22 research outputs found

    amda 2 13 a major update for automated cross platform microarray data analysis

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    Microarray platforms require analytical pipelines with modules for data pre-processing including data normalization, statistical analysis for identification of differentially expressed genes, cluster analysis, and functional annotation. We previously developed the Automated Microarray Data Analysis (AMDA, version 2.3.5) pipeline to process Affymetrix 3′ IVT GeneChips. The availability of newer technologies that demand open-source tools for microarray data analysis has impelled us to develop an updated multi-platform version, AMDA 2.13. It includes additional quality control metrics, annotation-driven (annotation grade of Affymetrix NetAffx) and signal-driven (Inter-Quartile Range) gene filtering, and approaches to experimental design. To enhance understanding of biological data, differentially expressed genes have been mapped into KEGG pathways. Finally, a more stable and user-friendly interface was designed to integrate the requirements for different platforms. AMDA 2.13 allows the analysis of Affymetrix..

    Hypoxia Modifies the Transcriptome of Human NK Cells, Modulates Their Immunoregulatory Profile, and Influences NK Cell Subset Migration

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    Hypoxia, which characterizes most tumor tissues, can alter the function of different immune cell types, favoring tumor escape mechanisms. In this study, we show that hypoxia profoundly acts on NK cells by influencing their transcriptome, affecting their immunoregulatory functions, and changing the chemotactic responses of different NK cell subsets. Exposure of human peripheral blood NK cells to hypoxia for 16 or 96 h caused significant changes in the expression of 729 or 1,100 genes, respectively. Gene Set Enrichment Analysis demonstrated that these changes followed a consensus hypoxia transcriptional profile. As assessed by Gene Ontology annotation, hypoxia-targeted genes were implicated in several biological processes: metabolism, cell cycle, differentiation, apoptosis, cell stress, and cytoskeleton organization. The hypoxic transcriptome also showed changes in genes with immunological relevance including those coding for proinflammatory cytokines, chemokines, and chemokine-receptors. Quantitative RT-PCR analysis confirmed the modulation of several immune-related genes, prompting further immunophenotypic and functional studies. Multiplex ELISA demonstrated that hypoxia could variably reduce NK cell ability to release IFNγ, TNFα, GM-CSF, CCL3, and CCL5 following PMA+Ionomycin or IL15+IL18 stimulation, while it poorly affected the response to IL12+IL18. Cytofluorimetric analysis showed that hypoxia could influence NK chemokine receptor pattern by sustaining the expression of CCR7 and CXCR4. Remarkably, this effect occurred selectively (CCR7) or preferentially (CXCR4) on CD56bright NK cells, which indeed showed higher chemotaxis to CCL19, CCL21, or CXCL12. Collectively, our data suggest that the hypoxic environment may profoundly influence the nature of the NK cell infiltrate and its effects on immune-mediated responses within tumor tissues

