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UNDERSTANDING HOMEOSTATIC CONTROL & ADAPTIVE RESPONSES TO LOW DOSES OF OXIDATIVE COMPOUNDS.

SARAH COOPER

SAFETY & ENVIRONMENTAL ASSURANCE CENTRE

NRF2 IN REDOX BIOLOGY (SOT 2016) – WEDNESDAY 16TH MARCH

OXIDATIVE STRESS CASE STUDY

• Determining the tipping-point when homeostatic regulatory mechanisms

become saturated and shift from an adaptive to an adverse state is critical to define regions of safety for chemical exposure.

• Oxidative stress and the role of the Nrf2 pathway in cellular defences is

used as a case study to develop these approaches to enable the progression of risk assessment through mechanistic understanding of human relevant systems.

HIGH CONTENT IN VITRO ASSAY DATA

TEMPORAL ALTERATION IN NRF2 SIGNALLING RESPONSE

0 uM 1 uM 10 uM 1.78 uM 3.16 uM 5.62 uM 17.8 uM 31.6 uM 56.2 uM6 100 uM 178 uM 562 uM 1000 uM 316 uM

The data highlights a temporal alteration in Nrf2 signaling response, moving from a low dose transient perturbation to a longer lasting activation state at higher doses. Suggests that tipping-point from adaptive to adverse could be defined based on the dose-dependent dynamics of cellular repair and recovery.

• B. van de Water

SYSTEMS BIOLOGY MODEL OF OXIDATIVE STRESS

1) FULL MECHANISTIC MODEL:

Model initially tuned with public domain data available in the literature. Aim to get a ‘complete’ set of data for a range of biomarkers in HepG2 cells for 19 compounds

Current aim is to see whether model can recapitulate the data:

SYSTEMS BIOLOGY MODEL OF OXIDATIVE STRESS

2) SIMPLIFIED MECHANISTIC MODEL:

5 variables (NRF2, KEAP1, GSH, ROS & SRXN1) and 30 parameters representing:

• Association and dissociation rates
• Translation rates
• Transcription rates
• Turnover/removal rates
• Concentration thresholds

TRANSLATION OF IN VITRO DATA TO HUMAN IN VIVO RELEVANCE

Idea of the human in vivo normal / homeostatic range. Distributions in levels of relevant biomarkers (e.g. GSH & MDA) following exercise have been taken from literature and analyzed:

SUMMARY

• Determination of the tipping-point is driven by a weight of evidence

– i.e. where we predict that the repair capacity of the system has been overloaded in relation to the relevant exposure scenarios for use.

• To aid the translation of in vitro data for human in vivo relevance we

need to compare the adaptive capacity/homeostatic range for the same biomarkers in humans.

• Examining where models may help to predict the effects of chronic

repeat doses & whether biomarkers stay in the homeostatic range – need to decide how complex the model needs to be.

ACKNOWLEDGEMENTS

Unilever

• Maja Aleksic
• Paul Carmichael
• Kristina Castle
• Carol Courage
• Sue Edwards
• Stephen Glavin
• Gaurav Jain
• Penny Jones
• Jin Li
• Alistair Middleton
• Jia Shao
• Jayasujatha Vethamanickam
• Sam Windebank
• Andrew White

Leiden University

• Bob van de Water
• Stephen Winks

Hamner Institutes

• Melvin Andersen
• Rebecca Clewell
• Bo-wen Huang
• Bin Sun

Strand Life Sciences

• Kas Subramanian
• Nalini R
• Narashima MK
• Sonali Das