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This is to certify that the
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EVALUATION, VALIDATION AND APPLICATION OF THE H295R
SYSTEM FOR THE ANALYSIS OF ENDOCRINE DISRUPTING
EFFECTS

presented by

Tannia Rocio Gracia Bustos

has been accepted towards fulfillment
of the requirements for the

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EVALUATION, VALIDATION AND APPLICATION OF THE H295R SYSTEM
FOR THE ANALYSIS OF ENDOCRINE DISRUPTIN G EFFECTS

By

Tannia Rocio Gracia Bustos

A DISSERTATION

Submitted to
Michigan State University
In partial fulfillment of the requirements
For the degree of

DOCTOR OF PHILOSOPHY
Department of Zoology

2007

ABSTRACT

EVALUATION, VALIDATION AND APPLICATION OF THE H295R CELL
SYSTEM FOR THE ANALYSIS OF ENDOCRINE DISRUPTING EFFECTS

By

Tannia Rocio Gracia Bustos

The continuously growing number of compounds synthetically derived or
extracted from natural materials daily discovered, designed or produced in order to
satisfy human’s necessities has brought along unintended effects that have been of
human concern for several decades. It has been clearly established that several of
these synthetic and naturally occurring chemical substances in the environment are
disrupting the normal functions of the endocrine system and its hormones in
humans and wildlife. Despite the wide range of studies that have been conducted in
this area, in many cases there is still insufficient data to demonstrate specific
associations between environmental exposure and endocrine-mediated adverse
effects. The need to evaluate endocrine disruption exerted by pathways other than
receptor-mediated mechanisms has driven scientists to intensively work in the
development of new, practical and more comprehensive bioassays in order to match
up the growing speed of chemical design/production. In this dissertation the
evaluation, validation and application of the new developed H295R cell bioassay
for the evaluation of potential effects of environmental contaminants as endocrine
disrupters, was conducted. Results from the executed studies corroborate the

versatility of the H295R cell bioassay to identify the different effects of chemicals

on steroid production and to point through the different molecular and
enzymatic mechanisms that may be responsible for such effects. This method is
applicable to any environmental contaminants identified up to the present time,
including complex mixtures of them. Moreover, the effectiveness shown in
identifying the potential endocrine effects of realistic environmental samples of

different matrices is without doubt one of its most valuables applications.

A mi madre, la mujer mas valiente que he conocido.

iv

ACKNOWLEDGEMENTS

I profoundly thank Dr. John Giesy for constantly creating opportunities for me to learn
more, to meet wonderful people and to go places in the world I never imagine I will be
able to go. I will be for ever grateful for his constant support; I am very proud to
belong to his family in science. Thanks to my study director, Dr. Paul Jones for being
always able to help me elucidate strange results, for teaching me how to deal with
chaos and for keeping me calm whenever the lab results made me go in panic mode.

Thanks to my graduate committee members, Dr. Richard Hill, Dr. Susan
Masten, Dr. R.J. Stevenson, for their patience, advice and assistance. Many thanks to
Dr. Jesus Olivero-Verbel for providing me the undergraduate research opportunities
that led me down this path, and for pointing the direction towards Dr. Giesy’s group.

To all the MSU’s Aquatic Toxicology Laboratory members, 2001-2006, many
thanks for providing the fun part of this journey. To my colleagues and friends Daniel
Lorenzo, Margriet, Leoni, Margaret, “Dr.” Higley and Amber, thanks much for all the
unforgettable moments.

I have no words to express my gratefulness to my wonderful mother, Margarita,
for her constant and unconditional support. To my brothers Gerson, Julio and Yohn for
their love and to my nephews Linda, Daniel and Valeria for being the force that keeps
me going. Thanks to my super fn'ends Damaris and Jose Vicente for the unconditional

friendship that I will cherish for ever.

TABLE OF CONTENTS

LIST OF TABLES ................................................................................. ix
LIST OF FIGURES ................................................................................... xi
ABBREVIATIONS .............................................................................. xii
INTRODUCTION ................................................................................. 1
CHAPTER 1
STEROIDOGENESIS, ENDOCRINE DISRUPTION AND THE H295R CELL
SYSTEM ............................................................................................. 5
The Endocrine System ..................................................................... 5
Hormones ........................................................................... 7
Type of Hormones ...................................................... 11
Hormone Release ....................................................... 16
Mechanism of Hormone Action ....................................... 16
Metabolism and excretion of hormones .............................. 21
Steroidogenesis ........................................................................... 22
Classification of Steroid Hormones ........................................... 24
Enzymology of Steroid Production ............................................ 25
Endocrine Disruption ..................................................................... 32
The H295R Cell System ................................................................. 38
References ................................................................................. 44
CHAPTER 2
THE H295R SYSTEM FOR THE EVALUATION OF ENDOCRINE DISRUPTING
EFFECTS ........................................................................................... 57
Introduction ................................................................................. 58
Materials and Methods .................................................................... 62
Test Chemicals ................................................................... 62
Experimental Design ............................................................ 62
Cell Viability/Cytotoxicity ..................................................... 65
RNA Isolation .................................................................... 65
cDNA Preparation ............................................................... 66
Real-time PCR ................................................................... 67
Hormone Quantification ........................................................ 68
Statistical Analysis ................................................................................. 69
Results ...................................................................................... 69
Chemical Dose and Time Courses ............................................ 69
Patterns of Gene Response to Chemical Mixtures .......................... 73
Hormone Production ............................................................ 78
Discussion ................................................................................. 80

vi

Dose and Time Dependent Patterns ........................................... 80

Chemical Treatments ............................................................ 83
Conclusions ................................................................................ 91
Acknowledgements ....................................................................... 91
References .................................................................................. 92

CHAPTER3
MODULATION OF STEROIDOTENIC GENE EXPRESSION AND HORMONE
PRODUCTION OF H295R CELLS BY PHARMACEUTICALS AND OTHER

ENVIRONMENTALLY ACTIVE COMPOUNDS .......................................... 96
Introduction ............................................................................... 97
Materials and Methods ................................................................. 101

Test Chemicals .................................................................. 101
Experimental Design .......................................................... 101
Cell Viability/Cytotoxicity ..................................................... 104
RNA Isolation .................................................................. 104
cDNA Preparation ............................................................. 105
Real-time PCR .................................................................. 105
Hormone Quantification ...................................................... 106
Statistical Analysis ............................................................. 107
Results .................................................................................... 108
Antibiotic Exposure ............................................................ 108
Hormone Therapy Drugs ..................................................... 109
Other Pharmaceuticals and Environmentally Active Compounds ...... 110
Pattern of Responses to Chemical Mixtures ................................ 113
Dose Response Analysis ...................................................... 117
Relationships Between Gene Expression and Hormone Production... 122
Discussion ................................................................................ 123
Pattern Responses by Group of Chemicals ................................. 126
Effects of Drugs Mixtures ..................................................... 131
Dose Response Analysis ...................................................... 133
Conclusions .............................................................................. 134
Acknowledgements ..................................................................... 1 3 5
References ................................................................................ l 36
CHAPTER 4

IN VITRO MODULATION OF ENDOCRINE FUNCTION IN H295R CELLS BY
EXTRACTS OF WATERS FROM THE VICINITY OF HONG KONG, S.A.R.,

CHINA ............................................................................................. 142
Introduction .............................................................................. 143
Materials and Methods .................................................................. 146

Sample Collection .............................................................. 146
Extract Preparation ............................................................. 148
H295R Cell Bioassay .......................................................... 150
Hormone Quantification ....................................................... 151
Statistical Analysis ............................................................. 152

vii

Results .................................................................................... 1 52

Discussion ................................................................................ 1 59
Conclusions .............................................................................. 160
Acknowledgements ..................................................................... 161
References ................................................................................ l 63
SUMMARY AND CONCLUSIONS ....................................................... 167

viii

LIST OF TABLES

CHAPTER 1
Table 1.1 Enzymology of steroid production ................................................. 25
Table 1.2 The adrenal glands ................................................................... 39
CHAPTER 2
Table 2.1 Chemical mixtures exposure ....................................................... 64

Table 2.2 Gene expression in H295R cells exposed to single chemicals and to binary
mixtures ............................................................................................. 74

Table 2.3 Hormone concentrations in media from H295R cells treated with single
chemicals or in binary mixtures ................................................................. 79

Table 2.4 Effects and interactions of single and mixture chemical exposures on

steroidogenic genes in H295R cell line and hormone
production .......................................................................................... 85
CHAPTER 3

Table 3.1 Pharmaceuticals and environmentally active compounds used to expose
H295R cells ....................................................................................... 102

Table 3.2 Gene expression and hormone production in H295R cells exposed to single
antibiotics ......................................................................................... 1 l 1

Table 3.3 Gene expression and hormone production in H295R cells exposed to single
hormone therapy drugs ......................................................................... 112

Table 3.4 Gene expression and hormone production in H295R cells exposed to single
drugs .............................................................................................. 115

Table 3.5 Gene expression and hormone production in H295R cells exposed to single
chemicals and to binary mixtures ............................................................. 116

Table 3.6 Pearson correlation matrix for steroidogenic genes and steroid hormones for
all chemical treatments ......................................................................... 124

Table 3.7 Pearson correlation matrix for steroidogenic genes and steroid hormones for
the antibiotic treatments ........................................................................ 125

ix

Table 3.8 Pearson correlation matrix for steroidogenic genes and steroid hormones for

the hormone therapy treatments ............................................................... 126
CHAPTER 4

Table 4.1 Sampling points for marine waters in Hong Kong, SAR, China ............. 155
Table 4.2 Gene expression results for methanolic water extracts ........................ 157

Table 4.3 Hormone Production in H295R cells exposed to methanolic extracts of
marine waters from Hong Kong ............................................................... 158

LIST OF FIGURES

CHAPTER 1

Figure 1.1 Simplified diagram depicting the major glands of the endocrine system in
charge of the regulation of homeostasis and reproductive functions in humans and '
animals ............................................................................................... 6

Figure 1.2 The role of hormones selecting targets and delivering the hormonal

message ............................................................................................... 9
Figure 1.3 Different mechanisms of hormonal signaling ................................... 10
Figure 1.4 Chemical structure of representative hormones ................................ 12

Figure 1.5 Protein synthesis. After DNA replication a transcription process translates

DNA into mRN A to be translated to protein in the ribosome ............................... 14
Figure 1.6 Mechanism and regulation ofhormone release....................................17
Figure 1.7 Mechanism of action of steroid hormones ...................................... 19

Figure 1.8 Cyclic AMP second messenger system ......................................... 20
Figure 1.9 Synthesis of several adrenal steroid hormones from cholesterol..............23

Figure 1.10 Chemical structure of the Cyclopentaneperydrophenantrene ring. .......2.4

Figure 1.11 Chemical structure of several known endocrine disrupter

compounds ......................................................................................... 34

CHAPTER 2

Figure 2.1 Alterations in expression of steroidogenic genes in H295R cells exposed to
a range of concentrations of forskolin for 24 or 48 h ........................................ 72

Figure 2.2 Potential mechanism for super-induction of CYP11B2 by a mixture of

forskolin and ketoconazole ...................................................................... 76
Figure 2.3 Principal pathways in steroid biosynthesis ...................................... 86
CHAPTER 3

Figure 3.1 Dose-response curve for the expression of steroidogenic genes and
hormone production after 48h exposure with different concentrations of
Ethynylestradiol ................................................................................. 1 18

xi

Figure 3.2 Dose-response curve for the expression of steroidogenic genes and
hormone production after 48h exposure with different concentrations of
Cyproterone ....................................................................................... 1 19

Figure 3.3 Dose-response curve for the expression of steroidogenic genes and
hormone production after 48h exposure with different concentrations of

Ethynylestradiol ................................................................................. 121
CHAPTER 4

Figure 4.1 Enzymes, substrates and products of the steroidogenic pathway in the
different zones of the human adrenal cortex ................................................. 147

Figure 4.2 Marine water monitoring stations in Hong Kong and Sampling points for
endocrine disruption evaluation ............................................................... 149

Figure 4.3 Gene expression and hormone production for methanolic extracts from

water samples from major water treatment plants in Hong Kong, SAR,
China .............................................................................................. 154

xii

ACETA

AhR

AMG

AMOXI

AMV

AN OVA

AR

ATCC

ATP

CAF OS

cAMP

CYP

CEPHA

CLOFI

CYPROT

DEET

DEPC

DEXA

DHEA

DMSO

ABBREVIATIONS

Acetaminophen

Aryl hydrocarbon Receptor
Aminoglutethimide

Amoxicillin

Avian Myeloblastosis Virus
Analysis of Variance

Androgren Receptor

American Type Culture Collection
Adenosine Triphosphate
Concentrated Animal Feeding Operations
cyclic Adenosine Monophosphate
Cytochrome P450

Cephalexin

Clofibrate

Cyproterone
3-methyl-N,N-diethylbenzamide
Diethylpyrocarbamate
Dexamethasone
Dehydroepiandrosterone

Dimethylsulfoxide

xiii

DNA

DNAse

dNTP

DOXYC

EDCs

EDSTAC

EDTA

E2

EE2

EEC

EIA

ELISA

ER

ERAS

ERY

FOR

FLUOX

GMP

HMGR

HRC

HSP

IBUPR

ITS

Deoxyribonucleic acid
Deoxyribonuclease
Deoxyribonucleotide triphosphate
Doxycycline

Endocrine Disrupting Compounds
Endocrine Disruptor Screening and Testing Advisory Committee
Ethylenediaminetetraacetic Acid
Estradiol

Ethynilestradiol

European Economic Community
Enzyme immunoassay
Enzyme—Linked lmmunoSorbent Assay
Estrogen Receptor

Environmental Risk Assessments
Erythromycin

F orskolin

Fluoxetine

Guanosine Monophosphate
3-Hydroxy-3-Methyl—Glutaryl-C0A Reductase
Hormone Receptor Complex

Heat Shock Protein

Ibuprofen

Insulin, Transferin, Selenium

xiv

Jak/STAT
KETO
LDLs
MeOH
mRNA
MET

NCI
NHEERL
NSAAID
0RD

OXY

PAHs
PBDEs
PCBs

PKA

PKC
Q-RT-PCR
SALBU
SAR

SF-l

SSDS

StAR

Janus Kinase/ Signal Transducers and Activators of Transcription
Ketoconazole

Low Density Lipoproteins

Methanol

messenger Ribonucleic Acid

Metyrapone

National Cancer Institute

National Health and Environmental Effects Research Laboratory
Non-Steroidal Analgesic Antiinflamatory Drugs
Office of Research and Development
Oxytetracycline

Progesterone

Polycyclic Aromatic Hydrocarbons
Polybrominated Diphenylethers

Polychlorinated Biphenyls

Protein Kinase A

Protein Kinase C

Quantitative Real Time Polymerase Chain Reaction
Salbutamol

Special Administrative Region

Steroidogenic Factor 1

Strategic Sewage Disposal Scheme

Steroidogenic Acute Regulatory Protein

XV

STW

TBT

ThR

TRENB

TRIME

TYL

USEPA

USFDA

WWTP

ZEARA

System Treatment Works

Testosterone

Tributylin

Thyroid Receptor

Trenbolone

Trimethoprim

Tylosin

United States Environmental Protection Agency
United States Food and Drug Administration
Wastewater Treatment Plant

a-Zearalanol

xvi

INTRODUCTION

Daily, a large number of compounds synthetically derived or extracted from natural
materials are being discovered, designed, produced and used in order to satisfy human’s
necessities. An unsurprising but unintended consequence of the increasing demand for
the use of these compounds has been the introduction of them and/or their metabolites
into the environment. For years it has been known that several of these synthetic and
naturally occurring chemical substances in the environment are disrupting the normal
functions of the endocrine system and its hormones in humans and wildlife. An
endocrine disruptor compound is a chemical substance that interferes with, or has
adverse effects on, the production, distribution, or function of these hormones. Clearly,
interference with or damage of hormone could have major impacts on the health and
reproductive system of humans and wildlife.

Endocrine Disrupting Compounds (EDCs) include a broad range of substances
with different chemical structure and physico-chemical properties which define their
potential. Human activities are the current major sources of concern although a wide
range compounds are also produced naturally. EDCs can be found in air, water, soil,
sediment, food and consumer products, and their potential effects of greatest concern
are reproductive malfunction and developmental disorders in humans and wildlife.
Despite the wide range of studies that have been conducted in this area, in many cases
there is still insufficient data to demonstrate specific associations between
environmental exposure and endocrine-mediated adverse effects.

It has been established that there are different ways in which synthetic or

naturally occurring chemicals can affect the endocrine system. Direct interaction with

hormone receptors such as ER, AR, and ThR are the most studied mechanisms
however, there are other, indirect mechanisms that do not involve contact with any of
these receptors, and still the compounds may produce disruption of several endocrine
activities, such as producing adverse effects on the enzymes involved in the hormone
synthesis and their metabolism.

Because most of the bioassays available to evaluate endocrine disruption are
based solely on direct interaction with hormone receptors, the main objective of this
dissertation is to present research centered on the evaluation, validation and application
of a new method that integrates the analysis of potential effects of EDCs on steroid
production exerted by direct-acting hormone mechanisms as well as other indirect
mechanisms or transduction pathways. The evaluated system is the H295R cell line
which not only has the ability to express all the key enzymes required for steroid
hormone synthesis, transport and metabolism, but is also capable of producing all the
major hormones responsible for homeostatic and reproductive activities in humans and
wildlife. This cell line therefore offers an integrative system to evaluate at the same
time several important endpoints in endocrine-disruption including gene expression,
enzyme activity and hormone production.

Chapter 1 of this dissertation presents a complete description of hormone
production and EDC mechanisms of action, the H295R cell system, and the molecular
techniques and criteria used in this EDC screening assay system. The biomolecular
methods include Quantitative-Real Time-Polymerase Chain Reaction (Q-RT-PCR) for

the evaluation of the expression of genes encoding for key enzymes driving

steroidogenesis, and the Enzyme-Linked Immunosorbent Assay (ELISA) used for
quantification of hormone production.

Chapter 2 presents an evaluation of the H295R cell system using four model
chemicals known to be inducers or inhibitors of hormone production. Exposures with
individual model chemicals as well as with binary mixtures of inducers and inhibitors
were conducted and the results evaluated. This chapter addresses the importance of the
evaluation of mixture effects since EDCs do not generally occur in the environment
individually but in complex mixtures, and they may interact synergistically increasing
the potential to exert stronger adverse effects. Moreover, it corroborates the fact that
every EDC reaching the environment varies in potency and in the level of exposure
required to produce an adverse effect. This portion of the dissertation has been
published in the journal Ecotoxicology and Evironmental Safety, 65 (3), 293-305.

