Effect of mitiglinide on Streptozotocin-induced experimental type 2 diabetic rats: A urinary metabonomics study based on ultra-performance liquid chromatography–tandem mass spectrometry

Metabolomics reveals the renoprotective effect of n-butanol extract and amygdalin extract from Amygdalus mongolica in rats with renal fibrosis

Renal fibrosis (RF) is a pathological process of progression from chronic kidney disease to end-stage renal disease. Amygdalus mongolica is a traditional Chinese medicine, and our previous studies demonstrated that the n-butanol extract (BUT) and amygdalin extract (AMY) from its seeds can prevent RF. However, the underlying mechanism remains unclear. The present study investigated the exact mechanism of the protective effect of A. mongolica on RF. A renal fibrosis rat model was induced with unilateral ureteral obstruction. Biochemical indicators were measured and combined with histopathology of renal tissue to evaluate the anti-RF effects. A serum metabonomic method was used to clarify the changes in the metabolic profile. The tubulointerstitial damage and fibrosis were significantly improved and metabolic perturbations were restored after treatment with BUT and AMY. Thirty-eight metabolites associated with RF progression and related to the regulation of arginine and proline metabolism, nicotinate and nicotinamide metabolism, and histidine metabolism were identified. They were restored to levels similar to those in controls after treatment. Moreover, no significant differences in efficacy were observed between the BUT and AMY groups. This study reveals and compares the potential mechanisms of the renoprotective effects after treatment with BUT and AMY from a metabolomic perspective.

The total flavonoids from Selaginella tamariscina (beauv.) Spring improve glucose and lipid metabolism in db/db mice

Objectives

This study aimed to investigate the glucose and lipid metabolism improving effect of the total flavonoids from Selaginella tamariscina (Beauv.) Spring (TFST) on db/db mice, and to study its mechanism of action.

Materials and Methods

The db/db mice were divided into 5 groups: the normal group (NC), the diabetic group (DM), the gliclazide group (GZ), the DM+TFST (110 mg/kg), and the DM+TFST (220 mg/kg). The body weight, blood glucose, INS, GC, TC, TG, LDL, and HDL were detected. HE staining was used to observe the liver and pancreas. Urine was tested by UPLC-QTOF-MS to study the metabolic differences of each group, coupled with SIMCA-P13.0 for PCA and OPLS-DA analysis, to identify potential biomarkers, find the metabolic pathway. Western blot was used to examine liver tissue of mice for studying effect of TFST on the PPAR-γ/PI3K/GLU4 pathway.

Results

TFST can reduce the weight and levels of TC, TG, and LDL-C, increase the level of GC in blood, and reduce the fat accumulation and inflammation in the liver, and repair the islet cell. 13 biomarkers were identified, they are mainly involved in amino acid metabolism, and purine and pyrimidine metabolism. The results of Western blot show TFST can improve the utilization rate of GLU4 by regulating PPAR-γ and PI3K expression in the liver of db/db mice.

Conclusion

TFST can improve glucose and lipid metabolism of DM, which relates to regulation of the PPAR-γ/PI3K/GLU4 signaling pathway, and affect the amino acid metabolism, purine, and pyrimidine metabolism.

Metabolic changes in rat urine after acute paraquat poisoning and discriminated by support vector machine

Paraquat is quick-acting and non-selective, killing green plant tissue on contact; it is also toxic to human beings and animals. In this study, we developed a urine metabonomic method by gas chromatography-mass spectrometry to evaluate the effect of acute paraquat poisoning on rats. Pattern recognition analysis, including both partial least squares discriminate analysis and principal component analysis revealed that acute paraquat poisoning induced metabolic perturbations. Compared with the control group, the levels of benzeneacetic acid and hexadecanoic acid of the acute paraquat poisoning group (intragastric administration 36 mg/kg) increased, while the levels of butanedioic acid, pentanedioic acid, altronic acid decreased. Based on these urinary metabolomics data, support vector machine was applied to discriminate the metabolomic change of paraquat groups from the control group, which achieved 100% classification accuracy. In conclusion, metabonomic method combined with support vector machine can be used as a useful diagnostic tool in paraquat-poisoned rats.

Host-guest Inclusion Complexes between Mitiglinide and the Naturally Occurring Cyclodextrins α, β, and γ: A Theoretical Approach

PURPOSE

The present study is aimed to study the host-guest inclusion complexation of the naturally occurring cyclodextrins (CDs), namely; (α-CD,β-CD, and γ-CD) with mitiglinide (MIT).

