Design of potent inhibitors of human RAD51 recombinase based on BRC motifs of BRCA2 protein: modeling and experimental validation of a chimera peptide.

We have previously shown that a 28-amino acid peptide derived from the BRC4 motif of BRCA2 tumor suppressor inhibits selectively human RAD51 recombinase (HsRad51). With the aim of designing better inhibitors for cancer treatment, we combined an in silico docking approach with in vitro biochemical testing to construct a highly efficient chimera peptide from eight existing human BRC motifs. We built a molecular model of all BRC motifs complexed with HsRad51 based on the crystal structure of the BRC4 motif-HsRad51 complex, computed the interaction energy of each residue in each BRC motif, and selected the best amino acid residue at each binding position. This analysis enabled us to propose four amino acid substitutions in the BRC4 motif. Three of these increased the inhibitory effect in vitro, and this effect was found to be additive. We thus obtained a peptide that is about 10 times more efficient in inhibiting HsRad51-ssDNA complex formation than the original peptide.

Stick insect genomes reveal natural selection's role in parallel speciation.

Natural selection can drive the repeated evolution of reproductive isolation, but the genomic basis of parallel speciation remains poorly understood. We analyzed whole-genome divergence between replicate pairs of stick insect populations that are adapted to different host plants and undergoing parallel speciation. We found thousands of modest-sized genomic regions of accentuated divergence between populations, most of which are unique to individual population pairs. We also detected parallel genomic divergence across population pairs involving an excess of coding genes with specific molecular functions. Regions of parallel genomic divergence in nature exhibited exceptional allele frequency changes between hosts in a field transplant experiment. The results advance understanding of biological diversification by providing convergent observational and experimental evidence for selection's role in driving repeatable genomic divergence.

Highly parallel genetic approaches in Mendelian and complex diseases

The recent advance in high-throughput sequencing and genotyping protocols allows rapid investigation of Mendelian and complex diseases on a scale not previously been possible. In my thesis research I took advantage of these modern techniques to study retinitis pigmentosa (RP), a rare inherited disease characterized by progressive loss of photoreceptors and leading to blindness; and hypertension, a common condition affecting 30% of the adult population. Firstly, I compared the performance of different next generation sequencing (NGS) platforms in the sequencing of the RP-linked gene PRPF31. The gene contained a mutation in an intronic repetitive element, which presented difficulties for both classic sequencing methods and NGS. We showed that all NGS platforms are powerful tools to identify rare and common DNA variants, also in case of more complex sequences. Moreover, we evaluated the features of different NGS platforms that are important in re-sequencing projects. The main focus of my thesis was then to investigate the involvement of pre-mRNA splicing factors in autosomal dominant RP (adRP). I screened 5 candidate genes in a large cohort of patients by using long-range PCR as enrichment step, followed by NGS. We tested two different approaches: in one, all target PCRs from all patients were pooled and sequenced as a single DNA library; in the other, PCRs from each patient were separated within the pool by DNA barcodes. The first solution was more cost-effective, while the second one allowed obtaining faster and more accurate results, but overall they both proved to be effective strategies for gene screenings in many samples. We could in fact identify novel missense mutations in the SNRNP200 gene, encoding an essential RNA helicase for splicing catalysis. Interestingly, one of these mutations showed incomplete penetrance in one family with adRP. Thus, we started to study the possible molecular causes underlying phenotypic differences between asymptomatic and affected members of this family. For the study of hypertension, I joined a European consortium to perform genome-wide association studies (GWAS). Thanks to the use of very informative genotyping arrays and of phenotipically well-characterized cohorts, we could identify a novel susceptibility locus for hypertension in the promoter region of the endothelial nitric oxide synthase gene (NOS3). Moreover, we have proven the direct causality of the associated SNP using three different methods: 1) targeted resequencing, 2) luciferase assay, and 3) population study. - Le récent progrès dans le Séquençage à haut Débit et les protocoles de génotypage a permis une plus vaste et rapide étude des maladies mendéliennes et multifactorielles à une échelle encore jamais atteinte. Durant ma thèse de recherche, j'ai utilisé ces nouvelles techniques de séquençage afin d'étudier la retinite pigmentale (RP), une maladie héréditaire rare caractérisée par une perte progressive des photorécepteurs de l'oeil qui entraine la cécité; et l'hypertension, une maladie commune touchant 30% de la population adulte. Tout d'abord, j'ai effectué une comparaison des performances de différentes plateformes de séquençage NGS (Next Generation Sequencing) lors du séquençage de PRPF31, un gène lié à RP. Ce gène contenait une mutation dans un élément répétable intronique, qui présentait des difficultés de séquençage avec la méthode classique et les NGS. Nous avons montré que les plateformes de NGS analysées sont des outils très puissants pour identifier des variations de l'ADN rares ou communes et aussi dans le cas de séquences complexes. De plus, nous avons exploré les caractéristiques des différentes plateformes NGS qui sont importantes dans les projets de re-séquençage. L'objectif principal de ma thèse a été ensuite d'examiner l'effet des facteurs d'épissage de pre-ARNm dans une forme autosomale dominante de RP (adRP). Un screening de 5 gènes candidats issus d'une large cohorte de patients a été effectué en utilisant la long-range PCR comme étape d'enrichissement, suivie par séquençage avec NGS. Nous avons testé deux approches différentes : dans la première, toutes les cibles PCRs de tous les patients ont été regroupées et séquencées comme une bibliothèque d'ADN unique; dans la seconde, les PCRs de chaque patient ont été séparées par code barres d'ADN. La première solution a été la plus économique, tandis que la seconde a permis d'obtenir des résultats plus rapides et précis. Dans l'ensemble, ces deux stratégies se sont démontrées efficaces pour le screening de gènes issus de divers échantillons. Nous avons pu identifier des nouvelles mutations faux-sens dans le gène SNRNP200, une hélicase ayant une fonction essentielle dans l'épissage. Il est intéressant de noter qu'une des ces mutations montre une pénétrance incomplète dans une famille atteinte d'adRP. Ainsi, nous avons commencé une étude sur les causes moléculaires entrainant des différences phénotypiques entre membres affectés et asymptomatiques de cette famille. Lors de l'étude de l'hypertension, j'ai rejoint un consortium européen pour réaliser une étude d'association Pangénomique ou genome-wide association study Grâce à l'utilisation de tableaux de génotypage très informatifs et de cohortes extrêmement bien caractérisées au niveau phénotypique, un nouveau locus lié à l'hypertension a été identifié dans la région promotrice du gène endothélial nitric oxide sinthase (NOS3). Par ailleurs, nous avons prouvé la cause directe du SNP associé au moyen de trois méthodes différentes: i) en reséquençant la cible avec NGS, ii) avec des essais à la luciférase et iii) une étude de population.

