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Toxicogenomics Heather Handley JP Student Toxicogenomics “… field of study that combines clinical, genomic, and proteomic data into a unified framework for understanding the biochemical and genetic basis for various diseases.” (Ballatori et al., 2003) “… a new scientific field that elucidates how the entire genome is involved in biological responses of organisms exposed to environmental toxicants/stressors. It combines information from studies of genomic-scale mRNA profiling, cell-wide or tissue-wide protein profiling (proteomics), genetic susceptibility, and computational models to understand the roles of gene-environment interactions in disease.” (Selkirk and Tennant, 2002) Toxicogenomics Functional Genomics Comparative Genomics TOXICOGENOMICS & PHARMACOGENOMICS Population Genomics Transcriptomics (Gene Expression) Agenda MICROARRAY OVERVIEW TOXICOGENOMICS EXAMPLES Sequence Analysis 1. Pharmacogenomics and individualized medicine 2. Comparative and functional toxicogenomics Gene Expression Profiling 3. Biomarkers of exposure and effect 4. 5. Genomic approaches to study of toxic mechanisms Toxicant “signature” profiling and predictive toxicology Cytochromes P450 • Monooxygenase enzymes responsible for metabolism of >80% of all clinical drugs and many organic pollutants • Known roles in pollutant toxicity/carcinogenicity, drug-drug interactions, adverse drug effects, drug reactivity • Large, complex gene superfamily … ~2,500 individual genes in bacteria, fungi, plants and animals • Most animals have ~100 genes thought to be derived from a single common ancestor via extensive gene/genome duplication events • Many inducible CYPs regulated by transcription factors in nuclear receptor or bHLH-PAS gene (super)families Microarrays 101 Definitions: • Platforms for massively parallel hybridization assays • High-density arrays of 100s to 1000s of probe-containing features immobilized on a solid substrate Terminology: Traditional hybridizations (e.g. Northern, Southern, Western): target = immobilized sample (e.g.all RNAs/DNAs) probe = specific molecule of intrest in liquid phase Microarrays: target = sample in liquid phase probes = molecules of interest immobilized on substrate Microarrays 101 • Probe type – cDNA: gene expression profiling – Genomic DNA: CGH, ChIP-on-CHIP – Oligonucleotides 25-80mers spotted or synthesized in situ (photolithography or inkjet) – Proteins: enzyme activity, protein-protein interactions – Antibodies: protein expression – Cells: biochemical functions, gene expression – Tissue sections (TMA): high-throughput ISH or IHC Microarrays 101 • Substrate – Membranes (nylon, cellulose, etc.) – Coated glass slides o o Poly L-lysine g-amino poly-silane (GAPS) sugars – Membrane-on-slide • Probe density – Low-density macroarrays (10-100s of features) – Moderate-density microarrays (1,000s) – High-density microarrays (10,000s) Microarrays 101 • Radioactive detection – Single sample per array – Good sensitivity A B • Fluorescent detection – CAN apply multiple samples per array – Less sensitive but more quantitative for changes A+B Pharmacogenomics • Effect of polymorphisms on drug metabolism and toxic side effects of pharmaceutical agents • Oligonucleotide arrays can be used to identify presence of specific alleles in individuals, or to quantify allele ratios in populations e.g. Affymetrix CYP chip (18 known mutations defining 10 alleles of CYP2D6 and 2 alleles of CYP2C19) CYP2D6 poor metabolizer genotypes protect against hepatitis C & cyrrhosis progression • Microelectronic arrays can improve sensitivity/accuracy in detecting single nucleotide differences The Thousand Dollar Genome Genome Resequencing Technologies • Sequencing by hybridization • Solid-phase multiplex PCR • Solexa TotalGenotyping with Single Molecule Arrays • Single molecule sequencing – Protein nanopore – U.S. Genomics Comparative Toxicogenomics • Species differences may exist at the level of gene complement, enzyme function (coding sequence), or transcriptional regulation (flanking genomic or intronic sequences) • Improved homology searching tools (combined with gene prediction) can be used to detect all members of a gene (super)family in a given genome • Evolutionary analyses full gene complements facilitate distinction of orthologous and paralogous relationships in large gene superfamily Functional Toxicogenomics • Species comparisons can be used to identify regions of functional constraint or positive selection • Algorithms for motif detection can be used to predict regulatory elements (and possibly transcription factors) • cDNA microarrays can be used to assess gene expression • Antibody arrays can be used to assess protein levels • Protein arrays can be used to assess enzyme function Biomarker Arrays • Biomarker = biological response (ideally quantifiable) to an environmental chemical, which provides a metric of exposure and sometimes toxic effect(s); may be at the molecular, cellular or whole organism level. • Multiple-gene biomarkers are likely to be more sensitive and discriminating than single genes e.g. Larkin et al. (2003) macroarrays for assessing exposure of fish to estrogenic compounds – Cost-effective – Well implemented – Non-model organism Genomic Approaches to Toxic Mechanisms • Toxicity of many compounds due to altered transcriptional regulation of gene expression • Gene expression profiling provides opportunities to identify affected molecular pathways and cellular functions • Platform(s) cDNAs for oligonucleotides on glass slides • Competitive hybridization with two-channel fluorescent detection used to compare gene-specific relative expression levels between two conditions (except Affymetrix) AHR signaling and Dioxin Toxicity * AHR-ARNT Estrogen-responsive genes ? AHR Gene Battery • Cytochrome P450 1A (CYP1A) • Glutathione S Transferase Oncogenes Cytokines TOXICITY “Adult Heart” Library Atrium Bulbus arteriosus Sinus venosus Ventricle Connective tissue Smooth Muscle Endothelium Blood (>2 cell types) TISSUE • 4+ cell-types • 10,000 genes? cDNA LIBRARY • 76,800 clones – Unsequenced – Redundant Adult Heart Microarrays 4,896 + ~100 AH clones controls/genes of interest 5,186 features (~2,500 genes?) Gene (mRNA) Expression Profiling Control Sample Experimental Sample Prepare total RNA Prepare total RNA Generate amino-allyl modified cDNA Generate amino-allyl modified cDNA Label with fluorescent green dye (Cy3) Label with fluorescent red dye (Cy5) Microarray Analysis Control Equal Expression More Expression In Experimental Experimental More Expression In Control Data Analysis 2-fold CYP1A Dioxin-responsive genes INDUCTION 159 41 94 0.5nM TCDD 5nM TCDD 1 54 58 SUPPRESSION GENERAL TRENDS • 361 clones differentially expressed (p-value 1*10-4) – 6 previously identified clones – 99 assembled into 17 contigs (15 known genes, 2 ESTs) – ~75 low quality sequence • Predominantly induction • Low-dose responses prevalent Chemical Profiling and Predictive Toxicology • Diagnostic features determined from training set of compounds with known mechanisms of action • Methods for determining diagnostic subset include: – Self Organizing Maps (SOMs) and Neural networks – Bayesian statistics • Caveats – Must be certain about mechanisms of training compounds – Can only distinguish states represented in training set Thomas et al., 2001 Thomas et al., 2001