Pharmaceuticals, one of latest emerging group of contaminants of
environmental concern, were among the chemicals chosen for the validation of the
H295R cell system whose results are described in Chapter 3. The potential endocrine
disrupting effects of 15 of the most commonly used pharmaceuticals, including
prescribed and over the counter drugs, and some natural estrogenic compounds were
evaluated at high and environmentally relevant concentrations. Antibiotics of medium
and broad spectrum, non steroidal analgesic anti-inflammatory drugs (N SAA), growth
promoters, antidepressants, birth control compounds, B-blockers and hormone therapy
drugs were part of the tested group. The steroidal side effects of these chemicals
designed to execute specific biological functions in animals and humans were

established, as well as the variation of endocrine responses with respect to the exposed

doses. Responses to mixtures of chemicals were also compared to individual compound
behavior.

Chapter 4 describes the applicability of the H295R cell system to relevant
environmental samples. H295R cells were exposed to extracts of water samples
collected in several waste water treatment plants before and after treatment, fish culture
zones, marine disposal areas and other aquatic environments in Hong Kong S.A.R,
China. The potential of compounds present in these extracts to cause endocrine
disruption was used to evaluate the relevance of EDCs in waters collected from one of
the most polluted areas in Asia.

Studies presented in this dissertation confirm that the H295R assay system
allows simultaneous analysis of the expression of key steroidogenic genes, enzyme
activities and hormone production, and that this assay can be used as a cost-effective,
sensitive and integrative screening system to evaluate the many potential effects of

chemicals or mixtures of chemicals that can lead to endocrine disruption.

Chapter 1

STEROIDOGENESIS, ENDOCRINE DISRUPTION AND THE H295R

CELL SYSTEM

INTRODUCTION

The Endocrine System

The endocrine system is the machinery in charge of the regulation coordination and
control of several important biological functions in the organism such as growth and
development, mood, tissue function, metabolism as well as sexual function and
reproductive processes (Figure 1.1). This system is composed of a collection of glands
that secrete chemical messengers called hormones that transfer information and
instructions from one set of cells to another. The major glands of the endocrine system
are the pineal body, hypothalamus, pituitary, thyroid, parathyroid, thymus, adrenals,
pancreas (although it is also part of the digestive system because it also produces and
secretes digestive enzymes), and the reproductive glands ovaries and testes (1).
Combine together, more than fifty hormones are secreted by the endocrine system and
released into the bloodstream. Each hormone is programmed to reach a target organ
which has specific cells genetically programmed to receive and respond exclusively to
its message. On their way to the target cells, many hormones bind to specific proteins,
known as carrier proteins, which act as vehicles of transport and at the same time
control the amount of hormone available to interact with the target cells (2). Usually,

hormones linked to carrier proteins are more stable

 

4' Hypothalamus ‘;

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Pineal Gland
Pituitary
Ovaries Adrenals Thyroid
Female

 

Pancreas

 

 

 

 

Testes

 

Male

Figure 1.1 Simplified diagram depicting the major glands of the endocrine system in
charge of the regulation of homeostasis and reproductive functions in humans and

animals.

 

increasing their half-life in the circulation. It has been also suggested that some binding
proteins can function in targeting and trafficking of hormones (3).

The endocrine system uses cycles and negative feedback to regulate
physiological functions (4). Cycles of secretion maintain physiological and
homeostatic control and they may last hours or months. Hibernation, mating behavior
and body temperature are examples of activities controlled by biological cycles (5).
Although the instances of positive feed-back certainly occur, negative feedback
regulates the secretion of almost every hormone. When hormone levels reach a certain
‘normal’ concentrations, further secretion is controlled to maintain that necessary level
of hormone in the blood. This down regulation of hormone production may involve the
hormone itself or another substance in the bloodstream (6-7). Hormone levels can also
be influenced by factors such as stress, infection, and changes in the balance of fluid
and minerals in the organism.

The endocrine and nervous systems work in parallel to control growth and
maturation along with homeostasis. The nervous system coordinates rapid and precise
responses to stimuli using action potentials, while the endocrine system maintains
homeostasis and long-term control using chemical signals (1, 8). Thus, nervous
messages are immediate and of short duration while hormonal effects still prevail

although hormonal levels return to basal values.

Hormones
A hormone is a chemical substance synthesized by particular endocrine glands

that later enters the bloodstream to be carried to a target tissue or cell type. The target

tissues have specific receptors that bind these messenger chemicals (9) (Figure 1.2).
This series of events defines the so called endocrine and neuro-endocrine signaling
mechanisms. Some hormones are not secreted into bloodstream; instead, they reach
their nearby target cells by diffusion. The effects generated by binding to the specific
receptors establish the different signaling mechanisms used by hormones. A simplified
mechanism of selecting target hormonal receptors is shown in Figure 1.3. An intracrine
mechanism involves the production and use of the signal/hormone within the same cell.
In autocrine signaling the cell produces and releases its own signal/hormone. A
paracrine mechanism is established between neighbor cells within a tissue or organ (10-
11).

The effects of hormones are broad and can include induction or inhibition of
cell death, stimulation or suppression of growth, regulation of metabolism, control of
life stages such as puberty and menopause, and in several systems hormones are
capable of regulating the production and release of other hormones (12). Although
hormones are produced mostly by classical endocrine glands other ‘non-endocrine’
organs such as the brain, thymus, heart, lungs, liver, kidneys, placenta and skin are also
capable of producing and releasing hormones (13-14).

Hormones are present at all times in the bloodstream, albeit at low
concentrations, in order to maintain receptors in the target tissues and to keep the tissue
‘prepared’ to mount a response. They are normally found in plasma and interstitial
tissues in trace amounts ranging between 10'9 — 10'6 g/l (15). The physiological effects

of hormones depend mostly on their concentration. Hormonal over- or under-

production, as well as non-functional receptors that make the target cells un—sensitive to

hormonal messages,

Secreting cell

Receptor

Hormone I
‘l

I

. r _ 6

Blood vessel

 

 

  
  
  

       
 

\‘9

' "1r,— .. _« —_ A. ._.. _

Not a target cell

 

Figure 1.2 The role of hormones selecting targets and delivering the hormonal
message. Once released to the blood stream hormones bind specific receptors on
target cells only.

Hormone

  

Receptor

 

Autocrine b

Blood Vessel

 

 

9c
is

Paracrine c

Figure 1.3 Different mechanisms of hormonal signaling. a) A chemical messenger
acts inside the secreting cell. b) Cells secrete chemical messenger that signal the same

cell. c) The target cell is close to the signal releasing cell.

10

are the most common causes of endocrine-related problems (16). Therefore, precise
control of circulating hormonal levels is crucial. In general, the concentration of a
hormone in the bloodstream is determined by three factors (1 7):
I Rate of production: Regulated by positive and negative feedback
mechanisms.
I Rate of transport: Determined by blood flow.
I Rate of degradation and excretion: Established by metabolism and
elimination processes, which determine hormone half-life.
The function of hormones is to serve as a signal to target cells to maintain homeostasis
and drive and coordinate changes in an organism. Hormone actions are determined by
the pattern of hormone secretion and by the signal transduction capabilities of the

receiving tissue.

Types of Hormones
Endocrine hormones are grouped into four major structural groups (18):
I Polypeptides, proteins and glycoproteins
I Amino-acid derivatives
I Fatty acid derivatives - Eicosanoids
I Steroids

Figure 1.4 shows chemical structures of representative hormones.

ll

OH

HO

HN

HO \

Adrenaline ”

 

Testosterone b Prostaglandin Elc

Figure 1.4 Chemical structure of representative hormones. a) Amino-acid derivative
hormone and neurotransmitter which drives the response to stress. b) Steroid hormone
from the androgenic group. It is the principal male sex hormone and plays key roll in
health and well being in male and female organisms. c) Fatty acid derivative hormone
important in the constriction and dilatation of muscle and mediator in inflammatory
process.

12

Peptide and amino-acid derivative hormones are secreted by the pituitary,
parathyroid, thyroid, heart, stomach, liver, kidneys and adrenal medulla. Polypeptides
and proteins are products of translation and vary considerably in size. The amino acid
sequence information of a protein is contained in the coding region of the gene that
codes for the protein in sequences of bases known as the genetic code; the code is
copied from DNA into mRNA by transcription and the mRNA coordinates the protein
synthesis by the process of translation (Figure 1.5). They can be as small as peptides
formed by 3 amino acids or as large as glycoproteins formed by multisubunits of
hundreds of amino acid residues. Several hormones belonging to the peptide group are
synthesized in the endoplasmic reticulum as pro-hormones, to later go through
proteolytic changes and convert them to the mature or acting form of the hormone; in
other cases the hormone is part of the sequence of a larger precursor that is '
proteolytically cleaved several times to release the active hormone (19). Once
synthesized, some peptide hormones are sent to the Golgi apparatus and packaged into
secretory vesicles for export (20). Because most of the peptide hormones circulate un-
attached to carrier proteins in the blood stream, their half-life is typically in the range of
a few minutes.

Tyrosine, tryptophan and glutamic acid are the amino acids from which several
hormones are synthesized. Thyroid hormones and catecholamine are derived directly
from tyrosine. Catecholamines such as epinephrine and norepineprhine have a dual
function; they can function as hormones and as neurotransmitters (21). While the half-
life of thyroid hormones is in the order of a few days, catecholamines are rapidly

degraded with half lives in the range of a few minutes (22-23). Tryptophan is the

13

 

Replication Transcription Translation
(RNA synthesis) (Protein synthesis)

lg.

 

 

 

 

 

 

 

 

.’ DNA ooooooooo’ mRNA .——§ PrOtein

 

 

 

 

Figure 1.5 Protein synthesis. After DNA replication a transcription process
translates DNA into mRNA to be translated to protein in the ribosome.

14

precursor of serotonin, which plays an important role in the regulation of mood and
sleep; tryptophan is also a precursor of melatonin which communicates information
about environmental lighting (24). Glutamic acid is converted to histamine, involved in
immune responses as well as regulating physiological functions in the gut and acting as
neurotransmitter (25).

Eicosanoid hormones are mostly derived from the arachidonic and other
essential fatty acids and are found virtually in all tissues and organs. Among the
eicosanoid hormones are prostaglandins, prostacyclines, thromboxanes and leukotrienes
(26). They are important agents in allergic and inflammation processes and control
blood flow and pressure. Leukotn'enes are made by leukocytes and are extremely
potent in vasoconstriction (27).

Steroid hormones are derivatives of the lipid cholesterol. They are synthesized
and secreted mainly by gonads and the adrenal glands (28). Gonad tissues specifically
produce the sex steroids estrogen and androgen that are responsible for female and male
secondary sexual characteristics. Female gonads also synthesize progestins,
responsible for the maintenance of pregnancy (29-31), while the adrenal cortex
synthesizes mineralocorticoids such as aldosterone, which increases sodium, chloride
and bicarbonate absorption to maintain blood flow and pressure. The glucocorticoids,
such as cortisol, are also produced by the adrenal cortex and their function is to
promote gluconeogenesis and fat and protein degradation (32). Once produced, steroid
hormones are immediately released and depending on the species and the hormone may
be bound by specific plasma protein carriers (33). In general steroid hormones are

inactivated by metabolic transformations and excreted in urine or bile (34).

15

Hormone Release

Internal signals or external stimuli from the environment such as smell, light,
temperature and sound trigger electrical responses in the nervous system causing the
release of ‘releasing hormone’ in the hypothalamus which are transported to the
pituitary through the portal system (10). This event induces the release of the trophic
hormones that are responsible for the release of the ultimate hormone by the target
glands (Figure 1.6). The critical characteristic of this domino effect is the intensity of
the response in each event. Releasing hormone is produced in nanograms amounts,
which induces production of the trophic hormone at the microgram level while the final
hormone is produced in miligram quantities. This is a good example of ‘amplified
responses’. The release of hormones can also be stimulated by the levels of several
metabolites (35).

In general, hormone secretion is a chain of events meticulously coordinated and

regulated in a rhythmic manner.

Mechanism of Hormone Action

Hormones induce a trigger effect in order to modulate the activity of specific
target cells. Most of the hormones act by binding to specific receptors, which are
proteins that are normally present in small numbers in the target cells and may be of
two kinds, plasma membrane receptors, also known as cell-surface receptors, and
intracellular receptors. Therefore, there are two mechanisms by which hormones can
activate/inactivate enzymes, alter membrane permeability and influence gene

expression

16

ti

Short loop
feedback signal

Inputs

./I\

 

 

Hypotalamus

detector

 

 

Neurohonnone

I

 

 

 

Inhibition

(I

 

 

Pituitary gland

control centre

 

 

Trophic hormone

 

 

Target gland

Thyroid, adrenal cortex, gonads

 

 

 

Figure 1.6 Mechanism and regulation of hormone release. External or internal inputs
induce the hypothalamus to produce releasing hormones which stimulate the pituitary
gland to release trophic hormones that consequently induce the activity of target

endocrine glands.

producing significant changes in target cells which translate later into a variety of

I

Raised blood levels of hormones

Utilization of hormones

Lowered blood levels of
honnones

observed physiological effects (36).

Non-steroid or water soluble hormones, because of their lipophobicity, do not

diffuse across the cell membranes; usually, they interact with cell-surface receptors.

17

A

 

Stimulation

Tl

 

 

Most of the receptors for peptide and protein hormones are G-protein linked receptors
which use a second messenger to transmit the hormone signal from the outside to the
inside of the cell. Hormone-receptor interactions provoke the dissociation of the
intracellular trimeric G protein, which results in the opening of ion channels or the
activation of membrane enzymes that may stimulate or inhibit the production of second
messengers. As is shown in Figure 1.7, the activated molecules or second messengers
then cause the phosphorylation of specific proteins that finally elicit the response.
Calcium, CAMP, GMP, and inositol triphosphate are the most common second
messengers (3 7).

Thyroid and steroid hormones, because of their lipophilicity, are believed to
pass passively through the plasma membrane and once inside the cell bind to specific
intracellular receptors forming an activated hormone-receptor complex, which binds to
DNA activating or suppressing the expression of specific genes (38) (Figure 1.8). Type
1 receptors are linked to heat shock proteins (HSPs) and are located in the cytoplasm;
this type of receptor is used for glucocorticoids, mineralocorticoids, androgens and
progestins; the estrogen receptors usually travel between the cytoplasm and nucleus.
Once the steroid hormone-receptor complex is formed the HSPs are released and the
receptor undergoes dimerization with another receptor. The dimeric structure

translocates to the nucleus where it binds a specific DNA sequence. Thyroid hormone

18

 
  
     
  
       
  
  
  

  

3. Transcription
H-R complex binds
chromatin & produces
mRNA

  

1. Uptake
Steroid hormone 4. mRNA leaves

nucleous

 

Steroid Receptor

 

 

  

2. Translocatlon
Hormone- Receptor
Complex enters nucleus

 
 

  
  

5. Translation
Ribosomes translate
mRNA into nmtein

Figure 1.7 Mechanism of action of steroid hormones. After binding of the hormone to
the receptor the formed Hormone-Receptor Complex (HRC) moves to the nucleus. A
dimmer of HRC interacts with hormone-responsive elements on specific genes. As a
consequence, template sites on DNA habilitate sites for RNA polymerase and increase
transcription. Once produced, mRNA leaves the nucleus and undergoes translation in
the ribosome.

19

Hormone-Receptor complex

 

\ Activation of Adenylate-cyclase by

_/
G-protern ATPl * G-protein

AMP CAMP

Protein kinase A

I

Protein —’ Phosphorilated protein —’ Cellular response

T—I

Phosphoprotein
phosphatase

Figure 1.8 Cyclic AMP second messenger system. The enzyme adenylate
cyclase catalyses the production of CAMP from ATP. The CAMP produced
then activates protein kinases which phosphorylate intracellular proteins to
alter their activity and produce a cellular response.

20

and retinoic X receptors are mostly found in the nucleus, bound to DNA and are known
as type 2 receptors. In contrast to steroid receptors, type 2 receptors undergo
dimerization with other non-identical receptors forming heterodimers; in some
instances they may initiate transcription in the monomeric form (39). Despite the ability
of lipophilic hormones pass through the cell membrane, some steroid or thyroid
hormones also interact with cell-surface receptors to produce rapid non-genomic
responses in target organs or cells. They may stimulate the production of protein
receptors at the cell surface level or affect the intracellular production of protein kinases
and other proteins needed in the action of peptide hormones (40).

After the interaction with the hormone-receptor occurs, both elements form a
single condensed structure that induces vesicular formation followed by endocytosis.
The hormones may be degraded by cell-surface enzymes and the receptors re-used or
catabolised by lysosomic enzymes. Second messengers may be disintegrated or

inactivated by phosphorylation/dephosphorylation processes (41 ).

Metabolism and excretion of hormones

Inactivation or degradation of hormones must occur in order to ensure steady-
state levels of hormones in the bloodstream this is achieved using feedback
mechanisms. Hormone inactivation and catabolism may occur in peripheral organs or
tissues such as liver and kidney, but can also occur in target tissues immediately after
the hormone trigges of the biological responses. The half-life of hormones in

circulation is directly related to hormone action (42).

21

Peptide and protein hormones are degraded by peptidases at specific structural
points, like carboxy or amino terminal groups (43). Usually, steroidal hormones are not
re-used and they must be inactivated first, and then converted to a more soluble form in
order to be excreted. P450 enzymes drive the inactivation of steroid hormones through
hydroxylation processes and then transferase enzymes conjugate these inactive
metabolites with glucoronic or sulfate groups to make them hydrophilic so they can be

eliminated via urine and bile (44).

STEROIDOGENESIS

The biological synthesis of steroids is termed steroidogenesis. Steroid hormones
are derivatives of cholesterol synthesized in the adrenal cortex and gonads, and in
smaller quantities by a variety of other tissues such as brain and placenta (Figure 9).
Synthesis occurs by two major types of enzymes located in both, mitochondria and
endoplasmic reticulum (45-46). The identified sources of cholesterol include
cholesterol synthesized de novo from acetate within the cell, cholesterol esters from
lipid droplets and from cholesterol-containing low density lipoproteins (LDLs), are
considered the main source of cholesterol in humans (47).