    Investigation of The Genetic Regulation of Delayed Puberty

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    PhDThe genetic control of puberty remains an important but mostly unanswered question. Late pubertal timing affects over 2% of adolescents and is associated with adverse health outcomes. Self-limited delayed puberty (DP) segregates in an autosomal dominant pattern and is highly heritable; however, its neuroendocrine pathophysiology and genetic regulation remain unclear. The genetic control of puberty remains an important but mostly unanswered question. Late pubertal timing affects over 2% of adolescents and is associated with adverse health outcomes. Self-limited delayed puberty (DP) segregates in an autosomal dominant pattern and is highly heritable; however, its neuroendocrine pathophysiology and genetic regulation remain unclear. Our large, accurately phenotyped cohort of patients with familial self-limited DP is a unique resource with a relatively homogeneous genetic composition. I have utilised this cohort to investigate the genetic variants segregating with the DP trait in these pedigrees. Whole exome sequencing in eighteen probands and their relatives, and subsequent targeted sequencing in an extended subgroup of the cohort, has revealed potential novel genetic regulators of pubertal timing. In ten unrelated probands, I identified rare mutations in IGSF10, a gene that is strongly expressed in the nasal mesenchyme during embryonic migration of gonadotropin-releasing hormone (GnRH) neurons. IGSF10 knockdown both in vitro and in a transgenic zebrafish model resulted in perturbed GnRH neuronal migration. Loss-of-function mutations in IGSF10 were also identified in five patients with absent puberty due to hypogonadotropic hypogonadism (HH). Additionally, I have identified and investigated one rare, pathogenic mutation in HS6ST1 – a gene known to cause HH - in one family with DP, and two rare variants in FTO – a gene implicated in the timing of menarche in the general population - in 3 families. Further potentially pathogenic variants have emerged from investigating candidate genes identified from microarray studies (LGR4, SEMA6A and NEGR1) and from related clinical phenotypes (IGSF1). Our large, accurately phenotyped cohort of patients with familial self-limited DP is a unique resource with a relatively homogeneous genetic composition. I have utilised this cohort to investigate the genetic variants segregating with the DP trait in these pedigrees. Whole exome sequencing in eighteen probands and their relatives, and subsequent targeted sequencing in an extended subgroup of the cohort, has revealed potential novel genetic regulators of pubertal timing. In ten unrelated probands, I identified rare mutations in IGSF10, a gene that is strongly expressed in the nasal mesenchyme during embryonic migration of gonadotropin-releasing hormone (GnRH) neurons. IGSF10 knockdown both in vitro and in a transgenic zebrafish model resulted in perturbed GnRH neuronal migration. Loss-of-function mutations in IGSF10 were also identified in five patients with absent puberty due to hypogonadotropic hypogonadism (HH). Additionally, I have identified and investigated one rare, pathogenic mutation in HS6ST1 – a gene known to cause HH - in one family with DP, and two rare variants in FTO – a gene implicated in the timing of menarche in the general population - in 3 families. Further potentially pathogenic variants have emerged from investigating candidate genes identified from microarray studies (LGR4, SEMA6A and NEGR1) and from related clinical phenotypes (IGSF1).Clinical Training Fellowship from Barts and the London Charity (grant number 417/1551), Clinical Research Training Fellowship from the Wellcome Trust (grant number 102745) and the Rosetrees Trust (grant number M222)

    Toll-Like Receptor 2 Mediates In Vivo Pro- and Anti-inflammatory Effects of Mycobacterium Tuberculosis and Modulates Autoimmune Encephalomyelitis

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    Mycobacteria display pro- and anti-inflammatory effects in human and experimental pathology. We show here that both effects are mediated by Toll-like receptor 2 (Tlr2), by exploiting a previously characterized Tlr2 variant (Met82Ile). Tlr2 82ile promoted self-specific proinflammatory polarization as well as expansion of ag-specific FoxP3(+) Tregs, while Tlr2 82met impairs the expansion of Tregs and reduces the production of IFN-γ and IL-17 proinflammatory cytokines. Preferential dimerization with Tlr1 or Tlr6 could not explain these differences. In silico, we showed that Tlr2 variant Met82Ile modified the binding pocket for peptidoglycans and participated directly to a putative binding pocket for sugars and cadherins. The distinct pro- and anti-inflammatory actions impacted severity, extent of remission, and distribution of the lesions within the central nervous system of experimental autoimmune encephalomyelitis. Thus, Tlr2 has a janus function in vivo as mediator of the role of bacterial products in balancing pro- and anti-inflammatory immune responses

    Abiotic stresses and ultrahigh diluted traetments: physiological and molecular effects on in vitro wheat growth

