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General Principles of Toxicogenomics

The document discusses the principles of toxicogenomics, focusing on genomics, microarray technologies, and experimental design for assessing chemical exposure effects on gene expression. It highlights applications of toxicogenomics in identifying biological pathways and potential health effects from exposure to toxicants, using the example of cigarette smoke analysis. Key topics include data handling, analysis methods, and quality control in experimental design to ensure reliable gene expression profiling.

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Healthy Environments and Consumer Safety Branch General Principle of Toxicogenomics Carole Yauk Environmental Health Sciences and Research Bureau Health Canada
Healthy Environments and Consumer Safety Branch OUTLINE 1. General genomics 2. What is toxicogenomics? g 3. Overview of microarray technologies 4. Data handling and data analysis 5. 5 Experimental Design 6. An example from our lab 7. Conclusions and needs
Healthy Environments and Consumer Safety Branch Genome = all an individual organism's genes Genomics = the study of all of the genes of a cell or tissues at the DNA, RNA and protein level , p
Genome and Epigenome DNA sequence DNA methylation Histones and histone modification Credit: Moving AHEAD with an international human epigenome project. Nature 454, 711-715
Gene Expression (mRNASafety Branch Healthy Environments and Consumer Transcriptome) Messenger RNA Source: http://www.news-medical.net/health/What-is-Gene-Expression.aspx
MicroRNAs: the newest piece of the puzzle Helping the people Aider les Canadiens et of Canada maintain and les Canadiennes à maintenir improve their health et à améliorer leur santé Controls mRNA translation by y mRNA degradation or translational repression Source: microRNAs join the p53 network — another piece in the tumour-suppression puzzle Lin He, Xingyue He, Scott W. Lowe & Gregory J. Hannon Nature Reviews Cancer 7, 819-822 (November 2007)
A single microRNAs controls many mRNA products Healthy Environments and Consumer Safety Branch miRNA mRNA mRNA mRNA mRNA RNA mRNA RNA mRNA
Healthy Environments and Consumer Safety Branch Toxicogenomics Treatment Genome G DNA Response Transcriptome RNA Disease Proteome Protein
FOCUS: mRNA Consumer Safety Branch Healthy Environments and (gene expression) Gene expression PRECEDES protein changes and toxicity p p g y Changes in gene expression are measurable at low doses Gene Expression
Chemicals perturb gene expression Healthy Environments and Consumer Safety Branch Example: aryl hydrocarbon receptor agonists Source: Miller and Ramos, Drug Metabolism Reviews, 2001
Genes are part of pathways that carry out cellular functions Healthy Environments and Consumer Safety Branch Source: www.rndsystems.com/mini_review_detail_objectname_MR03_DNADamageResponse .aspx
Identify perturbed genes and their pathways/functions Healthy Environments and Consumer Safety Branch Elevated and Prolonged Lead Exposure in Fisher 344 Rats Leads to Marked Hepatic Differentially Expressed Genes. Gato and Means, 2010.
Associate genes with biological pathways and processes Healthy Environments and Consumer Safety Branch Perturbations in specific pathways lead to disease Source: Kyoto Encyclopedia for Genes and Genomes
Healthy Environments and Consumer Safety Branch Applications • Deciphering mechanism of action (pathway analysis) of toxicant • Response at low doses • Revealing potentially novel health effects • Identification of perturbed pathways – targeted follow-up • Biomarker discovery • Investigating assumptions in toxicology • Predictive toxicogenomics
Healthy Environments and Consumer Safety Branch Gene Expression Analytical methods to study mRNA transcription • Gene by gene analysis: Northern Blotting, RT-PCR, qRT-PCR • PUBLICATION OF GENOMES • DNA microarrays i • Real-time PCR arrays
Healthy Environments and Consumer Safety Branch Cells of interest Microrray Technology Laser Scanning mRNA (“target”) isolation and labelling Hybridize & wash Microscope slide
Two colour experiment Healthy Environments and Consumer Safety Branch Slide 1 Slide 2 Gene A G Gene B
Two Environments and Consumer Safety Branch Healthy colour reference design Biological Sample g p Universal Mouse Reference RNA f External RNA control RNA Cy3 Cy5 labelled labelled cRNA cRNA Array Hybridization Fluorescence detection and image analysis
Expression profiling and Consumer Safety Branch GeneChips Healthy Environments using Affymetrix Source: Affymetrix.com
DNA microarrays: and Consumer Safety Branch Healthy Environments poor reproducibility in the early days led to a bad rap Publication Platforms Probe ID Validation Authors’ Conclusion Kane et al., 2000 Operon 50mer, cDNA Sequence similarity None Agreement Hughes et al., 2001 Agilent oligo, cDNA Sequence similarity None Agreement Yuen et al., 2002 Affymetrix, custom cDNA Sequence similarity QRT-PCR Agreement Kuo et al., 2002 cDNA versus Affymetrix Sequence similarity None Kothapalli et al., 2002 h ll l Incyte cDNA Affymetrix ff Sequence similarity l Northern h Li et al., 2002 Affymetrix, Incyte cDNA Unigene or Genbank QRT-PCR Barczak et al., 2003 Affymetrix, Operon 70mer Unigene ID None Agreement Carter et al., 2003 Agilent 60mer, cDNA Sequence matched QRT-PCR Agreement Wang et al., 2003 W l Custom oligo and cDNA C l d DN Sequence similarity l RT-PCR RT PCR Agreement Rogojina et al., 2003 Affymetrix, Clontech cDNA Genbank ID QRT-PCR and Q-immunoblot Tan et al., 2003 Agilent cDNA, Affy, Genbank ID None Amersham 30mer Meecham et al.,2004 Agilent cDNA, Affymetrix Sequence matched None Agreement Mah et al., 2004 cDNA array, Affymetrix Unigene (sequence QRT-PCR *Two different labs verified) Järvinen et al., 2004 Affymetrix, Agilent cDNA, Unigene ID None Custom-cDNA
Healthy Environments and Consumer Safety Branch EARLY PROBLEMS Non-specific ( i N ifi (or incorrect) probes. t) b Incorrect annotation. I t t ti Poor printing technology. Sub-optimal protocols.
