RDM1, a novel RNA recognition motif (RRM)-containing protein involved in the cell response to cisplatin in vertebrates.

A variety of cellular proteins has the ability to recognize DNA lesions induced by the anti-cancer drug cisplatin, with diverse consequences on their repair and on the therapeutic effectiveness of this drug. We report a novel gene involved in the cell response to cisplatin in vertebrates. The RDM1 gene (for RAD52 Motif 1) was identified while searching databases for sequences showing similarities to RAD52, a protein involved in homologous recombination and DNA double-strand break repair. Ablation of RDM1 in the chicken B cell line DT40 led to a more than 3-fold increase in sensitivity to cisplatin. However, RDM1-/- cells were not hypersensitive to DNA damages caused by ionizing radiation, UV irradiation, or the alkylating agent methylmethane sulfonate. The RDM1 protein displays a nucleic acid binding domain of the RNA recognition motif (RRM) type. By using gel-shift assays and electron microscopy, we show that purified, recombinant chicken RDM1 protein interacts with single-stranded DNA as well as double-stranded DNA, on which it assembles filament-like structures. Notably, RDM1 recognizes DNA distortions induced by cisplatin-DNA adducts in vitro. Finally, human RDM1 transcripts are abundant in the testis, suggesting a possible role during spermatogenesis.

Results of An International Study of Quantitative BCR/ABL Assays Using Defined RNA Samples

Molecular monitoring of BCR/ABL transcripts by real time quantitative reverse transcription PCR (qRT-PCR) is an essential technique for clinical management of patients with BCR/ABL-positive CML and ALL. Though quantitative BCR/ABL assays are performed in hundreds of laboratories worldwide, results among these laboratories cannot be reliably compared due to heterogeneity in test methods, data analysis, reporting, and lack of quantitative standards. Recent efforts towards standardization have been limited in scope. Aliquots of RNA were sent to clinical test centers worldwide in order to evaluate methods and reporting for e1a2, b2a2, and b3a2 transcript levels using their own qRT-PCR assays. Total RNA was isolated from tissue culture cells that expressed each of the different BCR/ABL transcripts. Serial log dilutions were prepared, ranging from 100 to 10-5, in RNA isolated from HL60 cells. Laboratories performed 5 independent qRT-PCR reactions for each sample type at each dilution. In addition, 15 qRT-PCR reactions of the 10-3 b3a2 RNA dilution were run to assess reproducibility within and between laboratories. Participants were asked to run the samples following their standard protocols and to report cycle threshold (Ct), quantitative values for BCR/ABL and housekeeping genes, and ratios of BCR/ABL to housekeeping genes for each sample RNA. Thirty-seven (n=37) participants have submitted qRT-PCR results for analysis (36, 37, and 34 labs generated data for b2a2, b3a2, and e1a2, respectively). The limit of detection for this study was defined as the lowest dilution that a Ct value could be detected for all 5 replicates. For b2a2, 15, 16, 4, and 1 lab(s) showed a limit of detection at the 10-5, 10-4, 10-3, and 10-2 dilutions, respectively. For b3a2, 20, 13, and 4 labs showed a limit of detection at the 10-5, 10-4, and 10-3 dilutions, respectively. For e1a2, 10, 21, 2, and 1 lab(s) showed a limit of detection at the 10-5, 10-4, 10-3, and 10-2 dilutions, respectively. Log %BCR/ABL ratio values provided a method for comparing results between the different laboratories for each BCR/ABL dilution series. Linear regression analysis revealed concordance among the majority of participant data over the 10-1 to 10-4 dilutions. The overall slope values showed comparable results among the majority of b2a2 (mean=0.939; median=0.9627; range (0.399 - 1.1872)), b3a2 (mean=0.925; median=0.922; range (0.625 - 1.140)), and e1a2 (mean=0.897; median=0.909; range (0.5174 - 1.138)) laboratory results (Fig. 1-3)). Thirty-four (n=34) out of the 37 laboratories reported Ct values for all 15 replicates and only those with a complete data set were included in the inter-lab calculations. Eleven laboratories either did not report their copy number data or used other reporting units such as nanograms or cell numbers; therefore, only 26 laboratories were included in the overall analysis of copy numbers. The median copy number was 348.4, with a range from 15.6 to 547,000 copies (approximately a 4.5 log difference); the median intra-lab %CV was 19.2% with a range from 4.2% to 82.6%. While our international performance evaluation using serially diluted RNA samples has reinforced the fact that heterogeneity exists among clinical laboratories, it has also demonstrated that performance within a laboratory is overall very consistent. Accordingly, the availability of defined BCR/ABL RNAs may facilitate the validation of all phases of quantitative BCR/ABL analysis and may be extremely useful as a tool for monitoring assay performance. Ongoing analyses of these materials, along with the development of additional control materials, may solidify consensus around their application in routine laboratory testing and possible integration in worldwide efforts to standardize quantitative BCR/ABL testing.

