Computational model of steroidogenesis in human H295R cells to predict biochemical response to endocrine-active chemicals: model development for metyrapone

Towards a microfluidic H295R steroidogenesis assay-biocompatibility study and steroid detection on a thiol-ene-based chip

The development of cell-based microfluidic assays offers exciting new opportunities in toxicity testing, allowing for integration of new functionalities, automation, and high throughput in comparison to traditional well-plate assays. As endocrine disruption caused by environmental chemicals and pharmaceuticals represents a growing global health burden, the purpose of the current study was to contribute towards the miniaturization of the H295R steroidogenesis assay, from the well-plate to the microfluidic format. Microfluidic chip fabrication with the established well-plate material polystyrene (PS) is expensive and complicated; PDMS and thiol-ene were therefore tested as potential chip materials for microfluidic H295R cell culture, and evaluated in terms of cell attachment, cell viability, and steroid synthesis in the absence and presence of collagen surface modification. Additionally, spike-recovery experiments were performed, to investigate potential steroid adsorption to chip materials. Cell aggregation with poor steroid recoveries was observed for PDMS, while cells formed monolayer cultures on the thiol-ene chip material, with cell viability and steroid synthesis comparable to cells grown on a PS surface. As thiol-ene overall displayed more favorable properties for H295R cell culture, a microfluidic chip design and corresponding cell seeding procedure were successfully developed, achieving repeatable and uniform cell distribution in microfluidic channels. Finally, H295R perfusion culture on thiol-ene chips was investigated at different flow rates (20, 10, and 2.5 µL/min), and 13 steroids were detected in eluting cell medium over 48 h at the lowest flow rate. The presented work and results pave the way for a time-resolved microfluidic H295R steroidogenesis assay.

Evaluating structure-based activity in a high-throughput assay for steroid biosynthesis

Data from a high-throughput human adrenocortical carcinoma assay (HT-H295R) for steroid hormone biosynthesis are available for >2000 chemicals in single concentration and 654 chemicals in multi-concentration (mc). Previously, a metric describing the effect size of a chemical on the biosynthesis of 11 hormones was derived using mc data referred to as the maximum mean Mahalanobis distance (maxmMd). However, mc HT-H295R assay data remain unavailable for many chemicals. This work leverages existing HT-H295R assay data by constructing structure-activity relationships to make predictions for data-poor chemicals, including: (1) identification of individual structural descriptors, known as ToxPrint chemotypes, associated with increased odds of affecting estrogen or androgen synthesis; (2) a random forest (RF) classifier using physicochemical property descriptors to predict HT-H295R maxmMd binary (positive or negative) outcomes; and, (3) a local approach to predict maxmMd binary outcomes using nearest neighbors (NNs) based on two types of chemical fingerprints (chemotype or Morgan). Individual chemotypes demonstrated high specificity (85-98%) for modulators of estrogen and androgen synthesis but with low sensitivity. The best RF model for maxmMd classification included 13 predicted physicochemical descriptors, yielding a balanced accuracy (BA) of 71% with only modest improvement when hundreds of structural features were added. The best two NN models for binary maxmMd prediction demonstrated BAs of 85 and 81% using chemotype and Morgan fingerprints, respectively. Using an external test set of 6302 chemicals (lacking HT-H295R data), 1241 were identified as putative estrogen and androgen modulators. Combined results across the three classification models (global RF model and two local NN models) predict that 1033 of the 6302 chemicals would be more likely to affect HT-H295R bioactivity. Together, these in silico approaches can efficiently prioritize thousands of untested chemicals for screening to further evaluate their effects on steroid biosynthesis.

Human adrenocortical carcinoma cell line (NCI-H295R): An in vitro screening model for the assessment of endocrine disruptors' actions on steroidogenesis with an emphasis on cell ultrastructural features

Cell lines as an in vitro model for xenobiotic screening and toxicity studies provide a very important tool in the field of scientific research at the level of molecular pathways and gene expression. Good cell culture practice and intracellular characterization, as well as physiological properties of the cell line are of critical importance for in vitro reproductive toxicity testing of various endocrine-disrupting chemicals. The NCI-H295R, human adrenocarcinoma cell line, is the most widely used in vitro cellular system to study the human adrenal steroidogenic pathway at the level of hormone production and gene expression, as it expresses genes that encode for all the key enzymes for steroidogenesis. In this review, we aim to highlight the information considering the origin, development, physiological and ultrastructural characteristics of the NCI-H295R cell line. The review also creates a broad overview of the cell line usage in various range of studies related to the steroidogenesis issues. To our best knowledge, the paper provides the first report of quantitative data (ex novo) from stereological estimates of component (volume, surface) densities of nuclei, mitochondria, and lipid droplets of the NCI-H295R cells. Such ultrastructural measurements can be valuable in the assessment of underlying mechanisms of changes in the cell steroid hormone production induced by the action of diverse endocrine disruptors. Thus, they can significantly contribute to complexity of structure-function relationships in association with steroidogenesis.