Healthy Environments and Consumer Safety Branch Problems with statistical analysis and experimental design Leniant filtering methods for poor or low intensity spots spots. Incorrect probe matching across platforms. Improper data handling (i.e. Normalization). Incorrect statistical analysis. Biological replication.
Improved reproducibility after 2004 Healthy Environments and Consumer Safety Branch Publication Platforms Probe ID Validation Authors’ Conclusion Yauk et al., 2004 Codelink, Agilent cDNA, Agilent Oligo, NIA cDNA, Unigene ID None Dependant on platform – good platforms M rg n, ffym tr Mergen, Affymetrix c rr at correlate Shippy et al., 2004 Affymetrix, Amersham Unigene ID Real Time RT-PCR Agreement after noise adjusted Irizarry et al., 2005 Lab- Affymetrix (5 labs), cDNA (3 labs), 2 colour Oligo Unigene, LocusLink, Real Time RT-PCR Agreement among best performing labs lab comparison (2 labs) RefSeq (10 labs) Larkin et al., 2005 Affymetrix, TIGR cDNA Sequence mapped Real Time RT-PCR Agreement TIGR TRC Group, 2005 5 custom cDNA, Amersham, Compugen, Agilent, Transcripts matched None Moderate Agreement (standardized *Lab-lab comparison Affy, Operon, 2 custom Oligo using NIA mouse index protocols and data analysis required) 7 labs, 12 platforms Pylatuik et al., 2005 Genomic Amplicon Arrays, Locus ID Northern blot Moderate agreement (signal intensity- Operon Oligo, Affymetrix dependant) Shi et al 2005 al., Tan et al 2003 dataset al., Genbank Acc. No. Acc No N/A Alternate analysis had 10X +concordance. Barnes et al., 2005 Affymetrix, Illumina BeadArrays Sequence matched None Agreement using BLAST Carter et al., 2005 Affymetrix, Stanford cDNA sequence matching None Agreement (overlapping probes) Schlingemann et al., 2005 hl l Affymetrix, In-house long Oligo ff h l l Unigene ID D Real Time RT-PCR l P Agreement Warnat et al., 2005 6 different cDNA and oligo array studies Unigene ID N/A Agreement (more platforms better for previously published predictive anal.) Ali-Seyed et al., 2006 Affymetrix Promoter Analysis Real Time RT-PCR AB more sensitive/ correlated RT-PCR. Applied Biosystems Severgnini et al., 2006 g Affymetrix, Codelink y LocusLink ID Real Time RT-PCR Disagreement g De Reyniès et al., 2006 Affymetrix, GE Healthcare (Amersham), Agilent Sequence mapped Real Time RT-PCR Moderate agreement (1 colour better than 2 colour) Wang et al., 2006 Applied Biosystems, Agilent Sequence matched Real Time RT-PCR Agreement (BLAST) (1375 genes confirmed with RT-PCR) Kuo et al., 2006 Affymetrix, Amersham Probes sequence Real Rime RT-PCR Agreement (commercial better than in- *Lab-lab comparison Lab lab Mergen, ABI, Mergen ABI Custom cDNA MGH MWG Agilent, cDNA, MGH, MWG, Agilent matched within 1 exon house, 1-colour house 1 colour better than 2) added* Compugen, Operon (Unigene, LocusLink, RefSeq, Refseq exon) Green = correlation between platforms See Yauk et al. Nucleic Acids Research, 2004 yellow = moderate correlation between platforms red = poor correlation between platforms Yauk and Berndt, Environ Mol Mutagen 2007
Healthy Environments and Consumer Safety Branch Obtaining useful information from a microarray experiment 1. Quality Control y 2. Remove probes in background. 3. Adjust (normalize) the measurements to facilitate comparisons. 4. Select genes that are differentially expressed between samples. l 5. Identify the biological processes and molecular functions that are altered altered. 6. Place data in the context of a health outcome.
1. Quality Healthy Environments andGarbageBranch Garbage out Measures: Consumer Safety in, A. Sample and RNA Quality B. Array (slide) quality • Percentage of spots with no signal • Number of saturated spots • Intensity Distribution • Summary Measures of the negative control spots • Median Signal to Noise Ratio • M di Brightness Median B i ht • External Controls
Example: Agilent Quality Reports Healthy Environments and Consumer Safety Branch
Healthy Environments and Consumer Safety Branch 2. Background noise: f l positives 2 B k d i false iti • Estimate the background? g Local Negative Control Spots g p Should we background subtract? • Limits of Detection, Presence/Absence Calls Flagging spots in the background gg g p g
3. Normalization: Cross-slide Consumer Safety Branch and removing bias Healthy Environments and comparisons ntensities Raw relative in Normalized relativ intensities ve Array number
Healthy Environments and Consumer Safety Branch 4. 4 Identify genes that are affected by the treatment • Fold change is not a statistical test • 50,000 comparisons on one chip – adjust for multiple comparisons • Levels of filtering to identify changing genes 1. Fold Change 2. T-tests/ANOVA 2 T t t /ANOVA 3. Permutation test a) MAANOVA b) Significance Analysis of Microarrays (SAM)
Healthy Environments and Consumer Safety Branch 5. Identify biological processes/molecular functions/pathways that are altered and link to a potential health outcome BIOINFORMATICS Gene Ontology: a controlled vocabulary of terms for describing gene product characteristics and gene product annotation data Includes: cellular compartment biological function molecular process Pathway: collection of manually drawn pathway maps representing knowledge on the th molecular i t l l interaction and reaction networks ti d ti t k Looking for over-representation of changing genes within these groups.