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    Gli stress abiotici determinando modificazioni a livello fisiologico, biochimico e molecolare delle piante, costituiscono una delle principali limitazioni per la produzione agricola mondiale. Nel 2007 la FAO ha stimato come solamente il 3,5% della superficie mondiale non sia sottoposta a stress abiotici. Il modello agro-industriale degli ultimi cinquant'anni, oltre ad avere contribuito allo sviluppo economico dell'Europa, è stato anche causa di inquinamento di acqua, aria e suolo, mediante uno sfruttamento indiscriminato delle risorse naturali. L'arsenico in particolare, naturalmente presente nell'ambiente e rilasciato dalle attività antropiche, desta particolare preoccupazione a causa dell'ampia distribuzione come contaminante ambientale e per gli effetti di fitotossicità provocati. In tale contesto, la diffusione di sistemi agricoli a basso impatto rappresenta una importante risorsa per rispondere all'emergenza del cambiamento climatico che negli anni a venire sottoporrà una superficie agricola sempre maggiore a stress di natura abiotica. Nello studio condotto è stato utilizzato uno stabile modello di crescita in vitro per valutare l'efficacia di preparati ultra diluiti (PUD), che non contenendo molecole chimiche di sintesi ben si adattano a sistemi agricoli sostenibili, su semi di frumento preventivamente sottoposti a stress sub-letale da arsenico. Sono state quindi condotte valutazioni sia a livello morfometrico (germinazione, lunghezza di germogli e radici) che molecolare (espressione genica valutata mediante analisi microarray, con validazione tramite Real-Time PCR) arricchendo la letteratura esistente di interessanti risultati. In particolare è stato osservato come lo stress da arsenico, determini una minore vigoria di coleptile e radici e a livello molecolare induca l'attivazione di pathways metabolici per proteggere e difendere le cellule vegetali dai danni derivanti dallo stress; mentre il PUD in esame (As 45x), nel sistema stressato ha indotto un recupero nella vigoria di germoglio e radici e livelli di espressione genica simili a quelli riscontrati nel controllo suggerendo un effetto "riequilibrante" del metabolismo vegetale.The unquestionable importance of abiotic stresses to world agriculture is demonstrated by the fact that altogether abiotic factors provide the major limitation to crop production worldwide. A 2007 FAO report stated that only 3.5% of the global land area is not affected by environmental stresses and that climate change will increase areas characterized by abiotic stresses. The agro-industrial model that enriched European population in the last fifty years, however has resulted in irreversible contamination of water, air and soil. In particular arsenic is a toxic metalloid widely disseminated in the environmental as a consequence of natural processes and anthropic activities, that causes global concern for health and environmental hazards. Within this context, sustainable farming systems and the use of organic treatments such as ultrahigh diluted treatments (PUD) could be important tools of mitigating the effects of climate change. The objective of the present study was to test the biological effect of PUD As45x on wheat seedling poisoned with a sub-letal dose of arsenic, using an in vitro plant system. The evaluation of the arsenic toxicity and the effectiveness of As45x was conducted through biometric measurements and molecular analyses (microarray and Real-Time PCR). The results provided evidence for a strong gene modulating effect of arsenic, upregulating molecular pathways involved in cellular protection and defense from oxidative stress. It was also observed a reduction in the length of shoots and roots. Inversely in seedlings grown from poisoned seeds and treated with PUD, a recovery of coleoptiles and roots vigor was detected together with a massive reduction of gene expression levels to values comparable to those of the control group. A plausible hypothesis is that PUD induced a reequilibration of those genes that were upregulated during arsenic stress by bringing the expression levels closer to the basal levels normally occurring in control plants

    Investigating the role of X chromosome breakpoints in premature ovarian failure

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    ABSTRACT: The importance of the genetic factor in the aetiology of premature ovarian failure (POF) is emphasized by the high percentage of familial cases and X chromosome abnormalities account for 10% of chromosomal aberrations. In this study, we report the detailed analysis of 4 chromosomal abnormalities involving the X chromosome and associated with POF that were detected during a screening of 269 affected women. Conventional and molecular cytogenetics were valuable tools for locating the breakpoint regions and thus the following karyotypes were defined: 46,X,der(X)t(X;19)(q21.1;q13.42)mat, 46,X,t(X;2)(q21.33;q14.3)dn, 46,X,der(X)t(X;Y)(q26.2;q11.223)mat and 46,X,t(X;13)(q13.3;q31)dn. A bioinformatic analysis of the breakpoint regions identified putative candidate genes for ovarian failure near the breakpoint regions on the X chromosome or on autosomes that were involved in the translocation event. HS6ST1, HS6ST2 and MATER genes were identified and their functions and a literature review revealed an interesting connection to the POF phenotype. Moreover, the 19q13.32 locus is associated with the age of onset of the natural menopause. These results support the position effect of the breakpoint on flanking genes, and cytogenetic techniques, in combination with bioinformatic analysis, may help to improve what is known about this puzzling disorder and its diagnostic potential

    Knowledge sharing and collaboration in translational research, and the DC-THERA Directory