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.

Effects of fast food packaging plasticizers and their metabolites on steroid hormone synthesis in H295R cells

The health risks of exposure to plasticizers have received widespread attention, however, little is known about the effects of fast food packaging plasticizers on steroid hormone synthesis. In the present study, the types and migration of plasticizers in some commonly used fast-food packaging materials were detected by GC-MS, and the interference effects of these plasticizers and their metabolites on steroid hormone synthesis in the human body were evaluated by the H295R steroidogenesis assay. The GC-MS results showed that the main plasticizer compounds that migrated from fast food packaging into food were di(2-ethylhexyl) phthalate (DEHP), dibutyl phthalate (DBP) and bis(2-ethylhexyl) adipate (DEHA). Exposure to these chemicals (100-1000 μM) can significantly reduce the viability of H295R cells in a dose-response manner, and these plasticizers and their metabolites that migrated into oily foods at high temperatures (0.25-25 μM) could significantly increase the E2 level and reduce the T level in H295R cells. According to the qRT-PCR data, 0.25 to 25 μM mono(2-ethylhexyl) phthalate (MEHP) significantly upregulated the expression levels of 17β-HSD1 and CYP19A1, and downregulated those of CYP17A1, CYP11A1 and StAR. The Western blot results were consistent with those of qRT-PCR. In summary, these results indicated that even exposure to low concentrations (≤1 mg/l or 2.5 μM) of these chemicals and their metabolites can cause significant endocrine-disrupting effects.

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.

High-Throughput H295R Steroidogenesis Assay: Utility as an Alternative and a Statistical Approach to Characterize Effects on Steroidogenesis

The U.S. Environmental Protection Agency Endocrine Disruptor Screening Program and the Organization for Economic Co-operation and Development (OECD) have used the human adrenocarcinoma (H295R) cell-based assay to predict chemical perturbation of androgen and estrogen production. Recently, a high-throughput H295R (HT-H295R) assay was developed as part of the ToxCast program that includes measurement of 11 hormones, including progestagens, corticosteroids, androgens, and estrogens. To date, 2012 chemicals have been screened at 1 concentration; of these, 656 chemicals have been screened in concentration-response. The objectives of this work were to: (1) develop an integrated analysis of chemical-mediated effects on steroidogenesis in the HT-H295R assay and (2) evaluate whether the HT-H295R assay predicts estrogen and androgen production specifically via comparison with the OECD-validated H295R assay. To support application of HT-H295R assay data to weight-of-evidence and prioritization tasks, a single numeric value based on Mahalanobis distances was computed for 654 chemicals to indicate the magnitude of effects on the synthesis of 11 hormones. The maximum mean Mahalanobis distance (maxmMd) values were high for strong modulators (prochloraz, mifepristone) and lower for moderate modulators (atrazine, molinate). Twenty-five of 28 reference chemicals used for OECD validation were screened in the HT-H295R assay, and produced qualitatively similar results, with accuracies of 0.90/0.75 and 0.81/0.91 for increased/decreased testosterone and estradiol production, respectively. The HT-H295R assay provides robust information regarding estrogen and androgen production, as well as additional hormones. The maxmMd from this integrated analysis may provide a data-driven approach to prioritizing lists of chemicals for putative effects on steroidogenesis.

Incorporation of 14C-cholesterol in human adrenal corticocarcinoma H295R cell line and online-radiodetection of produced 14C-steroid hormone metabolites

