Valproate treatment of human cord blood CD4-positive effector T cells confers on them the molecular profile (microRNA signature and FOXP3 expression) of natural regulatory CD4-positive cells through inhibition of histone deacetylase.

Regulatory T cells (Tregs) play a key role in immune system homeostasis and tolerance to antigens, thereby preventing autoimmunity, and may be partly responsible for the lack of an appropriate immune response against tumor cells. Although not sufficient, a high expression of forkhead box P3 (FOXP3) is necessary for their suppressive function. Recent reports have shown that histones deacetylase inhibitors increased FOXP3 expression in T cells. We therefore decided to investigate in non-Tregs CD4-positive cells, the mechanisms by which an aspecific opening of the chromatin could lead to an increased FOXP3 expression. We focused on binding of potentially activating transcription factors to the promoter region of FOXP3 and on modifications in the five miRs constituting the Tregs signature. Valproate treatment induced binding of Ets-1 and Ets-2 to the FOXP3 promoter and acted positively on its expression, by increasing the acetylation of histone H4 lysines. Valproate treatment also induced the acquisition of the miRs Tregs signature. To elucidate whether the changes in the miRs expression could be due to the increased FOXP3 expression, we transduced these non-Tregs with a FOXP3 lentiviral expression vector, and found no changes in miRs expression. Therefore, the modification in their miRs expression profile is not due to an increased expression of FOXP3 but directly results from histones deacetylase inhibition. Rather, the increased FOXP3 expression results from the additive effects of Ets factors binding and the change in expression level of miR-21 and miR-31. We conclude that valproate treatment of human non-Tregs confers on them a molecular profile similar to that of their regulatory counterpart.

The M-Coffee web server: a meta-method for computing multiple sequence alignments by combining alternative alignment methods.

The M-Coffee server is a web server that makes it possible to compute multiple sequence alignments (MSAs) by running several MSA methods and combining their output into one single model. This allows the user to simultaneously run all his methods of choice without having to arbitrarily choose one of them. The MSA is delivered along with a local estimation of its consistency with the individual MSAs it was derived from. The computation of the consensus multiple alignment is carried out using a special mode of the T-Coffee package [Notredame, Higgins and Heringa (T-Coffee: a novel method for fast and accurate multiple sequence alignment. J. Mol. Biol. 2000; 302: 205-217); Wallace, O'Sullivan, Higgins and Notredame (M-Coffee: combining multiple sequence alignment methods with T-Coffee. Nucleic Acids Res. 2006; 34: 1692-1699)] Given a set of sequences (DNA or proteins) in FASTA format, M-Coffee delivers a multiple alignment in the most common formats. M-Coffee is a freeware open source package distributed under a GPL license and it is available either as a standalone package or as a web service from www.tcoffee.org.

Molecular investigation of lymph nodes in colon cancer patients using one-step nucleic acid amplification (OSNA): a new road to better staging?

BACKGROUND: A new diagnostic system, called one-step nucleic acid amplification (OSNA), has recently been designed to detect cytokeratin 19 mRNA as a surrogate for lymph node metastases. The objective of this prospective investigation was to compare the performance of OSNA with both standard hematoxylin and eosin (H&E) analysis and intensive histopathology in the detection of colon cancer lymph node metastases. METHODS: In total, 313 lymph nodes from 22 consecutive patients with stage I, II, and III colon cancer were assessed. Half of each lymph node was analyzed initially by H&E followed by an intensive histologic workup (5 levels of H&E and immunohistochemistry analyses, the gold standard for the assessment of sensitivity/specificity of OSNA), and the other half was analyzed using OSNA. RESULTS: OSNA was more sensitive in detecting small lymph node tumor infiltrates compared with H&E (11 results were OSNA positive/H&E negative). Compared with intensive histopathology, OSNA had 94.5% sensitivity, 97.6% specificity, and a concordance rate of 97.1%. OSNA resulted in an upstaging of 2 of 13 patients (15.3%) with lymph node-negative colon cancer after standard H&E examination. CONCLUSIONS: OSNA appeared to be a powerful and promising molecular tool for the detection of lymph node metastases in patients with colon cancer. OSNA had similar performance in the detection of lymph node metastases compared with intensive histopathologic investigations and appeared to be superior to standard histology with H&E. Most important, the authors concluded that OSNA may lead to a potential upstaging of >15% of patients with colon cancer.

