Insect Repellents: Modulators of Mosquito Odorant Receptor Activity

Background: DEET, 2-undecanone (2-U), IR3535 and Picaridin are widely used as insect repellents to prevent interactions between humans and many arthropods including mosquitoes. Their molecular action has only recently been studied, yielding seemingly contradictory theories including odorant-dependent inhibitory and odorant-independent excitatory activities on insect olfactory sensory neurons (OSNs) and odorant receptor proteins (ORs). Methodology/Principal Findings: Here we characterize the action of these repellents on two Aedes aegypti ORs, AaOR2 and AaOR8, individually co-expressed with the common co-receptor AaOR7 in Xenopus oocytes; these ORs are respectively activated by the odors indole (AaOR2) and (R)-(2)-1-octen3-ol (AaOR8), odorants used to locate oviposition sites and host animals. In the absence of odorants, DEET activates AaOR2 but not AaOR8, while 2-U activates AaOR8 but not AaOR2; IR3535 and Picaridin do not activate these ORs. In the presence of odors, DEET strongly inhibits AaOR8 but not AaOR2, while 2-U strongly inhibits AaOR2 but not AaOR8; IR3535 and Picaridin strongly inhibit both ORs. Conclusions/Significance: These data demonstrate that repellents can act as olfactory agonists or antagonists, thus modulating OR activity, bringing concordance to conflicting models

Dynamic Modelling under Uncertainty: The Case of Trypanosoma brucei Energy Metabolism

Kinetic models of metabolism require detailed knowledge of kinetic parameters. However, due to measurement errors or lack of data this knowledge is often uncertain. The model of glycolysis in the parasitic protozoan Trypanosoma brucei is a particularly well analysed example of a quantitative metabolic model, but so far it has been studied with a fixed set of parameters only. Here we evaluate the effect of parameter uncertainty. In order to define probability distributions for each parameter, information about the experimental sources and confidence intervals for all parameters were collected. We created a wiki-based website dedicated to the detailed documentation of this information: the SilicoTryp wiki (http://silicotryp.ibls.gla.ac.uk/wiki/Glycolysis). Using information collected in the wiki, we then assigned probability distributions to all parameters of the model. This allowed us to sample sets of alternative models, accurately representing our degree of uncertainty. Some properties of the model, such as the repartition of the glycolytic flux between the glycerol and pyruvate producing branches, are robust to these uncertainties. However, our analysis also allowed us to identify fragilities of the model leading to the accumulation of 3-phosphoglycerate and/or pyruvate. The analysis of the control coefficients revealed the importance of taking into account the uncertainties about the parameters, as the ranking of the reactions can be greatly affected. This work will now form the basis for a comprehensive Bayesian analysis and extension of the model considering alternative topologies

Actin: its cumbersome pilgrimage through cellular compartments

In this article, we follow the history of one of the most abundant, most intensely studied proteins of the eukaryotic cells: actin. We report on hallmarks of its discovery, its structural and functional characterization and localization over time, and point to present days’ knowledge on its position as a member of a large family. We focus on the rather puzzling number of diverse functions as proposed for actin as a dual compartment protein. Finally, we venture on some speculations as to its origin

Muscle-specific loss of Bmal1 leads to disrupted tissue glucose metabolism and systemic glucose homeostasis

BACKGROUND: Diabetes is the seventh leading cause of death in the USA, and disruption of circadian rhythms is gaining recognition as a contributing factor to disease prevalence. This disease is characterized by hyperglycemia and glucose intolerance and symptoms caused by failure to produce and/or respond to insulin. The skeletal muscle is a key insulin-sensitive metabolic tissue, taking up ~80 % of postprandial glucose. To address the role of the skeletal muscle molecular clock to insulin sensitivity and glucose tolerance, we generated an inducible skeletal muscle-specific Bmal1(−/−) mouse (iMSBmal1(−/−)). RESULTS: Progressive changes in body composition (decreases in percent fat) were seen in the iMSBmal1(−/−) mice from 3 to 12 weeks post-treatment as well as glucose intolerance and non-fasting hyperglycemia. Ex vivo analysis of glucose uptake revealed that the extensor digitorum longus (EDL) muscles did not respond to either insulin or 5-aminoimidazole-4-carboxamide ribonucleotide (AICAR) stimulation. RT-PCR and Western blot analyses demonstrated a significant decrease in mRNA expression and protein content of the muscle glucose transporter (Glut4). We also found that both mRNA expression and activity of two key rate-limiting enzymes of glycolysis, hexokinase 2 (Hk2) and phosphofructokinase 1 (Pfk1), were significantly reduced in the iMSBmal1(−/−) muscle. Lastly, results from metabolomics analyses provided evidence of decreased glycolytic flux and uncovered decreases in some tricarboxylic acid (TCA) intermediates with increases in amino acid levels in the iMSBmal1(−/−) muscle. These findings suggest that the muscle is relying predominantly on fat as a fuel with increased protein breakdown to support the TCA cycle. CONCLUSIONS: These data support a fundamental role for Bmal1, the endogenous circadian clock, in glucose metabolism in the skeletal muscle. Our findings have implicated altered molecular clock dictating significant changes in altered substrate metabolism in the absence of feeding or activity changes. The changes in body composition in our model also highlight the important role that changes in skeletal muscle carbohydrate, and fat metabolism can play in systemic metabolism