Inhibition of stearoyl-CoA desaturase-1 in differentiating 3T3-L1 preadipocytes upregulates elongase 6 and downregulates genes affecting triacylglycerol synthesis.

BACKGROUND: Stearoyl-CoA desaturase-1 (SCD1) is rate limiting for the conversion of saturated fatty acids palmitate (16:0) and stearate (18:0) to monounsaturated fatty acids palmitoleate (16:1n7) and oleate (18:1n9), respectively. Given that reduced SCD1 activity is associated with improved insulin sensitivity and decreased body weight, there is considerable interest to elucidate the role of this enzyme in adipocytes. During adipogenesis, SCD1 levels increase concomitantly with the accumulation of triacylglycerol (TG); however, the extent to which reduced SCD1 activity can influence TG synthesis and metabolic pathways in differentiating adipocytes remains relatively unexplored. OBJECTIVE: The aim of this work was to delineate how reduced SCD1 activity affects gene expression, protein content and cellular fatty acids in differentiating murine preadipocytes. METHODS: 3T3-L1 preadipocytes were treated with an SCD1 inhibitor (10 nM) throughout differentiation. After 7 days, global gene expression, protein content and fatty acid profiles were examined using microarrays, western blotting and gas chromatography, respectively. RESULTS: SCD1 inhibition increased the abundance of 16:0 and 18:0 (45% and 194%, respectively) and decreased 16:1n7 and 18:1n7 (61% and 35%, respectively) in differentiated preadipocytes. Interestingly, 18:1n9 levels increased by 61%. The augmented 18:0 suggested a possible increase in elongase activity. Elongase 6 (Elovl6) gene expression was increased 2.8-fold (P = 0.04); however, changes were not detected for ELOVL6 protein content. Microarray analysis revealed that genes affecting TG synthesis were downregulated with SCD1 inhibition, which coincided with a 33% decrease in cellular TG content. CONCLUSION: These results provide new mechanistic insight into the role of SCD1 as a regulator of fatty acid profiles and TG synthesis in adipocytes, and reinforce that modulating SCD1 activity may help reduce the risk of obesity-related complications.

Unraveling the adipocyte inflammomodulatory pathways activated by North American ginseng.

BACKGROUND: North American (NA) ginseng (Panax quinquefolius) is a popular natural health product (NHP) that has been demonstrated to regulate immune function, inflammatory processes and response to stress and fatigue. Recent evidence suggests that various extracts of NA ginseng may have different bioactivities because of distinct profiles of ginsenosides and polysaccharides. To date, the bioactive role of ginseng on adipocytes remains relatively unexplored. OBJECTIVE: The goal of this work was to study the extract-specific bioactivity of NA ginseng on differentiated preadipocyte gene expression and adipocytokine secretion. METHODS: In vitro differentiated 3T3-L1 preadipocytes were treated with 25 and 50 µg ml of either crude ethanol (EtOH) or aqueous (AQ) NA ginseng extracts, or polysaccharide and ginsenoside extracts isolated from the AQ extract. Global gene expression was studied with microarrays and the resulting data were analyzed with functional pathway analysis. Adipocytokine secretion was also measured in media. RESULTS: Pathway analysis indicated that the AQ extract, and in particular the polysaccharide extract, triggered a global inflammomodulatory response in differentiated preadipocytes. Specifically, the expression of Il-6 (interleukin 6), Ccl5 (chemokine (C-C motif) ligand 5), Nfκb (nuclear factor-kappaB) and Tnfα (tumor necrosis factor alpha) was increased. These effects were also reflected at the protein level through the increased secretion of IL-6 and CCL5. No effect was seen with the EtOH extract or ginsenoside extract. Using a specific toll-like receptor 4 (TLR4) inhibitor reduced the upregulation of inflammatory gene expression, indicating the relevance of this pathway for the signaling capacity of NA ginseng polysaccharides. CONCLUSION: This work emphasizes the distinct bioactivities of different ginseng extracts on differentiated preadipocyte signaling pathways, and highlights the importance of TLR4 for mediating the inflammomodulatory role of ginseng polysaccharides.

Adipose tissue pathways involved in weight loss of cancer cachexia.