Example:Environments and Consumer Safety Branch Healthy Kegg pathway for P53 signalling
Healthy Environments and Consumer Safety Branch Designing an experiment to study mechanism of action 1. Adequate sample size! q p 2. Appropriate selection of time points (e.g., early, downstream, transformation, disease effects) 3. Appropriate selection of treatment conditions (non-toxic) 4. Appropriate tissue/cells sampled 5. Sample collection – randomization (time effects) 6. HIGH QUALITY RNA!!! 7. Randomization d i 7 R d i ti and microarray experimental d i i t l design 8. Implementation of QA/QC 9. Appropriate normalization and filtering 10. VALIDATION WITH ALTERNATIVE TECHNOLOGIES
Healthy Environments and Consumer Safety Branch An example from our lab
Toxicological Profiles of Cigarette Smoke Healthy Environments and Consumer Safety Branch Condensate C d t Use of high-density DNA microarrays to Investigate pathways induced by CSC exposure Correlation with other toxicity endpoints C l i ih h i i d i 5 cigarette brands: 1. Export A full flavour 2. 3. Gauloises Blonde 3 Gau o ses o de 3. Player’s Light King Size Carole Yauk and Paul White collaboration
Healthy Environments and Consumer Safety Branch Cigarette smoke condensate collection and characterization Brand # of cigarettes Total TPM TPM/cig Smoked Yield(mg) 1 – Export A 60 1625.5 27.09 2 – Gauloises Blondes 108 1826.0 16.91 3 – Player’s Light King Size 117 1659.0 14.18
Healthy Environments and Consumer Safety Branch Analyte Export A Gauloises Player’s Carcinogenicity Blonde Light g Tar (mg/cig) 15.6 12.9 12.4 NA Nicotine (mg/cig) 1.3 1.1 1.1 NA CO (mg/cig) ( g/ g) 14.0 13.6 12.7 NA Benzo[a]pyrene (ng/cig) 9 8 10 1 4-aminobiphenyl (ng/cig) 2 2 2 1 NNN (ng/cig) 37 178 25 1 NNK (ng/cig) 75 63 52 1 Cadmium (ng/cig) 90 47 90 1 Lead (ng/cig) NQ 19 NQ 2B Formaldehyde (μg/cig) 82 54 44 2A Acetaldehyde (μg/cig) 698 680 587 2B 1,3-butadiene 1 3 butadiene (μg/cig) 52 44 48 2A Isoprene (μg/cig) 276 376 301 2B Acrylonitrile (μg/cig) 11 12 10 2B Benzene (μg/cig) 49 43 49 1 Styrene (μg/cig) 14 10 10 2B
Toxicity/genotoxicity Healthy Environments and Consumer Safety Branch Phenotypic anchoring and dose selection Toxicity – Cloning Efficiency in Muta™Mouse Lung Epithelial Cells y g y g p Mutagenicity – Mutations Salmonella typhimurium Mutagenicity – Mutations in Muta™Mouse Lung Epithelial Cells i it Micronuclei in M t ™M Clastogenicity – Mi Cl t l i i Muta Mouse L Lung E ith li l C ll Epithelial Cells Essential to select meaningful concentrations for microarray experiments The Muta™Mouse
Healthy Environments and Consumer Safety Branch Toxicity Profiling Via Cloning Efficiency (LD50 Values Determined Using Probit Link Function) 120 100 LD 50 (µg/ml media) 80 60 40 20 0 Brand 1 Brand 2 Brand 3 Brand 4 Brand 5 E p Export A Player’s Special y p Gauloises Player’s Plain y Player’s Light y Lg Yauk et al., manuscript in preparation
Mutagenicity in the Healthy Environments and Consumer Safety Branch Ames Assay 1.2 12 Export A Gauloises Player's King Mutagenic Pot. (rev/µg TPM) 1.0 0.8 0.6 P 0.4 M 0.2 0.0 TA98 YG1041 G YG5161 G Yauk et al., manuscript in preparation
Healthy Environments and Consumer Safety Branch Cigarette smoke condensate does not induce DNA sequence mutations in the FE1 cell line Pilot Brand Pre- S9 Dose CSC Summary incubation ug/ml #1 Gauloises No 0 0, High Sp MF, No 20,40,60,80 response #2 Gauloises No 0.5% 0 5% 0, 0 High Sp MF, No MF 20,40,60,80 response #3 Export A Full 60min 0.5% 0, 60 Good Sp MF, No Flavor response #4 Export Full 15, 30, 0.5% 0,40,60,80,1 Good Sp MF, No Flavor 60min 00 response #5 Players Light 60 min 0.5% 0-150 No dose response #6 Gauloise 60 min 0.5,1,2,4% 100 No response #7 Players No 0,1,2,4 100,150,200 No dose Special response #8 Players Plain No No 20-120 No response
Healthy Environments and Consumer Safety Branch Cytokinesis-Block Micronucleus Assay
CBMN Assay in Muta™Mouse FE1 Cells Healthy Environments and Consumer Safety Branch Results for Player s Light Player’s 35.0 Total MN/500 cells *** ucleate Freq. (% ) MN Freq. (per 500 cells) ) 30.0 Binucleate Freq 0.80 25.0 ** * F 20.0 20 0 15.0 0.40 10.0 Binu F 5.0 0.0 0.00 0 60 90 120 0 Cigarette Smoke Condensate (µg/mL) *p<0.05, **p<0.01, ***p<0.001 Fisher’s Exact Test Yauk et al., manuscript in preparation
Cigarette smoke condensate isSafety Branch Healthy Environments and Consumer clastogenic in mouse p pulmonary epithelial cells in vitro y p 45 DMSO 40 90 μg/mL *** 35 120 μg/mL ** 150 μg/mL ** ** Cells with MN per 1000 * 30 * 25 20 w 15 10 5 0 Export Gauloises Player's Yauk et al., manuscript in preparation
Healthy Environments and Consumer Safety Branch TOXICOGENOMICS
Healthy Environments and Consumer Safety Branch Final Decision for Design of Microarray Study 2 time points (early response/late response) Early = after 6hr exposure Late = after 4hr recovery (10hr total) 3 doses (control, low, high) Low = 45μg TPM/mL, High 90μg TPM/mL TPM/mL High= 5 replicates/dose (required to obtain statistical significance) Agilent 22k toxicology arrays g gy y