Maf1, a new player in the regulation of human RNA polymerase III transcription.

BACKGROUND: Human RNA polymerase III (pol III) transcription is regulated by several factors, including the tumor suppressors P53 and Rb, and the proto-oncogene c-Myc. In yeast, which lacks these proteins, a central regulator of pol III transcription, called Maf1, has been described. Maf1 is required for repression of pol III transcription in response to several signal transduction pathways and is broadly conserved in eukaryotes. METHODOLOGY/PRINCIPAL FINDINGS: We show that human endogenous Maf1 can be co-immunoprecipitated with pol III and associates in vitro with two pol III subunits, the largest subunit RPC1 and the alpha-like subunit RPAC2. Maf1 represses pol III transcription in vitro and in vivo and is required for maximal pol III repression after exposure to MMS or rapamycin, treatments that both lead to Maf1 dephosphorylation. CONCLUSIONS/SIGNIFICANCE: These data suggest that Maf1 is a major regulator of pol III transcription in human cells.

CleanEx: a database of heterogeneous gene expression data based on a consistent gene nomenclature and linked to an improved annotation system

Résumé: L'automatisation du séquençage et de l'annotation des génomes, ainsi que l'application à large échelle de méthodes de mesure de l'expression génique, génèrent une quantité phénoménale de données pour des organismes modèles tels que l'homme ou la souris. Dans ce déluge de données, il devient très difficile d'obtenir des informations spécifiques à un organisme ou à un gène, et une telle recherche aboutit fréquemment à des réponses fragmentées, voir incomplètes. La création d'une base de données capable de gérer et d'intégrer aussi bien les données génomiques que les données transcriptomiques peut grandement améliorer la vitesse de recherche ainsi que la qualité des résultats obtenus, en permettant une comparaison directe de mesures d'expression des gènes provenant d'expériences réalisées grâce à des techniques différentes. L'objectif principal de ce projet, appelé CleanEx, est de fournir un accès direct aux données d'expression publiques par le biais de noms de gènes officiels, et de représenter des données d'expression produites selon des protocoles différents de manière à faciliter une analyse générale et une comparaison entre plusieurs jeux de données. Une mise à jour cohérente et régulière de la nomenclature des gènes est assurée en associant chaque expérience d'expression de gène à un identificateur permanent de la séquence-cible, donnant une description physique de la population d'ARN visée par l'expérience. Ces identificateurs sont ensuite associés à intervalles réguliers aux catalogues, en constante évolution, des gènes d'organismes modèles. Cette procédure automatique de traçage se fonde en partie sur des ressources externes d'information génomique, telles que UniGene et RefSeq. La partie centrale de CleanEx consiste en un index de gènes établi de manière hebdomadaire et qui contient les liens à toutes les données publiques d'expression déjà incorporées au système. En outre, la base de données des séquences-cible fournit un lien sur le gène correspondant ainsi qu'un contrôle de qualité de ce lien pour différents types de ressources expérimentales, telles que des clones ou des sondes Affymetrix. Le système de recherche en ligne de CleanEx offre un accès aux entrées individuelles ainsi qu'à des outils d'analyse croisée de jeux de donnnées. Ces outils se sont avérés très efficaces dans le cadre de la comparaison de l'expression de gènes, ainsi que, dans une certaine mesure, dans la détection d'une variation de cette expression liée au phénomène d'épissage alternatif. Les fichiers et les outils de CleanEx sont accessibles en ligne (http://www.cleanex.isb-sib.ch/). Abstract: The automatic genome sequencing and annotation, as well as the large-scale gene expression measurements methods, generate a massive amount of data for model organisms. Searching for genespecific or organism-specific information througout all the different databases has become a very difficult task, and often results in fragmented and unrelated answers. The generation of a database which will federate and integrate genomic and transcriptomic data together will greatly improve the search speed as well as the quality of the results by allowing a direct comparison of expression results obtained by different techniques. The main goal of this project, called the CleanEx database, is thus to provide access to public gene expression data via unique gene names and to represent heterogeneous expression data produced by different technologies in a way that facilitates joint analysis and crossdataset comparisons. A consistent and uptodate gene nomenclature is achieved by associating each single gene expression experiment with a permanent target identifier consisting of a physical description of the targeted RNA population or the hybridization reagent used. These targets are then mapped at regular intervals to the growing and evolving catalogues of genes from model organisms, such as human and mouse. The completely automatic mapping procedure relies partly on external genome information resources such as UniGene and RefSeq. The central part of CleanEx is a weekly built gene index containing crossreferences to all public expression data already incorporated into the system. In addition, the expression target database of CleanEx provides gene mapping and quality control information for various types of experimental resources, such as cDNA clones or Affymetrix probe sets. The Affymetrix mapping files are accessible as text files, for further use in external applications, and as individual entries, via the webbased interfaces . The CleanEx webbased query interfaces offer access to individual entries via text string searches or quantitative expression criteria, as well as crossdataset analysis tools, and crosschip gene comparison. These tools have proven to be very efficient in expression data comparison and even, to a certain extent, in detection of differentially expressed splice variants. The CleanEx flat files and tools are available online at: http://www.cleanex.isbsib. ch/.

