A Reduced Model for Bioconcentration and Biotransformation of Neutral Organic Compounds in Midge

Abstract

A bioconcentration factor (BCF) database and a toxicokinetic model considering only biota-water partitioning and biotransformation were constructed for neutral organic chemicals in midge. The database contained quality-reviewed BCF and toxicokinetic data with variability constrained to within 0.5 to 1 log unit. Diverse conditions in exposure duration, flow setup , substrate presence, temperature, and taxonomic classification did not translate into substantial variability in BCF, uptake rate constant (k 1), or depuration rate constant (k T), and no systematic bias was observed in BCFs derived in unlabeled versus radiolabeled studies. Substance-specific biotransformation rate constants k M were derived by difference between the calculated biota-water partitioning coefficient (K BW) and experimental BCF for developing a midge biotransformation model. Experimental midge BCF was modeled as BCF = K BW /(1 + k M/ k 2) with log k M (k M in h-1) =-0.37 log K OW-0.06T (in K) + 18.87 (root mean square error [RMSE] = 0.60), log k 1 (k 1 in L kg wet.wt-1 h-1) =-0.0747 W (body weight in mg wet.wt) + 2.35 (RMSE = 0.48). The K BW value was estimated using midge biochemical composition and established polyparameter linear free energy relationships, and the diffusive elimination rate constant (k 2) was computed as k 2 = k 1 /K BW. The BCF model predicted >85% of BCFs that associated with neutral organic compounds (log K OW = 1.46-7.75) to within 1 log-unit error margin and had comparable accuracy similar to amphipod or fish models. A number of outliers and critical limitations of the k M model were identified and examined, and they largely reflected the inherent limitation of difference-derived k M , the lack of chemical diversity, and inadequate temperature variation in existing data. Future modeling efforts can benefit from more BCF and toxicokinetic observations of BCF on structurally diverse chemicals for model training, validation, and diagnosis.

Speed it up: How temperature drives toxicokinetics of organic contaminants in freshwater amphipods

“…The applicability of the Arrhenius relationship to other studies for ectotherms could not be tested, because either only two temperatures were studied, no toxicokinetic rates were modelled or no equilibrium conditions were confirmed (Brown et al, 2021 ; Buchwalter et al, 2003 ; Camp & Buchwalter, 2016 ; Cerveny et al, 2021 ; Geisler et al, 2012 ; Kuo & Chen, 2021 ; Muijs & Jonker, 2009 ; Nawaz & Kirk, 1996 ). The different experimental scopes and approaches may also be the reason for different reported relationships between temperature and BCF kin .…”

“…Systematic investigations on the impact of temperature on toxicokinetics, such as determination of toxicokinetic rates or assuring equilibrium conditions, are rare (Dai et al, 2021 ; Mangold‐Döring et al, 2022 ). Furthermore, contrasting results such as higher (Buchwalter et al, 2003 ; Camp & Buchwalter, 2016 ; Dai et al, 2021 ; Nawaz & Kirk, 1996 ) (caddisfly, stonefly, mayfly, earthworm, daphnids), indifferent (Cerveny et al, 2021 ; Kuo & Chen, 2021 ) (fish, midge) or lower (Brown et al, 2021 ; Muijs & Jonker, 2009 ) (frog, aquatic worm) internal contaminant concentrations at higher temperatures are reported in ectothermic aquatic organisms.…”

Determination of In Vivo Biotransformation Kinetics Using Early‐Time Biota Concentrations

“…Models for the uptake rate constant ( k 1 ) and k M of organic contaminants typically carry an RMSE ranging from 0.5 to 0.7 (Chen & Kuo, 2018; Kuo & Di Toro, 2013a, 2013b; US Environmental Protection Agency, 2012c) or an uncertainty of ±0.5–0.7 log unit (Brooke et al, 2012; US Environmental Protection Agency, 2012c). Well‐trained bioaccumulation models perform less well than the individual k models and usually have RMSE spanning from 0.7 to 0.8 (Chen & Kuo, 2018; Kuo & Chen, 2021; Kuo & Di Toro, 2013b; US Environmental Protection Agency, 2012c). Models of environmental partitioning of organic chemicals generally have better performance than those associated with bioaccumulation or toxicokinetic parameters, with RMSEs ranging from 0.4 to 0.7 being reported (Kipka & Di Toro, 2009, 2011a, 2011b; Kuo & Di Toro, 2013a, 2013b).…”

“…Analytical solutions for B PC and B MB were obtained assuming all toxicokinetic processes of a chemical may be adequately represented by first‐order kinetics. The first‐order toxicokinetic model underlies the interpretation and modeling of experimental bioconcentration and bioaccumulation of chemicals in various organisms (Barber, 2003, 2008; Chen & Kuo, 2018; Kuo & Chen, 2021; Kuo & Di Toro, 2013a). It has also been adopted in most of the experimental biotransformation studies (Ashauer et al, 2012; Carrasco‐Navarro et al, 2015; Rösch et al, 2016; Ruotsalainen et al, 2010; Schuler et al, 2003) and biotransformation kinetic modeling studies (Arnot et al, 2008a; Kuo & Chen, 2016; Kuo & Di Toro, 2013b).…”

“…van der Linde et al ( 2001) estimated k M as the difference between the total depuration rate constant and the contributions of all nontransformative dissipation processes in selected animal species. This approach was later applied to fish (Arnot et al, 2008a), amphipods (Chen & Kuo, 2018), and midges (Kuo & Chen, 2021) to estimate the k M values of organic chemicals. However, the difference method is an indirect method-it relies on measurements or model estimates of rate constants, rather than utilizing first-hand observations.…”