Dissecting carotenoid from structural components of carotenoid-based coloration: a field experiment with great tits (Parus major).

Carotenoid-based yellowish to red plumage colors are widespread visual signals used in sexual and social communication. To understand their ultimate signaling functions, it is important to identify the proximate mechanism promoting variation in coloration. Carotenoid-based colors combine structural and pigmentary components, but the importance of the contribution of structural components to variation in pigment-based colors (i.e., carotenoid-based colors) has been undervalued. In a field experiment with great tits (Parus major), we combined a brood size manipulation with a simultaneous carotenoid supplementation in order to disentangle the effects of carotenoid availability and early growth condition on different components of the yellow breast feathers. By defining independent measures of feather carotenoid content (absolute carotenoid chroma) and background structure (background reflectance), we demonstrate that environmental factors experienced during the nestling period, namely, early growth conditions and carotenoid availability, contribute independently to variation in yellow plumage coloration. While early growth conditions affected the background reflectance of the plumage, the availability of carotenoids affected the absolute carotenoid chroma, the peak of maximum ultraviolet reflectance, and the overall shape, that is, chromatic information of the reflectance curves. These findings demonstrate that environment-induced variation in background structure contributes significantly to intraspecific variation in yellow carotenoid-based plumage coloration.

In silico prediction of human carboxylesterase-1 (hCES1) metabolism combining docking analyses and MD simulations.

Metabolic problems lead to numerous failures during clinical trials, and much effort is now devoted in developing in silico models predicting metabolic stability and metabolites. Such models are well known for cytochromes P450 and some transferases, whereas little has been done to predict the hydrolytic activity of human hydrolases. The present study was undertaken to develop a computational approach able to predict the hydrolysis of novel esters by human carboxylesterase hCES1. The study involves both docking analyses of known substrates to develop predictive models, and molecular dynamics (MD) simulations to reveal the in situ behavior of substrates and products, with particular attention being paid to the influence of their ionization state. The results emphasize some crucial properties of the hCES1 catalytic cavity, confirming that as a trend with several exceptions, hCES1 prefers substrates with relatively smaller and somewhat polar alkyl/aryl groups and larger hydrophobic acyl moieties. The docking results underline the usefulness of the hydrophobic interaction score proposed here, which allows a robust prediction of hCES1 catalysis, while the MD simulations show the different behavior of substrates and products in the enzyme cavity, suggesting in particular that basic substrates interact with the enzyme in their unprotonated form.

Extremity and eye lens doses in interventional radiology and cardiology procedures: first results of the ORAMED project.

The main objective of WP1 of the ORAMED (Optimization of RAdiation protection for MEDical staff) project is to obtain a set of standardised data on extremity and eye lens doses for staff in interventional radiology (IR) and cardiology (IC) and to optimise staff protection. A coordinated measurement program in different hospitals in Europe will help towards this direction. This study aims at analysing the first results of the measurement campaign performed in IR and IC procedures in 34 European hospitals. The highest doses were found for pacemakers, renal angioplasties and embolisations. Left finger and wrist seem to receive the highest extremity doses, while the highest eye lens doses are measured during embolisations. Finally, it was concluded that it is difficult to find a general correlation between kerma area product and extremity or eye lens doses.

Synchronous versus asynchronous modeling of gene regulatory networks.

MOTIVATION: In silico modeling of gene regulatory networks has gained some momentum recently due to increased interest in analyzing the dynamics of biological systems. This has been further facilitated by the increasing availability of experimental data on gene-gene, protein-protein and gene-protein interactions. The two dynamical properties that are often experimentally testable are perturbations and stable steady states. Although a lot of work has been done on the identification of steady states, not much work has been reported on in silico modeling of cellular differentiation processes. RESULTS: In this manuscript, we provide algorithms based on reduced ordered binary decision diagrams (ROBDDs) for Boolean modeling of gene regulatory networks. Algorithms for synchronous and asynchronous transition models have been proposed and their corresponding computational properties have been analyzed. These algorithms allow users to compute cyclic attractors of large networks that are currently not feasible using existing software. Hereby we provide a framework to analyze the effect of multiple gene perturbation protocols, and their effect on cell differentiation processes. These algorithms were validated on the T-helper model showing the correct steady state identification and Th1-Th2 cellular differentiation process. AVAILABILITY: The software binaries for Windows and Linux platforms can be downloaded from http://si2.epfl.ch/~garg/genysis.html.

