Dynamics of Uptake and Metabolism of Small Molecules in Cellular Response Systems

BACKGROUND: Proper cellular function requires uptake of small molecules from the environment. In response to changes in extracellular conditions cells alter the import and utilization of small molecules. For a wide variety of small molecules the cellular response is regulated by a network motif that combines two feedback loops, one which regulates the transport and the other which regulates the subsequent metabolism. RESULTS: We analyze the dynamic behavior of two widespread but logically distinct two-loop motifs. These motifs differ in the logic of the feedback loop regulating the uptake of the small molecule. Our aim is to examine the qualitative features of the dynamics of these two classes of feedback motifs. We find that the negative feedback to transport is accompanied by overshoot in the intracellular amount of small molecules, whereas a positive feedback to transport removes overshoot by boosting the final steady state level. On the other hand, the negative feedback allows for a rapid initial response, whereas the positive feedback is slower. We also illustrate how the dynamical deficiencies of one feedback motif can be mitigated by an additional loop, while maintaining the original steady-state properties. CONCLUSIONS: Our analysis emphasizes the core of the regulation found in many motifs at the interface between the metabolic network and the environment of the cell. By simplifying the regulation into uptake and the first metabolic step, we provide a basis for elaborate studies of more realistic network structures. Particularly, this theoretical analysis predicts that FeS cluster formation plays an important role in the dynamics of iron homeostasis

Automatic Annotation of Spatial Expression Patterns via Sparse Bayesian Factor Models

Advances in reporters for gene expression have made it possible to document and quantify expression patterns in 2D–4D. In contrast to microarrays, which provide data for many genes but averaged and/or at low resolution, images reveal the high spatial dynamics of gene expression. Developing computational methods to compare, annotate, and model gene expression based on images is imperative, considering that available data are rapidly increasing. We have developed a sparse Bayesian factor analysis model in which the observed expression diversity of among a large set of high-dimensional images is modeled by a small number of hidden common factors. We apply this approach on embryonic expression patterns from a Drosophila RNA in situ image database, and show that the automatically inferred factors provide for a meaningful decomposition and represent common co-regulation or biological functions. The low-dimensional set of factor mixing weights is further used as features by a classifier to annotate expression patterns with functional categories. On human-curated annotations, our sparse approach reaches similar or better classification of expression patterns at different developmental stages, when compared to other automatic image annotation methods using thousands of hard-to-interpret features. Our study therefore outlines a general framework for large microscopy data sets, in which both the generative model itself, as well as its application for analysis tasks such as automated annotation, can provide insight into biological questions

X-ray free electron laser heating of water and gold at high static pressure

The study of water at high pressure and temperature is essential for understanding planetary interiors but is hampered by the high reactivity of water at extreme conditions. Here, indirect X-ray laser heating of water in a diamond anvil cell is realized via a gold absorber, showing no evidence of reactivity

Interconversion between bound and free conformations of LexA orchestrates the bacterial SOS response

The bacterial SOS response is essential for the maintenance of genomes, and also modulates antibiotic resistance and controls multidrug tolerance in subpopulations of cells known as persisters. In Escherichia coli, the SOS system is controlled by the interplay of the dimeric LexA transcriptional repressor with an inducer, the active RecA filament, which forms at sites of DNA damage and activates LexA for self-cleavage. Our aim was to understand how RecA filament formation at any chromosomal location can induce the SOS system, which could explain the mechanism for precise timing of induction of SOS genes. Here, we show that stimulated self-cleavage of the LexA repressor is prevented by binding to specific DNA operator targets. Distance measurements using pulse electron paramagnetic resonance spectroscopy reveal that in unbound LexA, the DNA-binding domains sample different conformations. One of these conformations is captured when LexA is bound to operator targets and this precludes interaction by RecA. Hence, the conformational flexibility of unbound LexA is the key element in establishing a co-ordinated SOS response. We show that, while LexA exhibits diverse dissociation rates from operators, it interacts extremely rapidly with DNA target sites. Modulation of LexA activity changes the occurrence of persister cells in bacterial populations

Intrinsic Thermal Sensing Controls Proteolysis of Yersinia Virulence Regulator RovA

Pathogens, which alternate between environmental reservoirs and a mammalian host, frequently use thermal sensing devices to adjust virulence gene expression. Here, we identify the Yersinia virulence regulator RovA as a protein thermometer. Thermal shifts encountered upon host entry lead to a reversible conformational change of the autoactivator, which reduces its DNA-binding functions and renders it more susceptible for proteolysis. Cooperative binding of RovA to its target promoters is significantly reduced at 37°C, indicating that temperature control of rovA transcription is primarily based on the autoregulatory loop. Thermally induced reduction of DNA-binding is accompanied by an enhanced degradation of RovA, primarily by the Lon protease. This process is also subject to growth phase control. Studies with modified/chimeric RovA proteins indicate that amino acid residues in the vicinity of the central DNA-binding domain are important for proteolytic susceptibility. Our results establish RovA as an intrinsic temperature-sensing protein in which thermally induced conformational changes interfere with DNA-binding capacity, and secondarily render RovA susceptible to proteolytic degradation

Empirical investigation to explore potential gains from the amalgamation of Phase Changing Materials (PCMs) and wood shavings

The reduction of gained heat, heat peak shifting and the mitigation of air temperature fluctuations are some desirable properties that are sought after in any thermal insulation system. It cannot be overstated that these factors, in addition to others, govern the performance of such systems thus their effect on indoor ambient conditions. The effect of such systems extends also to Heating, Ventilation and Air-conditioning (HVAC) systems that are set up to operate optimally in certain conditions. Where literature shows that PCMs and natural materials such as wood-shavings can provide efficient passive insulation for buildings, it is evident that such approaches utilise methods that are of a degree of intricacy which requires specialist knowledge and complex techniques, such as micro-encapsulation for instance. With technical and economic aspects in mind, an amalgam of PCM and wood-shavings has been created for the purpose of being utilised as a feasible thermal insulation. The amalgamation was performed in the simplest of methods, through submerging the wood shavings in PCM. An experimental procedure was devised to test the thermal performance of the amalgam and compare this to the performance of the same un-amalgamated materials. Comparative analysis revealed that no significant thermal gains would be expected from such amalgamation. However, significant reduction in the total weight of the insulation system would be achieved that, in this case, shown to be up to 20.94%. Thus, further reducing possible strains on structural elements due to the application of insulation on buildings. This can be especially beneficial in vernacular architectural approaches where considerably large amounts and thicknesses of insulations are used. In addition, cost reduction could be attained as wood shavings are significantly cheaper compared to the cost of PCMs

The Inter-temporal relationship between Risk, Capital and Efficiency: The case of Islamic and conventional banks

The paper investigates the relationship between risk, capital and efficiency for Islamic and conventional banks using a dataset spanning 14 countries over the 2000-2012 period. We use the z-score as a proxy for insolvency risk, cost efficiency is estimated via a stochastic frontier approach and capitalisation is reflected on the equity to assets ratio. An array of bank-specific, macroeconomic and market structure variables are used in a system of three equations, estimated using the seemingly unrelated regression (SUR) technique. We find that the capitalisation response to increases in insolvency risk is more pronounced for Islamic banks but has an approximately five-times smaller effect on risk mitigation compared to conventional banks. Higher cost efficiency is related to lower risk for conventional banks, but the opposite is true for Islamic banks. The link between cost efficiency and capitalisation attests to a substitutional effect for the case of conventional banks, but a complementary effect for Islamic banks. Our findings give new insights on the use of efficiency to gauge capital requirements for financial institutions and are particularly relevant for regulators and policy makers in countries where both bank types operate