      ). The decreased level of Bifidobacteriaceae may result in bodily dysfunction. Prevotellaceae are carbohydrate-, protein- and acetate-fermenting bacteria, and they produce H2 (
      • Rode L.M.
      • Genthner B.R.
      • Bryant M.P.
      Syntrophic association by cocultures of the methanol- and CO2-H2-utilizing species eubacterium limosum and pectin-fermenting lachnospira multiparus during growth in a pectin medium.
      ). They are involved in biosynthesis, transport and catabolism of secondary metabolites. Erysipelotrichaceae are butyrate-producing bacteria that promote integrity of the intestinal endothelial barrier in the colon (
      • Pozuelo M.
      • Panda S.
      • Santiago A.
      • et al.
      Reduction of butyrate- and methane-producing microorganisms in patients with irritable bowel syndrome.
      ). Decreased levels of Prevotellaceae and Erysipelotrichaceae could decrease butyrate availability, increase endothelial permeability and result in intestinal dysfunction.
      Firmicutes contains 2 well-known families, Lachnospiraceae and Ruminococcaceae, which protect the colon endothelium by their production of butyrate (
      • Barcenilla A.
      • Pryde S.E.
      • Martin J.C.
      • et al.
      Phylogenetic relationships of butyrate-producing bacteria from the human gut.
      ). Decreased levels of Lachnospiraceae and Ruminococcaceae in the intestinal tract may cause dysfunction of the intestinal endothelium. On the other hand, increased levels of Lachnospiraceae and Ruminococcaceae may not be beneficial in diabetes as both have unusual effects on fermentation of carbohydrates (
      • Biddle A.
      • Stewart L.
      • Blanchard J.
      • Leschine S.
      Untangling the genetic basis of fibrolytic specialization by Lachnospiraceae and Ruminococcaceae in diverse gut communities.
      ). Ruminococcaceae, such as Ruminococcus flavefaciens, have unusual polysaccharide binding and degradation activities (
      • Flint H.J.
      • Bayer E.A.
      • Rincon M.T.
      • Lamed R.
      • Whit B.A.
      Polysaccharide utilization by gut bacteria: potential for new insights from genomic analysis.
      ), which produce short-chain fatty acids (
      • Canfora E.E.
      • Jocken J.W.
      • Blaak E.E.
      Short-chain fatty acids in control of body weight and insulin sensitivity.
      ). Bacteroidaceae are Gram-negative, anaerobic, non‒spore-forming rods that comprise a large portion of the intestinal microbiota in healthy people (
      • Burdon K.
      Bacterium melaninogenicum from normal and pathologic tissues.
      ). Increased Bacteroides (family Bacteroidaceae) has been associated with thrombophlebitis (
      • Ledger W.J.
      • Sweet R.L.
      • Headington J.T.
      Bacteroides species as a cause of severe infections in obstetric and gynecologic patients.
      ), and Bacteroidaceae are able to digest cellulose and produce H2, CO2, cellobiose, glucose, acetic acid and other products (
      • Saddler J.N.
      • Khan A.W.
      Cellulose degradation by a new isolate from sewage sludge, a member of the Bacteroidaceae family.
      ). Therefore, increased levels of Lachnospiraceae, Ruminococcaceae and Bacteroidaceae may lead to increased nutrient absorption from the intestinal tract and increased diabetic hyperglycemia.
      Helicobacteraceae has been associated with development of gallstones (
      • Murata H.
      • Tsuji S.
      • Tsujii M.
      • et al.
      Helicobacter bilis infection in biliary tract cancer.
      ), chronic gastritis (
      • Oxley A.P.A.
      • Powell M.
      • Mckay D.B.
      Species of the family Helicobacteraceae detected in an Australian sea lion (Neophoca cinerea) with chronic gastritis.
      ), chronic superficial gastritis and mucosa-associated lymphoid tissue lymphoma (
      • Heilmann K.L.
      • Borchard F.
      Gastritis due to spiral shaped bacteria other than Helicobacter pylori: Clinical, histological, and ultrastructural findings.
      ), as well as other gastrointestinal diseases in humans and animals (
      • Germani Y.
      • Dauga C.
      • Duval P.
      • et al.
      Strategy for the detection of Helicobacter species by amplification of 16s rRNA genes and identification of H. felis in a human gastric biopsy.
      ). Some Helicobacteraceae can produce urease (
      • Brodzik R.
      • Koprowski H.
      • Yusibov V.
      • Sirko A.
      Production of urease from Helicobacter pylori in transgenic tobacco plants.
      ), acuolating cytotoxin (
      • Murakita H.
      • Hirai M.
      • Ito S.
      • Azuma T.
      • Kato T.
      • Kohli Y.
      Vacuolating cytotoxin production by Helicobacter pylori isolates from peptic ulcer, atrophic gastritis and gastric carcinoma patients.
      ) or cytotoxin-associated proteins (
      • Rasmi Y.
      • Sadreddini M.
      • Jamali M.
      • Peirouvi T.
      • Khosravifar F.
      Frequency of cytotoxin associated gene a(+) Helicobacter pylori in peptic ulcer disease: Difference between gastric and duodenal ulcer disease.
      ) that have pathogenic activity. Enterobacteriaceae are a large family of Gram-negative bacteria belonging to the phylum Proteobacteria, which includes, along with many harmless symbionts, many of the more familiar pathogens, such as Salmonella, Escherichia coli, Yersinia pestis, Klebsiella and Shigella. Sutterellaceae and Rikenellaceae are both increased in diabetic mice. Sutterellaceae are Gram negative, oxidase- and catalase-negative bacteria that grow under microaerophilic or anaerobic conditions (
      • Morotomi M.
      • Nagai F.
      • Watanabe Y.
      Parasutterella secunda sp. nov. isolated from human faeces and proposal of Sutterellaceae fam. nov. in the order Burkholderiales.
      ), belonging to the phylum Proteobacteria. Proteobacteria is a major phylum of Gram-negative bacteria, including a wide variety of pathogens, such as Escherichia, Salmonella, Helicobacter, Yersinia, etc. Rikenellaceae belong to the phylum Bacteroidetes (
      • Su X.L.
      • Tian Q.
      • Zhang J.
      • et al.
      Acetobacteroides hydrogenigenes gen. nov. sp. nov. an anaerobic hydrogen-producing bacterium in the family Rikenellaceae isolated from a reed swamp.
      ), and Rikenellaceae include 2 genera, Rikenella and Alistipes (
      • Graf J.
      The family Rikenellaceae.
      ). Significantly changed quantities of these can represent a serious disorder of the intestinal microbiota.
      The results of 16S rDNA sequencing suggest that a cornstarch‒tea diet has beneficial effects on the intestinal microbiota of diabetic mice, particularly increased levels of Coriobacteriaceae, Lactobacillaceae, Prevotellaceae and Bifidobacteriaceae; decreased levels of Bacteroidaceae, Ruminococcaceae, Helicobacteraceae and Enterobacteriaceae; and the changes in the phyla Firmicutes, Bacteroidetes and Proteobacteria. Thus, the cornstarch‒tea diet improved and promoted balance of the intestinal bacterium group by reversing the changes in intestinal microbiota in diabetes induced by alloxan injection.