A modular approach for integrative analysis of large-scale gene-expression and drug-response data

High-throughput technologies are now used to generate more than one type of data from the same biological samples. To properly integrate such data, we propose using co-modules, which describe coherent patterns across paired data sets, and conceive several modular methods for their identification. We first test these methods using in silico data, demonstrating that the integrative scheme of our Ping-Pong Algorithm uncovers drug-gene associations more accurately when considering noisy or complex data. Second, we provide an extensive comparative study using the gene-expression and drug-response data from the NCI-60 cell lines. Using information from the DrugBank and the Connectivity Map databases we show that the Ping-Pong Algorithm predicts drug-gene associations significantly better than other methods. Co-modules provide insights into possible mechanisms of action for a wide range of drugs and suggest new targets for therapy

Comparison between computational alanine scanning and per-residue binding free energy decomposition for protein-protein association using MM-GBSA: application to the TCR-p-MHC complex.

Recognition by the T-cell receptor (TCR) of immunogenic peptides (p) presented by Class I major histocompatibility complexes (MHC) is the key event in the immune response against virus-infected cells or tumor cells. A study of the 2C TCR/SIYR/H-2K(b) system using a computational alanine scanning and a much faster binding free energy decomposition based on the Molecular Mechanics-Generalized Born Surface Area (MM-GBSA) method is presented. The results show that the TCR-p-MHC binding free energy decomposition using this approach and including entropic terms provides a detailed and reliable description of the interactions between the molecules at an atomistic level. Comparison of the decomposition results with experimentally determined activity differences for alanine mutants yields a correlation of 0.67 when the entropy is neglected and 0.72 when the entropy is taken into account. Similarly, comparison of experimental activities with variations in binding free energies determined by computational alanine scanning yields correlations of 0.72 and 0.74 when the entropy is neglected or taken into account, respectively. Some key interactions for the TCR-p-MHC binding are analyzed and some possible side chains replacements are proposed in the context of TCR protein engineering. In addition, a comparison of the two theoretical approaches for estimating the role of each side chain in the complexation is given, and a new ad hoc approach to decompose the vibrational entropy term into atomic contributions, the linear decomposition of the vibrational entropy (LDVE), is introduced. The latter allows the rapid calculation of the entropic contribution of interesting side chains to the binding. This new method is based on the idea that the most important contributions to the vibrational entropy of a molecule originate from residues that contribute most to the vibrational amplitude of the normal modes. The LDVE approach is shown to provide results very similar to those of the exact but highly computationally demanding method.

Differential roles of T cell receptor alpha and beta chains in ligand binding among H-2Kd-restricted cytolytic T lymphocyte clones specific for a photoreactive Plasmodium berghei circumsporozoite peptide derivative.

To study the interaction of T cell receptor with its ligand, a complex of a major histocompatibility complex molecule and a peptide, we derived H-2Kd-restricted cytolytic T lymphocyte clones from mice immunized with a Plasmodium berghei circumsporozoite peptide (PbCS) 252-260 (SYIPSAEKI) derivative containing photoreactive Nepsilon-[4-azidobenzoyl] lysine in place of Pro-255. This residue and Lys-259 were essential parts of the epitope recognized by these clones. Most of the clones expressed BV1S1A1 encoded beta chains along with specific complementary determining region (CDR) 3beta regions but diverse alpha chain sequences. Surprisingly, all T cell receptors were preferentially photoaffinity labeled on the alpha chain. For a representative T cell receptor, the photoaffinity labeled site was located in the Valpha C-strand. Computer modeling suggested the presence of a hydrophobic pocket, which is formed by parts of the Valpha/Jalpha C-, F-, and G-strands and adjacent CDR3alpha residues and structured to be able to avidly bind the photoreactive ligand side chain. We previously found that a T cell receptor specific for a PbCS peptide derivative containing this photoreactive side chain in position 259 similarly used a hydrophobic pocket located between the junctional CDR3 loops. We propose that this nonpolar domain in these locations allow T cell receptors to avidly and specifically bind epitopes containing non-peptidic side chains.

Application de la modélisation moléculaire à de nouvelles approches thérapeutiques du cancer [Application of molecular modeling to new therapeutic cancer approaches].

