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1,3-Butadiene (BD), a rodent carcinogen, is metabolized to mutagenic and DNA-reactive epoxides. In vitro data suggest that this oxidation is mediated by cytochrome P450 2E1 (CYP2E1). In this study, we tested the hypothesis that oxidation of BD by CYP2E1 is required for genotoxicity to occur. Inhalation exposures were conducted with B6C3F1 mice using a closed-chamber technique, and the maximum rate of butadiene oxidation was estimated. The total amount of butadiene metabolized was then correlated with the frequency of micronuclei (MN). Three treatment groups were used: (1) mice with no pretreatment; (2) mice pretreated with 1,2-trans-dichloroethylene (DCE), a specific CYP2E1 inhibitor; and (3) mice pretreated with 1-aminobenzotriazole (ABT), an irreversible inhibitor of cytochromes P450. Mice in all 3 groups were exposed to an initial BD concentration of 1100 ppm, and the decline in concentration of BD in the inhalation chamber with time, due to uptake and metabolism of BD, was monitored using gas chromatography. A physiologically based pharmacokinetic model was used to analyze the gas uptake data, estimate Vmax for BD oxidation, and compute the total amount of BD metabolized. Model simulations of the gas uptake data predicted the maximum rate of BD oxidation would be reduced by 60% and 100% for the DCE- and ABT-pretreated groups, respectively. Bone marrow was harvested 24 h after the onset of the inhalation exposure and analyzed for frequency of micronuclei in polychromatic erythrocytes (MN-PCE). The frequency of MN-PCE per 1000 PCE in mice exposed to BD was 28.2 ± 3.1, 19.8 ± 2.5, and 12.3 ± 1.9, for the mice with no pretreatment, DCE-pretreated mice and ABT-pretreated mice, respectively. Although inhibition of CYP2E1 decreased BD-mediated genotoxicity, it did not completely eliminate genotoxic effects. These data suggest that other P450 isoforms may contribute significantly to the metabolic activation of BD and resultant genotoxicity. [ABSTRACT FROM PUBLISHER]

Benzene is a ubiquitous environmental pollutant that is known to cause hematotoxicity and leukemia in humans. The initial oxidative metabolite of benzene has long been suspected to be benzene oxide (3,5-cyclohexadiene-1,2-oxide). During in vitro experiments designed to characterize the oxidative metabolism of [14C]benzene, a metabolite was detected by HPLC-radioactivity analysis that did not elute with other known oxidative metabolites. The purpose of our investigation was to prove the hypothesis that this metabolite was benzene oxide. Benzene (1 mM) was incubated with liver microsomes from human donors, male B6C3F1 mice, or male Fischer-344 rats, NADH (1 mM), and NADPH (1 mM) in 0.1 M sodium phosphate buffer (pH 7.4) and then extracted with methylene chloride. Gas chromatography-mass spectrometry analysis of incubation extracts for mice, rats, and humans detected a metabolite whose elution time and mass spectrum matched that of synthetic benzene oxide. The elution time of the benzene oxide peak was approximately 4.1 min, while phenol eluted at approximately 8 min. Benzene oxide also coeluted with the HPLC peak of the previously unidentified metabolite. Based on the 14C activity of this peak, the concentration of benzene oxide was determined to be approximately 18 microM, or 7% of total benzene metabolites, after 18 min of incubation of mouse microsomes with 1 mM benzene. The metabolite was not observed in incubations using heat-inactivated microsomes. This is the first demonstration that benzene oxide is a product of hepatic benzene metabolism in vitro. The level of benzene oxide detected suggests that benzene oxide is sufficiently stable to reach significant levels in the blood of mice, rats, and humans and may be translocated to the bone marrow. Therefore benzene oxide should not be excluded as a possible metabolite involved in benzene-induced leukemogenesis. [ABSTRACT FROM PUBLISHER]