Initially, a chain of reactions activated by trophic hormones hydrolyze
cholesterol complexes to form free cholesterol. This free cholesterol, by an assisted
mechanism, is transported to the inner mitochondria where it is converted by the P450
side chain cleavage enzyme to pregnenolone, not a hormone itself, but a precursor for

the synthesis of all steroid hormones (47-48). Subsequent biosynthetic steps involving

22

a movement of the various substrates thru the enzymatic batteries located in the

end0plasmic reticulum

 

 

 

 

CYPl 1 A Cholesterol
l7a-OH- CYPI 7
Pregnenolone Pregnenolone ' DHEA
l 3,6HSD2 l 3BHSD2 13BHSD2
CYP] 7 CYP] 7 .
Progesterone > 17a-OH- > Androstenedrone
Progesterone
CYP21 l CYP21 ll 7BHSD1
l l-Deoxy- 1 l-Deoxy- Testosterone
Corticosterone Corticosterone
l CYPllBl l CYPllBl lap”
Corticosterone Cortisol 17 B-Estradiol
CYPIIBZ
Aldosterone
Zona Glomerulosa Zona F asciculata Zona Reticularis

Figure 1.9 Synthesis of several adrenal steroid hormones from cholesterol. Enzymes
leading the production of precursors and active hormones are shown. Chemical
structures are presented only for terminal main hormones such as aldosterone and
cortisol and for main precursors such as corticosterone an androstenedione.

23

 

and mitochondria, give origin to all steroid hormones (49).

Classification of Steroid Hormones

Steroid hormones are classified according to their physiological behavior, a

consequence of their actions on one or more specific steroid hormone receptors (50):

Progestins: Essential for reproduction
Mineralocorticoids: Maintain electrolyte balance
Glucocorticoids: Mobilize carbohydrates

Androgens: Induce male secondary sex characteristics

Estrogens: Induce female secondary sex characteristics

Since they arise from a common series of pathways, all steroid hormones share

the cyclopentanoperhydrophenanthrene chemical structure (Figure 10).

    

Fr

Figure 1.10 Chemical structure of the Cyclopentaneperydrophenantrene ring.

Enzymology of the Steroid Production

Steroid oxydoreductases and Cytochrome P450 (CYP) are the two major types of

enzymes driving the pathways of steroid hormone biosynthesis. The capacity of a cell

24

to synthesize specific steroids is directly linked to its enzymatic expression;
steroidogenic capacity then, is regulated mainly by tissue and cell specific expression of
enzymes. Each enzyme involved in steroid production is encoded by one specific gene
(Table 1.1), which controls and regulates its expression in different tissues and organs

(49). The group of

Table 1.1 Enzymology of steroid production.

 

 

Functional name Common name Standard name/Gene
Desmolase; side chain cleavage P4505cc CYPl 1A
enzyme
313- hydroxyseteroid-dehydrogenase 3B-HSD2 3BHSD2
17-d-hydroxylase/ 1 7,20 lyase P450 cr7 CYP17
21-hydroxylase P450C21 CYP21
1 IB-hydroxylase P450113 CYPl 1B1
Aldosterone synthase P450] 1 AS CYPl 182
Aromatase P450arom CYPl 9
l 711-hydroxysteroid-dehydrogenase l 70-HSD(1 -7)a 1 7B-HSD(1 -7)

 

a Cytochrome P4505 and oxydoreductases controlling the production of steroid
hormones in the adrenal cortex. Each one of the steroidal P450 enzymes are encoded
by a single gene, instead, the oxydoreductases are usually encoded by different genes,
one for each isoform or isozyme. Human 17[3-hydroxysteroid-dehydrogenase has 7
known isozymes.

enzymes in the adrenal cortex and testis does not change during adult life. In contrast,
in the ovaries the amount of enzymes changes dramatically, especially during the final
stages of follicle development (51). Steroidogenic factor 1 (SF1) has been identified as
the transcription factor required for tissue-specific expression of steroid P4505 enzymes
as well as the gonadal and adrenal-specific isoforms of oxydoreductases. Despite the

mandatory presence of SFl for cell specific adrenal and gonadal expression, there are

other factors necessary for determining the amount and specificity of steroidogenic

25

gene expression (52). One unique property of several of the steroidogenic enzymes is
that they may catalyze more than one step in the pathway of steroid production.

The important role of enzyme expression in regulation of steroidogenesis is
demonstrated by the fact that the hormonal output is mainly regulated by enzyme
dependent events (51), such as:

I Substrate availability, which depends on enzyme-depended cholesterol
mobilization.

I Steroidogenic enzyme level, determined by the mRNAs encoding the enzymes.

I Steroidogenic enzyme activity, determined by intracellular conditions.

I Tissue growth, determined by cell division and directly related with enzyme

production.

Cytochrome P450 (CYP): These are oxidative enzymes, found mostly in the inner
membrane of mitochondria or in the endoplasmic reticulum. Their main characteristic
is wavelength of maximum absorption at around 450nm when the heme iron is reduced
and complexed to carbon monoxide, this is the reason they have been termed “Pigment
at 450nm” or P450. Hydroxylation is the most common reaction catalyzed by P450
enzymes but members of this superfarnily are able to perform a wide range of reactions
such as sulfoxidation, deamination, dehalogenation, N-oxydation or dealkylation (49-
53).

Besides driving biosynthesis and catabolism of steroids, CYP enzymes are also
involved in several other important physiological activities in mammals such as drug.

metabolism, cholesterol biosynthesis and blood homeostasis to name a few. Their

26

actions are also very important in metabolic processes of insects and in higher plants

due to their involvement in the synthesis of numerous secondary metabolites like

flavonoids, alkaloids and terpenoids (54-58).

The major steroidogenic CYP enzymes are:

P45 Oscc: This enzyme initiates the biosynthesis of all steroid hormones. In the
inner mitochondrial membrane, cholesterol is converted to the precursor
pregnenolone through monooxygenation processes that include hydroxylations
at C-22 and C-20 ending with cleavage of the C-20, C-22 bond. This step is
considered by many, the rate-limiting step of steroidogenesis. P4505cc is
encoded by the gene CYPl 1A and is expressed in the three zones of the adrenal
cortex, ovaries, testis and brain. Genetic lesions affecting the activity of this
enzyme are mostly rare, but if present, may result in an inability to synthesize
any steroid hormone with consequent immediate death due to mineralocorticoid
deficiency (49, 59-60).

P450c1 7: Encoded by the gene CYP17, this l7-alpha—hydroxylase is required
for androgen production and regulation of substrate supplies for aromatization,
as well as for cortisol biosynthesis. Cleavage of C17-C20 bond in C21 steroids
leads to androgenic production, while their 17-alpha-hydroxilation produces
cortisol. This enzyme is well expressed in zona fasciculate and zona reticularis
of the adrenal cortex and in smaller amounts in ovaries (49, 61). This enzyme is
expressed in most steroidgoenic tissues. Some vertebrate species, like rats, do

not express P450cl7; thus, corticosterone rather than cortisol is the major

27

glucocorticoid. The activity of this particular enzyme is said to be strongly
affected by the intracellular concentrations of substrates and products (62).
P450c21: At the endoplasmic reticulum this enzyme executes hydroxylation on
C21 in progesterone to the formation of cortisone and cortisol precursors, 11-
deoxycorticosterone and ll-deoxycortisol, respectively; P450c21 is key in the
production not only of mineralocorticoids but also glucocorticoids and is
exclusively expressed in all three zones of the adrenal cortex. CYP21A and
CYP2lB are the genes encoding this enzyme, but only CYP21B encodes the
active form of the enzyme (49, 63). Its deficiency, the most commonly
observed genetic lesion, conduces to congenital adrenal hyperplasia, an illness
characterized by deficient gluco and mineralocorticoid production and to
excessive androgenic biosynthesis showed morphologically through
enhancement of male characteristics, also known as virilization (64-65).

P45 0c] 1 : Is the final enzyme in the synthesis of adrenal mineralocorticoids and
glucocorticoids. P450c11 exerts not only llB-hydroxylase, but also 18-
hydroxylase, and 18 aldehyde synthetase activities to mediate the conversion of
ll-deoxycortisol to cortisol and the three final steps in the biosynthesis of
aldosterone from deoxycorticosterone (66). The known two forms of this
enzyme are localized mainly in the adrenal cortex, specifically in the inner
mitochondrial membrane. Type I works directly on cortisol production, while
type II focuses on aldosterone synthesis. Although the two forms of P450c11
are different in only 32 out of the 503 arninoacids of their primary sequence,

their catalytic properties are clearly different. It has been proved that CYPl 182

28

does not use efficiently cortisone as substrate for the aldosterone biosynthesis,
therefore the main mineralocorticoid is produced from ll-deoxycorticosterone
as precursor. The deficiency in P450011 hydroxylase and aldosterone synthase
activity is the second most common cause of congenital adrenal hyperplasia, the
first one is the lack of P45021c activity (68).

P450aro: It mediates the aromatization of C18 estrogenic steroids from C19
androgens in the endoplasmic reticulum. The aromatization process involves 2
hydroxylations at C19 methyl group and a third one at C2. These
hydroxylations result in the loss of C19 and the consequent aromatization of the
A ring of the steroid (49). CYP 19 is the gene encoding for P450aro, commonly
known as aromatase. This gene is the longest of all the steroidogenic genes and
its main characteristic is the presence of alternative promoters that are used in
tissue-specific manner (69). Aromatase is widely expressed in the ovary,
mostly in the granulose cells where the major estrogen production occurs. This
enzyme is also present in many other tissues besides gonads, such as breast,

skin, placenta and adipocytes (70-71).

Oxidoreductases: These enzymes that catalyze the transfer of electrons from one
molecule, the oxidant or hydrogen donor, to another, the reductant or hydrogen
acceptor. Oxidoreductases are more commonly known as dehydrogenases. 3B-
HSDs and l7l3-HSDs are the main steroidogenic dehydrogenases. They belong to
the same protein family as the short-chain alcohol dehydrogenase reductase
superfamily. While P450 enzymes are encoded by single genes, the steroid

dehydrogenases are usually encoded by at least 2-3 homologous genes since they

29

present several isoforms in the case of 3B-HSDs, or isozymes as is the case for 170-

HSDs. The number of isoforms or isozymes varies between species (49, 51, 62).

I 3 B-HSD/isomerases: Are the enzymes catalyzing the production of the first
biologically important steroid in the pathway, progesterone. Currently two
isoforms, I and II, of 3B-HSD have been identified in humans; each isoform is
the product of a distinct gene. Only type II is expressed in the 3 zones of the
human adrenal cortex and in gonads, but not in placenta. Instead, type I is
found in skin, placenta and breast tissue. Their functions are to convert 3B-
hydroxy-S-ene steroids into 3-keto-4-ene, pregnenolone into progesterone, 170t-
hydroxypregnenolone into 17(1- hydroxyprogesterone and DHEA into
androstenedione (49, 53, 57, 72-73).

I 17B-HSDs: Their main function is controlling the last step in the biosynthesis
of all gonadal androgens and estrogens. These isozymes convert inactive 17-
ketosteroids into their active 17B-hydroxy forms; 17B-HSDs are responsible for
the interconversion of 17-ketosteroids, such as dehydroepiandrosterone,
androstenedione and estrone with the respective 17B— hydroxysteroids, like
androst-5-ene-3 B, l7B-diol and l7B-estradiol (E2) (74). Usually they are found
membrane bound or as soluble enzymes. Currently, 11 different l7B-HSDs
have been identified. Each isoenzyme presents individual cell-specific
expression, subtrate specificity and regulatory mechanisms. Among the 11
known 17B-HSDs only 3 forms actively participate in the production of gonadal
steroidal hormones, types I, III and VII (75). 17B-HSD1, which is found in

ovary, placenta and mammary glands, was the first of these ketosteroid-

30

I

dehydrogenases to be characterized. In humans, the substrate of preference for
l7B-HSD1 are estrogens and its main function is to catalyze the inter-
conversion between estrone and estradiol, 17B-HSD7 only from estrone to
estrone and l7B-HSD3 is responsible of the conversion of weak androgens into
potent androgens, that is, from androstenedione to testosterone. The androgenic

17B-HSD3 is exclusively expressed in testes (76).

Other Enzymes

In the early steps of steroid production, before the formation of pregnenolone, two
critical events, enzymatically controlled by other type of enzymes, occur. One
event is the production of cholesterol, since it is the basic building block for all
steroids, and consequently, its transport to the inner mitochondrial membrane where
all the initial enzymatic machinery for steroidogenesis is present. Cholesterol
biosynthesis is controlled by hydroxymethylglutarleoA reductase (HMGR) and its
transport to the inner mitochondria is directed by the steroidogenic acute regulatory
protein, StAR.

I HMGR: Cholesterol production is controlled by 3-hydroxy-3-methyl—
glutaryl-CoA reductase or HMGR, which is the first enzyme in the
metabolic pathway that produces cholesterol and other physiologically
important biomolecules such as non-sterol isoprenoids and coenzyme Q
(77). HMGR is a polytopic transmembrane protein driving the key step in
the mevalonate pathway and its activity is regulated by transcription,

translation, degradation and phosphorylation (78-79). Since in humans the

31

 

mevalonate pathway is the main mechanism of cholesterol production, this
enzyme is the main target in the design of hypercholesterolemia and
atherosclerosis drugs (80). The enzyme activity is mostly regulated by a
negative feedback mediated by its own products, thus in mammalian cells
this enzyme is suppressed by cholesterol derived from the internalization
and degradation of LDL (77). This enzyme can also be found in prokaryotes

and plants.

 

I StAR: The steroidogenic acute regulatory protein is a mitochondrial
phosphoprotein that defines the well considered rate-limited step in steroid
production (81). This enzyme/transport protein regulates the delivery of
cholesterol from the outer to the inner mitochondrial membrane where is
cleaved by the P4505cc also known as CYPllA enzyme. The lipid
properties of cholesterol make it difficult for it to cross the aqueous phase
between the two membranes requiring the assistance of several proteins
(82). StAR is found in the adrenal cortex and gonads where its presence
increases the steroid production. The expression of this enzyme is stimulated
by the cAMP signaling pathway and also by trophic hormones stimulation.
Patients with mutations in the StAR gene suffer from congenital lipoid
adrenal hyperplasia, which drastically impairs adrenal and gonadal

biosynthesis (83).

ENDOCRINE DISRUPTION

32

Among all the compounds released to the environment there are a range of chemicals
that have the ability to adversely affect the normal functioning of the endocrine system.
Specifically, a variety of chemicals with a diversity of physicochemical properties
(Figure 1.11) are able to interfere with endogenous hormone activities so having major
impacts on the health and reproductive functions in humans and wildlife. The ability of
these chemicals to interfere with endocrine regulatory systems has lead to their being
described as endocrine disrupting compounds (EDCs) (84-85). EDCs have been
officially defined by the US. EPA as “exogenous agents who interfere with the
synthesis, secretion, transport, binding, action, or elimination of natural hormones in
the body that are responsible for the maintenance of homeostasis, reproduction,
development and/or behavior” (86). Among the most frequent adverse effects of EDCs
postulated to occur in animals and humans are: reproductive effects, birth defects,
cancer, low sperm count, sexual dysfunction, heart disease, cognitive disorders, sex
reversal and premature puberty (87-97). The complexity of EDC effects results to a
great extent from the inherent complexity of the endocrine system and the fact that via a
variety of signaling mechanisms the endocrine system is connected to the immune and
nervous systems. As a
result some compounds classed as EDCs can also reduce the effectiveness of the
immune system increasing the incidence of infections or produce neurotoxicity (98).
Natural sources of EDCs include plants and animals as well as human activities.
A variety of naturally produced phytochemicals in foods, most of them with
‘estrogenic’ activities, may act in a similar way to estrogen due to their ability to bind

to the estrogen receptor. However, phytoestrogens are much weaker than actual

33

estrogen, so their effects are different from those of the natural hormone (99).
Moreover, the consumption of a phytoestrogen-rich diet has been linked to either
reduced or increased rates of heart disease and cancer (100-101). Good examples of

natural phytoestrogen sources include soybeans, legumes, clover, yams and flax.

Vs

Tributyltin ” Trenbolone

 

b

CI CI

0/.

Aldrin c

Cl

CI

Figure 1.11 Chemical structure of several known Endocrine Disrupter Compounds
(EDCs). a) Tributyltin, biocide used as antifoulant paint additive. b) Trenbolone,
anabolic steroid used by veterinarians on livestock to increase muscle growth and
appetite. c) Aldrin, a pesticide commonly used in crop fields.

34

Humans and animals also produce hormones naturally; they also consume hormonal
products by taking pharmaceuticals such as birth control pills and by using hormone
replacement therapy containing mixtures of estrogens, progestagens and androgens;
once they are excreted from humans and animals, these hormonally active chemicals
can easily flow into sewage treatment and drinking water systems. An area of current
high concern is the waste produced by concentrated animal feed operations (CAFOS)
since they discharge environmentally relevant doses of natural and pharmaceutically
produced hormones. Pregnant animals on CAFOS naturally produce high levels of
estrogens and several pharmaceuticals such as growth promoters and antibiotics are
administrated to maximize animal growth and health (102-106). Residues of these
chemicals can be excreted in manure and by run-off they may easily reach aquatic
environments (107-109). Since these compounds were designed to produce a
biological effect, once they reach the environment, unwanted effects on non-target
organisms may be exerted (110). Besides pharmaceuticals, some compounds used in
the cosmetic industry have also raised concern. Chemicals used in dental sealants, skin
lotions, and makeup are suspected of causing endocrine disruptor effects (111-113).
Other human activities also release synthetic compounds capable of disrupting
the normal functioning of the endocrine system. These ubiquitous EDCs are used in
plastics, food production and packaging, paints, wetting agents, carpets and firrniture,
detergents and pesticides. Phthalates, for example, are chemicals used as plasticizers to
manipulate the physical properties of plastics. Although it has been established that
human exposure does not currently appear to be toxicologically relevant, several bans

haven been introduced in Europe for these compounds in children’s toys as a

35

precautionary measure (114). Bisphenol A is widely used as an inner lining on food
and beverage cans. Despite several studies that have shown Bisphenol A to produce
hormone related effects at high doses, there is still an ongoing debate about whether or
not these results are toxicologically relevant (115-116).

Tributyltin (TBT) is a compound primarily used as an antifoulant paint additive
on ship and boat hulls, docks, fishnets, and buoys to discourage the growth of marine
organisms such as barnacles, bacteria, tubeworms, mussels and algae (117). TBT
concentrations in harbors and bays in Britain, France and the United States were
historically high enough to significantly affect oyster and mussel production (118-120).
At low levels, TBT can cause structural changes, growth retardation, and inhibit
reproduction Imposex, the development of male characteristics in females, has been
initiated by TBT exposure in several snail species (121). Other compounds, such as
brominated flame retardants used in fumiture, carpet and electronics manufacture have
also been reported to occur in human breast milk, fatty tissue and blood. These
compounds have been banned by the European Union for suggestive risks associated
with accumulation processes (122-123).

Alkylphenols and their ethoxylates are compounds commonly used in liquid
detergents and as wetting agents in different industrial applications. They have been
shown to have both acute and chronic effects in aquatic organisms, including alterations
in reproduction, feminization, hermaphroditism, and lower survival rates in fish and
other aquatic organisms living in alkylphenol-contaminated waters (124-126). These

effects have been found even at low doses.

