Microarray gene expression profiling in obesity and insulin resistance

Gut Microbiome and Metabolome Profiles Associated with High-Fat Diet in Mice

Obesity can be caused by microbes producing metabolites; it is thus important to determine the correlation between gut microbes and metabolites. This study aimed to identify gut microbiota-metabolomic signatures that change with a high-fat diet and understand the underlying mechanisms. To investigate the profiles of the gut microbiota and metabolites that changed after a 60% fat diet for 8 weeks, 16S rRNA gene amplicon sequencing and gas chromatography-mass spectrometry (GC-MS)-based metabolomic analyses were performed. Mice belonging to the HFD group showed a significant decrease in the relative abundance of Bacteroidetes but an increase in the relative abundance of Firmicutes compared to the control group. The relative abundance of Firmicutes, such as Lactococcus, Blautia, Lachnoclostridium, Oscillibacter, Ruminiclostridium, Harryflintia, Lactobacillus, Oscillospira, and Erysipelatoclostridium, was significantly higher in the HFD group than in the control group. The increased relative abundance of Firmicutes in the HFD group was positively correlated with fecal ribose, hypoxanthine, fructose, glycolic acid, ornithine, serum inositol, tyrosine, and glycine. Metabolic pathways affected by a high fat diet on serum were involved in aminoacyl-tRNA biosynthesis, glycine, serine and threonine metabolism, cysteine and methionine metabolism, glyoxylate and dicarboxylate metabolism, and phenylalanine, tyrosine, and trypto-phan biosynthesis. This study provides insight into the dysbiosis of gut microbiota and metabolites altered by HFD and may help to understand the mechanisms underlying obesity mediated by gut microbiota.

Diet-induced obesity is associated with altered expression of sperm motility-related genes and testicular post-translational modifications in a mouse model

Obesity is a metabolic disease and its relation with male subfertility has aroused a growing concern. However, it is unclear whether gene expression and post-translational modifications (PTMs), two vital molecular mechanisms regulating cellular functions, are associated with obesity-induced male reproductive dysfunction. In this study, male obesity with compromised sperm motility was induced by a high-fat diet (HFD) using a mouse model. The expression of motility related-genes, the level of histone modifications, and the global profiles of post-translational modifications (PTMs), were examined in testes of HFD and control mice by quantitative real-time PCR and western blot, respectively. Outer dense fiber protein 2, a major component of outer dense fibers in the sperm tail, is the most obviously down-regulated gene out of 11 evaluated genes, showing a reduction of about 50% RNA level in testes of obese male mice compared with that in control mice. Semi-quantitative analysis of the western blot demonstrated that ∼56% enrichment of di-methylated histone (H)3 lysine (K)36, ∼59% enrichment of 2-hydroxyisobutyrylated H4K8, ∼32% decrease of propionylated H3K23, ∼33% decrease of crotonylated H4K8, and ∼45% decrease of acetylated H3K122 and H4K8 were detected in testes of male HFD mice compared with that in control mice. In addition, male obesity up-regulated the testicular levels of ubiquitination by ∼18%, tyrosine nitration by ∼20%, lysine succinylation by ∼25%, lysine benzoylation by ∼28%, lysine malonylation by ∼32%, lysine glutarylation by ∼36%, lysine propionylation by ∼42%, lysine 2-hydroxyisobutyrylation by ∼45%, and SUMO1 modification by ∼59%, and down-regulated the testicular levels of O-GlcNAcylation by ∼12%, lysine crotonylation by ∼22%, and lysine acetylation by 35%. These findings indicate that altered gene expression and PTMs are associated with the obesity-induced male reproductive dysfunction.

Cynometra cauliflora Linn. Attenuates metabolic abnormalities in high-fat diet-induced obese mice

ETHNOPHARMACOLOGICAL RELEVANCE

Cynometra cauliflora Linn. belongs to the Fabaceae family and is known locally in Malaysia as nam-nam. Traditionally, a decoction of the C. cauliflora leaves is used for treating hyperlipidemia and diabetes.

