Detailed analysis and follow-up studies of a high-throughput screening for indoleamine 2,3-dioxygenase 1 (IDO1) inhibitors.

Indoleamine 2,3-dioxygenase 1 (IDO1) is a key regulator of immune responses and therefore an important therapeutic target for the treatment of diseases that involve pathological immune escape, such as cancer. Here, we describe a robust and sensitive high-throughput screen (HTS) for IDO1 inhibitors using the Prestwick Chemical Library of 1200 FDA-approved drugs and the Maybridge HitFinder Collection of 14,000 small molecules. Of the 60 hits selected for follow-up studies, 14 displayed IC50 values below 20 μM under the secondary assay conditions, and 4 showed an activity in cellular tests. In view of the high attrition rate we used both experimental and computational techniques to identify and to characterize compounds inhibiting IDO1 through unspecific inhibition mechanisms such as chemical reactivity, redox cycling, or aggregation. One specific IDO1 inhibitor scaffold, the imidazole antifungal agents, was chosen for rational structure-based lead optimization, which led to more soluble and smaller compounds with micromolar activity.

Effects of repeated slash removal in thinned stands on soil chemistry and understorey vegetation

Abstract

Computational problems in perfect phylogeny haplotyping: Typing without calling the allele

A haplotype is an m-long binary vector. The XOR-genotype of two haplotypes is the m-vector of their coordinate-wise XOR. We study the following problem: Given a set of XOR-genotypes, reconstruct their haplotypes so that the set of resulting haplotypes can be mapped onto a perfect phylogeny (PP) tree. The question is motivated by studying population evolution in human genetics and is a variant of the PP haplotyping problem that has received intensive attention recently. Unlike the latter problem, in which the input is '' full '' genotypes, here, we assume less informative input and so may be more economical to obtain experimentally. Building on ideas of Gusfield, we show how to solve the problem in polynomial time by a reduction to the graph realization problem. The actual haplotypes are not uniquely determined by the tree they map onto and the tree itself may or may not be unique. We show that tree uniqueness implies uniquely determined haplotypes, up to inherent degrees of freedom, and give a sufficient condition for the uniqueness. To actually determine the haplotypes given the tree, additional information is necessary. We show that two or three full genotypes suffice to reconstruct all the haplotypes and present a linear algorithm for identifying those genotypes.

Long synthetic peptides for the production of vaccines and drugs: a technological platform coming of age.

Long synthetic peptides (LSPs) have a variety of important clinical uses as synthetic vaccines and drugs. Techniques for peptide synthesis were revolutionized in the 1960s and 1980s, after which efficient techniques for purification and characterization of the product were developed. These improved techniques allowed the stepwise synthesis of increasingly longer products at a faster rate, greater purity, and lower cost for clinical use. A synthetic peptide approach, coupled with bioinformatics analysis of genomes, can tremendously expand the search for clinically relevant products. In this Review, we discuss efforts to develop a malaria vaccine from LSPs, among other clinically directed work.

Chemistry in Catalonia 1990-1995

The seven-year period studied here differs very little from the sixyear period described in the previous Report (1990-1995). Sustained growth was observed in almost all the indicators used to evaluate the resources invested and the scientific results obtained

Chemistry in Catalonia 1990-1995

The seven-year period studied here differs very little from the sixyear period described in the previous Report (1990-1995). Sustained growth was observed in almost all the indicators used to evaluate the resources invested and the scientific results obtained

Lipase Improvement: Goals and strategies

Lipases have received great attention as industrial biocatalysts in areas like oils and fats processing, detergents, baking, cheese making, surface cleaning, or fine chemistry . They can catalyse reactions of insoluble substrates at the lipid-water interface, preserving their catalytic activity in organic solvents. This makes of lipases powerful tools for catalysing not only hydrolysis, but also various reverse reactions such as esterification, transesterification, aminolysis, or thiotransesterifications in anhydrous organic solvents. Moreover, lipases catalyse reactions with high specificity, regio and enantioselectivity, becoming the most used enzymes in synthetic organic chemistry. Therefore, they display important advantages over classical catalysts, as they can catalyse reactions with reduced side products, lowered waste treatment costs, and under mild temperature and pressure conditions. Accordingly, the use of lipases holds a great promise for green and economical process chemistry.