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    Biomedical research relies increasingly on large collections of data sets and knowledge whose generation, representation and analysis often require large collaborative and interdisciplinary efforts. This dimension of ‘big data’ research calls for the development of computational tools to manage such a vast amount of data, as well as tools that can improve communication and access to information from collaborating researchers and from the wider community. Whenever research projects have a defined temporal scope, an additional issue of data management arises, namely how the knowledge generated within the project can be made available beyond its boundaries and life-time. DC-THERA is a European ‘Network of Excellence’ (NoE) that spawned a very large collaborative and interdisciplinary research community, focusing on the development of novel immunotherapies derived from fundamental research in dendritic cell immunobiology. In this article we introduce the DC-THERA Directory, which is an information system designed to support knowledge management for this research community and beyond. We present how the use of metadata and Semantic Web technologies can effectively help to organize the knowledge generated by modern collaborative research, how these technologies can enable effective data management solutions during and beyond the project lifecycle, and how resources such as the DC-THERA Directory fit into the larger context of e-science

    Classification of dendritic cell phenotypes from gene expression data

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    <p>Abstract</p> <p>Background</p> <p>The selection of relevant genes for sample classification is a common task in many gene expression studies. Although a number of tools have been developed to identify optimal gene expression signatures, they often generate gene lists that are too long to be exploited clinically. Consequently, researchers in the field try to identify the smallest set of genes that provide good sample classification. We investigated the genome-wide expression of the inflammatory phenotype in dendritic cells. Dendritic cells are a complex group of cells that play a critical role in vertebrate immunity. Therefore, the prediction of the inflammatory phenotype in these cells may help with the selection of immune-modulating compounds.</p> <p>Results</p> <p>A data mining protocol was applied to microarray data for murine cell lines treated with various inflammatory stimuli. The learning and validation data sets consisted of 155 and 49 samples, respectively. The data mining protocol reduced the number of probe sets from 5,802 to 10, then from 10 to 6 and finally from 6 to 3. The performances of a set of supervised classification models were compared. The best accuracy, when using the six following genes --Il12b, Cd40, Socs3, Irgm1, Plin2 and Lgals3bp-- was obtained by Tree Augmented Naïve Bayes and Nearest Neighbour (91.8%). Using the smallest set of three genes --Il12b, Cd40 and Socs3-- the performance remained satisfactory and the best accuracy was with Support Vector Machine (95.9%). These data mining models, using data for the genes Il12b, Cd40 and Socs3, were validated with a human data set consisting of 27 samples. Support Vector Machines (71.4%) and Nearest Neighbour (92.6%) gave the worst performances, but the remaining models correctly classified all the 27 samples.</p> <p>Conclusions</p> <p>The genes selected by the data mining protocol proposed were shown to be informative for discriminating between inflammatory and steady-state phenotypes in dendritic cells. The robustness of the data mining protocol was confirmed by the accuracy for a human data set, when using only the following three genes: Il12b, Cd40 and Socs3. In summary, we analysed the longitudinal pattern of expression in dendritic cells stimulated with activating agents with the aim of identifying signatures that would predict or explain the dentritic cell response to an inflammatory agent.</p

    eXframe: reusable framework for storage, analysis and visualization of genomics experiments

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    <p>Abstract</p> <p>Background</p> <p>Genome-wide experiments are routinely conducted to measure gene expression, DNA-protein interactions and epigenetic status. Structured metadata for these experiments is imperative for a complete understanding of experimental conditions, to enable consistent data processing and to allow retrieval, comparison, and integration of experimental results. Even though several repositories have been developed for genomics data, only a few provide annotation of samples and assays using controlled vocabularies. Moreover, many of them are tailored for a single type of technology or measurement and do not support the integration of multiple data types.</p> <p>Results</p> <p>We have developed eXframe - a reusable web-based framework for genomics experiments that provides 1) the ability to publish structured data compliant with accepted standards 2) support for multiple data types including microarrays and next generation sequencing 3) query, analysis and visualization integration tools (enabled by consistent processing of the raw data and annotation of samples) and is available as open-source software. We present two case studies where this software is currently being used to build repositories of genomics experiments - one contains data from hematopoietic stem cells and another from Parkinson's disease patients.</p> <p>Conclusion</p> <p>The web-based framework eXframe offers structured annotation of experiments as well as uniform processing and storage of molecular data from microarray and next generation sequencing platforms. The framework allows users to query and integrate information across species, technologies, measurement types and experimental conditions. Our framework is reusable and freely modifiable - other groups or institutions can deploy their own custom web-based repositories based on this software. It is interoperable with the most important data formats in this domain. We hope that other groups will not only use eXframe, but also contribute their own useful modifications.</p
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