Genomic studies provide scientists with methods to quickly analyse genes and their products en masse. The first high-throughput techniques to be developed were sequencing methods. A great number of genomes from different organisms have thus been sequenced. Genomics is now shifting to the study of gene expression and function. In the past 5-10 years genomics, proteomics and high-throughput microarray technologies have fundamentally changed our ability to study the molecular basis of cells and tissues in health and diseases, giving a new comprehensive view. For example, in cancer research we have seen new diagnostic opportunities for tumour classification, and prognostication. A new exciting development is metabolomics and lab-on-a-chip techniques (which combine miniaturization and automation) for metabolic studies. However, to interpret the large amount of data, extensive computational development is required. In the coming years, we will see the study of biological networks dominating the scene in Physiology. The great accumulation of genomics information will be used in computer programs to simulate biologic processes. Originally developed for genome analysis, bioinformatics now encompasses a wide range of fields in biology from gene studies to integrated biology (i.e. combination of different data sets from genes to metabolites). This is systems biology which aims to study biological organisms as a whole. In medicine, scientific results and applied biotechnologies arising from genomics will be used for effective prediction of diseases and risk associated with drugs. Preventive medicine and medical therapy will be personalized. Widespread applications of genomics for personalized medicine will require associations of gene expression pattern with diagnoses, treatment and clinical data. This will help in the discovery and development of drugs. In agriculture and animal science, the outcomes of genomics will include improvement in food safety, in crop yield, in traceability and in quality of animal products (dairy products and meat) through increased efficiency in breeding and better knowledge of animal physiology. Genomics and integrated biology are huge tasks and no single lab can pursue this alone. We are probably at the end of the beginning rather than at the beginning of the end because Genomics will probably change Biology to a greater extent than previously forecasted. In addition, there is a great need for more information and better understanding of genomics before complete public acceptance. (+info)
A novel C. elegans zinc finger transcription factor, lsy-2, required for the cell type-specific expression of the lsy-6 microRNA.
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The two Caenorhabditis elegans gustatory neurons, ASE left (ASEL) and ASE right (ASER) are morphologically bilaterally symmetric, yet left/right asymmetric in function and in the expression of specific chemosensory signaling molecules. The ASEL versus ASER cell-fate decision is controlled by a complex gene regulatory network composed of microRNAs (miRNAs) and transcription factors. Alterations in the activities of each of these regulatory factors cause a complete lateral cell-fate switch. Here, we describe lsy-2, a novel C2H2 zinc finger transcription factor that is required for the execution of the ASEL stable state. In lsy-2 null mutants, the ASEL neuron adopts the complete ASER gene expression profile, including both upstream regulatory and terminal effector genes. The normally left/right asymmetric ASE neurons are therefore ;symmetrized' in lsy-2 mutants. Cell-specific rescue experiments indicate that lsy-2 is required autonomously in ASEL for the activation of ASEL-specifying factors and the repression of ASER-specifying factors. Genetic epistasis experiments demonstrate that lsy-2 exerts its activity by regulating the transcription of the lsy-6 miRNA in the ASEL neuron, thereby making lsy-2 one of the few factors known to control the cell-type specificity of miRNA gene expression. (+info)
Identification of novel transcriptional networks in response to treatment with the anticarcinogen 3H-1,2-dithiole-3-thione.
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3H-1,2-dithiole-3-thione (D3T), an inducer of antioxidant and phase 2 genes, is known to enhance the detoxification of environmental carcinogens, prevent neoplasia, and elicit other protective effects. However, a comprehensive view of the regulatory pathways induced by this compound has not yet been elaborated. Fischer F344 rats were gavaged daily for 5 days with vehicle or D3T (0.3 mmol/kg). The global changes of gene expression in liver were measured with Affymetrix RG-U34A chips. With the use of functional class scoring, a semi-supervised method exploring both the expression pattern and the functional annotation of the genes, the Gene Ontology classes were ranked according to the significance of the impact of D3T treatment. Two unexpected functional classes were identified for the D3T treatment, cytosolic ribosome constituents with 90% of those genes increased, and cholesterol biosynthesis with 91% of the genes repressed. In another novel approach, the differentially expressed genes were evaluated by the Ingenuity computational pathway analysis tool to identify specific regulatory networks and canonical pathways responsive to D3T treatment. In addition to the known glutathione metabolism pathway (P = 0.0011), several other significant pathways were also revealed, including antigen presentation (P = 0.000476), androgen/estrogen biosynthesis (P = 0.000551), fatty acid (P = 0.000216), and tryptophan metabolism (P = 0.000331) pathways. These findings showed a profound impact of D3T on lipid metabolism and anti-inflammatory/immune-suppressive response, indicating a broader cytoprotective effect of this compound than previously expected. (+info)
A genome-scale assessment of peripheral blood B-cell molecular homeostasis in patients with rheumatoid arthritis.
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OBJECTIVE: While rheumatoid arthritis (RA) is considered a prototypical autoimmune disease, the specific roles of B-cells in RA pathogenesis is not fully delineated. METHODS: We performed microarray expression profiling of peripheral blood B-cells from RA patients and controls. Data were analysed using differential gene expression analysis and 'gene networking' analysis (characterizing clusters of functionally inter-relelated genes) to identify both regulatory genes and the pathways in which they participate. Results were confirmed by quantitative real-time polymerase chain reaction and by measuring the levels of 10 serum cytokines involved in the pathways identified. RESULTS: Genes regulating and effecting the cell-cycle, proliferation, apoptosis, autoimmunity, cytokine networks, angiogenesis and neuro-immune regulation were differentially expressed in RA B-cells. Moreover, the serum levels of several soluble factors that modulate these pathways, including IL-1beta, IL-5, IL-6, IL-10, IL-12p40, IL-17 and VEGF were significantly increased in this cohort of RA patients. CONCLUSIONS: These results outline aspects of the multifaceted role B-cells play in RA pathogenesis in which immune dysregulation in RA modulates B-cell biology and thereby contributes to the induction and perpetuation of a pathogenic humoral immune response. (+info)
Network regulation of calcium signal in stomatal development.
