Estimating parameters for generalized mass action models using constraint propagation.

As modern molecular biology moves towards the analysis of biological systems as opposed to their individual components, the need for appropriate mathematical and computational techniques for understanding the dynamics and structure of such systems is becoming more pressing. For example, the modeling of biochemical systems using ordinary differential equations (ODEs) based on high-throughput, time-dense profiles is becoming more common-place, which is necessitating the development of improved techniques to estimate model parameters from such data. Due to the high dimensionality of this estimation problem, straight-forward optimization strategies rarely produce correct parameter values, and hence current methods tend to utilize genetic/evolutionary algorithms to perform non-linear parameter fitting. Here, we describe a completely deterministic approach, which is based on interval analysis. This allows us to examine entire sets of parameters, and thus to exhaust the global search within a finite number of steps. In particular, we show how our method may be applied to a generic class of ODEs used for modeling biochemical systems called Generalized Mass Action Models (GMAs). In addition, we show that for GMAs our method is amenable to the technique in interval arithmetic called constraint propagation, which allows great improvement of its efficiency. To illustrate the applicability of our method we apply it to some networks of biochemical reactions appearing in the literature, showing in particular that, in addition to estimating system parameters in the absence of noise, our method may also be used to recover the topology of these networks.

Structural Insight into the Mode of Action of a Direct Inhibitor of Coregulator Binding to the Thyroid Hormone Receptor.

The development of nuclear hormone receptor antagonists that directly inhibit the association of the receptor with its essential coactivators would allow useful manipulation of nuclear hormone receptor signaling. We previously identified 3-(dibutylamino)-1-(4-hexylphenyl)-propan-1-one (DHPPA), an aromatic β-amino ketone that inhibits coactivator recruitment to thyroid hormone receptor β (TRβ), in a high-throughput screen. Initial evidence suggested that the aromatic β-enone 1-(4-hexylphenyl)-prop-2-en-1-one (HPPE), which alkylates a specific cysteine residue on the TRβ surface, is liberated from DHPPA. Nevertheless, aspects of the mechanism and specificity of action of DHPPA remained unclear. Here, we report an x-ray structure of TRβ with the inhibitor HPPE at 2.3-Å resolution. Unreacted HPPE is located at the interface that normally mediates binding between TRβ and its coactivator. Several lines of evidence, including experiments with TRβ mutants and mass spectroscopic analysis, showed that HPPE specifically alkylates cysteine residue 298 of TRβ, which is located near the activation function-2 pocket. We propose that this covalent adduct formation proceeds through a two-step mechanism: 1) β-elimination to form HPPE; and 2) a covalent bond slowly forms between HPPE and TRβ. DHPPA represents a novel class of potent TRβ antagonist, and its crystal structure suggests new ways to design antagonists that target the assembly of nuclear hormone receptor gene-regulatory complexes and block transcription.

Implicit methods for qualitative modeling of gene regulatory networks.

Advancements in high-throughput technologies to measure increasingly complex biological phenomena at the genomic level are rapidly changing the face of biological research from the single-gene single-protein experimental approach to studying the behavior of a gene in the context of the entire genome (and proteome). This shift in research methodologies has resulted in a new field of network biology that deals with modeling cellular behavior in terms of network structures such as signaling pathways and gene regulatory networks. In these networks, different biological entities such as genes, proteins, and metabolites interact with each other, giving rise to a dynamical system. Even though there exists a mature field of dynamical systems theory to model such network structures, some technical challenges are unique to biology such as the inability to measure precise kinetic information on gene-gene or gene-protein interactions and the need to model increasingly large networks comprising thousands of nodes. These challenges have renewed interest in developing new computational techniques for modeling complex biological systems. This chapter presents a modeling framework based on Boolean algebra and finite-state machines that are reminiscent of the approach used for digital circuit synthesis and simulation in the field of very-large-scale integration (VLSI). The proposed formalism enables a common mathematical framework to develop computational techniques for modeling different aspects of the regulatory networks such as steady-state behavior, stochasticity, and gene perturbation experiments.