RNA interference screening identifies a novel role for PCTK1/CDK16 in medulloblastoma with c-Myc amplification.

Medulloblastoma (MB) is the most common malignant brain tumor in children and is associated with a poor outcome. cMYC amplification characterizes a subgroup of MB with very poor prognosis. However, there exist so far no targeted therapies for the subgroup of MB with cMYC amplification. Here we used kinome-wide RNA interference screening to identify novel kinases that may be targeted to inhibit the proliferation of c-Myc-overexpressing MB. The RNAi screen identified a set of 5 genes that could be targeted to selectively impair the proliferation of c-Myc-overexpressing MB cell lines: AKAP12 (A-kinase anchor protein), CSNK1α1 (casein kinase 1, alpha 1), EPHA7 (EPH receptor A7) and PCTK1 (PCTAIRE protein kinase 1). When using RNAi and a pharmacological inhibitor selective for PCTK1, we could show that this kinase plays a crucial role in the proliferation of MB cell lines and the activation of the mammalian target of rapamycin (mTOR) pathway. In addition, pharmacological PCTK1 inhibition reduced the expression levels of c-Myc. Finally, targeting PCTK1 selectively impaired the tumor growth of c-Myc-overexpressing MB cells in vivo. Together our data uncover a novel and crucial role for PCTK1 in the proliferation and survival of MB characterized by cMYC amplification.

Genome-wide DNA methylation detection by MethylCap-seq and Infinium HumanMethylation450 BeadChips: an independent large-scale comparison.

Two cost-efficient genome-scale methodologies to assess DNA-methylation are MethylCap-seq and Illumina's Infinium HumanMethylation450 BeadChips (HM450). Objective information regarding the best-suited methodology for a specific research question is scant. Therefore, we performed a large-scale evaluation on a set of 70 brain tissue samples, i.e. 65 glioblastoma and 5 non-tumoral tissues. As MethylCap-seq coverages were limited, we focused on the inherent capacity of the methodology to detect methylated loci rather than a quantitative analysis. MethylCap-seq and HM450 data were dichotomized and performances were compared using a gold standard free Bayesian modelling procedure. While conditional specificity was adequate for both approaches, conditional sensitivity was systematically higher for HM450. In addition, genome-wide characteristics were compared, revealing that HM450 probes identified substantially fewer regions compared to MethylCap-seq. Although results indicated that the latter method can detect more potentially relevant DNA-methylation, this did not translate into the discovery of more differentially methylated loci between tumours and controls compared to HM450. Our results therefore indicate that both methodologies are complementary, with a higher sensitivity for HM450 and a far larger genome-wide coverage for MethylCap-seq, but also that a more comprehensive character does not automatically imply more significant results in biomarker studies.