Computational and statistical analysis of copy number variants in normal and cancer genomes

AbstractAlthough the genomes from any two human individuals are more than 99.99% identical at the sequence level, some structural variation can be observed. Differences between genomes include single nucleotide polymorphism (SNP), inversion and copy number changes (gain or loss of DNA). The latter can range from submicroscopic events (CNVs, at least 1kb in size) to complete chromosomal aneuploidies. Small copy number variations have often no (lethal) consequences to the cell, but a few were associated to disease susceptibility and phenotypic variations. Larger re-arrangements (i.e. complete chromosome gain) are frequently associated with more severe consequences on health such as genomic disorders and cancer. High-throughput technologies like DNA microarrays enable the detection of CNVs in a genome-wide fashion. Since the initial catalogue of CNVs in the human genome in 2006, there has been tremendous interest in CNVs both in the context of population and medical genetics. Understanding CNV patterns within and between human populations is essential to elucidate their possible contribution to disease. But genome analysis is a challenging task; the technology evolves rapidly creating needs for novel, efficient and robust analytical tools which need to be compared with existing ones. Also, while the link between CNV and disease has been established, the relative CNV contribution is not fully understood and the predisposition to disease from CNVs of the general population has not been yet investigated.During my PhD thesis, I worked on several aspects related to CNVs. As l will report in chapter 3, ! was interested in computational methods to detect CNVs from the general population. I had access to the CoLaus dataset, a population-based study with more than 6,000 participants from the Lausanne area. All these individuals were analysed on SNP arrays and extensive clinical information were available. My work explored existing CNV detection methods and I developed a variety of metrics to compare their performance. Since these methods were not producing entirely satisfactory results, I implemented my own method which outperformed two existing methods. I also devised strategies to combine CNVs from different individuals into CNV regions.I was also interested in the clinical impact of CNVs in common disease (chapter 4). Through an international collaboration led by the Centre Hospitalier Universitaire Vaudois (CHUV) and the Imperial College London I was involved as a main data analyst in the investigation of a rare deletion at chromosome 16p11 detected in obese patients. Specifically, we compared 8,456 obese patients and 11,856 individuals from the general population and we found that the deletion was accounting for 0.7% of the morbid obesity cases and was absent in healthy non- obese controls. This highlights the importance of rare variants with strong impact and provides new insights in the design of clinical studies to identify the missing heritability in common disease.Furthermore, I was interested in the detection of somatic copy number alterations (SCNA) and their consequences in cancer (chapter 5). This project was a collaboration initiated by the Ludwig Institute for Cancer Research and involved other groups from the Swiss Institute of Bioinformatics, the CHUV and Universities of Lausanne and Geneva. The focus of my work was to identify genes with altered expression levels within somatic copy number alterations (SCNA) in seven metastatic melanoma ceil lines, using CGH and SNP arrays, RNA-seq, and karyotyping. Very few SCNA genes were shared by even two melanoma samples making it difficult to draw any conclusions at the individual gene level. To overcome this limitation, I used a network-guided analysis to determine whether any pathways, defined by amplified or deleted genes, were common among the samples. Six of the melanoma samples were potentially altered in four pathways and five samples harboured copy-number and expression changes in components of six pathways. In total, this approach identified 28 pathways. Validation with two external, large melanoma datasets confirmed all but three of the detected pathways and demonstrated the utility of network-guided approaches for both large and small datasets analysis.RésuméBien que le génome de