AIM OF THE STUDY

This study aims to investigate the anti-obesity and lipid lowering effects of ethanolic extract of C. cauliflora leaves and its major compound (vitexin) in C57BL/6 obese mice induced by high-fat diet (HFD), as well as to further identify the molecular mechanism underlying this action.

METHODS AND MATERIAL

Male C57BL/6 mice were fed with HFD (60% fat) for 16 weeks to become obese. The treatment started during the last 8 weeks of HFD feeding and the obese mice were treated with C. cauliflora leaf extract at 200 and 400 mg/kg/day, orlistat (10 mg/kg) and vitexin (10 mg/kg).

RESULTS

The oral administration of C. cauliflora (400 and 200 mg/kg) and vitexin significantly reduced body weight, adipose tissue and liver weight and lipid accumulation in the liver compared to control HFD group. Both doses of C. cauliflora also significantly (P ≤ 0.05) decreased serum triglyceride, LDL, lipase, IL-6, peptide YY, resistin levels, hyperglycemia, hyperinsulinemia, and hyperleptinemia compared to the control HFD group. Moreover, C. cauliflora significantly up-regulated the expression of adiponectin, Glut4, Mtor, IRS-1 and InsR genes, and significantly decreased the expression of Lepr in white adipose tissue. Furthermore, C. cauliflora significantly up-regulated the expression of hypothalamus Glut4, Mtor and NF-kB genes. GC-MS analysis of C. cauliflora leaves detected the presence of phytol, vitamin E and β-sitosterol. Besides, the phytochemical evaluation of C. cauliflora leaves showed the presence of flavonoid, saponin and phenolic compounds.

CONCLUSION

This study shows interesting outcomes of C. cauliflora against HFD-induced obesity and associated metabolic abnormalities. Therefore, the C. cauliflora extract could be a potentially effective agent for obesity management and its related metabolic disorders such as insulin resistance and hyperlipidemia.

Serum circulating microRNA profiling for identification of potential type 2 diabetes and obesity biomarkers

Background and Aim

MicroRNAs are small non-coding RNAs that play important regulatory roles in a variety of biological processes, including complex metabolic processes, such as energy and lipid metabolism, which have been studied in the context of diabetes and obesity. Some particular microRNAs have recently been demonstrated to abundantly and stably exist in serum and to be potentially disease-specific. The aim of this profiling study was to characterize the expression of miRNA in serum samples of obese, nonobese diabetic and obese diabetic individuals to determine whether miRNA expression was deregulated in these serum samples and to identify whether any observed deregulation was specific to either obesity or diabetes or obesity with diabetes.

Patients and Methods

Thirteen patients with type 2 diabetes, 20 obese patients, 16 obese patients with type 2 diabetes and 20 healthy controls were selected for this study. MiRNA PCR panels were employed to screen serum levels of 739 miRNAs in pooled samples from these four groups. We compared the levels of circulating miRNAs between serum pools of each group. Individual validation of the twelve microRNAs selected as promising biomarkers was carried out using RT-qPCR.

Results

Three serum microRNAs, miR-138, miR-15b and miR-376a, were found to have potential as predictive biomarkers in obesity. Use of miR-138 or miR-376a provides a powerful predictive tool for distinguishing obese patients from normal healthy controls, diabetic patients, and obese diabetic patients. In addition, the combination of miR-503 and miR-138 can distinguish diabetic from obese diabetic patients.

Conclusion

This study is the first to show a panel of serum miRNAs for obesity, and compare them with miRNAs identified in serum for diabetes and obesity with diabetes. Our results support the use of some miRNAs extracted from serum samples as potential predictive tools for obesity and type 2 diabetes.