Study of tergal glands morphogenesis through an integrative analysis of genomic data

About 50% of living species are holometabolan insects. Therefore, unraveling the ori- gin of insect metamorphosis from the hemimetabolan (gradual metamorphosis) to the holometabolan (sudden metamorphosis at the end of the life cycle) mode is equivalent to explaining how all this biodiversity originated. One of the problems with studying the evolution from hemimetaboly to holometaboly is that most information is available only in holometabolan species. Within the hemimetabolan group, our model, the cock- roach Blattella germanica, is the most studied species. However, given that the study of adult morphogenesis at organismic level is still complex, we focused on the study of the tergal gland (TG) as a minimal model of metamorphosis. The TG is formed in tergites 7 and 8 (T7-8) in the last days of the last nymphal instar (nymph 6). The comparative study of four T7-T8 transcriptomes provided us with crucial keys of TG formation, but also essential information about the mechanisms and circuitry that allows the shift from nymphal to adult morphogenesis.

Chromatoid body mediated RNA regulation in mouse male germline

Male germ cell differentiation, spermatogenesis is an exceptional developmental process that produces a massive amount of genetically unique spermatozoa. The complexity of this process along with the technical limitations in the germline research has left many aspects of spermatogenesis poorly understood. Post-meiotic haploid round spermatids possess the most complex transcriptomes of the whole body. Correspondingly, efficient and accurate control mechanisms are necessary to deal with the huge diversity of transcribed RNAs in these cells. The high transcriptional activity in round spermatids is accompanied by the presence of an uncommonly large cytoplasmic ribonucleoprotein granule, called the chromatoid body (CB) that is conjectured to participate in the RNA post-transcriptional regulation. However, very little is known about the possible mechanisms of the CB function. The development of a procedure to isolate CBs from mouse testes was this study’s objective. Anti-MVH immunoprecipitation of cross-linked CBs from a fractionated testicular cell lysate was optimized to yield considerable quantities of pure and intact CBs from mice testes. This protocol produced reliable and reproducible data from the subsequent analysis of CB’s protein and RNA components. We found that the majority of the CB’s proteome consists of RNA-binding proteins that associate functionally with different pathways. We also demonstrated notable localization patterns of one of the CB transient components, SAM68 and showed that its ablation does not change the general composition or structure of the CB. CB-associated RNA analysis revealed a strong accumulation of PIWI-interacting RNAs (piRNAs), mRNAs and long non-coding RNAs (lncRNAs) in the CB. When the CB transcriptome and proteome analysis results were combined, the most pronounced molecular functions in the CB were related to piRNA pathway, RNA post-transcriptional processing and CB structural scaffolding. In addition, we demonstrated that the CB is a target for the main RNA flux from the nucleus throughout all steps of round spermatid development. Moreover, we provided preliminary evidence that those isolated CBs slice target RNAs in vitro in an ATPdependent manner. Altogether, these results make a strong suggestion that the CB functions involve RNA-related and RNA-mediated mechanisms. All the existing data supports the hypothesis that the CB coordinates the highly complex haploid transcriptome during the preparation of the male gametes for fertilization. Thereby, this study provides a fundamental basis for the future functional analyses of ribonucleoprotein granules and offers also important insights into the mechanisms governing male fertility.

Transcriptional and Epigenetic Regulation of Human CD4+ T Helper Lineage Specification

