Analysis of tox & deg data Bas Kooijman Dept theoretical biology Vrije Universiteit Amsterdam Maarssen, 2004/10/21

Contents Introduction DEB theory DEB laboratory Effects of toxicants sublethal effects tumour induction & growth lethal effects extrapolation Biodegradation microbial flocs co-metabolism adaptation Foundation Biomass imbedding modes of operation Maarssen, 2004/10/21

Dynamic Energy Budget theory links levels of organization molecules, cells, individuals, populations, ecosystems scales in space and time: scale separation interplay between biology, mathematics, physics, chemistry, earth system sciences framework of general systems theory quantitative; first principles only equivalent of theoretical physics fundamental to biology; many practical applications (bio)production, medicine, (eco)toxicity, climate change for metabolic organization

molecule cell individual population ecosystem system earth time space Space-time scales When changing the space-time scale, new processes will become important other will become less important Individuals are special because of straightforward energy/mass balances Each process has its characteristic domain of space-time scales

Some DEB pillars life cycle perspective of individual as primary target embryo, juvenile, adult (levels in metabolic organization) life as coupled chemical transformations (reserve & structure) time, energy & mass balances surface area/ volume relationships (spatial structure & transport) homeostasis (stoichiometric constraints via Synthesizing Units) syntrophy (basis for symbioses, evolutionary perspective) intensive/extensive parameters: body size scaling

1-  maturity maintenance maturity offspring maturation reproduction Basic DEB scheme foodfaeces assimilation reserve feeding defecation structure somatic maintenance growth 

Electronic DEB laboratory DEBtool for research applications open source (Octave, Matlab) covers full range of DEB research (fundamental + applied) advanced regression routines for simultaneous model fitting DEBtox for routine ecotoxicity applications load module (free download site)

DEBtox Present tasks: analysis of bioassays on survival, body growth, reproduction, population growth NEC (including profile likelihood), ECx-time curves OECD/ISO report on analysis of toxicity data NOEC methods: not recommended, for historic continuity only ECx methods: fixed exposure times only, descriptive Biology-based methods: DEBtox; process-based OECD-meeting Braunschweig 1996: stimulate exposure-explicit regression methods DEBtox: only exposure time-explicit method presently available Near-future extensions: biodegradation models, multi-sample analysis, population consequences profile likelihoods for more parameters (elimination rate, toxicity parameters) Future extensions: more bioassays, sensitivity-variations, ecosystem effects, predictions based on physical chemistry mixture toxicity, coupling to exposure models, implementation in environmental risk assessment

Concentration ranges of chemicals too little def: variations in concentration come with variations in effects enough def: variations in concentration within this range hardly affect physiological behaviour of individuals too much def: variations in concentration come with variations in effects e.g. water concentration can be too much even for fish no basic difference between toxic and non-toxic chemicals “too little” and “enough” can have zero range for some chemicals Implication: lower & upper NEC for each compound

Effects on organisms Process-based perspective on disturbances chemicals, temperature, parasites, noise exposure-time explicit methods (response surface) Primary target: individuals some effects at sub-organism level can be compensated (NEC) Effects on populations derived from individuals energy budget basic to population dynamics Parameters of budget model individual specific and (partly) under genetic control

Models for toxic effects Three model components: kinetics external concentration  internal concentration example: one-compartment kinetics change in target parameter(s) internal concentration  value of target parameter(s) example: linear relationship physiology value of parameter  endpoint (survival, reproduction) example: DEB model

1-  maturity maintenance maturity offspring maturation reproduction Modes of action of toxicants foodfaeces assimilation reserve feeding defecation structure somatic maintenance growth    assimilation   maintenance costs   growth costs   reproduction costs   hazard to embryo uu tumour maint tumour induction 6 6 endocr. disruption 7 7 lethal effects: hazard rate Mode of action affects translation to pop level 8