A stratified approach for modeling the distribution of a threatened ant species in the Swiss National Park

We present models predicting the potential distribution of a threatened ant species, Formica exsecta Nyl., in the Swiss National Park ( SNP). Data to fit the models have been collected according to a random-stratified design with an equal number of replicates per stratum. The basic aim of such a sampling strategy is to allow the formal testing of biological hypotheses about those factors most likely to account for the distribution of the modeled species. The stratifying factors used in this study were: vegetation, slope angle and slope aspect, the latter two being used as surrogates of solar radiation, considered one of the basic requirements of F. exsecta. Results show that, although the basic stratifying predictors account for more than 50% of the deviance, the incorporation of additional non-spatially explicit predictors into the model, as measured in the field, allows for an increased model performance (up to nearly 75%). However, this was not corroborated by permutation tests. Implementation on a national scale was made for one model only, due to the difficulty of obtaining similar predictors on this scale. The resulting map on the national scale suggests that the species might once have had a broader distribution in Switzerland. Reasons for its particular abundance within the SNP might possibly be related to habitat fragmentation and vegetation transformation outside the SNP boundaries.

Modeling the biophysical impacts of global change in mountain biosphere reserves

Mountains and mountain societies provide a wide range of goods and services to humanity, but they are particularly sensitive to the effects of global environmental change. Thus, the definition of appropriate management regimes that maintain the multiple functions of mountain regions in a time of greatly changing climatic, economic, and societal drivers constitutes a significant challenge. Management decisions must be based on a sound understanding of the future dynamics of these systems. The present article reviews the elements required for an integrated effort to project the impacts of global change on mountain regions, and recommends tools that can be used at 3 scientific levels (essential, improved, and optimum). The proposed strategy is evaluated with respect to UNESCO's network of Mountain Biosphere Reserves (MBRs), with the intention of implementing it in other mountain regions as well. First, methods for generating scenarios of key drivers of global change are reviewed, including land use/land cover and climate change. This is followed by a brief review of the models available for projecting the impacts of these scenarios on (1) cryospheric systems, (2) ecosystem structure and diversity, and (3) ecosystem functions such as carbon and water relations. Finally, the cross-cutting role of remote sensing techniques is evaluated with respect to both monitoring and modeling efforts. We conclude that a broad range of techniques is available for both scenario generation and impact assessments, many of which can be implemented without much capacity building across many or even most MBRs. However, to foster implementation of the proposed strategy, further efforts are required to establish partnerships between scientists and resource managers in mountain areas.

Sleep deprivation effects on circadian clock gene expression in the cerebral cortex parallel electroencephalographic differences among mouse strains.