EADock : design of a new molecular docking algorithm and some of its applications

3 Summary 3. 1 English The pharmaceutical industry has been facing several challenges during the last years, and the optimization of their drug discovery pipeline is believed to be the only viable solution. High-throughput techniques do participate actively to this optimization, especially when complemented by computational approaches aiming at rationalizing the enormous amount of information that they can produce. In siiico techniques, such as virtual screening or rational drug design, are now routinely used to guide drug discovery. Both heavily rely on the prediction of the molecular interaction (docking) occurring between drug-like molecules and a therapeutically relevant target. Several softwares are available to this end, but despite the very promising picture drawn in most benchmarks, they still hold several hidden weaknesses. As pointed out in several recent reviews, the docking problem is far from being solved, and there is now a need for methods able to identify binding modes with a high accuracy, which is essential to reliably compute the binding free energy of the ligand. This quantity is directly linked to its affinity and can be related to its biological activity. Accurate docking algorithms are thus critical for both the discovery and the rational optimization of new drugs. In this thesis, a new docking software aiming at this goal is presented, EADock. It uses a hybrid evolutionary algorithm with two fitness functions, in combination with a sophisticated management of the diversity. EADock is interfaced with .the CHARMM package for energy calculations and coordinate handling. A validation was carried out on 37 crystallized protein-ligand complexes featuring 11 different proteins. The search space was defined as a sphere of 15 R around the center of mass of the ligand position in the crystal structure, and conversely to other benchmarks, our algorithms was fed with optimized ligand positions up to 10 A root mean square deviation 2MSD) from the crystal structure. This validation illustrates the efficiency of our sampling heuristic, as correct binding modes, defined by a RMSD to the crystal structure lower than 2 A, were identified and ranked first for 68% of the complexes. The success rate increases to 78% when considering the five best-ranked clusters, and 92% when all clusters present in the last generation are taken into account. Most failures in this benchmark could be explained by the presence of crystal contacts in the experimental structure. EADock has been used to understand molecular interactions involved in the regulation of the Na,K ATPase, and in the activation of the nuclear hormone peroxisome proliferatoractivated receptors a (PPARa). It also helped to understand the action of common pollutants (phthalates) on PPARy, and the impact of biotransformations of the anticancer drug Imatinib (Gleevec®) on its binding mode to the Bcr-Abl tyrosine kinase. Finally, a fragment-based rational drug design approach using EADock was developed, and led to the successful design of new peptidic ligands for the a5ß1 integrin, and for the human PPARa. In both cases, the designed peptides presented activities comparable to that of well-established ligands such as the anticancer drug Cilengitide and Wy14,643, respectively. 3.2 French Les récentes difficultés de l'industrie pharmaceutique ne semblent pouvoir se résoudre que par l'optimisation de leur processus de développement de médicaments. Cette dernière implique de plus en plus. de techniques dites "haut-débit", particulièrement efficaces lorsqu'elles sont couplées aux outils informatiques permettant de gérer la masse de données produite. Désormais, les approches in silico telles que le criblage virtuel ou la conception rationnelle de nouvelles molécules sont utilisées couramment. Toutes deux reposent sur la capacité à prédire les détails de l'interaction moléculaire entre une molécule ressemblant à un principe actif (PA) et une protéine cible ayant un intérêt thérapeutique. Les comparatifs de logiciels s'attaquant à cette prédiction sont flatteurs, mais plusieurs problèmes subsistent. La littérature récente tend à remettre en cause leur fiabilité, affirmant l'émergence .d'un besoin pour des approches plus précises du mode d'interaction. Cette précision est essentielle au calcul de l'énergie libre de liaison, qui est directement liée à l'affinité du PA potentiel pour la protéine cible, et indirectement liée à son activité biologique. Une prédiction précise est d'une importance toute particulière pour la découverte et l'optimisation de nouvelles molécules actives. Cette thèse présente un nouveau logiciel, EADock, mettant en avant une telle précision. Cet algorithme évolutionnaire hybride utilise deux pressions de sélections, combinées à une gestion de la diversité sophistiquée. EADock repose sur CHARMM pour les calculs d'énergie et la gestion des coordonnées atomiques. Sa validation a été effectuée sur 37 complexes protéine-ligand cristallisés, incluant 11 protéines différentes. L'espace de recherche a été étendu à une sphère de 151 de rayon autour du centre de masse du ligand cristallisé, et contrairement aux comparatifs habituels, l'algorithme est parti de solutions optimisées présentant un RMSD jusqu'à 10 R par rapport à la structure cristalline. Cette validation a permis de mettre en évidence l'efficacité de notre heuristique de recherche car des modes d'interactions présentant un RMSD inférieur à 2 R par rapport à la structure cristalline ont été classés premier pour 68% des complexes. Lorsque les cinq meilleures solutions sont prises en compte, le taux de succès grimpe à 78%, et 92% lorsque la totalité de la dernière génération est prise en compte. La plupart des erreurs de prédiction sont imputables à la présence de contacts cristallins. Depuis, EADock a été utilisé pour comprendre les mécanismes moléculaires impliqués dans la régulation de la Na,K ATPase et dans l'activation du peroxisome proliferatoractivated receptor a (PPARa). Il a également permis de décrire l'interaction de polluants couramment rencontrés sur PPARy, ainsi que l'influence de la métabolisation de l'Imatinib (PA anticancéreux) sur la fixation à la kinase Bcr-Abl. Une approche basée sur la prédiction des interactions de fragments moléculaires avec protéine cible est également proposée. Elle a permis la découverte de nouveaux ligands peptidiques de PPARa et de l'intégrine a5ß1. Dans les deux cas, l'activité de ces nouveaux peptides est comparable à celles de ligands bien établis, comme le Wy14,643 pour le premier, et le Cilengitide (PA anticancéreux) pour la seconde.