Toxic effect on survival Effect of Dieldrin on survival of Poecilia One-compartment kinetics Hazard rate is linear in internal concentration killing rate l  g -1 d -1 elimination rate d -1 NEC 4.49  g l -1

DEB-based effects on body growth Indirect effects indicator: effects on ultimate size at constant food decrease of assimilation rate (food intake, digestion) increase of specific maintenance costs Direct effects indicator: no effects on ultimate size at constant food increase of costs for synthesis of biomass (structural)

Effect on assimilation CuCl 2 mg/kgtime, d weight 1/3, mg 1/3 Data from Klok & de Roos 1996 NEC = 4.45 mg CuCl2 /kg on Lumbricus rubellus

DEB-based effects on reproduction Indirect effects indicator: effects on onset of reproduction decrease of assimilation rate (food intake, digestion) increase of specific maintenance costs increase of costs for synthesis of biomass (structural) Direct effects indicator: no effects on onset of reproduction increase of costs for the synthesis of offspring decrease of survival probability at birth

Direct effect on reproduction time, d cum. # young/female  g Cd/l Effect on hazard NEC =  g Cd/l

Effects on populations At constant food density: At variable food density: individual-based modelling of populations requires modelling of resources

Population effects can depend on food density Population growth of rotifer Brachionus rubens at 20˚C for different algal concentrations 3,4-dichloroaniline direct effect on reproduction potassium metavanadate effect on maintenance

0 number of daphnids Maintenance first 10 6 cells.day max number of daphnids time, d 30  10 6 cells.day -1 Chlorella-fed batch cultures of Daphnia magna, 20°C neonates at 0 d: 10 winter eggs at 37 d: 0, 0, 1, 3, 1, 38 Kooijman, 1985 Toxicity at population level. In: Cairns, J. (ed) Multispecies toxicity testing. Pergamon Press, New York, pp Maitenance requirements: 6 cells.sec -1.daphnid -1

Food intake at carrying capacity 10 3 cells/daphnid.d log mg V/l log mg Br/llog mg DMQ/l log mg K 2 Cr 2 O 7 /l log mg AA/llog mg Col/l 9-aminoacridine colchicine 2,6-dimethylquinoline sodium bromidemetavanadate potassium dichromate

Advantages of DEBtox method effective use of all data smaller number of parameters per data-point reduction of required test animals simultaneous use of data on multiple end points more informative standard statistics (NOEC, ECx, slope) can be calculated from new ones (NEC, tolerance conc., elimination rate), but not vice versa process-based characterizations of effect independent of exposure time allows NEC estimates for risk assessments to replace NOEC tight link of toxicity with pharmacology/physiology/ecology extrapolations are facilitated acute  chronic; individual  population; lab  field one species  other species; one chemical  other chemicals

Biodegradation Uptake of substrates is core-element of DEB theory Special issues microbes typically grow in flocs this limits access to substrate by several orders of magnitude adaptation to new substrates short term: by expression of genes for this substrate long term: by change in species-composition co-metabolism uptake of new substrate can depend on that of other substrates co-limitation (e.g. by nutrients such as N-compounds) this is a core-element of DEB theory

Yield vs growth 1/spec growth rate, 1/h 1/yield, mmol glucose/ mg cells Streptococcus bovis, Russell & Baldwin (1979) Marr-Pirt (no reserve) DEB spec growth rate yield Russell & Cook (1995): this is evidence for down-regulation of maintenance at low growth rates DEB theory: high reserve density gives high growth rates structure requires maintenance, reserves not

Growth of microbial flocs Brandt & Kooijman 2000 Two parameters account for the flocculated growth of microbes in biodegradation assays. Biotech & Bioeng 70: Microbes in sewage treatment plants grow in flocs < 10% of microbes is metabolic active Growth limited by transport of substrate into the floc core starves to death substrate  living + dead biomass (detritus) flocculated growth rate r F << suspension growth rate r (upto factor 1000) 2 extra parameters: size at which floc destabilizes penetration rate of substrate into floc

