Biomarkers in Action
Examining the Effects of DormantSeason Pesticide Runoff on Resident
Fish Species
><> Andrew Whitehead <><
UC Davis, Bodega Marine Laboratory
Talk Overview:
Biomarkers:
• Definition
• Traits
• Advantages / Strengths
• Drawbacks / Difficulties
Biomarkers in Action: Pesticides Project
• Goals
• Experimental Design
• Data
Biomarkers: Definition
Physiological / biochemical response of an organism that is
mechanistically / functionally related to xenobiotic exposure
Principle:
Xenobiotics interact with molecular targets
through defined biochemical pathways which result in
predictable physiological effects
Definition (cont.)
Biomarkers of Exposure:
Biomarkers of Effect:
- induction of accommodation
responses
• metallothionein induction
• P450 induction
• DNA adducts
• heat shock protein induction
• increase in plasma cortisol levels
• induction of immune system
• measurement of metabolites
• serum leukocyte levels, antibody
production
- exposure has exceeded
organism’s ability to accommodate
• tissue necrosis
• DNA mutations
• AChE inhibition
• developmental abnormalities
• eggshell thinning
• demasculinization, feminization
• neoplasia, tumor formation
Biomarkers: Traits
• Variability
• Sensitivity
• Selectivity
• Clarity of Interpretation
• Biological Significance
• Duration of Response
• Ease of use, Cost, Labor
Biomarkers vs. Other Approaches
H2O Chemistry Monitoring:
 Unequivocal demonstration of presence/absence
 Snapshot in time/space, partitioning, exposure pathways, linkage
to biological responses...
Body Burden Analysis:
 Multiple exposure pathways
 Metabolism, sequestration
Bioassays:
 Biological consequences
 Lab setting, standard test species
Biomarkers: Advantages/Strengths
• “So What?”
• Linking Exposure to Effects
• Integrated Information
- Spatial
- Temporal
- Additive effects
• Lab and Field experiments
• Resident / Native organisms
• Complex Field Evaluations: “Do Contaminants Play a Role?”
Biomarkers: Drawbacks/Difficulties
• Interpretation
- Inferring causes
- Scaling to meaningful effects
- Timecourse of response
• Understanding components of variation
• Choice of biomarkers: What to measure?
- Use tiered approach
- Use other tools (chemistry) to focus choice
Examining the Effects of DormantSeason Pesticide Runoff on Resident
Fish Species
PI:
Dr. Susan Anderson – UC Davis, Bodega Marine Laboratory
Coinvestigators:
Dr. Bernie May – UC Davis
Dr. Kathryn Kuivila – USGS
Dr. David Hinton – Duke U
Dr. Barry Wilson – UC Davis
Graduate Student:
Andrew Whitehead – UC Davis, Bodega Marine Laboratory
Funding: EPA Star Grant, 1998
Project Goals:
Overall: Examine biological effects of landscape-scale pesticide
contamination on native fish at the individual and population
levels.
Characterize Exposure:
• GIS mapping of pesticide use databases
• Water chemistry
Examine Effects on Individuals:
• Acetylcholinesterase (AChE) inhibition assay
• DNA strand break (comet) assay
Examine Effects on Populations:
• DNA fingerprinting / population genetic analysis using AFLP and
microsatellites
Experimental Design: Exposure
Field-Caging Approach:
• Cage suckers at 1 reference, 2 impacted sites
• Retrieve cages at multiple timepoints, in order to:
A) Capture pesticide peak
B) Examine recovery time
 Environmentally realistic
Risky, chance of catastrophe
 Water and sediment exposure
Lab Exposure to Field-collected water approach:
• collect field water in SS milk cans, transport to BML, expose fish - 6 d.