This study demonstrates the addition of ¹⁴C-cholesterol to the human cell line H295R will in-situ form radiolabeled steroid hormones allowing for new mechanistic and metabolic insights. The aim of the present study was to in-situ radiolabel steroid hormones from cell line-incorporated ¹⁴C-cholesterol using the OECD guideline 456, H295R steroidogenesis in-vitro assay. Radiodetection of the steroid metabolites of the steroidogenic pathway allows for an improved understanding of the various enzymatic mechanisms involved without necessarily being dependent on quantification. Generated radiolabeled steroids were analyzed using HPLC hyphenated with a Flow Scintillation Analyzer (FSA). H295R cells were incubated with radiolabeled cholesterol and cell media were collected and prepared by solid phase extraction and analyzed with HPLC-FSA. For successful radiolabeling of the steroids in the steroidogenesis of H295R cells, radioactive cholesterol may potentially only need to be added just before the cells are incubated for 72h in well plates. Based on the obtained HPLC-FSA chromatograms, and confirmation of the observations by studies in the literature, a qualitative time profile for the production of steroid hormones was estimated. Multiple radiolabeled steroid hormones were identified by means of analytical standards and UV (ultraviolet) co-chromatography, though the elucidation of multiple metabolites remains unresolved. Although online radiodetection proved to suffer from suboptimal sensitivity, the concept of radiolabeling the steroidogenesis in H295R cells with ¹⁴C-cholesterol and detecting the radiolabeled steroid hormones online was proved and may assist in further toxicological studies.

Effects of bisphenol analogues on steroidogenic gene expression and hormone synthesis in H295R cells

The use of Bisphenol A (BPA) has been regulated in many countries because of its potential adverse effects on human health. As a result of the restriction, structural anologues such as bisphenol S (BPS) and bisphenol F (BPF) have already been used for industrial applications as alternatives to BPA. Bisphenol AF (BPAF) is mainly used as a crosslinker in the synthesis of specialty fluoroelastomers. These compounds have been detected in various environmental matrices and human samples. Previous studies have shown that these compounds have potential endocrine disrupting effects on wildlife and mammals in general. However, the effects on adrenocortical function and the underlying mechanisms are not fully understood. In the present study, the H295R cell line was used as a model to compare the cell toxicity and to investigate the potential endocrine disrupting action of four BPs (including BPA, BPS, BPF, and BPAF). The half lethal concentration (LC50) values at 72 h exposure indicated that the rank order of toxicities of the chemicals was BPAF > BPA > BPS > BPF. The hormone results demonstrated that BPA analogues, such as BPF, BPS and BPAF were capable of altering steroidogenesis in H295R cells. BPA and BPS exhibited inhibition of hormone production, BPF predominantly led to increased progesterone and 17β-estradiol levels and BPAF showed induction of progesterone and reduction of testosterone. Inhibition effects of BPA and BPAF on hormone production were probably mediated by down-regulation of steroidogenic genes in H295R cells. However, the mechanisms of the endocrine interrupting action of BPF and BPS are still unclear, which may have additional mechanisms that have not been detected with BPA.

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.

Air Pollution Exposure Model for Individuals (EMI) in Health Studies: Evaluation for Ambient PM2.5 in Central North Carolina

Air pollution health studies of fine particulate matter (diameter ≤2.5 μm, PM2.5) often use outdoor concentrations as exposure surrogates. Failure to account for variability of indoor infiltration of ambient PM2.5 and time indoors can induce exposure errors. We developed and evaluated an exposure model for individuals (EMI), which predicts five tiers of individual-level exposure metrics for ambient PM2.5 using outdoor concentrations, questionnaires, weather, and time-location information. We linked a mechanistic air exchange rate (AER) model to a mass-balance PM2.5 infiltration model to predict residential AER (Tier 1), infiltration factors (Tier 2), indoor concentrations (Tier 3), personal exposure factors (Tier 4), and personal exposures (Tier 5) for ambient PM2.5. Using cross-validation, individual predictions were compared to 591 daily measurements from 31 homes (Tiers 1-3) and participants (Tiers 4-5) in central North Carolina. Median absolute differences were 39% (0.17 h(-1)) for Tier 1, 18% (0.10) for Tier 2, 20% (2.0 μg/m(3)) for Tier 3, 18% (0.10) for Tier 4, and 20% (1.8 μg/m(3)) for Tier 5. The capability of EMI could help reduce the uncertainty of ambient PM2.5 exposure metrics used in health studies.

Metyrapone, an inhibitor of cytochrome oxidases, does not affect viability in a neuroblastoma cell model of bilirubin toxicity

Background

Unconjugated hyperbilirubinemia may cause brain damage in infants, and globally remains a source of neonatal morbidity and mortality. A significant inter-individual variability in vulnerability to bilirubin toxicity remains largely unexplained. An enzyme located in mitochondria oxidizes bilirubin. We hypothesized that inhibiting bilirubin oxidation in human neuronal cell cultures exposed to bilirubin would increase cell death.