Activated T helper (Th) cells have ability to differentiate into functionally distinct Th1, Th2 and Th17 subsets through a series of overlapping networks that include signaling and transcriptional control and the epigenetic mechanisms to direct immune responses. However, inappropriate execution in the differentiation process and abnormal function of these Th cells can lead to the development of several immune mediated diseases. Therefore, the thesis aimed at identifying genes and gene regulatory mechanisms responsible for Th17 differentiation and to study epigenetic changes associated with early stage of Th1/Th2 cell differentiation. Genome wide transcriptional profiling during early stages of human Th17 cell differentiation demonstrated differential regulation of several novel and currently known genes associated with Th17 differentiation. Selected candidate genes were further validated at protein level and their specificity for Th17 as compared to other T helper subsets was analyzed. Moreover, combination of RNA interference-mediated downregulation of gene expression, genome-wide transcriptome profiling and chromatin immunoprecipitation followed by massive parallel sequencing (ChIP-seq), combined with computational data integration lead to the identification of direct and indirect target genes of STAT3, which is a pivotal upstream transcription factor for Th17 cell polarization. Results indicated that STAT3 directly regulates the expression of several genes that are known to play a role in activation, differentiation, proliferation, and survival of Th17 cells. These results provide a basis for constructing a network regulating gene expression during early human Th17 differentiation. Th1 and Th2 lineage specific enhancers were identified from genome-wide maps of histone modifications generated from the cells differentiating towards Th1 and Th2 lineages at 72h. Further analysis of lineage-specific enhancers revealed known and novel transcription factors that potentially control lineage-specific gene expression. Finally, we found an overlap of a subset of enhancers with SNPs associated with autoimmune diseases through GWASs suggesting a potential role for enhancer elements in the disease development. In conclusion, the results obtained have extended our knowledge of Th differentiation and provided new mechanistic insights into dysregulation of Th cell differentiation in human immune mediated diseases.

Inhibition of STAT3 by RNA interference suppresses angiogenesis in colorectal carcinoma

In order to investigate signal transduction and activation of transcription 3 (STAT3) signaling on angiogenesis in colorectal carcinoma (CRC) after inhibiting STAT3 expression, we constructed the HT-29-shSTAT3 cell line by lentivirus-mediated RNAi. Cell growth was assessed with MTT and the cell cycle distribution by flow cytometry. CRC nude mouse models were established and tumor growth was monitored periodically. On day 30, all mice were killed and tumor tissues were removed. Microvessel density (MVD) was determined according to CD34-positive staining. The expression of vascular endothelial growth factor A (VEGFA), matrix metalloproteinase-2 (MMP2) and basic fibroblast growth factor (FGF2) was monitored by quantitative real-time PCR and Western blot analysis. Knockdown of STAT3 expression significantly inhibited cell growth in HT-29 cells, with a significantly higher proportion of cells at G0/G1 (P < 0.01). Consistently, in vivo data also demonstrated that tumor growth was significantly inhibited in mice injected with HT-29-shSTAT3 cells. MVD was 9.80 ± 3.02 in the HT-29-shSTAT3 group, significantly less than that of the control group (P < 0.01). mRNA and protein levels of VEGFA and MMP2 in the HT-29-shSTAT3 group were significantly lower than in the control group (P < 0.05), but no significant difference was observed in the mRNA or protein level of FGF2 (P > 0.05). Taken together, these results demonstrate that STAT3 signaling is important to the growth of CRC and promotes angiogenesis by regulating VEGFA and MMP2 expression.

Proteomic data show an increase in autoantibodies and alpha-fetoprotein and a decrease in apolipoprotein A-II with time in sera from senescence-accelerated mice

We evaluated changes in levels by comparing serum proteins in senescence-accelerated mouse-prone 8 (SAMP8) mice at 2, 6, 12, and 15 months of age (SAMP8-2 m, -6 m, -12 m, -15 m) to age-matched SAM-resistant 1 (SAMR1) mice. Mice were sacrificed, and blood was analyzed by 2-dimensional electrophoresis combined with mass spectrometry. Five protein spots were present in all SAMP8 serum samples, but only appeared in SAMR1 samples at 15 months of age except for spot 3, which also showed a slight expression in SAMR1-12 m sera. Two proteins decreased in the sera from SAMP8-2 m, -6 m, and -12 m mice, and divided into 2 spots each in SAMP8-15 m sera. Thus, the total number of altered spots in SAMP8 sera was 7; of these, 4 were identified as Ig kappa chain V region (M-T413), chain A of an activity suppressing Fab fragment to cytochrome P450 aromatase (32C2_A), alpha-fetoprotein, and apolipoprotein A-II. M-T413 is a monoclonal CD4 antibody, which inhibits T cell proliferation. We found that M-T413 RNA level was significantly enhanced in splenocytes from SAMP8-2 m mice. This agreed with serum M-T413 protein alterations and a strikingly lower blood CD4+ T cell count in SAMP8 mice when compared to the age-matched SAMR1 mice, with the latter negatively correlating with serum M-T413 protein volume. Age-related changes in serum proteins favored an increase in autoantibodies and alpha-fetoprotein and a decrease of apolipoprotein A-II, which occurred in SAMP8 mice at 2 months of age and onwards. These proteins may serve as candidate biomarkers for early aging.