Recent progress in the experimental determination of protein structures allow to understand, at a very detailed level, the molecular recognition mechanisms that are at the basis of the living matter. This level of understanding makes it possible to design rational therapeutic approaches, in which effectors molecules are adapted or created de novo to perform a given function. An example of such an approach is drug design, were small inhibitory molecules are designed using in silico simulations and tested in vitro. In this article, we present a similar approach to rationally optimize the sequence of killer T lymphocytes receptors to make them more efficient against melanoma cells. The architecture of this translational research project is presented together with its implications both at the level of basic research as well as in the clinics.

MAMOT: hidden Markov modeling tool.

Hidden Markov models (HMMs) are probabilistic models that are well adapted to many tasks in bioinformatics, for example, for predicting the occurrence of specific motifs in biological sequences. MAMOT is a command-line program for Unix-like operating systems, including MacOS X, that we developed to allow scientists to apply HMMs more easily in their research. One can define the architecture and initial parameters of the model in a text file and then use MAMOT for parameter optimization on example data, decoding (like predicting motif occurrence in sequences) and the production of stochastic sequences generated according to the probabilistic model. Two examples for which models are provided are coiled-coil domains in protein sequences and protein binding sites in DNA. A wealth of useful features include the use of pseudocounts, state tying and fixing of selected parameters in learning, and the inclusion of prior probabilities in decoding. AVAILABILITY: MAMOT is implemented in C++, and is distributed under the GNU General Public Licence (GPL). The software, documentation, and example model files can be found at http://bcf.isb-sib.ch/mamot

Multivariate QST-FST comparisons: a neutrality test for the evolution of the g matrix in structured populations.

Neutrality tests in quantitative genetics provide a statistical framework for the detection of selection on polygenic traits in wild populations. However, the existing method based on comparisons of divergence at neutral markers and quantitative traits (Q(st)-F(st)) suffers from several limitations that hinder a clear interpretation of the results with typical empirical designs. In this article, we propose a multivariate extension of this neutrality test based on empirical estimates of the among-populations (D) and within-populations (G) covariance matrices by MANOVA. A simple pattern is expected under neutrality: D = 2F(st)/(1 - F(st))G, so that neutrality implies both proportionality of the two matrices and a specific value of the proportionality coefficient. This pattern is tested using Flury's framework for matrix comparison [common principal-component (CPC) analysis], a well-known tool in G matrix evolution studies. We show the importance of using a Bartlett adjustment of the test for the small sample sizes typically found in empirical studies. We propose a dual test: (i) that the proportionality coefficient is not different from its neutral expectation [2F(st)/(1 - F(st))] and (ii) that the MANOVA estimates of mean square matrices between and among populations are proportional. These two tests combined provide a more stringent test for neutrality than the classic Q(st)-F(st) comparison and avoid several statistical problems. Extensive simulations of realistic empirical designs suggest that these tests correctly detect the expected pattern under neutrality and have enough power to efficiently detect mild to strong selection (homogeneous, heterogeneous, or mixed) when it is occurring on a set of traits. This method also provides a rigorous and quantitative framework for disentangling the effects of different selection regimes and of drift on the evolution of the G matrix. We discuss practical requirements for the proper application of our test in empirical studies and potential extensions.

The spread of incompatibility-inducing parasites in sub-divided host populations.

BACKGROUND:Maternally transmitted symbionts have evolved a variety of ways to promote their spread through host populations. One strategy is to hamper the reproduction of uninfected females by a mechanism called cytoplasmic incompatibility (CI). CI occurs in crosses between infected males and uninfected females and leads to partial to near-complete infertility. CI-infections are under positive frequency-dependent selection and require genetic drift to overcome the range of low frequencies where they are counter-selected. Given the importance of drift, population sub-division would be expected to facilitate the spread of CI. Nevertheless, a previous model concluded that variance in infection between competing groups of breeding individuals impedes the spread of CI.RESULTS:In this paper we derive a model on the spread of CI-infections in populations composed of demes linked by restricted migration. Our model shows that population sub-division facilitates the invasion of CI. While host philopatry (low migration) favours the spread of infection, deme size has a non-monotonous effect, with CI-invasion being most likely at intermediate deme size. Individual-based simulations confirm these predictions and show that high levels of local drift speed up invasion but prevent high levels of prevalence across the entire population. Additional simulations with sex-specific migration rates further show that low migration rates of both sexes are required to facilitate the spread of CI.CONCLUSION:Our analyses show that population structure facilitates the invasion of CI-infections. Since some level of sub-division is likely to occur in most natural populations, our results help to explain the high incidence of CI-infections across species of arthropods. Furthermore, our work has important implications for the use of CI-systems in order to genetically modify natural populations of disease vectors.

