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Metabolic effect of 1-Deoxynojirimycin from Mulberry Leaves on db/db Diabetic Mice using LC-MS based Metabolomics Xue-Qin Hu, Kiran Thakur, Gui-Hai Chen, Fei Hu, Jian-Guo Zhang, Hong-bin Zhang, and Zhao-Jun Wei J. Agric. Food Chem., Just Accepted Manuscript • Publication Date (Web): 25 May 2017 Downloaded from http://pubs.acs.org on May 26, 2017

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Journal of Agricultural and Food Chemistry

Metabolic effect of 1-Deoxynojirimycin from Mulberry Leaves on db/db Diabetic Mice using LC-MS based Metabolomics Xue-Qin Hu†‡, Kiran Thakur †, Gui-Hai Chen§, Fei Hu †, Jian-Guo Zhang †, Hong-Bin Zhang‡, Zhao-Jun Wei †* †

School of Food Science and Engineering, Hefei University of Technology, Hefei

230009, People’s Republic of China ‡

School of Biotechnology and Medicine, Hefei University of Technology, Hefei

230009, People’s Republic of China §

Department of Neurology, The Affiliated Chaohu Hospital of Anhui Medical

University, Chaohu, Hefei 238000, People’s Republic of China

*Correspondence: E-mail: [email protected]; Tel: +86-551-62901539; Fax: +86-551-62901539.

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ACS Paragon Plus Environment


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Abstract: Metabolomics was applied to LC-MS urinary metabolic profile of type 2

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diabetes (T2DM) mice treated with mulberry 1-deoxynojirimycin (DNJ). The serum

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biochemical indicators related to T2DM like blood glucose, insulin, triglyceride,

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total cholesterol, nitrogen, malondialdehyde and creatinine decreased significantly in

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treated group. The histopathological changes in liver cells were marked by

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deformations and disruptions in central area of nuclei in DM mice, whereas, DNJ

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treatment recovered regular liver cells with normal nuclei. Most of the metabolites of

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T2DM were significantly different from healthy controls in the bulk data generated.

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The level of 16 metabolites showed that the diabetic group was closer to the healthy

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group as the DNJ treatment time prolonged. Moreover, DNJ inhibited the activity of

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glucosidase on glucose, lipid and amino acid metabolism. Our results showed the

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mechanism of DNJ treatment of T2DM and could fetch deep insights into the potent

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metabolite markers of the applied anti-diabetic interventions.

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Keywords: Type 2 diabetes; Mulberry; 1-deoxynojirimycin; Urinary metabolites;

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LC-MS; Metabolomics

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Introduction

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Type 2 diabetes mellitus (T2DM) is generally characterized by both clinical features

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such as chronic hyperglycemia and insulin secretion deficiency. Multiple risk factors

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(family history, aging, obesity, high blood pressure and energy intake) are

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responsible for T2DM pathogenesis.1 It is more likely that the next decade would

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witness T2DM in more than 250 million individuals worldwide. However,

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understanding towards its causes and optimal treatment are still in lag phase. Thus,

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shift of focused research on the metabolic phenotype of T2DM would help us to

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investigate its pathogenesis to some extent.

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Mulberry (Morus spp.) has been cultivated widely in many Asian countries and its

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leaves enjoy the status of functional foods in China, Japan, Korea, Thailand and

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many other Asian countries.2, 3 Mulberry 1-deoxynojirimycin (DNJ) is glucose

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analog with a NH group substituting for the oxygen atom of the pyranose ring.4, 5

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Previous studies have claimed that DNJ displayed high alpha-glucosidase inhibitory,

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antioxidant, antimicrobial and anti-inflammatory activity, inhibition of adipogenesis

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as well as protection from age-related behavioral.6-9 Kong et al. (2008) reported the

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antiobesity and postprandial hypoglycemic effects of DNJ in Otsuka Long-Evans

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Tokushima Fatty rats.10 Kimura et al. (2007) suggested that DNJ-enriched powder

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can be used as a dietary supplement for preventing diabetes mellitus.9 Kwon et al.

