Blood pressure normalization in a large population of hypertensive patients treated with perindopril/indapamide combination: results of the OPTIMAX trial.

OBJECTIVE: To determine if the fixed-dose perindopril/indapamide combination (Per/Ind) normalizes blood pressure (BP) in the same fraction of hypertensive patients when treated in everyday practice or in controlled trials. METHODS: In this prospective trial, 17 938 hypertensive patients were treated with Per 2 mg/Ind 0.625 mg for 3-6 months. In Group 1 Per/Ind was initiated in newly diagnosed patients (n = 7032); in Group 2 Per/Ind replaced previous therapy in patients already treated but having either their BP still uncontrolled or experiencing side-effects (n = 7423); in Group 3 Per/Ind was added to previous treatment in patients with persistently high BP (n = 3483). BP was considered normalized when < or = 140/90 mm Hg. A multivariate analysis for predictors of BP normalization was performed. RESULTS: Subjects were on average 62 years old and had a baseline BP of 162.3/93.6 mm Hg. After treatment with Per/Ind, BP normalization was reached in 69.6% of patients in the Initiation group, 67.5% in the Replacement Group, and 67.4% in the Add-on Group (where patients were more frequently at risk, diabetic, or with target organ damage). Mean decreases in systolic BP of 22.8 mm Hg and in diastolic BP of 12.4 mm Hg were recorded. CONCLUSIONS: This trial was established to reflect everyday clinical practice, and a treatment strategy based on the Per/Ind combination, administered as initial, replacement, or add-on therapy, led to normalization rates that were superior to those observed in Europe in routine practice. These results support recent hypertension guidelines which encourage the use of combination therapy in the management of arterial hypertension.

Bacterial and viral superantigens: roles in autoimmunity?

Superantigens are bacterial, viral, or retroviral proteins which can activate specifically a large proportion of T cells. In contrast with classical peptide antigen recognition, superantigens do not require processing to small peptides but act as complete or partially processed proteins. They can bind to major histocompatibility complex class II molecules and stimulate T cells expressing particular T cell receptor V beta chains. The other polymorphic parts of the T cell receptor, which are crucial for classical antigen recognition, are not important for this interaction. When this strategy is used a large proportion of the host immune system can be activated shortly after infection. The activated cells have a wide variety of antigen specificities. The ability to stimulate polyclonal B (IgG) as well as T cell responses raises possibilities of a role for superantigens in the induction of autoimmune diseases. Superantigens have been a great tool in the hands of immunologists in unravelling some of the basic mechanisms of tolerance and immunity.

Analyses of six homologous proteins of Protochlamydia amoebophila UWE25 encoded by large GC-rich genes (lgr): a model of evolution and concatenation of leucine-rich repeats.

BACKGROUND: Along the chromosome of the obligate intracellular bacteria Protochlamydia amoebophila UWE25, we recently described a genomic island Pam100G. It contains a tra unit likely involved in conjugative DNA transfer and lgrE, a 5.6-kb gene similar to five others of P. amoebophila: lgrA to lgrD, lgrF. We describe here the structure, regulation and evolution of these proteins termed LGRs since encoded by "Large G+C-Rich" genes. RESULTS: No homologs to the whole protein sequence of LGRs were found in other organisms. Phylogenetic analyses suggest that serial duplications producing the six LGRs occurred relatively recently and nucleotide usage analyses show that lgrB, lgrE and lgrF were relocated on the chromosome. The C-terminal part of LGRs is homologous to Leucine-Rich Repeats domains (LRRs). Defined by a cumulative alignment score, the 5 to 18 concatenated octacosapeptidic (28-meric) LRRs of LGRs present all a predicted alpha-helix conformation. Their closest homologs are the 28-residue RI-like LRRs of mammalian NODs and the 24-meres of some Ralstonia and Legionella proteins. Interestingly, lgrE, which is present on Pam100G like the tra operon, exhibits Pfam domains related to DNA metabolism. CONCLUSION: Comparison of the LRRs, enable us to propose a parsimonious evolutionary scenario of these domains driven by adjacent concatenations of LRRs. Our model established on bacterial LRRs can be challenged in eucaryotic proteins carrying less conserved LRRs, such as NOD proteins and Toll-like receptors.

Evolutionary dynamics of coding and non-coding transcriptomes.