      Conclusions

      Diabetic mice had significant weight loss, hyperphagia and hyperglycemia, and also showed significant increases in Bacteroidaceae, Helicobacteraceae, Ruminococcaceae, Enterobacteriaceae, Rikenellaceae and Saccharibacteria_genera_incertae_sedis, and significant decreases in Lactobacillaceae, Prevotellaceae, Coriobacteriaceae, Verrucomicrobiaceae and Bifidobacteriaceae. The cornstarch instant tea or matcha diet decreased food intake, improved body weight loss and resulted in a trend in reduced blood glucose. In particular, the cornstarch tea diet increased Coriobacteriaceae, Lactobacillaceae, Prevotellaceae and Bifidobacteriaceae levels, and decreased Bacteroidaceae, Ruminococcaceae, Helicobacteraceae and Enterobacteriaceae. Thus, the cornstarch tea diet has beneficial effects on regulation of metabolism, blood glucose and gut microbiota and can reverse the changes in the microbiota, and, finally, the regulation pathway is bacterium-group regulation rather than single-species regulation.

      Acknowledgments

      The authors thank International Science Editing (http://www.internationalscienceediting.com) for editing this manuscript. This work was supported by a grant from the Public Benefit Foundation of Zhejiang Province ( LGN18C200010 ).

      Author Disclosures

      Conflicts of interest: None.

      Author Contributions

      H.Z. and J.L. conceived and designed the experiments; Y.J., Y.L., J.P., Y.Z. and J.L. performed the experiments; H.Z., J.P., J.L., S.Z. and M.H. analyzed the data; H.Z., Y.Z., S.Z. and J.L. contributed the reagents/materials/analysis tools and J.L. wrote the manuscript.

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