 Safe back-up
Less environmentally realistic
 Can examine more sites
Minimal sediment exposure
Field Caging Design
Cage 1
OUT
3 Cages IN
River Flow
Cage 2
OUT
Cage 3
OUT
Rain
Rain
11
12
13
14
15 16 17 18 19
Date (February, 2000)
20
21
22
23
San Joaquin River
@ Vernalis
Orestimba Creek @ River Road
Orestimba Creek @ Orestimba Road
Lab Exposure Design
• Composite samples collected in 35-L stainless steel milk cans
• 6-day laboratory exposure to Sacramento sucker
• Multiple tissues excised and archived for biomarker analysis
(Brain, muscle, liver, gill, blood)
Sites:
• Feather R. upstream of ag.
• Feather R. downstream
• Orestimba Ck. upstream
• Orestimba Ck. downstream
• San Joaquin R. downstream
• Laboratory control
Experimental Design: Effects
AChE Activity:
• Indicator of exposure to and/or effects from specific class of
xenobiotics with same mechanism of action
= Organophosphate and carbamate pesticides
DNA Strand Breaks: Comet Assay
• Indicator of exposure to and/or effects from variety of stressors.
= dormant-spray pesticides?
Mutagenicity: Ames Assay
Cytochrome P450 Activity
DATA: AChE Activity - Field
300
San Joaquin R.
120
250
100
200
80
150
60
100
40
50
20
0
OP Pesticide Concentration (ng/L)
Brain Acetylcholinesterase Activity
(umol/min/g wet wt)
140
0
2/11/00
2/13/00
2/15/00
2/17/00
2/19/00
2/21/00
2/23/00
Date Sampled
SJ AChE Activity
OU AChE Activity (Ref)
Diazinon + Methidathion Concentration
DATA: AChE Activity - Lab
60
120
50
100
40
80
30
60
20
40
10
20
0
OP Pesticide Concentration (ng/L)
Brain Acetylcholinesterase
Activity (umol/min/g wet wt)
140
0
CON
OU
SJ
FU
FD
Water Source
AChE Activity
Diazinon + Methidathion Concentration
DATA: DNA Strand Breaks - Field
300
San Joaquin R.
50
250
40
200
30
150
20
100
10
50
0
0
2/11/00
2/13/00
2/15/00
2/17/00
2/19/00
2/21/00
Date Sampled
SJ DNA Strand Breaks
Diazinon + Methidathion Concentration
OU DNA Strand Breaks (Ref)
2/23/00
OP Pesticide Concentration
(ng/L)
Index of DNA Strand Breaks
(%DNA in Comet Tail)
60
50.0
200
45.0
180
40.0
160
35.0
140
30.0
120
25.0
100
20.0
80
15.0
60
10.0
40
5.0
20
0.0
0
OU
OD
OP Pesticide Concentration (ng/L)
Index of DNA Strand Breaks
(%DNA in Comet Tail)
DATA: DNA Strand Breaks - Lab
SJ
Water Source
DNA Strand Breaks
Diazinon + Methidathion Concentration
Summary: Project
Suite of indicators, coupled with chemistry, has been a strong approach
for assessing effects in the field, and in lab, on relevant species
AChE Data:
- As hypothesized, dormant-season pesticides are affecting resident fish
- Would not have expected effects based on chemistry alone
DNA Strand Break Data:
- Indicates importance of chemicals other than pesticides
Ongoing/Future Work:
- Other indicators: Mutagenicity assay, P450 activity, more chemistry
- Population genetic approach
Overall Summary
For simple problems, use simple tools
Complex problems demand more sophisticated approaches
Biomarker information
• “So What?”
• Focus - what are the real problems?
• Integrated information
• Relevant organisms
• Field and lab evaluations
A Day in the Life...
4X4?
Catch anything?
Speed, anyone?
Hmm...
Population-Level
Biomarker Approach
Working H: Long-term exposure to contaminants can alter gene pools
of exposed populations.
Rationale: Population genetic structure = historical record
• Record of environmental influences on previous generations
Challenges:
• Distinguish natural variation from induced genetic change (field design)
• Step from correlation to attribution (test for mechanisms)
Hypotheses of Mechanisms that may Drive Pop’n Genetic Change:
A) Natural Selection: Loss of sensitive individuals
B) Mutation: Accumulation of rare mutations over generations
C) Random Genetic Drift: Bottleneck Erosion of genetic diversity