METHODS

Host-guest inclusion complexation was simulated using semi-empirical PM3 method.

RESULTS

The obtained results clearly indicate that the complexes formed are energetically favored in the presence of γ-CD (Ecomp = -17.884 kcal/mol) of the optimal configurations of (1:1) MIT/γ-CD inclusion complexes. Moreover, the results obtained reveal that the formation of more stable MIT/γ-CD complex compared to MIT/α-CD or MIT/β-CD complexes is primarily due to differences in intermolecular hydrogen bonding.

CONCLUSION

The present theoretical results may be informative to scientists who are devoting themselves to developing effective methods for enhancing the drug solubility.

Plasma metabolomic profiling of patients with diabetes-associated cognitive decline

Diabetes related cognitive dysfunction (DACD), one of the chronic complications of diabetes, seriously affect the quality of life in patients and increase family burden. Although the initial stage of DACD can lead to metabolic alterations or potential pathological changes, DACD is difficult to diagnose accurately. Moreover, the details of the molecular mechanism of DACD remain somewhat elusive. To understand the pathophysiological changes that underpin the development and progression of DACD, we carried out a global analysis of metabolic alterations in response to DACD. The metabolic alterations associated with DACD were first investigated in humans, using plasma metabonomics based on high-performance liquid chromatography coupled with quadrupole time-of-flight tandem mass spectrometry and multivariate statistical analysis. The related pathway of each metabolite of interest was searched in database online. The network diagrams were established KEGGSOAP software package. Receiver operating characteristic (ROC) analysis was used to evaluate diagnostic accuracy of metabolites. This is the first report of reliable biomarkers of DACD, which were identified using an integrated strategy. The identified biomarkers give new insights into the pathophysiological changes and molecular mechanisms of DACD. The disorders of sphingolipids metabolism, bile acids metabolism, and uric acid metabolism pathway were found in T2DM and DACD. On the other hand, differentially expressed plasma metabolites offer unique metabolic signatures for T2DM and DACD patients. These are potential biomarkers for disease monitoring and personalized medication complementary to the existing clinical modalities.

Urine bile acids relate to glucose control in patients with type 2 diabetes mellitus and a body mass index below 30 kg/m2

Bile acids are important endocrine signalling molecules, modulating glucose homeostasis through activation of cell surface and nuclear receptors. Bile acid metabolism is altered in type 2 diabetes mellitus; however, whether this is of pathogenic consequence is not fully established. In this study urinary bile acid excretion in individuals with type 2 diabetes and matched healthy volunteers was assessed. Urinary bile acid excretion in type 2 diabetes patients was considered in the context of prevailing glycaemia and the patient body mass index. Urine bile acids were measured by liquid chromatography-tandem mass spectrometry, allowing individual quantification of 15 bile acid species. Urinary bile acid excretion in patients with type 2 diabetes who were normal weight (BMI 18.5-24.9 kg/m2) and overweight (BMI 25-29.9 kg/m2) were elevated compared to healthy normal weight volunteers, both p<0.0001. In obese (BMI ≥ 30 kg/m2) type 2 diabetes patients, urinary bile acid excretion was significantly lower than in the normal and overweight type 2 diabetes groups (both p<0.01). Total bile acid excretion positively correlated with HbA1c in normal (rs=0.85, p=<0.001) and overweight (rs=0.61, p=0.02) but not obese type 2 diabetes patients (rs=-0.08, p=0.73). The glycaemia-associated increases in urine bile acid excretion in normal weight and overweight type 2 diabetes seen in this study may represent compensatory increases in bile acid signalling to maintain glucose homeostasis. As such alterations appear blunted by obesity; further investigation of weight-dependent effects of bile acid signalling on type 2 diabetes pathogenesis is warranted.