Gene expression changes may underlie much of phenotypic evolution. The development of high-throughput RNA sequencing protocols has opened the door to unprecedented large-scale and cross-species transcriptome comparisons by allowing accurate and sensitive assessments of transcript sequences and expression levels. Here, we review the initial wave of the new generation of comparative transcriptomic studies in mammals and vertebrate outgroup species in the context of earlier work. Together with various large-scale genomic and epigenomic data, these studies have unveiled commonalities and differences in the dynamics of gene expression evolution for various types of coding and non-coding genes across mammalian lineages, organs, developmental stages, chromosomes and sexes. They have also provided intriguing new clues to the regulatory basis and phenotypic implications of evolutionary gene expression changes.

Phylogenomics of C(4) photosynthesis in sedges (Cyperaceae): multiple appearances and genetic convergence.

C(4) photosynthesis is an adaptive trait conferring an advantage in warm and open habitats. It originated multiple times and is currently reported in 18 plant families. It has been recently shown that phosphoenolpyruvate carboxylase (PEPC), a key enzyme of the C(4) pathway, evolved through numerous independent but convergent genetic changes in grasses (Poaceae). To compare the genetics of multiple C(4) origins on a broader scale, we reconstructed the evolutionary history of the C(4) pathway in sedges (Cyperaceae), the second most species-rich C(4) family. A sedge phylogeny based on two plastome genes (rbcL and ndhF) has previously identified six fully C(4) clades. Here, a relaxed molecular clock was used to calibrate this tree and showed that the first C(4) acquisition occurred in this family between 19.6 and 10.1 Ma. According to analyses of PEPC-encoding genes (ppc), at least five distinct C(4) origins are present in sedges. Two C(4) Eleocharis species, which were unrelated in the plastid phylogeny, acquired their C(4)-specific PEPC genes from a single source, probably through reticulate evolution or a horizontal transfer event. Acquisitions of C(4) PEPC in sedges have been driven by positive selection on at least 16 codons (3.5% of the studied gene segment). These sites underwent parallel genetic changes across the five sedge C(4) origins. Five of these sites underwent identical changes also in grass and eudicot C(4) lineages, indicating that genetic convergence is most important within families but that identical genetic changes occurred even among distantly related taxa. These lines of evidence give new insights into the constraints that govern molecular evolution.

Large scale assessment of regulatory evolution and transcriptome complexity in mammals

AbstractIn addition to genetic changes affecting the function of gene products, changes in gene expression have been suggested to underlie many or even most of the phenotypic differences among mammals. However, detailed gene expression comparisons were, until recently, restricted to closely related species, owing to technological limitations. Thus, we took advantage of the latest technologies (RNA-Seq) to generate extensive qualitative and quantitative transcriptome data for a unique collection of somatic and germline tissues from representatives of all major mammalian lineages (placental mammals, marsupials and monotremes) and birds, the evolutionary outgroup.In the first major project of my thesis, we performed global comparative analyses of gene expression levels based on these data. Our analyses provided fundamental insights into the dynamics of transcriptome change during mammalian evolution (e.g., the rate of expression change across species, tissues and chromosomes) and allowed the exploration of the functional relevance and phenotypic implications of transcription changes at a genome-wide scale (e.g., we identified numerous potentially selectively driven expression switches).In a second project of my thesis, which was also based on the unique transcriptome data generated in the context of the first project we focused on the evolution of alternative splicing in mammals. Alternative splicing contributes to transcriptome complexity by generating several transcript isoforms from a single gene, which can, thus, perform various functions. To complete the global comparative analysis of gene expression changes, we explored patterns of alternative splicing evolution. This work uncovered several general and unexpected patterns of alternative splicing evolution (e.g., we found that alternative splicing evolves extremely rapidly) as well as a large number of conserved alternative isoforms that may be crucial for the functioning of mammalian organs.Finally, the third and final project of my PhD consisted in analyzing in detail the unique functional and evolutionary properties of the testis by exploring the extent of its transcriptome complexity. This organ was previously shown to evolve rapidly both at the phenotypic and molecular level, apparently because of the specific pressures that act on this organ and are associated with its reproductive function. Moreover, my analyses of the amniote tissue transcriptome data described above, revealed strikingly widespread transcriptional activity of both functional and nonfunctional genomic elements in the testis compared to the other organs. To elucidate the cellular source and mechanisms underlying this promiscuous transcription in the testis, we generated deep coverage RNA-Seq data for all major testis cell types as well as epigenetic data (DNA and histone methylation) using the mouse as model system. The integration of these complete dataset revealed that meiotic and especially post-meiotic germ cells are the major contributors to the widespread functional and nonfunctional transcriptome complexity of the testis, and that this "promiscuous" spermatogenic transcription is resulting, at least partially, from an overall transcriptionally permissive chromatin state. We hypothesize that this particular open state of the chromatin results from the extensive chromatin remodeling that occurs during spermatogenesis which ultimately leads to the replacement of histones by protamines in the mature spermatozoa. Our results have important functional and evolutionary implications (e.g., regarding new gene birth and testicular gene expression evolution).Generally, these three large-scale projects of my thesis provide complete and massive datasets that constitute valuables resources for further functional and evolutionary analyses of mammalian genomes.

