The eukaryotic Pso2/Snm1/Artemis proteins and their function as genomic and cellular caretakers

DNA double-strand breaks (DSBs) represent a major threat to the genomic stability of eukaryotic cells. DNA repair mechanisms such as non-homologous end joining (NHEJ) are responsible for the maintenance of eukaryotic genomes. Dysfunction of one or more of the many protein complexes that function in NHEJ can lead to sensitivity to DNA damaging agents, apoptosis, genomic instability, and severe combined immunodeficiency. One protein, Pso2p, was shown to participate in the repair of DSBs induced by DNA inter-strand cross-linking (ICL) agents such as cisplatin, nitrogen mustard or photo-activated bi-functional psoralens. The molecular function of Pso2p in DNA repair is unknown, but yeast and mammalian cell line mutants for PSO2 show the same cellular responses as strains with defects in NHEJ, e.g., sensitivity to ICLs and apoptosis. The Pso2p human homologue Artemis participates in V(D)J recombination. Mutations in Artemis induce a variety of immunological deficiencies, a predisposition to lymphomas, and an increase in chromosomal aberrations. In order to better understand the role of Pso2p in the repair of DSBs generated as repair intermediates of ICLs, an in silico approach was used to characterize the catalytic domain of Pso2p, which led to identification of novel Pso2p homologues in other organisms. Moreover, we found the catalytic core of Pso2p fused to different domains. In plants, a specific ATP-dependent DNA ligase I contains the catalytic core of Pso2p, constituting a new DNA ligase family, which was named LIG6. The possible functions of Pso2p/Artemis/Lig6p in NHEJ and V(D)J recombination and in other cellular metabolic reactions are discussed.

Modulation de l’expression du gène CFTR par le produit du gène FIC1 responsable de la cholestase familiale intra-hépatique progressive de type 1 : Identification des mécanismes moléculaires impliqués

Réalisé en cotutelle avec l'Université de Cergy-Pontoise

Crystal structure of Schistosoma purine nucleoside phosphorylase complexed with a novel monocyclic inhibitor

A novel inhibitor of Schistosoma PNP was identified using an ""in silico"" approach allied to enzyme inhibition assays. The compound has a monocyclic structure which has not been previously described for PNP inhibitors The crystallographic structure of the complex was determined and used to elucidate the binding mode within the active site Furthermore, the predicted pose was very similar to that determined crystallographically, validating the methodology The compound Sm_VS1, despite its low molecular weight, possesses an IC(50) of 1 3 mu M, surprisingly low when compared with purine analogues This is presumably due to the formation of eight hydrogen bonds with key residues in the active site E203, N245 and T244. The results of this study highlight the importance of the use of multiple conformations for the target during virtual screening. Indeed the Sm_VS1 compound was only identified after flipping the N245 side chain It is expected that the structure will be of use in the development of new highly active non-purine based compounds against the Sclustosoma enzyme. (c) 2010 Elsevier B V. All rights reserved

Analysis of independent microarray datasets of renal biopsies identifies a robust transcript signature of acute allograft rejection

Transcriptomics could contribute significantly to the early and specific diagnosis of rejection episodes by defining 'molecular Banff' signatures. Recently, the description of pathogenesis-based transcript sets offered a new opportunity for objective and quantitative diagnosis. Generating high-quality transcript panels is thus critical to define high-performance diagnostic classifier. In this study, a comparative analysis was performed across four different microarray datasets of heterogeneous sample collections from two published clinical datasets and two own datasets including biopsies for clinical indication, and samples from nonhuman primates. We characterized a common transcriptional profile of 70 genes, defined as acute rejection transcript set (ARTS). ARTS expression is significantly up-regulated in all AR samples as compared with stable allografts or healthy kidneys, and strongly correlates with the severity of Banff AR types. Similarly, ARTS were tested as a classifier in a large collection of 143 independent biopsies recently published by the University of Alberta. Results demonstrate that the 'in silico' approach applied in this study is able to identify a robust and reliable molecular signature for AR, supporting a specific and sensitive molecular diagnostic approach for renal transplant monitoring.

