Toxicogenomic Assessment of Estrogenic
Endocrine Disruptors: Effects of Ethynyl
Estradiol on Gene Expression
Tim Zacharewski
Department of Biochemistry & Molecular Biology
Institute For Environmental Toxicology and
The National Food Safety &Toxicology Center
Michigan State University
tel: (517) 355-1607
fax: (517) 353-9334
e-mail: tzachare@pilot.msu.edu
http://www.bch.msu.edu/~zacharet
Research Program Supported by:
National Institutes of Health
US Environmental Protection Agency
American Chemistry Council
Endocrine Disruptor: Definition
An endocrine disruptor is an exogenous
substance that causes adverse health effects
in an intact organism, or its progeny,
secondary to changes in endocrine function.
Endocrine Disruption - Issues
Human Concerns
-
increased incidence of hormone-dependent cancers
impaired cognitive abilities
compromised fertility
increased incidence of reproductive tract abnormalities
Wildlife Concerns
-
intersex
abnormal reproductive behavior
increased incidence of developmental abnormalities
compromised reproductive fitness
U.S. LEGISLATION
- Food Quality Protection Act (FQPA)
- Safe Drinking Water Act (SDWA)
Develop screening tests for chemicals that mimic
estrogen, androgen and thyroid by August 1998 and
implement program by August 1999
Includes effects on humans and wildlife
U.S. Environmental Protection Agency
Endocrine Disruptor Screening Program
http://www.epa.gov/oscpmont/oscpendo/index.htm
Initial Sorting
Priority Setting
Tier 1 Screening
Tier 2 Testing
Endocrine Disruptor Screening Program
Initial Sorting - 87,000 chemicals
- 900 pesticide active ingredients
- 2,500 other pesticide formulate ingredients
- 75,500 industrial chemicals
- 8,000 cosmetics, food additives and nutritional supplements
Priority Setting
- based on:
- production volume, environmental persistence, exposure
- quantitative structure activity relationships (QSARs)
- high throughput prescreening assays
: competitive ligand binding
: reporter gene induction
Structural Diversity of Estrogenic Endocrine Disruptors
Pharmaceuticals
Ethynyl Estradiol OH
C CH
Industrial Chemicals
OH
H3CO
OCH3
Methoxychlor
CCl3
HC
H3C 3 CH3
HO
CH3
HO
Diethylstilbestrol (DES)
Environmental Pollutants
o,p' -DDT
4-t -Octylphenol HO
Phytoestrogens/Natural Products
HO
Cl
Zearalenone
O
Cl
Clx
3
2
2`
3`
1`
4
4`
1
5
6
6`
Cly
HO
CCl3
HO
O
5`
Polychlorinated Biphenyl
(PCB)
CH3
O
HO
O
O
Genistein
OH
Proposed Mechanism of Action of
Estrogen Receptors
L
L
ER
hsp90
ER*L
ER*L
EREs
hsp90
transcriptional effects
protein level changes
PLEIOTROPIC RESPONSE
Other Possible Actions of Estrogenic Endocrine Disruptors
Estrogenic
Endocrine
Disrupting
Chemical
Binding
Globulin
Extracellular
Membrane
Bound
Estrogen
Receptor
Binding
Globulin
Receptor
Intracellular
Oxidative
Metabolism
Kinase
New
Ligands
Transcription
Factors
Receptors
Gene
Expression
Protein
Cellular
Effects
Tissue Effects
The Emerging Paradigm
In order to fully assess the risk of chronic
and subchronic exposure to synthetic
chemicals and natural products, a more
comprehensive understanding of the
physiological, cellular and molecular effects
is required within the context of the whole
organism, its genome, transcriptome,
proteome and metabonome.
Data Integration Across Biological Levels
Biological Networks
- depicts interactions between
gene, protein and metabolite
levels
- regulation distributed over all
levels
- each level can influence the other
- network provides molecular
basis for phenotype
From Brazhnik et al, Trends Biotechnol, 2002
Translational Toxicogenomic Research
Integration of global assessment technologies into
environmental health and drug development.