Molecular evidence of interhuman transmission of Pneumocystis pneumonia among renal transplant recipients hospitalized with HIV-infected patients.

Ten Pneumocystis jirovecii pneumonia (PCP) cases were diagnosed in renal transplant recipients (RTRs) during a 3-year period. Nosocomial transmission from HIV-positive patients with PCP was suspected because these patients shared the same hospital building, were not isolated, and were receiving suboptimal anti-PCP prophylaxis or none. P. jirovecii organisms were typed with the multitarget polymerase chain reaction-single-strand conformation polymorphism method. Among the 45 patients with PCP hospitalized during the 3-year period, 8 RTRs and 6 HIV-infected patients may have encountered at least 1 patient with active PCP within the 3 months before the diagnosis of their own PCP episode. In six instances (five RTRs, one HIV-infected patient), the patients harbored the same P. jirovecii molecular type as that found in the encountered PCP patients. The data suggest that part of the PCP cases observed in this building, particularly those observed in RTRs, were related to nosocomial interhuman transmission.

Study of the impact of tissue density heterogeneities on 3-dimensional abdominal dosimetry: comparison between dose kernel convolution and direct monte carlo methods.

Dose kernel convolution (DK) methods have been proposed to speed up absorbed dose calculations in molecular radionuclide therapy. Our aim was to evaluate the impact of tissue density heterogeneities (TDH) on dosimetry when using a DK method and to propose a simple density-correction method. METHODS: This study has been conducted on 3 clinical cases: case 1, non-Hodgkin lymphoma treated with (131)I-tositumomab; case 2, a neuroendocrine tumor treatment simulated with (177)Lu-peptides; and case 3, hepatocellular carcinoma treated with (90)Y-microspheres. Absorbed dose calculations were performed using a direct Monte Carlo approach accounting for TDH (3D-RD), and a DK approach (VoxelDose, or VD). For each individual voxel, the VD absorbed dose, D(VD), calculated assuming uniform density, was corrected for density, giving D(VDd). The average 3D-RD absorbed dose values, D(3DRD), were compared with D(VD) and D(VDd), using the relative difference Δ(VD/3DRD). At the voxel level, density-binned Δ(VD/3DRD) and Δ(VDd/3DRD) were plotted against ρ and fitted with a linear regression. RESULTS: The D(VD) calculations showed a good agreement with D(3DRD). Δ(VD/3DRD) was less than 3.5%, except for the tumor of case 1 (5.9%) and the renal cortex of case 2 (5.6%). At the voxel level, the Δ(VD/3DRD) range was 0%-14% for cases 1 and 2, and -3% to 7% for case 3. All 3 cases showed a linear relationship between voxel bin-averaged Δ(VD/3DRD) and density, ρ: case 1 (Δ = -0.56ρ + 0.62, R(2) = 0.93), case 2 (Δ = -0.91ρ + 0.96, R(2) = 0.99), and case 3 (Δ = -0.69ρ + 0.72, R(2) = 0.91). The density correction improved the agreement of the DK method with the Monte Carlo approach (Δ(VDd/3DRD) < 1.1%), but with a lesser extent for the tumor of case 1 (3.1%). At the voxel level, the Δ(VDd/3DRD) range decreased for the 3 clinical cases (case 1, -1% to 4%; case 2, -0.5% to 1.5%, and -1.5% to 2%). No more linear regression existed for cases 2 and 3, contrary to case 1 (Δ = 0.41ρ - 0.38, R(2) = 0.88) although the slope in case 1 was less pronounced. CONCLUSION: This study shows a small influence of TDH in the abdominal region for 3 representative clinical cases. A simple density-correction method was proposed and improved the comparison in the absorbed dose calculations when using our voxel S value implementation.