deux individus soit similaire à plus de 99.99%, des différences de structure peuvent être observées. Ces différences incluent les polymorphismes simples de nucléotides, les inversions et les changements en nombre de copies (gain ou perte d'ADN). Ces derniers varient de petits événements dits sous-microscopiques (moins de 1kb en taille), appelés CNVs (copy number variants) jusqu'à des événements plus large pouvant affecter des chromosomes entiers. Les petites variations sont généralement sans conséquence pour la cellule, toutefois certaines ont été impliquées dans la prédisposition à certaines maladies, et à des variations phénotypiques dans la population générale. Les réarrangements plus grands (par exemple, une copie additionnelle d'un chromosome appelée communément trisomie) ont des répercutions plus grave pour la santé, comme par exemple dans certains syndromes génomiques et dans le cancer. Les technologies à haut-débit telle les puces à ADN permettent la détection de CNVs à l'échelle du génome humain. La cartographie en 2006 des CNV du génome humain, a suscité un fort intérêt en génétique des populations et en génétique médicale. La détection de différences au sein et entre plusieurs populations est un élément clef pour élucider la contribution possible des CNVs dans les maladies. Toutefois l'analyse du génome reste une tâche difficile, la technologie évolue très rapidement créant de nouveaux besoins pour le développement d'outils, l'amélioration des précédents, et la comparaison des différentes méthodes. De plus, si le lien entre CNV et maladie a été établit, leur contribution précise n'est pas encore comprise. De même que les études sur la prédisposition aux maladies par des CNVs détectés dans la population générale n'ont pas encore été réalisées.Pendant mon doctorat, je me suis concentré sur trois axes principaux ayant attrait aux CNV. Dans le chapitre 3, je détaille mes travaux sur les méthodes d'analyses des puces à ADN. J'ai eu accès aux données du projet CoLaus, une étude de la population de Lausanne. Dans cette étude, le génome de plus de 6000 individus a été analysé avec des puces SNP et de nombreuses informations cliniques ont été récoltées. Pendant mes travaux, j'ai utilisé et comparé plusieurs méthodes de détection des CNVs. Les résultats n'étant pas complètement satisfaisant, j'ai implémenté ma propre méthode qui donne de meilleures performances que deux des trois autres méthodes utilisées. Je me suis aussi intéressé aux stratégies pour combiner les CNVs de différents individus en régions.Je me suis aussi intéressé à l'impact clinique des CNVs dans le cas des maladies génétiques communes (chapitre 4). Ce projet fut possible grâce à une étroite collaboration avec le Centre Hospitalier Universitaire Vaudois (CHUV) et l'Impérial College à Londres. Dans ce projet, j'ai été l'un des analystes principaux et j'ai travaillé sur l'impact clinique d'une délétion rare du chromosome 16p11 présente chez des patients atteints d'obésité. Dans cette collaboration multidisciplinaire, nous avons comparés 8'456 patients atteint d'obésité et 11 '856 individus de la population générale. Nous avons trouvés que la délétion était impliquée dans 0.7% des cas d'obésité morbide et était absente chez les contrôles sains (non-atteint d'obésité). Notre étude illustre l'importance des CNVs rares qui peuvent avoir un impact clinique très important. De plus, ceci permet d'envisager une alternative aux études d'associations pour améliorer notre compréhension de l'étiologie des maladies génétiques communes.Egalement, j'ai travaillé sur la détection d'altérations somatiques en nombres de copies (SCNA) et de leurs conséquences pour le cancer (chapitre 5). Ce projet fut une collaboration initiée par l'Institut Ludwig de Recherche contre le Cancer et impliquant l'Institut Suisse de Bioinformatique, le CHUV et les Universités de Lausanne et Genève. Je me suis concentré sur l'identification de gènes affectés par des SCNAs et avec une sur- ou sous-expression dans des lignées cellulaires dérivées de mélanomes métastatiques. Les données utilisées ont été générées par des puces ADN (CGH et SNP) et du séquençage à haut débit du transcriptome. Mes recherches ont montrées que peu de gènes sont récurrents entre les mélanomes, ce qui rend difficile l'interprétation des résultats. Pour contourner ces limitations, j'ai utilisé une analyse de réseaux pour définir si