36

 

There are several mechanisms whereby EDCs could modulate endocrine
systems and potentially cause adverse effects. The most direct mechanism of action for
EDCs is the direct binding of the compounds to hormone receptors at the cell surface,
cytoplasm, or nucleus, followed by a complex series of events that can lead to changes
in gene expression (127). Therefore, the most studied mechanisms of EDC action are
those involving the best known receptors: estrogen (ER), androgen (AR), aryl
hydrocarbon (AhR) and thyroid (ThR). However, there is evidence demonstrating that
other receptor systems may also be of importance when evaluating EDC effects. These
include the cytokine systems, the retinoic acid receptor and some of the ‘orphan
receptors’, receptors without known ligands and/or function (128-131). Some of the
EDCs can imitate and/or amplify the effects of the endogenous hormones, they may
function by direct binding the hormone receptors and triggering the same response as
the natural hormone would or in some cases producing even a stronger response.
Others EDCs may instead, stimulate the production of more hormone receptors
resulting in increased sensitivity or responses to natural hormones. In contrast, there
are compounds that bind to a receptor and activate a weaker response than the natural
hormone would or produce no biochemical effect but prevent hormonal action simply
by taking the hormone’s specific site on the receptor (132). All mechanisms involving
direct interaction with any of the mentioned receptors are known as Direct Mechanisms
of Endocrine Disruption.

The modes of action of EDCs are not limited to direct interactions with
hormone receptors. There are other mechanisms that include inhibition of enzyme

activity for hormonal synthesis, or binding to carrier proteins reducing their availability

37

 

to transport hormones or altering the endogenous hormone levels by accelerating their
breakdown and elimination, or by deactivating the enzymes leading to hormone
breakdown (133-135). Some compounds even react directly with hormones to alter
their structure or modify their synthesis. Others less known mechanisms involve
indirect receptor activation by phosphorylation or cellular complexes (136). Together,
these mechanisms are known as Indirect Mechanisms of Endocrine Disruption.

There are numerous experimental assays available for the evaluation of specific
interactions of xenobiotics with most of the endocrine receptors, ER, AR, ThR and
AhR, However, there are very few methods currently available for the evaluation of
integrated endocrine disrupting effects. Therefore, new practical experimental systems
are needed for the identification of effects caused by pathways different to hormone-

receptor interaction.

THE H295R CELL SYSTEM

The adrenal glands, also known as suprarenal glands, are the small, orange and
triangular shaped endocrine glands located on the top of both kidneys. Each gland is
divided into an inner medulla and an outer cortex, and both tissues receive input from
the nervous system but through different mechanisms; the adrenal cortex is regulated
mostly by negative feedback through the hypothalamus and ACTH, while the medulla
is regulated by nerve impulses. The adrenal cortex is essential to life but the medulla
can be removed withouth life-threatening effects (137).

Each part of the adrenal glands, medulla and cortex, performs separate specific

functions (Table 1.2). The adrenal medulla is the main source of the catecholamines

38

adrenaline and noradrenaline. Adrenaline increases heart rate and relaxation of smooth
muscles, while noradrenaline posessess strong vasoconstrictive effects, increasing
blood pressure; these two hormones are secreted by stimulation via sympathetic nerves,
particularly in response to stressful situations (138). The outer portion of the adrenal
gland or adrenal cortex consists of three different regions: zona glomerulosa, zona
fasciculata and zona reticularis, with each region producing different types of
hormones, although chemically all of them are steroids. Aldosterone is the major
mineralocorticoid secreted by the outermost portion, the glomerulosa; this hormone
controls sodium and water absorption in the body. Glucorticoids such as cortisol are
produced for the thicker zona fasciculate. Cortisol increases glucose levels in the
bloodstream. Sex hormones are produced in the innermost region. Androgens and
estrogens are secreted in minimum levels by both, male and female; their effects are

usually masked by the hormones produced in testes and ovaries (139).

Table 1.2 The adrenal glands 3.

 

 

 

 

 

 

Zona Mineralocorticoids
Glomerulosa Aldosterone
Zona Glucocorticoids
Adrenal Cortex Fasciculata Cortisol
Zona Sex Steroids
Reticularis Androgens & Estrogens
Medulla Catecholamines: Epinephrine & Norepinephrine

 

a Major hormones and neurotransmitters produced by the different zones of adrenal
cortex and medulla of the adrenal glands.

In 1990, Adi Gazdar and his colleagues at the NCI-Navy Medical Oncology

Branch established and characterized a continuous human adrenocortical carcinoma cell

39

line that expresses multiple pathways of steroid biosynthesis. The NCI-H295
adrenocarcinoma cell line was initiated from a portion of the adrenal tumor removed in
1980 from a 48-years old, black female patient born in the Bahamas. Pieces of the
adrenal tumor were finely minced and placed in culture in microwells with one of four
growth media. Initially, the cells grew slowly in all four media, some of them attached
and some of them floating. Only HITES media, which lacks attachment factors,
provided floating aggregated cells with fewer numbers of fibroblasts. Following
culture of the NCI-H295 cells, mice were inoculated to evaluate its tumorogenic
properties. Mice developed tumors at the inoculation site 6 to 9 weeks later. The cell
line and developed tumors demonstrated their steroidogenic character after
ultrastructural studies showed the presence of exaggerated numbers of mitochondria,
smooth endoplasmic reticulum, prominent Golgi apparatus and nucleoli, meanwhile
cytogenetic studies showed the presence of 65 marker chromosomes. Steroid secretion
of the NCI-H295 was evaluated after 7-10 years of the cells being in culture and high
concentrations of the precursor pregnenolone, 17-hydroxy pregnenolone and
dehydroepiandrosterone were present. Aldosterone, deoxycortisol, progesterone and
androstenedione were found in lower amounts. With the production of the quantified
steroids, the presence of all major adrenocortical enzyme system including, 110-
hydroxylase, desmolase, Mar-hydroxylase, 17a-hydroxylase, lyase and sulfokinase was
proved. The estrogens measured suggested aromatase presence. NCI-H295 cells were
proven to be capable of synthesizing the cholesterol required for steroid production,

since steroid synthesis occurred in serum-free, cholesterol-free medium. Androgens

40

were the main product in cells fed with serum free media. No steroids were to be found
in control medium samples (140).

Some years after the establishment of this cell line it was demonstrated to
possess all of the major pathways of adrenal steroidogenesis. In addition these
pathways were based on expression of the same enzymes found in normal adrenal
glands. It was also determined that the genes encoding the required enzymes responded
to intracellular second messengers in a manner similar to that of normal human
adrenals. Although this cell line is capable of producing most of the steroids
synthesized in the three different zones of the adrenal cortex, there is supportive
evidence that the NCI-H295 cell line is zonally undifferentiated (141).

It was subsequently demonstrated that this cell line also retains hormonal
responsiveness and that because of its steroidogenic properties it could provide an in
vitro model to help ascertain factors controlling adrenal androgen and glucocorticoid
production. This would permit the examination of pharmacological, biochemical and
molecular mechanisms that control adrenal steroid biosynthesis (142-143). Following
studies corroborated the utility of the NCI-H295 cell line to expand the evaluation of
endocrine disruption since prior to its use most of the assays available were restricted to
chemical-receptor interactions (144-146). The potential for environmental
contaminants to affect endocrine systems at levels other than receptor binding was now
available. This cell line has also been found useful in the evaluation of adrenostatic
compounds used in the treatment of patients with adrenal malfunctioning. Drugs as

aminoglutethimide, metyrapone and etomidate, frequently used in patients with

41

— .-_—-v»——_ .—
L

Cushing’s syndrome, have proven to not only suppress steroid enzyme activity but also
influence both ACTH-receptor expression and cell proliferation in adrenal cells (147).

The NCI-H295 cell line is available through the American Type Culture
Collection (ATCC) under the code CRL-10296. Because the population doubling time
of the cells growing as free aggregates was higher then 96 hours, it was necessary to
modify the grth conditions. A monolayer population of more actively growing H295
cells is now available for use and it is named H295R.

In previously reported studies from our laboratory we have established a
standardized system to culture and expose H295R cells to evaluate the potential effects
of chemicals on the expression of 10 genes involved in steroid production. The results
of exposures with known inducers and inhibitors of steroidogenesis have proven the
ability of the H295R cell line to identify similar expression patterns for chemicals
acting through common mechanisms of action. Time-dependent expression profiles
were also established through time-course studies (148). The reproducibility of this
method was corroborated with later studies using a different method of gene expression
evaluation and a different method of quantification, such as molecular beacon and the
standard curve methods (149). Moreover, the H295R standard methods of exposure
established by our group were proven to be effective in the evaluation of effects of
environmental samples, such as fresh water sediments, on steroid production (150).

The continuous development of molecular biology techniques lends them to the
study and understanding of the multiple mechanisms that drive life. The creative
molecular methods available today, not only have made it possible to find explanations

for normal and abnormal processes, but also have provided the basic tools for

42

diagnostics and research. For the purposes of this dissertation, the standardized
methods for the use of the H295R cell in the evaluation of gene expression and
hormone production chosen were the Polymerase Chain Reaction (PCR), which is an in
vitro molecular biology technique used to replicate enzymatically specific regions of
DNA and the Enzyme Linked Immunosorbent Assay (ELISA), a molecular method that
combines the specificity of antibodies or antigens with the sensitivity of simple enzyme

assays.

43

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148. Hilscherova K, Jones PD, Gracia T, Newsted JL, Zhang X, Sanderson
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150. Blaha, L., Hilscherova, K., Mazurova, E., Hecker, M., Jones, P.,
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Environment International 32, 749-757

56

Chapter 2

THE H295R SYSTEM FOR. THE EVALUATION OF ENDOCRINE DISRUPTING

EFFECTS

ABSTRACT

The present studies were undertaken to evaluate the utility of the H295R system as an
in vitro assay to assess the potential of chemicals to modulate steroidogenesis. The
effects of four model chemicals on the expression of ten steroidogenic genes and on the
production of three steroid hormones were examined. Exposures with individual model
chemicals as well as binary mixtures were conducted. Although the responses reflect
the known mode of action of the various compounds, the results show that designating
a chemical as “specific inducer or inhibitor” is unwise. Not all changes in the mixtures
exposures could be predicted based on results from individual exposures. Hormone
production was not always directly related to gene expression. The H295R system
integrates the effects of direct-acting hormone agonists and antagonists as well as
chemicals affecting signal transduction pathways for steroid production and provides
data on both gene expression and hormone secretion which makes this cell line a

valuable tool to examine effects of chemicals on steroidogenesis.

Keywords: Bioassay, Steroidogenesis, Screening, Endocrine Disruptors, Mixtures

57

INTRODUCTION

Concern about the potential effects of chemicals on the endocrine systems of
wildlife (Ankley et a1 1998) and humans (Kavlock et al 1996) has increased over the
past few years. On October 26th, 2000 the European Parliament adopted a resolution on
endocrine disrupters, emphasizing the application of the precautionary principle and
calling on the Commission to identify substances for immediate action. In 2004, the
Commission presented an update on the implementation of the strategy which among
other recommendations includes an adaptation/amendment of current legislation to
consider potential effects of Endocrine Disrupters. In particular, Regulation No Z_9__3_/9_3
of the European Economic Community (EEC) on risk assessment and Directive
67/548/EEC on the classification of dangerous substances have been promulgated. In
the United States, legislation such as the Safe Drinking Water Act Amendments of
1995 and the Food Quality Protection Act of 1996 have been promulgated. These
legislative mandates require screening for endocrine disrupting properties of chemicals
used in commerce or resulting from process that might occur in drinking water or food.

It has been difficult to develop the necessary screening tools because there are
so many potential effects that could lead to endocrine disruption. In fact, any stressor,
chemical or otherwise that forces an organisms out of its’ normal homeostatic range
could be defined as an endocrine disruptor. The federal Endocrine Disruptor Screening
and Testing Advisory Committee (EDSTAC) recommended that chemicals be screened
as agonists or antagonists of estrogen (ER), androgen (AR), aryl hydrocarbon (AhR)

and thyroid (ThR) hormone receptors (EDSTAC 1998). Specifically, much of the early

58

research focused on the effects of direct-acting effects such as chemicals that act as
hormone mimics by acting as agonists for hormone receptors, in particular interest
focused on the ER. In 1938, Dodds and Lawson conducted perhaps the first published
study to show the estrogenicity of Bisphenol A and Alkylphenols using ovariectomized
rats. Although more evidence for the endocrine disruption effects of these compounds
was found in the 70’s (Muller and Kim 1978) health concerns were only raised when
effects of bisphenol A and nonylphenol on cultured human breast cells were observed
(Kirshnan et al 1993; Soto et a1 1991). A yeast screen containing a human androgen
receptor showed that bisphenol A can also act as an antiandrogen (Sohoni and Sumpter
1998). In the late 90’s the list of endocrine disrupters grew when some PCBs
metabolites were found to mimic oestradiol (McKinney and Waller 1994) and dioxins
showed not only to alter hormone production but also alter the immune system
(Grassman et a1 1998). The pesticide o,p-DDT was also found to be a weak estrogen
agonist (Colbom et al 1997). The relevance of this finding is questionable since the
primary form of the DDT metabolites found in the environment and animal tissues is
actually o,p-DDE. Nevertheless, much of the initial research, public interest and
legislation focused on hormone mimics. Furthermore, most of the initial work was on
developing methods of predicting the ability of chemicals to serve as ER agonists. This
included both structure activity models to predict ER binding (Kanno et a1 2001) as
well as ER binding assays (Legler et a1 1999). More recently several eukaryotic cell
based expression assays have been developed where an endogenous or exogenous
reporter gene is expressed under control of the estrogen receptor (Pons et a1 1990;

Legler et a1 1999) or androgen receptor (Sonneveld et al 2004; Wilson et al. 2002). In

59

addition, there have also been some in vitro systems based on prokaryotic cells
(Routledge and Sumpter 1996). Together these systems have made possible the
identification of many environmental contaminants which may act by binding directly
to hormone receptors. The utility of in vitro assay systems for the identification of
novel mechanisms of endocrine disruption was demonstrated by the observation that
some chemicals are able to alter the production of enzymes involved in steroid
production (Sanderson et a1 2000). While some chemicals have been shown to
modulate the endocrine system as direct receptor agonists or antagonists (Villenueve et
a1 1998) other chemicals can cause effects by non-receptor-mediated mechanisms
(Sanderson et a1 2000). In particular, chemicals that alter the expression of
steroidogenic enzymes have the potential to alter rates, as well as absolute and relative
concentrations of hormones in blood and tissues (Hilscherova et al 2004).

The H295R assay system is now being developed and validated for use in a
tiered screening approach by the US EPA (EDSTAC Final Report 1998) and the results
of preliminary work conducted in our laboratory have been presented to the OECD at
their annual meeting in Paris (2005). At this time the US EPA is considering using the
H295R system to replace two currently used assays, the Hershberger uterotropic assay
for estrogenicity (Kanno et a1 2001) and the rat minced testis assay for determining
effects on aromatase (CYP19). If the H295R assay is adopted, it is anticipated that it
will result in more rapid, accurate and less expensive assays as well as obviating the
need for the use of live animals, which is required in the in vivo or ex vivo assays
currently being utilized. Because of the great potential utility of the H295R assay as a

screening tool and to discern the mechanisms of action of specific endocrine

60

modulating compounds, we are presenting this demonstration of the utility of the assay
as a “frontiers” article, indicative of a publication with novel contributions in sciences.
The H295R cell line was derived from a human adrenal carcinoma and has all
the enzymes necessary to produce steroid hormones (Gazdar et al 1990; Rainey et a1
1993; Staels et a1 1993). H295R cells have physiological characteristics of zonally
undifferentiated human fetal adrenal cells and as a result have the ability to produce the
steroid hormones of each of the three phenotypically distinct zones found in the adult
adrenal cortex (Gazdar et a1 1990; Staels et al 1993). Since the cells maintain the
ability to express these genes and produce these enzymes, they are a useful model
system for the study of potential effects on steroidogenesis. The genes measured in the
current studies include C YPI 1A (cholesterol side-chain cleavage), C YPIIBZ
(aldosterone synthetase), C YPI 7 (steroid 170t-hydroxylase and/or 17,20 lyase), CYP19
(aromatase), I 7B-HSDI and I 7B-HSD4 (17B—hydroxysteroid dehydrogenase, type 1 and
4), CYP21 BZ (steroid 21-hydroxylase), 3B-HSDZ (3B—hydroxysteroid dehydrogenase),
HMGR (Hydroxymethylgutaryl CoA reductase) and the cholesterol transfer protein
StAR (steroid acute regulatory protein). Treatment with a variety of agents has been
shown to alter steroid production in H295R cells (Ohno et a1 2002). Previous studies
have demonstrated that measurement of gene expression in the H295R system not only
permit the evaluation of the potential of chemicals to interfere with the expression of
steroidogenic enzymes, but also provides a means of profiling the modes of action of
chemicals (Hilscherova et a1 2004; Zhang et al 2005). Furthermore, the H295R cell
line has also shown to be useful for measuring the activity of the enzymes as it has been

observed in the studies conducted by Sanderson et al (Sanderson et al 2000 and 2001)

61

where it was demonstrated that commonly used 2-chloro-s-triazine herbicides dose-
dependently induced aromatase (CYP19) activity in this cell line.

The H295R system therefore represents a unique bioassay system in that it
allows for the measurement of alterations in gene expression and at the same time
permits determination of alterations in steroid hormone production by the same cell
cultures. In this paper we report firrther on the development of the H295R assay system
and for the first time present data demonstrating the relationship between gene

expression and steroid production.

MATERIALS AND METHODS

Test Chemicals

Forskolin, ketoconazole and aminoglutethimide, were obtained from Sigma (St. Louis,
MO, USA), metyrapone was obtained from Aldrich (St. Louis, MO, USA); purity of all
test chemicals exceeded 98%. The chemicals used in this study were chosen based on
the known effects on steroid metabolism as well as their effects on steroidogenic gene

expression (Hilscherova et al, 2004).