Computational analysis of the genetic and environmental contributions to disease-related human phenotypes: From predicting adverse lipid response of HIV patients receiving antiretroviral therapy to genome-wide association studies of cardiovascular and lipid related disorders

Genetic variants influence the risk to develop certain diseases or give rise to differences in drug response. Recent progresses in cost-effective, high-throughput genome-wide techniques, such as microarrays measuring Single Nucleotide Polymorphisms (SNPs), have facilitated genotyping of large clinical and population cohorts. Combining the massive genotypic data with measurements of phenotypic traits allows for the determination of genetic differences that explain, at least in part, the phenotypic variations within a population. So far, models combining the most significant variants can only explain a small fraction of the variance, indicating the limitations of current models. In particular, researchers have only begun to address the possibility of interactions between genotypes and the environment. Elucidating the contributions of such interactions is a difficult task because of the large number of genetic as well as possible environmental factors.In this thesis, I worked on several projects within this context. My first and main project was the identification of possible SNP-environment interactions, where the phenotypes were serum lipid levels of patients from the Swiss HIV Cohort Study (SHCS) treated with antiretroviral therapy. Here the genotypes consisted of a limited set of SNPs in candidate genes relevant for lipid transport and metabolism. The environmental variables were the specific combinations of drugs given to each patient over the treatment period. My work explored bioinformatic and statistical approaches to relate patients' lipid responses to these SNPs, drugs and, importantly, their interactions. The goal of this project was to improve our understanding and to explore the possibility of predicting dyslipidemia, a well-known adverse drug reaction of antiretroviral therapy. Specifically, I quantified how much of the variance in lipid profiles could be explained by the host genetic variants, the administered drugs and SNP-drug interactions and assessed the predictive power of these features on lipid responses. Using cross-validation stratified by patients, we could not validate our hypothesis that models that select a subset of SNP-drug interactions in a principled way have better predictive power than the control models using "random" subsets. Nevertheless, all models tested containing SNP and/or drug terms, exhibited significant predictive power (as compared to a random predictor) and explained a sizable proportion of variance, in the patient stratified cross-validation context. Importantly, the model containing stepwise selected SNP terms showed higher capacity to predict triglyceride levels than a model containing randomly selected SNPs. Dyslipidemia is a complex trait for which many factors remain to be discovered, thus missing from the data, and possibly explaining the limitations of our analysis. In particular, the interactions of drugs with SNPs selected from the set of candidate genes likely have small effect sizes which we were unable to detect in a sample of the present size (<800 patients).In the second part of my thesis, I performed genome-wide association studies within the Cohorte Lausannoise (CoLaus). I have been involved in several international projects to identify SNPs that are associated with various traits, such as serum calcium, body mass index, two-hour glucose levels, as well as metabolic syndrome and its components. These phenotypes are all related to major human health issues, such as cardiovascular disease. I applied statistical methods to detect new variants associated with these phenotypes, contributing to the identification of new genetic loci that may lead to new insights into the genetic basis of these traits. This kind of research will lead to a better understanding of the mechanisms underlying these pathologies, a better evaluation of disease risk, the identification of new therapeutic leads and may ultimately lead to the realization of "personalized" medicine.

Context-dependent dual role of SKI8 homologs in mRNA synthesis and turnover.

Eukaryotic mRNA transcription and turnover is controlled by an enzymatic machinery that includes RNA polymerase II and the 3' to 5' exosome. The activity of these protein complexes is modulated by additional factors, such as the nuclear RNA polymerase II-associated factor 1 (Paf1c) and the cytoplasmic Superkiller (SKI) complex, respectively. Their components are conserved across uni- as well as multi-cellular organisms, including yeast, Arabidopsis, and humans. Among them, SKI8 displays multiple facets on top of its cytoplasmic role in the SKI complex. For instance, nuclear yeast ScSKI8 has an additional function in meiotic recombination, whereas nuclear human hSKI8 (unlike ScSKI8) associates with Paf1c. The Arabidopsis SKI8 homolog VERNALIZATION INDEPENDENT 3 (VIP3) has been found in Paf1c as well; however, whether it also has a role in the SKI complex remains obscure so far. We found that transgenic VIP3-GFP, which complements a novel vip3 mutant allele, localizes to both nucleus and cytoplasm. Consistently, biochemical analyses suggest that VIP3-GFP associates with the SKI complex. A role of VIP3 in the turnover of nuclear encoded mRNAs is supported by random-primed RNA sequencing of wild-type and vip3 seedlings, which indicates mRNA stabilization in vip3. Another SKI subunit homolog mutant, ski2, displays a dwarf phenotype similar to vip3. However, unlike vip3, it displays neither early flowering nor flower development phenotypes, suggesting that the latter reflect VIP3's role in Paf1c. Surprisingly then, transgenic ScSKI8 rescued all aspects of the vip3 phenotype, suggesting that the dual role of SKI8 depends on species-specific cellular context.