Premature replacement of mu with alpha immunoglobulin chains impairs lymphopoiesis and mucosal homing but promotes plasma cell maturation.

Sequentially along B cell differentiation, the different classes of membrane Ig heavy chains associate with the Ig alpha/Ig beta heterodimer within the B cell receptor (BCR). Whether each Ig class conveys specific signals adapted to the corresponding differentiation stage remains debated. We investigated the impact of the forced expression of an IgA-class receptor throughout murine B cell differentiation by knocking in the human C alpha Ig gene in place of the S mu region. Despite expression of a functional BCR, homozygous mutant mice showed a partial developmental blockade at the pro-B/pre-BI and large pre-BII cell stages, with decreased numbers of small pre-BII cells. Beyond this stage, peripheral B cell compartments of reduced size developed and allowed specific antibody responses, whereas mature cells showed constitutive activation and a strong commitment to plasma cell differentiation. Secreted IgA correctly assembled into polymers, associated with the murine J chain, and was transported into secretions. In heterozygous mutants, cells expressing the IgA allele competed poorly with those expressing IgM from the wild-type allele and were almost undetectable among peripheral B lymphocytes, notably in gut-associated lymphoid tissues. Our data indicate that the IgM BCR is more efficient in driving early B cell education and in mucosal site targeting, whereas the IgA BCR appears particularly suited to promoting activation and differentiation of effector plasma cells.

TCRep 3D: an automated in silico approach to study the structural properties of TCR repertoires.

TCRep 3D is an automated systematic approach for TCR-peptide-MHC class I structure prediction, based on homology and ab initio modeling. It has been considerably generalized from former studies to be applicable to large repertoires of TCR. First, the location of the complementary determining regions of the target sequences are automatically identified by a sequence alignment strategy against a database of TCR Vα and Vβ chains. A structure-based alignment ensures automated identification of CDR3 loops. The CDR are then modeled in the environment of the complex, in an ab initio approach based on a simulated annealing protocol. During this step, dihedral restraints are applied to drive the CDR1 and CDR2 loops towards their canonical conformations, described by Al-Lazikani et. al. We developed a new automated algorithm that determines additional restraints to iteratively converge towards TCR conformations making frequent hydrogen bonds with the pMHC. We demonstrated that our approach outperforms popular scoring methods (Anolea, Dope and Modeller) in predicting relevant CDR conformations. Finally, this modeling approach has been successfully applied to experimentally determined sequences of TCR that recognize the NY-ESO-1 cancer testis antigen. This analysis revealed a mechanism of selection of TCR through the presence of a single conserved amino acid in all CDR3β sequences. The important structural modifications predicted in silico and the associated dramatic loss of experimental binding affinity upon mutation of this amino acid show the good correspondence between the predicted structures and their biological activities. To our knowledge, this is the first systematic approach that was developed for large TCR repertoire structural modeling.