Experimental design

The H295R human adrenocortical carcinoma cell line was obtained from the American
Type Culture Collection (ATCC # CRL-2128, ATCC, Manassas, VA, USA) and cells
were grown in 75 cm2 flasks with 12.5 ml of supplemented medium at 37°C with a 5%
C02 atmosphere. Supplemented medium was a 1:1 mixture of Dulbecco’s modified
Eagle’s medium with Ham’s F-12 Nutrient mixture with 15 mM HEPES buffer. The

medium was supplemented with 1.2 g/l NazCO3, ITS+ Premix (BD Bioscience, 1 ml

62

Premix/ 100 ml medium), and 12.5 ml/500ml NuSerum (BD Bioscience, San Jose, CA,
USA). Final component concentrations in the medium were: 15 mM HEPES; 6.25
ug/ml insulin; 6.25 ug/ml transferrin; 6.25 ng/ml selenium; 1.25 mg/ml bovine serum
albumin; 5.35 ug/ml linoleic acid; and 2.5 % NuSerum. The medium was changed 2-3
times a week and cells were detached from flasks for sub-culturing using trypsin/EDTA
(Sterile 1x Trypsin- EDTA (Life Technologies Inc.). Cells were exposed to test
chemicals dissolved in DMSO using 6-well Tissue Culture Plates (Nalgene Nunc Inc.,
Rochester, NY, USA). Cells were detached from flasks with trypsin/EDTA (Sterile 1x
Trypsin— EDTA (Life Technologies Inc.) and were harvested into a final volume of
llmL of medium. Cell density was determined using a hemocytometer. For dosing, 3
m1 of cell suspension containing 1 x 106 cells/ml were placed in each well.

In the dose-response experiment, H295R cells were exposed to 0.03, 0.1, 1.0,
3.0, 10, or 50 uM forskolin for 24 h while only the 10 and 50 uM concentrations were
measured at 48 h. The solvent used in these experiments was DMSO at a final
concentration of 0.1%. Matching solvent controls were run concurrently and used to
evaluate gene expression at each time interval.

To ascertain the effects of chemical mixtures on H295R cells, cells were treated
with forskolin in combination with other chemicals previously shown to alter gene
expression (Hilscherova et al, 2004) (Table 2.1). The chemicals used in this study were
chosen based on their variety of known effects on steroid metabolism. Among other
effects aminoglutethimide is an aromatase inhibitor (Bastisda et a1, 2001); forskolin
increases cellular CAMP concentrations (Thomson et a1, 2001); ketoconazole works

principally by inhibition of cytochrome P450 14 or-demethylase (P45014DM); and

63

Table 2.1 Chemical mixtures exposure. a

 

 

Chemical 1 Chemical 2
Solvent control na
10 uM Forskolin 300 uM Metyraponeb
10 “M Forskolin 300 uM AMG"
10 uM Forskolin 20 uM Ketoconazoleb

 

a H295R cells were exposed to individual or chemical mixtures for 24 h.

b . . . . . .
Gene expressron data for rndrvrdual chemicals were prevrously reported

in Hilscherova et al 2004.

na not applicable

64

metyrapone is a specific inhibitor of 11 B-hydroxylase (Parthasarathy et al, 2002). The
data used in these analyses are a compilation 'of several different exposure studies
where some data for individual compounds were run separately from those that
evaluated chemical mixtures. All chemical mixtures contained 10 uM forskolin in
combination with 300 uM metyrapone, 300 uM aminoglutethimide or 20 uM

ketoconazole.

Cell viability/Cytotoxicity

Before nucleic acid isolation and hormone analysis, cell viability was determined.
Cells were visually inspected under a microscope to evaluate viability and cell number.
In addition, cell viability was determined with the Live/Dead cell viability kit
(Molecular Probes, Eugene, OR, USA). While ketoconazole inhibited cell growth at
concentrations greater than 30 uM, no adverse effects on cell growth or viability were
observed for any of the tested chemicals at concentrations up to 300 uM. In instances
where exposure to model compounds resulted in cell death or decreased viability, the

data were not used to evaluate gene expression or hormone production.

RNA Isolation

For nucleic acid extraction, after removal of the medium, cells were lysed in the culture
plate, by the addition of 580 uL/well of Lysis Buffer-B-ME mixture (Stratagene, La
Jolla, CA, USA) and RNA was isolated as described in (Hilscherova et a1. 2004).
Briefly, lysed cells were mixed and then centrifuged in a pre-filter spin cup and the

mixture centrifuged. The filtrate was diluted with 70% ethanol and vortexed. The

65

mixture was transferred to an RNA spin cup and centrifuged for 1 min. The filtrate was
discarded and the spin cup was washed with a low-salt buffer and then centrifuged for 1
min. RNase-Free DNase I solution (Strategene, La Jolla CA, USA) was added to the
fiber matrix inside the spin cup and the sample was incubated at 37°C for 15 min. The
sample was then washed with high-salt followed by a low salt buffer. After each wash
cycle, the filtrate was discarded. After the final wash, the sample was centrifuged and
nuclease-free water was added directly to the fiber matrix inside the spin cup. The tube
was incubated for 2 min at room temperature and centrifuged. This elution step was
repeated to maximize the yield of RNA. The purified RNA was used immediately or
stored at —80°C until needed. An appropriate dilution of the RNA sample (1:50) was
prepared for RNA quantification. The absorbance of the RNA solution was measured
at 260 nm and 280 nm and the 260/280 ratio was calculated. The concentration of total
RNA was estimated using the A360 value and a standard with an A260 of 1 that was

equivalent to 40 ug RNA/ml.

cDNA preparation

Total RNA (1-5 ug) was combined with 50 uM oligo-(dT)20, 10 mM dNTPs, and
diethylpyrocarbamate (DEPC)-treated water to a final volume of 12 pL. RNA and
primers were denatured at 65°C for 5 min and then incubated on ice for 5 min. Reverse
transcription was performed using 8 uL of a master mix containing 5x cDNA synthesis
buffer (Carlsbad CA, USA) and DEPC-treated water. Reactions were incubated at

50°C for 45 min and were terminated by incubation at 85"C for 5 min. Samples were

66

either used directly for PCR or were stored at —20°C until analyzed.

Real-time PCR

Real-time PCR (quantitative PCR) was performed by using a Smart Cycler System
(Cepheid, Sunnyvale, CA, USA) in 25 uL sterile tubes using a master mix containing
25 mM MgC12, lU/uL AmpErase (Applied Biosystems, Foster City, CA, USA), 5
U/uL Taq DNA polymerase AmpIiTaq Gold, 10x SYBR Green (PE Biosystems,

Warrington, UK), nuclease free water and between 10 pg and 1 ug of cDNA. The
thermal cycling program included an initial denaturation step at 94°C for 10 min,
followed by 25-35 cycles of denaturation (95°C for 155), primer annealing (at 60-64°C
for 40-605), and cDNA extension (72°C for 305); a final extension step at 72°C for 5-10
min was also included. Melting curve analyses were performed immediately following
the final PCR cycle to differentiate between the desired amplicons and any primer-
dimers or DNA contaminants. Specifics of the assay parameters such as primers used
and annealing temperatures have been published previously (Hilscherova et a1, 2004).
For quantification of PCR results Cr (the cycle at which the fluorescence signal
is first significantly different from background) was determined for each reaction. Cr
values for each gene of interest were normalized to the endogenous control gene, [3-
actin. Normalized values were used to calculate the degree of induction or inhibition
expressed as a “fold difference” compared to normalized control values. Therefore, all
data were statistically analyzed as “fold induction” between exposed and control
cultures. Gene expression was measured in triplicate for each control or exposed cell

culture and each exposure was repeated at least three times.

67

Hormone Quantification

Hormone extraction and quantification by ELISA were conducted as previously
(Hecker et al 2005). Briefly, frozen media samples were thawed on ice, and the
hormones were extracted twice with diethyl ether (5 ml) in glass tubes. To determine
extraction recoveries a trace amount of 3H-testosterone was added to each sample prior
to extraction. The solvent extract was separated from the water phase by centrifugation
at 2,000 x g for 10 min and transferred into small glass vials. The solvent was
evaporated under a stream of nitrogen, and the residue was dissolved in EIA buffer
from Cayman Chemical Company and either immediately measured or frozen at —80°C
for later hormone determination. Concentrations of hormones in media were measured
by competitive ELISA using Cayman Chemical® hormone EIA kits (Cayman Chemical
Company, Ann Arbor, MI, USA; progesterone [Cat # 582601], testosterone [Cat #
582701], estradiol [Cat # 582251]). Because the antibody to progesterone exhibits
cross-reactivity with pregnenolone of 61% and the method does not allow for the
separation of these two hormones, progesterone concentrations are expressed as
progesterone/ pregnenolone. The working ranges of these assays for the determination of
steroid hormones in H295R media were determined to be: Progesterone (P): 7.8 - 1000
pg/well; testosterone (T): 3.9 - 500 pg/well; 17l3-estradiol (E2): 7.8 - 1000 pg/well.
Media extracts were diluted 1:25 and 1:100 for T while for P and E2 dilutions were

1:50 to 1:100 and 1:2 to 1:10, respectively.

68

Statistical Analysis

Statistical analyses of gene expression profiles were conducted using SYSTAT
(SYSTAT Software Inc., Point Richmond, CA, USA). Differences in gene expression
were evaluated by ANOVA followed by Tukey’s Test. Differences with p<0.05 were

considered significant.

RESULTS

Chemical Dose and Time Courses

Results from the time course study indicated that gene expression profiles could be
grouped into three general categories. These categories were based on gene expression
levels measured in H295R cells exposed to a range of forskolin concentrations for

either 24 or 48 h (Figure 1). The genes were grouped as follows:

Group I Genes (CYP21, C YP19, 3 B—HSDZ, and CYP] 1B2). At 24 h, the dose-response

 

curve for Group I genes was characterized by a relatively great increase in gene
expression from the solvent control levels to 10 uM that was followed by a ‘plateau’ in
expression from 10 to 50 uM. At 48h, the pattern in gene expression was similar to
that observed at 24 h except that gene expression was approximately 2 to 3-fold greater
than that observed at similar concentrations at 24 h. Overall, the genes in this group
showed the greatest levels of induction with gene expression levels commonly being

10-fold in excess of that observed in solvent controls.

Grosz II Genes (CYPI 7 and CYP] IA). At 24 h, gene expression was characterized by

 

rapid increase that reached a maximal level between 5 to 10 uM forskolin. At

69

concentrations greater than 10 uM forskolin, gene expression increased but to a lesser
degree indicating that maximal expression levels may have not yet been reached. In the
48 h exposure, genes were characterized by an increase in expression up to
approximately 10 uM forskolin followed by a ‘plateau’ up to 50 uM. However, unlike
that observed at 24h, gene expression did not significantly differ between 10 and 50
uM indicating that these genes may have reached a maximal expression level. Finally,
while the shape of the gene expression profile for these genes was similar to that
observed with Group 1 genes, the induction of these genes was not as pronounced and

was generally in excess of 3 fold but no greater than 10-fold.

Group 111 genes (StAR, 17B -HSDl and 17B -HSD4L Unlike the profiles observed for
Group I and 11 genes, the expression profiles at 24 and 48 h in the Group 111 genes
differed considerably. At 24 h, the dose-response curve was characterized by relatively
great increase in gene expression in cells exposed up to 3 uM forskolin. This was
followed by a large decrease in expression at 10 uM. Levels of gene expression at 10
uM were similar to that observed in the solvent controls. However, this decrease was
followed by a slight increase in activity at concentrations up to 50 uM. In contrast, in
cells exposed for 48 h, gene expression increased sharply from control levels up to 10
uM forskolin that was followed by less than a 1.5-fold increase in activity in the 50 uM
exposure. Overall, the level of gene expression observed at 10 and 50 11M at 48 h was
similar to that observed at the 3 uM forskolin dose in cells exposed to 24 h.

Alterations in expression of HMGR did not appear to be similar to any of the

above categories. The HMGR gene expression profile at 24 h was characterized by a 2-

70

fold increase in gene expression up to 3 uM that was followed by approximately a 4-
fold decrease in expression at 10 uM and 50 uM. The gene expression profile at 48 h
differed from that observed at 24 h in that gene expression was suppressed from control
levels at all doses with the greatest suppression being observed in cells exposed to 50
uM. These steroidogenic genes were also categorized by the time of induction with
Group I genes being capable of further induction relatively ‘late’ (48 h) in the exposure.
In contrast, HMGR along with the Group II and 111 genes appeared to be induced by
low concentrations of forskolin to a greater degree at 24 h than higher doses at 48 h,
unlike the response observed for the Group I genes. The observed results were in good
agreement with those published previously (Hilscherova et al, 2004) demonstrating the
general robustness of the assay procedure. While there were slight differences in gene
expression alterations between the two studies for Group II and Group 111 these
differences were generally less than 2-fold between the two experiments. The most
profound differences between the current study and Hilscherova’s study were observed
for Group I genes. In the current study, the expression levels of CYPl 152, CYP19, and
CYP21 ranged from 3-fold less to 1.5-fold greater than the results observed by
Hilscherova et al. for cells exposed under similar conditions. These results most likely
represent differences in culture and exposure conditions.

The dose-response curves for forskolin at 24 h were tri-modal for all of the
genes studied (Figure 2.1). This is particularly evident for HMGR, STAR, 17B-HSD1
and 17B-HSD4. For these genes, induction of expression was greatest at 1 and 3 uM

forskolin and

71

 

I vT 47 T I

CYP11BZ

1 —‘r——r f—T‘fihf“ 4TT—q_-j

CYP19

 

 

 

 

 

 

 

 

 

 

 

8
FOLDI
6, j i 20-
.l 4 .4
I .L4
I {’wkfl ,‘ ‘\ .4 1JI— -—4
2 f ‘ ‘—‘
01 L4, I 1 I .1 ELL. 0 ._A___i.._J___J____L__d or 0 I I
-10010203_0405060-100102030405060-100102030405060400102030405060
Concentration (pM) Concentration (uM) Concentration (pM) Concentration (uM)

 

I I T

CYP11A

2—“:;——-—-.--

‘TE

1
O)
1
-:>4

I
2t ,I" I

I
I

 

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\

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I l l l

 

 

 

 

1 I +
‘ l
l l 1 1 l 1 ] 0L4, 1 EL 1 l 1

-1o 0 10 20 30 4o 5 60 -1o 0 1o 20 30 4o 50 60
Concentration (pM) Concentration (uM)

Group III

r r 2. I

 

 

I I

 

17B-HSD1

I 4T T7 I
17B-HSD4

   

 

 

 

 

 

 

 

 

 

 

 

 

0L 1 1 r r L r 0; l 1 I; 0 r 1 r r 1 1
-100102030405060 400102090405060-100102030405060
Concentration (pM) Concentration (uM) Concentration (pM)
2,5 I r r r r r
HMGR I
20~ II
———----—--— 48 Hours ll I
15* I
————24 Hours 1.0- I
\§ “
0.5— />‘*<‘: 4
r 1 ELLE 1 1 T

 

 

0'-1o 0 1o 20 30 4o 50 60
Concentration (pM)

Figure 2.1 Alterations in expression of steroidogenic genes in H295R cells exposed to
a range of concentrations of forskolin for 24 or 48 h.

72

was decreased markedly at 10 uM. While there was a moderate increase in expression
between 10 and 50 uM, the expression at these greater concentrations never reached the
levels attained at 3 uM. In contrast, nearly all the gene expression measures at 48h
were unirnodal and consistent, either increases or decreases, over the exposure range.
The complex nature of the dose-response curve clearly demonstrates the complex,

multiply regulated nature of the steroidogenesis pathway.

Patterns of Gene Response to Chemical Mixtures

Exposure of H295R cells to 10 uM forskolin for 24 h resulted in statistically significant
(2-fold or greater) increases in the expression of the CYP17, CYP19, 17B-HSD4,
CYPllA, StAR and CYP11I32 genes as compared to control levels (Table 2). No
significant changes were observed in the expression of CYP21, 17B-HSD1, 3B-HSD2
or HMGR genes when compared to control gene expression levels. Furthermore
exposure to forskolin was not associated with any decrease in the expression of the
targeted genes indicating that this chemical was a general inducer of steroidogenic
genes in H295R cells. As a result, all comparisons in the binary mixture studies were
made relative to forskolin while changes in gene expression with single chemicals were
evaluated relative to solvent controls.

Metyrapone did not alter the forskolin-induced expression of CYP19, 17B-
HSD4, StAR or CYP11[32 in the mixture (Table 2.2). However, there was
approximately a 2-fold decrease in forskolin-induced gene expression of CYP17 and
CYP1 1A that was accompanied by an ll-fold decrease in 3B-HSD2 gene expression.

The reduction of 3B-

73

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74

HSD2 is interesting in that forskolin alone induced 3B-HSD2 gene expression by
about 1.5 fold whereas metyrapone decreased expression of this gene by
approximately 2-fold when compared to control levels. However, the mixture
resulted in 7.7-fold decrease in gene expression when compared to solvent control
levels. All other metyrapone- forskolin mixture related changes in forskolin altered
gene expression were less than 1.5-fold.

Aminoglutethimide did not significantly alter the forskolin-induced gene
expression of StAR, CYP17, or CYP11B2 in the mixture exposure (Table 2).
However, there was approximately a 2-fold reduction in the forskolin-induced
expression of the CYP1 1A and l7B-HSD1 genes in cells exposed to the mixture. The
greatest effect in the mixture experiment was observed for CYP19. The expression of
this gene was reduced approximately 13- fold less than that observed in cells treated
with forskolin alone. Ketoconazole did not alter the forskolin induced gene
expression of CYP19, 17B- HSDl or StAR while it reduced by approximately 2-fold
the expression of CYP17 and CYP1 1A (Table 2). In addition, while forskolin itself
did not alter the expression of HMGR, CYP21 and 3B-HSD2, the forskolin-
ketoconazole mixture significantly decreased the expression levels of these genes
when compared to controls. The reductions in the expression of these genes were
similar to those observed in cells exposed to ketoconazole indicating there was no
interaction but that the effects were being moderated only by ketoconazole. Forskolin
and ketoconazole caused 6.6-fold and 4.8- fold increases in CYPIIB2 expression
respectively. However, a binary mixture of these two chemicals resulted in a much

greater increase in expression (37-fold) than would have been predicted from

75

exposures to the individual chemicals. This super-induction was not observed for any
of the other genes in that most other changes in gene expression were typically less
than 3-fold. We hypothesize that this super-induction was due to the combined.
effects of increased CYP1 1A activity induced by forskolin and inhibition of CYP17
and CYP21 (Figure 2.2). Increases in CYP1 1A activity caused by forskolin would
increase the flux towards and production of pregnenolone (Cauet et al 2001). At the
same time the inhibition of CYP17 and CYP21 would prevent the conversion of
pregnenolone to products other than progesterone (Hu et a1 2001; Hu et a1 2002).
This should lead to an increase in the flux of metabolites to progesterone. The super-
induced enzyme, CYP11B2 is responsible for the subsequent metabolism of
progesterone such that under these experimental conditions, the large increase in
expression of this enzyme could be reasonably expected. Several other enzymes also
metabolize progesterone but their expression was not measured in this study. In
addition at least one of these enzymes, 17- hydroxylase (EC 1.14.999) has previously
been reported to be inhibited by ketoconazole (DiMattina et al, 1988). The
interactive effects of the chemicals in this situation are also understandable since
increased metabolism due to CYP1 1A induction by forskolin alone would not result
in a great increase in CYPllBZ metabolism of progesterone. This is because the
increased flux would be dispersed to other parts of the synthetic pathway by CYP17
and CYP21 activities. Also in the absence of increased CYPllA activity the
inhibition of CYP17 and CYP21 would not necessarily lead to accumulation of

progesterone and subsequent induction of CYP1 1B2.

