Torreya nucifera seed oil improves 3T3-L1 adipocyte differentiation.

BACKGROUND: Adipose tissue is a critical regulator of lipid storage and endocrine function. Impairment of the recruitment of new adipocytes in the adipose tissue is associated with ectopic fat accumulation, diabetes and insulin resistance. Torreya nucifera, an evergreen conifer that grows in warm temperate climates, has been found to exert beneficial effects against inflammation, infection and diabetes. However, the molecular mechanisms responsible for these effects at the cellular level remain unknown. This study aimed to investigate effects of Torreya nucifera seed oil (TNSO) on 3T3-L1 adipocyte differentiation and its underlying regulatory mechanism. METHODS: To investigate the effects of TNSO on adipocyte differentiation, 3T3-L1 cells were induced to differentiate for 5 days in the presence of 0.75 µL/mL TNSO. Oil Red O staining and an assay for intracellular triglyceride were performed to determine the extent of lipid accumulation in 3T3-L1 cells. To elucidate the underlying mechanism of TNSO, adipogenic gene expression was analyzed using quantitative real-time PCR. Moreover, we monitored TNSO-derived activation of PPARγ and STAT3 with 3T3-L1 reporter cell lines engineered to secrete Gaussia luciferase upon the interaction of a transcription factor to its DNA binding element. RESULTS: Oil Red O staining revealed that TNSO improved the differentiation of 3T3-L1 preadipocytes into mature adipocytes. The mRNA levels of adipogenic genes, including adiponectin, fatty acid synthase (FAS) and adipocyte fatty acid-binding protein (FABP4), were upregulated and intracellular triglyceride levels increased upon TNSO treatment. We also established that adipocyte differentiation was improved by TNSO-derived activation of PPARγ and STAT3. CONCLUSIONS: Our results suggest that TNSO improves adipocyte differentiation by regulating the activation of adipogenic transcription factors, indicating that it may serve as a potential treatment strategy for adipocyte dysfunction.

MODELING INTER-KINGDOM REGULATION OF INFLAMMATORY SIGNALING IN HUMAN INTESTINAL EPITHELIAL CELLS.

The human gastrointestinal (GI) tract is colonized by a highly diverse and complex microbial community (i.e., microbiota). The microbiota plays an important role in the development of the immune system, specifically mediating inflammatory responses, however the exact mechanisms are poorly understood. We have developed a mathematical model describing the effect of indole on host inflammatory signaling in HCT-8 human intestinal epithelial cells. In this model, indole modulates transcription factor nuclear factor κ B (NF-κB) and produces the chemokine interleukin-8 (IL-8) through the activation of the aryl hydrocarbon receptor (AhR). Phosphorylated NF-κB exhibits dose and time-dependent responses to indole concentrations and IL-8 production shows a significant down-regulation for 0.1 ng/mL TNF-α stimulation. The model shows agreeable simulation results with the experimental data for IL-8 secretion and normalized NF-κB values. Our results suggest that microbial metabolites such as indole can modulate inflammatory signaling in HTC-8 cells through receptor-mediated processes.

Cofactor Regeneration Using Permeabilized Escherichia coli Expressing NAD(P)+-Dependent Glycerol-3-Phosphate Dehydrogenase.

Oxidoreductases are effective biocatalysts, but their practical use is limited by the need for large quantities of NAD(P)H. In this study, a whole-cell biocatalyst for NAD(P)H cofactor regeneration was developed using the economical substrate glycerol. This cofactor regeneration system employs permeabilized Escherichia coli cells in which the glpD and gldA genes were deleted and the gpsA gene, which encodes NAD(P)+-dependent glycerol-3-phosphate dehydrogenase, was overexpressed. These manipulations were applied to block a side reaction (i.e., the conversion of glycerol to dihydroxyacetone) and to switch the glpD-encoding enzyme reaction to a gpsA-encoding enzyme reaction that generates both NADH and NADPH. We demonstrated the performance of the cofactor regeneration system using a lactate dehydrogenase reaction as a coupling reaction model. The developed biocatalyst involves an economical substrate, bifunctional regeneration of NAD(P)H, and simple reaction conditions as well as a stable environment for enzymes, and is thus applicable to a variety of oxidoreductase reactions requiring NAD(P)H regeneration.