Co-metabolism Co-metabolic degradation of 3-chloroaniline by Rhodococcus with glucose as primary substrate Data from Schukat et al, 1983 Brandt et al, 2003 Water Research 37,

Diauxic growth time, h biomass conc., OD 433 acetate oxalate Substrate conc., mM Growth of acetate-adapted Pseudomonas oxalaticus OX1 data from Dijkhuizen et al 1980 SU-based DEB curves fitted by Bernd Brandt Adaptation to different substrates is controlled by: enzyme turnover 0.15 h -1 preference ratio 0.5 cells Brandt et al, 2004 Water Research 38,

Members NCEM : Foundation for Biomathematical Assessments Biomass (Vrije Universiteit, Amsterdam) effects of toxicants on organisms, bio-degradation Radboud Center for Environmental Modelling RCEM (Radboud Univ. Nijmegen) emission, transport & transformation of chemicals Dept Indust. Ecol.; Inst. Environ. Sciences IE-MCL (Leiden University) life-cycle studies for chemicals and products Aims: collaboration coordinated research acquisition Netherlands Center for Environmental Modeling Dik van de Meent RUN + RIVM Bilthoven Bas Kooijman VUA Gjalt Huppes LU

Aims of Biomass stimulation interaction between dept Theoretical Biology (TB-VU), and companies, governmental institutions modelling, data analysis, computational sciences, advice on setup of experiments offering talented scientists opportunities to contribute in this interaction stimulate talented students to specialize in research areas of the foundation development of applications of Dynamic Energy Budget (DEB) theory: ecotoxicology, risk assessment, nutrition, medical biology and biotechnology organizing specialized courses research areas of foundation, application of math. & computer science in biology

Modes of operation person-oriented research acquisition partners hire scientists on part-time basis (restrictions on info-flux) employed by & detached at the foundation (Amsterdam) partner controls work package for specified amount of time project-oriented research acquisition clients sponsor projects by PhD students or postdocs who are part-time (80%) employed by VU (NOW, STW, EU projects) temporarily supplemented by the foundation on project basis support for selected students financial support for explicit commitments excellent study results (full focus on study) specialization in mathematical biology information supply: courses generation of resources, stimulation of research

Benefits for partners who support foundation staff hire highly skilled modelers on part-time basis and use them for data analysis, advice on experimental research benefit from a team that supports these specialists in fundamental research, data analysis, statistics, computer science contact & train talented students via traineeships who may become future employees access to & influence on new developments in DEB applications & fundamental research that generates these applications

Benefits for clients who sponsor projects solve a particular problem using knowledge of experts who are supported by TB-VU and foundation staff and who participate in the Netherlands Center for Environmental Modeling and have assistance from students with traineeships get into contact with talented young scientists and students who may become future employees

First permanent staff member: Tjalling Jager (0.8 fte) he has developed EUSES at RIVM Analysis of ecotoxicity & biodegradation data, such as those from standardized tests (ISO/OECD) toxico-kinetic & effect data Prediction of transport & fate of chemicals in the environment possible effect scenarios in collaboration with RCEM in NCEM life cycle studies in collaboration with IE-CML in NCEM Aim: second permanent staff member in same field Future developments: food production/conservation, biotechnology Permanent foundation staff members

Yearly costs in k-euro: salary 80% 69 =  0.8 auditor 1 room(14m 2 ) 4 exploitation 10 total 84 faculty 9% financial admin 4% computer service 3% personnel service 1% general 1% (incl use library) guidance by TB-VU staff 10% total 19% 104 = 84/ ( ) Estimated financial costs Yearly effective hours: 1280 = 1600  0.8 background research 50% contracted = 640 h/a costs per hour (excl vat): 104/ 640 = 163 euro/h 2 partners = 320 h/partner = 52 k-euro/(partner  a) Yearly index 3% PM: liability insurance