Multi-scale systems analysis of plant development : beyond cellular signaling and tissue morphodynamics

Les plantes sont essentielles pour les sociétés humaines. Notre alimentation quotidienne, les matériaux de constructions et les sources énergétiques dérivent de la biomasse végétale. En revanche, la compréhension des multiples aspects développementaux des plantes est encore peu exploitée et représente un sujet de recherche majeur pour la science. L'émergence des technologies à haut débit pour le séquençage de génome à grande échelle ou l'imagerie de haute résolution permet à présent de produire des quantités énormes d'information. L'analyse informatique est une façon d'intégrer ces données et de réduire la complexité apparente vers une échelle d'abstraction appropriée, dont la finalité est de fournir des perspectives de recherches ciblées. Ceci représente la raison première de cette thèse. En d'autres termes, nous appliquons des méthodes descriptives et prédictives combinées à des simulations numériques afin d'apporter des solutions originales à des problèmes relatifs à la morphogénèse à l'échelle de la cellule et de l'organe. Nous nous sommes fixés parmi les objectifs principaux de cette thèse d'élucider de quelle manière l'interaction croisée des phytohormones auxine et brassinosteroïdes (BRs) détermine la croissance de la cellule dans la racine du méristème apical d'Arabidopsis thaliana, l'organisme modèle de référence pour les études moléculaires en plantes. Pour reconstruire le réseau de signalement cellulaire, nous avons extrait de la littérature les informations pertinentes concernant les relations entre les protéines impliquées dans la transduction des signaux hormonaux. Le réseau a ensuite été modélisé en utilisant un formalisme logique et qualitatif pour pallier l'absence de données quantitatives. Tout d'abord, Les résultats ont permis de confirmer que l'auxine et les BRs agissent en synergie pour contrôler la croissance de la cellule, puis, d'expliquer des observations phénotypiques paradoxales et au final, de mettre à jour une interaction clef entre deux protéines dans la maintenance du méristème de la racine. Une étude ultérieure chez la plante modèle Brachypodium dystachion (Brachypo- dium) a révélé l'ajustement du réseau d'interaction croisée entre auxine et éthylène par rapport à Arabidopsis. Chez ce dernier, interférer avec la biosynthèse de l'auxine mène à la formation d'une racine courte. Néanmoins, nous avons isolé chez Brachypodium un mutant hypomorphique dans la biosynthèse de l'auxine qui affiche une racine plus longue. Nous avons alors conduit une analyse morphométrique qui a confirmé que des cellules plus anisotropique (plus fines et longues) sont à l'origine de ce phénotype racinaire. Des analyses plus approfondies ont démontré que la différence phénotypique entre Brachypodium et Arabidopsis s'explique par une inversion de la fonction régulatrice dans la relation entre le réseau de signalisation par l'éthylène et la biosynthèse de l'auxine. L'analyse morphométrique utilisée dans l'étude précédente exploite le pipeline de traitement d'image de notre méthode d'histologie quantitative. Pendant la croissance secondaire, la symétrie bilatérale de l'hypocotyle est remplacée par une symétrie radiale et une organisation concentrique des tissus constitutifs. Ces tissus sont initialement composés d'une douzaine de cellules mais peuvent aisément atteindre des dizaines de milliers dans les derniers stades du développement. Cette échelle dépasse largement le seuil d'investigation par les moyens dits 'traditionnels' comme l'imagerie directe de tissus en profondeur. L'étude de ce système pendant cette phase de développement ne peut se faire qu'en réalisant des coupes fines de l'organe, ce qui empêche une compréhension des phénomènes cellulaires dynamiques sous-jacents. Nous y avons remédié en proposant une stratégie originale nommée, histologie quantitative. De fait, nous avons extrait l'information contenue dans des images de très haute résolution de sections transverses d'hypocotyles en utilisant un pipeline d'analyse et de segmentation d'image à grande échelle. Nous l'avons ensuite combiné avec un algorithme de reconnaissance automatique des cellules. Cet outil nous a permis de réaliser une description quantitative de la progression de la croissance secondaire révélant des schémas développementales non-apparents avec une inspection visuelle classique. La formation de pôle de phloèmes en structure répétée et espacée entre eux d'une longueur constante illustre les bénéfices de notre approche. Par ailleurs, l'exploitation approfondie de ces résultats a montré un changement de croissance anisotropique des cellules du cambium et du phloème qui semble en phase avec l'expansion du xylème. Combinant des outils génétiques et de la modélisation biomécanique, nous avons démontré que seule la croissance plus rapide des tissus internes peut produire une réorientation de l'axe de croissance anisotropique des tissus