des réseaux de signalisations enrichis en gènes amplifiés ou perdus, étaient communs aux différents échantillons. En fait, parmi les 28 réseaux détectés, quatre réseaux sont potentiellement dérégulés chez six mélanomes, et six réseaux supplémentaires sont affectés chez cinq mélanomes. La validation de ces résultats avec deux larges jeux de données publiques, a confirmée tous ces réseaux sauf trois. Ceci démontre l'utilité de cette approche pour l'analyse de petits et de larges jeux de données.Résumé grand publicL'avènement de la biologie moléculaire, en particulier ces dix dernières années, a révolutionné la recherche en génétique médicale. Grâce à la disponibilité du génome humain de référence dès 2001, de nouvelles technologies telles que les puces à ADN sont apparues et ont permis d'étudier le génome dans son ensemble avec une résolution dite sous-microscopique jusque-là impossible par les techniques traditionnelles de cytogénétique. Un des exemples les plus importants est l'étude des variations structurales du génome, en particulier l'étude du nombre de copies des gènes. Il était établi dès 1959 avec l'identification de la trisomie 21 par le professeur Jérôme Lejeune que le gain d'un chromosome supplémentaire était à l'origine de syndrome génétique avec des répercussions graves pour la santé du patient. Ces observations ont également été réalisées en oncologie sur les cellules cancéreuses qui accumulent fréquemment des aberrations en nombre de copies (telles que la perte ou le gain d'un ou plusieurs chromosomes). Dès 2004, plusieurs groupes de recherches ont répertorié des changements en nombre de copies dans des individus provenant de la population générale (c'est-à-dire sans symptômes cliniques visibles). En 2006, le Dr. Richard Redon a établi la première carte de variation en nombre de copies dans la population générale. Ces découvertes ont démontrées que les variations dans le génome était fréquentes et que la plupart d'entre elles étaient bénignes, c'est-à-dire sans conséquence clinique pour la santé de l'individu. Ceci a suscité un très grand intérêt pour comprendre les variations naturelles entre individus mais aussi pour mieux appréhender la prédisposition génétique à certaines maladies.Lors de ma thèse, j'ai développé de nouveaux outils informatiques pour l'analyse de puces à ADN dans le but de cartographier ces variations à l'échelle génomique. J'ai utilisé ces outils pour établir les variations dans la population suisse et je me suis consacré par la suite à l'étude de facteurs pouvant expliquer la prédisposition aux maladies telles que l'obésité. Cette étude en collaboration avec le Centre Hospitalier Universitaire Vaudois a permis l'identification d'une délétion sur le chromosome 16 expliquant 0.7% des cas d'obésité morbide. Cette étude a plusieurs répercussions. Tout d'abord elle permet d'effectuer le diagnostique chez les enfants à naître afin de déterminer leur prédisposition à l'obésité. Ensuite ce locus implique une vingtaine de gènes. Ceci permet de formuler de nouvelles hypothèses de travail et d'orienter la recherche afin d'améliorer notre compréhension de la maladie et l'espoir de découvrir un nouveau traitement Enfin notre étude fournit une alternative aux études d'association génétique qui n'ont eu jusqu'à présent qu'un succès mitigé.Dans la dernière partie de ma thèse, je me suis intéressé à l'analyse des aberrations en nombre de copies dans le cancer. Mon choix s'est porté sur l'étude de mélanomes, impliqués dans le cancer de la peau. Le mélanome est une tumeur très agressive, elle est responsable de 80% des décès des cancers de la peau et est souvent résistante aux traitements utilisés en oncologie (chimiothérapie, radiothérapie). Dans le cadre d'une collaboration entre l'Institut Ludwig de Recherche contre le Cancer, l'Institut Suisse de Bioinformatique, le CHUV et les universités de Lausanne et Genève, nous avons séquencés l'exome (les gènes) et le transcriptome (l'expression des gènes) de sept mélanomes métastatiques, effectués des analyses du nombre de copies par des puces à ADN et des caryotypes. Mes travaux ont permis le développement de nouvelles méthodes d'analyses adaptées au cancer, d'établir la liste des réseaux de signalisation cellulaire affectés de façon récurrente chez le mélanome et d'identifier deux cibles thérapeutiques potentielles jusqu'alors ignorées dans les cancers de la peau.