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AIM: Each cell is the production of multiple signal transduction programs involving the expression of thousands of genes. This study aims to gain insights into the gene regulation mechanisms of stomatal development and will investigate the relationships among some signaling transduction pathways. METHODS: Nail enamel printing was conducted to observe the stomatal indices of wild type and 10 mutants (plant hormone mutants, Pi-starvation induced CaM mutants and Pi-starvation-response mutant) in Arabidopsis, and their stomatal indices were analyzed by ANOVA. We analyzed the stomatal indices of 10 Arabidopsis mutants were analyzed by a model PRGE (potential relative effect of genes) to research relations among these genes. RESULTS: In wild type and 10 mutants, the stomatal index did not differ with respect to location on the lower epidermis. Compared with wild type, the stomatal indices of 10 mutants all decreased significantly. Moreover, significant changes and interactions might exist between some mutant genes. CONCLUSION: It was the stomatal intensity in Arabidopsis might be highly sensitive to most mutations in genome. While the effect of many gene mutations on the stomatal index might be negative, we also could assume the stomatal development was regulated by a signal network in which one signal transduction change might influence the stomatal development more or less, and the architecture might be reticulate. Furthermore, we could speculate that calcium was a hub in stomatal development signal regulation network, and other signal transduction pathways regulated stomatal development by influencing or being influenced by calcium signal transduction pathways. (+info)
Versatility and connectivity efficiency of bipartite transcription networks.
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The modulation of promoter activity by DNA-binding transcription regulators forms a bipartite network between the regulators and genes, in which a smaller number of regulators control a much lager number of genes. To facilitate representation of gene expression data with the simplest possible network structure, we have characterized the ability of bipartite networks to describe data. This has led to the classification of two types of bipartite networks, versatile and nonversatile. Versatile networks can describe any data of the same rank, and are indistinguishable from one another. Nonversatile networks require constraints to be present in data they describe, which may be used to distinguish between different network topologies. By quantifying the ability of bipartite networks to represent data we were able to define connectivity efficiency, which is a measure of how economic the use of connections is within a network with respect to data representation and generation. We postulated that it may be desirable for an organism to maximize its gene expression range per network edge, since development of a regulatory connection may have some evolutionary cost. We found that the transcriptional regulatory networks of both Saccharomyces cerevisiae and Escherichia coli lie close to their respective connectivity efficiency maxima, suggesting that connectivity efficiency may have some evolutionary influence. (+info)
Transcriptional regulatory network analysis of developing human erythroid progenitors reveals patterns of coregulation and potential transcriptional regulators.
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Deciphering the molecular basis for human erythropoiesis should yield information benefiting studies of the hemoglobinopathies and other erythroid disorders. We used an in vitro erythroid differentiation system to study the developing red blood cell transcriptome derived from adult CD34+ hematopoietic progenitor cells. mRNA expression profiling was used to characterize developing erythroid cells at six time points during differentiation (days 1, 3, 5, 7, 9, and 11). Eleven thousand seven hundred sixty-three genes (20,963 Affymetrix probe sets) were expressed on day 1, and 1,504 genes, represented by 1,953 probe sets, were differentially expressed (DE) with 537 upregulated and 969 downregulated. A subset of the DE genes was validated using real-time RT-PCR. The DE probe sets were subjected to a cluster metric and could be divided into two, three, four, five, or six clusters of genes with different expression patterns in each cluster. Genes in these clusters were examined for shared transcription factor binding sites (TFBS) in their promoters by comparing enrichment of each TFBS relative to a reference set using transcriptional regulatory network analysis. The sets of TFBS enriched in genes up- and downregulated during erythropoiesis were distinct. This analysis identified transcriptional regulators critical to erythroid development, factors recently found to play a role, as well as a new list of potential candidates, including Evi-1, a potential silencer of genes upregulated during erythropoiesis. Thus this transcriptional regulatory network analysis has yielded a focused set of factors and their target genes whose role in differentiation of the hematopoietic stem cell into distinct blood cell lineages can be elucidated. (+info)
As current antibiotic therapy is increasingly challenged by emerging drug-resistant bacteria, new technologies are required to identify and develop novel classes of antibiotics. A major bottleneck in today's discovery efforts, however, is a lack of an efficient and standardized method for assaying the efficacy of a drug candidate. We propose a new high content screening approach for identifying efficacious molecules suitable for development of antibiotics. Key to our approach is a new microarray-based efficacy biomarker discovery strategy. We first produced a large dataset of transcriptional responses of Bacillus subtilis to numerous structurally diverse antibacterial drugs. Second we evaluated different protocols to optimize drug concentration and exposure time selection for profiling compounds of unknown mechanism. Finally we identified a surprisingly low number of gene transcripts (approximately 130) that were sufficient for identifying the mechanism of novel substances with reasonable accuracy (approximately 90%). We show that the statistics-based approach reveals a physiologically meaningful set of biomarkers that can be related to major bacterial defense mechanisms against antibiotics. We provide statistical evidence that a parallel measurement of the expression of the biomarkers guarantees optimal performance when using expression systems for screening libraries of novel substances. The general approach is also applicable to drug discovery for medical indications other than infectious diseases. (+info)