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.

Combining hypoxic methods for peak performance.

New methods and devices for pursuing performance enhancement through altitude training were developed in Scandinavia and the USA in the early 1990s. At present, several forms of hypoxic training and/or altitude exposure exist: traditional 'live high-train high' (LHTH), contemporary 'live high-train low' (LHTL), intermittent hypoxic exposure during rest (IHE) and intermittent hypoxic exposure during continuous session (IHT). Although substantial differences exist between these methods of hypoxic training and/or exposure, all have the same goal: to induce an improvement in athletic performance at sea level. They are also used for preparation for competition at altitude and/or for the acclimatization of mountaineers. The underlying mechanisms behind the effects of hypoxic training are widely debated. Although the popular view is that altitude training may lead to an increase in haematological capacity, this may not be the main, or the only, factor involved in the improvement of performance. Other central (such as ventilatory, haemodynamic or neural adaptation) or peripheral (such as muscle buffering capacity or economy) factors play an important role. LHTL was shown to be an efficient method. The optimal altitude for living high has been defined as being 2200-2500 m to provide an optimal erythropoietic effect and up to 3100 m for non-haematological parameters. The optimal duration at altitude appears to be 4 weeks for inducing accelerated erythropoiesis whereas &lt;3 weeks (i.e. 18 days) are long enough for beneficial changes in economy, muscle buffering capacity, the hypoxic ventilatory response or Na(+)/K(+)-ATPase activity. One critical point is the daily dose of altitude. A natural altitude of 2500 m for 20-22 h/day (in fact, travelling down to the valley only for training) appears sufficient to increase erythropoiesis and improve sea-level performance. 'Longer is better' as regards haematological changes since additional benefits have been shown as hypoxic exposure increases beyond 16 h/day. The minimum daily dose for stimulating erythropoiesis seems to be 12 h/day. For non-haematological changes, the implementation of a much shorter duration of exposure seems possible. Athletes could take advantage of IHT, which seems more beneficial than IHE in performance enhancement. The intensity of hypoxic exercise might play a role on adaptations at the molecular level in skeletal muscle tissue. There is clear evidence that intense exercise at high altitude stimulates to a greater extent muscle adaptations for both aerobic and anaerobic exercises and limits the decrease in power. So although IHT induces no increase in VO(2max) due to the low 'altitude dose', improvement in athletic performance is likely to happen with high-intensity exercise (i.e. above the ventilatory threshold) due to an increase in mitochondrial efficiency and pH/lactate regulation. We propose a new combination of hypoxic method (which we suggest naming Living High-Training Low and High, interspersed; LHTLHi) combining LHTL (five nights at 3000 m and two nights at sea level) with training at sea level except for a few (2.3 per week) IHT sessions of supra-threshold training. This review also provides a rationale on how to combine the different hypoxic methods and suggests advances in both their implementation and their periodization during the yearly training programme of athletes competing in endurance, glycolytic or intermittent sports.