BACKGROUND: The regulatory gene pathways that accompany loss of adipose tissue in cancer cachexia are unknown and were explored using pangenomic transcriptome profiling. METHODS: Global gene expression profiles of abdominal subcutaneous adipose tissue were studied in gastrointestinal cancer patients with (n=13) or without (n=14) cachexia. RESULTS: Cachexia was accompanied by preferential loss of adipose tissue and decreased fat cell volume, but not number. Adipose tissue pathways regulating energy turnover were upregulated, whereas genes in pathways related to cell and tissue structure (cellular adhesion, extracellular matrix and actin cytoskeleton) were downregulated in cachectic patients. Transcriptional response elements for hepatic nuclear factor-4 (HNF4) were overrepresented in the promoters of extracellular matrix and adhesion molecule genes, and adipose HNF4 mRNA was downregulated in cachexia. CONCLUSIONS: Cancer cachexia is characterised by preferential loss of adipose tissue; muscle mass is less affected. Loss of adipose tissue is secondary to a decrease in adipocyte lipid content and associates with changes in the expression of genes that regulate energy turnover, cytoskeleton and extracellular matrix, which suggest high tissue remodelling. Changes in gene expression in cachexia are reciprocal to those observed in obesity, suggesting that regulation of fat mass at least partly corresponds to two sides of the same coin.

Using gene expression to predict the secretome of differentiating human preadipocytes.

OBJECTIVE: To characterize the secretome of differentiating human preadipocytes using global gene expression profiling. DESIGN: Gene expression was measured using microarrays at days 0, 1, 3, 5, 7 and 10 in primary preadipocytes undergoing adipogenesis (n=6 independent subjects). Predictive bioinformatic algorithms were employed to identify those differentially expressed genes that code for secreted proteins. MEASUREMENTS: Gene expression was assessed using microarrays and real-time reverse transcriptase PCR, bioinformatic predictive algorithms were used to identify the secretome of differentiating preadipocytes, and the secretion of the most significant candidates were confirmed at the protein level using western blots or ELISA tests. Gene expression was also assayed in the adipocyte and stroma vascular fraction (SVF) of obese subjects. RESULTS: Microarray analysis identified 33 genes whose expression significantly changed (false discovery rate of 1%) during adipogenesis and code for secreted proteins. Of these genes, 18 are novel candidate adipose tissue 'secretome' genes. Their relative gene expression in adipocyte and SVF of obese subjects revealed that most of these genes are more highly expressed in the SVF. A novel candidate, matrix gla protein (MGP), was upregulated (approximately 30-fold) during adipogenesis, second only to leptin (approximately 50-fold). MGP and another secretome candidate protein, inhibin beta B (INHBB), were detected in the secretion media of adipocytes isolated from adipose tissue explants. CONCLUSIONS: Gene expression coupled with predictive bioinformatic algorithms has proved a valid and alternative approach to further define the adipocyte secretome. Many of the novel candidate secretome genes are components of the coagulation and fibrinolytic systems. MGP and INHBB represent new adipokines whose function in adipose tissue remains to be unravelled.

Cathepsin S genotypes are associated with Apo-A1 and HDL-cholesterol in lean and obese French populations.

Cathepsin S (CTSS) is a cysteine protease that has a central role in remodeling the extracellular matrix and, as such, has been implicated in the etiology of cardiovascular disease. This study used five tag single nucleotide polymorphisms (tSNPs) to screen the CTSS gene in healthy lean (n = 1891) and obese French populations (n = 477) for their association with various phenotypes: body mass index, waist-to-hip ratio, glycemia, total cholesterol, triglycerides, high-density lipoprotein cholesterol (HDL-C), apolipoprotein A1 (Apo-A1) and apolipoprotein B. Significant associations were identified between rs11576175 tSNP (A/G) and Apo-A1 and HDL-C plasma levels in a sex-specific manner. Lean female subjects homozygous for the minor A-allele had higher levels of circulating Apo-A1 (p = 0.0003), while lean male A/A carriers had higher levels of HDL-C (p = 0.007) compared with the other genotypes. In the obese cohort, associations were found between three tSNPs and Apo-A1 levels in adult female subjects: rs10888390 (G/A), p = 0.01; rs10888394 (T/C), p = 0.03; and rs1136774 (C/T), p = 0.02; however, only rs10888390 remained significant in a combined model (p = 0.03). These results provide the first evidence that CTSS sequence variations are associated with two human metabolic risk factors for cardiovascular diseases: plasma Apo-A1 and HDL-C concentrations.

