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Bioactive Constituents, Metabolites, and Functions

Prebiotic mannan-oligosaccharides augment the hypoglycemic effects of metformin in correlation with modulating gut microbiota Jialin Zheng, Heng Li, Xiaojuan Zhang, Min Jiang, Chunqin Luo, Zhenming Lu, Zheng-Hong Xu, and Jin-Song Shi J. Agric. Food Chem., Just Accepted Manuscript • DOI: 10.1021/acs.jafc.8b00829 • Publication Date (Web): 27 Apr 2018 Downloaded from http://pubs.acs.org on April 27, 2018

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Journal of Agricultural and Food Chemistry

Prebiotic mannan-oligosaccharides augment the hypoglycemic effects of metformin in correlation with modulating gut microbiota §

Jialin Zheng†, Heng Li*,†, Xiaojuan Zhang‡, Min Jiang†, Chunqin Luo , Zhenming Lu‡, Zhenghong Xu‡,#, Jinsong Shi*,† †

Key Laboratory of Carbohydrate Chemistry and Biotechnology, Ministry of Education, School

of Pharmaceutical Science, Jiangnan University, 1800 Lihu Avenue, Wuxi 214122, China ‡

National Engineering Laboratory for Cereal Fermentation Technology, Jiangnan University,

1800 Lihu Avenue, Wuxi 214122, China §

Chengdu Yongan Yuanhe Biotechnology Co. Ltd., 5th Tianfu Street, Chengdu 611630, China

#

School of Biotechnology, Jiangnan University, 1800 Lihu Avenue, Wuxi 214122, China

*

Corresponding author, Tel: +86-510-85328177; Fax: +86-510-85328177; E-mail:

[email protected], [email protected]

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ACS Paragon Plus Environment


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ABSTRACT

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Type 2 diabetes (T2D) induced by obesity and high-fat diet is significantly associated with gut

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microbiota dysbacteriosis. Due to the first line clinical medicine of metformin has several

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intestinal drawbacks, combination usage of metformin with a prebiotic of konjac

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mannan-oligosaccharides (MOS) was conceived and implemented aiming to investigate whether

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there was some intestinal synergetic effects and how MOS would function. Composite treatment

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of metformin and MOS demonstrated synergistic effects on ameliorating insulin resistance and

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glucose tolerance, and repairing islet and hepatic histology. In addition, MF+MOS altered the gut

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community composition and structure by decreasing the relative abundances of family

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Rikenellaceae and order Clostridiales while increasing an unnamed OTU05945 of family S24-7,

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Akkermansia muciniphila, and Bifidobacterium pseudolongum. The present study suggested that

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usage of MOS could augment the hypoglycemic effects of metformin in association with gut

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microbiota modulation, which could provide references for further medication.

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KEYWORDS: konjac mannan-oligosaccharides (MOS); gut microbiota; type 2 diabetes;

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metformin

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2 Environment ACS Paragon Plus

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INTRODUCTION

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Diabetes has become a severe health issue accompanied by obesity, sedentary lifestyles, and

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population aging.1 It is estimated that global diabetic population is rapidly growing from 415

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million in 2015 to 642 million by 2040,1 within which 90% above are type 2 diabetes patients

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characterized by insulin resistance and impaired glucose tolerance.2 This situation imposes a

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great socio-economic burden on public health, and meanwhile hastens new intervention

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mechanisms and therapeutic strategies to come out.

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Gut microbiota plays an important role in health. It is causally concerned with the onset or

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progression of many diseases, including cancer, inflammatory bowel disease, and metabolic

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disease.3 Accumulating evidences indicate that gut microbiota is strongly associated with T2D

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development.4 Qin et al found that patients with T2D were characterized by a moderate degree of

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gut microbial dysbiosis.5 The composition of the microbiome differed between diabetic and

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normal individuals. Specifically, diabetes was associated with a decrease in the abundance of

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some universal butyrate-producing bacteria and an increase in various opportunistic pathogens.