Postmortem chemistry update part II.

As a continuation of "Postmortem Chemistry Update Part I," Part II deals with molecules linked to liver and cardiac functions, alcohol intake and alcohol misuse, myocardial ischemia, inflammation, sepsis, anaphylaxis, and hormonal disturbances. A very important array of new material concerning these situations had appeared in the forensic literature over the last two decades. Some molecules, such as procalcitonin and C-reactive protein, are currently researched in cases of suspected sepsis and inflammation, whereas many other analytes are not integrated into routine casework. As in part I, a literature review concerning a large panel of molecules of forensic interest is presented, as well as the results of our own observations, where possible.

Entropic transport in confined media: a challenge for computational studies in biological and soft-matter systems

Transport in small-scale biological and soft-matter systems typically occurs under confinement conditions in which particles proceed through obstacles and irregularities of the boundaries that may significantly alter their trajectories. A transport model that assimilates the confinement to the presence of entropic barriers provides an efficient approach to quantify its effect on the particle current and the diffusion coefficient. We review the main peculiarities of entropic transport and treat two cases in which confinement effects play a crucial role, with the appearance of emergent properties. The presence of entropic barriers modifies the mean first-passage time distribution and therefore plays a very important role in ion transport through micro- and nano-channels. The functionality of molecular motors, modeled as Brownian ratchets, is strongly affected when the motor proceeds in a confined medium that may constitute another source of rectification. The interplay between ratchet and entropic rectification gives rise to a wide variety of dynamical behaviors, not observed when the Brownian motor proceeds in an unbounded medium. Entropic transport offers new venues of transport control and particle manipulation and new ways to engineer more efficient devices for transport at the nanoscale.

Living with an imperfect cell wall: compensation of femAB inactivation in Staphylococcus aureus.

BACKGROUND: Synthesis of the Staphylococcus aureus peptidoglycan pentaglycine interpeptide bridge is catalyzed by the nonribosomal peptidyl transferases FemX, FemA and FemB. Inactivation of the femAB operon reduces the interpeptide to a monoglycine, leading to a poorly crosslinked peptidoglycan. femAB mutants show a reduced growth rate and are hypersusceptible to virtually all antibiotics, including methicillin, making FemAB a potential target to restore beta-lactam susceptibility in methicillin-resistant S. aureus (MRSA). Cis-complementation with wild type femAB only restores synthesis of the pentaglycine interpeptide and methicillin resistance, but the growth rate remains low. This study characterizes the adaptations that ensured survival of the cells after femAB inactivation. RESULTS: In addition to slow growth, the cis-complemented femAB mutant showed temperature sensitivity and a higher methicillin resistance than the wild type. Transcriptional profiling paired with reporter metabolite analysis revealed multiple changes in the global transcriptome. A number of transporters for sugars, glycerol, and glycine betaine, some of which could serve as osmoprotectants, were upregulated. Striking differences were found in the transcription of several genes involved in nitrogen metabolism and the arginine-deiminase pathway, an alternative for ATP production. In addition, microarray data indicated enhanced expression of virulence factors that correlated with premature expression of the global regulators sae, sarA, and agr. CONCLUSION: Survival under conditions preventing normal cell wall formation triggered complex adaptations that incurred a fitness cost, showing the remarkable flexibility of S. aureus to circumvent cell wall damage. Potential FemAB inhibitors would have to be used in combination with other antibiotics to prevent selection of resistant survivors.

An integrative computational analysis provides evidence for FBN1-associated network deregulation in trisomy 21

Although approximately 50% of Down Syndrome (DS) patients have heart abnormalities, they exhibit an overprotection against cardiac abnormalities related with the connective tissue, for example a lower risk of coronary artery disease. A recent study reported a case of a person affected by DS who carried mutations in FBN1, the gene causative for a connective tissue disorder called Marfan Syndrome (MFS). The fact that the person did not have any cardiac alterations suggested compensation effects due to DS. This observation is supported by a previous DS meta-analysis at the molecular level where we have found an overall upregulation of FBN1 (which is usually downregulated in MFS). Additionally, that result was cross-validated with independent expression data from DS heart tissue. The aim of this work is to elucidate the role of FBN1 in DS and to establish a molecular link to MFS and MFS-related syndromes using a computational approach. To reach that, we conducted different analytical approaches over two DS studies (our previous meta-analysis and independent expression data from DS heart tissue) and revealed expression alterations in the FBN1 interaction network, in FBN1 co-expressed genes and FBN1-related pathways. After merging the significant results from different datasets with a Bayesian approach, we prioritized 85 genes that were able to distinguish control from DS cases. We further found evidence for several of these genes (47%), such as FBN1, DCN, and COL1A2, being dysregulated in MFS and MFS-related diseases. Consequently, we further encourage the scientific community to take into account FBN1 and its related network for the study of DS cardiovascular characteristics.