Biomolecular signatures of diabetic wound healing by structural mass spectrometry

Wound fluid is a complex biological sample containing byproducts associated with the wound repair process. Contemporary techniques, such as immunoblotting and enzyme immunoassays, require extensive sample manipulation and do not permit the simultaneous analysis of multiple classes of biomolecular species. Structural mass spectrometry, implemented as ion mobility-mass spectrometry (IM-MS), comprises two sequential, gas-phase dispersion techniques well suited for the study of complex biological samples because of its ability to separate and simultaneously analyze multiple classes of biomolecules. As a model of diabetic wound healing, poly(vinyl alcohol) sponges were inserted subcutaneously into nondiabetic (control) and streptozotocin-induced diabetic rats to elicit a granulation tissue response and to collect acute wound fluid. Sponges were harvested at days 2 or 5 to capture different stages of the early wound-healing process. Utilizing IM-MS, statistical analysis, and targeted ultraperformance liquid chromatography analysis, biomolecular signatures of diabetic wound healing have been identified. The protein S100-A8 was highly enriched in the wound fluids collected from day 2 diabetic rats. Lysophosphatidylcholine (20:4) and cholic acid also contributed significantly to the differences between diabetic and control groups. This report provides a generalized workflow for wound fluid analysis demonstrated with a diabetic rat model.

Effect of 20(S)-ginsenoside Rg3 on streptozotocin-induced experimental type 2 diabetic rats: a urinary metabonomics study by rapid-resolution liquid chromatography/mass spectrometry

RATIONALE

20(S)-ginsenoside Rg3 is an active component of Panax ginseng. It is known that 20(S)-ginsenoside Rg3 has a protective effect against hyperglycemia, obesity and diabetes in vivo, but the precise mechanisms of these actions have not yet been entirely elucidated.

METHODS

A urinary metabonomics method based on rapid-resolution liquid chromatography/mass spectrometry (RRLC/MS) was developed to investigate the effect of 20(S)-ginsenoside Rg3 on type 2 diabetic rats.

RESULTS

With multivariate statistical analysis, a clear separation between type 2 diabetic rats and those treated with 20(S)-ginsenoside Rg3 was achieved. Six potential biomarkers were found and identified.

CONCLUSIONS

This work shows that the mechanism of the effect of 20(S)-ginsenoside Rg3 on type 2 diabetes may be involved with the regulation of nucleic acid metabolism, energy metabolism and gut flora metabolism.

Urinary metabonomics characterization of liver fibrosis induced by CCl₄ in rats and intervention effects of Xia Yu Xue Decoction

Xia Yu Xue Decoction (XYXD) is a traditional Chinese medicine which has been widely used in clinic practice for treating liver disease. However, its mechanism of action remains unknown. In this study, a urinary metabonomic method, based on gas chromatography coupled with mass spectrometry (GC/MS), was developed to investigate the effect of XYXD on liver fibrosis. Pattern recognition analysis, including principal component analysis (PCA) and partial least square discriminant analysis (PLS-DA), showed that metabolic perturbations induced by CCl(4) were restored after treatment with XYXD. Ten potential biomarkers associated with modulation of energy metabolism, microflora metabolism, amino acid and fatty acid metabolism were identified, suggesting that the mechanism of action of XYXD may involve these processes. Our findings indicate that metabonomic methods based on GC/MS may provide a useful means of exploring biomarkers involved in liver fibrosis and for elucidating the mechanisms of action of therapies used in traditional Chinese medicine.

Effect of ginseng polysaccharide on the urinary excretion of type 2 diabetic rats studied by liquid chromatography-mass spectrometry

Ginseng polysaccharide is known to have anti-hyperglycemic and anti-hyperlipidemic effects in vivo and its precise mechanism of action is not clear. A urinary metabolomics method based on rapid-resolution liquid chromatography/mass spectrometry (RRLC/MS) was developed to investigate the effect of water-soluble ginseng polysaccharide (WGP) on type 2 diabetes in rats. Principal component analysis (PCA) was carried out for pattern recognition and a clear separation between type 2 diabetic rats and those treated with WGP was achieved. Eight potential biomarkers were found and identified. Significantly increased inosine, serotonin, phenylpropionylglycine and dodecanedioic acid showed the effect of WGP on purine metabolism, tryptophan metabolism, fatty acid metabolism and energy metabolism. 1-Methyladenine, 4-deoxyerythronic acid, 5-hydroxyhexanoic acid and tetrahydrocortisol were significantly decreased which indicated that WGP can regulate DNA metabolism, organic acids metabolism and steroid hormone metabolism. This work is helpful in the effect mechanism study of ginseng polysaccharide.