Global gene expression under nitrogen starvation in Xylella fastidiosa: contribution of the sigma(54) regulon

Background: Xylella fastidiosa, a Gram-negative fastidious bacterium, grows in the xylem of several plants causing diseases such as citrus variegated chlorosis. As the xylem sap contains low concentrations of amino acids and other compounds, X. fastidiosa needs to cope with nitrogen limitation in its natural habitat. Results: In this work, we performed a whole-genome microarray analysis of the X. fastidiosa nitrogen starvation response. A time course experiment (2, 8 and 12 hours) of cultures grown in defined medium under nitrogen starvation revealed many differentially expressed genes, such as those related to transport, nitrogen assimilation, amino acid biosynthesis, transcriptional regulation, and many genes encoding hypothetical proteins. In addition, a decrease in the expression levels of many genes involved in carbon metabolism and energy generation pathways was also observed. Comparison of gene expression profiles between the wild type strain and the rpoN null mutant allowed the identification of genes directly or indirectly induced by nitrogen starvation in a sigma(54)-dependent manner. A more complete picture of the sigma(54) regulon was achieved by combining the transcriptome data with an in silico search for potential sigma(54)-dependent promoters, using a position weight matrix approach. One of these sigma(54)-predicted binding sites, located upstream of the glnA gene (encoding glutamine synthetase), was validated by primer extension assays, confirming that this gene has a sigma(54)-dependent promoter. Conclusions: Together, these results show that nitrogen starvation causes intense changes in the X. fastidiosa transcriptome and some of these differentially expressed genes belong to the sigma(54) regulon.

Sequence conservation in Plasmodium falciparum alpha-helical coiled coil domains proposed for vaccine development.

BACKGROUND: The availability of the P. falciparum genome has led to novel ways to identify potential vaccine candidates. A new approach for antigen discovery based on the bioinformatic selection of heptad repeat motifs corresponding to alpha-helical coiled coil structures yielded promising results. To elucidate the question about the relationship between the coiled coil motifs and their sequence conservation, we have assessed the extent of polymorphism in putative alpha-helical coiled coil domains in culture strains, in natural populations and in the single nucleotide polymorphism data available at PlasmoDB. METHODOLOGY/PRINCIPAL FINDINGS: 14 alpha-helical coiled coil domains were selected based on preclinical experimental evaluation. They were tested by PCR amplification and sequencing of different P. falciparum culture strains and field isolates. We found that only 3 out of 14 alpha-helical coiled coils showed point mutations and/or length polymorphisms. Based on promising immunological results 5 of these peptides were selected for further analysis. Direct sequencing of field samples from Papua New Guinea and Tanzania showed that 3 out of these 5 peptides were completely conserved. An in silico analysis of polymorphism was performed for all 166 putative alpha-helical coiled coil domains originally identified in the P. falciparum genome. We found that 82% (137/166) of these peptides were conserved, and for one peptide only the detected SNPs decreased substantially the probability score for alpha-helical coiled coil formation. More SNPs were found in arrays of almost perfect tandem repeats. In summary, the coiled coil structure prediction was rarely modified by SNPs. The analysis revealed a number of peptides with strictly conserved alpha-helical coiled coil motifs. CONCLUSION/SIGNIFICANCE: We conclude that the selection of alpha-helical coiled coil structural motifs is a valuable approach to identify potential vaccine targets showing a high degree of conservation.

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

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

Novel MLPA procedure using self-designed probes allows comprehensive analysis for CNVs of the genes involved in Hirschsprung disease.

Background: Hirschsprung disease is characterized by the absence of intramural ganglion cells in the enteric plexuses, due to a fail during enteric nervous system formation. Hirschsprung has a complex genetic aetiology and mutations in several genes have been related to the disease. There is a clear predominance of missense/nonsense mutations in these genes whereas copy number variations (CNVs) have been seldom described, probably due to the limitations of conventional techniques usually employed for mutational analysis. In this study, we have looked for CNVs in some of the genes related to Hirschsprung (EDNRB, GFRA1, NRTN and PHOX2B) using the Multiple Ligation-dependent Probe Amplification (MLPA) approach. Methods: CNVs screening was performed in 208 HSCR patients using a self-designed set of MLPA probes, covering the coding region of those genes. Results: A deletion comprising the first 4 exons in GFRA1 gene was detected in 2 sporadic HSCR patients and in silico approaches have shown that the critical translation initiation signal in the mutant gene was abolished. In this study, we have been able to validate the reliability of this technique for CNVs screening in HSCR. Conclusions: The implemented MLPA based technique presented here allows CNV analysis of genes involved in HSCR that have not been not previously evaluated. Our results indicate that CNVs could be implicated in the pathogenesis of HSCR, although they seem to be an uncommon molecular cause of HSCR.