Symmetry-breaking in cumulative measures of shapes of polymer models.

Using numerical simulations we investigate shapes of random equilateral open and closed chains, one of the simplest models of freely fluctuating polymers in a solution. We are interested in the 3D density distribution of the modeled polymers where the polymers have been aligned with respect to their three principal axes of inertia. This type of approach was pioneered by Theodorou and Suter in 1985. While individual configurations of the modeled polymers are almost always nonsymmetric, the approach of Theodorou and Suter results in cumulative shapes that are highly symmetric. By taking advantage of asymmetries within the individual configurations, we modify the procedure of aligning independent configurations in a way that shows their asymmetry. This approach reveals, for example, that the 3D density distribution for linear polymers has a bean shape predicted theoretically by Kuhn. The symmetry-breaking approach reveals complementary information to the traditional, symmetrical, 3D density distributions originally introduced by Theodorou and Suter.

Incompletely resolved phylogenetic trees inflate estimates of phylogenetic conservatism.

The tendency for more closely related species to share similar traits and ecological strategies can be explained by their longer shared evolutionary histories and represents phylogenetic conservatism. How strongly species traits co-vary with phylogeny can significantly impact how we analyze cross-species data and can influence our interpretation of assembly rules in the rapidly expanding field of community phylogenetics. Phylogenetic conservatism is typically quantified by analyzing the distribution of species values on the phylogenetic tree that connects them. Many phylogenetic approaches, however, assume a completely sampled phylogeny: while we have good estimates of deeper phylogenetic relationships for many species-rich groups, such as birds and flowering plants, we often lack information on more recent interspecific relationships (i.e., within a genus). A common solution has been to represent these relationships as polytomies on trees using taxonomy as a guide. Here we show that such trees can dramatically inflate estimates of phylogenetic conservatism quantified using S. P. Blomberg et al.'s K statistic. Using simulations, we show that even randomly generated traits can appear to be phylogenetically conserved on poorly resolved trees. We provide a simple rarefaction-based solution that can reliably retrieve unbiased estimates of K, and we illustrate our method using data on first flowering times from Thoreau's woods (Concord, Massachusetts, USA).

Access of extracellular cations to their binding sites in Na,K-ATPase: role of the second extracellular loop of the alpha subunit.

Na,K-ATPase, the main active transport system for monovalent cations in animal cells, is responsible for maintaining Na(+) and K(+) gradients across the plasma membrane. During its transport cycle it binds three cytoplasmic Na(+) ions and releases them on the extracellular side of the membrane, and then binds two extracellular K(+) ions and releases them into the cytoplasm. The fourth, fifth, and sixth transmembrane helices of the alpha subunit of Na,K-ATPase are known to be involved in Na(+) and K(+) binding sites, but the gating mechanisms that control the access of these ions to their binding sites are not yet fully understood. We have focused on the second extracellular loop linking transmembrane segments 3 and 4 and attempted to determine its role in gating. We replaced 13 residues of this loop in the rat alpha1 subunit, from E314 to G326, by cysteine, and then studied the function of these mutants using electrophysiological techniques. We analyzed the results using a structural model obtained by homology with SERCA, and ab initio calculations for the second extracellular loop. Four mutants were markedly modified by the sulfhydryl reagent MTSET, and we investigated them in detail. The substituted cysteines were more readily accessible to MTSET in the E1 conformation for the Y315C, W317C, and I322C mutants. Mutations or derivatization of the substituted cysteines in the second extracellular loop resulted in major increases in the apparent affinity for extracellular K(+), and this was associated with a reduction in the maximum activity. The changes produced by the E314C mutation were reversed by MTSET treatment. In the W317C and I322C mutants, MTSET also induced a moderate shift of the E1/E2 equilibrium towards the E1(Na) conformation under Na/Na exchange conditions. These findings indicate that the second extracellular loop must be functionally linked to the gating mechanism that controls the access of K(+) to its binding site.