Analysis of tox & deg data

Analysis of tox & deg data Bas Kooijman Dept theoretical biology Vrije Universiteit Amsterdam Bas@bio.vu.nl http://www.bio.vu.nl/thb Maarssen, 2004/10/21

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

Dynamic Energy Budget theory for metabolic organization • 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

Space-time scales Each process has its characteristic domain of space-time scales system earth space ecosystem population 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 individual cell time molecule

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

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

Electronic DEB laboratory http://www.bio.vu.nl/thb/deb/deblab/ (free download site) 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

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

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

Toxic effect on survival Effect of Dieldrin on survival of Poecilia One-compartment kinetics Hazard rate is linear in internal concentration killing rate 0.038 l g-1 d-1 elimination rate 0.712 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 weight1/3, mg1/3 time, d CuCl2 mg/kg 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 g Cd/l 0 0.2 0.4 cum. # young/female 0.8 1 2 Effect on hazard NEC = 0.023 g Cd/l time, d

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

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

Maintenance first 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 143 - 164 30106 cells.day-1 400 Maitenance requirements: 6 cells.sec-1.daphnid-1 300 300 number of daphnids max number of daphnids 200 200 100 100 106 cells.day-1 0 0 6 12 30 60 120 8 11 15 18 21 24 28 32 35 37 30 time, d

Food intake at carrying capacity metavanadate sodium bromide 2,6-dimethylquinoline 103 cells/daphnid.d log mg Br/l log mg DMQ/l log mg V/l potassium dichromate colchicine 9-aminoacridine 103 cells/daphnid.d log mg AA/l log mg Col/l log mg K2Cr2O7/l

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 Streptococcus bovis, Russell & Baldwin (1979) Marr-Pirt (no reserve) DEB 1/yield, mmol glucose/ mg cells spec growth rate yield 1/spec growth rate, 1/h 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 • 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 rF • << suspension growth rate r • (upto factor 1000) • 2 extra parameters: • size at which floc destabilizes • penetration rate of substrate into floc Brandt & Kooijman 2000 Two parameters account for the flocculated growth of microbes in biodegradation assays. Biotech & Bioeng70: 677-684

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, 4843-4854

Diauxic growth Adaptation to different substrates is controlled by: enzyme turnover 0.15 h-1 preference ratio 0.5 acetate cells Substrate conc., mM biomass conc., OD433 oxalate time, h Growth of acetate-adapted Pseudomonas oxalaticus OX1 data from Dijkhuizen et al 1980 SU-based DEB curves fitted by Bernd Brandt Brandt et al, 2004 Water Research 38, 1003-1013

Netherlands Center for Environmental Modeling Bas Kooijman VUA • Members NCEM: http://www.ncem.nl • 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 Dik van de Meent RUN + RIVM Bilthoven 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 partnerswho 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 clientswho 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

Permanent foundation staff members 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

Estimated financial costs Yearly costs in k-euro:salary 80% 69 = 86.25  0.8auditor 1room(14m2) 4exploitation 10total 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/ (1 - 0.19) 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

Analysis of tox & deg data