Population PK-guided simulation study in children exposed to drugs in human milk

Risks of significant infant drug exposure through human milk arepoorly defined due to lack of large-scale PK data. We propose to useBayesian approach based on population PK (popPK)-guided modelingand simulation for risk prediction. As a proof-of-principle study, weexploited fluoxetine milk concentration data from 25 women. popPKparameters including milk-to-plasma ratio (MP ratio) were estimatedfrom the best model. The dose of fluoxetine the breastfed infant wouldreceive through mother's milk, and infant plasma concentrations wereestimated from 1000 simulated mother-infant pairs, using randomassignment of feeding times and milk volume. A conservative estimateof CYP2D6 activity of 20% of the allometrically-adjusted adult valuewas assumed. Derived model parameters, including MP ratio were consistentwith those reported in the literature. Visual predictive check andother model diagnostics showed no signs of model misspecifications.The model simulation predicted that infant exposure levels to fluoxetinevia mother's milk were below 10% of weight-adjusted maternal therapeuticdoses in >99% of simulated infants. Predicted median ratio ofinfant-mother serum levels at steady state was 0.093 (range 0.033-0.31),consistent with literature reported values (mean=0.07; range 0-0.59).Predicted incidence of relatively high infant-mother ratio (>0.2) ofsteady-state serum fluoxetine concentrations was <1.3%. Overall, ourpredictions are consistent with clinical observations. Our approach maybe valid for other drugs, allowing in silico prediction of infant drugexposure risks through human milk. We will discuss application of thisapproach to another drug used in lactating women.

In vitro biotransformation of imatinib by the tumor expressed CYP1A1 and CYP1B1.

The main objective of the study was to examine the biotransformation of the anticancer drug imatinib in target cells by incubating it with oxidoreductases expressed in tumor cells. The second objective was to obtain an in silico prediction of the potential activity of imatinib metabolites. An in vitro enzyme kinetic study was performed with cDNA expressed human oxidoreductases and LC-MS/MS analysis. The kinetic parameters (Km and Vmax) were determined for six metabolites. A molecular modeling approach was used to dock these metabolites to the target Abl or Bcr-Abl kinases. CYP3A4 isozyme showed the broadest metabolic capacity, whereas CYP1A1, CYP1B1 and FMO3 isozymes biotransformed imatinib with a high intrinsic clearance. The predicted binding modes for the metabolites to Abl were comparable to that of the parent drug, suggesting potential activity. These findings indicate that CYP1A1 and CYP1B1, which are known to be overexpressed in a wide range of tumors, are involved in the biotransformation of imatinib. They could play a role in imatinib disposition in the targeted stem, progenitor and differentiated cancer cells, with a possible contribution of the metabolites toward the activity of the drug.

Minimal analytical characterisation of engineered nanomaterials need for hazard assessment in biological matrices