1,3-Butadiene (BD) is a more potent tumor inducer in mice than in rats. BD also shows striking differences in metabolic activation, with substantially higher blood concentrations of 1,2:3,4-diepoxybutane (butadiene diepoxide; BDE) in BD-exposed mice than in similarly exposed rats. The objective of this study was to develop a single mechanistic model structure capable of describing BD disposition in both species. To achieve this objective, known pathways of 1,2-epoxy-3-butene (butadiene monoepoxide; BMO) and BDE metabolism were incorporated into a physiologically based pharmacokinetic model by scaling rates determined in vitro. With this model structure, epoxide clearance was underestimated for both rats and mice. Improved simulation of blood epoxide concentrations was achieved by addition of first-order metabolism in the slowly perfused tissues, verified by simulation of data on the time course for BMO elimination after i.v. injection of BMO. Blood concentrations of BD were accurately predicted for mice and rats exposed by inhalation to constant concentrations of BD. However, if all BD was assumed to be metabolized to BMO, blood concentrations of BMO were overpredicted. By assuming that only a fraction of BD metabolism produces BMO, blood concentrations of BMO could be predicted over a range of BD exposure concentrations for both species. In vitro and in vivo studies suggest an alternative cytochrome P-450-mediated pathway for BD metabolism that does not yield BMO. Including an alternative pathway for BD metabolism in the model also gave accurate predictions of blood BDE concentrations after inhalation of BD. Blood concentrations of BMO and BDE observed in both mice and rats are best explained by the existence of an alternative pathway for BD metabolism which does not produce BMO. [ABSTRACT FROM PUBLISHER]

Benzene is a ubiquitous, highly flammable, colorless liquid that is a known hematotoxin, myelotoxin, and human leukemogen. Benzene-induced toxicity in animals is clearly mediated by its metabolism. The mechanisms of acute hemato- and myelotoxicity in humans are almost certainly the same as in animals, and there is compelling evidence that metabolism is requisite for the induction of leukemia in humans. A very large number of experimental investigations of benzene metabolism have been conducted with animals, both in vivo and in vitro. There have also been many investigations of benzene metabolism in humans and with human tissues, Although the blood or tissue concentrations of benzene metabolites in humans resulting from benzene exposure have never been measured. Further, a number of mathematical models of benzene metabolism and dosimetry have been developed. In this article, we consider results from both experimental and mathematical modeling research, with particular emphasis on the last decade, and discuss the factors that are likely to be most influential in the metabolism of benzene.

Benzene (C6H6) is a highly flammable, colorless liquid. Ubiquitous exposures result from its presence in gasoline vapors, cigarette smoke, and industrial processes. Benzene increases the incidence of leukemia in humans when they are exposed to high doses for extended periods; however, leukemia risks in humans at low exposures are uncertain. The exposure-dose-response relationship of benzene in humans is expected to be nonlinear because benzene undergoes a series of metabolic transformations, detoxifying and activating, in the liver, resulting in multiple metabolites that exert toxic effects on the bone marrow. We developed a physiologically based pharmacokinetic model for the uptake and elimination of benzene in mice to relate the concentration of inhaled and orally administered benzene to the tissue doses of benzene and its key metabolites, benzene oxide, phe nol, and hydroquinone. As many parameter values as possible were taken from the literature; in particular, metabolic parameters obtained from in vitro studies with mouse liver were used since comparable parameters are also available for humans. Parameters estimated by fitting the model to published data were first-order rate constants for pathways lacking in vitro data and the concentrations of microsomal and cytosolic protein, which effectively alter overall enzyme activity. The model was constrained by using the in vitro metabolic parameters (maximum velocities, first-order rate constants, and saturation parameters), and data from multiple laboratories and experiments were used. Despite these constraints and sources of variability, the model simulations matched the data reasonably well in most cases, showing that in vitro metabolic constants can be successfully extrapolated to predict in vivo data for benzene metabolism and dosimetry. Therefore in vitro metabolic constants for humans can subsequently be extrapolated to predict the dosimetry of benzene and its metabolites in humans. This will allow us to better estimate the risks of adverse effects from low-level benzene exposures.