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(2011) demonstrated the postprandial hypoglycemic effects of DNJ and aqueous

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mulberry leaf extracts through in vivo and in vitro studies.8 Mulberry DNJ serves as

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the main component of mulberry leaf that prevents T2DM by inhibiting 3



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α-glucosidase in the small intestine and in postprandial hyperglycemia and

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suppresses lipid accumulation.11Additonally, chronic DNJ treatment alleviated the

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age-related changes, and DNJ may have the potential to maintain successful brain

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aging.12 . The above results prove DNJ as a potent candidate to be used as a

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functional or medical food to control postprandial blood glucose.2, 9-10

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Generally, metabolomics is applied for disease diagnosis and drug analysis. It

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can be applied to any bio‑fluid, including serum, urine, saliva or bile and it has been

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identified as a promising and reliable novel diagnostic approach for several types of

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metabolic disorders.13 An LC-MS-based metabonomics method can quickly obtain

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comprehensive information about endogenous metabolites in biological samples.14, 15

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Till date, few reports have depicted the metabolite profiling of urine from T2DM

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KK-Ay mice treated with repaglinide by GC-MS,16 in type 2 diabetic KK-Ay mice 17

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and urine metabolism in type two diabetic patients based on GC-MS .18 The previous

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studies19-21 showed that the metabolites of urine using various treatment resulted into

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significantly differences, due to different biological processes involved in their

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construction.22 Therefore, by ignoring the urinary metabolism, we might miss an

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important research link which contains feedback information and is convenient to

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carry out. Moreover, metabolic analysis of body fluids like urine, blood, and tissue

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line, is important for analysis of small molecules and among them, urine is

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non-invasive and more convenient.

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In the view of the previous research about the therapeutic effects of DNJ, only few studies have paid close attention to the changes in the endogenous metabolites of 4


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urine in diabetic mice using DNJ. With this aim, a urinary metabolomics method of

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type 2 diabetic db/db mice based on LC-MS was employed to represent the

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metabolic characteristics of T2DM followed by gavage feeding of DNJ for nine

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weeks followed by serum and urine collection for further analysis of metabolites.

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After nine weeks, body weight, fasting blood glucose (FBG), insulin,

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malondialdehyde (MDA), advanced glycation end products (AGEs), triglyceride

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(TG), total cholesterol (TC), high-density lipoprotein (HDL), low-density lipoprotein

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(LDL), aminotransferase (ALT), blood urea nitrogen (BUN), creatinine (Cr) and

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liver hematoxylin-eosin staining (HE) and urine metabolomics analysis were

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targeted. Furthermore, principal component analysis (PCA), Partial Least Squares

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Discriminant Analysis (PLS-DA) and one-way ANOVA analysis were applied to

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directly demonstrate the changed footprint of the mice groups after treatment with

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DNJ. The metabolic profiling in urine of mice treated with DNJ which ultimately

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can provide hints for patho-physiology of T2DM and may be useful as a source of

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novel T2DM-associated biomarkers. Compared to conventional biochemical

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indicators for T2DM, these biomarkers may be more exclusive and effective.

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Material and Methods

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DNJ procurement

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DNJ were extracted from mulberry leaves followed the description by Kimura et al.

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(2007) 9 with minor revisions. In brief, DNJ was extracted from mulberry leaves with

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60% ethanol (pH = 2) and stored at -80 oC for 2 h followed by the treatment with

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AB-8 macroporous resin. The purification process was followed by using 1 BV 5



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deionized water, 1.5 BV 0.3 M ammonia water and 2 BV0.5 M ammonia water with

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an elution flow rate of 2 BV/h at pH 9-10. Then after, the elute was collected and

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purified by preparative liquid phase (column packing: strong polar amino-bonded

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silica gel, mobile phase: acetonitrile 70%, water 30%). The final product was

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collected and concentrated after crystallization in 96% ethanol, re-dissolved after

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detection of 98% purity and freeze-dried until use. The purity of DNJ was

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determined with MS, 1H-NMR spectra and 13C-NMR spectra analysis (Supplemental

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Figure 1-3)

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Animal treatment

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The sixteen 7 weeks old male mice [BKSCg-Dock7m+/m+Leprdb/Nju(db/db) and 8

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C57BLKS / J Nju (db/m) mice of the same litter size with Animal Production

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License No.: SCXK (Su) 2010. 0001] were purchased from Nanjing University

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Model Animal Research Institute. All mice were fed with standard pellets. The

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housing conditions like laboratory ventilation, natural day night lighting and

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temperature were maintained at 20-24 oC and relative humidity remained at 50-60%.

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All mice were subjected to adaptive feeding for one week before the start of the

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formal experiment. All the experimental protocols were in accordance with the

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National Standard for the Administration of Laboratory Animals, and were reviewed

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and approved by the Experimental Animal Ethics Committee of Hefei University of

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Technology. Seven db/m mice were randomly divided into normal control group

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(CC group). Fourteen db/db mice were randomly assigned to two treatment groups:

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seven in the DM group and seven in the DMT intervention group. DMT mice were 6


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given DNJ aqueous solution by intragastric administration (20 mg / kg daily) for

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nine weeks. The mice in CC and DM groups were fed with the same volume of

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saline every day for 9 weeks. Throughout the experiment, all mice were not exposed

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to any hypoglycemic agents. All mice were weighed by electronic analytical balance

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(MP200A, Shanghai Precision Instrument Co., Ltd.) at the beginning of the

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experiment, and body weight was recorded weekly during the experiment.