périphériques. Cette prédiction a été confirmée par le calcul du ratio des taux de croissance du xylème et du phloème au cours de développement secondaire ; des ratios élevés sont effectivement observés et concomitant à l'établissement progressif et tangentiel du cambium. Ces résultats suggèrent un mécanisme d'auto-organisation établi par un gradient de division méristématique qui génèrent une distribution de contraintes mécaniques. Ceci réoriente la croissance anisotropique des tissus périphériques pour supporter la croissance secondaire. - Plants are essential for human society, because our daily food, construction materials and sustainable energy are derived from plant biomass. Yet, despite this importance, the multiple developmental aspects of plants are still poorly understood and represent a major challenge for science. With the emergence of high throughput devices for genome sequencing and high-resolution imaging, data has never been so easy to collect, generating huge amounts of information. Computational analysis is one way to integrate those data and to decrease the apparent complexity towards an appropriate scale of abstraction with the aim to eventually provide new answers and direct further research perspectives. This is the motivation behind this thesis work, i.e. the application of descriptive and predictive analytics combined with computational modeling to answer problems that revolve around morphogenesis at the subcellular and organ scale. One of the goals of this thesis is to elucidate how the auxin-brassinosteroid phytohormone interaction determines the cell growth in the root apical meristem of Arabidopsis thaliana (Arabidopsis), the plant model of reference for molecular studies. The pertinent information about signaling protein relationships was obtained through the literature to reconstruct the entire hormonal crosstalk. Due to a lack of quantitative information, we employed a qualitative modeling formalism. This work permitted to confirm the synergistic effect of the hormonal crosstalk on cell elongation, to explain some of our paradoxical mutant phenotypes and to predict a novel interaction between the BREVIS RADIX (BRX) protein and the transcription factor MONOPTEROS (MP),which turned out to be critical for the maintenance of the root meristem. On the same subcellular scale, another study in the monocot model Brachypodium dystachion (Brachypodium) revealed an alternative wiring of auxin-ethylene crosstalk as compared to Arabidopsis. In the latter, increasing interference with auxin biosynthesis results in progressively shorter roots. By contrast, a hypomorphic Brachypodium mutant isolated in this study in an enzyme of the auxin biosynthesis pathway displayed a dramatically longer seminal root. Our morphometric analysis confirmed that more anisotropic cells (thinner and longer) are principally responsible for the mutant root phenotype. Further characterization pointed towards an inverted regulatory logic in the relation between ethylene signaling and auxin biosynthesis in Brachypodium as compared to Arabidopsis, which explains the phenotypic discrepancy. Finally, the morphometric analysis of hypocotyl secondary growth that we applied in this study was performed with the image-processing pipeline of our quantitative histology method. During its secondary growth, the hypocotyl reorganizes its primary bilateral symmetry to a radial symmetry of highly specialized tissues comprising several thousand cells, starting with a few dozens. However, such a scale only permits observations in thin cross-sections, severely hampering a comprehensive analysis of the morphodynamics involved. Our quantitative histology strategy overcomes this limitation. We acquired hypocotyl cross-sections from tiled high-resolution images and extracted their information content using custom high-throughput image processing and segmentation. Coupled with an automated cell type recognition algorithm, it allows precise quantitative characterization of vascular development and reveals developmental patterns that were not evident from visual inspection, for example the steady interspace distance of the phloem poles. Further analyses indicated a change in growth anisotropy of cambial and phloem cells, which appeared in phase with the expansion of xylem. Combining genetic tools and computational modeling, we showed that the reorientation of growth anisotropy axis of peripheral tissue layers only occurs when the growth rate of central tissue is higher than the peripheral one. This was confirmed by the calculation of the ratio of the growth rate xylem to phloem throughout secondary growth. High ratios are indeed observed and concomitant with the homogenization of cambium anisotropy. These results suggest a self-organization mechanism, promoted by a gradient of division in the cambium that generates a pattern of mechanical constraints. This, in turn, reorients the growth anisotropy of peripheral tissues to sustain the secondary growth.