Methods

The ability of mitochondrial membranes from CHP-212 human neuroblastoma cells to oxidize bilirubin was verified by spectrophotometry. Intact cells in culture were exposed to bilirubin (75 μM) with or without metyrapone (250 μM) for 24 h, stained with Annexin-V and Propidium iodide and analyzed for apoptosis and necrosis by flow cytometry.

Results

Bilirubin caused a significant reduction of viability, from 84 ± 2.0% (mean ± SEM) vs 67 ± 2.7% (p < 0.05), but adding metyrapone to the bilirubin-exposed cells did not further impact cell viability. Metyrapone alone did not influence cell viability.

Conclusion

Herein we have shown that metyrapone does not increase cell death in neuroblastoma cells in culture exposed to bilirubin. Our results question the relationship between the oxidative mechanism evaluated by spectrophotometry and cell viability. Our findings add to the discussion on whether bilirubin oxidation represents a potentially important protective mechanism in neurons challenged by hyperbilirubinemia.

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Neonatal jaundice may cause brain damage in newborn infants.

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Oxidation of bilirubin in the brain has been proposed as a protective mechanism.

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In a cell model, blocking the enzyme responsible for bilirubin oxidation did not increase toxicity.

Zebrafish embryos/larvae for rapid determination of effects on hypothalamic-pituitary-thyroid (HPT) and hypothalamic-pituitary-interrenal (HPI) axis: mRNA expression

To identify and prioritize chemicals that may affect thyroid and adrenal/interregnal endocrine system and to reduce cost and animal use by conventional toxicity assay, an in vivo screening assay was developed using zebrafish embryos/larvae based on measurement of expression of genes that were suggested to play important roles in hypothalamic-pituitary-thyroid (HPT) and hypothalamic-pituitary-interrenal (HPI) axis. Model chemicals that could modulate HPT and HPI axis in adult fish were selected in assay validation, including anti-thyroid agent 6-Propyl-2-thiouracil (PTU) and cytochrome P450 11B (Cyp11b) enzyme inhibitor metyrapone (MET). Zebrafish embryos were exposed to different concentrations of model chemical from 4h post-fertilization (hpf) to 5d post-fertilization (dpf). Exposure to PTU increased mRNA expression of sodium iodide symporter (nis) and thyroglobulin (tg) involved in HPT axis, and MET treatment up-regulated all the mRNA expression tested involved in HPI axis by a compensatory mechanism. These results suggested that HPT and HPI axis were active upon chemical exposure at least at 5 dpf zebrafish. Furthermore, we studied the effects of PTU or MET on the cross-talk between HPT and HPI axis. The results demonstrated that PTU and MET could affect cross-talk responses in zebrafish embryos/larvae.

Mathematical modeling of the hypothalamic-pituitary-adrenal gland (HPA) axis, including hippocampal mechanisms

This paper presents a mathematical model of the HPA axis. The HPA axis consists of the hypothalamus, the pituitary and the adrenal glands in which the three hormones CRH, ACTH and cortisol interact through receptor dynamics. Furthermore, it has been suggested that receptors in the hippocampus have an influence on the axis. A model is presented with three coupled, non-linear differential equations, with the hormones CRH, ACTH and cortisol as variables. The model includes the known features of the HPA axis, and includes the effects from the hippocampus through its impact on CRH in the hypothalamus. The model is investigated both analytically and numerically for oscillating solutions, related to the ultradian rhythm seen in data, and for multiple fixed points related to hypercortisolemic and hypocortisolemic depression. The existence of an attracting trapping region guarantees that solution curves stay non-negative and bounded, which can be interpreted as a mathematical formulation of homeostasis. No oscillating solutions are present when using physiologically reasonable parameter values. This indicates that the ultradian rhythm originate from different mechanisms. Using physiologically reasonable parameters, the system has a unique fixed point, and the system is globally stable. Therefore, solutions converge to the fixed point for all initial conditions. This is in agreement with cortisol levels returning to normal, after periods of mild stress, in healthy individuals. Perturbing parameters lead to a bifurcation, where two additional fixed points emerge. Thus, the system changes from having a unique stable fixed point into having three fixed points. Of the three fixed points, two are stable and one is unstable. Further investigations show that solutions converge to one of the two stable fixed points depending on the initial conditions. This could explain why healthy people becoming depressed usually fall into one of two groups: a hypercortisolemic depressive group or a hypocortisolemic depressive group.