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Blood sample collection

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After the end of the test and fasting with water, the blood was collected from inferior

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vena cava and liver tissues were collected by subjecting the mice to anesthesia.

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Whole blood was centrifuged at 3000 rpm for 15 minutes; upper serum layer was

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carefully obtained and stored at -80 oC until analysis of biochemical indicators. Four

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mice in each group were placed in 10% formaldehyde solution for haematoxylin and

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eosin (HE) staining to observe the liver morphology.

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Biochemical Indicators

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2 mL of blood was taken from the inferior vena cava and heparin was added to it and

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was centrifuged at 3500 rpm for 10 minutes to afford the supernatant, which was

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stored in a -80 oC freezer. At the end of the experiment, insulin, FBG, TC, TG, HDL,

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MDA, AGEs, ALT, BUN and Cr were measured according to procedures given in

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previous reports.16, 19, 23, 24 The serum analysis was done using total seven mice from

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DM and DMT groups.

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Histopathology

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Histopathology (H&E) staining was carried out by Baratta et al. (2009).25 After the

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mice were euthanized and small pieces from the livers were fixed in 10% formalin,

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embedded in paraffin, sectioned with a 6-mm thickness, and stained with H&E. In

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brief, slide mounted 8–12 µm sections and were dehydrated through absolute alcohol

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and rehydrated to water followed by hematoxylin stain for 4 minutes, rinsed in water

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and differentiated in 70% alcohol. The samples were re-stained in 0.01% eosin Y for

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2 seconds, rinsed with 95% ethanol, followed by dehydration and finally cover

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slipped. The slides were observed with microscope.

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Urine sample preparation

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The urinary analysis was performed according to Men et al. (2017). 19 Urine samples

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of 24 h urine of seven mice (DM and DMT group) were collected into tubes over

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wet ice at the end of the experiment after 9-weeks. The collected urine was

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centrifuged at 3000 rpm for 10 min. The supernatant was transferred and stored at

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−80 oC until analysis. Before LC-MS analysis, urine samples were thawed and

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centrifuged at 15000 rpm for 10 min at 4◦C.

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LC−MS Data acquirement

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LC-MS analysis was carried out according to Luo et al. (2013). 26 An Agilent 1100

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HPLC equipped with a photodiode array detector (PAD) coupled to a 6210 TOF

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mass spectrometer with electro spray ionization (ESI) source was used for urinary

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metabolites. An Agilent Eclipse XDB-C18 (5 µm, 150 × 2.1 mm inner diameter) was

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used for chromatographic separation and the LC parameters were as follows: 5 µL

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was injected into the system, column temperature was maintained at 40 °C and flow 8


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rate was 0.3 mL/min. The eluates were monitored with a PAD at full-length scan

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from 200 to 600 nm. The mobile phase consisted of (1) 0.1% formic acid in water

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and (2) 0.1% formic acid in acetonitrile, and then, gradient elution was carried out:

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5% (2) for 0−3 min, 5−100% (2) for 3−50 min, and 100% (2) for 50−60 min. The

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initial gradient for reconditioning the column was set for 12 min. The mass

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spectrometry consisted of positive and negative ionization mode, drying gas, 12

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L/min; gas temperature, 350 °C; nebulizer pressure, 45 psi; capillary voltage, 4000 V

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in positive mode and 3500 V in negative mode; fragment or voltage, 215 V in

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positive mode and 170 V in negative mode; skimmer voltage, 60 V; and OCT 1 RF,

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250 V. Data acquisition m/z range was from 50−1100 Da.

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Data Processing and Statistical Analysis

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The raw data from LC−TOF were preprocessed by using Mass Hunter software

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(Agilent Technologies, Santa Clara, CA). The automated peak detection and

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chromatographic deconvolution were carried out using the molecular feature

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extraction (MFE) algorithm. Signal-to-noise (S/N) ratios for each peak was set as 5

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and lower than that were rejected. The mass/retention time/peak height data array for

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each sample were generated and exported as a .csv file. Then, MetaboAnalyst for

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subsequent data process was used for analyzing data and statistical analysis. Peaks

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were aligned across all samples using the parameters of 0.01 Da and 0.5 min

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tolerance. Multivariate analysis was used for processed data. Principal component

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analysis (PCA) and orthogonal projection to latent structure discriminant analysis

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(OPLS-DA) were performed by SIMCA-P+ (version 12.0, Umetrics, Umea, 9



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Sweden). The intensity for each peak was normalized to the sum of the peak

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intensities for each data set, and then, pareto scaling was applied for PCA and

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OPLS-DA. MetaboAnalysis was used for One-way analysis of variation (ANOVA) ,

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and hierarchical clustering analysis (HCA).