Investigating potential mechanisms of obesity by metabolomics

Obesity is a serious health problem with an increased risk of several common diseases including diabetes, cardiovascular disease, and cancer. Metabolomics is an emerging analytical technique for systemic determination of metabolite profiles, which is useful for understanding the biochemical changes in obesity or related diseases both in individual organs and at the organism level. Increasingly, this technology has been applied to the study of obesity, complementing transcriptomics and/or proteomics analyses. Indeed, the alterations of metabolites in biofluids/tissues are direct indicators of variations in physiology or pathology. In this paper, we will examine the obesity-related alterations in significant metabolites that have been identified by metabolomics as well as their metabolic pathway associations. Issues concerning the screening of biologically significant metabolites related to obesity will also be discussed.

Unconventional microarray design reveals the response to obesity is largely tissue specific: analysis of common and divergent responses to diet-induced obesity in insulin-sensitive tissues

Obesity is a chronic condition involving the excessive accumulation of adipose tissue that adversely affects all systems in the body. The aim of the present study was to employ an unbiased, genome-wide assessment of transcript abundance in order to identify common gene expression pathways within insulin-sensitive tissues in response to dietary-induced diabetes. Following 20 weeks of chow or high-fat feeding (60% kcal), age-matched mice underwent a euglycemic-hyperinsulinemic clamp to assess insulin sensitivity. High-fat-fed animals were obese and highly insulin resistant, disposing of ∼75% less glucose compared with their chow-fed counterparts. Tissues were collected, and gene expression was examined by microarray in 4 tissues known to exhibit obesity-related metabolic disturbances: white adipose tissue, skeletal muscle, liver, and heart. A total of 463 genes were differentially expressed between diets. Analysis of individual tissues showed skeletal muscle to exhibit the largest number of differentially expressed genes (191) in response to high-fat feeding, followed by adipose tissue (169), liver (115), and heart (65). Analyses revealed that the response of individual genes to obesity is distinct and largely tissue specific, with less than 10% of transcripts being shared among tissues. Although transcripts are largely tissue specific, a systems approach shows numerous commonly activated pathways, including those involved in signal transduction, inflammation, oxidative stress, substrate transport, and metabolism. This suggests a coordinated attempt by tissues to limit metabolic perturbations occurring in early-stage obesity. Many identified genes were associated with a variety of disorders, thereby serving as potential links between obesity and its related health risks.

Microarray evidences the role of pathologic adipose tissue in insulin resistance and their clinical implications

Clustering of insulin resistance and dysmetabolism with obesity is attributed to pathologic adipose tissue. The morphologic hallmarks of this pathology are adipocye hypertrophy and heightened inflammation. However, it's underlying molecular mechanisms remains unknown. Study of gene function in metabolically active tissues like adipose tissue, skeletal muscle and liver is a promising strategy. Microarray is a powerful technique of assessment of gene function by measuring transcription of large number of genes in an array. This technique has several potential applications in understanding pathologic adipose tissue. They are: (1) transcriptomic differences between various depots of adipose tissue, adipose tissue from obese versus lean individuals, high insulin resistant versus low insulin resistance, brown versus white adipose tissue, (2) transcriptomic profiles of various stages of adipogenesis, (3) effect of diet, cytokines, adipokines, hormones, environmental toxins and drugs on transcriptomic profiles, (4) influence of adipokines on transcriptomic profiles in skeletal muscle, hepatocyte, adipose tissue etc., and (5) genetics of gene expression. The microarray evidences of molecular basis of obesity and insulin resistance are presented here. Despite the limitations, microarray has potential clinical applications in finding new molecular targets for treatment of insulin resistance and classification of adipose tissue based on future risk of insulin resistance syndrome.

Insulin resistance at the crossroads of metabolic syndrome: systemic analysis using microarrays

Recently, it has been suggested that insulin resistance is a better predictor of metabolic syndrome than obesity. Numerous studies have been conducted to identify insulin resistance susceptibility genes in various model systems. This review focuses on recent findings in microarray analyses, which have indicated that (i) in the liver, genes involved in lipid synthesis and gluconeogenesis are increased in an animal model of insulin resistance that leads into liver steatosis and hyperglycemia; (ii) in adipose tissues, genes involved in fatty acid synthesis and adipogenesis are down-regulated both in insulin-resistant humans and in animals; and (iii) in muscle, overall gene expression, including genes involved in fatty acid oxidation and biosynthesis, is either decreased or unresponsive compared to that of insulin-sensitive control human subjects or animals. Considering the multifaceted effects of insulin resistance in various tissues, aiming at multi-targets rather than a single target will be a more promising strategy for the prevention or treatment of insulin resistance.

