Comparing methods for metabolic network analysis and an application to metabolic engineering

Bioinformatics tools have facilitated the reconstruction and analysis of cellular metabolism of various organisms based on information encoded in their genomes. Characterization of cellular metabolism is useful to understand the phenotypic capabilities of these organisms. It has been done quantitatively through the analysis of pathway operations. There are several in silico approaches for analyzing metabolic networks, including structural and stoichiometric analysis, metabolic flux analysis, metabolic control analysis, and several kinetic modeling based analyses. They can serve as a virtual laboratory to give insights into basic principles of cellular functions. This article summarizes the progress and advances in software and algorithm development for metabolic network analysis, along with their applications relevant to cellular physiology, and metabolic engineering with an emphasis on microbial strain optimization. Moreover, it provides a detailed comparative analysis of existing approaches under different categories.     

Technologies for integrating biological data

The process of building a new database relevant to some field of study in biomedicine involves transforming, integrating and cleansing multiple data sources, as well as adding new material and annotations. This paper reviews some of the requirements of a general solution to this data integration problem. Several representative technologies and approaches to data integration in biomedicine are surveyed. Then some interesting features that separate the more general data integration technologies from the more specialised ones are highlighted.     

The application of a model of glucose and insulin dynamics to explain an observed effect of leptin administration in reversal of developmental programming

A dynamical model describing the glucose-insulin physiological system was applied to an experiment on the administration of the adipokine leptin between neonatal days 3 and 13 to rats whose dams were subject to different levels of nutrition during gestation. The effect of leptin treatment on the glucose-insulin equilibrium point and on the levels of other associated metabolites showed a significant change in direction that depended on the level of prenatal nutrition. Leptin has been shown to affect two factors that affect the equilibrium levels of glucose and insulin, gluconeogenesis and insulin sensitivity. Each effect is described by a parameter in the dynamical model. Mathematical analysis shows that changes in these parameters in the manner promoted by leptin would indeed increase or decrease the glucose-insulin equilibria depending on their initial equilibrium levels which might be induced by the level of prenatal nutrition. This analysis explains the results of the leptin experiment in the context of the dynamics of the glucocorticoid system. It also proposes a physiological mechanism for the expression of plasticity in the organism based on the status of the glucose and insulin equilibria.     

In vitro regulatory models for systems biology

The reductionist approach has revolutionized biology in the past 50 years. Yet its limits are being felt as the complexity of cellular interactions is gradually revealed by high-throughput technology. In order to make sense of the deluge of “omic data”, a hypothesis-driven view is needed to understand how biomolecular interactions shape cellular networks. We review recent efforts aimed at building in vitro biochemical networks that reproduce the flow of genetic regulation. We highlight how those efforts have culminated in the rational construction of biochemical oscillators and bistable memories in test tubes. We also recapitulate the lessons learned about in vivo biochemical circuits such as the importance of delays and competition, the links between topology and kinetics, as well as the intriguing resemblance between cellular reaction networks and ecosystems.     

Intrauterine growth retarded piglet as a model for humans – Studies on the perinatal development of the gut structure and function

The overall acceptance of pig models for human biomedical studies is steadily growing. Results of rodent studies are usually confirmed in pigs before extrapolating them to humans. This applies particularly to gastrointestinal and metabolism research due to similarities between pig and human physiology. In this context, intrauterine growth retarded (IUGR) pig neonate can be regarded as a good model for the better understanding of the IUGR syndrome in humans. In pigs, the induction of IUGR syndrome may include maternal diet intervention, dexamethasone treatment or temporary reduction of blood supply. However, in pigs, like in humans, circa 8% of neonates develop IUGR syndrome spontaneously. Studies on the pig model have shown changes in gut structure, namely a reduced thickness of mucosa and muscle layers, and delayed kinetic of disappearance of vacuolated enterocytes were found in IUGR individuals in comparison with healthy ones. Functional changes include reduced dynamic of gut mucosa rebuilding, decreased activities of main brush border enzymes, and changes in the expression of proteins important for carbohydrate, amino acids, lipid, mineral and vitamin metabolism. Moreover, profiles of intestinal hormones are different in IUGR and non-IUGR piglets. It is suggested that supplementation of the mothers during the gestation and/or the IUGR offspring after birth can help in restoring the development of the gastrointestinal tract. The pig provides presumably the optimal animal model for humans to study gastrointestinal tract structure and function development in IUGR syndrome.