Locomotor Mode and the Evolution of the Hindlimb in Western Mediterranean Anurans

Evolutionary Biology - The evolutionary association between morphology, locomotor performance and habitat use is a central element of the ecomorphological paradigm, and it is known to underlie the...     

Large-scale de novo prediction of physical protein-protein association

Information about the physical association of proteins is extensively used for studying cellular processes and disease mechanisms. However, complete experimental mapping of the human interactome will remain prohibitively difficult in the near future. Here we present a map of predicted human protein interactions that distinguishes functional association from physical binding. Our network classifies more than 5 million protein pairs predicting 94,009 new interactions with high confidence. We experimentally tested a subset of these predictions using yeast two-hybrid analysis and affinity purification followed by quantitative mass spectrometry. Thus we identified 462 new protein-protein interactions and confirmed the predictive power of the network. These independent experiments address potential issues of circular reasoning and are a distinctive feature of this work. Analysis of the physical interactome unravels subnetworks mediating between different functional and physical subunits of the cell. Finally, we demonstrate the utility of the network for the analysis of molecular mechanisms of complex diseases by applying it to genome-wide association studies of neurodegenerative diseases. This analysis provides new evidence implying TOMM40 as a factor involved in Alzheimer's disease. The network provides a high-quality resource for the analysis of genomic data sets and genetic association studies in particular. Our interactome is available via the hPRINT web server at: www.print-db.org.     

Sexual dimorphism in bill morphology and feeding ecology in Cory's shearwater (Calonectris diomedea)

The bill is a sexually dimorphic structure in many bird species and implicated in numerous functions. Sexual differences may arise from sexual selection or ecological divergence. Here, we examined differences in bill size and shape between males and females and explored to what extent these relate to feeding ecology of each sex in Cory's shearwater (Calonectris diomedea). We applied linear measurements and geometric morphometric methods to examine sexual differences in bill size and shape. We investigated feeding ecology by tracking foraging movements during the breeding period and by analysing stable isotope signatures in blood during the breeding period and in feathers grown during the non-breeding period. Bill traits were all sexually dimorphic, both in absolute and relative terms, and scaled hypermetrically with body mass in several characters in males. However, males and females did not differ in their feeding areas or isotopic signatures and no significant correlation was observed between these traits and bill dimorphism. Therefore, we discard the foraging-niche divergence hypothesis, and suggest that sexual dimorphism in bill size in this species is more likely driven by sexual selection related to antagonistic interactions.     

Genetic polymorphisms within tumor necrosis factor gene promoter region: a role for susceptibility to ventilator-associated pneumonia

Debatable findings exist among various studies regarding the impact of single nucleotide polymorphisms (SNPs) within the promoter region of the tumor necrosis factor (TNF) gene for susceptibility to infections. Their impact was investigated in a cohort of mechanically ventilated patients who developed ventilator-associated pneumonia (VAP). Two-hundred and thirteen mechanically ventilated patients who developed VAP were enrolled. Genomic DNA was extracted and SNPs at the -376, -308 and -238 position of the promoter region of the TNF gene were assessed by restriction fragment length polymorphisms. Monocytes were isolated from 47 patients when they developed sepsis and stimulated by bacterial endotoxin for the production of TNFα and of interleukin-6 (IL-6). Patients were divided into two groups; 166 patients bearing only wild-type alleles of all three studied polymorphisms; and 47 patients carrying at least one A allele of the three studied SNPs. Time between start of mechanical ventilation and advent of VAP was significantly shorter in the second group than in the first group (log-rank: 4.416, p: 0.041). When VAP supervened, disease severity did not differ between groups. Stimulation of TNFα and of IL-6 was much greater by monocytes for patients carrying A alleles. Carriage of at least one A allele of the three studied SNPs at the promoter region of the TNF-gene is associated with shorter time to development of VAP but it is not associated with disease severity. Findings may be related with a role of the studied SNPs in the production of pro-inflammatory cytokines.     

A Bayesian inference scheme to extract diffusivity and potential fields from confined single-molecule trajectories

Currently used techniques for the analysis of single-molecule trajectories only exploit a small part of the available information stored in the data. Here, we apply a Bayesian inference scheme to trajectories of confined receptors that are targeted by pore-forming toxins to extract the two-dimensional confining potential that restricts the motion of the receptor. The receptor motion is modeled by the overdamped Langevin equation of motion. The method uses most of the information stored in the trajectory and converges quickly onto inferred values, while providing the uncertainty on the determined values. The inference is performed on the polynomial development of the potential and on the diffusivities that have been discretized on a mesh. Numerical simulations are used to test the scheme and quantify the convergence toward the input values for forces, potential, and diffusivity. Furthermore, we show that the technique outperforms the classical mean-square-displacement technique when forces act on confined molecules because the typical mean-square-displacement analysis does not account for them. We also show that the inferred potential better represents input potentials than the potential extracted from the position distribution based on Boltzmann statistics that assumes statistical equilibrium.     

Maintenance of the keratocyte phenotype during cell proliferation stimulated by insulin

Keratocytes normally express high levels of aldehyde dehydrogenase and keratocan. They proliferate and lose their keratocyte markers when they become fibroblastic during corneal wound healing. Keratocytes cultured in fetal bovine serum also become fibroblastic, proliferate, and lose these markers. In this report, we studied the effects of three serum growth factors, fibroblast growth factor-2, insulin, and platelet-derived growth factor-BB, on keratocyte proliferation and the maintenance of the keratocyte markers in 7-day cultures in cells plated at low (5,000 cells/cm2) and high (20,000 cells/cm2) density in serum-free medium. Keratocyte proliferation was measured by [3H]thymidine incorporation and by DNA content of the cultures. Cytosolic aldehyde dehydrogenase and keratocan accumulated in the medium were quantified by Western blot. The results showed that all the growth factors stimulated proliferation, but insulin stimulated proliferation more consistently. The keratocyte markers aldehyde dehydrogenase and keratocan were maintained after 7 days in culture in all growth factors, but keratocyte cell morphology was only maintained in medium containing insulin. Most of the proteoglycans were degraded in cultures of keratocytes plated at low density and cultured in the absence of growth factors. This degradation was prevented when keratocytes were cultured in the presence of the growth factors or when keratocytes were plated at high density. The results of this study show that insulin can expand keratocytes in vitro, maintain their phenotype, and prevent proteoglycan degradation.     

Delta-like Ligand-4-Notch Signaling Inhibition Regulates Pancreatic Islet Function and Insulin Secretion

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A Primer on the Bayesian Approach to High-Density Single-Molecule Trajectories Analysis

Tracking single molecules in living cells provides invaluable information on their environment and on the interactions that underlie their motion. New experimental techniques now permit the recording of large amounts of individual trajectories, enabling the implementation of advanced statistical tools for data analysis. In this primer, we present a Bayesian approach toward treating these data, and we discuss how it can be fruitfully employed to infer physical and biochemical parameters from single-molecule trajectories.