76

/ Cholesterol\

CYP11AT CYP11A
CYP17 x i I

 

CYP11A CYP11A

' T
CYPI'l‘lA
CYP17 X Pregnenolone x CYP21

 

 

 

 

CYP17 X Progesterone X CYP21

CYP1 182111

Figure 2.2 Potential mechanism for super-induction of CYP11B2 by a mixture of
forskolin and ketoconazole. Arrows indicate increased gene expression crosses
represent decreased gene expression.

77

Hormone production

Medium from the solvent controls and most of the chemical treatments contained
measurable concentrations of P, T and E2 (Table 2.3). The average concentrations of
E2, T and P in the solvent controls were 14.2 pg/ml, 3,845 pg/ml, and 13,948 pg/ml,
respectively. Coefficients of variation for E2, T and P were 0.8, 3.4 and 49%
respectively.

In H295R cells treated with forskolin, the production of P, T and E2 was
increased from control levels by approximately 2.5-, 1.7- and 21-fold, respectively
(Table 2.3). Thus, while forskolin increased all three hormone concentrations, the
production of E2 preferentially increased when compared to the other two hormones.
In contrast, treatment of H295R cells with aminoglutethimide and ketoconazole
resulted in decreased production of all three hormones compared to solvent controls.
In cells treated with aminoglutethimide, the production of E2 and P were decreased to
below their assay detection limits (7.8 and 440 pg/ml respectively) while T was
reduced 3-fold when compared to the solvent control. Treatment with ketoconazole
resulted in approximately a 7-fold reduction in P, a 10-fold reduction in T and a 1.1-
fold reduction in E2 compared to control levels.

In the forskolin-aminoglutethimide binary mixture, the concentration of P and
E2 in the medium was reduced by approximately 50-fold and greater than 40-fold,
respectively, from that measured in cells exposed to forskolin alone. In contrast, T
concentrations were only reduced approximately 6-fold from forskolin-induced
levels. However, when compared to solvent control, there were 20-fold and 3.5-fold

reductions in P and T concentrations while E2 concentrations were only 2-fold less

78

than control. In the forskolin-ketoconazole mixture, there was approximately a 40-

fold reduction of T concentrations from that observed in the forskolin alone

experiment. However the reductions in P and E2 concentrations were only 5-fold and

1.5-fold, respectively, that observed with forskolin alone.

A comparison of the

mixture hormone data to the solvent control had a slightly different pattern in that P

and T concentrations were reduced from control levels by 2-fold and 25-fold

respectively.

Table 2.3 Hormone concentrations in media from H295R cells treated with single
chemicals or in binary mixtures.a

 

Progesterone Testosterone Estradiol
Treatment b (pg/ml) (pg/ml) (pg/ml)
Solvent control 13948 i 6907 3845 i 129 14.2 d: 0.109
Forskolin (FOR) 35542 d: 6006 6513 d: 151* 303 :1: 4.55*
Aminoglutethimide <440 c 440 i 165* < 7.3c
(AMG)
Ketoconazole (KETO) 1949 i: 116* 374 i 3.81* 12.6 i 1.88*
Metyrapone (MET) na na na
Forskolin+AMG 693 :h 129* 1112 :t 190* < 7.3 c
Forskolin+KETO 7429 d: 105* 149 i 485* 207 d: 62.3
Forskolin+ MET 5902 i 892* 508 :I: 105* < 7.3 c

 

a H295R cells exposed to either forskolin (10 uM); aminoglutethimide (300 uM); metyrapone (300
uM); ketoconazole (20 uM). Binary mixtures had the same chemical concentrations. All exposures

were 24h.

b Statistical comparisons for individual chemicals were to the solvent control. Binary mixtures were

compared to forskolin alone.

C Indicates that hormone concentrations were less than the assay detection limit
na is not analyzed

* Indicates a Statistically significant difference (p <0.05 in a two-tailed test).

79

These reductions represent approximately a 50% change from that observed in the
mixture. In contrast, E2 concentrations were more than lS-fold greater than observed
in the solvent control confirming the observation that ketoconazole did not greatly
affect E2 concentrations. In the forskolin-metyrapone exposure, concentrations of P
and T were reduced approximately 6- and l3—fold from the forskolin alone while E2

was reduced by approximately 80-fold.

DISCUSSION

Previous studies have demonstrated the utility of the H295R assay system as a rapid,
sensitive and predictive in vitro system to assess the potential effects of chemicals on
steroidogenesis (Hilscherova et al 2004; Zhang et a1 2005). However, to more fully
interpret the results obtained from this system it was necessary to develop a more
detailed understanding of the effects of exposure concentration and time on the results
for model compounds. Additionally, to be of use in real world scenarios the response
of the system to chemical mixtures needs to be understood. Finally, the results of
alterations on gene expression can now be related to alterations in actual
steroidogenic function as determined by rates of synthesis and release of hormones to

the culture medium.

Dose and time dependent patterns
The results of the time course experiments for the forskolin exposure demonstrated
the coordinated expression of distinct groups of genes based on the shape and time

dependence of the dose-response curve. The ability to group genes based on

80

chemical- induced alterations in expression suggests a mechanistic linkage in the
regulation of these genes. When a group of chemicals alter the same set of genes it is
possible to establish the general mechanism by which they disrupt steroid production;
furthermore, based on their chemical structures, response profiles may be established
and used to predict the effects of other chemicals with similar chemical structure and
unknown mechanism of action. Thus, the genes that exhibited the greatest change in
transcription, those classified in Group I, are the genes coding for the enzymes
involved directly in the production of the final steroid products such as aldosterone
(CYP1 182) and E2 (CYP19). These downstream genes exhibited the greatest
increase in expression when compared to the other genes studied in the 24 and 48 h
exposure to forskolin. Group I also included genes involved in the production of key
steroidogenic substrates such as ll-deoxycortisol, an important precursor in the
production of glucocorticoids that is regulated by CYP21; and androstenedione, an
indispensable substrate for the formation of sex steroids by 313 - HSD2; this gene, 38-
HSD2, is also involved in the production of progesterone, a key steroid end-product
as well as an important substrate in the formation of glucocorticoids. As observed in
earlier studies, forskolin has relatively little impact on the expression of 17B-HSD1
and 17B-HSD4. These two genes code for two of the ten types of mammalian 17B-
hydroxysteroid dehydrogenases (l7B-HSDs) (Baker, 2001). These enzymes have the
crucial role of controlling the last step in the formation of the essential active
estrogens and androgens as well as the role of inactivating these potent sex steroids to
produce compounds with little or no biological activity. Although the ten 17B-HSDs

belong to the same protein super-family, their amino acid sequences and structures

81

demonstrate relatively low degrees of identity. In addition, each protein demonstrates
distinct tissue-specific expression, substrate specificity, regulatory mechanisms and
catalytic activity. In particular, human 1713 -HSD type I and 4 have distinctly
opposite functions. While 17B-HSD1 catalyzes the formation of 17B-estradiol from
estrone, l7[3-HSD4 functions mainly in the conversion of 17B-estradiol to estrone and
androst-S-ene-3B, 17B diol (Labrie et a1, 1997), in the current study the alteration of
expression of these two genes by forskolin was minimal. The greatest induction
observed relative to control was approximately 2-fold at 48 h for both, 17B—HSD1
and 17B-HSD4.

The relationship observed between HMGR and the other genes evaluated in
this study was also of interest. At 24 h, the HMGR expression in cells exposed to up
to 3 uM forskolin increased rapidly to approximately 2-fold control levels but then
decreased by approximately 2.5 to 3-fold from maximal levels at forskolin
concentrations equal to or greater than 10 uM. This increase in HMGR gene
expression was accompanied by increases in most other genes and was most evident
for StAR and 17B-HSD4. In contrast, at 48 h there was a linear reduction in HMGR
expression over the entire dose range (Figure 2.3). This differed from that observed
for the other genes evaluated in the study in that there was general increase in their
expression from control levels over the exposure range. In animal models, HMGR is
the rate-limiting step in cholesterol biosynthesis that is subject to complex regulatory
controls (Goldstein and Brown 1990). However, while it is the primary mechanism
for controlling cholesterol biosynthesis, other mechanisms are also involved in these

processes (Kojima et a1 2004). Furthermore, the long term control of HMGR

82

enzymatic activity and its gene expression is influenced by the presence of cholesterol
in the cell where high cholesterol concentrations reduce HMGR expression levels
while reduced levels of cholesterol can activate gene expression. However, other
non-sterol regulatory mechanisms may also be important in the control HMGR
activity.

In figure 2.1, picturing the forskolin dose response analysis, it can be observed
that most of the genes reach the maximum expression when exposed to concentration
of lOuM during 48h. Based on these results, this concentration and time of exposure
were chosen to evaluate the effects of other chemicals on the maximum effects
observed by forskolin.

Overall, depending on the mode of action, time can be an important factor in
evaluating the effect of chemicals or groups of chemicals on steroidogenic enzymes

and genes.

Chemical Treatments

The experiments with individual chemicals and simple binary mixtures in this study
clearly indicate the existence of a variety of control mechanisms regulating the
expression of these genes that result in responses that would not be easily predicted
from the results of studies with the individual chemicals (Table 2.4). However,
because of the limitations of the experimental design the occurrence of antagonism,
additivity and super-additivity can only be suggested. A most complete study design,
including a quantitative definition of summation and individual dose-effect

relationships for model chemical 1, model chemical 2 and their mixture (at known

83

ratio of 1 and 2) is required in order to establish any type of interaction between
these chemicals. Here it can only be concluded that for the binary mixtures
cumulative effects and possible antagonist behavior were observed.
Aminoglutethimide (AMG), a drug also known as Cytraden, is used as an
aromatase inhibitor in patients with breast cancer and adrenal anomalies. In our
study, treatment of H295R cells with 300 uM AMG resulted in the inhibition of
expression of CYP17, StAR and 17B-HSD4 while no effect on the expression of
CYP19 was observed. While this would suggest that this dose of AMG would not
adversely affect the production of E2 due to inhibition of degradation to estrone as a
consequence of decreased expression of 17B-HSD4 (Figure 2.3), it is important to
note that this concentration is relatively high and that at lower concentrations E2
could be decreased due to an inhibition of aromatase (Hecker et al 2005). On the
other hand, when H295R cells are exposed to a mixture of forskolin and AMG,
CYP19 is inhibited but 17B-HSD4 is up-regulated possibly to compensate for the lack
of E2 for aromatase inhibition. The inhibition of aromatase is in agreement with the
results of other studies (Bastisda et al 2001), in which the inhibitory action of AMG
on protein kinase A was demonstrated. Recently, several aromatase promoter regions
have been identified in H295R cells that were shown to be responsive to different
stimuli and have implications relative to the regulation of aromatase activities
(Heneweer et al 2004). Thus, chemicals or chemical mixtures may have the potential
to act on different promoter regions through alterations in second messenger systems

such as PKA, PKC or Jak/STAT such that aromatase gene

84

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CYP11A Cholesterol

 

 

 

 

_ _ CYP17
17“ OH 4 DHEA
Pregnenolone Pregnenolone
l 3flHSD2 l 3,6HSDZ 3BHSD2
a CYP1 7 CYP1 7 .
Progesterone % l7a-OH- > Androstenedlone
Progesterone
CYP21 l CYP21 ll7BHSD1
ll-Deoxy- ll-Deoxy- Testosterone e
Corticosterone Corticosterone
l CYPllBl l CYPllBl 1071219
Corticosterone Cortisol ° Nil-Estradiol d
C YPI 132
Aldosterone b
Zona Glomerulosa Zona F asciculata Zona Reticularis

Figure 2.3 Principal pathways in steroid biosynthesis where (a) major progestagen, (b)
major mineralo-corticoid, (c) major gluco-corticoid, ((1) major estrogen and (e) major
androgen.

86

expression or activities are changed in a manner not predicted based on single chemical
exposures. As a result, the mechanism of forskolin-mediated alterations in gene
expression may be the action that makes AMG such a potent steroidogenic inhibitor
rather than the blockade of the steroidogenesis pathway.

The forskolin related induction of CYP17 and CYP11A gene expression was
reduced to almost the same extent by all chemicals; only AMG did not significantly
affect the forskolin induced expression of 3B-HSD2 whereas the other chemicals
reduced the expression of this enzyme to well below the level of expression seen in
either the forskolin only treatment or that of the solvent control. Finally, while
forskolin and ketoconazole both caused moderate increases (4 to 6-fold) in the
expression of CYP1 $2, a binary mixture of these two compounds resulted in a greater
increase in expression (3 7-fold) than would have been predicted from exposures to the
individual chemicals. It can be speculated that the reason for this notorious up-
regulation may be explained by the interaction of the two known modes of action of the
individual chemicals and the fact that these two modes of action come to a critical
conjunction which forces the metabolic pathway toward specific products. In contrast,
the other chemical mixtures tested had little to no effect on the forskolin-induced
expression of CYPIIBZ since they did not have modes of action which caused the
specific alterations in the metabolic network.

Exposure of H295R cells to forskolin resulted in significant increases in T and
E2 production. Although greater than those for E2 and T, differences in P
concentrations were not statistically significant, which is likely due to the relatively

high variability of control P concentrations. The super production of E2 was most

87

likely directly related to an increase in the expression of the CYP19 gene, and a
subsequent increase in aromatase enzyme concentrations. In addition, the up-regulation
of the CYP17 gene expression by forskolin treatment may shift the steroidogenic
process to the production of androgenic substrates leading to the formation of
testosterone and E2 (Cobb et a1 1996).

AMG treatment significantly decreased the production of all three hormones
and in particular P and E2 where concentrations were reduced to less than their assay
detection limit (Table 2.3). This result may be related to the decrease in CYP17 gene
expression that could potentially result in a decrease in the production of androgenic
substrates required for the formation of these hormones, but mostly, AMG is an
endocrine antihorrnone that blocks adrenal steroidogenesis by inhibiting the enzymatic
conversion of cholesterol to pregnenolone and also blocks the aromatization of
androgenic precursors to estrogens by inhibiting aromatase activity. Therefore, it could
be speculated that AMG decreased P and E2 production by a mechanism other than
gene expression, since 3B-HSD2 and CYP19 gene expression were not affected by this
chemical treatment. Because the versatility of the H295R cell line for the evaluation of
aromatase activity have been shown before (Sanderson et a1 2000, 2001), several
experiments are being conducted in our laboratories to evaluate the effects of AMG in
the activity of this enzyme in order to search for a more detailed explanation related to
the E2 production. However, since all three hormones were greatly decreased by AMG
the reduction was most likely due to general stress rather than a specific action of this
chemical within the steroidogenic pathway. The powerful antagonism of AMG to

forskolin is clearly observed when E2 concentrations dramatically decreased in the

88

forskolin-AMG treatment compared to the greatest induction by forskolin. In addition,
the ten-fold induction in T production by forskolin treatment matches the ten-fold
decrement in T production observed in the forskolin-AMG exposure. The
ketoconazole-forskolin treatment produced the same effects as those observed with
either chemical singly on 17B-HSD1 gene expression resulting in no significant change
in E2 concentrations. However, exposure to the mixture resulted in significant
decreases in the production of T and P. The decrease in P may have been linked to the
down regulation of 3B-HSD2 since no effects were noted on the expression of CYP17
as compared to the solvent controls. Furthermore, the massive increase in CYP1 182
expression could have resulted in an increased synthesis of aldosterone, thus, resulting
in the depletion of further upstream precursors including P. A possible explanation for
the decrease in T could be a result of increased CYP19 expression in combination with
the reduction of precursors such as P, with the lack of a concomitant increase of E2 due
to the shift of the E2/estrone balance towards estrone due to increasing l7B-HSD4 gene
expression. However, it is difficult to link changes in hormone production with
changes in steroidogenic gene expression without the knowledge on how these translate
into effects at the enzyme activity levels, and thus, the exact causes for the observed
alterations in hormone concentrations remain unclear.

The results from this study underscore the utility of the H295R cell system to
investigate the interactions of chemicals on steroidogenic gene expression and hormone
production. However, to better understand these interactions it will be necessary to
evaluate other endpoints such as steroidogenic enzyme activities, which link the

alterations in gene expression to biologically important processes that are controlled by

89

endocrine systems. Given that enviromnental exposure to chemical contaminants is
almost always in the form of mixtures the use of a system such as the H295R assay is a
powerful tool to investigate the effects of single compounds and complex mixtures of
xenobiotics, and to investigate the molecular mechanisms of those effects and the
molecular mechanisms of chemical interaction.

This study and our previous work (Hilscherova et a1 2004) have demonstrated
the ability of the H295R assay system to evaluate the effects of xenobiotics on
steroidogenesis. By observing the effects of chemical exposure on 10 different
steroidogenic endpoints (i.e. the expression of 10 different genes) the assay system has
revealed that in general even ‘specific’ inhibitors affect the expression of multiple
genes. This is not surprising given the complex regulatory mechanisms controlling
steroidogenesis, but clearly demonstrates that designating any chemical as a “specific
inhibitor or inducer” is unwise. However, the responses observed clearly reflect the
known mode of action of the various compounds. In the present study the complex
non-additive responses observed as a result of exposure to some chemical mixtures can
be explained by mechanistic interactions of the known modes of action of the specific
chemicals. The additional complexity observed in many of the responses required
considerably more effort to be put into interpretation of the gene expression profiles,
thus hormone production was also evaluated to observe any correlation to gene
expression. The H295R assay together with hormone quantification is a useful in vitro
system to investigate regulatory and chemical interaction mechanisms as well as

providing a system for screening chemicals for effects on steroidogenesis.

9O

CONCLUSIONS

The H295R assay system is unique among bioassays in that it measures alterations in
gene expression and hormone production at the same time. This dual response is
particularly significant for chemicals that are able to alter the production of steroid
hormones since the ultimate effects of these chemicals are expressed thru the alterations
in hormone concentrations in exposed organisms. The results of the H295R assay to
date have demonstrated that chemicals maybe grouped alternatively by effects on gene
expression or by effects on hormone production. These results clearly show that the
chemicals tested have a range of modes of action. Significantly, there are clear
examples of interaction between modes of action leading to supra-additive effects. This
finding is clearly of significance given that environmental contaminants are most
commonly found in complex mixtures. The H295R system is an effective tool for
understanding potential mechanisms of action as well as a rapid, sensitive and cost-
effective tool for high throughput screening of a range of potential effects of
compounds. Furthermore, the H295R system is attractive because it minimizes the use

of whole organisms.

