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Biological questions solved on microarrays

Biological questions solved on microarrays. Françoise de Longueville Cell biology and biochemistry, University of Namur, 61 Rue de Bruxelles , 5000 Namur, Belgium Tel : 32-81-724129 Email: francoise.delongueville@fundp.ac.be. Genome sequencing. More than 24 genomes sequenced

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Biological questions solved on microarrays

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  1. Biological questions solved on microarrays Françoise de Longueville Cell biology and biochemistry, University of Namur, 61 Rue de Bruxelles , 5000 Namur, Belgium Tel : 32-81-724129 Email: francoise.delongueville@fundp.ac.be

  2. Genome sequencing • More than 24 genomes sequenced • Human genome completed in 2001 • More than 100 sequencing projects in progress • More than 3 billion DNA bases in the data bank

  3. Genomic Request • Necessity of tool for easy detection of genes to understand • their function and role in pathologies • How using sequence information to detect thousands of genes •  Technology : DNA hybridization •  TechnologyDevelopment: DNA microarray

  4. DNA microarray Evolution Gene by gene study (by hybridization)Simultaneous study of >1000 genes B A

  5. B C Steps of microarray development 1) Glass activation 2) Capture probes cDNA (100-1000 bases) or oligonucleotides (20 bases) 3) Spotting: covalent attachment by an arrayer (mechanical) 4) Hybridization 5) Detection:fluorescence, radioactivity, colorimetry

  6. DNA Microarray technology 1.Characteristics: multiparametric assays with miniaturization of the process and fastdetection  well suited for molecular analysis of hundreds or thousands of genes.  main tool of the genomic field (easy to plan the sequences to be detected) 2. Aims :  Gene identification (Target = DNA)  Gene expression monitoring (Target = mRNA) 3. Applications :  Gene discover  Disease diagnosis  Drug discovery : Pharmacogenomics  Toxicological research : Toxicogenomics

  7. Gene expression analysis: Development of Rat HepatoChips: a predictive tool for potential side effects of new drugs

  8. DNA microarray technology • Advantages of DNA microarray • Miniaturization,small volume, time saving • Simultaneous analysis of hundreds of genes • Advantages of low density DNA microarray (10 - 400 spots) • Possibility to optimize each capture probes • comparable hybridization yield allows reliable quantification • Easier data processing and data mining • Low cost

  9. The Gene Expression Challenge in molecular toxicology field • DNA microarray answers key questions: • Identification of chemical compounds with potential side effects • Better understanding of the toxicity mechanism • Number of toxicology issues including mode of action, dose response relationships and chemical interactions

  10. ‘ Treated ’ cell Normal cell mRNA extraction Reverse transcription and labelling B B Hybridization on DNA microarray A A C D C D B D Detection and data analysis A D DNA microarray applied to gene expression

  11. Gene Category Selected Genes Apoptosis Cell cycle DNA damage/Repair Inflammation Metabolism Oncogene Stress response Peroxisome Proliferators Transcription factors, growth factors Transport Bax, Bcl-2, TNF, Smp30 Cyclin D1, JNK-1, Telomerase GADD45, GADD153, MGMT Il-6, cyclooxygenase-2 P450s, glutathione enzymes, glucoronidation enzymes c-jun, c-myc, elk-1 Oxidative stress genes, ApoJ, Hsp70, Heme oxygenase 2, SOD Enoyl coA hydratase, PPAR , Acyl coA oxidase C/EBP, IB-, NFB, erk-1, p38, HGF, TGFB RII Multi-drug Resistance protein, albumin, transferrin 60 genes (rat) carefully selected by pharmaceutical toxicologists

  12. DNA capture probe synthesis • Covalent attachment of capture probe on glass slides • Specificity of capture probe • Optimization of the reverse transcription • Optimization of hybridization conditions • Microarray validation with toxic reference compounds • Data processing and data mining Overview of Rat Hepatochips development

  13. ) Scanning with a confocale scanner 2) Quantification with the software ‘ Imagene’ of biodiscovery • 3) Treatment of raw data (excel template) • Normalization: • First Step: internal Standard Normalization • 3 internal standards (plants) • Second Step:  Housekeeping genesNormalization • 8 housekeeping genes 4) Determination of significant ratio statistical test described by Chen Y. et Dougherty E.R. (Journal of biomedical optics 2(4), 364-374, 1997) determination of confidence interval based on the variance of houseKeeping genes Data processing

  14. Phenobarbital treatment on rat min max Control PB

  15. Phenobarbital assay: Scatterplot

  16. Phenobarbital assay: Histogram

  17. Rat HepatoChips Validation 3 Control 3 Control 3 Control 3 Control 3 Control 3 PB 3 Dex 3 MIC 3 BNF 3 CLOT 3 PCN 3 ISN 3 TAO 3 MCP Rat HepatoChips validation

  18. Rat HepatoChips validation Control First Animal Compound replicat #1 replicat #2 replicat #3

  19. Rat HepatoChips validation Control Second Animal Compound replicat #1 replicat #2 replicat #3

  20. Rat HepatoChips validation Control Third Animal Compound replicat #1 replicat #2 replicat #3

  21. Rat Hepatochips Issues • Development & Optimizations are completed • Hepatochips validation with reference compounds Collaboration with UCB-Pharma and Merck Sharp&Dohme • Data processing and statistical analysis • Development of a data bank for reference compounds • Cluster analysis Collaboration with Vincent Bertholet, François Roland and Prof. J.P. Rasson

  22. Challenge in data mining • Recovering the biological information from the experimental data is nontrivial • Measurement of gene expression depends on : • Multiple sources of noise • False hybridization • Inherent variability across individuals, tissues or cell lines • Request to improve the existing analysis tools

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