-
Used to rank and prioritize drug candidates/chemicals for
further development/testing
-
Earlier incorporation of toxicology in drug development
pipeline
-
Identification of biomarkers for exposure and clinical
trail monitoring
Toxicology
Comprehensive
Safety Assessment
Strategy:
correlate molecular
changes to observed
effects in order to
enhance predictive
accuracy
Tissue
Cell
Metabolome
Proteome
Transcriptome
Genome
Ethynyl Estradiol Induction of
Global Gene Expression
Study Design
harvest
tissue
hrs
0 2
8
12
24
48
vehicle
+/estrogen
•
•
•
•
•
ovx immature C57BL/6 mice
0.1 mg/kg EE or with vehicle (sesame oil) by gavage
uteri, liver, bone and mammary gland were harvested
uteri - Affymetrix Mu11KSubA GeneChips
liver, bone, mammary gland – cDNA microarray
72
Ethynyl Estradiol Induction of
Uterine Global Gene Expression
• Uterus
• Affymetrix Mu11KSubA GeneChip
Data Analysis Approach
6523
Probe sets on Mu11KSubA GeneChip
Screen 1: Nonparametric empirical Bayes
881
Significant time and/or treatment effect
Screen 2: ANOVA
392
Significant treatment or treatment*time effect
k-means clustering; Annotation: UniGene
268
Genes (not unknown ESTs)
Annotation: Gene Ontology
263
Physiological/Toxicological interpretation
Used gene ontology and RefSeq annotation to link
transcriptional and physiologic changes
Affymetrix GeneChip
Affymetrix GeneChips:
Photolithographic Synthesis of GeneChips
Lamp
Mask
http://www.affymetrix.com
GeneChip
GeneChip Expression Tiling Array Design
Gene
Sequence
5´
3´
Multiple
oligo probes
Perfect Match
Mismatch
Perfect match
Mismatch
A-C-T-G-T-T-T-A-C-G-C-T-C-A-G-T-C-G-G-G-T-C-A-A-T
A-C-T-G-T-T-T-A-C-G-C-T-A-A-G-T-C-G-G-G-T-C-A-A-T
GeneChip Expression Analysis
Hybridization and Staining
Array
Hybridized Array
cRNA Target
Streptravidinphycoerythrin
conjugate
Microarray Data Management, Analysis, and Storage
Modular Architecture of dbZach
(http://dbZach.fst.msu.edu)
Under Development:
- Promoter Subsystem
- Pathway Subsystem
- Toxicology Subsystem
- Real-Time PCR
Subsystem
- Sample Annotation
Subsystem
- Gene Annotation Tool
- Correlation Tool
- QA/QC monitoring
- Feature Inspection Tool
1
0.8
0.7
0.6
p1z
Verification
by QRT-PCR
0.9
0.5
0.4
0.3
0.2
0.1
0
1
•
•
•
•
•
2
3
4
5
6
7
8
9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26
26 known genes selected based on p1z value
Pearson correlations were calculated
profiles for 23/26 genes exhibited strong correlation
profiles for 2/26 exhibited marginal correlation
profile for 1/26 genes did not correlate
K-Means Clustering
7 K-means clusters
General response
1.
2.
3.
Confirm previously
reported estrogenregulated gene
responses
4.
5.
6.
7.
Describe new
estrogen-regulated
gene responses and
hypothesize about
specific mechanisms
Summary: Temporal Trends
0
4
8
12
16
20
24 .
.
.
Increased dry
mass, hyperplasia
Water
imbibition
Cell cycle
G1/S
DNA synthesis
(d)NTPs
RNA/protein
synthesis
Immune
S
G2/M
dNDPs
dNTP recycling
RNAPol; polyA-BP;
tRNA-synth.; eIFs
+/- migration and cytokine signaling suppressors
- protectin (inhibits complement-mediated lysis)
Energy
3x24 hr
ATP
Solute/ water
transport
complement
components
ATP transport
Cl- transport
polyamine
depletion
Sat
3x24 hr
Arginine/Ornithine Utilization
Abp1
3x24 hr
tissue
proliferation
polyamines
Myc/Max
Odc
8-24 hr
-neg
Oaz2
2-3x24 hr
-neg
-neg
Mxi1
8-24hr
Oazi
N.D.
ornithine
-neg
Arg1
3x24 hr
Rars
8-12 hr
proteins
Pdi2
3x24 hr
citrulline
-neg
arginine
Nos3
2-8 hr
nitric oxide
vasodilation, immune stimulation,
inhibition of smooth muscle cell growth
polyamine
depletion
Sat
3x24 hr
2-24 hr Following EE Exposure
Abp1
3x24 hr
tissue
proliferation
polyamines
Myc/Max
Odc
8-24 hr
-neg
Oaz2
2-3x24 hr
-neg
-neg
Mxi1
8-24hr
Oazi
N.D.
ornithine
-neg
Arg1
3x24 hr
Rars
8-12 hr
proteins
Pdi2
3x24 hr
citrulline
-neg
arginine
Nos3
2-8 hr
nitric oxide
vasodilation, immune stimulation,
inhibition of smooth muscle cell growth
polyamine
depletion
Sat
3x24 hr
3x24 hr Following EE Exposure
Abp1
3x24 hr
tissue
proliferation
polyamines
Myc/Max
Odc
8-24 hr
-neg
Oaz2
2-3x24 hr
-neg
-neg
Mxi1
8-24hr
Oazi
N.D.