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Statistical analysis of serum biochemical indicators was carried out by using SPSS

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18.0 software. All the data were expressed as mean ± standard deviation (SD).

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One-way analysis of variance (ANOVA) was per-formed using the Origin Lab

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(Origin Pro 8.0) software at significance level p < 0.05 and p < 0.01.

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Result and Discussion

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Effects of DNJ on body weight, blood glucose and Serum insulin

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Body weight was monitored each week during the experimental nine weeks after

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administration with DNJ (20mg /kg/day). After two weeks, the body weight

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of db/db mice administered with DNJ decreased significantly compared with DM

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control (Figure 1A). After seven weeks, the difference between DMT and DM

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vanished gradually. Our results agreed with previous studies which reported the

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effects of anti-diabetic agents on body weight under in vivo trails.20 Moreover, the

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time span of our treatment was nine week which was possibly longer duration than

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other studies.

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There are previous reports which also mentioned that after definite period of time,

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the effect of treatment was diminished in case of body weight but other parameters

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differed significantly till the end of treatments. The fasting blood glucose level was

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significantly reduced after oral glucose challenge following treatment with both 10


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single anti-diabetic compounds and their combination compared with untreated HF

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diet-fed mice27. Whereas, another study 28 have reported that there was no

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significant difference in the first week of treatment, the body weight of db/db mice

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treated with DNJ decreased significantly in a dose dependent manner from second

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week. Kong et al. (2008)10 have studied the anti-obesity effects of DNJ in Otsuka

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Long-Evans Tokushima Fatty rats. Do et al., (2015)29 have concluded that final

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body weights were significantly higher in the high fat group (38.08gm) than in

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control (30.00 gm) or DNJ group (34.01gm). While comparing all the mentioned

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studies, we could conclude that DNJ has less effect for control of body weight

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regulation.

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The db/db mice maintained the constant high blood glucose compared to CC

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throughout the experimental period. Nine weeks after administration with DNJ,

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FBG administration decreased significantly compared with DM control group

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(Figure 1B). Previous studies have also reported the significant decrease in FBG in

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anti-diabetic drug administered mice 9, 20, 21. It is well known that the increasing

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glucose concentration, enters the urine, and therefore, diabetes increases. Urinary

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glucose reduction serves as direct feedback information on therapeutic effect of

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anti-diabetic agents. This means that glucose is well regulated during meals, but it

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can last for a short time of 4 hours.16

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Serum insulin was monitored after nine weeks treatment with DNJ, and the

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insulin level of db/db mice was higher than that of CC. The insulin levels of DMT

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were significantly decreased than that of DM, with the value of 1.27 and 3.18 µg/L, 11



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respectively (Figure 1C). Our result was in accordance with previous reports

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suggesting the decrease in treatment group of different diabetic mice models.20

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Early insulin secretion is a typical defect found in T2DM, which may lead to high

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FBG concentration and postprandial hyperglycaemia.16 The homeostatic model

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assessment (HOMA) test which was performed to quantify the insulin resistance

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also led to significantly lowered values in treatment group (33.23 IR) than in

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diabetic group (97.87 IR) as shown in Figure 1D. Previous studies have also

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reported that DNJ could decrease the levels of glucose and insulin sensitivity via

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increasing skeletal muscle insulin sensitivity28, 30.

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Effects of DNJ on biochemical indicators

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The serum levels of TG and TC of DMT group were significantly lower than that

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of DM group (Figure 2A, B). The higher levels of TG led to the disorder of lipid

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metabolism in diabetic mice. The HDL levels in two groups of db/db mice were

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significantly lower than that of CC group. After administered with DNJ, the HDL

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level of DMT group was slightly increased as compared to DM group (Figure 2C).

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The LDL of DMT group was slightly lower than that of DM group, but no

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significant differences was observed (Figure 2D). Previous researches have also

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reported the significant increase in TG of anti-diabetic drug administered mice and

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high-fat diet induced obesity.19-21 Compared with DM group mice, DMT group has

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effectively decreased the TC and TG biochemical indexes which are in agreement

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with the previous study (Liu et al., 2016). Many studies have shown that DNJ-rich

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mulberry leaf extract can be used to potentially improve lipid profiles in clinical

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trials31and also to suppress the lipid accumulation in vivo 32.