Our objective was to construct a physiologically-based pharmacokinetic (PBPK) model describing the kinetic behavior of 2,4-dichlorophenoxyacetic acid (2,4-D) on rats after long-term exposures to low doses. Our study demonstrated the model's ability to simulate uptake of 2,4-D in discrete areas of the rat brain. The model was derived from the generic PBPK model that was first developed for high-dose, single exposures of 2,4-D to rats or rabbits (Kim, C.S., Gargas, M.L., Andersen, M.E., 1994. Pharmacokinetic modeling of 2,4-dichlorophenoxyacetic acid (2,4-D) in rats and rabbits brain following single dose administration. Toxicol. Lett. 74, 189-201; Kim, C.S., Slikker, W., Jr., Binienda, Z., Gargas, M.L., Andersen, M.E., 1995. Development of a physiologically based pharmacokinetic (PBPK) model for 2,4-dichlorophenoxyacetic acid (2,4-D) dosimetry in discrete areas of the brain following a single intraperitoneal or intravenous dose. Neurotox. Teratol. 17, 111-120.), to which a subcutaneous (hypodermal) compartment was incorporated for low-dose, long-term infusion. It consisted of two body compartments, along with compartments for venous and arterial blood, cerebrospinal fluid, brain plasma and six brain regions. Uptake of the toxin was membrane-limited by the blood-brain barrier with clearance from the brain provided by cerebrospinal fluid 'sink' mechanisms. This model predicted profiles of 2,4-D levels in brain and blood over a 28-day period that compared well with concentrations measured in vivo with rats that had been given 2,4-D (1 or 10 mg/kg per day) with [14C]-2,4-D subcutaneously (s.c.) for 7, 14, or 28 days, respectively. This PBPK model should be an effective tool for evaluating the target tissue doses that may produce the neurotoxicity of organic acid toxicants after low-dose, long-term exposures to contaminated foods or the environment.

Increasing concerns that environmental contaminants may disrupt the endocrine system require development of mathematical tools to predict the potential for such compounds to significantly alter human endocrine function. The endocrine system is largely self-regulating, compensating for moderate changes in dietary phytoestrogens (e.g., in soy products) and normal variations in physiology. However, severe changes in dietary or oral exposures or in health status (e.g., anorexia), can completely disrupt the menstrual cycle in women. Thus, risk assessment tools should account for normal regulation and its limits. We present a mathematical model for the synthesis and release of luteinizing hormone (LH) and follicle-stimulating hormone (FSH) in women as a function of estrogen, progesterone, and inhibin blood levels. The model reproduces the time courses of LH and FSH during the menstrual cycle and correctly predicts observed effects of administered estrogen and progesterone on LH and FSH during clinical studies. The model should be useful for predicting effects of hormonally active substances, both in the pharmaceutical sciences and in toxicology and risk assessment.

The mucociliary apparatus is an important respiratory-tract defense system that may provide significant protection of the underlying epithelium from gases and vapors. Limiting-case calculations were performed to determine the significance of convective mucus transport and chemical reaction for formaldehyde (HCHO) and ozone (O(3)) in rat nasal respiratory epithelial mucus. Less than 4.6% of absorbed HCHO can be bound to amino groups (serum albumin) after 20 min of exposure. Thus, at the slowest measured mucus flow rates in rats, approximately 1 mm/min, a fluid element of mucus could travel more than 2 cm before binding 5% of absorbed HCHO, by which time the element would probably leave the nose (the site of toxic responses). In other calculations, HCHO removed by chemical reaction from a volume of mucus exposed for longer times was determined to be less than 0.54% of that removed by mucus flow (convection). Given the solubility of HCHO in mucus (water) and estimates of total mucus flow, however, as much as 22-42% of inhaled HCHO may be removed by total mucus flow. Alternately, O(3) dissolved in mucus would react completely with unsaturated fatty acids in 8.3 x 10(-4) s, in which time the mucus could flow no more than approximately 0.42 microm at the maximum reported flow rate of 30 mm/min. Even if a volume of mucus is flushed by net flow in 1 s, the amount of O(3) removed by flow would only be 0.12% of that removed by chemical reaction. Finally, based on the solubility of ozone, less than 8.0 x 10(-5)% of inhaled material could be removed from the nose by mucus flow. These results indicate which mucociliary processes are significant in site-specific dosimetry modeling.