ornithine
-neg
Arg1
3x24 hr
Rars
8-12 hr
proteins
Pdi2
3x24 hr
citrulline
-neg
arginine
Nos3
2-8 hr
nitric oxide
vasodilation, immune stimulation,
inhibition of smooth muscle cell growth
Ethynyl Estradiol Induction of
Hepatic Global Gene Expression
• Liver
• cDNA/EST microarray
Construction and Use of cDNA Arrays
cDNA clones in bacteria
plasmid DNA
PCR
tissue/cells
purified PCR product
total RNA
agarose gel analysis
array production
informatics db
probe hybridization
signal detection
data analysis
probe generation by
RT labeling
Gene Expression Analysis Using cDNA Microarrays
Control
Treated
RNA Isolation
Cy3
Reverse
Transcription
Cy5
Mix cDNAs and
Apply to µArray
cDNA µArray
Hybridize Under
Coverslip
Scan
Current and Future cDNA/EST Arrays
Includes ESTs with >70% similarity
Mus musculus:
Homo sapiens:
3636
VAI 40K
dbZach
dbZach
10656
6432
1162
UniGene build: 154
2625
3472
NIA 15K
Affy subset
Lion Biosciences
UniGene build: 113
Rattus norvegicus:
Lion Biosciences
5801
STRATEGY:
UniGene build: 106
Orthologs represented on each array in order
to examine in vitro and in vivo extrapolation between species
Ethynyl Estradiol Induction of
Hepatic Global Gene Expression
Summary
• growth and proliferation
• cytoskeleton and extracellular matrix
• monoxygenases, antioxidants
• glutathoine transferases
• lipid metabolism and transport
Hepatic vs. Uterine Global Gene Expression
Liver
Uterus
(cDNA/EST microarray)
(Affymetric Mu11KSubA GeneChip)
2,258 unique genes
5,543 unique genes
2,150 genes with
LocusLink
5,543 genes with
LocusLink
1,318 genes with
common LocusLink
979 genes exhibit
significant change in
expression in at least one
tissue
286 genes
exhibited significant
change in both
tissues
693 genes
exhibited significant
change in only
one tissue
•
264 genes only
expressed in liver
•
429 genes only
expressed in uterus
Other Global Gene Expression Comparisons
Uterus vs. Liver vs. Mammary Gland vs. Bone
- no common ethynyl estradiol elicited gene expression
profile
- significant differences in gene expression profile kinetics
that can not be explained by metabolism
Mouse Hep1c1c7 cells vs. Mouse Liver
- only 10% overlap in ethynyl estradiol elicited gene
expression profiles
Summary
Ethynyl estradiol gene expression profile overlap between
tissues and in vitro vs. in vivo models is minimal
Examination of pathways and elucidation of mechanisms
will identify biomarkers with greater predictive value
e.g. Arginase 1 indicates attenuation of proliferation
Several anomalous and absent responses were observed
suggesting estrogen receptor-independent mechanisms
and post-transcriptional activities
Predictive ability of in vitro screens to identify endocrine
disruptors with in vivo activity is questionable
Future Directions
Complementary “omic” technologies
e.g. proteomics, metabonomics
Phenotypic anchoring
e.g. in situ hybridization, immunohistochemistry, histology,
clinical chemistry, toxicology
Mechanisms/Pathway Discovery
e.g. ChIP on Chip, reverse engineering, support vector machines
Computational Biology
e.g. PBPK, network elucidation, computational modeling
Risk Assessment
Systems
Toxicology
The iterative development of computational models that
integrate disparate biological (DNA, RNA, protein, protein
interactions, biomodules, cells, tissues, etc.), chemical, and
toxicological data which can be used to further elucidate
the mechanisms of toxicity of a substance as well as
support risk assessment.
Acknowledgements
Chris Gennings
Virginia Commonwealth University
Jennette Eckel
Mayo Clinic
Molecular & Genomic Toxicology Lab
TOXICOGENOMICS
Research Associate, Post Doctoral Fellow and
Graduate Student Positions Available
Positions available to investigate:
1. Gene expression profiles for estrogenic and dioxin-like
chemicals and mixtures using human, rat and mouse
in vitro and in vivo models
2. Develop bioinformatic and computational resources
(e.g. relational database, analysis tools, modeling) in
support of toxicology studies
Further information regarding research activities
in the laboratory is available at www.bch.msu.edu/~zacharet
Toxicogenomic Positions cont’d
These are multifaceted position that will require a highly motivated and
well organized individual with excellent writing and verbal communication
skills. Knowledge of molecular biology and/or biochemistry is essential.
Experience with animal handling, statistical analysis, genomics,
bioinformatics, computer programming and database management is
highly desirable. Competitive salary, including benefits, will be based on
training and experience.
Interested individuals are requested to submit a cover letter outlining
their research experience, career aspirations, a curriculum vitae and copies
of relevant reprints to:
Tim Zacharewski, PhD,
Michigan State University
Department of Biochemistry & Molecular Biology
223 Biochemistry Building, Wilson Road
East Lansing, Michigan 48824-1319 USA
Tel: (517) 355-1607
Fax: (517) 353-9334
E-mail: tzachare@pilot.msu.edu