Acknowledgement
We acknowledge many helpful discussions and manuscript review by Dr. Ralph
Cooper, Dr. Jerome Goldman and Dr. Robert Kavlock, Endocrinology Branch,

NHEERL, US EPA Research Triangle Park, North Carolina.

91

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Chapter 3
MODULATION OF STEROIDOTENIC GENE EXPRESSION AND HORMONE
PRODUCTION OF H295R CELLS BY PHARMACEUTICALS AND OTHER

ENVIRONMENTALLY ACTIVE COMPOUNDS

ABSTRACT
The recently developed H295R cell bioassay was used to evaluate the potential
endocrine disrupting effects of 18 of the pharmaceuticals most commonly used in the
United States. Exposures for 48 h with single chemicals and binary mixtures of
pharmaceuticals were conducted and the expression of 4 steroidogenic genes, 3BHSD2,
CYP11B2, CYP17 and CYP19, was quantified by Q-RT-PCR. Production of the
steroid hormones estradiol (E2), Testosterone (T) and Progesterone (P) was also
evaluated. Antibiotics were shown to modulate gene expression and hormone
production. Amoxicillin up-regulated the expression of CYP11B2 and CYP19 by more
than 2-fold and induced estradiol production up to almost 3-fold. Erythromycin not
only increased CYP11B2 expression but also increased the production of P and E2 by
3.5- and 2.4-fold, respectively. Production of T was also significantly decreased by
erythromycin. The B-blocker, salbutamol, caused the greatest induction of CYP17,
13.64-fold, and significantly decreased E2 production. The binary mixture of
cyproterone and salbutamol significantly down-regulated expression of CYP19 while a
mixture of ethynylestradiol (EE2) and trenbolone increased E2 production 3.7-fold.

Not all the genes measured responded to changes in exposure concentrations. Estradiol

96

 

production was significantly affected by changes in concentrations of trenbolone,

cyproterone, and EE2.

INTRODUCTION

Based on information obtained from the US. Food and Drug Administration (USF DA),
approximately 82,000 drugs are registered in the US. for human use accounting for
more than 3000 active. ingredients. Besides the active substances, adjuvants and, in
some instances, pigments and dyes are also components of the formulated drug product.
After administration to humans and animals, pharmaceuticals are excreted in waste
products and many unused medications are disposed of in drains or sewage systems.
Sewage treatment facilities, depending on their technology and the chemical’s
physicochemical properties, are not always effective in removing the active chemicals
from waste-water. As a result, pharmaceuticals find their way into the environment,
where they can directly affect terrestrial and aquatic organisms and can be incorporated
into food chains (Dial-Cruz et al., 2003; Cecchini and LoPresti, 2006). In recent years,
extensive and detailed reports about residues of pharmaceuticals and their metabolites
in the environment have been published in the scientific literature (Jorgensen and
Halling-Sorensen, 2000; Hereber, 2002; Sanderson et al., 2004; Jones, et al., 2004).
Most of these reports concern the situation in Europe, but as yet the potential ecological
effects associated with the presence of these compounds have been largely ignored. In
Europe, pharmaceuticals in the environment have received regulatory attention through

the submission of Environmental Risk Assessments (ERAS) that accompany Marketing

97

Authorization Approval. Revised draft guidelines for European ERAS were recently
reviewed by various stakeholders, and the final guidelines were available in 2004. In
Canada, a requirement for environmental assessment is in place and the ERA process is
under consideration. Most of the methods used today for the identification and
quantification of pharmaceuticals in the environment and the first attempts of eco-
toxicity evaluations of these active compounds have been developed in European
countries (Commission of the European Communities, 1992). Moreover, the European
Union has taken the lead on banning the use of the majority of growth-promoting
antibiotics used for livestock on the basis of the “Precautionary Principle” (Casewell,
2003).

Among the frequently detected substances in rivers are beta blockers such as
metoprolol at concentrations up to 1.5 ug/l and beta-sympathomimetics (Hirsch et al.,
1996; Sedlak et al., 2001), analgesic and anti-inflammatory drugs like diclofenac up to
1.2 pg/l observed in several studies (Temes, 1998; Stumph et al., 1998; Buser et al.,
1998); estrogens such as 17|3-estradiol have been found at concentrations up to 13 ng/l
(Kuch and Ballschmitter, 2000). In addition, antibiotics such as erythromycin have
been reported to occur at concentrations as great as 1.7 ug/l concentrations (Hirsch et
al., 1999; Lindsey et al., 2001). Estrogenic compounds have also been identified in
rivers of southern and middle Germany (Adler et al., 2001), as well as lipid lowering
agents such as the clofibric acid at concentrations as great as 0.2 pg/l (Ollers et al.,
2001); and anti-epileptic drugs such as carbamazepine at concentrations as up to 2.1

ug/l (Mohle et al., 1999).

98

During 1999-2000, the US. Geological Survey conducted the first nationwide
investigation of the occurrence of pharmaceuticals, hormones and other organic
contaminants in 139 streams from 30 states (Kolpin et al., 2002). A total of 95 residues
were targeted including antibiotics, prescription, and nonprescription drugs, steroids
and hormones, 82 of which were found in at least one sample. Although researchers
caution that sites were chosen based on their increased susceptibility to contamination
from urban or agricultural activities, a surprising 80% of streams sampled were positive
for one or more of the targeted pharmaceutical. Furthermore, 75% of the streams
contained two or more of the targeted pharmaceuticals, 54% had more than five, while
34% had more than 10 and 13% tested positive for more than 20 targeted contaminants.
Similar reconnaissance studies are ongoing all over the world to evaluate the presence
of pharmaceuticals in groundwater and surface water sources of drinking water.
Identification of the environmental exposure routes to these drugs is crucial for
estimating a realistic environmental assessment of pharmaceuticals because it is the
dose of drugs and the duration of treatment that gives a certainty of the environmental
loading. The fact that the same drug may be used for several applications and that there
are different exposure routes through various environmental matrices, the fate of the
drug may also vary resulting in quite different environmental concentrations.

Since they are transformed to some extent in humans, pharmaceuticals are
sometimes thought to be easily (bio)degraded in the environment, but it has been
established that large proportions of many pharmaceuticals can be excreted from the
body un-metabolized and enter wastewater as biologically active substances (Fent et al.,

2006; Kummerer, 2001). Thus, human drugs used will be discharged to the sewer

99

systems in urine and feces and so enter sewage treatment plants (STP) (Loefler et al.,
2005; Cleuvers, 2003). Alternatively, for drugs which are metabolized before being
released from the body, when exposed to the environment, some can be reactivated to
the parent compound (Pickrell, 2002). This has been demonstrated for the glucoronide
metabolite of chloramphenicol and the acetylated metabolite of sulphadimidine in
samples of liquid manure (Berger et al., 1986). Thus, it is often not only the parent
compound which should be the subject for a risk assessment but also the main
metabolites. Additionally, drug residues found in the environment, especially in
aquatic systems, usually occur as mixtures, not as single contaminants therefore
scientific assessment of risk to aquatic life should consider these complex exposure

situations.

Since pharmaceuticals are specifically designed to be biologically active they may
have unintended effects on non-target organisms in the environment, even at low
concentrations. Information concerning possible eco-toxicological risks of
pharmaceuticals is rather scarce (van Wezel et al., 2002); unfortunately there is still not
only a real lack of information to perform an environmental risk characterization,
particularly about data for eco-toxicity, but also a lack of information about the
additional effects, other than the original innate function for which the chemical or

pharmaceutical was designed and/or produced.

The objective of the present study was to evaluate the potential effects of 18 of the
most used human and veterinary pharmaceuticals in the United States (Table 3.1) on

steroidogenesis in H295R cells. The effects of antibiotics, growth promoters, hormone

100

therapy drugs, analgesics, anti-inflammatory medications, anti-lipidics, anti-dcpressives
and B-blockers on the expression of 4 steroidogenic genes encoding for the production
of 4 important enzymes in the steroidogenic pathway was evaluated by use of Q-RT-
PCR. In addition, the production of the hormones estradiol (E2), testosterone (T), and
progesterone (P) were quantified using ELISA methods and related to gene expression.
Dose-response curves were also developed to evaluate the effects of chemical

concentration on both, gene expression and hormone production.

MATERIALS AND METHODS

Test Chemicals

All chemicals were obtained from Sigma (St. Louis, MO, USA), except for amoxicillin,
cephalexin hydrate and erythromycin that were obtained from BioChemiKa (St. Louis,
MO, USA). Purity of all test chemicals from Sigma exceeded 98% while chemicals
from BioChemiKa exceeded 97%. The chemicals used in this study were selected
based on the list of the top 300 prescriptions drugs dispensed in the USA during 2005

(Rx list) and also by their prevalence in surface waters.

Experimental design

The H295R human adrenocortical carcinoma cell line was obtained from the American
Type Culture Collection (ATCC # CRL-2128, ATCC, Manassas, VA, USA) and cells
were grown in 75 cm2 flasks with 12.5 mL of supplemented medium at 37°C with a 5%
C02 atmosphere. Supplemented medium was a 1:1 mixture of Dulbecco’s modified

Eagle’s medium with Ham’s F-12 Nutrient mixture with 15 mM HEPES buffer. The

101

 

medium was supplemented with 1.2 g/l NazCO3, ITS+ Premix (BD Bioscience, 1 ml
Premix/ 100 ml medium), and 12.5 ml/500ml NuSerum (BD Bioscience, San Jose, CA,
USA). Final component concentrations in the medium were: 15 mM HEPES; 6.25
ug/ml insulin; 6.25 itng transferrin; 6.25 ng/mL selenium; 1.25 mg/ml bovine serum
albumin; 5.35 ug/ml linoleic acid; and 2.5 % NuSerum. The medium was changed 2-3
times a week and cells were detached from flasks for sub-culturing using trypsin-EDTA
(Sterile 1X trypsin-EDTA (Life Technologies Inc.). For exposure, cells were detached
from flasks with trypsin/EDTA (Sterile trypsin- EDTA (Life Technologies Inc.) and
harvested into a final volume of 10ml of medium. Cell density was determined using a
hemacytometer. For dosing, 3 ml of cell suspension containing approximately 1x106
cells/ml were placed in each well. Cells were exposed for 48 h to different groups of
pharmaceuticals and several other compounds of relevant environmental importance
dissolved in DMSO or methanol using 6-well Tissue Culture Plates (Nalgene Nunc
Inc., Rochester, NY, USA). Final concentrations of DMSO and methanol were of
0.1%. H295R cells were exposed for 48 h to individual antibiotics with different
spectrums of action (Table 3.1). Amoxicillin, cephalexin, erythromycin, tetracyclines,
trimethoprim and tylosin were the antibiotics chosen. A group of drugs used for
hormone therapies including cyproterone, dexamethasone, EE2, and trenbolone were
also tested. Over the counter drugs, such as the analgesics acetaminophen and
ibuprofen were also included. The pharmaceuticals assessed also included other drugs
from different therapeutic groups, such as the antidepressant fluoxetine, the antilipidic
clofibrate, the B-agonist salbutamol, growth promoters such as trenbolone and

zearalanol, and the insect repellant, DEET, which are also frequently found in

102

Table 3.1. Pharmaceuticals and environmentally active compounds used to expose
H295R cells 3".

 

 

 

 

 

Compound Therapeutic Use Conc".
Acetaminophen Analgesic 300 jig/ml
Clofibrate Lipid agent 3 jig/ml
Dexamethasone Corticosteroid 2 ug/ml
Doxycycline Antibiotic 10 ug/ml
DEET Pesticide 3 ug/ml
Erythromycin Antibiotic 3 ug/ml
Ibuprofen NSAAI 250 ug/ml
Trimethoprim Antibiotic 3 ug/ml
Tylosin Antibiotic/grth 3 jig/ml
Compound Therapeutic Use Concb.
Amoxicillin Antibiotic 71 pg/l
Cephalexin Antibiotic 73 pg/l
Cyproterone Cancer treatment 62 pg/l
Oxytetracyclin Antibiotic/growth 81 pg/l
Salbutamol Asthma/B-agonist 50 ng/l
Trenbolone Growth prom. 25 pg/l
a-Zearalanol Hyperestrogen/Nat 2.8 ng/l
Ethynil Estradiol Oral Contraceptive 1 pg/l
Fluoxetine Antidepressant 1 ug/l

 

 

3 Hi h concentrations b Environmentall relevant concentrations.
9

103

environmental samples. The effects of the target chemicals on gene expression were
compared to the effects of exposures to solvent controls at each time interval. Since
pharmaceuticals can occur in surface waters as mixtures, a set of 4 binary mixtures of
pharmaceuticals were also used as exposure solutions for the H295R cells. The
chemicals used in mixture solutions were chosen based on the results of individual
exposures. Moreover, dose-response curves were constructed for 3 of the drugs used in
hormone therapies to evaluate whether or not changes in gene expression and hormone

production were directly related to changes in drug concentration.

Cell viability/Cytotoxicity

Before nucleic acid isolation and hormone analysis, cell viability was determined. Cells
were visually inspected under a microscope to evaluate viability and cell number. In
addition, to establish the range of chemical concentrations that may be used without
producing physical harm to the cells, a Live/Dead cell viability assay kit (Molecular
Probes, Eugene, OR, USA) was used. In instances where exposure resulted in cell death
or decreased viability the data were not used to evaluate gene expression or hormone

production.

RNA Isolation

For nucleic acid extraction, after removal of the medium, cells were lysed in the culture
plate, by the addition of 580 til/well of lysis buffer-B-ME mixture (Stratagene, La Jolla,
CA, USA) and RNA was isolated as previously described (Hilscherova et al., 2004).

Briefly, lysed cells were mixed and then centrifuged in a pre-filter spin cup and the

104

mixture centrifuged. The filtrate was diluted with 70% ethanol and vortexed. The
mixture was transferred to an RNA spin cup and centrifuged for 1 min. The filtrate was
discarded and the spin cup was washed with a low-salt buffer and then centrifuged for 1
min. RNase-Free DNase I solution (Strategene, La Jolla CA, USA) was added to the
fiber matrix inside the spin cup and the sample was incubated at 37 °C for 15 min. The
sample was then washed with high-salt followed by a low salt buffer. After each wash
cycle, the filtrate was discarded. After the final wash, the sample was centrifuged and
nuclease-free water was added directly to the fiber matrix inside the spin cup. The tube
was incubated for 2 min at room temperature and centrifuged. This elution step was
repeated to maximize the yield of RNA. The purified RNA was used immediately or
' stored at —80 °C until needed. An appropriate dilution of the RNA sample (1:50) was
prepared for RNA quantification. The absorbance of the RNA solution was measured at
260 nm and 280 nm and the 260/280 ratio was calculated. The concentration of total
RNA was estimated using the A260 value and a standard with an A260 of 1 that was

equivalent to 40 pg RNA/mL.

cDNA Preparation

Total RNA (1-5 pg) was combined with 50 pM oligo-(dT)20, 10 mM dNTPs, and
diethylpyrocarbamate (DEPC)-treated water to a final volume of 12 ul. RNA and primers
were denatured at 65 °C for 5 min and then incubated on ice for 5 min. Reverse
transcription was performed using 8 ul of a master mix containing, 5X cDNA synthesis
buffer (Carlsbad CA, USA) and RNase/DNase free water. Reactions were incubated at

50 °C for 45 min and were terminated by incubation at 85°C for 5 min. Samples were

105

either used directly for PCR or were stored at —20 0C until analyzed.

Real-time PCR

Real-time PCR (quantitative PCR) was performed by using a Smart Cycler System
(Cepheid, Sunnyvale, CA, USA) in 25 pl sterile tubes using a master mix containing 25
mM MgC12, lU/pl AmpErase (Applied Biosystems, Foster City, CA, USA), 5 U/pL Taq
DNA polymerase AmpliTaq Gold, 10X SYBR Green (PE Biosystems, Warrington, UK),
nuclease free water and between 10 pg and 1 pg of cDNA. The thermal cycling program
included an initial denaturing step at 94 0C for 10 min, followed by 25-35 cycles of
denaturing (95°C for 153), primer annealing (at 60-64 0C for 40-60 s), and cDNA
extension (72 0C for 30 s); a final extension step at 72 0C for 5-10 min was also included.
Melting curve analyses were performed immediately following the final PCR cycle to
differentiate between the desired amplicons and any primer-dimers or DNA
contaminants. Specifics of the assay parameters such as primers used and annealing
temperatures have been published previously (Hilscherova et al., 2004).

For quantification of PCR results C: (the cycle at which the fluorescence signal is
first significantly different from background) was determined for each reaction. C: values
for each gene of interest were normalized to the endogenous control gene, B-actin.
Normalized values were used to calculate the degree of induction or inhibition expressed
as a “fold difference” compared to normalized control values. Therefore, all data were
statistically analyzed as “fold induction” between exposed and control cultures. Gene
expression was measured in triplicate for each control or exposed cell culture and each

exposure was repeated at least three times.

106

Hormone Quantification

Hormone extraction and quantification by ELISA were conducted as previously
described (Hecker et al., 2006). Briefly, frozen samples of media were thawed on ice,
and the hormones were extracted twice with diethyl ether (5 mL) in glass tubes. To
determine extraction recoveries a trace amount of 3H-T was added to each sample prior to
extraction. The solvent extract was separated from the water phase by centrifirgation at
2,000 x g for 10 min and transferred into small glass vials. The solvent was evaporated
under a stream of nitrogen, and the residue was dissolved in EIA buffer from Cayman
Chemical Company and either immediately measured or frozen at ~80°C for later
hormone determination. Concentrations of hormones in media were measured by
competitive ELISA using Cayman Chemical® hormone EIA kits (Cayman Chemical
Company, Ann Arbor, MI, USA; P [P; Cat # 582601], T [T; Cat # 582701], l7l3-estradiol
[E2; Cat # 582251]). Because the antibody to P exhibits cross-reactivity with
pregnenolone of 61% and the method does not allow for the separation of these two
hormones, P concentrations are expressed as P/ pregnenolone. The working ranges of
these assays for the determination of steroid hormones in H295R media were determined to
be: P: 7.8 - 1000 pg/ml; T: 3.9 - 500 pg/ml; E2 estradiol: 7.8 - 1000 pg/ml. Media
extracts were diluted 1:25 and 1:100 for T while for P and, E2 dilutions were 1:50 to

1:100 and 1:2 to 1:10, respectively.

Statistical Analysis
Statistical analyses of gene expression profiles were conducted using SYSTAT

(SYSTAT Software Inc., Point Richmond, CA, USA). Differences in gene expression

107

and hormone production were evaluated by ANOVA followed by Tukey’s Test.
Differences with p<0.05 were considered significant. Statistical correlations between
gene expression and hormone production were established by Pearson correlation
analysis followed by Bonferroni probability test. Correlations with p<0.05 were

considered significant.

