1. Chemical (and other) stress in DEB 3: the ‘target site’ and effects on survival Tjalling Jager Dept. Theoretical Biology TexPoint fonts used in EMF. Read the TexPoint manual before you delete this box.: AAA A AA A A A

2. Contents Toxicodynamics  About ‘targets’ and the ‘dose metric’ how to link internal concentrations to DEB  Effects on survival in a very simple setup (no growth)  Ageing affects survival

3. external concentration (in time) toxico-kinetic model toxico-kinetic model “Biology-based” modelling internal concentration in time process model for the organism process model for the organism effects on endpoints in time toxicokinetics toxicodynamics

4. “Biology-based” modelling internal concentration in time process model for the organism process model for the organism effects on endpoints in time toxicodynamics

5. “Mechanism of action”  Toxicants have different ‘molecular targets’: narcosis or ‘baseline toxicity’ (cell membranes) uncoupling (mitochondria) reactivity (macro molecules) AChE inhibition (nerve transmission)... Start a bit more general...  Effects on life-history traits must be reflected in a change in one or more DEB parameters

6. Targets link to parameters Assumption internal toxicant affects a target site target is linked to one or more DEB parameters  If interaction with target is fast and reversible... target sitetoxicant DEB parameter organism DEB parameter

7. Targets link to parameters  Model for target site dynamics ‘damage’ stage (Lee et al, 2002, Ashauer et al, 2007) receptor kinetics with limited number of receptors (Jager & Kooijman, 2005)  What if we used the scaled internal concentration?? toxicant DEB parameter organism ‘damage’ or ‘receptor’

8. Receptors: AChE inhibition

9. Dose metric options external concentration (in time) toxico- kinetics toxico- kinetics (scaled) internal conc. in time DEB parameters in time buffer structure reserve

10. Dose metric options external concentration (in time) toxico- kinetics toxico- kinetics (scaled) internal conc. in time DEB parameters in time receptor kinetics receptor kinetics receptor occupation in time damage kinetics damage kinetics damage density in time

11. Selecting a dose metric  The appropriate dose metric depends on … the nature of the target site species and chemical dependant  What about measured body residues? always good to have more information... whole-body residue may not represent ‘target site’...  Advice: start with a scaled TK model …

12. Link dose metric to parameter Assumptions low levels of the dose metric have no effect on the DEB parameter (NEC) internal concentration too muchoktoo little performance

13. Link dose metric to parameter Assumptions low levels of the dose metric have no effect on the DEB parameter (NEC) above the NEC, value of DEB parameter is linearly related to the dose metric e.g., scaled internal concentration e.g., maintenance rate NEC blank value tolerance

14. Survival  Why does an organism die? this is a rather complex question... Assumption death can be treated as a chance event in time chemical exposure increases probability to die Popular alternative individuals differ in their threshold for effects immediate and certain death above threshold  Can we have combinations? yes, see GUTS (Jager et al, acc. ES&T)

15. Chance events in time 0 2 4 6 8 10 12 02468 time (days) surviving chickens 0 cars/hr 10 cars/hr 20 cars/hr 50 cars/hr Hazard rate is the ‘instantaneous probability’ to die by car encounter Hazard rate increases with traffic

16. Simple survival model concentration external internal time external concentration over time toxicokinetics internal concentration over time toxic effect scaled 1-comp. scaled 1-comp.

17. internal concentration over time animal model Simple survival model scaled internal concentration hazard rate NEC blank value target parameter toxicokinetics toxic effect killing rate Assumptions no growth, no reproduction, constant reserve density …

18. In equations …

19. Hazard modelling concentration external internal external internal NEC time hazard rate time survival probability time

20. Minnow, hexachloroethane 01.331.843.325.819.25 020 2420 4 4820 150 7220 1920120 9620 1920100 concentration (μmol/L) time (hour) fathead minnow

21. Survival in time 020406080100 0 0.2 0.4 0.6 0.8 1 time (hours) fraction surviving 0 1.33 1.84 3.32 5.81 9.25 conc. μmol/L elimination rate0.141 hr -1 NEC 5.54 (5.26-5.68) μmol/L killing rate 0.0408 L/μmol/hr blank hazard0.000124 hr -1