Proteomic analysis of human adipose tissue after rosiglitazone treatment shows coordinated changes to promote glucose uptake

The aim of this study was to identify potential protein targets for insulin sensitization in human adipose tissue using unbiased proteomic approaches. Ten moderately obese, but otherwise healthy, subjects were treated with rosiglitazone 4 mg b.i.d. for 14 days and global protein and gene expression changes were monitored. Proteomic analysis revealed distinct up- or downregulation (greater than twofold) in 187 protein spots on the two-dimensional (2-D) gel images between day 0 and day 1 adipose tissue samples. When comparing the protein spots on the gels from day 0 with that of 14-day-treated samples, 122 spots showed differential expression. There was a striking increase in the expression of proteins involved in glucose transporter-4 (GLUT4) granule transport and fusion (actin, myosin-9, tubulin, vimentin, annexins, moesin, LIM, and SH3 domain protein-1), signaling (calmodulin, guanine nucleotide-binding proteins), redox regulation (superoxide dismutase, catalase, ferritin, transferrin, heat shock proteins), and adipogenesis (collagens, galectin-1, nidogen-1, laminin, lamin A/C). However, there was an intriguing absence of correlated changes in mRNA expression, suggesting adaptation at a post-transcriptional level in response to rosiglitazone. Thus, the major changes observed were among proteins involved in cytoskeletal rearrangement, insulin and calcium signaling, and inflammatory and redox signals that decisively upregulate GLUT4 granule trafficking in human adipose tissue. Such orchestrated changes in expression of multiple proteins provide insights into the mechanism underlying the increased efficiency in glucose uptake and improvement of insulin sensitivity in response to rosiglitazone treatment.

Application of DNA microarray to the study of human adipose tissue/cells

Adipose tissue is increasingly recognized as a metabolically active endocrine organ with multiple functions beyond its lipid storage capability. Various constituents of the tissue, such as mature adipocytes and stromal vascular cells, have distinct functions. For example, they express and secrete different kinds of bioactive molecules collectively called adipokines. Altered adipokine secretion patterns characterize obesity and insulin resistance, which are major risk factors for type 2 diabetes mellitus. The contribution of dysregulated adipokine expression to these diseases may be assembled from transcriptomic profiles of the tissue and/or its cellular constituents. The gene expression profiles may also complement genetic approaches to identify disease susceptibility genes. Here, we describe an application of gene expression profiling using DNA microarrays to study human adipose tissue, adipocytes, and stromal vascular cells.