Evolutionary aspects of population structure for molecular and quantitative traits in the freshwater snail Radix balthica.

Detecting the action of selection in natural populations can be achieved using the QST-FST comparison that relies on the estimation of FST with neutral markers, and QST using quantitative traits potentially under selection. QST higher than FST suggests the action of directional selection and thus potential local adaptation. In this article, we apply the QST-FST comparison to four populations of the hermaphroditic freshwater snail Radix balthica located in a floodplain habitat. In contrast to most studies published so far, we did not detect evidence of directional selection for local optima for any of the traits we measured: QST calculated using three different methods was never higher than FST. A strong inbreeding depression was also detected, indicating that outcrossing is probably predominant over selfing in the studied populations. Our results suggest that in this floodplain habitat, local adaptation of R. balthica populations may be hindered by genetic drift, and possibly altered by uneven gene flow linked to flood frequency.

Urinary low-molecular-weight protein excretion in pediatric idiopathic nephrotic syndrome.

BACKGROUND: Minimal change disease (MCD) and focal segmental glomerulosclerosis (FSGS) are the most common causes of idiopathic nephrotic syndrome (INS). We have evaluated the reliability of urinary neutrophil-gelatinase-associated lipocalin (uNGAL), urinary alpha1-microglobulin (uα1M) and urinary N-acetyl-beta-D-glucosaminidase (uβNAG) as markers for differentiating MCD from FSGS. We have also evaluated whether these proteins are associated to INS relapses or to glomerular filtration rate (GFR). METHODS: The patient cohort comprised 35 children with MCD and nine with FSGS; 19 healthy age-matched children were included in the study as controls. Of the 35 patients, 28 were in remission (21 MCD, 7 FSGS) and 16 were in relapse (14 MCD, 2 FSGS). The prognostic accuracies of these proteins were assessed by receiver operating characteristic (ROC) curve analyses. RESULTS: The level of uNGAL, indexed or not to urinary creatinine (uCreat), was significantly different between children with INS and healthy children (p = 0.02), between healthy children and those with FSGS (p = 0.007) and between children with MCD and those with FSGS (p = 0.01). It was not significantly correlated to proteinuria or GFR levels. The ROC curve analysis showed that a cut-off value of 17 ng/mg for the uNGAL/uCreat ratio could be used to distinguish MCD from FSGS with a sensitivity of 0.77 and specificity of 0.78. uβNAG was not significantly different in patients with MCD and those with FSGS (p = 0.86). Only uα1M, indexed or not to uCreat, was significantly (p < 0.001) higher for patients in relapse compared to those in remission. CONCLUSIONS: Our results indicate that in our patient cohort uNGAL was a reliable biomarker for differentiating MCD from FSGS independently of proteinuria or GFR levels.