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In addition, a study investigating 277 non-diabetic Danish individuals and 75 T2D Danish

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patients showed that human gut microbiome impacted the serum metabolome and associates with

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insulin resistance.6 On the basis, gut microbiota has been developed as a new therapeutic target

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for diabetes and other disorders associated with metabolic syndrome. Fecal microbiota

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transplantation (FMT) has provided the most direct evidences. Taken for examples, FMT from

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lean donors to obese patients with metabolic syndrome improved insulin sensitivity notably.7

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Meanwhile, diets supplemented with probiotics and prebiotics are considered to be beneficial in

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diabetes mellitus management.8



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As a first line clinical medicine for T2D, metformin performed significant effects on inhibition

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of hepatic glucose production, promotion of glucose uptake increase9, and alleviation of

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insulitis10. Recent studies in mice showed that metformin could also influence gut microbiota and

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corresponding metabolic pathways11. Nevertheless, metformin treatment is associated with a

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number of intestinal side effects, such as adverse lipid metabolism, vitamin B12 deficiency, and

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digestive disorders.12,13 However, these drawbacks could be alleviated by adding prebiotics to

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promote intestinal beneficial bacteria proliferation and vitamin B supply.14 Clinical data also

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show that reasonable dietary fiber intake and diet regulation can control obesity and T2D, which

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was even more effective and safer than metformin.15 As a result, a proposal that combination of

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prebiotics or probiotics with metformin to treat diabetes had been developed.16

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Konjac mannan oligosaccharides (MOS) is consisted of β-D-mannose and β-D-glucose

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residues jointed together in 1→4 linkages.17 It is generally obtained through depolymerization of

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Konjac glucomannan (KG), which is an essential polysaccharide and the main component of the

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roots and tubers of Amorphophallus konjac plant.18 KG and MOS cannot be hydrolyzed by

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digestive enzymes in human upper gastrointestinal tract. It has already been verified that KG

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performed prebiotic effects in alleviating hypercholesterolemia and hyperglycemia.19,20 In a

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randomized cross over study including 22 T2D patients, it was found that the KG supplement

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improved blood lipid levels and alleviated the elevated glucose levels in diabetic subjects.21

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Evidences also showed that konjac glucomannan hydrolysates could potentially improve gut

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health by promoting the growth of beneficial bacteria and suppressing the pathogenic ones, and

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seemed to lower the blood glucose and cholesterol in mice.22 In addition, with the ability to bind

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and limit the colonization of gut pathogens, MOS has proven to be an effective solution for

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antibiotic-free diets, as well as applying in immunity and digestion and food ingredients.23


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Owing to the superiorities of MOS in prebiotic properties and dissolvability, it is worth

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investigating in detail whether there is some synergetic effects for composite treatment of MOS

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and metformin and how MOS would function therein.

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Consequently, experiments with MOS alone and its combination with metformin treatments

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were both conceived and conducted on a T2D model in mice in this study. The biochemical

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indexes were first examined to verify whether MOS possessed the hypoglycemic effects and

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whether there was a synergistic effect between MOS and metformin. Gut microbiota was then

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analyzed by 16S rRNA gene sequencing to elucidate the potential possible mechanism.

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MATERIALS AND METHODS

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Materials and Animals. MOS (average molecular weight ca. 1000 Da, mole ratio of glucose

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to mannose 1:1.2, degree of polymerization 2-6) was supplied from Yongan Yuanhe

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Biotechnology Co., Ltd (Chengdu, China). Metformin and streptozotocin (STZ) was purchased

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from Sigma-Aldrich (St. Louis, MO, USA). High-fat diet (#TP23300, fat 60.0%, carbohydrate

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20.6% protein 19.4%) and normal control diet (#TP23302, fat 10.0%, carbohydrate 71.0%,

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protein 19.0%) were supplied by TROPHIC Animal Feed High-Tech Co., Ltd. Glucometer and

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strips were purchased from Roche Diagnostics GmbH (Mannheim, Germany). Glycosylated

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hemoglobin (HbA1c) assay kit and insulin ELISA kits was purchased from Nanjing Jiancheng

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Bioengineering Institute (Nanjing, China). QIAamp DNA Stool minikit was obtained from

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Qiagen (Hilden, Germany).

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A total of 88 three-week-old male C57BL/6J mice were purchased from SLAC laboratory

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(Shanghai, China) and housed at constant temperature of 25 °C and relative humidity of 55 ± 5%

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under an artificial 12 h light/darkness cycle with ad libitum access to chow diet and water.

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Animal experiments were approved and performed in accordance with the guidelines of



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Institutional

Animal

Care

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No20170505-20170609[57]).

and

Use

Committee

of

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Jiangnan

University

(JN.

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Type 2 Diabetes Model Construction. After being acclimated for a week, 80 C57BL/6J mice

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were used to establish the diabetic models, which were first fed with high fat diet for 4 weeks

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and then injected with STZ (30 mg/kg, dissolved in 0.01 M sodium citrate buffer, pH 4.4)

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intraperitoneally for 7 consecutive days.24 During the next 4 weeks, fasting blood glucose (FBG)

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was detected every week. Those mice (80) whose blood glucose were 11.1 mmol/L above were

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considered as diabetic rats and ready for further pharmacological studies.

