A logical model provides insights into T cell receptor signaling

Cellular decisions are determined by complex molecular interaction networks. Large-scale signaling networks are currently being reconstructed, but the kinetic parameters and quantitative data that would allow for dynamic modeling are still scarce. Therefore, computational studies based upon the structure of these networks are of great interest. Here, a methodology relying on a logical formalism is applied to the functional analysis of the complex signaling network governing the activation of T cells via the T cell receptor, the CD4/CD8 co-receptors, and the accessory signaling receptor CD28. Our large-scale Boolean model, which comprises 94 nodes and 123 interactions and is based upon well-established qualitative knowledge from primary T cells, reveals important structural features (e.g., feedback loops and network-wide dependencies) and recapitulates the global behavior of this network for an array of published data on T cell activation in wild-type and knock-out conditions. More importantly, the model predicted unexpected signaling events after antibody-mediated perturbation of CD28 and after genetic knockout of the kinase Fyn that were subsequently experimentally validated. Finally, we show that the logical model reveals key elements and potential failure modes in network functioning and provides candidates for missing links. In summary, our large-scale logical model for T cell activation proved to be a promising in silico tool, and it inspires immunologists to ask new questions. We think that it holds valuable potential in foreseeing the effects of drugs and network modifications.     

From inverse problems in mathematical physiology to quantitative differential diagnoses

The improved capacity to acquire quantitative data in a clinical setting has generally failed to improve outcomes in acutely ill patients, suggesting a need for advances in computer-supported data interpretation and decision making. In particular, the application of mathematical models of experimentally elucidated physiological mechanisms could augment the interpretation of quantitative, patient-specific information and help to better target therapy. Yet, such models are typically complex and nonlinear, a reality that often precludes the identification of unique parameters and states of the model that best represent available data. Hypothesizing that this non-uniqueness can convey useful information, we implemented a simplified simulation of a common differential diagnostic process (hypotension in an acute care setting), using a combination of a mathematical model of the cardiovascular system, a stochastic measurement model, and Bayesian inference techniques to quantify parameter and state uncertainty. The output of this procedure is a probability density function on the space of model parameters and initial conditions for a particular patient, based on prior population information together with patient-specific clinical observations. We show that multimodal posterior probability density functions arise naturally, even when unimodal and uninformative priors are used. The peaks of these densities correspond to clinically relevant differential diagnoses and can, in the simplified simulation setting, be constrained to a single diagnosis by assimilating additional observations from dynamical interventions (e.g., fluid challenge). We conclude that the ill-posedness of the inverse problem in quantitative physiology is not merely a technical obstacle, but rather reflects clinical reality and, when addressed adequately in the solution process, provides a novel link between mathematically described physiological knowledge and the clinical concept of differential diagnoses. We outline possible steps toward translating this computational approach to the bedside, to supplement today's evidence-based medicine with a quantitatively founded model-based medicine that integrates mechanistic knowledge with patient-specific information.     

The influence of native populations’ genetic history on the reconstruction of invasion routes: the case of a highly invasive aquatic species

Biological Invasions - Insufficient data on the origins of the first introduced propagule and the initial stages of invasion complicate the reconstruction of a species’ invasion history....     

Extracellular hemoglobin combined with an O2-generating material overcomes O2 limitation in the bioartificial pancreas

The bioartificial pancreas encapsulating pancreatic islets in immunoprotective hydrogel is a promising therapy for Type 1 diabetes. As pancreatic islets are highly metabolically active and exquisitely sensitive to hypoxia, maintaining O₂ supply after transplantation remains a major challenge. In this study, we address the O₂ limitation by combining silicone-encapsulated CaO₂ (silicone-CaO₂) to generate O₂ with an extracellular hemoglobin O₂-carrier coencapsulated with islets. We showed that the hemoglobin improved by 37% the O₂-diffusivity through an alginate hydrogel and displayed antioxidant properties neutralizing deleterious reactive O₂ species produced by silicone-CaO₂. While the hemoglobin alone failed to maintain alginate macroencapsulated neonate pig islets under hypoxia, silicone-CaO₂ alone or combined to the hemoglobin restored islet viability and insulin secretion and prevented proinflammatory metabolism (PTGS2 expression). Interestingly, the combination took the advantages of the two individual strategies, improved neonate pig islet viability and insulin secretion in normoxia, and VEGF secretion and PDK1 normalization in hypoxia. Moreover, we confirmed the specific benefits of the combination compared to silicone-CaO₂ alone on murine pseudo-islet viability in normoxia and hypoxia. For the first time, our results show the interest of combining an O₂ provider with hemoglobin as an effective strategy to overcome O₂ limitations in tissue engineering.     