Microarray Analyses – Main Experiment Healthy Environments and Consumer Safety Branch Generated 1,365,000 data points MAANOVA to Identify Significant Changes Clustering and pathway analyses Affected genes, biomarkers and brand-specific signatures
Healthy Environments and Consumer Safety Branch Summary of gene expression findings 296 known genes were up- or down-regulated relative to solvent 54 down-regulated g 6 hours 115 genes 61 up-regulated 172 down-regulated 10 hours 254 genes 82 up-regulated Yauk et al., manuscript in preparation
Summary of geneConsumer Safety Branch Healthy Environments and expression findings 6 hours 10 hours 45 ug/ml 90 ug/ml 45 ug/ml 90 ug/ml ↑ ↓ ↑ ↓ ↑ ↓ ↑ ↓ Export A 5 3 22 24 24 5 66 171 Gauloise 2 0 54 30 13 11 54 46 Player’s 4 12 37 42 8 7 82 103 Light Yauk et al., manuscript in preparation
Large overlap among the brands Healthy Environments and Consumer Safety Branch e.g., 10 hours, 90 μg/ml Export A E t Player’s Li ht Pl ’ Light 8 93 2 87 49 3 2 Gauloises Yauk et al., manuscript in preparation
Up-regulated in Exposed Down-regulated in Exposed Healthy Environments and Consumer Safety Branch (Higher in Dose 90) (Lower in Dose 90) aurora kinase A guanine nucleotide binding protein, b t 4 bi di t i beta cell division cycle 20 homolog sulfiredoxin 1 homolog cell division cycle 2 homolog A tetraspanin 33 cell di i i ll division cycle associated 5 l i t d DNA-damage inducible DEP domain containing 1B transcript 3 F-box only protein 5 serine peptidase inhibitor, clade E, , , histone 1, H1b member 1 inner centromere protein glutathione synthetase karyopherin ( p y p (importin) alpha 2 ) p zinc finger protein 330 polo-like kinase 1 cytochrome P450, family 1, subfamily b, protein regulator of cytokinesis polypeptide 1 1 Control Control 6 hours Export A 45 μg/ml 10 hours Gauloises Blonde 90 μg/ml Player’s light king size Yauk et al., manuscript in preparation
10 hour Gene Ontology Analysis Healthy Environments and Consumer Safety Branch Benjamini B j i i Benjamini p- B j i i Term p-value Term value cell division 0.000 p53 signaling 0.015 metabolic etabo c mitosis 0.000 processes 0.017 regulation of g cell cycle 0.000 cell death 0.019 cell cycle y DNA damage g process 0.000 response 0.027 regulation of cell division 0.000 0 000 apoptosis 0.047 mitosis 0.000 Yauk et al., manuscript in preparation
Helping the people Aider les Canadiens et of Canada maintain and les Canadiennes à maintenir improve their health et à améliorer leur santé
Dose Trends between 6 and 10 hrs Healthy Environments and Consumer Safety Branch 77 genes decreasing tensity in expression with dose Normalized Int 6 hrs 10 hrs 66 genes increasing in expression with d ith dose N 6 hrs 10 hrs
Screening in genetic toxicology Healthy Environments and Consumer Safety Branch 1 year yea 2 year yea Cancer Cost:$2M/cmpd 2 year rodent cancer bioassay Time: 3 years Mutation Cost: $60K/cmpd Dominant Lethal Test Time: 6-12 months } In vitro mammalian mutation Cost: $60K/cmpd In vivo mutation Time: 3 months Salmonella bacteria assays Genomics Cost: $10K/cmpd Gene expression analysis Time: 1 month HIGH CONTENT!
Predictive toxicogenomics: Healthy Environments and Consumer Safety Branch medium throughput MOA analysis Ellinger-Ziegelbauer H, et al., Toxicology Letters 186 (2009) 36-44.
Increasing number of papers analyzing gene expression to support Healthy Environments and Consumer Safety Branch observed endpoints: Focussed quantitative real-time PCR arrays y
Healthy Environments and Consumer Safety Branch Concluding remarks on gene expression technologies • Technologies have come a long way over the past decade • Appropriate experimental design in combination with correct data handling generate reproducible and reliable data • Improved annotation and bioinformatics tools are leading to a better ability to interpret findings • Expression technologies are highly useful for: • The identification of mechanisms of action • Biomarker discovery • Exploring potentially novel health effects • Chemical categorization
Healthy Environments and Consumer Safety Branch Needs for application to identify MOA • Identification and validation of adverse outcome genes/pathways (differentiating adaptive versus adverse effects) • Increasing the database of c e ca s a a y ed c eas g t e o chemicals analyzed • Identification of low-dose effects • Improved bioinformatics tools for data interpretation • Guidelines for use of expression data in regulatory assessments

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General Principles of Toxicogenomics

  • 1.
    Healthy Environments andConsumer Safety Branch General Principle of Toxicogenomics Carole Yauk Environmental Health Sciences and Research Bureau Health Canada
  • 2.