Kimbell and coworkers (Toxicol, Appl. Pharmacol, 121, 253-263, 1993) developed a computational fluid dynamics (CFD) model of a F344 rat nasal passage to quantify local wall mass flux (uptake rate) of inhaled chemical. To simulate formaldehyde uptake, Kimbell et al. assumed that mass transfer of formaldehyde from the air into the nasal lining was fast and complete. This was approximated in the CFD model by setting the formaldehyde concentration at the airway walls to zero. Experimental confirmation of formaldehyde mass-flux predictions is desirable if the CFD model is to be used for predicting formaldehyde dosimetry. The purpose of this study was to see if the CFD model predictions of formaldehyde mass flux are consistent with laboratory data on formaldehyde dosimetry. In this study, a mathematical model of the nasal lining was modified to link CFD dosimetry predictions for inhaled formaldehyde with measured tissue disposition of inhaled gas. This model treats the nasal lining as a single, well-stirred compartment, accounts for formaldehyde reaction via saturable and first-order pathways, and allows comparison of model-predicted DNA-protein cross-links (DPX) with regional DPX measured in formaldehyde-exposed rats. Effective Michaelis-Menten kinetic parameters (Vmax = 3040 microM/min and Km = 59 microM) and a pseudo-first-order rate constant for elimination of formaldehyde by nonsaturable pathways (kf = 6 min-1) were estimated (fit) using an average mass flux derived from experimentally measured uptake of formaldehyde. DPX predictions obtained using the estimated kinetic parameters and linking the CFD model to the nasal-lining model compared well with experimentally measured DPX. The close correlation between predicted and measured DPX in the rat nasal passage supports the CFD model predictions of formaldehyde mass flux at the level of resolution provided by the experimental data.

In vitro and in vivo butadiene (BD) metabolism data from laboratory animals were integrated into a rodent physiologically based pharmacokinetic (PBPK) model with flow- and diffusion-limited compartments. The resulting model describes experimental data from multiple sources under scenarios such as closed chamber inhalation and nose-only flow-through inhalation exposures. Incorporation of diurnal glutathione (GSH) variation allows accurate simulation of GSH changes observed in air control nose-only exposures and BD exposures. An isolated tissue model based on rate parameters determined in vitro predicts the decrease in epoxide concentrations in intact animals during the time lag between exsanguination and tissue removal for tissues capable of epoxide biotransformation, providing a better indication of in vivo dosimetry. Further refinements of the model are required relative to model predictions of an important BD metabolite, diepoxybutane.

Parameter estimates can be obtained by fitting a numerical simulation model to experimental data, but these estimates may be biased and/or imprecise because of noise in the experimental data. Appropriate choice of experimental conditions, such as exposure or substrate concentrations and sampling times, can minimize the effect of experimental noise on parameter estimates, thus reducing bias and improving precision. This article describes a technique for selecting experimental (initial) conditions and measurement times for optimal parameter estimation. The technique makes use of a user-supplied mathematical simulation model for the process under study with a set of "current" parameter values specified. These "current" parameter values are the best that can be obtained using all available experimental data and/or literature information at the time when design calculations are performed. Early in a modeling study, the "current" parameter values will be tentative--based on a relatively small amount of information. Later in a study, the "current" parameter values may be known to reasonable accuracy, but final confirmation is desired. The technique uses the simulation model to calculate a numerical index for each possible experimental design. The numerical index, or Information Index, is a measure of the response of a simulation model to changes in parameter values, described by Kalogerakis and Luus (1983, 1984). The experimental design with the greatest value of Information Index is the one under which parameters can be most precisely estimated. Computation of the Information Index, described in detail, can be somewhat complicated, depending on the software available. The results, however, are simple to interpret and provide valuable information on the quality of alternate proposed experiments. The technique is applicable to a broad range of dynamical systems. Its use is demonstrated by application to a simulation model being developed to describe the in vitro metabolism of benzene by mouse liver microsomes.

