In silico pathway reconstruction: Iron-sulfur cluster biogenesis in Saccharomyces cerevisiae

BACKGROUND: Current advances in genomics, proteomics and other areas of molecular biology make the identification and reconstruction of novel pathways an emerging area of great interest. One such class of pathways is involved in the biogenesis of Iron-Sulfur Clusters (ISC). RESULTS: Our goal is the development of a new approach based on the use and combination of mathematical, theoretical and computational methods to identify the topology of a target network. In this approach, mathematical models play a central role for the evaluation of the alternative network structures that arise from literature data-mining, phylogenetic profiling, structural methods, and human curation. As a test case, we reconstruct the topology of the reaction and regulatory network for the mitochondrial ISC biogenesis pathway in S. cerevisiae. Predictions regarding how proteins act in ISC biogenesis are validated by comparison with published experimental results. For example, the predicted role of Arh1 and Yah1 and some of the interactions we predict for Grx5 both matches experimental evidence. A putative role for frataxin in directly regulating mitochondrial iron import is discarded from our analysis, which agrees with also published experimental results. Additionally, we propose a number of experiments for testing other predictions and further improve the identification of the network structure. CONCLUSION: We propose and apply an iterative in silico procedure for predictive reconstruction of the network topology of metabolic pathways. The procedure combines structural bioinformatics tools and mathematical modeling techniques that allow the reconstruction of biochemical networks. Using the Iron Sulfur cluster biogenesis in S. cerevisiae as a test case we indicate how this procedure can be used to analyze and validate the network model against experimental results. Critical evaluation of the obtained results through this procedure allows devising new wet lab experiments to confirm its predictions or provide alternative explanations for further improving the models

The associative basis of cue-elicited drug taking in humans.

Rationale: Drug cues play an important role in motivating human drug taking, lapse and relapse, but the psychological basis of this effect has not been fully specified. Method: To clarify these mechanisms, the study measured the extent to which pictorial and conditioned tobacco cues enhanced smoking topography in an ad libitum smoking session simultaneously with cue effects on subjective craving, pleasure and anxiety. Results: Both cue types increased the number of puffs consumed and craving, but pleasure and anxiety responses were dissociated across cue type. Moreover, cue effects on puff number correlated with effects on craving but not pleasure or anxiety. Finally, whereas overall puff number and craving declined across the two blocks of consumption, consistent with burgeoning satiety, cue enhancement of puff number and craving were both unaffected by satiety. Conclusions: Overall, the data suggest that cue-elicited drug taking in humans is mediated by an expectancy-based associative learning architecture, which paradoxically is autonomous of the current incentive value of the drug

In situ Characterisation of Practical Heterogeneous Catalysts

In situ methods are considered as a curiosity within the standard methodology of practical catalyst characterization. The methods are not commercially available and need to be adapted and validated for each specific problem. The great advantage of these methods is, however, that they deliver immediately relevant characteristics of the working state of a heterogeneous catalyst and allow justified structure-function relations to be deduced. To achieve this it is essential that the experiments are planned and conducted in such away that the proven to be active state of the catalyst is investigated. This can only be ascertained if simultaneous kinetic and spectroscopic data are acquired. The contribution lists a selection of methods with their main characteristics that allows to choose from the wide spectrum of information those that are most relevant for the given problem. A tabulated selection of case studies from the literature gives some insight in the current practice