    Healthy Environments andConsumer Safety Branch OUTLINE 1. General genomics 2. What is toxicogenomics? g 3. Overview of microarray technologies 4. Data handling and data analysis 5. 5 Experimental Design 6. An example from our lab 7. Conclusions and needs
  • 3.
    Healthy Environments andConsumer Safety Branch Genome = all an individual organism's genes Genomics = the study of all of the genes of a cell or tissues at the DNA, RNA and protein level , p
  • 4.
    Genome and Epigenome DNA sequence DNA methylation Histones and histone modification Credit: Moving AHEAD with an international human epigenome project. Nature 454, 711-715
  • 5.
    Gene Expression (mRNASafetyBranch Healthy Environments and Consumer Transcriptome) Messenger RNA Source: http://www.news-medical.net/health/What-is-Gene-Expression.aspx
  • 6.
    MicroRNAs: the newestpiece of the puzzle Helping the people Aider les Canadiens et of Canada maintain and les Canadiennes à maintenir improve their health et à améliorer leur santé Controls mRNA translation by y mRNA degradation or translational repression Source: microRNAs join the p53 network — another piece in the tumour-suppression puzzle Lin He, Xingyue He, Scott W. Lowe & Gregory J. Hannon Nature Reviews Cancer 7, 819-822 (November 2007)
  • 7.
    A single microRNAscontrols many mRNA products Healthy Environments and Consumer Safety Branch miRNA mRNA mRNA mRNA mRNA RNA mRNA RNA mRNA
  • 8.
    Healthy Environments andConsumer Safety Branch Toxicogenomics Treatment Genome G DNA Response Transcriptome RNA Disease Proteome Protein
  • 9.
    FOCUS: mRNA ConsumerSafety Branch Healthy Environments and (gene expression) Gene expression PRECEDES protein changes and toxicity p p g y Changes in gene expression are measurable at low doses Gene Expression
  • 10.
    Chemicals perturb geneexpression Healthy Environments and Consumer Safety Branch Example: aryl hydrocarbon receptor agonists Source: Miller and Ramos, Drug Metabolism Reviews, 2001
  • 11.
    Genes are partof pathways that carry out cellular functions Healthy Environments and Consumer Safety Branch Source: www.rndsystems.com/mini_review_detail_objectname_MR03_DNADamageResponse .aspx
  • 12.
    Identify perturbed genesand their pathways/functions Healthy Environments and Consumer Safety Branch Elevated and Prolonged Lead Exposure in Fisher 344 Rats Leads to Marked Hepatic Differentially Expressed Genes. Gato and Means, 2010.
  • 13.
    Associate genes withbiological pathways and processes Healthy Environments and Consumer Safety Branch Perturbations in specific pathways lead to disease Source: Kyoto Encyclopedia for Genes and Genomes
  • 14.
    Healthy Environments andConsumer Safety Branch Applications • Deciphering mechanism of action (pathway analysis) of toxicant • Response at low doses • Revealing potentially novel health effects • Identification of perturbed pathways – targeted follow-up • Biomarker discovery • Investigating assumptions in toxicology • Predictive toxicogenomics
  • 15.
    Healthy Environments andConsumer Safety Branch Gene Expression Analytical methods to study mRNA transcription • Gene by gene analysis: Northern Blotting, RT-PCR, qRT-PCR • PUBLICATION OF GENOMES • DNA microarrays i • Real-time PCR arrays
  • 16.
    Healthy Environments andConsumer Safety Branch Cells of interest Microrray Technology Laser Scanning mRNA (“target”) isolation and labelling Hybridize & wash Microscope slide
  • 17.
    Two colour experiment HealthyEnvironments and Consumer Safety Branch Slide 1 Slide 2 Gene A G Gene B
  • 18.
    Two Environments andConsumer Safety Branch Healthy colour reference design Biological Sample g p Universal Mouse Reference RNA f External RNA control RNA Cy3 Cy5 labelled labelled cRNA cRNA Array Hybridization Fluorescence detection and image analysis
  • 19.
    Expression profiling andConsumer Safety Branch GeneChips Healthy Environments using Affymetrix Source: Affymetrix.com
  • 20.
    DNA microarrays: andConsumer Safety Branch Healthy Environments poor reproducibility in the early days led to a bad rap Publication Platforms Probe ID Validation Authors’ Conclusion Kane et al., 2000 Operon 50mer, cDNA Sequence similarity None Agreement Hughes et al., 2001 Agilent oligo, cDNA Sequence similarity None Agreement Yuen et al., 2002 Affymetrix, custom cDNA Sequence similarity QRT-PCR Agreement Kuo et al., 2002 cDNA versus Affymetrix Sequence similarity None Kothapalli et al., 2002 h ll l Incyte cDNA Affymetrix ff Sequence similarity l Northern h Li et al., 2002 Affymetrix, Incyte cDNA Unigene or Genbank QRT-PCR Barczak et al., 2003 Affymetrix, Operon 70mer Unigene ID None Agreement Carter et al., 2003 Agilent 60mer, cDNA Sequence matched QRT-PCR Agreement Wang et al., 2003 W l Custom oligo and cDNA C l d DN Sequence similarity l RT-PCR RT PCR Agreement Rogojina et al., 2003 Affymetrix, Clontech cDNA Genbank ID QRT-PCR and Q-immunoblot Tan et al., 2003 Agilent cDNA, Affy, Genbank ID None Amersham 30mer Meecham et al.,2004 Agilent cDNA, Affymetrix Sequence matched None Agreement Mah et al., 2004 cDNA array, Affymetrix Unigene (sequence QRT-PCR *Two different labs verified) Järvinen et al., 2004 Affymetrix, Agilent cDNA, Unigene ID None Custom-cDNA
  • 21.
    Healthy Environments andConsumer Safety Branch EARLY PROBLEMS Non-specific ( i N ifi (or incorrect) probes. t) b Incorrect annotation. I t t ti Poor printing technology. Sub-optimal protocols.