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The level of serum MDA and serum AGEs were measured to estimate the

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oxidative stress capacity of db/db mice after administered with DNJ. Compared to

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CC group, the level of MDA and AGEs of two group db/db mice were higher than

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those of CC group (Figure 2E, F). DNJ treatment led to down regulation of MDA

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level in db/db mice significantly (Figure 2E), and the AGEs level was cut down

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non-significantly (Figure 2F). MDA known as oxidative stress marker is a highly

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toxic by-product formed during lipid oxidation derived free radicals which plays

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critical role in the oxidation–reduction reaction as well as it is closely related to the

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deficiency of vital energy.19 Its interactions with proteins and phospholipids have

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intense effects which ultimately attack and damage lipids, proteins and nucleic

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acids resulting into diabetic complications. In addition to the important role of

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advanced AGEs in the pathogenesis of diabetic vascular complications, previous

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studies suggested that advanced glycation end products can also impair insulin

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action in vitro.33 After accumulating in the body, AGEs contribute to the reduced

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susceptibility to catabolism and lead to the aging of tissues which ultimately play an

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important role in the development of diabetic complications due to their intra- and

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extracellular cross linking with proteins and other endogenous key molecules

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including lipids and nucleic acids. Moreover, AGEs are accompanied by increased

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free radical activity (oxidative stress markers) that contributes towards the bio

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molecular damage in diabetic patients. Thus, we can conclude that MDA and AGEs

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have close association in the pathogenesis of T2DM.

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The effects of DNJ on the levels of ALT (liver damage monitoring/ liver function

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indicator), and urea and Cr (kidney damage detection index) were determined

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(Figure 2G, H, I). Compared with CC group, ALT, BUN and Cr significantly

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increased in DM and DMT group. After DNJ administration, the serum ALT and

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BUN decreased slightly (Figure 2G, H), but the serum Cr level significantly reduced

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(Figure 2I) which was in agreement with the previous report.15

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Effect of DNJ on hepatic pathological changes

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DNJ had a very good recovery impact to restore the histopathological changes

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occurred due to diabetic liver tissues. The histopathology of liver tissues

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descriptions are shown in Figure 3. HE staining showed that the morphology of liver

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cells in CC group was normal and the nuclei were round and clear. In DM group, the

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morphological alterations like sever liver cell damage, nuclear deformations and

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disruptions of central areas of liver cells were observed, whereas, in DMT group, all

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the marked changes were recovered through DNJ treatment. Our results are in

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accordance with previous reports which claim protective effects of DNJ on liver30.

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Multivariate Analysis by PCA and OPLS-DA

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Multivariate statistical analysis was used to analyze the metabolomic differences of

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urine of three mice groups. PCA is an unsupervised method to visualize metabolic

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differences between the groups. PCA was performed on the urine LC-MS data to

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identify the key metabolites regulated differently in CC, DMT and DM mice. As 14


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shown in Figure 4, PCA score plots of three groups mice based on positive (Figure

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4A) and negative ionization models (Figure 4B) demonstrated that DM group was

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clearly separated from other two group. The DMT group was closer to CC group.

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Some overlaps could be observed with CC group in negative ionization model

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(Figure 4B), which indicated that DNJ could strongly affect the metabolisms of

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db/db mice.

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Considering the overlaps between CC and DMT groups, OPLS-DA, a supervised

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pattern recognition method, was further used to maximize the separation among the

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groups and discriminate the different metabolites of three groups. The OPLS -DA

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score plots for both the positive and negative ion modes are shown in Figure 5. The

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data points of three groups in the OPLS-DA score plots are separate from each other

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in both positive (Figure 5 A, B, C) and negative (Figure 5 D, E, F) ion mode.

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Furthermore, the S plots from the OPLS-DA models were constructed to definite the

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metabolites responsible for the differentiation among three groups (Figure 6). To

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each S plots between two groups, the lower left quadrant represented the higher

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levels of metabolites in the left group related to the right group; correspondingly,

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those located in the higher right quadrant displayed the higher levels of metabolites

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in this group. The S plots from positive (Figure 6 A, B, C) and negative (Figure 6 D,

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E, F) demonstrated that there were some metabolic changes between two groups.

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Metabolites profiling through LC-MS and related pathway analysis

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In the present study, main metabolites, involved in the metabolism of sugars

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(glucose), organic acids, amino acids, fatty acids were identified from urine to 15



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discriminate the metabolic phenotype of T2DM db/db mice and listed in Table 1, 2

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and Figure 7.

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The high-resolution ESI-TOF-MS data for some metabolites are shown in

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supplemental Figure 4. As shown in Table 1 and 2, some metabolites significantly

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changed in the urine of DNJ treated db/db mice as compared to DM group (29 were

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decreased and 9 were increased) at p < 0.01 and p < 0.05. In particular, compared

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with CC group, 22 metabolites of DM group were found to be increased more than

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10% (Value of DM/CC＞1.10), four metabolites of DM group were observed to be

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relatively normal (1.10＞Value of DM/CC＞0.90) and 12 metabolites of DM group

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were observed to be decreased than 10% (Value of DM/CC＜0.900).