Low levels of benzene from sources including cigarette smoke and automobile emissions are ubiquitous in the environment. Since the toxicity of benzene probably results from oxidative metabolites, an understanding of the profile of biotransformation of low levels of benzene is critical in making a valid risk assessment. To that end, we have investigated metabolism of a low concentration of [14C]benzene (3.4 microM) by microsomes from human, mouse and rat liver. The extent of phase I benzene metabolism by microsomal preparations from 10 human liver samples and single microsomal preparations from both mice and rats was then related to measured activities of cytochrome P450 (CYP) 2E1. Measured CYP 2E1 activities, as determined by hydroxylation of p-nitrophenol, varied 13-fold (0.253-3.266 nmol/min/mg) for human samples. The fraction of benzene metabolized in 16 min ranged from 10% to 59%. Also at 16 min, significant amounts of oxidative metabolites were formed. Phenol was the main metabolite formed by all but two human microsomal preparations. In those samples, both of which had high CYP 2E1 activity, hydroquinone was the major metabolite formed. Both hydroquinone and catechol formation showed a direct correlation with CYP 2E1 activity over the range of activities present. A simulation model was developed based on a mechanism of competitive inhibition between benzene and its oxidized metabolites, and was fit to time-course data for three human liver preparations. Model calculations for initial rates of benzene metabolism ranging from 0.344 to 4.442 nmol/mg/min are directly proportional to measured CYP 2E1 activities. The model predicted the dependence of benzene metabolism on the measured CYP 2E1 activity in human liver samples, as well as in mouse and rat liver samples. These results suggest that differences in measured hepatic CYP 2E1 activity may be a major factor contributing to both interindividual and interspecies variations in hepatic metabolism of benzene. Validation of this system in vivo should lead to more accurate assessment of the risk of benzene's toxicity following low-level exposure.

Benzene, an important industrial solvent and constituent of unleaded gasoline, causes leukemia and aplastic anemia in humans. Mice are more sensitive than rats to benzene toxicity, though neither species has been shown to respond consistently with benzene-induced leukemia. Benzene biotransformation in liver to phenol, hydroquinone, catechol and/or muconaldehyde is thought to be necessary for its hematotoxicity and/or genotoxicity. Our goal is to develop a mathematical simulation model capable of describing the pathways and kinetics of benzene metabolism by rat and mouse liver microsomes and to assess the role of species metabolic differences in species sensitivity. Microsomes were incubated with 4 microM [U-14C]-benzene or 4 microM [U-14C]phenol. Metabolite production was quantified by extraction into ethyl acetate, HPLC separation and liquid scintillation spectroscopy. After 45 min, mouse liver microsomes converted 20% of the benzene to phenol, 31% to hydroquinone and 2% to catechol. Rat liver microsomes converted 23% of benzene to phenol, 8% to hydroquinone and 0.5% to catechol. Production of hydroquinone and catechol continued for 90 min for mouse liver microsomes, while production by rat liver microsomes had virtually ceased by 90 min. Muconic acid production by mouse liver microsomes was < 0.2% and < 0.04% from benzene and phenol respectively after 90 min. A quantitative simulation model was constructed to describe the in vitro metabolism of benzene, incorporating the reaction sequences: benzene-->phenol-->catechol-->trihydroxybenzene and phenol-->hydroquinone-->trihydroxybenzene. In the model, all of the reaction steps are assumed to be catalyzed by the same enzyme(s), cytochrome(s) P450, and benzene, phenol, hydroquinone and catechol in solution are all assumed to compete, through reversible binding, for the same reaction site(s) on cytochrome(s) P450. The simulation model accurately described both the benzene and phenol kinetic data, supporting this proposed mechanism. In particular, this model suggests that the observed inhibition of benzene on phenol metabolism, and of phenol on benzene metabolism, occurs through competition for a common reaction site, which can also bind catechol and hydroquinone.

An inherent problem in studying the behavior of a metabolic pathway is the impossibility of developing a complete, detailed model that includes all the cellular processes that have an impact on the set of fluxes in such a pathway. Lacking this, one requires some means of modeling the interactions between a metabolic pathway and other cellular processes for the purpose of analyzing pathway characteristics within the cell (e.g., determining sensitivity coefficients for various steps in the pathway) with a minimal amount of time and effort. A general framework is developed for studying these issues in a rigorous manner. Using this framework, detailed knowledge about a metabolic pathway (i.e., a set of rate expressions for steps in the pathway) can be combined with the results from a relatively simple set of experiments in order to obtain estimates for the sensitivity of the pathway to enzyme activities, inhibition constants, and other parameters that determine the pathway's behavior, while accounting for the pathway's interaction with the rest of the cellular metabolism. A model system representing amino acid production is used to illustrate the problem and to provide results based on computational experiments. The modeling strategy described here should be useful in genetic design to improve pathway fluxes and metabolic network selectivity.