Sleep deprivation (SD) results in increased electroencephalographic (EEG) delta power during subsequent non-rapid eye movement sleep (NREMS) and is associated with changes in the expression of circadian clock-related genes in the cerebral cortex. The increase of NREMS delta power as a function of previous wake duration varies among inbred mouse strains. We sought to determine whether SD-dependent changes in circadian clock gene expression parallel this strain difference described previously at the EEG level. The effects of enforced wakefulness of incremental durations of up to 6 h on the expression of circadian clock genes (bmal1, clock, cry1, cry2, csnk1epsilon, npas2, per1, and per2) were assessed in AKR/J, C57BL/6J, and DBA/2J mice, three strains that exhibit distinct EEG responses to SD. Cortical expression of clock genes subsequent to SD was proportional to the increase in delta power that occurs in inbred strains: the strain that exhibits the most robust EEG response to SD (AKR/J) exhibited dramatic increases in expression of bmal1, clock, cry2, csnkIepsilon, and npas2, whereas the strain with the least robust response to SD (DBA/2) exhibited either no change or a decrease in expression of these genes and cry1. The effect of SD on circadian clock gene expression was maintained in mice in which both of the cryptochrome genes were genetically inactivated. cry1 and cry2 appear to be redundant in sleep regulation as elimination of either of these genes did not result in a significant deficit in sleep homeostasis. These data demonstrate transcriptional regulatory correlates to previously described strain differences at the EEG level and raise the possibility that genetic differences underlying circadian clock gene expression may drive the EEG differences among these strains.

Personalized modeling for drug concentration prediction using Support Vector Machine

Building a personalized model to describe the drug concentration inside the human body for each patient is highly important to the clinical practice and demanding to the modeling tools. Instead of using traditional explicit methods, in this paper we propose a machine learning approach to describe the relation between the drug concentration and patients' features. Machine learning has been largely applied to analyze data in various domains, but it is still new to personalized medicine, especially dose individualization. We focus mainly on the prediction of the drug concentrations as well as the analysis of different features' influence. Models are built based on Support Vector Machine and the prediction results are compared with the traditional analytical models.

Prediction of infant drug exposure through breastfeeding: population PK modeling and simulation of fluoxetine

BACKGROUND: Risks of significant infant drug exposurethrough breastmilk are poorly defined for many drugs, and largescalepopulation data are lacking. We used population pharmacokinetics(PK) modeling to predict fluoxetine exposure levels ofinfants via mother's milk in a simulated population of 1000 motherinfantpairs.METHODS: Using our original data on fluoxetine PK of 25breastfeeding women, a population PK model was developed withNONMEM and parameters, including milk concentrations, wereestimated. An exponential distribution model was used to account forindividual variation. Simulation random and distribution-constrainedassignment of doses, dosing time, feeding intervals and milk volumewas conducted to generate 1000 mother-infant pairs with characteristicssuch as the steady-state serum concentrations (Css) and infantdose relative to the maternal weight-adjusted dose (relative infantdose: RID). Full bioavailability and a conservative point estimate of1-month-old infant CYP2D6 activity to be 20% of the adult value(adjusted by weigth) according to a recent study, were assumed forinfant Css calculations.RESULTS: A linear 2-compartment model was selected as thebest model. Derived parameters, including milk-to-plasma ratios(mean: 0.66; SD: 0.34; range, 0 - 1.1) were consistent with the valuesreported in the literature. The estimated RID was below 10% in >95%of infants. The model predicted median infant-mother Css ratio was0.096 (range 0.035 - 0.25); literature reported mean was 0.07 (range0-0.59). Moreover, the predicted incidence of infant-mother Css ratioof >0.2 was less than 1%.CONCLUSION: Our in silico model prediction is consistent withclinical observations, suggesting that substantial systemic fluoxetineexposure in infants through human milk is rare, but further analysisshould include active metabolites. Our approach may be valid forother drugs. [supported by CIHR and Swiss National Science Foundation(SNSF)]

The challenge of modeling nuclear receptor regulatory networks in mammalian cells.

Nuclear receptors are a major component of signal transduction in animals. They mediate the regulatory activities of many hormones, nutrients and metabolites on the homeostasis and physiology of cells and tissues. It is of high interest to model the corresponding regulatory networks. While molecular and cell biology studies of individual promoters have provided important mechanistic insight, a more complex picture is emerging from genome-wide studies. The regulatory circuitry of nuclear receptor regulated gene expression networks, and their response to cellular signaling, appear highly dynamic, and involve long as well as short range chromatin interactions. We review how progress in understanding the kinetics and regulation of cofactor recruitment, and the development of new genomic methods, provide opportunities but also a major challenge for modeling nuclear receptor mediated regulatory networks.