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In brief, the DNJ administration had positive effects on glucose, lipid and amino

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acid metabolism. The urinary metabolic profile of diabetic (DM) mice showed the

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higher concentrations of glucose, but much less Cis-aconitic acid content. Whereas,

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galactitol and glycerol-3 phosphate content increased, indicating that conversion of

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glucose into the tricarboxylic acid cycle process is blocked, partial conversion of

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glucose into sugar alcohol and glycerin which resulted into the high blood glucose.

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These alternations into glycolysis pathway led to abnormal energy and lipid

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metabolism, while the DNJ group (DMT) mice showed reduced glucose, galactose

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alcohol, glycerol -3 phosphate content but the cis- aconitic acid content increased

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significantly, indicating the positive effect of DNJ on glucose metabolism, energy

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metabolism and lipid metabolism. Our study showed that treatment with DNJ can

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restore the metabolic disturbance back to normal state. Previous studies have 16


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demonstrated a major concern for glycogen synthesis disorders in T2DM and also

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reported a significant reduction in liver glycogen content in insulin resistant animal

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models 34, 35. Besides, DNJ could also promote the conversion of phenylalanine to

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acetyl-CoA which finally enters TCA rather than the converting into

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phenylethylamine or phenylacetaldehyde and later two compounds accumulate in

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body as well as in urine. DNJ can reduce phenlyalanine purine metabolites and it can

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direct the conversion of glucose to pyruvate into one step as a raw material to start

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the TCA cycle 28.

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Subsequently, the urinary metabolic profile of DM mice have shown increased

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levels of many amino acid metabolites, such as phenylalanine metabolites, arginine

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metabolite argininosuccinate, a-ketobutyric acid. The DM mice have shown elevated

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tyrosine metabolism due to increased hordenine and acetoacetate. Due to the failure

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of glucose metabolism, the body lacked sufficient energy, which led to increased

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degradation of amino acids and fat degradation to male up the energy levels in

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diabetic mice.

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In the urine of DM group mice, the increased cholesterol metabolites

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(2-methoxyesterone-3phosphate and lombricine) indicating the strong fat

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metabolism of body. On the other hand, DNJ intervention could lower the content of

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these substances significantly, indicating that DNJ has also been adjusted for lipid

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metabolism. The current results revealed that the increased lipid metabolism in DM

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group may possibly be due to shift in energy metabolism from glucose to lipids. The

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diabetic dyslipidemia can be caused by the effects of the peripheral activities of 17



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insulin in muscle and adipose tissue.36, 37 Our results showed the increased amino acids metabolism in DM group and the

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significant difference was observed between DMT and DM (Table 1 and 2). Diabetes

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is known to cause an increase in several amino acids, which can improve insulin

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secretion by beta-cell lines and primary islet cells through various mechanisms. In

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DM mice, metabolism of these amino acids led to accumulation of hordenine or

351

acetoacetate which have no use in the body, whereas, DNJ could decrease this

352

abnormal tyrosine metabolism. From our results, it was concluded that DNJ may

353

also improve cholesterol and purine metabolism by down regulating the level of

354

2-methoxyesterone 3-sulfate and lombricine.

355

In summary, the treatment with DNJ increased the levels of TCA intermediates,

356

possibly indicating an increase in glycolysis and decrease in gluconeogenesis and,

357

thus, improvement of the TCA cycle 38-41. Therefore, the complications of T2DM

358

may arise due to the effects of this cycle on most of the metabolic pathways in the

359

mitochondria.42 Phenylalanine is an essential amino acid and the precursor for

360

tyrosine which exhibits a connection to T2DM. Therefore, it is reasonable to infer

361

that DNJ could impact the energy metabolism and consequently affects the

362

phenylalanine metabolism.19 Dyslipidemia in diabetes mellitus are characterized by a

363

high plasma triglyceride concentration, low HDL cholesterol concentration and

364

increased concentration of LDL-cholesterol particles which could eventually

365

increase the risk of cardiovascular diseases.37 In this study, the increased glycerol

366

level in DM group suggested an increase in lipid metabolism and energy metabolic 18


Page 18 of 39

Page 19 of 39


367

shift from glucose to lipids 25, 43, 44. In the previous studies, the urine and serum

368

creatinine levels in diabetic rats were lowered in comparison to CC which is

369

proportional to the low urine creatinine level in T2DM patients42, 45, 46. The levels of

370

amino acids (leucine, isoleucine, alanine and glutamate) in the urine of DM group

371

were also decreased, indicating an increase in protein metabolism through

372

gluconeogenesis, which is a common phenomenon in diabetic condition.25

373

The lipid, amino acid, glucose metabolism and other metabolic pathways in

374

T2DM db/db mice had different degrees of disorders and affects on each other which

375

are caused by the action of multi- factors. Therefore, T2DM pathogenesis research

376

should be integrated into variety of factors analysis, to obtain a more accurate

377

method for clinical diagnosis and treatment of T2DM. By analysis of these

378

metabolites, we could conclude that these metabolites were mainly related to glucose

379

metabolism and energy metabolism, lipid metabolism, amino acid metabolism and

380

other metabolic pathways.