Novel insulated gamma and lentis retroviral vectors towards safer genetic modification of stem cells

In otherwise successful gene therapy trials insertional mutagenesis has resulted in leukemia. The identification of new short synthetic genetic insulator elements (GIE) which would both prevent such activation effects and shield the transgene from silencing, is a main challenge. Previous attempts with e.g. b-globin HS4, have met with poor efficacy and genetic instability. We have investigated potential improvement with two new candidate synthetic GIEs in SIN-gamma and lentiviral vectors. With each constructs two internal promoters have been tested: either the strong Fr- MuLV-U3 or the housekeeping hPGK.We could identify a specific combination of insulator 2 repeats which translates into best functional activity, high titers and boundary effect in both gammaretro and lentivectors. In target cells a dramatic shift of expression is observed with an homogenous profile the level of which strictly depends on the promoter strength. These data remain stable in both HeLa cells over three months and cord blood HSCs for two months, irrespective of the multiplicity of infection (MOI). In comparison, control native and SIN vectors expression levels show heterogeneous, depend on the MOI and prove unstable. We have undertaken genotoxicity assessment in comparing integration patterns ingenuity in human target cells sampled over three months using high-throughput pyro-sequencing. Data will be presented. Further genotoxicity assessment will include in vivo studies. We have established insulated vectors which harbour both boundary and enhancer-blocking effect and show stable in prolonged in vitro culture conditions. Work performed with support of EC-DG research FP6-NoE, CLINIGENE: LSHB-CT-2006-018933

Strategies and tools for preventing neurotoxicity: to test, to predict and how to do it

A change in paradigm is needed in the prevention of toxic effects on the nervous system, moving from its present reliance solely on data from animal testing to a prediction model mostly based on in vitro toxicity testing and in silico modeling. According to the report published by the National Research Council (NRC) of the US National Academies of Science, high-throughput in vitro tests will provide evidence for alterations in"toxicity pathways" as the best possible method of large scale toxicity prediction. The challenges to implement this proposal are enormous, and provide much room for debate. While many efforts address the technical aspects of implementing the vision, many questions around it need also to be addressed. Is the overall strategy the only one to be pursued? How can we move from current to future paradigms? Will we ever be able to reliably model for chronic and developmental neurotoxicity in vitro? This paper summarizes four presentations from a symposium held at the International Neurotoxicology Conference held in Xi"an, China, in June 2011. A. Li reviewed the current guidelines for neurotoxicity and developmental neurotoxicity testing, and discussed the major challenges existing to realize the NCR vision for toxicity testing. J. Llorens reviewed the biology of mammalian toxic avoidance in view of present knowledge on the physiology and molecular biology of the chemical senses, taste and smell. This background information supports the hypothesis that relating in vivo toxicity to chemical epitope descriptors that mimic the chemical encoding performed by the olfactory system may provide a way to the long term future of complete in silico toxicity prediction. S. Ceccatelli reviewed the implementation of rodent and human neural stem cells (NSCs) as models for in vitro toxicity testing that measures parameters such as cell proliferation, differentiation and migration. These appear to be sensitive endpoints that can identify substances with developmental neurotoxic potential. C. Sun ol reviewed the use of primary neuronal cultures in testing for neurotoxicity of environmental pollutants, including the study of the effects of persistent exposures and/or in differentiating cells, which allow recording of effects that can be extrapolated to human developmental neurotoxicity.

