Two Component Systems: Physiological Effect of a Third Component

Signal transduction systems mediate the response and adaptation of organisms to environmental changes. In prokaryotes, this signal transduction is often done through Two Component Systems (TCS). These TCS are phosphotransfer protein cascades, and in their prototypical form they are composed by a kinase that senses the environmental signals (SK) and by a response regulator (RR) that regulates the cellular response. This basic motif can be modified by the addition of a third protein that interacts either with the SK or the RR in a way that could change the dynamic response of the TCS module. In this work we aim at understanding the effect of such an additional protein (which we call “third component”) on the functional properties of a prototypical TCS. To do so we build mathematical models of TCS with alternative designs for their interaction with that third component. These mathematical models are analyzed in order to identify the differences in dynamic behavior inherent to each design, with respect to functionally relevant properties such as sensitivity to changes in either the parameter values or the molecular concentrations, temporal responsiveness, possibility of multiple steady states, or stochastic fluctuations in the system. The differences are then correlated to the physiological requirements that impinge on the functioning of the TCS. This analysis sheds light on both, the dynamic behavior of synthetically designed TCS, and the conditions under which natural selection might favor each of the designs. We find that a third component that modulates SK activity increases the parameter space where a bistable response of the TCS module to signals is possible, if SK is monofunctional, but decreases it when the SK is bifunctional. The presence of a third component that modulates RR activity decreases the parameter space where a bistable response of the TCS module to signals is possible

Multi-scale, whole-system models of liver metabolic adaptation to fat and sugar in non-alcoholic fatty liver disease

Non-alcoholic fatty liver disease (NAFLD) is a serious public health issue associated with high fat, high sugar diets. However, the molecular mechanisms mediating NAFLD pathogenesis are only partially understood. Here we adopt an iterative multi-scale, systems biology approach coupled to in vitro experimentation to investigate the roles of sugar and fat metabolism in NAFLD pathogenesis. The use of fructose as a sweetening agent is controversial; to explore this, we developed a predictive model of human monosaccharide transport, signalling and metabolism. The resulting quantitative model comprising a kinetic model describing monosaccharide transport and insulin signalling integrated with a hepatocyte-specific genome-scale metabolic network (GSMN). Differential kinetics for the utilisation of glucose and fructose were predicted, but the resultant triacylglycerol production was predicted to be similar for monosaccharides; these predictions were verified by in vitro data. The role of physiological adaptation to lipid overload was explored through the comprehensive reconstruction of the peroxisome proliferator activated receptor alpha (PPARα) regulome integrated with a hepatocyte-specific GSMN. The resulting qualitative model reproduced metabolic responses to increased fatty acid levels and mimicked lipid loading in vitro. The model predicted that activation of PPARα by lipids produces a biphasic response, which initially exacerbates steatosis. Our data support the evidence that it is the quantity of sugar rather than the type that is critical in driving the steatotic response. Furthermore, we predict PPARα-mediated adaptations to hepatic lipid overload, shedding light on potential challenges for the use of PPARα agonists to treat NAFLD

Targeting pathogen metabolism without collateral damage to the host

The development of drugs that can inactivate disease-causing cells (e.g. cancer cells or parasites) without causing collateral damage to healthy or to host cells is complicated by the fact that many proteins are very similar between organisms. Nevertheless, due to subtle, quantitative differences between the biochemical reaction networks of target cell and host, a drug can limit the flux of the same essential process in one organism more than in another. We identified precise criteria for this â €network-based' drug selectivity, which can serve as an alternative or additive to structural differences. We combined computational and experimental approaches to compare energy metabolism in the causative agent of sleeping sickness, Trypanosoma brucei, with that of human erythrocytes, and identified glucose transport and glyceraldehyde-3-phosphate dehydrogenase as the most selective antiparasitic targets. Computational predictions were validated experimentally in a novel parasite-erythrocytes co-culture system. Glucose-transport inhibitors killed trypanosomes without killing erythrocytes, neurons or liver cells

Non Linear Programming (NLP) Formulation for Quantitative Modeling of Protein Signal Transduction Pathways

Modeling of signal transduction pathways plays a major role in understanding cells' function and predicting cellular response. Mathematical formalisms based on a logic formalism are relatively simple but can describe how signals propagate from one protein to the next and have led to the construction of models that simulate the cells response to environmental or other perturbations. Constrained fuzzy logic was recently introduced to train models to cell specific data to result in quantitative pathway models of the specific cellular behavior. There are two major issues in this pathway optimization: i) excessive CPU time requirements and ii) loosely constrained optimization problem due to lack of data with respect to large signaling pathways. Herein, we address both issues: the former by reformulating the pathway optimization as a regular nonlinear optimization problem; and the latter by enhanced algorithms to pre/post-process the signaling network to remove parts that cannot be identified given the experimental conditions. As a case study, we tackle the construction of cell type specific pathways in normal and transformed hepatocytes using medium and large-scale functional phosphoproteomic datasets. The proposed Non Linear Programming (NLP) formulation allows for fast optimization of signaling topologies by combining the versatile nature of logic modeling with state of the art optimization algorithms.National Institutes of Health (U.S.) (Grant P50-GM068762)National Institutes of Health (U.S.) (Grant R24-DK090963)United States. Army Research Office (Grant W911NF-09-0001)German Research Foundation (Grant GSC 111