The safe and responsible development of engineered nanomaterials (ENM), nanotechnology-based materials and products, together with the definition of regulatory measures and implementation of "nano"-legislation in Europe require a widely supported scientific basis and sufficient high quality data upon which to base decisions. At the very core of such a scientific basis is a general agreement on key issues related to risk assessment of ENMs which encompass the key parameters to characterise ENMs, appropriate methods of analysis and best approach to express the effect of ENMs in widely accepted dose response toxicity tests. The following major conclusions were drawn: Due to high batch variability of ENMs characteristics of commercially available and to a lesser degree laboratory made ENMs it is not possible to make general statements regarding the toxicity resulting from exposure to ENMs. 1) Concomitant with using the OECD priority list of ENMs, other criteria for selection of ENMs like relevance for mechanistic (scientific) studies or risk assessment-based studies, widespread availability (and thus high expected volumes of use) or consumer concern (route of consumer exposure depending on application) could be helpful. The OECD priority list is focussing on validity of OECD tests. Therefore source material will be first in scope for testing. However for risk assessment it is much more relevant to have toxicity data from material as present in products/matrices to which men and environment are be exposed. 2) For most, if not all characteristics of ENMs, standardized methods analytical methods, though not necessarily validated, are available. Generally these methods are only able to determine one single characteristic and some of them can be rather expensive. Practically, it is currently not feasible to fully characterise ENMs. Many techniques that are available to measure the same nanomaterial characteristic produce contrasting results (e.g. reported sizes of ENMs). It was recommended that at least two complementary techniques should be employed to determine a metric of ENMs. The first great challenge is to prioritise metrics which are relevant in the assessment of biological dose response relations and to develop analytical methods for characterising ENMs in biological matrices. It was generally agreed that one metric is not sufficient to describe fully ENMs. 3) Characterisation of ENMs in biological matrices starts with sample preparation. It was concluded that there currently is no standard approach/protocol for sample preparation to control agglomeration/aggregation and (re)dispersion. It was recommended harmonization should be initiated and that exchange of protocols should take place. The precise methods used to disperse ENMs should be specifically, yet succinctly described within the experimental section of a publication. 4) ENMs need to be characterised in the matrix as it is presented to the test system (in vitro/ in vivo). 5) Alternative approaches (e.g. biological or in silico systems) for the characterisation of ENMS are simply not possible with the current knowledge. Contributors: Iseult Lynch, Hans Marvin, Kenneth Dawson, Markus Berges, Diane Braguer, Hugh J. Byrne, Alan Casey, Gordon Chambers, Martin Clift, Giuliano Elia1, Teresa F. Fernandes, Lise Fjellsbø, Peter Hatto, Lucienne Juillerat, Christoph Klein, Wolfgang Kreyling, Carmen Nickel1, and Vicki Stone.

A novel in vitro metabolomics approach for neurotoxicity testing, proof of principle for methyl mercury chloride and caffeine

There is a need for more efficient methods giving insight into the complex mechanisms of neurotoxicity. Testing strategies including in vitro methods have been proposed to comply with this requirement. With the present study we aimed to develop a novel in vitro approach which mimics in vivo complexity, detects neurotoxicity comprehensively, and provides mechanistic insight. For this purpose we combined rat primary re-aggregating brain cell cultures with a mass spectrometry (MS)-based metabolomics approach. For the proof of principle we treated developing re-aggregating brain cell cultures for 48h with the neurotoxicant methyl mercury chloride (0.1-100muM) and the brain stimulant caffeine (1-100muM) and acquired cellular metabolic profiles. To detect toxicant-induced metabolic alterations the profiles were analysed using commercial software which revealed patterns in the multi-parametric dataset by principal component analyses (PCA), and recognised the most significantly altered metabolites. PCA revealed concentration-dependent cluster formations for methyl mercury chloride (0.1-1muM), and treatment-dependent cluster formations for caffeine (1-100muM) at sub-cytotoxic concentrations. Four relevant metabolites responsible for the concentration-dependent alterations following methyl mercury chloride treatment could be identified using MS-MS fragmentation analysis. These were gamma-aminobutyric acid, choline, glutamine, creatine and spermine. Their respective mass ion intensities demonstrated metabolic alterations in line with the literature and suggest that the metabolites could be biomarkers for mechanisms of neurotoxicity or neuroprotection. In addition, we evaluated whether the approach could identify neurotoxic potential by testing eight compounds which have target organ toxicity in the liver, kidney or brain at sub-cytotoxic concentrations. PCA revealed cluster formations largely dependent on target organ toxicity indicating possible potential for the development of a neurotoxicity prediction model. With such results it could be useful to perform a validation study to determine the reliability, relevance and applicability of this approach to neurotoxicity screening. Thus, for the first time we show the benefits and utility of in vitro metabolomics to comprehensively detect neurotoxicity and to discover new biomarkers.