PAX3/FOXO1 fusion gene status is the key prognostic molecular marker in rhabdomyosarcoma and significantly improves current risk stratification.

PURPOSE: To improve the risk stratification of patients with rhabdomyosarcoma (RMS) through the use of clinical and molecular biologic data. PATIENTS AND METHODS: Two independent data sets of gene-expression profiling for 124 and 101 patients with RMS were used to derive prognostic gene signatures by using a meta-analysis. These and a previously published metagene signature were evaluated by using cross validation analyses. A combined clinical and molecular risk-stratification scheme that incorporated the PAX3/FOXO1 fusion gene status was derived from 287 patients with RMS and evaluated. RESULTS: We showed that our prognostic gene-expression signature and the one previously published performed well with reproducible and significant effects. However, their effect was reduced when cross validated or tested in independent data and did not add new prognostic information over the fusion gene status, which is simpler to assay. Among nonmetastatic patients, patients who were PAX3/FOXO1 positive had a significantly poorer outcome compared with both alveolar-negative and PAX7/FOXO1-positive patients. Furthermore, a new clinicomolecular risk score that incorporated fusion gene status (negative and PAX3/FOXO1 and PAX7/FOXO1 positive), Intergroup Rhabdomyosarcoma Study TNM stage, and age showed a significant increase in performance over the current risk-stratification scheme. CONCLUSION: Gene signatures can improve current stratification of patients with RMS but will require complex assays to be developed and extensive validation before clinical application. A significant majority of their prognostic value was encapsulated by the fusion gene status. A continuous risk score derived from the combination of clinical parameters with the presence or absence of PAX3/FOXO1 represents a robust approach to improving current risk-adapted therapy for RMS.

Microbial diagnosis of bloodstream infection: towards molecular diagnosis directly from blood.

When a bloodstream infection (BSI) is suspected, most of the laboratory results-biochemical and haematologic-are available within the first hours after hospital admission of the patient. This is not the case for diagnostic microbiology, which generally takes a longer time because blood culture, which is to date the reference standard for the documentation of the BSI microbial agents, relies on bacterial or fungal growth. The microbial diagnosis of BSI directly from blood has been proposed to speed the determination of the etiological agent but was limited by the very low number of circulating microbes during these paucibacterial infections. Thanks to recent advances in molecular biology, including the improvement of nucleic acid extraction and amplification, several PCR-based methods for the diagnosis of BSI directly from whole blood have emerged. In the present review, we discuss the advantages and limitations of these new molecular approaches, which at best complement the culture-based diagnosis of BSI.

Molecular Analysis of NOTCH2 in Patients with Primary Open-Angle Glaucoma.

BACKGROUND AND PURPOSE: Transgenic mice overexpressing Notch2 in the uvea exhibit a hyperplastic ciliary body leading to increased IOP and glaucoma. The aim of this study was to investigate the possible presence of NOTCH2 variants in patients with primary open-angle glaucoma (POAG). METHODS: We screened DNA samples from 130 patients with POAG for NOTCH2 variants by denaturing high-performance liquid chromatography after PCR amplification and validated our data by direct Sanger sequencing. RESULTS: No mutations were observed in the coding regions of NOTCH2 or in the splice sites. 19 known SNPs (single nucleotide polymorphisms) were detected. An SNP located in intron 24, c.[4005+45A>G], was seen in 28.5% of the patients (37/130 patients). As this SNP is reported to have a minor allele frequency of 7% in the 1000 genomes database, it could be associated with POAG. However, we evaluated its frequency in an ethnic-matched control group of 96 subjects unaffected by POAG and observed a frequency of 29%, indicating that it was not related to POAG. CONCLUSION: NOTCH2 seemed to be a good candidate for POAG as it is expressed in the anterior segment in the human eye. However, mutational analysis did not show any causative mutation. This study also shows that proper ethnic-matched control groups are essential in association studies and that values given in databases are sometimes misleading.