381

Because of limited knowledge in this area, the biology of the remaining

382

biomarkers is still unclear and requires follow up studies. Of the total identified

383

metabolite associations, many are in pathways which play a role in diabetes,

384

including serine, phenylalanine and tyrosine metabolism, glycolysis pathway and

385

TCA cycle as well as nucleotide and pentose metabolism, thus linking them to

386

diabetes. Our results emphasize that the markers and associations of diabetes-related

387

metabolic perturbations, reported in Table 1, 2 and Figure 7 will contribute to the

388

growing understanding of metabolic changes associated with diabetes. Furthermore, 19



389

they will improve the functional understanding of the disease with a view of

390

developing new therapeutic approaches and diagnostic tools. The metabolomics

391

approach has allowed the separation of the DNJ treatment groups from the control

392

group, thus it can be used as a sensitive predictive tool. Though, the identification of

393

discriminating metabolites and the mechanistic underpinnings of their roles in DNJ

394

treatment are still critical.

395

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396

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556

index and dipsticks for detection of microproteinuria in diabetes mellitus patients. J.

557

Clin. Diagn. Res. 2013, 7, 622-626. 26


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558

Funding

559

This study was supported by the Major Projects of Science and Technology in Anhui

560

Province (15czz03115), the grants from the National Natural Science Foundation of

561

China (31371947 and 31272111), the Key projects of Natural Science Research of

562

Anhui Province (KJ2016A575) and the Special Fund for Agro-scientific Research in

563

the Public Interest of China (201403064).

564

Conflict of Interest: There is no conflict of interest to declare.

565

27



566

Figure captions

567

Figure 1. (A) Body weight, (B) Blood glucose and (C) insulin levels (D)

568

Homeostatic model assessment (HOMA) for insulin resistance (IR) in three groups

569

of mice at the end of the experiment. Comparison between CC, DM and DMT (DNJ

570

intervention) groups. The data are presented as the mean ± SEM (n=7). Statistical

571

analysis was performed using one-way ANOVA at P < 0.01 (superscript a, b, c) and

572

P < 0.05 (superscript A, B, C). FBG, fasting blood-glucose; 3h, represent the blood

573

glucose of 3h after eating foods.

574

Figure 2. Effect of DNJ treatment on (A) TC, (B) TG, (C) HDL, (D) LDL, (E), MDA,

575

(F) AGEs, (G) ALT, (H) BUN and (I) Cr levels in mice. Comparison between CC,

576

DM and DMT (DNJ intervention) groups. The data are presented as the mean ±

577

SEM (n=7). Statistical analysis was performed using one-way ANOVA at P < 0.01

578

(superscript a, b, c) and P < 0.05 (superscript A, B, C).

579

Figure 3. Effect of DNJ on hepatic pathological changes by using liver HE staining

580

methods. Comparison between CC, DM and DMT (DNJ intervention) groups.

581

Figure 4. Comparison of PCA score plots of three groups mice based on (A) positive

582

(B) and negative ionization models.

583

Figure 5. Comparison of OPLS-DA score plots of three groups of mice which were

584

separated from each other in both positive (A, B, C) and negative (D, E, F) ion

585

mode.

586

Figure 6. Comparison of S plots from the OPLS-DA models which were constructed

587

to definite the metabolites responsible for the differentiation among three groups.

28


Page 28 of 39

Page 29 of 39


588

The S plots from (A, B, C) positive and (D, E, F) negative demonstrated the

589

metabolic changes between two groups compared each time.

590

Figure 7. General biosynthetic pathways of some metabolites according to the

591

KEGG database. Red, yellow and blue corresponded to high, middle and low levels

592

of metabolites, respectively. The significantly changed metabolites were depicted by

593

different range of color from higher, middle to lower.

