Correspondence/Rebuttal pubs.acs.org/est
Response to Comment on “Assessing Aromatic-Hydrocarbon Toxicity to Fish Early Life Stages Using Passive-Dosing Methods and Target-Lipid and Chemical-Activity Models”
W
polyaromatic hydrocarbons),7 adjusted values are increased and thus plot higher than activities calculated from the unadjusted LC50s. The rationale for applying adjusted LC50s in our analysis was 2-fold. First, use of adjusted values were used in regression analysis so that CTLBB estimates could be derived in a manner consistent with previous work8−11 to allow comparison of the relative sensitivity to other test species. In this analysis we assumed a constant slope of −0.94 in accordance with eq 1. The actual slopes obtained by regressing the adjusted 2 and 5 day LC50 values were −1.02 ± 0.02 (n = 4, r2 = 0.998, p = 0.0005) and −1.13 ± 0.14 (n = 6, r2 = 0.939, p = 0.001), respectively. While the slope derived from the 2 day tests is slightly lower than assumed, the slope obtained for the 5 day LC50s is not significantly different from the universal TLM estimate of −0.94 derived from analysis of an extensive data set.7 Further, the Δc accounts for differential partitioning of certain chemical classes to target lipid, the assumed site of action.6 Therefore, calculation of activity on adjusted effect levels is assumed to more accurately represent the activity of the chemicals in the target lipids. Second, since we wanted to compare our toxicity data to literature data encompassing a broader domain of substances beyond aromatic hydrocarbons (i.e., aliphatic hydrocarbons, ketones, ethers and alcohols, aliphatic halogens, monoaromatic hydrocarbons, monoaromatic halogens, polyaromatic hydrocarbons) with variable correction factors (see Table S7 from ref 2) plotting adjusted LC50 values provided a convenient normalization procedure to facilitate graphical display of toxicity data across test substances consistent with earlier studies that have applied the TLM framework.8−11 However, we included unadjusted values in either the main body or in the Supporting Information of our paper so interested readers could evaluate our study independently as nicely illustrated by Mayer and Schmidt.1 Another important issue that these authors raise is the assumed relationship between the log subcooled aqueous solubility and the Log Kow which has the form:
e appreciate the thoughtful review and constructive comments provided by Mayer and Schmidt1 on our 2 study. These authors compliment the well-controlled exposures delivered in exposing embryo-larval stages of zebrafish to aromatic hydrocarbons using passive dosing and conclude our toxicity results are in agreement with previous literature. However, the authors have questioned the subsequent data analysis applied to compare the target lipid model (TLM) and chemical activity (CA) paradigms to inform toxicity prediction. The authors raise concern that our analysis might be misconstrued to conclude that observed acute toxicity occurs within a higher CA range than previously reported. Further, the authors question the relationships between empirical toxicity and subcooled liquid solubility with log Kow are correct and resulting implications regarding a toxicity cutoff. The authors highlight two possible reasons to help account for these apparent inconsistencies. First, it is suggested that toxicity tests associated with shorter durations may be confounded by bioconcentration kinetics that preclude equilibrium thereby inflating effect concentrations and associated CA. However, bioconcentration studies using zebrafish embryos with several aromatic hydrocarbons suggest equilibrium is achieved within 2 days 3 . Nevertheless, regressions of 2 and 5d LC50s reported in Table 1 of our paper with log Kow suggest greater deviations between these relationships with increasing hydrophobicity. Further, for the most hydrophobic PAH tested for which a 5 day acute LC50 could be derived (pyrene), 0 and 40% lethality were observed at the highest dose after 2 and 4 day exposures, respectively, see Table S5 from ref 2. One hypothesis to explain the continuation of time-dependent toxicity despite likely achievement of equilibrium is the increasing metabolic capability by the embryo which appears to increase with hydrophobicity.3−5 The potential formation of metabolites may contribute to observed acute effects. While we concur that exposure duration is important, we accounted for this variable in analysis by presenting 2 day and 4−5 day tests from our study and the literature, separately, c.f., Figure 2a and b in ref 2. Second, the authors point out that we plotted TLM-adjusted rather than actual LC50s which increased CAs corresponding to acute effects. As outlined in ref 2, the TLM describes the relationship between acute toxicity and the octanol−water partition coefficient by log LC50 = log(CTLBB) − 0.94logK ow + Δc
logSL = A − BlogK ow
where SL is given in units of mmol/L. We elected to use the coefficients reported by ref 12 (A = 3.54, B = 1.10) since this relationship was derived using mostly aromatic hydrocarbons and SPARC log Kow values consistent with the TLM formulation. However, such relationships are most reliable when developed using a homologous series of substances. Based on a critical review, Mackay13 proposes A = 4.1 and B = 1.25 as generic parameters for more hydrophobic chemicals. The fact that the slope term is less than unity suggests that the activity coefficient increases and corresponding solubility in