An investigation into differences between indoleacetic acid and fusicoccin in their influence on RNA synthesis, protein synthesis and growth in Avena coleoptile tissue

Growth stimulation of Avena coleoptile tissue by indoleacetic acid (IAA) and fusicoccin (FC) was compared by measuring both their influence on RNA and protein synthesis during IAA or FC stimulated growth. FC stimulated growth more than IAA during the initial four hour exposure, after which the growth rate gradually declined to the control rate. FC, but not IAA, increased the uptake of 3H-Ieucine into tissue and the specific radioactivity of extracted protein. Cycloheximide inhibited the incorporation of 3H-Ieucine into protein by approximately 60% to 70% in all cases. In the presence of cycloheximide 3H-radioactivity accumulated in FC-treated tissue, whereas IAA did not seem to influence 3H-accumulation. These results suggest that FC stimulated leucine uptake into the tissue and that increased specific activity of coleoptile protein is due to increased leucine uptake, not an increased rate of protein synthesis. There was no measurable influence of IAA and/or FC on RNA and protein synthesis during the initial hours of a growth stimulation. Inhibitors of RNA and protein synthesis, actinomycin D and cycloheximide, respectively, severely inhibited IAA enhanced growth but only partially inhibited FC stimulated growth. The data are consistent with suggestions that a rapidly turning over protein participates in IAA stimulated growth, and that a continual synthesis of RNA and proteins is an absolute requirement for a long term growth response to IAA. On the contrary, FC-stimulated growth exhibited less dependency on the transcription and translation processes. The data are consistent with proposals suggesting different sites of action for FC and IAA stimulated growth. l?hen compared to CO2-free air, CO2 at 300 ppm had no significant influence on coleoptile growth and protein synthesis in the presence or absence of lAA or FC. Also, I mM malate, pH 6.0 did not influence growth of coleoptiles in the presence or absence of lAA. This result was obtained despite reports indicating that 300 ppm CO2 or I mM malate stimulates growth and protein synthesis. This lack of difference between CO2-treated and untreated tissue could indicate either that the interstitial space CO2 concentration is not actually different in the two treatments due to significant endogenous respiratory CO2 or else the data would suggest a very loose coupling between dark CO2 fixation and growth. IAA stimulated the in vivo fixation of 14c-bicarbonate (NaHI4c03) by about 25% and the addition of cycloheximide caused an inhibition of bicarbonate fixation within 30 min. Cycloheximide has also been reported to inhibit IAA-stimulated H+ excretion. These data are consistent with the acid growth theory and suggest that lAA stimulated growth involves dark CO2 fixation. The roles of dark CO2 fixation in lAA-stimulated growth are discussed.

Recognition of hepatitis C virus RNA by toll like receptors 7 and 8 : implications for the initiation of innate immune response

