Presentation : Development of an age-specific genome-scale model of skeletal muscle metabolism

Skeletal myocytes are among the most metabolically active cell types, implicated in nutrient balance, contributing to the insulin-stimulated clearance of glucose from the blood, and secreting myokines that contribute in regulating inflammation and the ageing process. The loss of muscle mass and strength with age (sarcopenia), is a risk factor for cardiovascular and metabolic diseases, it increases the risk of falls, of developing frailty and disabilities, and results in an impairment in the quality of life and autonomy of an individual.An active lifestyle is the most immediate and accessible treatment to prevent sarcopenia, with a considerable impact on the ageing process: PANINI is a European Training Network whose aim is understanding how lifestyle factors can influence healthy ageing.In this context, we present the first age-specific genome-scale metabolic model of the skeletal muscle, a mathematical representation of the myocyte metabolic network in the elderly, built using RECON2, the human metabolic reconstruction, and gene expression data, gathered from older adults' muscle tissue biopsies.This model will be used to analyze patient-specific data for potential mechanisms able to explain the different ageing paces of different individuals and to investigate the effectiveness of different nutritional and physical exercise regimes in stimulating post-exercise protein synthesis, which is often impaired in the elderly.The aim is to identify an optimal and personalized lifestyle change intervention able to prevent the onset of sarcopenia. <br/

Targeted experiment design using the posterior predictive distribution

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Use of genome-scale metabolic models for plant metabolism

Genome-scale metabolic models (GSMM) have been extensively applied for a wide variety of organisms. However, for plants genome-scale modeling is still in its infancy. It has been successfully developed for Arabidopsis in the last few years. In this study we appraise the existing GSMM for Arabidopsis by computing biomass accumulation using flux balance analysis (FBA) and attempt to outline potential applications for horticultural crops in the future. The predicted growth rates for the Poolman et al. (2009) and Dal’Molin et al. (2010) model were quite similar, despite different carbon sources were provided (glucose and sucrose,100 mmol/g*h DW). The exchange fluxes for respiration in nonphotosynthetic cells confirmed that plants prefer NH3 in the process of nitrogen assimilation. When carbohydrates were used as substrate for respiration the Respiratory quotient (RQ) of Poolman’s model approached 1, which is consistent with experimental data. For the Dal’Molin’s model the RQ is less than 1. H2S is utilized in the Dal’Molin model as sulfur source, whereas sulfate (SO42-) is consumed in the Poolman’s model. The Poolman’s model seems to reflect biological reality more closely than the Dal’Molin model. This could be due to the subcellular compartmentation included in the Dal’Molin model, adding subcellular compartmentation of reactions was done manually. In conclusion, to apply constraints-based reconstruction and analysis (COBRA) methods, including FBA, to plant metabolism requires careful analysis and possibly curation of existing GSMM’s

Blue light phototherapy for Psoriasis from a systems biology perspective

This work analyses the effect of UV-free blue light (BL) irradiation of the skin using mathematical modelling. Prior research has shown that blue light reduces the proliferation of keratinocytes by inducing their differentiation, and causes apoptosis of lymphocytes. The effects of blue light on these cells make it an attractive phototherapy alternative for inflammatory skin conditions, such as psoriasis. Nevertheless, the exact process by which BL affects these cells is not fully understood. A modelling approach may give further insight to understanding how BL irradiation of psoriatic skin leads to the control of the disease. However, no mathematical model is available describing this phenomenon. Two deterministic models were therefore made to describe the epidermal kinetics and interaction between keratinocytes and lymphocytes under the effect of BL irradiation; focusing mainly on the case of psoriasis. We employed a systems biology approach to characterize the effect of BL irradiation of the skin. Since in phototherapy parameters such as fluence and power have a strong impact on the outcome, a parameter sensitivity analysis (PSA) was performed to estimate a range of fluence and power at which BL phototherapy could be successful. The models results suggest that the management of psoriasis is achieved by inducing symmetric differentiation of the keratinocytes in the epidermal proliferative compartment. It is observed that BL irradiation of psoriatic skin decreases the density of keratinocytes and transiently increases the density of lymphocytes, leading to the regulation of the interaction between these two cell types. The PSA of the models predicts that the higher the peak power the better the outcome of the BL phototherapy with a dose of 90J/cm2 per day. This systems biology approach provides additional insight into the use of BL phototherapy for inflammatory skin disorders