(1)
where the CTLBB corresponds to the critical body burden (umol/g octanol) and the Δc term corresponds to an empirically derived chemical class-specific correction factor that accounts for partitioning differences between octanol and target lipid.6Adjusted LC50 values were obtained by subtracting the correction term from the observed LC50 value. Since Δc is negative (−0.109 for monoaromatic hydrocarbons, −0.352 for © XXXX American Chemical Society
(4)
A
DOI: 10.1021/acs.est.7b00384 Environ. Sci. Technol. XXXX, XXX, XXX−XXX
Environmental Science & Technology
Correspondence/Rebuttal
(6) Kipka, U.; DiToro, D. M. Technical Basis for Polar and Nonpolar Narcotic Chemicals and Polycyclic Aromatic Hydrocarbon Criteria: III. A Polyparamter Model for Target Lipid Partitioning. Environ. Toxicol. Chem. 2009, 28, 1429−1438. (7) McGrath, J. A.; Di Toro, D. M. Validation of the target lipid model for toxicity assessment of residual petroleum constituents: Monocyclic and polycyclic aromatic hydrocarbons. Environ. Toxicol. Chem. 2009, 28 (6), 1130−1148. (8) Di Toro, D. M.; McGrath, J. A.; Hansen, D. J. Technical basis for narcotic chemicals and polycyclic aromatic hydrocarbon criteria. I. Water and tissue. Environ. Toxicol. Chem. 2000, 19, 1951−1970. (9) McGrath, J. A.; Parkerton, T. F.; Di Toro, D. M. Application of the narcosis target lipid model to algal toxicity and deriving predicted no effect concentrations. Environ. Toxicol. Chem. 2004, 23, 2503− 2517. (10) Redman, A. J.; McGrath, T.; Parkerton, E.; Febbo, D.; Letinski, D.; Winkelmann, D.; DiToro. Application of the Target Lipid Model for Deriving Predicted No Effect Concentrations for Wastewater Organisms. Environ. Toxicol. Chem. 2007, 26, 102−112. (11) Redman, A. D.; Parkerton, T. F.; Paumen, M. L.; McGrath, J. A.; Di Toro, D. M. Extension and validation of the target lipid model for deriving predicted no effect concentrations for soils and sediments. Environ. Toxicol. Chem. 2104, 33, 2679−2687. (12) Di Toro, D. M.; McGrath, J. A.; Stubblefield, W. A. Predicting the toxicity of neat and weathered crude oil: toxic potential and the toxicity of saturated mixtures. Environ. Toxicol. Chem. 2007, 26 (1), 24−36. (13) Mackay, D. Solubility in Water. In Handbook of Property Estimation Methods for Chemicals: Environmental Health Sciences, Chapter 7; Edit Mackay, Boethling, RS, Eds.; CRC Press, 2000; pp 125−139.
octanol decreases with increasing log Kow. The standard error associated with predictions from this equation was reported to be 0.3 log units so this equation is expected to provide order of magnitude estimates. This uncertainty impacts the potential range of CA where effects are observed. A more generic form of the equation presented in ref 2 linking the CA and TLM frameworks is log LA50 = log(CTLBB) + (0.94 − B)logK ow − A + Δc (5)
Thus, characterizing toxicity in terms of CA depends on both the organism, CTLBB as well as the substance defined by the magnitude of A/B, log Kow and the chemical class correction. Since the TLM explicitly attempts to quantify the contribution of both organism and substance-dependent components of observed toxicity, this framework affords more tailored toxicity predictions and offers insights for advancing and interpreting effects data using CA as the exposure metric.
Josh D. Butler*,† Thomas F. Parkerton‡ Aaron D. Redman† Daniel J. Letinski† Keith R. Cooper§
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† Toxicology & Environmental Sciences Division, ExxonMobil Biomedical Sciences, Inc. 1545 US Highway 22 East, Annandale, New Jersey 08801-3059, United States ‡ Toxicology & Environmental Sciences Division, ExxonMobil Biomedical Sciences, Inc., 800 Bell Street, Houston, Texas 77002, United States § Environmental Sciences Department, Rutgers University 14 College Farm Rd. New Brunswick, New Jersey 08901, United States
AUTHOR INFORMATION
Corresponding Author
*Phone: 980-730-1003; e-mail:
[email protected]. ORCID
Josh D. Butler: 0000-0003-0112-135X Notes
The authors declare no competing financial interest.
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REFERENCES
(1) Mayer, P., Schmidt, S. Comment on “Assessing AromaticHydrocarbon Toxicity to Fish Early Life Stages Using Passive-Dosing Methods and Target-Lipid and Chemical-Activity Models, Environ. Sci. Technol.2017, DOI: 10.1021/acs.est.6b06416. (2) Butler, J. D.; Parkerton, T. F.; Redman, A. D.; Letinski, D. J.; Cooper, K. R. Assessing Aromatic-Hydrocarbon Toxicity to Fish Early Life Stages Using Passive-Dosing Methods and Target- Lipid and Chemical- Activity Models. Environ. Sci. Technol. 2016, 50, 8305− 8315. (3) Kuhnert, A. V.; Altenburger, C; Küster, E. A. The internal concentration of organic substances in fish embryos - a toxicokinetic approach. Environ. Toxicol. Chem. 2013, 32 (8), 1819−1827. (4) Nichols, J. W.; Hoffman, A. D.; ter Laak, T. L.; Fitzsimmons, P. N. Hepatic clearance of 6 Polycyclic Aromatic Hydrocarbons by Isolated Perfused Trout Livers: Prediction From In Vitro Clearance by Liver S9 Fractions. Toxicol. Sci. 2013, 136 (2), 359−372. (5) Matthew, R.; Mcgrath, J. A.; DiToro, D. M. Modeling Polycyclic Aromatic Hydrocarbon Bioaccumulation and Metabolism in TimeVariable Early Life Stage Exposures. Environ. Toxicol. Chem. 2008, 27 (7), 1515−1525. B
DOI: 10.1021/acs.est.7b00384 Environ. Sci. Technol. XXXX, XXX, XXX−XXX
