Mechanistic computational model of steroidogenesis in H295R cells: role of oxysterols and cell proliferation to improve predictability of biochemical response to endocrine active chemical--metyrapone

Computational modelling of the Δ4 and Δ5 adrenal steroidogenic pathways provides insight into hypocortisolism

This study demonstrates the application of a mathematical steroidogenic model, constructed with individual in vitro enzyme characterisations, to simulate in vivo steroidogenesis in a diseased state. This modelling approach was applied to the South African Angora goat, that suffers from hypocortisolism caused by altered adrenal function. These animals are extremely vulnerable to cold stress, leading to substantial monetary loss in the mohair industry. The Angora goat has increased CYP17A1 17,20-lyase enzyme activity in comparison with hardy livestock species. Determining the effect of this altered adrenal function on adrenal steroidogenesis during a cold stress response is difficult. We developed a model describing adrenal steroidogenesis under control conditions, and under altered steroidogenic conditions where the animal suffers from hypocortisolism. The model is parameterised with experimental data from in vitro enzyme characterisations of a hardy control species. The increased 17,20-lyase activity of the Angora goat CYP17A1 enzyme was subsequently incorporated into the model and the response to physiological stress is simulated under both control and altered adrenal steroidogenic conditions.

Development of a prioritization method for chemical-mediated effects on steroidogenesis using an integrated statistical analysis of high-throughput H295R data

Synthesis of 11 steroid hormones in human adrenocortical carcinoma cells (H295R) was measured in a high-throughput steroidogenesis assay (HT-H295R) for 656 chemicals in concentration-response as part of the US Environmental Protection Agency's ToxCast program. This work extends previous analysis of the HT-H295R dataset and model by examining the utility of a novel prioritization metric based on the Mahalanobis distance that reduced these 11-dimensional data to 1-dimension via calculation of a mean Mahalanobis distance (mMd) at each chemical concentration screened for all hormone measures available. Herein, we evaluated the robustness of mMd values, and demonstrate that covariance and variance of the hormones measured appear independent of the chemicals screened and are inherent to the assay; the Type I error rate of the mMd method is less than 1%; and, absolute fold changes (up or down) of 1.5 to 2-fold have sufficient power for statistical significance. As a case study, we examined hormone responses for aromatase inhibitors in the HT-H295R assay and found high concordance with other ToxCast assays for known aromatase inhibitors. Finally, we used mMd and other ToxCast cytotoxicity data to demonstrate prioritization of the most selective and active chemicals as candidates for further in vitro or in silico screening.

A steady state system for in vitro evaluation of steroidogenic pathway dynamics: Application for CYP11B1, CYP11B2 and CYP17 inhibitors

Disorders featuring dysregulated adrenal steroidogenesis, such as primary aldosteronism, can benefit from targeted therapies. The aldosterone and cortisol producing enzymes, aldosterone synthase (CYP11B2) and 11-beta-hydroxylase (CYP11B1), share 93% homology requiring selective drugs for pharmacological treatment. Herein, we introduce an effective in vitro assay for evaluation of steroidogenic enzyme kinetics based on intracellular flux calculations. H295RA cells were cultured in chambers under constant medium flow. Four hourly samples were collected (control samples), followed by collections over an additional four hours after treatment with fadrozole (10 nM), metyrapone (10 μM), SI_191 (5 nM), a novel CYP11B2 inhibitor or SI_254 (100 nM), a newly synthesized 17-alpha-hydroxylase/17,20-lyase inhibitor. Mass spectrometric measurements of multiple steroids combined with linear system computational modeling facilitated calculation of intracellular fluxes and changes in rate constants at different steroidogenic pathway steps, enabling selectivity of drugs for those steps to be evaluated. While treatment with fadrozole, metyrapone and SI_191 all reduced fluxes of aldosterone, corticosterone and cortisol production, treatment with SI_254 led to increased flux through the mineralocorticoid pathway and reduced production of steroids downstream of 17-alpha-hydroxylase/17,20-lyase. Drug-induced decreases in rate constants revealed higher selectivity of SI_191 compared to other drugs for CYP11B2 over CYP11B1, this reflecting additional inhibitory actions of SI_191 on catalytic steps of CYP11B2 downstream from the initial 11-beta-hydroxlase step. By culturing cells under perfusion the described system provides a realistic model for simple and rapid calculations of intracellular fluxes and changes in rate constants, thereby offering a robust procedure for investigating drug or other effects at specific steps of steroidogenesis.

LC-MS/MS based profiling and dynamic modelling of the steroidogenesis pathway in adrenocarcinoma H295R cells

Endocrine disrupting chemicals have been reported to exert effects directly on enzymes involved in steroid biosynthesis. Here, we present a new liquid chromatography-tandem mass spectrometry (LC-MS/MS) method for profiling the steroid metabolome of H295R human adrenocarcinoma cells. Our method can simultaneously analyse 19 precursors, intermediates and end-products, representing the adrenal steroid biosynthesis pathway. In order to obtain better insights into the processes of steroidogenesis, we investigated the dose-response relationship of forskolin, an activator of adenylate cyclase, on steroid production in H295R cells. We observed that 1.5 μM forskolin stimulated steroid production at approximately 50% of the maximum rate for most steroids. Hence, we studied the time course for steroid synthesis over 72 h in H295R cells that were stimulated with forskolin. At 24 h, we observed a peak in steroid levels for the intermediate metabolites, such as progesterone and pregnenolone, while end-products such as testosterone and cortisol continued to increase until 72 h. Finally, we show how global data provide a unique basis to develop a comprehensive, dynamic model for steroidogenesis using first order kinetics. The timeline data made it possible to estimate all reaction rate constants of the network. We propose this method as a unique and sensitive screening tool to identify effects on adrenal steroidogenesis by endocrine disrupting compounds.