Le virus de l’hépatite C (VHC) est un virus à ARN simple brin positif (ssARN) qui se replique dans le foie. Deux cents millions de personnes sont infectées par le virus dans le monde et environ 80% d’entre elles progresseront vers un stade chronique de l’infection. Les thérapies anti-virales actuelles comme l’interféron (IFN) ou la ribavirin sont de plus en plus utilisées mais ne sont efficaces que dans la moitié des individus traités et sont souvent accompagnées d’une toxicité ou d’effets secondaires indésirables. Le système immunitaire inné est essentiel au contrôle des infections virales. Les réponses immunitaires innées sont activées suite à la reconnaissance par les Pathogen Recognition Receptors (PRRs), de motifs macromoléculaires dérivés du virus appelés Pathogen-Associated Molecular Patterns (PAMPs). Bien que l'activation du système immunitaire par l'ARN ou les protéines du VHC ait été largement étudiée, très peu de choses sont actuellement connues concernant la détection du virus par le système immunitaire inné. Et même si l’on peut très rapidement déceler des réponses immunes in vivo après infection par le VHC, l’augmentation progressive et continue de la charge virale met en évidence une incapacité du système immunitaire à contrôler l’infection virale. Une meilleure compréhension des mécanismes d’activation du système immunitaire par le VHC semble, par conséquent, essentielle au développement de stratégies antivirales plus efficaces. Dans le présent travail nous montrons, dans un modèle de cellule primaire, que le génome ARN du VHC contient des séquences riches en GU capables de stimuler spécifiquement les récepteurs de type Toll (TLR) 7 et 8. Cette stimulation a pour conséquence la maturation des cellules dendritiques plasmacytoïdes (pDCs), le production d’interféron de type I (IFN) ainsi que l’induction de chémokines et cytokines inflammatoires par les différentes types de cellules présentatrices d’antigènes (APCs). Les cytokines produites après stimulation de monocytes ou de pDCs par ces séquences ssARN virales, inhibent la production du virus de façon dépendante de l’IFN. En revanche, les cytokines produites après stimulation de cellules dendritiques myéloïdes (mDCs) ou de macrophages par ces mêmes séquences n’ont pas d’effet inhibiteur sur la production virale car les séquences ssARN virales n’induisent pas la production d’IFN par ces cellules. Les cytokines produites après stimulation des TLR 7/8 ont également pour effet de diminuer, de façon indépendante de l’IFN, l’expression du récepteur au VHC (CD81) sur la lignée cellulaire Huh7.5, ce qui pourrait avoir pour conséquence de restreindre l’infection par le VHC. Quoiqu’il en soit, même si les récepteurs au VHC comme le CD81 sont largement exprimés à la surface de différentes sous populations lymphocytaires, les DCs et les monocytes ne répondent pas aux VHC, Nos résultats indiquent que seuls les macrophages sont capables de reconnaître le VHC et de produire des cytokines inflammatoires en réponse à ce dernier. La reconnaissance du VHC par les macrophages est liée à l’expression membranaire de DC-SIGN et l’engagement des TLR 7/8 qui en résulte. Comme d’autres agonistes du TLR 7/8, le VHC stimule la production de cytokines inflammatoires (TNF-α, IL-8, IL-6 et IL-1b) mais n’induit pas la production d’interféron-beta par les macrophages. De manière attendue, la production de cytokines par des macrophages stimulés par les ligands du TLR 7/8 ou les séquences ssARN virales n’inhibent pas la réplication virale. Nos résultats mettent en évidence la capacité des séquences ssARN dérivées du VHC à stimuler les TLR 7/8 dans différentes populations de DC et à initier une réponse immunitaire innée qui aboutit à la suppression de la réplication virale de façon dépendante de l’IFN. Quoiqu’il en soit, le VHC est capable d’échapper à sa reconnaissance par les monocytes et les DCs qui ont le potentiel pour produire de l’IFN et inhiber la réplication virale après engagement des TLR 7/8. Les macrophages possèdent quant à eux la capacité de reconnaître le VHC grâce en partie à l’expression de DC-SIGN à leur surface, mais n’inhibent pas la réplication du virus car ils ne produisent pas d’IFN. L’échappement du VHC aux défenses antivirales pourrait ainsi expliquer l’échec du système immunitaire inné à contrôler l’infection par le VHC. De plus, la production de cytokines inflammatoires observée après stimulation in vitro des macrophages par le VHC suggère leur potentielle contribution dans l’inflammation que l’on retrouve chez les individus infectés par le VHC.

Mean Squared Residue Based Biclustering Algorithms for the Analysis of Gene Expression Data