Networking of differentially expressed genes in human cancer cells resistant to methotrexate

BACKGROUND: The need for an integrated view of data obtained from high-throughput technologies gave rise to network analyses. These are especially useful to rationalize how external perturbations propagate through the expression of genes. To address this issue in the case of drug resistance, we constructed biological association networks of genes differentially expressed in cell lines resistant to methotrexate (MTX). METHODS: Seven cell lines representative of different types of cancer, including colon cancer (HT29 and Caco2), breast cancer (MCF-7 and MDA-MB-468), pancreatic cancer (MIA PaCa-2), erythroblastic leukemia (K562) and osteosarcoma (Saos-2), were used. The differential expression pattern between sensitive and MTX-resistant cells was determined by whole human genome microarrays and analyzed with the GeneSpring GX software package. Genes deregulated in common between the different cancer cell lines served to generate biological association networks using the Pathway Architect software. RESULTS: Dikkopf homolog-1 (DKK1) is a highly interconnected node in the network generated with genes in common between the two colon cancer cell lines, and functional validations of this target using small interfering RNAs (siRNAs) showed a chemosensitization toward MTX. Members of the UDP-glucuronosyltransferase 1A (UGT1A) family formed a network of genes differentially expressed in the two breast cancer cell lines. siRNA treatment against UGT1A also showed an increase in MTX sensitivity. Eukaryotic translation elongation factor 1 alpha 1 (EEF1A1) was overexpressed among the pancreatic cancer, leukemia and osteosarcoma cell lines, and siRNA treatment against EEF1A1 produced a chemosensitization toward MTX. CONCLUSIONS: Biological association networks identified DKK1, UGT1As and EEF1A1 as important gene nodes in MTX-resistance. Treatments using siRNA technology against these three genes showed chemosensitization toward MTX.

Genome-wide transcriptional responses to shade: Linking shade avoidance and auxin

Plants have the ability to use the composition of incident light as a cue to adapt development and growth to their environment. Arabidopsis thaliana as well as many crops are best adapted to sunny habitats. When subjected to shade, these plants exhibit a variety of physiological responses collectively called shade avoidance syndrome (SAS). It includes increased growth of hypocotyl and petioles, decreased growth rate of cotyledons and reduced branching and crop yield. These responses are mainly mediated by phytochrome photoreceptors, which exist either in an active, far-red light (FR) absorbing or an inactive, red light (R) absorbing isoform. In direct sunlight, the R to FR light (R/FR) ratio is high and converts the phytochromes into their physiologically active state. The phytochromes interact with downstream transcription factors such as PHYTOCHROME INTERACTING FACTOR (PIF), which are subsequently degraded. Light filtered through a canopy is strongly depleted in R, which result in a low R/FR ratio and renders the phytochromes inactive. Protein levels of downstream transcription factors are stabilized, which initiates the expression of shade-induced genes such as HFR1, PIL1 or ATHB-2. In my thesis, I investigated transcriptional responses mediated by the SAS in whole Arabidopsis seedlings. Using microarray and chromatin immunoprecipitation data, we identified genome-wide PIF4 and PIF5 dependent shade regulated gene as well as putative direct target genes of PIF5. This revealed evidence for a direct regulatory link between phytochrome signaling and the growth promoting phytohormone auxin (IAA) at the level of biosynthesis, transport and signaling. Subsequently, it was shown, that free-IAA levels are upregulated in response to shade. It is assumed that shade-induced auxin production takes predominantly place in cotyledons of seedlings. This implies, that IAA is subsequently transported basipetally to the hypocotyl and enhances elongation growth. The importance of auxin transport for growth responses has been established by chemical and genetic approaches. To gain a better understanding of spatio-temporal transcriptional regulation of shade-induce auxin, I generated in a second project, an organ specific high throughput data focusing on cotyledon and hypocotyl of young Arabidopsis seedlings. Interestingly, both organs show an opposite growth regulation by shade. I first investigated the spatio-transcriptional regulation of auxin re- sponsive gene, in order to determine how broad gene expression pattern can be explained by the hypothesized movement of auxin from cotyledons to hypocotyls in shade. The analysis suggests, that several genes are indeed regulated according to our prediction and others are regulated in a more complex manner. In addition, analysis of gene families of auxin biosynthetic and transport components, lead to the identification of essential family members for shade-induced growth re- sponses, which were subsequently experimentally confirmed. Finally, the analysis of expression pattern identified several candidate genes, which possibly explain aspects of the opposite growth response of the different organs.