A computational model to predict rat ovarian steroid secretion from in vitro experiments with endocrine disruptors

A finely tuned balance between estrogens and androgens controls reproductive functions, and the last step of steroidogenesis plays a key role in maintaining that balance. Environmental toxicants are a serious health concern, and numerous studies have been devoted to studying the effects of endocrine disrupting chemicals (EDCs). The effects of EDCs on steroidogenic enzymes may influence steroid secretion and thus lead to reproductive toxicity. To predict hormonal balance disruption on the basis of data on aromatase activity and mRNA level modulation obtained in vitro on granulosa cells, we developed a mathematical model for the last gonadal steps of the sex steroid synthesis pathway. The model can simulate the ovarian synthesis and secretion of estrone, estradiol, androstenedione, and testosterone, and their response to endocrine disruption. The model is able to predict ovarian sex steroid concentrations under normal estrous cycle in female rat, and ovarian estradiol concentrations in adult female rats exposed to atrazine, bisphenol A, metabolites of methoxychlor or vinclozolin, and letrozole.

Variation in 3β-hydroxysteroid dehydrogenase activity and in pregnenolone supply rate can paradoxically alter androstenedione synthesis

The 3β-hydroxysteroid dehydrogenase/Δ(5)-Δ(4) isomerase (3β-HSD) and 17α-hydroxylase/17,20-lyase cytochrome P450 (P450c17) enzymes are important in determining the balance of the synthesis of different steroids such as progesterone (P4), glucocorticoids, androgens, and estrogens. How this is achieved is not a simple matter because each of the two enzymes utilizes more than one substrate and some substrates are shared in common between the two enzymes. The two synthetic pathways, Δ(4) and Δ(5), are interlinked such that it is difficult to predict how the synthesis of each steroid changes when any of the enzyme activities is varied. In addition, the P450c17 enzyme exhibits different substrate specificities among species, particularly with respect to the 17,20-lyase activity. The mathematical model developed in this study simulates the network of reactions catalyzed by 3β-HSD and P450c17 that characterizes steroid synthesis in human, non-human primate, ovine, and bovine species. In these species, P450c17 has negligible 17,20-lyase activity with the Δ(4)-steroid 17α-hydroxy-progesterone (17OH-P4); therefore androstenedione (A4) is synthesized efficiently only from dehydroepiandrosterone (DHEA) through the Δ(5) pathway. The model helps to understand the interplay between fluxes through the Δ(4) and Δ(5) pathways in this network, and how this determines the response of steroid synthesis to the variation in 3β-HSD activity or in the supply of the precursor substrate, pregnenolone (P5). The model simulations show that A4 synthesis can change paradoxically when 3β-HSD activity is varied. A decrease in 3β-HSD activity to a certain point can increase A4 synthesis by favouring metabolism through the Δ(5) pathway, though further decrease in 3β-HSD activity beyond that point eventually limits A4 synthesis. The model also showed that due to the competitive inhibition of the enzymes' activities by substrates and products, increasing the rate of P5 supply above a certain point can suppress the synthesis of A4, DHEA, and 17OH-P4, and consequently drive more P5 towards P4 synthesis.

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

The human adrenocortical carcinoma cell line H295R is being used as an in vitro steroidogenesis screening assay to assess the impact of endocrine active chemicals (EACs) capable of altering steroid biosynthesis. To enhance the interpretation and quantitative application of measurement data in risk assessments, we are developing a mechanistic computational model of adrenal steroidogenesis in H295R cells to predict the synthesis of steroids from cholesterol (CHOL) and their biochemical response to EACs. We previously developed a deterministic model that describes the biosynthetic pathways for the conversion of CHOL to steroids and the kinetics for enzyme inhibition by the EAC, metyrapone (MET). In this study, we extended our dynamic model by (1) including a cell proliferation model supported by additional experiments and (2) adding a pathway for the biosynthesis of oxysterols (OXY), which are endogenous products of CHOL not linked to steroidogenesis. The cell proliferation model predictions closely matched the time-course measurements of the number of viable H295R cells. The extended steroidogenesis model estimates closely correspond to the measured time-course concentrations of CHOL and 14 adrenal steroids both in the cells and in the medium and the calculated time-course concentrations of OXY from control and MET-exposed cells. Our study demonstrates the improvement of the extended, more biologically realistic model to predict CHOL and steroid concentrations in H295R cells and medium and their dynamic biochemical response to the EAC, MET. This mechanistic modeling capability could help define mechanisms of action for poorly characterized chemicals for predictive risk assessments.