Computational Biology is the research are that contributes to the analysis of biological data through the development of algorithms which will address significant research problems.The data from molecular biology includes DNA,RNA ,Protein and Gene expression data.Gene Expression Data provides the expression level of genes under different conditions.Gene expression is the process of transcribing the DNA sequence of a gene into mRNA sequences which in turn are later translated into proteins.The number of copies of mRNA produced is called the expression level of a gene.Gene expression data is organized in the form of a matrix. Rows in the matrix represent genes and columns in the matrix represent experimental conditions.Experimental conditions can be different tissue types or time points.Entries in the gene expression matrix are real values.Through the analysis of gene expression data it is possible to determine the behavioral patterns of genes such as similarity of their behavior,nature of their interaction,their respective contribution to the same pathways and so on. Similar expression patterns are exhibited by the genes participating in the same biological process.These patterns have immense relevance and application in bioinformatics and clinical research.Theses patterns are used in the medical domain for aid in more accurate diagnosis,prognosis,treatment planning.drug discovery and protein network analysis.To identify various patterns from gene expression data,data mining techniques are essential.Clustering is an important data mining technique for the analysis of gene expression data.To overcome the problems associated with clustering,biclustering is introduced.Biclustering refers to simultaneous clustering of both rows and columns of a data matrix. Clustering is a global whereas biclustering is a local model.Discovering local expression patterns is essential for identfying many genetic pathways that are not apparent otherwise.It is therefore necessary to move beyond the clustering paradigm towards developing approaches which are capable of discovering local patterns in gene expression data.A biclusters is a submatrix of the gene expression data matrix.The rows and columns in the submatrix need not be contiguous as in the gene expression data matrix.Biclusters are not disjoint.Computation of biclusters is costly because one will have to consider all the combinations of columans and rows in order to find out all the biclusters.The search space for the biclustering problem is 2 m+n where m and n are the number of genes and conditions respectively.Usually m+n is more than 3000.The biclustering problem is NP-hard.Biclustering is a powerful analytical tool for the biologist.The research reported in this thesis addresses the problem of biclustering.Ten algorithms are developed for the identification of coherent biclusters from gene expression data.All these algorithms are making use of a measure called mean squared residue to search for biclusters.The objective here is to identify the biclusters of maximum size with the mean squared residue lower than a given threshold. All these algorithms begin the search from tightly coregulated submatrices called the seeds.These seeds are generated by K-Means clustering algorithm.The algorithms developed can be classified as constraint based,greedy and metaheuristic.Constarint based algorithms uses one or more of the various constaints namely the MSR threshold and the MSR difference threshold.The greedy approach makes a locally optimal choice at each stage with the objective of finding the global optimum.In metaheuristic approaches particle Swarm Optimization(PSO) and variants of Greedy Randomized Adaptive Search Procedure(GRASP) are used for the identification of biclusters.These algorithms are implemented on the Yeast and Lymphoma datasets.Biologically relevant and statistically significant biclusters are identified by all these algorithms which are validated by Gene Ontology database.All these algorithms are compared with some other biclustering algorithms.Algorithms developed in this work overcome some of the problems associated with the already existing algorithms.With the help of some of the algorithms which are developed in this work biclusters with very high row variance,which is higher than the row variance of any other algorithm using mean squared residue, are identified from both Yeast and Lymphoma data sets.Such biclusters which make significant change in the expression level are highly relevant biologically.

Phylogenomics of eukaryotes: Impact of missing data on large alignments

Resolving the relationships between Metazoa and other eukaryotic groups as well as between metazoan phyla is central to the understanding of the origin and evolution of animals. The current view is based on limited data sets, either a single gene with many species (e.g., ribosomal RNA) or many genes but with only a few species. Because a reliable phylogenetic inference simultaneously requires numerous genes and numerous species, we assembled a very large data set containing 129 orthologous proteins (similar to30,000 aligned amino acid positions) for 36 eukaryotic species. Included in the alignments are data from the choanoflagellate Monosiga ovata, obtained through the sequencing of about 1,000 cDNAs. We provide conclusive support for choanoflagellates as the closest relative of animals and for fungi as the second closest. The monophyly of Plantae and chromalveolates was recovered but without strong statistical support. Within animals, in contrast to the monophyly of Coelomata observed in several recent large-scale analyses, we recovered a paraphyletic Coelamata, with nematodes and platyhelminths nested within. To include a diverse sample of organisms, data from EST projects were used for several species, resulting in a large amount of missing data in our alignment (about 25%). By using different approaches, we verify that the inferred phylogeny is not sensitive to these missing data. Therefore, this large data set provides a reliable phylogenetic framework for studying eukaryotic and animal evolution and will be easily extendable when large amounts of sequence information become available from a broader taxonomic range.