Evolving team compositions by agent swapping

Optimizing collective behavior in multiagent systems requires algorithms to find not only appropriate individual behaviors but also a suitable composition of agents within a team. Over the last two decades, evolutionary methods have emerged as a promising approach for the design of agents and their compositions into teams. The choice of a crossover operator that facilitates the evolution of optimal team composition is recognized to be crucial, but so far, it has never been thoroughly quantified. Here, we highlight the limitations of two different crossover operators that exchange entire agents between teams: restricted agent swapping (RAS) that exchanges only corresponding agents between teams and free agent swapping (FAS) that allows an arbitrary exchange of agents. Our results show that RAS suffers from premature convergence, whereas FAS entails insufficient convergence. Consequently, in both cases, the exploration and exploitation aspects of the evolutionary algorithm are not well balanced resulting in the evolution of suboptimal team compositions. To overcome this problem, we propose combining the two methods. Our approach first applies FAS to explore the search space and then RAS to exploit it. This mixed approach is a much more efficient strategy for the evolution of team compositions compared to either strategy on its own. Our results suggest that such a mixed agent-swapping algorithm should always be preferred whenever the optimal composition of individuals in a multiagent system is unknown.

Rapid cohort generation and analysis of disease spectrum of large animal model of cone dystrophy.

Large animal models are an important resource for the understanding of human disease and for evaluating the applicability of new therapies to human patients. For many diseases, such as cone dystrophy, research effort is hampered by the lack of such models. Lentiviral transgenesis is a methodology broadly applicable to animals from many different species. When conjugated to the expression of a dominant mutant protein, this technology offers an attractive approach to generate new large animal models in a heterogeneous background. We adopted this strategy to mimic the phenotype diversity encounter in humans and generate a cohort of pigs for cone dystrophy by expressing a dominant mutant allele of the guanylate cyclase 2D (GUCY2D) gene. Sixty percent of the piglets were transgenic, with mutant GUCY2D mRNA detected in the retina of all animals tested. Functional impairment of vision was observed among the transgenic pigs at 3 months of age, with a follow-up at 1 year indicating a subsequent slower progression of phenotype. Abnormal retina morphology, notably among the cone photoreceptor cell population, was observed exclusively amongst the transgenic animals. Of particular note, these transgenic animals were characterized by a range in the severity of the phenotype, reflecting the human clinical situation. We demonstrate that a transgenic approach using lentiviral vectors offers a powerful tool for large animal model development. Not only is the efficiency of transgenesis higher than conventional transgenic methodology but this technique also produces a heterogeneous cohort of transgenic animals that mimics the genetic variation encountered in human patients.

Comparative performance of supertree algorithms in large data sets using the soapberry family (Sapindaceae) as a case study.

For the last 2 decades, supertree reconstruction has been an active field of research and has seen the development of a large number of major algorithms. Because of the growing popularity of the supertree methods, it has become necessary to evaluate the performance of these algorithms to determine which are the best options (especially with regard to the supermatrix approach that is widely used). In this study, seven of the most commonly used supertree methods are investigated by using a large empirical data set (in terms of number of taxa and molecular markers) from the worldwide flowering plant family Sapindaceae. Supertree methods were evaluated using several criteria: similarity of the supertrees with the input trees, similarity between the supertrees and the total evidence tree, level of resolution of the supertree and computational time required by the algorithm. Additional analyses were also conducted on a reduced data set to test if the performance levels were affected by the heuristic searches rather than the algorithms themselves. Based on our results, two main groups of supertree methods were identified: on one hand, the matrix representation with parsimony (MRP), MinFlip, and MinCut methods performed well according to our criteria, whereas the average consensus, split fit, and most similar supertree methods showed a poorer performance or at least did not behave the same way as the total evidence tree. Results for the super distance matrix, that is, the most recent approach tested here, were promising with at least one derived method performing as well as MRP, MinFlip, and MinCut. The output of each method was only slightly improved when applied to the reduced data set, suggesting a correct behavior of the heuristic searches and a relatively low sensitivity of the algorithms to data set sizes and missing data. Results also showed that the MRP analyses could reach a high level of quality even when using a simple heuristic search strategy, with the exception of MRP with Purvis coding scheme and reversible parsimony. The future of supertrees lies in the implementation of a standardized heuristic search for all methods and the increase in computing power to handle large data sets. The latter would prove to be particularly useful for promising approaches such as the maximum quartet fit method that yet requires substantial computing power.

EADock: docking of small molecules into protein active sites with a multiobjective evolutionary optimization.

