deciphering multiple stressor effects of gamma radiation
TRANSCRIPT
Deciphering multiple stressor effects of
gamma radiation and uranium on Atlantic
salmon (Salmo salar):
Transcriptomics-based mixture modeling
Y. Song, J. Asselman, K.A.C. De Schamphelaere, B. Salbu, and K.E. Tollefsen
Norwegian Institute for Water Research
Multiple stressors: The reality!
Organics
Metals
Radionuclides Radiations
Physical conditions
Other organisms
Prediction of combined effect
Assumption: Additive
Model prediction: Single vs Combined
No deviation
Additivity (1+1=2)
Synergism (1+1>2)
Deviation
Antagonism (1+1<2)
Concentration addition (CA)
Similar mode of action and target
Independent action (IA)
Dissimilar modes of action and targets
Survival Growth
Reproduction
Multi-bio-level assessment of combined effect
Adverse Outcome Pathway (AOP)
Can we better understand the combined
effect based on the OMICS data?
(Altenburger et al., 2012 Environ. Sci. Technol.)
Case study: Combined effect of uranium &
gamma radiation on Atlantic salmon
Gamma radiation
Depleted U
Antioxidant defense
DNA damage & repair
Apoptosis
Protein degradation
Macromolecule oxidation/peroxidation
Oxidative stress
Ionization Excitation
H2O
Damage > repair
Compromised energetics
Inflammation Tissue damage
Aging Death
Causality ?
H2O2
Reactive oxygen species (ROS)
Fenton-type reaction
H2O
•O2−
•OH
Exposure and hepatic transcriptomic analysis
(0.25 mg/L) (70 mGy)
(48h exposure)
Transcriptomic analysis (Microarray)
Liver
RNA
Qualitative assessment (mode of action comparison)
Novel data analysis strategies
Transcriptomic analysis
Normalized expression
Stressor A Stressor B
Mixture modeling (IA)
Predicted (Stressor A+B)
Observed (Stressor A+B)
Deviation test
Gene set (Synergistic)
Gene set (Additive)
Gene set (Antagonistic)
Stressor A Stressor B Stressor A+B
Statistical analysis
DEGs (Stressor A)
DEGs (Stressor B)
DEGs (Stressor A+B)
DEGs (Synergistic)
DEGs (Additive)
DEGs (Antagonistic)
Non DEGs
Functional analysis
Phenotypic anchoring
Synergistic hazard?
Qu
alit
ati
ve c
om
pa
riso
n Q
ua
ntita
tive assessm
ent
Statistical analysis
Statistical analysis
Gene set classification (Venn diagram etc.)
Toxicity pathway identification
Adverse outcome pathway
Stressor A+B
Cumulative risk?
qPCR verification
Combined effect on gene expression
Differentially expressed genes due to interactive effects
Synergy: 323 genes Antagony: 14 genes
Differentially expressed genes due
to additive effects
Functional analysis of genes (pathways)
•Antigen Presentation Pathway •Apoptosis Signaling •Calcium-induced T Lymphocyte Apoptosis •DNA Methylation and Transcriptional Repression Signaling •Mitochondrial Dysfunction •NRF2-mediated Oxidative Stress Response •Oxidative Phosphorylation •PPARα/RXRα Activation •Protein Ubiquitination Pathway •Superoxide Radicals Degradation •Xenobiotic Metabolism Signaling
•Fatty Acid β-oxidation III •p53 Signaling •GADD45 Signaling •SAPK/JNK Signaling •Sumoylation Pathway •ATM Signaling
•Role of BRCA1 in DNA Damage Response
•B Cell Receptor Signaling •Molecular Mechanisms of Cancer •IL-8 Signaling
Additive Synergistic
Antagonistic
+
DNA damage (?) Mutation (?) Tumorigenesis
(↑?Synergistic?)
Mutation (?) Epigenetic
dysregulation (?)
myc (↑Synergistic)
p53 (↓?Synergistic?)
gadd45 (↓Synergistic)
cdk inhibitor (↓Synergisti
c)
cdk (↑Synergistic)
DNA repair (↓?)
Apoptosis (↓?) Cell cycle progression (↑
Synergistic?)
Cancer signaling (↑ Synergistic?)
prdx (↑Synergistic)
ROS(↑)
Nucleus
Cell cycle arrest (↓Synergistic?) Activation
Inhibition ↑ Induction ↓ Suppression ? Hypothetical response
Identification of synergistic toxicity pathway
Summary
• Potential interactive effects of gamma and uranium identified at the molecular level
• A toxicity pathway leading to tumorigenesis potentially synergized due to interactive effect
• A conceptual quantitative approach proposed for better understanding of synergy using OMICS
• Future: AOP-assisted cumulative hazard assessment
Stressor Molucular initiating
event
Key molecular
cellular event(s)
Key tissue organ
event(s)
Adverse outcome (Indiv.)
Adverse outcome (Popul.)
Acknowledgement
Thank you!
Funding:
• Norwegian Research Council, Project No. 223268/F50 Centre of Excellence (CoE) • Norwegian Research Council, Project No. 178621 MixTox
People:
• Tore Høgåsen • Karina Petersen • Eivind Farmen • Hans Christian Teien • Lene Sørlie Heier • Ole Christian Lind • Lindis Skipperud • Deborah Oughton • Tove Loftaas • Marit Nandrup • Merethe Kleiven
NMBU NIVA
Web:
• http://www.niva.no/cerad • https://www.nmbu.no/en/services/centers/cerad