Molecular insight into heart development and congenital heart disease: An update review from the Arab countries.

Congenital heart defect (CHD) has a major influence on affected individuals as well as on the supportive and associated environment such as the immediate family. Unfortunately, CHD is common worldwide with an incidence of approximately 1% and consequently is a major health concern. The Arab population has a high rate of consanguinity, fertility, birth, and annual population growth, in addition to a high incidence of diabetes mellitus and obesity. All these factors may lead to a higher incidence and prevalence of CHD within the Arab population than in the rest of the world, making CHD of even greater concern. Sadly, most Arab countries lack appropriate public health measures directed toward the control and prevention of congenital malformations and so the importance of CHD within the population remains unknown but is thought to be high. In approximately 85% of CHD patients, the multifactorial theory is considered as the pathologic basis. The genetic risk factors for CHD can be attributed to large chromosomal aberrations, copy number variations (CNV) of particular regions in the chromosome, and gene mutations in specific nuclear transcription pathways and in the genes that are involved in cardiac structure and development. The application of modern molecular biology techniques such as high-throughput nucleotide sequencing and chromosomal array and methylation array all have the potential to reveal more genetic defects linked to CHD. Exploring the genetic defects in CHD pathology will improve our knowledge and understanding about the diverse pathways involved and also about the progression of this disease. Ultimately, this will link to more efficient genetic diagnosis and development of novel preventive therapeutic strategies, as well as gene-targeted clinical management. This review summarizes our current understanding of the molecular basis of normal heart development and the pathophysiology of a wide range of CHD. The risk factors that might account for the high prevalence of CHD within the Arab population and the measures required to be undertaken for conducting research into CHD in Arab countries will also be discussed.

Quantitative proteomics of heat-treated human cells show an across-the-board mild depletion of housekeeping proteins to massively accumulate few HSPs.

Classic semiquantitative proteomic methods have shown that all organisms respond to a mild heat shock by an apparent massive accumulation of a small set of proteins, named heat-shock proteins (HSPs) and a concomitant slowing down in the synthesis of the other proteins. Yet unexplained, the increased levels of HSP messenger RNAs (mRNAs) may exceed 100 times the ensuing relative levels of HSP proteins. We used here high-throughput quantitative proteomics and targeted mRNA quantification to estimate in human cell cultures the mass and copy numbers of the most abundant proteins that become significantly accumulated, depleted, or unchanged during and following 4 h at 41 °C, which we define as mild heat shock. This treatment caused a minor across-the-board mass loss in many housekeeping proteins, which was matched by a mass gain in a few HSPs, predominantly cytosolic HSPCs (HSP90s) and HSPA8 (HSC70). As the mRNAs of the heat-depleted proteins were not significantly degraded and less ribosomes were recruited by excess new HSP mRNAs, the mild depletion of the many housekeeping proteins during heat shock was attributed to their slower replenishment. This differential protein expression pattern was reproduced by isothermal treatments with Hsp90 inhibitors. Unexpectedly, heat-treated cells accumulated 55 times more new molecules of HSPA8 (HSC70) than of the acknowledged heat-inducible isoform HSPA1A (HSP70), implying that when expressed as net copy number differences, rather than as mere "fold change" ratios, new biologically relevant information can be extracted from quantitative proteomic data. Raw data are available via ProteomeXchange with identifier PXD001666.