29



Page 30 of 39

Table 1 Effect of DNJ on significantly different urine metabolites putatively identified by HPLC-TOF-MS in positive mode. Mass

Molecular formula

Ionization mode

242.26 138.03 195.05 109.02 90.03 113.05 129.08

C16H34O C7H6O3 C9H9NO4 C2H7NO2S C3H6O3 C5H7NO2 C6H11NO2

ESI(+) ESI(+) ESI(+) ESI(+) ESI(+) ESI(+) ESI(+)

308.16

C17H24O5

ESI(+)

92.05 290.15 98.04 157.05

C3H8O3 C7H15O10P C6H10O C10H7NO

ESI(+) ESI(+) ESI(+) ESI(+)

Metabolite 16-Hexadecanol Gentisate aldehyde Dopaquinone Hypotaurine L-Glyceraldehyde L-1-Pyrroline-5-carboxylate pipecolic acid 15-acetoxy-12,13-epoxy9-trichothecene-3-ol glycerol D-Sedoheptulose 7-phosphate Cyclohexanone 1-Nitrosonaphthalene

DMT/CC

DM/CC

DMT/DM

Change*

0.22 0.36 0.31 0.50 0.56 1.30 0.33

1.03 1.07 0.73 1.10 1.00 1.16 0.22

0.21 0.34 0.42 0.45 0.56 1.12 1.49

↓ ↓ ↓ ↓ ↓ ↑ ↑

0.09

0.06

1.49

↑

1.69 1.69 1.69 1.10

1.14 1.14 1.14 0.40

1.49 1.49 1.49 2.78

↑ ↑ ↑ ↑

* The changes are shown in comparison to DMT and DM groups

30


Page 31 of 39


Table 2 Effect of DNJ on significantly different urine metabolites putatively identified by HPLC-TOF-MS in negative mode. Mass

Molecular formula

Ionization mode

Metabolite

DMT/CC DM/CC

DMT/DM

Change*

160.04

C6H8O5

ESI(−)

2,4-Diketo-3-deoxy-L-fuconate

0.04

1.39

0.03

↓

116

C4H4O4

ESI(−)

Fumarate

0.08

1.37

0.06

↓

173.08

C6H11N3O3

ESI(−)

2-Oxo-5-guanidino-pentanoate

9.09

21.91

0.41

↓

360.08

C18H16O8

ESI(−)

Rosmarinate

0.51

1.16

0.43

↓

270.12

C15H14N2O3

ESI(−)

10,11-Dihydroxycarbamazepine

0.38

0.86

0.44

↓

156.01

C5H4N2O4

ESI(−)

Orotate

0.74

1.30

0.56

↓

92.05

C3H8O3

ESI(−)

Glycerol

0.60

0.89

0.68

↓

165.12

C10H15NO

ESI(−)

Hordenine

1.14

1.61

0.70

↓

115.06

C5H9NO2

ESI(−)

Proline

0.75

1.04

0.71

↓

120.05

C8H8O

ESI(−)

Phenylacetaldehyde

5.26

7.21

0.73

↓

179.08

C6H13NO5

ESI(−)

D-Galactosamine

0.57

0.76

0.76

↓

135.05

C5H5N5

ESI(−)

Adenine

0.62

0.78

0.79

↓

172.15

C10H20O2

ESI(−)

Decanoic acid

1.19

1.44

0.83

↓

94.04

C6H6O

ESI(−)

Phenol

1.18

1.41

0.83

↓

102.03

C4H6O3

ESI(−)

Acetoacetate

1.16

1.38

0.84

↓

270.07

C6H15N4O6P

ESI(−)

Lombricine

1.19

1.39

0.85

↓

290.12

C10H18N4O6

ESI(−)

L-Argininosuccinate

1.22

1.40

0.87

↓

380.13

C19H24O6S

ESI(−)

2-Methoxyestrone 3-sulfate

1.82

2.09

0.87

↓

399.33

C23H45NO4

ESI(−)

L-Palmitoyl carnitine

1.23

1.41

0.88

↓

121.09

C8H11N

ESI(−)

Phenethylamine

1.25

1.41

0.88

↓

182.08

C6H14O6

ESI(−)

Galactitol

1.25

1.41

0.88

↓

172.01

C3H9O6P

ESI(−)

sn-Glycerol 3-phosphate

1.18

1.33

0.88

↓

139.06

C3H10NO3P

ESI(−)

2-Methylaminoethylphosphonate

0.43

0.49

0.88

↓

261.03

C10H16NO3PS

ESI(−)

Aminoparathion

0.31

0.35

0.88

↓

262.05

C6H15O9P

ESI(−)

Galactitol 1-phosphate

0.49

0.51

0.95

↓

174.02

C6H6O6

ESI(−)

cis-Aconitate

0.83

0.07

12.50

↑

* The changes are shown in comparison to DMT and DM groups.

31



Figure 1

32


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Figure 2

33



Figure 3

34


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Figure 4

35



Figure 5

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Figure 6

37



Figure 7

38


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Table of Contents Graphic (TOC)

39


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