Aerodynamic drag modeling of alpine skiers performing giant slalom turns.

PURPOSE: Aerodynamic drag plays an important role in performance for athletes practicing sports that involve high-velocity motions. In giant slalom, the skier is continuously changing his/her body posture, and this affects the energy dissipated in aerodynamic drag. It is therefore important to quantify this energy to understand the dynamic behavior of the skier. The aims of this study were to model the aerodynamic drag of alpine skiers in giant slalom simulated conditions and to apply these models in a field experiment to estimate energy dissipated through aerodynamic drag. METHODS: The aerodynamic characteristics of 15 recreational male and female skiers were measured in a wind tunnel while holding nine different skiing-specific postures. The drag and the frontal area were recorded simultaneously for each posture. Four generalized and two individualized models of the drag coefficient were built, using different sets of parameters. These models were subsequently applied in a field study designed to compare the aerodynamic energy losses between a dynamic and a compact skiing technique. RESULTS: The generalized models estimated aerodynamic drag with an accuracy of between 11.00% and 14.28%, and the individualized models estimated aerodynamic drag with an accuracy between 4.52% and 5.30%. The individualized model used for the field study showed that using a dynamic technique led to 10% more aerodynamic drag energy loss than using a compact technique. DISCUSSION: The individualized models were capable of discriminating different techniques performed by advanced skiers and seemed more accurate than the generalized models. The models presented here offer a simple yet accurate method to estimate the aerodynamic drag acting upon alpine skiers while rapidly moving through the range of positions typical to turning technique.

Stoneley wave modeling in heterogeneous porous media with viscous pore fluids

We implemented Biot-type porous wave equations in a pseudo-spectral numerical modeling algorithm for the simulation of Stoneley waves in porous media. Fourier and Chebyshev methods are used to compute the spatial derivatives along the horizontal and vertical directions, respectively. To prevent from overly short time steps due to the small grid spacing at the top and bottom of the model as a consequence of the Chebyshev operator, the mesh is stretched in the vertical direction. As a large benefit, the Chebyshev operator allows for an explicit treatment of interfaces. Boundary conditions can be implemented with a characteristics approach. The characteristic variables are evaluated at zero viscosity. We use this approach to model seismic wave propagation at the interface between a fluid and a porous medium. Each medium is represented by a different mesh and the two meshes are connected through the above described characteristics domain-decomposition method. We show an experiment for sealed pore boundary conditions, where we first compare the numerical solution to an analytical solution. We then show the influence of heterogeneity and viscosity of the pore fluid on the propagation of the Stoneley wave and surface waves in general.

GeoKernels: Modeling of Spatial Data on GeoManifolds

This paper presents a review of methodology for semi-supervised modeling with kernel methods, when the manifold assumption is guaranteed to be satisfied. It concerns environmental data modeling on natural manifolds, such as complex topographies of the mountainous regions, where environmental processes are highly influenced by the relief. These relations, possibly regionalized and nonlinear, can be modeled from data with machine learning using the digital elevation models in semi-supervised kernel methods. The range of the tools and methodological issues discussed in the study includes feature selection and semisupervised Support Vector algorithms. The real case study devoted to data-driven modeling of meteorological fields illustrates the discussed approach.

Parallel imaging with phase scrambling.

PURPOSE: Most existing methods for accelerated parallel imaging in MRI require additional data, which are used to derive information about the sensitivity profile of each radiofrequency (RF) channel. In this work, a method is presented to avoid the acquisition of separate coil calibration data for accelerated Cartesian trajectories. METHODS: Quadratic phase is imparted to the image to spread the signals in k-space (aka phase scrambling). By rewriting the Fourier transform as a convolution operation, a window can be introduced to the convolved chirp function, allowing a low-resolution image to be reconstructed from phase-scrambled data without prominent aliasing. This image (for each RF channel) can be used to derive coil sensitivities to drive existing parallel imaging techniques. As a proof of concept, the quadratic phase was applied by introducing an offset to the x(2) - y(2) shim and the data were reconstructed using adapted versions of the image space-based sensitivity encoding and GeneRalized Autocalibrating Partially Parallel Acquisitions algorithms. RESULTS: The method is demonstrated in a phantom (1 × 2, 1 × 3, and 2 × 2 acceleration) and in vivo (2 × 2 acceleration) using a 3D gradient echo acquisition. CONCLUSION: Phase scrambling can be used to perform parallel imaging acceleration without acquisition of separate coil calibration data, demonstrated here for a 3D-Cartesian trajectory. Further research is required to prove the applicability to other 2D and 3D sampling schemes. Magn Reson Med, 2014. © 2014 Wiley Periodicals, Inc.