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Chemical (and other) stress in DEB 3: the ‘target site’ and effects on survival

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.: A A A A A A A A A. Contents. Toxicodynamics About ‘targets’ and the ‘dose metric’

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Chemical (and other) stress in DEB 3: the ‘target site’ and effects on survival

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  1. Chemical (and other) stress in DEB3: 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.: AAAAAAAAA

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

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

  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. organism toxicant target site DEB parameter DEB parameter 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 ...

  7. ‘damage’ or ‘receptor’ 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?? organism toxicant DEB parameter

  8. Receptors: AChE inhibition

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

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

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

  13. Link dose metric to parameter NEC e.g., maintenance rate blank value e.g., scaled internal concentration tolerance 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

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

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

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

  18. In equations …

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

  20. Minnow, hexachloroethane concentration (μmol/L) fathead minnow time (hour)

  21. Survival in time 1 elimination rate 0.141 hr-1 NEC 5.54 (5.26-5.68) μmol/L killing rate 0.0408 L/μmol/hr blank hazard 0.000124 hr-1 0.8 conc. μmol/L 0.6 fraction surviving 0 1.33 0.4 1.84 3.32 5.81 0.2 9.25 0 0 20 40 60 80 100 time (hours)

  22. Daphnia, nonylphenol

  23. 1 0.8 0.6 fraction surviving 0.004 0.032 0.4 0.056 0.1 0.18 0.2 0.32 0.56 0 0 10 20 30 40 50 time (hours) Daphnia, nonylphenol elimination rate 0.057 hr-1 NEC 0.14 (0.094-0.17) mg/L killing rate 0.66 L/mg/hr blank hazard 0 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 PVd and efficiency of target interaction ‘narcotic’ narcotic target ‘reactive’ reactive target

  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’ narcotic target ‘reactive’ reactive target

  30. B A C D 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 … target

  31. 400 350 7 300 6.5 250 cumulative offspring per female 6 200 5.5 150 5 body length 100 4.5 50 4 0 3.5 0 10 20 30 40 50 3 1 2.5 0 20 40 60 80 100 120 time 0.8 0.6 fraction surviving 0.4 0.2 0 0 10 20 30 40 50 time What is ageing? Jager et al (2004)

  32. 3000 2500 7 2000 6.5 cumulative offspring per female 6 1500 5.5 1000 5 body length 4.5 500 4 0 0 20 40 60 80 100 120 3.5 3 2.5 1 0 20 40 60 80 100 120 time 0.8 0.6 fraction surviving 0.4 0.2 0 0 20 40 60 80 100 120 time What is ageing? 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. reserve mobilisation amplification free radicals damage-inducing compunds damage compounds dilution by growth hazard rate dilution by growth Ageing in DEB3 • Treated as a toxicant effect … There is good news and bad news … e.g., affected mitochondria e.g., “wrong” proteins

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

  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

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