OMICS-driven biomarker discovery in nutrition and health

While traditional nutrition research has dealt with providing nutrients to nourish populations, it nowadays focuses on improving health of individuals through diet. Modern nutritional research is aiming at health promotion and disease prevention and on performance improvement. As a consequence of these ambitious objectives, the disciplines "nutrigenetics" and "nutrigenomics" have evolved. Nutrigenetics asks the question how individual genetic disposition, manifesting as single nucleotide polymorphisms, copy-number polymorphisms and epigenetic phenomena, affects susceptibility to diet. Nutrigenomics addresses the inverse relationship, that is how diet influences gene transcription, protein expression and metabolism. A major methodological challenge and first pre-requisite of nutrigenomics is integrating genomics (gene analysis), transcriptomics (gene expression analysis), proteomics (protein expression analysis) and metabonomics (metabolite profiling) to define a "healthy" phenotype. The long-term deliverable of nutrigenomics is personalised nutrition for maintenance of individual health and prevention of disease. Transcriptomics serves to put proteomic and metabolomic markers into a larger biological perspective and is suitable for a first "round of discovery" in regulatory networks. Metabonomics is a diagnostic tool for metabolic classification of individuals. The great asset of this platform is the quantitative, non-invasive analysis of easily accessible human body fluids like urine, blood and saliva. This feature also holds true to some extent for proteomics, with the constraint that proteomics is more complex in terms of absolute number, chemical properties and dynamic range of compounds present. Apart from addressing the most complex "-ome", proteomics represents the only platform that delivers not only markers for disposition and efficacy but also targets of intervention. The Omics disciplines applied in the context of nutrition and health have the potential to deliver biomarkers for health and comfort, reveal early indicators for disease disposition, assist in differentiating dietary responders from non-responders, and, last but not least, discover bioactive, beneficial food components. This paper reviews the state-of-the-art of the three Omics platforms, discusses their implication in nutrigenomics and elaborates on applications in nutrition and health such as digestive health, allergy, diabetes and obesity, nutritional intervention and nutrient bioavailability. Proteomic developments, applications and potential in the field of nutrition have been specifically addressed in another review issued by our group.

Insulin Resistance Does Not Influence Gene Expression in Skeletal Muscle

Insulin resistance is commonly observed in patients prior to the development of type 2 diabetes and may predict the onset of the disease. We tested the hypothesis that impairment in insulin stimulated glucose-disposal in insulin resistant patients would be reflected in the gene expression profile of skeletal muscle. We performed gene expression profiling on skeletal muscle of insulin resistant and insulin sensitive subjects using microarrays. Microarray analysis of 19,000 genes in skeletal muscle did not display a significant difference between insulin resistant and insulin sensitive muscle. This was confirmed with real-time PCR. Our results suggest that insulin resistance is not reflected by changes in the gene expression profile in skeletal muscle.

Microarray technology in the study of obesity and non-alcoholic fatty liver disease

The recent development of high-throughput gene expression technology permits simultaneous investigation of thousands of genes, providing a snapshot of the transcription state of diseased tissue. Microarray-based expression profiling is well suited to investigate the molecular basis of complex diseases such as obesity and chronic liver disease. With the help of microarray technology, functional genomics will surely advance our understanding of these diseases, and lead to more effective, targeted interventions that lack the toxicity of many conventional treatments. Despite their tremendous potential, microarray studies are subject to potential flaws in experimental design, experimental techniques, data analysis, and data interpretation. Besides the technical issues, the most important challenge is to develop integrative databases that combine gene expression data with the clinical data. Over the next few years, advances in technology and refinements in study design and data analysis will make clinically relevant translational research even more engaging and productive.

Diabetes mellitus in a domesticated Spanish Mustang

An 18-year-old Spanish Mustang mare was referred for evaluation of progressive weight loss and persistent hyperglycemia. Clinicopathologic abnormalities included marked hyperglycemia and glycosuria. Serum cortisol concentration was appropriately decreased following administration of dexamethasone, indicating that the horse did not have pituitary pars intermedia dysfunction. Serum insulin and plasma C-peptide concentrations were low, suggesting that hyperglycemia was a result of decreased secretion of insulin by pancreatic beta cells. In addition, glucose concentration did not return to the baseline concentration until 5 hours after i.v. administration of a glucose bolus, suggesting that insulin secretion, insulin effect, or both were reduced. However, i.v. administration of insulin caused only a slight decrease in the plasma glucose concentration, giving the impression that the action of insulin was impaired. Within 5 hours after administration of a combination of glyburide and metformin, which is used to treat diabetes mellitus in humans, the glucose concentration was within reference limits. The horse was euthanized, and a postmortem examination was done. Immunohistochemical staining of sections of the pancreas revealed attenuation of the pancreatic islet beta-cell population, with beta cells that remained generally limited to the periphery of the islets. These findings indicate that, albeit rare, pancreatic beta-cell failure may contribute to the development of diabetes mellitus in horses.