  • 22.
    Healthy Environments andConsumer Safety Branch Problems with statistical analysis and experimental design Leniant filtering methods for poor or low intensity spots spots. Incorrect probe matching across platforms. Improper data handling (i.e. Normalization). Incorrect statistical analysis. Biological replication.
  • 23.
    Improved reproducibility after2004 Healthy Environments and Consumer Safety Branch Publication Platforms Probe ID Validation Authors’ Conclusion Yauk et al., 2004 Codelink, Agilent cDNA, Agilent Oligo, NIA cDNA, Unigene ID None Dependant on platform – good platforms M rg n, ffym tr Mergen, Affymetrix c rr at correlate Shippy et al., 2004 Affymetrix, Amersham Unigene ID Real Time RT-PCR Agreement after noise adjusted Irizarry et al., 2005 Lab- Affymetrix (5 labs), cDNA (3 labs), 2 colour Oligo Unigene, LocusLink, Real Time RT-PCR Agreement among best performing labs lab comparison (2 labs) RefSeq (10 labs) Larkin et al., 2005 Affymetrix, TIGR cDNA Sequence mapped Real Time RT-PCR Agreement TIGR TRC Group, 2005 5 custom cDNA, Amersham, Compugen, Agilent, Transcripts matched None Moderate Agreement (standardized *Lab-lab comparison Affy, Operon, 2 custom Oligo using NIA mouse index protocols and data analysis required) 7 labs, 12 platforms Pylatuik et al., 2005 Genomic Amplicon Arrays, Locus ID Northern blot Moderate agreement (signal intensity- Operon Oligo, Affymetrix dependant) Shi et al 2005 al., Tan et al 2003 dataset al., Genbank Acc. No. Acc No N/A Alternate analysis had 10X +concordance. Barnes et al., 2005 Affymetrix, Illumina BeadArrays Sequence matched None Agreement using BLAST Carter et al., 2005 Affymetrix, Stanford cDNA sequence matching None Agreement (overlapping probes) Schlingemann et al., 2005 hl l Affymetrix, In-house long Oligo ff h l l Unigene ID D Real Time RT-PCR l P Agreement Warnat et al., 2005 6 different cDNA and oligo array studies Unigene ID N/A Agreement (more platforms better for previously published predictive anal.) Ali-Seyed et al., 2006 Affymetrix Promoter Analysis Real Time RT-PCR AB more sensitive/ correlated RT-PCR. Applied Biosystems Severgnini et al., 2006 g Affymetrix, Codelink y LocusLink ID Real Time RT-PCR Disagreement g De Reyniès et al., 2006 Affymetrix, GE Healthcare (Amersham), Agilent Sequence mapped Real Time RT-PCR Moderate agreement (1 colour better than 2 colour) Wang et al., 2006 Applied Biosystems, Agilent Sequence matched Real Time RT-PCR Agreement (BLAST) (1375 genes confirmed with RT-PCR) Kuo et al., 2006 Affymetrix, Amersham Probes sequence Real Rime RT-PCR Agreement (commercial better than in- *Lab-lab comparison Lab lab Mergen, ABI, Mergen ABI Custom cDNA MGH MWG Agilent, cDNA, MGH, MWG, Agilent matched within 1 exon house, 1-colour house 1 colour better than 2) added* Compugen, Operon (Unigene, LocusLink, RefSeq, Refseq exon) Green = correlation between platforms See Yauk et al. Nucleic Acids Research, 2004 yellow = moderate correlation between platforms red = poor correlation between platforms Yauk and Berndt, Environ Mol Mutagen 2007
  • 24.
    Healthy Environments andConsumer Safety Branch Obtaining useful information from a microarray experiment 1. Quality Control y 2. Remove probes in background. 3. Adjust (normalize) the measurements to facilitate comparisons. 4. Select genes that are differentially expressed between samples. l 5. Identify the biological processes and molecular functions that are altered altered. 6. Place data in the context of a health outcome.
  • 25.
    1. Quality HealthyEnvironments andGarbageBranch Garbage out Measures: Consumer Safety in, A. Sample and RNA Quality B. Array (slide) quality • Percentage of spots with no signal • Number of saturated spots • Intensity Distribution • Summary Measures of the negative control spots • Median Signal to Noise Ratio • M di Brightness Median B i ht • External Controls
  • 26.
    Example: Agilent QualityReports Healthy Environments and Consumer Safety Branch
  • 27.
    Healthy Environments andConsumer Safety Branch 2. Background noise: f l positives 2 B k d i false iti • Estimate the background? g Local Negative Control Spots g p Should we background subtract? • Limits of Detection, Presence/Absence Calls Flagging spots in the background gg g p g
  • 28.
    3. Normalization: Cross-slideConsumer Safety Branch and removing bias Healthy Environments and comparisons ntensities Raw relative in Normalized relativ intensities ve Array number
  • 29.
    Healthy Environments andConsumer Safety Branch 4. 4 Identify genes that are affected by the treatment • Fold change is not a statistical test • 50,000 comparisons on one chip – adjust for multiple comparisons • Levels of filtering to identify changing genes 1. Fold Change 2. T-tests/ANOVA 2 T t t /ANOVA 3. Permutation test a) MAANOVA b) Significance Analysis of Microarrays (SAM)
  • 30.
    Healthy Environments andConsumer Safety Branch 5. Identify biological processes/molecular functions/pathways that are altered and link to a potential health outcome BIOINFORMATICS Gene Ontology: a controlled vocabulary of terms for describing gene product characteristics and gene product annotation data Includes: cellular compartment biological function molecular process Pathway: collection of manually drawn pathway maps representing knowledge on the th molecular i t l l interaction and reaction networks ti d ti t k Looking for over-representation of changing genes within these groups.