Characterisation of the putative effector interaction site of the regulatory HbpR protein from Pseudomonas azelaica by site-directed mutagenesis.

Bacterial transcription activators of the XylR/DmpR subfamily exert their expression control via σ(54)-dependent RNA polymerase upon stimulation by a chemical effector, typically an aromatic compound. Where the chemical effector interacts with the transcription regulator protein to achieve activation is still largely unknown. Here we focus on the HbpR protein from Pseudomonas azelaica, which is a member of the XylR/DmpR subfamily and responds to biaromatic effectors such as 2-hydroxybiphenyl. We use protein structure modeling to predict folding of the effector recognition domain of HbpR and molecular docking to identify the region where 2-hydroxybiphenyl may interact with HbpR. A large number of site-directed HbpR mutants of residues in- and outside the predicted interaction area was created and their potential to induce reporter gene expression in Escherichia coli from the cognate P(C) promoter upon activation with 2-hydroxybiphenyl was studied. Mutant proteins were purified to study their conformation. Critical residues for effector stimulation indeed grouped near the predicted area, some of which are conserved among XylR/DmpR subfamily members in spite of displaying different effector specificities. This suggests that they are important for the process of effector activation, but not necessarily for effector specificity recognition.

Local optima networks of hard combinatorial landscapes

Combinatorial optimization involves finding an optimal solution in a finite set of options; many everyday life problems are of this kind. However, the number of options grows exponentially with the size of the problem, such that an exhaustive search for the best solution is practically infeasible beyond a certain problem size. When efficient algorithms are not available, a practical approach to obtain an approximate solution to the problem at hand, is to start with an educated guess and gradually refine it until we have a good-enough solution. Roughly speaking, this is how local search heuristics work. These stochastic algorithms navigate the problem search space by iteratively turning the current solution into new candidate solutions, guiding the search towards better solutions. The search performance, therefore, depends on structural aspects of the search space, which in turn depend on the move operator being used to modify solutions. A common way to characterize the search space of a problem is through the study of its fitness landscape, a mathematical object comprising the space of all possible solutions, their value with respect to the optimization objective, and a relationship of neighborhood defined by the move operator. The landscape metaphor is used to explain the search dynamics as a sort of potential function. The concept is indeed similar to that of potential energy surfaces in physical chemistry. Borrowing ideas from that field, we propose to extend to combinatorial landscapes the notion of the inherent network formed by energy minima in energy landscapes. In our case, energy minima are the local optima of the combinatorial problem, and we explore several definitions for the network edges. At first, we perform an exhaustive sampling of local optima basins of attraction, and define weighted transitions between basins by accounting for all the possible ways of crossing the basins frontier via one random move. Then, we reduce the computational burden by only counting the chances of escaping a given basin via random kick moves that start at the local optimum. Finally, we approximate network edges from the search trajectory of simple search heuristics, mining the frequency and inter-arrival time with which the heuristic visits local optima. Through these methodologies, we build a weighted directed graph that provides a synthetic view of the whole landscape, and that we can characterize using the tools of complex networks science. We argue that the network characterization can advance our understanding of the structural and dynamical properties of hard combinatorial landscapes. We apply our approach to prototypical problems such as the Quadratic Assignment Problem, the NK model of rugged landscapes, and the Permutation Flow-shop Scheduling Problem. We show that some network metrics can differentiate problem classes, correlate with problem non-linearity, and predict problem hardness as measured from the performances of trajectory-based local search heuristics.