Genomics: food and nutrition.

Nutrition is traditionally a multidisciplinary field applying principles of molecular biochemistry and statistical epidemiology to integrative metabolism and population health. Genomics, with its global perspective, is now reinventing the future of human metabolic health. Creative experimental designs are addressing metabolic questions in nutrition ranging from energy regulation to aging, and from mechanisms of absorption to the interspecies molecular crosstalk of bacteria and human cells within the intestine.

Fatty acid-gene interactions, adipokines and obesity.

It is now recognized that the low-grade inflammation observed with obesity is associated with the development of a wide range of downstream complications. As such, there is considerable interest in elucidating the regulatory mechanisms underlying the production of inflammatory molecules to improve the prevention and treatment of obesity and its co-morbidities. White adipose tissue is no longer considered a passive reservoir for storing lipids, but rather an important organ influencing energy metabolism, insulin sensitivity and inflammation by the secretion of proteins, commonly referred to as adipokines. Dysregulation of several adipokines, such as tumor necrosis factor-alpha (TNF-α), interleukin-6 (IL-6) and adiponectin, contributes to the low-grade inflammation that is a hallmark of obesity. Evidence now suggests that fatty acids represent a class of molecules that can modulate adipokine production, thereby influencing inflammatory status. Although the precise molecular mechanisms by which dietary fats regulate adipokine production remain unclear, recent findings indicate that diet-gene interactions may have an important role in the transcriptional and secretory regulation of adipokines. Single-nucleotide polymorphisms in the genes encoding TNF-α, IL-6 and adiponectin can modify circulating levels of these adipokines and, subsequently, obesity-related phenotypes. This genetic variation can also alter the influence of dietary fatty acids on adipokine production. Therefore, the current review will show that it is paramount to consider both genetic information and dietary fat intake to unravel the inter-individual variability in inflammatory response observed in intervention protocols targeting obesity.

Microarray data analysis: a practical approach for selecting differentially expressed genes.

BACKGROUND: The biomedical community is rapidly developing new methods of data analysis for microarray experiments, with the goal of establishing new standards to objectively process the massive datasets produced from functional genomic experiments. Each microarray experiment measures thousands of genes simultaneously producing an unprecedented amount of biological information across increasingly numerous experiments; however, in general, only a very small percentage of the genes present on any given array are identified as differentially regulated. The challenge then is to process this information objectively and efficiently in order to obtain knowledge of the biological system under study and by which to compare information gained across multiple experiments. In this context, systematic and objective mathematical approaches, which are simple to apply across a large number of experimental designs, become fundamental to correctly handle the mass of data and to understand the true complexity of the biological systems under study. RESULTS: The present report develops a method of extracting differentially expressed genes across any number of experimental samples by first evaluating the maximum fold change (FC) across all experimental parameters and across the entire range of absolute expression levels. The model developed works by first evaluating the FC across the entire range of absolute expression levels in any number of experimental conditions. The selection of those genes within the top X% of highest FCs observed within absolute expression bins was evaluated both with and without the use of replicates. Lastly, the FC model was validated by both real time polymerase chain reaction (RT-PCR) and variance data. Semi-quantitative RT-PCR analysis demonstrated 73% concordance with the microarray data from Mu11K Affymetrix GeneChips. Furthermore, 94.1% of those genes selected by the 5% FC model were found to lie above measurement variability using a SDwithin confidence level of 99.9%. CONCLUSION: As evidenced by the high rate of validation, the FC model has the potential to minimize the number of required replicates in expensive microarray experiments by extracting information on gene expression patterns (e.g. characterizing biological and/or measurement variance) within an experiment. The simplicity of the overall process allows the analyst to easily select model limits which best describe the data. The genes selected by this process can be compared between experiments and are shown to objectively extract information which is biologically & statistically significant.