CYP11B1 has no role in mitotane action and metabolism in adrenocortical carcinoma cells

Mitotane is the reference drug for adrenocortical carcinoma (ACC) and the metabolic activation of the drug is considered as essential for its activity. The aim of this study was to assess the role of CYP11B1 on mitotane action and metabolism in H295R ACC cells to understand whether this enzyme may influence mitotane action. The simultaneous incubation with mitotane and metyrapone, an adrenolytic molecule targeting 11-beta-hydroxylase, did not influence mitotane-mediated cytotoxic effect and metabolism in H295R ACC cells. CYP11B1 silencing confirmed the lack of a significant metyrapone effect on mitotane action. The present findings do not support the view that CYP11B1 catalyzes a crucial step in the metabolic activation of mitotane and that CYP11B1 confers the adrenal specificity to mitotane.

Estimation of the Mechanism of Adrenal Action of Endocrine-Disrupting Compounds Using a Computational Model of Adrenal Steroidogenesis in NCI-H295R Cells

Adrenal toxicity is one of the major concerns in drug development. To quantitatively understand the effect of endocrine-active compounds on adrenal steroidogenesis and to assess the human adrenal toxicity of novel pharmaceutical drugs, we developed a mathematical model of steroidogenesis in human adrenocortical carcinoma NCI-H295R cells. The model includes cellular proliferation, intracellular cholesterol translocation, diffusional transport of steroids, and metabolic pathways of adrenal steroidogenesis, which serially involve steroidogenic proteins and enzymes such as StAR, CYP11A1, CYP17A1, HSD3B2, CYP21A2, CYP11B1, CYP11B2, HSD17B3, and CYP19A1. It was reconstructed in an experimental dynamics of cholesterol and 14 steroids from an in vitro steroidogenesis assay using NCI-H295R cells. Results of dynamic sensitivity analysis suggested that HSD3B2 plays the most important role in the metabolic balance of adrenal steroidogenesis. Based on differential metabolic profiling of 12 steroid hormones and 11 adrenal toxic compounds, we could estimate which steroidogenic enzymes were affected in this mathematical model. In terms of adrenal steroidogenic inhibitors, the predicted action sites were approximately matched to reported target enzymes. Thus, our computer-aided system based on systems biological approach may be useful to understand the mechanism of action of endocrine-active compounds and to assess the human adrenal toxicity of novel pharmaceutical drugs.

Computational analysis of liquid chromatography-tandem mass spectrometric steroid profiling in NCI H295R cells following angiotensin II, forskolin and abiraterone treatment

Adrenal steroid hormones, which regulate a plethora of physiological functions, are produced via tightly controlled pathways. Investigations of these pathways, based on experimental data, can be facilitated by computational modeling for calculations of metabolic rate alterations. We therefore used a model system, based on mass balance and mass reaction equations, to kinetically evaluate adrenal steroidogenesis in human adrenal cortex-derived NCI H295R cells. For this purpose a panel of 10 steroids was measured by liquid chromatographic-tandem mass spectrometry. Time-dependent changes in cell incubate concentrations of steroids - including cortisol, aldosterone, dehydroepiandrosterone and their precursors - were measured after incubation with angiotensin II, forskolin and abiraterone. Model parameters were estimated based on experimental data using weighted least square fitting. Time-dependent angiotensin II- and forskolin-induced changes were observed for incubate concentrations of precursor steroids with peaks that preceded maximal increases in aldosterone and cortisol. Inhibition of 17-alpha-hydroxylase/17,20-lyase with abiraterone resulted in increases in upstream precursor steroids and decreases in downstream products. Derived model parameters, including rate constants of enzymatic processes, appropriately quantified observed and expected changes in metabolic pathways at multiple conversion steps. Our data demonstrate limitations of single time point measurements and the importance of assessing pathway dynamics in studies of adrenal cortical cell line steroidogenesis. Our analysis provides a framework for evaluation of steroidogenesis in adrenal cortical cell culture systems and demonstrates that computational modeling-derived estimates of kinetic parameters are an effective tool for describing perturbations in associated metabolic pathways.

Systems Biology and Synthetic Biology: A New Epoch for Toxicology Research

Systems biology and synthetic biology are emerging disciplines which are becoming increasingly utilised in several areas of bioscience. Toxicology is beginning to benefit from systems biology and we suggest in the future that is will also benefit from synthetic biology. Thus, a new era is on the horizon. This review illustrates how a suite of innovative techniques and tools can be applied to understanding complex health and toxicology issues. We review limitations confronted by the traditional computational approaches to toxicology and epidemiology research, using polycyclic aromatic hydrocarbons (PAHs) and their effects on adverse birth outcomes as an illustrative example. We introduce how systems toxicology (and their subdisciplines, genomic, proteomic, and metabolomic toxicology) will help to overcome such limitations. In particular, we discuss the advantages and disadvantages of mathematical frameworks that computationally represent biological systems. Finally, we discuss the nascent discipline of synthetic biology and highlight relevant toxicological centred applications of this technique, including improvements in personalised medicine. We conclude this review by presenting a number of opportunities and challenges that could shape the future of these rapidly evolving disciplines.