Mathematically modelling the dynamics of cholesterol metabolism and ageing

Cardiovascular disease (CVD) is the leading cause of morbidity and mortality in the UK. This conditionbecomes increasingly prevalent during ageing; 34.1% and 29.8% of males and females respectively, over 75years of age have an underlying cardiovascular problem. The dysregulation of cholesterol metabolism isinextricably correlated with cardiovascular health and for this reason low density lipoprotein cholesterol(LDL-C) and high density lipoprotein cholesterol (HDL-C) are routinely used as biomarkers of CVD risk. Theaim of this work was to use mathematical modelling to explore how cholesterol metabolism is affectedby the ageing process. To do this we updated a previously published whole-body mathematical model ofcholesterol metabolism to include an additional 96 mechanisms that are fundamental to this biologicalsystem. Additional mechanisms were added to cholesterol absorption, cholesterol synthesis, reversecholesterol transport (RCT), bile acid synthesis, and their enterohepatic circulation. The sensitivity of themodel was explored by the use of both local and global parameter scans. In addition, acute cholesterolfeeding was used to explore the effectiveness of the regulatory mechanisms which are responsible formaintaining whole-body cholesterol balance. It was found that our model behaves as a hypo-responderto cholesterol feeding, while both the hepatic and intestinal pools of cholesterol increased significantly.The model was also used to explore the effects of ageing in tandem with three different cholesterolester transfer protein (CETP) genotypes. Ageing in the presence of an atheroprotective CETP genotype,conferring low CETP activity, resulted in a 0.6% increase in LDL-C. In comparison, ageing with a genotypereflective of high CETP activity, resulted in a 1.6% increase in LDL-C. Thus, the model has illustrated theimportance of CETP genotypes such as I405V, and their potential role in healthy ageing

Coherent ultrafast lattice-directed reaction dynamics of triiodide anion photodissociation

Solid-state reactions are influenced by the spatial arrangement of the reactants and the electrostatic environment of the lattice, which may enable lattice-directed chemical dynamics. Unlike the caging imposed by an inert matrix, an active lattice participates in the reaction, however, little evidence of such lattice participation has been gathered on ultrafast timescales due to the irreversibility of solid-state chemical systems. Here, by lowering the temperature to 80 K, we have been able to study the dissociative photochemistry of the triiodide anion (I₃−) in single-crystal tetra-n-butylammonium triiodide using broadband transient absorption spectroscopy. We identified the coherently formed tetraiodide radical anion (I₄•−) as a reaction intermediate. Its delayed appearance after that of the primary photoproduct, diiodide radical I₂•−, indicates that I₄•− was formed via a secondary reaction between a dissociated iodine radical (I^•) and an adjacent I₃−. This chemistry occurs as a result of the intermolecular interaction determined by the crystalline arrangement and is in stark contrast with previous solution studies

Stable nuclear transformation of Eudorina elegans

Lerche K, Hallmann A. Stable nuclear transformation of Eudorina elegans. BMC Biotechnology. 2013;13(1): 11.UNLABELLED: ABSTRACT: BACKGROUND: A fundamental step in evolution was the transition from unicellular to differentiated, multicellular organisms. Volvocine algae have been used for several decades as a model lineage to investigate the evolutionary aspects of multicellularity and cellular differentiation. There are two well-studied volvocine species, a unicellular alga (Chlamydomonas reinhardtii) and a multicellular alga with differentiated cell types (Volvox carteri). Species with intermediate characteristics also exist, which blur the boundaries between unicellularity and differentiated multicellularity. These species include the globular alga Eudorina elegans, which is composed of 16-32 cells. However, detailed molecular analyses of E. elegans require genetic manipulation. Unfortunately, genetic engineering has not yet been established for Eudorina, and only limited DNA and/or protein sequence information is available. RESULTS: Here, we describe the stable nuclear transformation of E. elegans by particle bombardment using both a chimeric selectable marker and reporter genes from different heterologous sources. Transgenic algae resistant to paromomycin were achieved using the aminoglycoside 3'-phosphotransferase VIII (aphVIII) gene of Streptomyces rimosus, an actinobacterium, under the control of an artificial promoter consisting of two V. carteri promoters in tandem. Transformants exhibited an increase in resistance to paromomycin by up to 333-fold. Co-transformation with non-selectable plasmids was achieved with a rate of 50 - 100%. The luciferase (gluc) gene from the marine copepod Gaussia princeps, which previously was engineered to match the codon usage of C. reinhardtii, was used as a reporter gene. The expression of gluc was mediated by promoters from C. reinhardtii and V. carteri. Heterologous heat shock promoters induced an increase in luciferase activity (up to 600-fold) at elevated temperatures. Long-term stability and both constitutive and inducible expression of the co-bombarded gluc gene was demonstrated by transcription analysis and bioluminescence assays. CONCLUSIONS: Heterologous flanking sequences, including promoters, work in E. elegans and permit both constitutive and inducible expression of heterologous genes. Stable nuclear transformation of E. elegans is now routine. Thus, we show that genetic engineering of a species is possible even without the resources of endogenous genes and promoters