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Grouping and Treatment Experiment Design. Three kinds of treatments consisting of

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metformin alone (MF), MOS and combination of the above two (MF+MOS) were employed and

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compared. 80 diabetic mice were randomly divided into 10 groups (8 mice per group) and treated

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as per the following specifications. Diabetic model control group (MC): diabetic mice treated

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with saline in a matched volume (10 mL/kg), MF treatment groups: diabetic mice administered

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with MF respectively at high (200 mg/kg/day, MFH) and low dosages (75 mg/kg/day, MFL),

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MOS treatment groups: diabetic mice treated with MOS separately at high (8 g/kg/day, MOSH),

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medium (4 g/kg/day, MOSM) and low (2 g/kg/day, MOSL) dosages, composite treatment of MF

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and MOS groups: MF treatment groups at two dosages and MOS treatment groups at high and

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medium dosages were selected and combined in pairs randomly. Then there came out four

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composite treatment groups: MFH+MOSH, MFH+MOSM, MFL+MOSH, and MFL+MOSM. A

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normal group (NC, n = 8) treated with saline in a same volume was also set for control. All

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treatments were given orally consecutively for 5 weeks. Body weight, food/water intake and

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FBG were detected and monitored weekly. At the end of experiments, all mice were

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anaesthetized and humanely sacrificed by cervical dislocation after overnight fasting. Blood


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samples were collected from mice orbit and then quickly separated at 4 oC to obtain plasma and

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red blood cells, which were stored at -80 oC. For histological analysis, pancreases and the right

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lobe of livers were fixed in 10% neutral formalin at room temperature. Fresh feces samples of

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different treatments were collected for the last week and stored at -80 °C.

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Oral Glucose Tolerance Tests (OGTT). At the last week, mice were fasted for 12 h and then

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gavaged with glucose solution at the dose of 1 g/kg. Tail vein blood samples were collected for

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blood glucose concentration detection with a glucose meter at 0, 30, 60, and 120 min. The results

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were expressed as an integrated area under glucose concentration-time curve (AUC).

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Biochemical Parameters. Hemoglobin A1c (HbA1c) in red blood cells was estimated by

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diagnostic kits according to the instruction of the kits. HbA1c was calculated as optical density

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value per 10 g hemoglobin. Plasma insulin was estimated using ELISA kits according to the

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manufacturer’s instructions. Homeostasis assessment of insulin resistance (HOMA-IR) was then

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calculated.

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Histological Examination of Pancreas and Livers. After being dehydrated with graded

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alcohol series, pancreas and liver samples were embedded in paraffin and cut into sections.

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Sections with 4 µm thickness were stained with hematoxylin and eosin and evaluated the related

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indicators under light microscope.

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Sequencing and Sequence Data Analysis. Total fecal bacterial genome DNA was extracted

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from the faeces using a QIAamp DNA Stool minikit following the manufacturer’s instructions.

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The V3-V4 region of the 16S rRNA gene was amplified using forward primer 338F and reverse

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primer 806R.25 After being purified and recovered, PCR products were barcoded and quantified

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using a QuantiFluor-ST Fluorometer (Promega, USA) and were pooled for sequencing.



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Sequencing was performed on the Illumina®MiSeq sequencer (Illumina, San Diego, CA, USA)

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by Majorbio Bio-pharm Technology Co., Ltd. (Shanghai, China).

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QIIME 1.9.1 was used to process the resulting sequence data. Briefly, high quality (quality

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value > 25) sequence data derived from the sequencing process were demultiplexed. USEARCH

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was used to obtain operational taxonomic units (OTUs) with 97% sequence similarity. Principal

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Coordinate Analysis (PCoA) and Unweighted Pair Group Method with Arithmetic mean

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(UPGMA) Clustering tree were used to assess the variation between experimental groups (beta

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diversity). Alpha diversity was calculated for all the samples. Analysis of similarities (ANOSIM)

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and Pearson correlation analysis was conducted by Phylogenetic Investigation of Communities

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by Reconstruction of Unobserved States (PiCRUSt, http://picrust.github.com) and performed to

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predict the abundances of functional gene categories on KEGG pathway database.

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Statistical Analysis. Data were expressed as mean ± standard error of the mean.26 The

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significance of difference among diet groups was analyzed by one-way ANOVA followed by

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Tukey’s post hoc test. Probability values lower than 0.05 were taken to indicate statistical

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significance. All analyses were performed using GraphPad Prism version 7.0. A non-parametric

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statistical t test was conducted by ANOSIM to determine statistically significant changes (p

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