In vivo magnetic resonance spectroscopy of lipid handling in steatotic rat liver

Objective: Examine lipid handling in liver of rats fed with different high-fat diets using 1H-[13C] magnetic resonance spectroscopy (MRS) together with oral administration of 13C labeled lipids. Methods: 6 male Wistar rats (11 weeks old; 348 ± 8g) were divided into three diet groups: low-fat (10% fat, CON), high-fat lard (45% fat, HFL), and high-fat palm oil (45%, HFP). After 10 weeks of diet, MRS experiments were performed at baseline, and 4 and 24 h after oral administration of 1.5 g [U-13C] Algal lipid mixture per kg body weight. Results: At 4 h after administration of the 13C labeled lipids, 13C enrichment of intracellular liver lipids was similarly increased in all three groups compared to baseline (CON: 0.031 ± 0.017 %; HFL: 0.045 ± 0.022 %; HFP: 0.033 ± 0.013 %), demonstrating that lipid uptake was not affected by the diet regimen. At 24 h, on the other hand, 13C enrichment of liver lipids decreased in CON, whereas in both high-fat diet groups the 13C enrichment did not change compared to 4 h, indicating a lower turnover of the stored liver lipids. Conclusion: High-fat diet feeding did not alter liver lipid uptake in rats, but resulted in a decreased turnover of the lipids stored in the liver. This research was funded by the Netherlands Consortium for Systems Biology (NCSB) which is part of the Netherlands Genomics Initiative/Netherlands Organisation for Scientific Research

Lessons learned from computer models on blue light therapy for psoriasis vulgaris

Blue light irradiation has been clinically proven to reduce the symptoms of psoriasis vulgaris, a common chronic inflammatory skin disease that affects 2% - 3% of the world’s population. This dermatological condition is characterized by hyperproliferation and disturbed differentiation of keratinocytes, which is evident in lesional areas as thick flaky skin. The lesional areas also exhibit sustained inflammation, induced by immune cells, such as T cells and dendritic cells, infiltrating the affected skin. Blue light reduces the proliferation of keratinocytes and increases their differentiation in a wavelength and fluence dependent manner. Also, it induces apoptosis in T cells and suppresses the activation of dendritic cells. These effects can explain the symptom reduction after treatment. But, the efficacy shown in the clinical studies could be further improved by having a deeper understanding on the underlying mechanism of this therapeutic approach and optimizing the treatment regimens currently used. Diverse findings have been published in different studies of blue light therapy for psoriasis describing large, little or no therapeutic effect. These results may be due to variances in the main treatment parameters of the implemented protocols, i.e. fluence, intensity, and length of treatment. Computational methods can provide a suitable platform to investigate the complex interactions leading to the management of psoriasis by blue light therapy and optimize the treatment protocols. Here, we explore in silico the underlying mechanism of blue light irradiation of psoriatic skin and predict the outcome of a wide range of therapeutic regimens with varying fluence, intensity, and length of treatment. The computational model is defined by a set of ordinary differential equations describing the time evolution of keratinocytes as they move vertically through the layers of the epidermis. The results of our simulations suggest that the temporary decrease in the severity of psoriasis can be explained by the transient decline in the proliferative capacity of keratinocytes. However, it is still unclear how the effects of blue light on the immune system contribute to the reduction of psoriasis symptoms. Simulations implemented for several combinations of treatment parameters predict that high efficacy is achieved by protocols with long duration and high fluence levels, regardless of the chosen intensity. These predictions provide general guidelines for treatment. Our in silico approach constitutes a framework for testing diverse hypotheses on the underlying mechanism of blue light therapy and designing effective strategies for the treatment of psoriasis vulgaris