Instrumentation and Monitoring of Precast Bridge Approach Tied to an Integral Abutment Bridge in Bremer County, SPR 0000-005, 2010

Approach slab pavement at integral abutment (I-A) bridges are prone to settlement and cracking, which has been long recognized by the Iowa Department of Transportation (DOT). A commonly recommended solution is to integrally attach the approach slab to the bridge abutment. This study sought to supplement a previous project by instrumenting, monitoring, and analyzing the behavior of an approach slab tied to a integral abutment bridge. The primary objective of this investigation was to evaluate the performance of the approach slab. To satisfy the research needs, the project scope involved reviewing a similar previous study, implementing a health monitoring system on the approach slab, interpreting the data obtained during the evaluation, and conducting periodic visual inspections of the bridge and approach slab. Based on the information obtained from the testing, the following general conclusions were made: the integral connection between the approach slab and the bridge appears to function well with no observed distress at this location and no relative longitudinal movement measured between the two components; the measured strains in the approach slabs indicate a force exists at the expansion joint and should be taken into consideration when designing both the approach slab and the bridge and the observed responses generally followed an annual cyclic and/or short term cyclic pattern over time; the expansion joint at one side of the approach slab does not appear to be functioning as well as elsewhere; much larger frictional forces were observed in this study compared to the previous study.

Qualitative modeling identifies IL-11 as a novel regulator in maintaining self-renewal in human pluripotent stem cells.

Pluripotency in human embryonic stem cells (hESCs) and induced pluripotent stem cells (iPSCs) is regulated by three transcription factors-OCT3/4, SOX2, and NANOG. To fully exploit the therapeutic potential of these cells it is essential to have a good mechanistic understanding of the maintenance of self-renewal and pluripotency. In this study, we demonstrate a powerful systems biology approach in which we first expand literature-based network encompassing the core regulators of pluripotency by assessing the behavior of genes targeted by perturbation experiments. We focused our attention on highly regulated genes encoding cell surface and secreted proteins as these can be more easily manipulated by the use of inhibitors or recombinant proteins. Qualitative modeling based on combining boolean networks and in silico perturbation experiments were employed to identify novel pluripotency-regulating genes. We validated Interleukin-11 (IL-11) and demonstrate that this cytokine is a novel pluripotency-associated factor capable of supporting self-renewal in the absence of exogenously added bFGF in culture. To date, the various protocols for hESCs maintenance require supplementation with bFGF to activate the Activin/Nodal branch of the TGFβ signaling pathway. Additional evidence supporting our findings is that IL-11 belongs to the same protein family as LIF, which is known to be necessary for maintaining pluripotency in mouse but not in human ESCs. These cytokines operate through the same gp130 receptor which interacts with Janus kinases. Our finding might explain why mESCs are in a more naïve cell state compared to hESCs and how to convert primed hESCs back to the naïve state. Taken together, our integrative modeling approach has identified novel genes as putative candidates to be incorporated into the expansion of the current gene regulatory network responsible for inducing and maintaining pluripotency.

Use of physiological constraints to identify quantitative design principles for gene expression in yeast adaptation to heat shock

Background: Understanding the relationship between gene expression changes, enzyme activity shifts, and the corresponding physiological adaptive response of organisms to environmental cues is crucial in explaining how cells cope with stress. For example, adaptation of yeast to heat shock involves a characteristic profile of changes to the expression levels of genes coding for enzymes of the glycolytic pathway and some of its branches. The experimental determination of changes in gene expression profiles provides a descriptive picture of the adaptive response to stress. However, it does not explain why a particular profile is selected for any given response. Results: We used mathematical models and analysis of in silico gene expression profiles (GEPs) to understand how changes in gene expression correlate to an efficient response of yeast cells to heat shock. An exhaustive set of GEPs, matched with the corresponding set of enzyme activities, was simulated and analyzed. The effectiveness of each profile in the response to heat shock was evaluated according to relevant physiological and functional criteria. The small subset of GEPs that lead to effective physiological responses after heat shock was identified as the result of the tuning of several evolutionary criteria. The experimentally observed transcriptional changes in response to heat shock belong to this set and can be explained by quantitative design principles at the physiological level that ultimately constrain changes in gene expression. Conclusion: Our theoretical approach suggests a method for understanding the combined effect of changes in the expression of multiple genes on the activity of metabolic pathways, and consequently on the adaptation of cellular metabolism to heat shock. This method identifies quantitative design principles that facilitate understating the response of the cell to stress.