22. Daphnia, nonylphenol mg/L0 h24 h48 h 0.00420 0.03220 0.05620 0.10020 0.18020 16 0.32020132 0.5602020

23. Daphnia, nonylphenol elimination rate0.057 hr -1 NEC 0.14 (0.094-0.17) mg/L killing rate 0.66 L/mg/hr blank hazard0 hr -1

24. Summary survival model  Based on hazard modelling simple method for chance events in time linked to simple TK model DEB-content is very limited!  Resulting parameters are time-independent have biological/toxicological meaning  Helps to understand toxicity e.g., why juveniles often have lower LC50 patterns in parameter values across chemicals …

25. Fathead minnow database In the 1980’s...  University of Wisconsin-Superior Brooke et al (1984) Geiger et al (1985, 1986, 1988, 1990)  What’s special? large number of chemicals measured exposure raw data in reports!

26. Parameter covariation Jager and Kooijman, 2009

27. Why slope of -1? Assumption hazard rate is determined by occupation of a target site  At this target, there is 1 NEC and 1 killing rate variation follows from P Vd and efficiency of target interaction narcotic target‘narcotic’ reactive target‘reactive’

28. Process-based QSAR Jager and Kooijman, 2009

29. Why difference in elimination?  Using the scaled TK model... elimination rate is based on effects over time elimination rate represents slowest process in the chain narcotic target‘narcotic’ reactive target‘reactive’

30. Why so much noise?  Measurements errors of exposure concentration  Biological variation in animals  Death is assumed to be stochastic …  Fish biotransform many compounds … metabolites have different targets, elimination rates, …  Assumed mechanism is too simple … A B C D target

31. What is ageing? 020406080100120 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 time body length 01020304050 0 100 150 200 250 300 350 400 cumulative offspring per female 01020304050 0 0.2 0.4 0.6 0.8 1 time fraction surviving Jager et al (2004)

32. What is ageing? 020406080100120 2.5 3 3.5 4 4.5 5 5.5 6 6.5 7 time body length 020406080100120 0 500 1000 1500 2000 2500 3000 cumulative offspring per female 020406080100120 0 0.2 0.4 0.6 0.8 1 time fraction surviving Jager et al (2004)

33. Old-age effects  With increasing age... survival probability decreases feeding rates often decrease reproduction rates decrease...  ‘DEB3’ offers a model (currently survival only) observed: caloric restriction increases lifespan model links ageing to respiration via ROS

34. Ageing and ROS Weindruch R 1996 Caloric restriction and aging. Scientific American 231, 46-52.

35. Ageing in DEB3  Treated as a toxicant effect … damage compounds dilution by growth hazard rate amplification dilution by growth reserve mobilisation damage-inducing compunds damage-inducing compunds free radicals e.g., affected mitochondria e.g., “wrong” proteins There is good news and bad news …

36. Example: guppies caloric restriction Kooijman, 2010 Implicit assumptions there is no “repair” of damage (inducing) compounds there is no threshold for effects on the hazard rate

37. Ageing effects on repro?  Still to be investigated in detail!  Observations: reproduction rate declines with old age feeding rates decline with old age body size does not change (much) with old age

38. Toxicants influence ageing Folsomia candida and cadmium (fit is not DEB3!) Jager et al (2004) time (days)

39. Toxicants influence ageing Acrobeloides nanus and carbendazim (not DEB3!) Alda Álvarez et al (2006)

40. Open questions  How to explain increased longevity in e.g., Folsomia? less growth means decreased production of damage but, counteracted by decrease in growth dilution …  How to explain changes in reproduction? should be linked to survival in some way... link through decrease in feeding?  Further work is needed! re-analysis of existing data sets dedicated testing, e.g., full life cycle at different food levels

41. Summarising  Internal concentration affects one (or more) DEB parameter(s) through a ‘target’  Start by using scaled internal concentration ‘elimination’ rate does not necessarily reflect kinetics of whole-body residue  One target parameter is the hazard rate in case of non-growing organisms and short tests, model becomes extremely simple  Ageing affects hazard rate ROS as byproduct of metabolism; 2-stage ‘damage’ model