  • 31.
    Example:Environments and ConsumerSafety Branch Healthy Kegg pathway for P53 signalling
  • 32.
    Healthy Environments andConsumer Safety Branch Designing an experiment to study mechanism of action 1. Adequate sample size! q p 2. Appropriate selection of time points (e.g., early, downstream, transformation, disease effects) 3. Appropriate selection of treatment conditions (non-toxic) 4. Appropriate tissue/cells sampled 5. Sample collection – randomization (time effects) 6. HIGH QUALITY RNA!!! 7. Randomization d i 7 R d i ti and microarray experimental d i i t l design 8. Implementation of QA/QC 9. Appropriate normalization and filtering 10. VALIDATION WITH ALTERNATIVE TECHNOLOGIES
  • 33.
    Healthy Environments andConsumer Safety Branch An example from our lab
  • 34.
    Toxicological Profiles ofCigarette Smoke Healthy Environments and Consumer Safety Branch Condensate C d t Use of high-density DNA microarrays to Investigate pathways induced by CSC exposure Correlation with other toxicity endpoints C l i ih h i i d i 5 cigarette brands: 1. Export A full flavour 2. 3. Gauloises Blonde 3 Gau o ses o de 3. Player’s Light King Size Carole Yauk and Paul White collaboration
  • 35.
    Healthy Environments andConsumer Safety Branch Cigarette smoke condensate collection and characterization Brand # of cigarettes Total TPM TPM/cig Smoked Yield(mg) 1 – Export A 60 1625.5 27.09 2 – Gauloises Blondes 108 1826.0 16.91 3 – Player’s Light King Size 117 1659.0 14.18
  • 36.
    Healthy Environments andConsumer Safety Branch Analyte Export A Gauloises Player’s Carcinogenicity Blonde Light g Tar (mg/cig) 15.6 12.9 12.4 NA Nicotine (mg/cig) 1.3 1.1 1.1 NA CO (mg/cig) ( g/ g) 14.0 13.6 12.7 NA Benzo[a]pyrene (ng/cig) 9 8 10 1 4-aminobiphenyl (ng/cig) 2 2 2 1 NNN (ng/cig) 37 178 25 1 NNK (ng/cig) 75 63 52 1 Cadmium (ng/cig) 90 47 90 1 Lead (ng/cig) NQ 19 NQ 2B Formaldehyde (μg/cig) 82 54 44 2A Acetaldehyde (μg/cig) 698 680 587 2B 1,3-butadiene 1 3 butadiene (μg/cig) 52 44 48 2A Isoprene (μg/cig) 276 376 301 2B Acrylonitrile (μg/cig) 11 12 10 2B Benzene (μg/cig) 49 43 49 1 Styrene (μg/cig) 14 10 10 2B
  • 37.
    Toxicity/genotoxicity Healthy Environments and Consumer Safety Branch Phenotypic anchoring and dose selection Toxicity – Cloning Efficiency in Muta™Mouse Lung Epithelial Cells y g y g p Mutagenicity – Mutations Salmonella typhimurium Mutagenicity – Mutations in Muta™Mouse Lung Epithelial Cells i it Micronuclei in M t ™M Clastogenicity – Mi Cl t l i i Muta Mouse L Lung E ith li l C ll Epithelial Cells Essential to select meaningful concentrations for microarray experiments The Muta™Mouse
  • 38.
    Healthy Environments andConsumer Safety Branch Toxicity Profiling Via Cloning Efficiency (LD50 Values Determined Using Probit Link Function) 120 100 LD 50 (µg/ml media) 80 60 40 20 0 Brand 1 Brand 2 Brand 3 Brand 4 Brand 5 E p Export A Player’s Special y p Gauloises Player’s Plain y Player’s Light y Lg Yauk et al., manuscript in preparation
  • 39.
    Mutagenicity in the Healthy Environments and Consumer Safety Branch Ames Assay 1.2 12 Export A Gauloises Player's King Mutagenic Pot. (rev/µg TPM) 1.0 0.8 0.6 P 0.4 M 0.2 0.0 TA98 YG1041 G YG5161 G Yauk et al., manuscript in preparation
  • 40.
    Healthy Environments andConsumer Safety Branch Cigarette smoke condensate does not induce DNA sequence mutations in the FE1 cell line Pilot Brand Pre- S9 Dose CSC Summary incubation ug/ml #1 Gauloises No 0 0, High Sp MF, No 20,40,60,80 response #2 Gauloises No 0.5% 0 5% 0, 0 High Sp MF, No MF 20,40,60,80 response #3 Export A Full 60min 0.5% 0, 60 Good Sp MF, No Flavor response #4 Export Full 15, 30, 0.5% 0,40,60,80,1 Good Sp MF, No Flavor 60min 00 response #5 Players Light 60 min 0.5% 0-150 No dose response #6 Gauloise 60 min 0.5,1,2,4% 100 No response #7 Players No 0,1,2,4 100,150,200 No dose Special response #8 Players Plain No No 20-120 No response
  • 41.
    Healthy Environments andConsumer Safety Branch Cytokinesis-Block Micronucleus Assay
  • 42.
    CBMN Assay inMuta™Mouse FE1 Cells Healthy Environments and Consumer Safety Branch Results for Player s Light Player’s 35.0 Total MN/500 cells *** ucleate Freq. (% ) MN Freq. (per 500 cells) ) 30.0 Binucleate Freq 0.80 25.0 ** * F 20.0 20 0 15.0 0.40 10.0 Binu F 5.0 0.0 0.00 0 60 90 120 0 Cigarette Smoke Condensate (µg/mL) *p<0.05, **p<0.01, ***p<0.001 Fisher’s Exact Test Yauk et al., manuscript in preparation
  • 43.