In recent years, protein-ligand docking has become a powerful tool for drug development. Although several approaches suitable for high throughput screening are available, there is a need for methods able to identify binding modes with high accuracy. This accuracy is essential to reliably compute the binding free energy of the ligand. Such methods are needed when the binding mode of lead compounds is not determined experimentally but is needed for structure-based lead optimization. We present here a new docking software, called EADock, that aims at this goal. It uses an hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 A around the center of mass of the ligand position in the crystal structure, and on the contrary to other benchmarks, our algorithm was fed with optimized ligand positions up to 10 A root mean square deviation (RMSD) from the crystal structure, excluding the latter. This validation illustrates the efficiency of our sampling strategy, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures could be explained by the presence of crystal contacts in the experimental structure. Finally, the ability of EADock to accurately predict binding modes on a real application was illustrated by the successful docking of the RGD cyclic pentapeptide on the alphaVbeta3 integrin, starting far away from the binding pocket.

Addressing trypsin bias in large scale (phospho)proteome analysis by size exclusion chromatography and secondary digestion of large post-trypsin peptides.

In the vast majority of bottom-up proteomics studies, protein digestion is performed using only mammalian trypsin. Although it is clearly the best enzyme available, the sole use of trypsin rarely leads to complete sequence coverage, even for abundant proteins. It is commonly assumed that this is because many tryptic peptides are either too short or too long to be identified by RPLC-MS/MS. We show through in silico analysis that 20-30% of the total sequence of three proteomes (Schizosaccharomyces pombe, Saccharomyces cerevisiae, and Homo sapiens) is expected to be covered by Large post-Trypsin Peptides (LpTPs) with M(r) above 3000 Da. We then established size exclusion chromatography to fractionate complex yeast tryptic digests into pools of peptides based on size. We found that secondary digestion of LpTPs followed by LC-MS/MS analysis leads to a significant increase in identified proteins and a 32-50% relative increase in average sequence coverage compared to trypsin digestion alone. Application of the developed strategy to analyze the phosphoproteomes of S. pombe and of a human cell line identified a significant fraction of novel phosphosites. Overall our data indicate that specific targeting of LpTPs can complement standard bottom-up workflows to reveal a largely neglected portion of the proteome.

Evolutionary history of the greater white-toothed shrew (Crocidura russula) inferred from analysis of mtDNA, Y, and X chromosome markers.

We investigate the evolutionary history of the greater white-toothed shrew across its distribution in northern Africa and mainland Europe using sex-specific (mtDNA and Y chromosome) and biparental (X chromosome) markers. All three loci confirm a large divergence between eastern (Tunisia and Sardinia) and western (Morocco and mainland Europe) lineages, and application of a molecular clock to mtDNA divergence estimates indicates a more ancient separation (2.25 M yr ago) than described by some previous studies, supporting claims for taxonomic revision. Moroccan ancestry for the mainland European population is inconclusive from phylogenetic trees, but is supported by greater nucleotide diversity and a more ancient population expansion in Morocco than in Europe. Signatures of rapid population expansion in mtDNA, combined with low X and Y chromosome diversity, suggest a single colonization of mainland Europe by a small number of Moroccan shrews >38 K yr ago. This study illustrates that multilocus genetic analyses can facilitate the interpretation of species' evolutionary history but that phylogeographic inference using X and Y chromosomes is restricted by low levels of observed polymorphism.

Keeping the Vermin Out: Perceived Disease Threat and Ideological Orientations as Predictors of Exclusionary Immigration Attitudes

Integrating evolutionary and social representations theories, the current study examines the relationship between perceived disease threat and exclusionary immigration attitudes in the context of a potential avian influenza pandemic. This large-scale disease provides a realistic context for investigating the link between disease threat and immigration attitudes. The main aim of this cross-sectional study (N=412) was to explore mechanisms through which perceived chronic and contextual disease threats operate on immigration attitudes. Structural equation models show that the relationship between chronic disease threat (germ aversion) and exclusionary immigration attitudes (assimiliationist immigration criteria, health-based immigration criteria and desire to reduce the proportion of foreigners) was mediated by ideological and normative beliefs (social dominance orientation, belief in a dangerous world), but not by contextual disease threat (appraisal of avian influenza pandemic threat). Contextual disease threat only predicted support for health-based immigration criteria. The conditions under which real-life disease threats influence intergroup attitudes are scrutinized. Convergence and dissimilarity of evolutionary and social representational approaches in accounting for the link between disease threat and immigration attitudes are discussed.