Chemical (and other) stress in DEB3: the ‘target site’ and effects on survival

Tjalling Jager

Dept. Theoretical Biology

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

externalconcentration

(in time)

toxico-kineticmodel

toxico-kineticmodel

“Biology-based” modelling

internalconcentration

in time

process modelfor the organism

process modelfor the organism

effects onendpoints

in timetoxicokinetics

toxicodynamics

“Biology-based” modelling

internalconcentration

in time

process modelfor the organism

process modelfor the organism

effects onendpoints

in time

toxicodynamics

“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

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

DEBparameter

organism

DEBparameter

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

DEBparameter

organism ‘damage’or ‘receptor’

Receptors: AChE inhibition

Dose metric options

externalconcentration

(in time)

toxico-kinetics

toxico-kinetics (scaled)

internal conc.in time

DEBparameters

in time

bufferbufferstructurestructure

reservereserve

Dose metric options

externalconcentration

(in time)

toxico-kinetics

toxico-kinetics (scaled)

internal conc.in time

DEBparameters

in time

receptorkinetics

receptorkinetics

damagekinetics

damagekinetics

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 …

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

perf

orm

ance

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.

, m

aint

enan

ce r

ate

NEC

blank value

toler

ance

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)

Chance events in time

0

2

4

6

8

10

12

0 2 4 6 8time (days)

surv

ivin

g c

hic

ken

s

0 cars/hr10 cars/hr20 cars/hr50 cars/hr

Hazard rate is the ‘instantaneous probability’ to die by car encounter

Hazard rate increases with traffic

Simple survival model

c

on

ce

ntr

ati

on

external

internal

time

external concentrationover timetoxicokinetics

internal concentrationover time

toxic effect

scaled1-comp.

scaled1-comp.

internal concentrationover time

animal model

Simple survival model

scaled internal concentration

haza

rd r

ate

NEC

blank value

targetparameter

toxicokinetics

toxic effect

killin

g rate

Assumptions• no growth, no reproduction, constant reserve density …

Assumptions• no growth, no reproduction, constant reserve density …

In equations …

Hazard modelling

concentration

external

internal

external

internal

NEC

NEC

time

time

hazard rate

time

survival probability

time

time time

Minnow, hexachloroethane

0 1.33 1.84 3.32 5.81 9.25

0 20 20 20 20 20 20

24 20 20 20 20 20 4

48 20 20 20 20 15 0

72 20 20 19 20 12 0

96 20 20 19 20 10 0

concentration (μmol/L)

time

(h

our

)fathead minnow

Survival in time

0 20 40 60 80 1000

0.2

0.4

0.6

0.8

1

time (hours)

fra

cti

on

su

rviv

ing

01.331.843.325.819.25

conc. μmol/L

elimination rate 0.141 hr-1

NEC 5.54 (5.26-5.68) μmol/Lkilling rate 0.0408 L/μmol/hrblank hazard 0.000124 hr-1

Daphnia, nonylphenol

mg/L 0 h 24 h 48 h

0.004 20 20 20

0.032 20 20 20

0.056 20 20 20

0.100 20 20 20

0.180 20 20 16

0.320 20 13 2

0.560 20 2 0

Daphnia, nonylphenol

elimination rate 0.057 hr-1

NEC 0.14 (0.094-0.17) mg/Lkilling rate 0.66 L/mg/hrblank hazard 0 hr-1

0 10 20 30 40 500

0.2

0.4

0.6

0.8

1

time (hours)

frac

tio

n s

urv

ivin

g

0.0040.0320.0560.10.180.320.56

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 …

0 10 20 30 40 500

0.2

0.4

0.6

0.8

1

time (hours)

frac

tio

n s

urv

ivin

g

0.0040.0320.0560.10.180.320.56

0 10 20 30 40 500

0.2

0.4

0.6

0.8

1

time (hours)

frac

tio

n s

urv

ivin

g

0.0040.0320.0560.10.180.320.56

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!

Parameter covariation

10-4

10-2

100

102

10-4

10-2

100

102

104

NEC (mmol/L)

kil

lin

g r

ate

(L

/mm

ol/

h)

narcoticreactivenarcoticreactive

Jager and Kooijman, 2009

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 target‘narcotic’

reactive target‘reactive’

Process-based QSAR

-2 -1 0 1 2 3 4 5 610

-3

10-2

10-1

100

101

102

log Kow

elim

ina

tio

n r

ate

(1/

h)

narcoticreactivenarcoticreactive

Jager and Kooijman, 2009

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’

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 …

AA

BB

CC

DD

target

What is ageing?

0 20 40 60 80 100 1202.5

3

3.5

4

4.5

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5.5

6

6.5

7

time

bo

dy

le

ng

th

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lati

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off

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rin

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er f

em

ale

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1

time

frac

tio

n s

urv

ivin

g

Jager et al (2004)

What is ageing?

0 20 40 60 80 100 1202.5

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bo

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ng

th

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Jager et al (2004)

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

Ageing and ROS

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

Ageing in DEB3

Treated as a toxicant effect …

damage compoundsdamage compoundsdilution by growth

hazard ratehazard rate

amplification

dilution by growth

reserve mobilisationreserve mobilisation

damage-inducingcompunds

damage-inducingcompunds

free radicals

e.g., affected mitochondria

e.g., “wrong” proteins

There is good news and bad news …There is good news and bad news …

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

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

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Toxicants influence ageing

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volu

me

tric

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h (m

m)

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Folsomia candidaand cadmium (fit is not DEB3!)

Jager et al (2004)

time (days)0 20 40 60 80 100 120

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Toxicants influence ageing

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Acrobeloides nanusand carbendazim (not DEB3!)

Alda Álvarez et al (2006)

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

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