    Cigarette smoke condensateisSafety Branch Healthy Environments and Consumer clastogenic in mouse p pulmonary epithelial cells in vitro y p 45 DMSO 40 90 μg/mL *** 35 120 μg/mL ** 150 μg/mL ** ** Cells with MN per 1000 * 30 * 25 20 w 15 10 5 0 Export Gauloises Player's Yauk et al., manuscript in preparation
  • 44.
    Healthy Environments andConsumer Safety Branch TOXICOGENOMICS
  • 45.
    Healthy Environments andConsumer Safety Branch Final Decision for Design of Microarray Study 2 time points (early response/late response) Early = after 6hr exposure Late = after 4hr recovery (10hr total) 3 doses (control, low, high) Low = 45μg TPM/mL, High 90μg TPM/mL TPM/mL High= 5 replicates/dose (required to obtain statistical significance) Agilent 22k toxicology arrays g gy y
  • 46.
    Microarray Analyses –Main Experiment Healthy Environments and Consumer Safety Branch Generated 1,365,000 data points MAANOVA to Identify Significant Changes Clustering and pathway analyses Affected genes, biomarkers and brand-specific signatures
  • 47.
    Healthy Environments andConsumer Safety Branch Summary of gene expression findings 296 known genes were up- or down-regulated relative to solvent 54 down-regulated g 6 hours 115 genes 61 up-regulated 172 down-regulated 10 hours 254 genes 82 up-regulated Yauk et al., manuscript in preparation
  • 48.
    Summary of geneConsumerSafety Branch Healthy Environments and expression findings 6 hours 10 hours 45 ug/ml 90 ug/ml 45 ug/ml 90 ug/ml ↑ ↓ ↑ ↓ ↑ ↓ ↑ ↓ Export A 5 3 22 24 24 5 66 171 Gauloise 2 0 54 30 13 11 54 46 Player’s 4 12 37 42 8 7 82 103 Light Yauk et al., manuscript in preparation
  • 49.
    Large overlap amongthe brands Healthy Environments and Consumer Safety Branch e.g., 10 hours, 90 μg/ml Export A E t Player’s Li ht Pl ’ Light 8 93 2 87 49 3 2 Gauloises Yauk et al., manuscript in preparation
  • 50.
    Up-regulated in Exposed Down-regulated in Exposed Healthy Environments and Consumer Safety Branch (Higher in Dose 90) (Lower in Dose 90) aurora kinase A guanine nucleotide binding protein, b t 4 bi di t i beta cell division cycle 20 homolog sulfiredoxin 1 homolog cell division cycle 2 homolog A tetraspanin 33 cell di i i ll division cycle associated 5 l i t d DNA-damage inducible DEP domain containing 1B transcript 3 F-box only protein 5 serine peptidase inhibitor, clade E, , , histone 1, H1b member 1 inner centromere protein glutathione synthetase karyopherin ( p y p (importin) alpha 2 ) p zinc finger protein 330 polo-like kinase 1 cytochrome P450, family 1, subfamily b, protein regulator of cytokinesis polypeptide 1 1 Control Control 6 hours Export A 45 μg/ml 10 hours Gauloises Blonde 90 μg/ml Player’s light king size Yauk et al., manuscript in preparation
  • 51.
    10 hour GeneOntology Analysis Healthy Environments and Consumer Safety Branch Benjamini B j i i Benjamini p- B j i i Term p-value Term value cell division 0.000 p53 signaling 0.015 metabolic etabo c mitosis 0.000 processes 0.017 regulation of g cell cycle 0.000 cell death 0.019 cell cycle y DNA damage g process 0.000 response 0.027 regulation of cell division 0.000 0 000 apoptosis 0.047 mitosis 0.000 Yauk et al., manuscript in preparation
  • 52.
    Helping the people Aider les Canadiens et of Canada maintain and les Canadiennes à maintenir improve their health et à améliorer leur santé
  • 53.
    Dose Trends between6 and 10 hrs Healthy Environments and Consumer Safety Branch 77 genes decreasing tensity in expression with dose Normalized Int 6 hrs 10 hrs 66 genes increasing in expression with d ith dose N 6 hrs 10 hrs
  • 54.
    Screening in genetictoxicology Healthy Environments and Consumer Safety Branch 1 year yea 2 year yea Cancer Cost:$2M/cmpd 2 year rodent cancer bioassay Time: 3 years Mutation Cost: $60K/cmpd Dominant Lethal Test Time: 6-12 months } In vitro mammalian mutation Cost: $60K/cmpd In vivo mutation Time: 3 months Salmonella bacteria assays Genomics Cost: $10K/cmpd Gene expression analysis Time: 1 month HIGH CONTENT!
  • 55.
    Predictive toxicogenomics: Healthy Environments and Consumer Safety Branch medium throughput MOA analysis Ellinger-Ziegelbauer H, et al., Toxicology Letters 186 (2009) 36-44.
  • 56.
    Increasing number ofpapers analyzing gene expression to support Healthy Environments and Consumer Safety Branch observed endpoints: Focussed quantitative real-time PCR arrays y
  • 57.
    Healthy Environments andConsumer Safety Branch Concluding remarks on gene expression technologies • Technologies have come a long way over the past decade • Appropriate experimental design in combination with correct data handling generate reproducible and reliable data • Improved annotation and bioinformatics tools are leading to a better ability to interpret findings • Expression technologies are highly useful for: • The identification of mechanisms of action • Biomarker discovery • Exploring potentially novel health effects • Chemical categorization
  • 58.
    Healthy Environments andConsumer Safety Branch Needs for application to identify MOA • Identification and validation of adverse outcome genes/pathways (differentiating adaptive versus adverse effects) • Increasing the database of c e ca s a a y ed c eas g t e o chemicals analyzed • Identification of low-dose effects • Improved bioinformatics tools for data interpretation • Guidelines for use of expression data in regulatory assessments