COMPASS identifies T-cell subsets correlated with clinical outcomes.

Advances in flow cytometry and other single-cell technologies have enabled high-dimensional, high-throughput measurements of individual cells as well as the interrogation of cell population heterogeneity. However, in many instances, computational tools to analyze the wealth of data generated by these technologies are lacking. Here, we present a computational framework for unbiased combinatorial polyfunctionality analysis of antigen-specific T-cell subsets (COMPASS). COMPASS uses a Bayesian hierarchical framework to model all observed cell subsets and select those most likely to have antigen-specific responses. Cell-subset responses are quantified by posterior probabilities, and human subject-level responses are quantified by two summary statistics that describe the quality of an individual's polyfunctional response and can be correlated directly with clinical outcome. Using three clinical data sets of cytokine production, we demonstrate how COMPASS improves characterization of antigen-specific T cells and reveals cellular 'correlates of protection/immunity' in the RV144 HIV vaccine efficacy trial that are missed by other methods. COMPASS is available as open-source software.

EMS mutagenesis in mature seed-derived rice calli as a new method for rapidly obtaining tilling mutant populations.

Background: TILLING (Targeting Induced Local Lesions IN Genomes) is a reverse genetic method that combines chemical mutagenesis with high-throughput genome-wide screening for point mutation detection in genes of interest. However, this mutation discovery approach faces a particular problem which is how to obtain a mutant population with a sufficiently high mutation density. Furthermore, plant mutagenesis protocols require two successive generations (M1, M2) for mutation fixation to occur before the analysis of the genotype can begin. Results: Here, we describe a new TILLING approach for rice based on ethyl methanesulfonate (EMS) mutagenesis of mature seed-derived calli and direct screening of in vitro regenerated plants. A high mutagenesis rate was obtained (i.e. one mutation in every 451 Kb) when plants were screened for two senescence-related genes. Screening was carried out in 2400 individuals from a mutant population of 6912. Seven sense change mutations out of 15 point mutations were identified. Conclusions: This new strategy represents a significant advantage in terms of time-savings (i.e. more than eight months), greenhouse space and work during the generation of mutant plant populations. Furthermore, this effective chemical mutagenesis protocol ensures high mutagenesis rates thereby saving in waste removal costs and the total amount of mutagen needed thanks to the mutagenesis volume reduction.

Structural Insight into the Mode of Action of a Direct Inhibitor of Coregulator Binding to the Thyroid Hormone Receptor.

The development of nuclear hormone receptor antagonists that directly inhibit the association of the receptor with its essential coactivators would allow useful manipulation of nuclear hormone receptor signaling. We previously identified 3-(dibutylamino)-1-(4-hexylphenyl)-propan-1-one (DHPPA), an aromatic β-amino ketone that inhibits coactivator recruitment to thyroid hormone receptor β (TRβ), in a high-throughput screen. Initial evidence suggested that the aromatic β-enone 1-(4-hexylphenyl)-prop-2-en-1-one (HPPE), which alkylates a specific cysteine residue on the TRβ surface, is liberated from DHPPA. Nevertheless, aspects of the mechanism and specificity of action of DHPPA remained unclear. Here, we report an x-ray structure of TRβ with the inhibitor HPPE at 2.3-Å resolution. Unreacted HPPE is located at the interface that normally mediates binding between TRβ and its coactivator. Several lines of evidence, including experiments with TRβ mutants and mass spectroscopic analysis, showed that HPPE specifically alkylates cysteine residue 298 of TRβ, which is located near the activation function-2 pocket. We propose that this covalent adduct formation proceeds through a two-step mechanism: 1) β-elimination to form HPPE; and 2) a covalent bond slowly forms between HPPE and TRβ. DHPPA represents a novel class of potent TRβ antagonist, and its crystal structure suggests new ways to design antagonists that target the assembly of nuclear hormone receptor gene-regulatory complexes and block transcription.