Urine metabolomics combined with the personalized diagnosis guided by Chinese medicine reveals subtypes of pre-diabetes

The prevalence of type 2 diabetes continuously increases globally. A personalized strategy applied in the pre-diabetic stage is vital for diabetic prevention and management. The personalized diagnosis of Chinese Medicine (CM) may help to stratify the diabetics. Metabolomics is regarded as a potential platform to provide biomarkers for disease-subtypes. We designed an explorative study of 50 pre-diabetic males, combining GC-MS urine metabolomics with CM diagnosis in order to identify diagnostic biomarkers for pre-diabetic subtypes. Three CM physicians reached 85% diagnosis consistency resulting in the classification of 3 pre-diabetic groups. The urine metabolic patterns of groups 1 'Qi-Yin deficiency' and 2 'Qi-Yin deficiency with dampness' (subtype A) and group 3 'Qi-Yin deficiency with stagnation' (subtype B) were clearly discriminated. The majority of metabolites (51%), mainly sugars and amino acids, showed higher urine levels in subtype B compared with subtype A. This indicated more disturbances of carbohydrate metabolism and renal function in subtype B compared with subtype A. No differences were found for hematological and biochemical parameters except for levels of glucose and γ-glutamyltransferase that were significantly higher in subtype B compared with subtype A. This study proved that combining metabolomics with CM diagnosis can reveal metabolic signatures for pre-diabetic subtypes. The identified urinary metabolites may be of special clinical relevance for non-invasive screening for subtypes of pre-diabetes, which could lead to an improvement in personalized interventions for diabetics.

A metabolomic study of low estimated GFR in non-proteinuric type 2 diabetes mellitus

AIMS/HYPOTHESIS

We carried out a urinary metabolomic study to gain insight into low estimated GFR (eGFR) in patients with non-proteinuric type 2 diabetes.

METHODS

Patients were identified as being non-proteinuric using multiple urinalyses. Cases (n = 44) with low eGFR and controls (n = 46) had eGFR values <60 and ≥60 ml min(-1) 1.73 m(-2), respectively, as calculated using the Modification of Diet in Renal Disease formula. Urine samples were analysed by liquid chromatography/mass spectrometry (LC/MS) and GC/MS. False discovery rates were used to adjust for multiple hypotheses testing, and selection of metabolites that best predicted low eGFR status was achieved using least absolute shrinkage and selection operator logistic regression.

RESULTS

Eleven GC/MS metabolites were strongly associated with low eGFR after correction for multiple hypotheses testing (smallest adjusted p value = 2.62 × 10(-14), largest adjusted p value = 3.84 × 10(-2)). In regression analysis, octanol, oxalic acid, phosphoric acid, benzamide, creatinine, 3,5-dimethoxymandelic amide and N-acetylglutamine were selected as the best subset for prediction and allowed excellent classification of low eGFR (AUC = 0.996). In LC/MS, 19 metabolites remained significant after multiple hypotheses testing had been taken into account (smallest adjusted p value = 2.04 × 10(-4), largest adjusted p value = 4.48 × 10(-2)), and several metabolites showed stronger evidence of association relative to the uraemic toxin, indoxyl sulphate (adjusted p value = 3.03 × 10(-2)). The potential effect of confounding on the association between metabolites was excluded.

CONCLUSIONS/INTERPRETATION

Our study has yielded substantial new insight into low eGFR and provided a collection of potential urinary biomarkers for its detection.

A metabonomic analysis of urine from rats treated with rhizoma alismatis using ultra-performance liquid chromatography/mass spectrometry

A metabonomic approach based on ultra-performance liquid chromatography coupled to mass spectrometry (UPLC/MS) was used to study the nephrotoxicity of rhizoma alismatis (RA) in rats. Potential biomarkers of RA toxicity were identified and the toxicological mechanism is discussed. Urine samples were collected from control and treated rats at various stages and analyzed by UPLC/MS in positive ionization mode. Histopathological analysis was used to evaluate renal function. The differences in the metabolic profiles of the control and treated rats were clearly distinguishable with principal components analysis (PCA) of the chromatographic data, and significant changes in 13 metabolite biomarkers were detected in the urine. This metabonomic method combined with PCA could discriminate the treated rats from the control rats on days 60, 120, and 180 after treatment, before serious organic renal damage was apparent on day 180 with histopathology. This research indicates that UPLC/MS-based metabonomic analysis of urine samples can be used to predict the chronic nephrotoxicity induced by rhizoma alismatis.