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

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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