Prediction and quantification of bioactive microbiota metabolites in the mouse gut.

Metabolites produced by the intestinal microbiota are potentially important physiological modulators. Here we present a metabolomics strategy that models microbiota metabolism as a reaction network and utilizes pathway analysis to facilitate identification and characterization of microbiota metabolites. Of the 2,409 reactions in the model, ~53% do not occur in the host, and thus represent functions dependent on the microbiota. The largest group of such reactions involves amino-acid metabolism. Focusing on aromatic amino acids, we predict metabolic products that can be derived from these sources, while discriminating between microbiota- and host-dependent derivatives. We confirm the presence of 26 out of 49 predicted metabolites, and quantify their levels in the caecum of control and germ-free mice using two independent mass spectrometry methods. We further investigate the bioactivity of the confirmed metabolites, and identify two microbiota-generated metabolites (5-hydroxy-L-tryptophan and salicylate) as activators of the aryl hydrocarbon receptor.

Analysis of transcription factor network underlying 3T3-L1 adipocyte differentiation.

Lipid accumulation in adipocytes reflects a balance between enzymatic pathways leading to the formation and breakdown of esterified lipids, primarily triglycerides. This balance is extremely important, as both high and low lipid levels in adipocytes can have deleterious consequences. The enzymes responsible for lipid synthesis and breakdown (lipogenesis and lipolysis, respectively) are regulated through the coordinated actions of several transcription factors (TFs). In this study, we examined the dynamics of several key transcription factors (TFs) - PPARγ, C/EBPß, CREB, NFAT, FoxO1, and SREBP-1c - during adipogenic differentiation (week 1) and ensuing lipid accumulation. The activation profiles of these TFs at different times following induction of adipogenic differentiation were quantified using 3T3-L1 reporter cell lines constructed to secrete the Gaussia luciferase enzyme upon binding of a TF to its DNA binding element. The dynamics of the TFs was also modeled using a combination of logical gates and ordinary differential equations, where the logical gates were used to explore different combinations of activating inputs for PPARγ, C/EBPß, and SREBP-1c. Comparisons of the experimental profiles and model simulations suggest that SREBP-1c could be independently activated by either insulin or PPARγ, whereas PPARγ activation required both C/EBPß as well as a putative ligand. Parameter estimation and sensitivity analysis indicate that feedback activation of SREBP-1c by PPARγ is negligible in comparison to activation of SREBP-1c by insulin. On the other hand, the production of an activating ligand could quantitatively contribute to a sustained elevation in PPARγ activity.

Systems biology of adipose tissue metabolism: regulation of growth, signaling and inflammation.

Adipose tissue (AT) depots actively regulate whole body energy homeostasis by orchestrating complex communications with other physiological systems as well as within the tissue. Adipocytes readily respond to hormonal and nutritional inputs to store excess nutrients as intracellular lipids or mobilize the stored fat for utilization. Co-ordinated regulation of metabolic pathways balancing uptake, esterification, and hydrolysis of lipids is accomplished through positive and negative feedback interactions of regulatory hubs comprising several pleiotropic protein kinases and nuclear receptors. Metabolic regulation in adipocytes encompasses biogenesis and remodeling of uniquely large lipid droplets (LDs). The regulatory hubs also function as energy and nutrient sensors, and integrate metabolic regulation with intercellular signaling. Over-nutrition causes hypertrophic expansion of adipocytes, which, through incompletely understood mechanisms, initiates a cascade of metabolic and signaling events leading to tissue remodeling and immune cell recruitment. Macrophage activation and polarization toward a pro-inflammatory phenotype drives a self-reinforcing cycle of pro-inflammatory signals in the AT, establishing an inflammatory state. Sustained inflammation accelerates lipolysis and elevates free fatty acids in circulation, which robustly correlates with development of obesity-related diseases. The adipose regulatory network coupling metabolism, growth, and signaling of multiple cell types is exceedingly complex. While components of the regulatory network have been individually studied in exquisite detail, systems approaches have rarely been utilized to comprehensively assess the relative engagements of the components. Thus, need and opportunity exist to develop quantitative models of metabolic and signaling networks to achieve a more complete understanding of AT biology in both health and disease.