Structural investigation of the complexation properties between horse spleen apoferritin and metalloporphyrins

Crystallographic studies of L-chain horse spleen apoferritin (HSF) co-crystallized with Pt-hematoporphyrin IX and Sn-protoporphyrin IX have brought significant new insights into structure-function relationships in ferritins. Interactions of HSF with porphyrins are discussed. Structural results show that the nestling properties into HSF are dependent on the porphyrin moiety. (Only protoporphyrin IX significantly interacts with the protein, whereas hematoporphyrin IX does not.) These studies additionally point out the L-chain HSF ability to demetalate metalloporphyrins, a result which is of importance in looking at the iron storage properties of ferritins. In both compound investigated (whether the porphyrin reaches the binding site or not), the complexation appears to be concomitant with the extraction of the metal from the porphyrin. To analyze further the previous results, a three-dimensional alignment of ferritin sequences based on available crystallographic coordinates, including the present structures, is given. It confirms a high degree of homology between these members of the ferritin family and thus allows us to emphasize observed structural differences: 1) unlike L-chain HSF, H-chain human ferritin presents no preformed binding site; and 2) despite the absence of axial ligands, and due to the demetalation, L-chain HSF is able to host protoporphyrin at a similar location to that naturally found in bacterioferritin.     

Electronic tags for the tracking of insects in flight: effect of weight on flight performance of adult Colorado potato beetles

The wing loading of the Colorado potato beetle, Leptinotarsa decemlineata (Say) (Coleoptera: Chrysomelidae), was found to decrease slightly with increasing size over a wide range of individual sizes and independent of sex. This makes it possible to use tags of the same weight for beetles of all sizes and suggests that if the addition of light electronic tags has any effect on the beetle's flight it will be similar across beetle size. The wing loading of individual potato beetles ranged from an average minimum 10.9 N m^–2 to an average maximum of 15.6 N m^–2 as their weights fluctuated over time following water and food uptake or dispersal. However, tests carried out in flight chambers indicate that beetles become incapable of upward flight as they go beyond an average wing loading of 11.8 N m^–2, that is 101 N (10.3 mg) beyond their minimum weight. It is estimated from our results that electronic tags should weigh no more than 23–33% of the potato beetle's acceptable extra loading for the technique to have no or minimal impact on the number and quality of upward flights taken.     

X-ray structure of TMP kinase from Mycobacterium tuberculosis complexed with TMP at 1.95 A resolution

The X-ray structure of Mycobacterium tuberculosis TMP kinase at 1.95 A resolution is described as a binary complex with its natural substrate TMP. Its main features involve: (i) a clear magnesium-binding site; (ii) an alpha-helical conformation for the so-called LID region; and (iii) a high density of positive charges in the active site. There is a network of interactions involving highly conserved side-chains of the protein, the magnesium ion, a sulphate ion mimicking the beta phosphate group of ATP and the TMP molecule itself. All these interactions conspire in stabilizing what appears to be the closed form of the enzyme. A complete multialignment of all (32) known sequences of TMP kinases is presented. Subtle differences in the TMP binding site were noted, as compared to the Escherichia coli, yeast and human enzyme structures, which have been reported recently. These differences could be used to design specific inhibitors of this essential enzyme of nucleotide metabolism. Two cases of compensatory mutations were detected in the TMP binding site of eukaryotic and prokaryotic enzymes. In addition, an intriguing high value of the electric field is reported in the vicinity of the phosphate group of TMP and the putative binding site of the gamma phosphate group of ATP.     

The putative bioactive surface of insect-selective scorpion excitatory neurotoxins

Scorpion neurotoxins of the excitatory group show total specificity for insects and serve as invaluable probes for insect sodium channels. However, despite their significance and potential for application in insect-pest control, the structural basis for their bioactivity is still unknown. We isolated, characterized, and expressed an atypically long excitatory toxin, Bj-xtrIT, whose bioactive features resembled those of classical excitatory toxins, despite only 49% sequence identity. With the objective of clarifying the toxic site of this unique pharmacological group, Bj-xtrIT was employed in a genetic approach using point mutagenesis and biological and structural assays of the mutant products. A primary target for modification was the structurally unique C-terminal region. Sequential deletions of C-terminal residues suggested an inevitable significance of Ile73 and Ile74 for toxicity. Based on the bioactive role of the C-terminal region and a comparison of Bj-xtrIT with a Bj-xtrIT-based model of a classical excitatory toxin, AaHIT, a conserved surface comprising the C terminus is suggested to form the site of recognition with the sodium channel receptor.