RESULTS

Antibiotic Exposure

 

Gene Expression

Responses of gene expression for the exposures conducted with 7 of the most commonly
used antibiotics in human medicine and for veterinary purposes are given (Table 3.2).
The responses of gene expression for the blank and solvent control exposures were
consistent. Treatment of the H295R cells with environmentally relevant or greater
concentrations of the selected antibiotics resulted in significant changes in the expression
of several genes. H295R cells when exposed to environmentally relevant concentrations
of amoxicillin, cephalexin, oxytetracycline and tylosin significantly altered the pattern of
expression of the 4 target genes, relative to that of solvent exposed cells. Amoxicillin
significantly increased the expression of CYP17 and CYP19 more than 4-fold compared
to solvent control, while cephalexin and oxytetracycline significantly increased
expression of CYP19 more than 2-fold. Oxytetracycline was also the only antibiotic
studied to affect the expression of the progesterogenic gene 3BHSD2. Tylosin increased
expression of the aldosteronogenic gene, CY11B2 approximately 10-fold; although

tylosin also decreased the expression of the CYP19, this decrement was not statistically

108

significant. Erythromycin, oxytetracycline and trimethoprim were used at non-relevant
environmental concentrations of 3 to lOpg/mL. Oxytetracycline was not soluble in
DMSO and so methanol was used to dissolve this compound. A methanol control was
also included among the exposures. Trimethoprim did not affect the expression of any of
the genes, while erythromycin increased the expression of CYP11B2 approximately 7-

fold and doxycycline induced the expression of CY19 almost 3-fold.

Hormone Production

While concentrations of all the hormones measured were very consistent in the Blank,
DMSO and methanol exposures (Table 3.2) some of the pharmaceuticals resulted in
changes in production of hormones. Erythromycin increased the production of P and E2
more than 2- and 3-fold respectively, and reduced the production of T by more than 50%.
In contrast, the tetracyclines did not significantly affect the production of any of the
hormones. Tylosin decreased the production of T and E2, while cephalexin only

decreased T production and amoxicillin increased production of E2 more than 2-fold.

Hormone Therapy Drugs

Gene Expression

None of the 4 hormone therapy drugs with hormonal properties that are commonly used
in the treatment of cancer, birth control, inflammatory processes and as growth promoters
in animal production, significantly affected the expression of 3BHSD2 (Table 3.3).
Environmentally relevant concentrations of the cancer therapy drug cyproterone induced

the expression of the CYP19 more than 4-fold, but only induced the expression of the

109

androgenic gene CYP17 3-fold. Dexamethasone and EE2 exposures induced expression
of CY11B2 approximately 5-fold. The growth promoter trenbolone only increased the

expression of CYP19 by about 3-fold.

Hormone Production

Hormone therapy drugs affected hormone production (Table 3.3). EE2 significantly
increased P and E2 production by more than 2-fold and at the same time significantly
decreased T production by about 66%. Trenbolone and cyproterone decreased T
production by approximately 50% and 66% respectively. However, neither chemical

affected E2 or P production.

Other Pharmaceuticals and Environmentally Active Compounds
A non steroidal anti-inflammatory drug, analgesics, an antilipidic, antidepressant, [32-
agonist, a growth-promoter and a commonly used insect repellent (Table 3.4), were also

included in this study to evaluate their potential effects on steroidogenesis.

Gene Expression

A significant up regulation of CYP17 was observed for the exposure with the fig-agonist
salbutamol, which increased the expression of this gene for more than 10 fold. None of
the other genes studied were affected by this compound. Of the analgesics studied, only
acetaminophen significantly affected the expression of CYP1 182 by increasing it
approximately 4-fold. CYP11B2 was induced by the antilipidic, clofibrate, the

antidepressant, fluoxetine, approximately 5-fold and by the analgesic acetaminophen by

110

Table 3.2 Gene expression and hormone production inH295R cell exposed to single antibiotics.
Treatment

Gene DMSO MeOH AMOXI CEPHA ERYT oxvrc ooxvc more mo
0.1% 0.1% 71 ugh 73 ug/L 3uglmL 81ug/L lOua’mL’ 3ug1ml. 3ug/mL

 

CYP11B2 1.00 10.33 1.001019 1.95 10.24 0.771 0.33 6.91 1097* 1.7210.31 06910.73 06410.05 9.9911.09*
CYP19 10010.61 10010.16 4.4510.55* 2.871 113* 0.5410.14 2.5810.25* 2.8710.40* 0.581008 04910.33
CYP17 10010.10 1.0010.16 4.4810.35* 1.7410.56 0.7510.06 1.8910071 0.8510.04 1.901008 1.031004
3BHSD2 1.001013 10010.16 1.421075 0.721052 0.921025 2.51 1017* 10010.08 0.601036 1.321027

 

 

Hormone DMSO MeOH AMOXI CEPHA ERYI OXYIC DOXYCa TYLO
0.1% 0.1% 71 ug/L 73 ugll. 3 ug’mL 81 ug/L 10 ug’mL 3 uglmL

 

Testosterone 1.001 0.27 1.001034 0.71 10.02 0.11 1 003* 0.441 008* 1.23 10.007 1.55 1 0.085 0.4210.09*
Progesterone 1.00 1 0.01 10010.13 06310.13 0.891004 3.551058* 1.321055 1.261020 1.301 0.28
Estradiol 1.001 0.32 10010.60 2.51 061* 0.51 10.30 2.461 033* 0.15 10.05 2.04 10.60 0.1210.08*
A11 exposures were conducted for48 h under standard conditions. All gene expressiomnd hormone productionvalues for fold change relative to
control given as means and standard deviationsDMSO: Dimethylsulfoxide; MeOH: Methanol; AMOXIAmoxicillin; ERYTzErythromycirr
9m C: Oxytetracycline;DOXY: Doxycycline;TR1ME:Trimethoprim;TYl.0: Tylosin.
Compared to MeOH as solvent contro1.* Indicates statistically significant differences at p “0.05.

111

Table 3.3Gene expression and hormone production in H295R cells exposed to single hormone

 

 

therapy drugs.
Treatment
Gene DMSO CYPROT DEXAM EE2 TRENB ZEARA
0.1% 62 ug/L 2 ug/mL 1 ug/L 25 ug/L 2.8 ng/L

 

CYP11B2 1.00 1 0.33 1.34 1 0.52 5.39 1 0.50* 4.88 1 0.97* 0.81 1 0.43 0.22 1 0.03
CYP19 1.00 1 0.61 4.62 11.51* 0.98 1 0.19 0.54 1 0.14 2.56 1 0.55* 0.32 1 0.10
CYP17 1.00 1 0.10 2.81 1 0.5* 0.71 1 0.04 0.75 1 0.06 1.79 1 0.41 0.20 1 0.04

3BHSD2 1.00 1 0.13 0.90 1 0.32 0.64 1 0.09 0.92 1 0.25 0.77 1 0.15 0.14 1 003*

 

 

Hormone DMSO CYPROT DEXAM EE2 TRENB ZEARA
0.1% 62 ug/L 2 ug/mL 1 ug/L 25 ug/L 2.8 ng/L

 

Testosterone 1.00 1 0.27 0.29 j: 003* 0.25 1 005* 0.36 1 0.12* 0.48 1 009* 1.06 1 0.15
Progesterone 1.00 1 0.01 1.02 1 0.30 0.74 1 0.05 2.71 1 0.39* 0.72 1 0.20 1.02 1 0.21
Estradiol 1.00 1 0.32 1.25 1 0.47 1.4 1 0.26 2.33 1 027* 1.6 1 0.25 0.17 1 0.03
A11 exposures were conducted for 48 h under standard conditions. All gene expression and hormone
production values for fold change relative to control given as means and sta ndard deviations.
DMSO: Dimethylsulfoxide; CYPROT: Cyproterone; DEXAM:Dexamethasone; E2:Ethynylestradiol;
TRENBzTrenbolone Acetate; ZEARA: -Zeara1anol
* Indicates statistically significant differences at p <0.05.

112

approximately 4-fold. The insect repellent, DEET, also increased the expression of this
gene for more than 8-fold. Although the natural phytoestrogen a-zearalanol decreased the
expression of all the 4 genes evaluated, only the decrease in 3BHSD2 was statistically
significant. The non steroidal analgesic anti-inflammatory drug (NSAAID) ibuprofen did

not produce any significant changes in the expression of the steroidogenic genes.

Hormone Production

In the group of drugs with different pharmaceutical applications several changes were
observed in hormone production. Ibuprofen and fluoxetine did not produce significant
changes in the production of any of the hormones analyzed compared to blank and
solvent controls. However, T production was decreased by clofibrate and DEET, while
E2 production was significantly inhibited by salbutamol and DEET. Also, the analgesic

acetaminophen produced a 2 fold increase in P concentrations (Table 3.4).

Pattern of Responses to Chemical Mixtures

Gene Expression

Exposure of H295R cells to lpg/L of EE2 for 48 h resulted in statistically significant
increases in the expression of the CYP11B2 and in the production of P and E2 by
approximately 2-fold. The expression of CYP19, CYP17 and 3BHSD2 were not affected
by EE2 but T production was decreased by this environmentally active compound. When
H295R cells were exposed to binary mixtures where one of the components was EE2 the

gene expression responses were very diverse (Table 3.5).

113

 

When exposed to trenbolone, the aromatase gene CYP19 was up-regulated
approximately 2.5-fold. Exposure to a mixture of trenbolone and EE2 caused a decrease
in CYP19 expression of as much as 50% compared to solvent control. Cyproterone up-
regulated expression of CYP19 more than 4-fold, but when exposed to a mixture of
cyproterone and EE2, expression of this gene was not significantly different from that of
the control. Although tylosin reduced CYP19 expression this reduction was not
statistically significant when compared to that of cells exposed to the solvent only. The
tylosin-EE2 mixture did not produce changes in the expression of this gene compared to
controls. Cyproterone significantly up-regulated the expression of the aromatase gene
CYP19 up to 4.6-fold and salbutamol did not produce any effects on this gene, but when
these two compounds are mixed together the expression of CYP19 is almost completely
inhibited. Salbutamol caused maximum induction of CYP17 which was more than 13-
fold; cyproterone on the other hand induced significantly this gene almost 3-fold. Neither
tylosin nor EE2 affected the expression of CYP17 moreover none of the binary mixture
studied affected significantly the expression of this gene.

3BHSD2 was the gene least affected by any of the treatments. Individual
exposures with the chosen chemicals did not produce any significant changes in the
normal expression of this gene. However, the cyproterone/salbutamol mixture
significantly decreased the expression of 3BHSD2. A variety of responses was also
observed for CYP11B2. This gene was increased significantly around 5-fold by EE2.
Mixtures of cyproterone and trenbolone with EE2 did not affect the expression of
CYP1 1B2, and although tylosin treatment significantly induced lO-fold the expression of

this gene, the tylosin/EE2 mixture only produced a 2-fold induction

114

 

Table 3.4 Gene expression and hormone production in H295R cells exposed to single drugs.

 

 

 

 

 

 

Treatment
Gene DMSO ACETA IBUPR SALBU CLOFI DEET F LUOX
0.1% 300 ugmL 250 ug/mL 50 ng/L 3 ug/mL 3 ug/mL 1 ug/L
CYPllBZ 1.001033 3.66 1089* 2.610.77 20010.38 4.671 124* 8.201 130* 5.69 0.77*
CYP19 10010.61 0.88 10.10 07210.01 18810.62 13010.15 0.5 10.04 1.41 10.09
CYP17 1.0010.10 0.6410.08 0.5510.08 13.64 1098* 1.0410.09 1.2610.13 0.9010.05
3BHSD2 1.00 10.13 0.45 1 0.20 0.371 0.23 1.05 1 0.19 0.66 10.03 1.04 10.44 0.691007
Hormone DMSO ACETA IBUPR SALBU CLOFI DEET FLUOX
300 ug/mL 250 ug/mL 50 ng/L 3 ug/mL 3 ug/mL 1 ug/L
Testosterone 1.00 10.27 1.121004 0.88 0.51 10.17 0.6810.13* 0.3910.01* 0.75 10.01
Progesterone 1.00 1 0.01 2.3 1015* 1.84 0.30 1 0.30 0.75 10.09 1.68 10.48 1.371008
Estradiol 1.00 10.32 05010.2 0.42 0.3210.32* 1.55 10.05 O.1710.10* 1.301030

A11 exposures were conducted for 48 h under standard conditions. All gene expression and hormone production values for
fold change relative to control given as means and standard devi ations. DMSO: Dimethylsulfoxide; ACETA:
Acetaminophen; lBUzlbuprofen; SALBUzSalbutamol; CLOFlzClotibrate; DEET: N,N-diethyl-3-methylbenzamide;
FLUOX:F1uoxetine. * Indicates statistically significant differences at p <0.05.

 

115

Table 3.5 Gene express1on and hormone product1on 1n H295R cells exposed to smgle chem1ca1s and to b1nary mixtures.

 

Treatment CYP17 CYP19 31311302 (31101132 PROG 11331 135111
3011111111 Control 1.041005) 0.99002) 094(009) 10010.01) 1.001001) 1.001027) 1.001032)
Ethynylestradiol 10510.13) 10510.13) 0.76(0.l) 4.88(0.88)* 2.7110.39)* 0.3610.12* 2.33(o.27)*
Ethynylestradiol+Trenbolone 05510.50) 05710.50) 0450.25) 1460.16) 2.72(1.67) 0.771 0.026) 3.7711.13)*
Ethynylestradiol+Cyproterone 0.88(0.01) 09910.03) 04310.33) I.28(0.39) 24910.42) 0.701014) 1.091019)
Ethynylestradiol+Tylosin 0.091043) 10410.44) 05410.47) 23310.27) 13910.95) 0.85(0.l7) 0.741009)
Cyproterone’rSalbutamol 0.76(0.27) 0.0110.00)* 0.33(0.06)* 25311.34) ND ND ND

1).-105111 10310.04) 0.491003) 1.321027) 9.9911.09)* 1.031004) 0.42(0.09)* 0.12(o.0s)*
Trenbolone 17910.41) 2.56(0.55)* 0.771015) 0.81(0.43) 0.721020) 0.48(0.09)* 1.60(0.25)
Cyproterone 2.111(0.50)* 4.62(1.51)* 0.901032) 1.341052) 1021030) 0.290031 1.251047)
Salbutamol 13.041051 1.001019) 1.88(0.62) 2.00(0.38) 03010.30) 0.5110.17)* 0.3210.32)*

 

aAll exposures were conducted for 481 under standard conditions. All gene expression and hormone production values for fold change
relative to control given as means and standard deviations.

bConcentrations of single chemicals and mixtures exposures were: Ethynylestradiol (1 ug/l). Trenbolone (25ug/1), C yproterone (62ug/1),
Tylosin (3ug/ml), Salbutamol.(50ng/1).

ND No Data.

* Indicates statistically significant differences at p <0.05.A11 treatment comparisons made to solvent control

116

that showed to be not statistically significant.

Hormone Production

Responses in hormone production by cells exposed to the mixtures could not be predicted
from the results for the individual chemical exposures. Although T production was
reduced significantly by all of the five chemicals chosen for the mixture treatments,
binary mixtures of these compounds with EE2 did not show significant changes in T
production when compared to values from solvent controls.

Production of P was only significantly increased by treatment with EE2 when
exposed to compounds individually. However, the cyproterone-E2 mixture increased the
production of P by more than 2-fold. E2 production, on the other hand, was significantly
increased by more than 3-fold by the trenbolone-EE2 mixture. Exposure to the tylosin-

EE2 did not cause significant changes in the production of any of the hormones analyzed.

Dose-Response Analysis

 

Gene Expression
Dose-response curves were constructed after 48 h of exposure to trenbolone, EE2, and
cyproterone in the ranges of 0-39 pg/l, 0-150 pg/L and 0-45 pg/l respectively. Relative
expression of 3BHSD2, CYP11132, CYP17 and CYP19 values normalized to B-actin were
compared to solvent controls. 17BHSD1 responses were also analyzed for cyproterone
and trenbolone only.

In the EE2 exposure (Figure 3.1) 3 BHSDZ, CYP17 and CYP19 were not affected

by the different concentrations of this chemical, however, CYP11B2 expression values

117

tend to start increasing at 1.5 pg/l and be constant up to 75 pg/l where expression levels

started to rise again. For the cyproterone exposure (Figure 3.2), 3BHSD2, CYP19 and

 

Dose Response
Ge ne Expression

4.5 1
4.0 4
3.5 4
3.0 <
2.5 w
2.0 «
1.5 -
1.0 -
0.5 -

0.0+—-—— . . . -___ . . 1
o 0.15 0.75 1.5 15 75 150

a (uglL)

 

+3BHSD2
—e—CYP11BZ
+CYP17
—o—CYP19

Fold

 

 

 

 

 

 

 

 

 

 

 

 

 

Dose Response
Hormone Production

18.0 1
16.0 -
14.0 1
12.0 -

— —- PROGESTERONE
10.0 -

------- TESTOSTERONE
—— ESTRADIOL

Fold

 

 

 

o 0.15 0.75 1.5 15 75 150
EE2(ugIL)

 

 

 

 

 

Figure 3.1 Dose-response curve for the expression of steroidogenic genes
and hormone production after 48h exposure with different
concentrations of Ethynylestradiol.

118

 

 

 

 

 

 

 

 

 

 

 

 

 

 

 

Dose Response
Gene Expression
3.5 -
3.0 1
2-5 7 + 33113132
3 2.0 1 —I— CYP17
13 1.5 ~ —o—CYP19
1.0 - +17BHSD1
0.5 n
0.0 1— 1 fl
0 0.09 0.9 9 45
CYPROTERONE (ugIL)
5 Dose Response
Hormone Production
35.
3 1
25.
Fold 2 _ — — PROGESTERONE
- . . . TESTOSTERONE
1'5‘ ESTRADIOL
1 a
0.5
o . . , , _
o 0.09 0.9 9 45
CYPROTERONE (ugIL)

 

 

_,-J

 

Figure 3.2 Dose-response curve for the expression of steroidogenic genes
and hormone production after 48h exposure with different
concentrations of Cyproterone.

119

l7BIISDl expression remained at basal levels, while the androgenic gene CYP17
increase in expression to approximately 3-fold to a concentration of 0.9 pg of
cyproterone/l. Expression of none of the 5 genes studied in the dose-response exposures,
changed when exposed to trenbolone at concentrations ranging from 0 to 780 pg/l
(Figure 3.3). Most of the genes fluctuated positively around basal values of expression,
except for CYl IBZ which showed a decrease in expression at 78 pg/l but then at greater

concentrations, such as 780 pg/l, expression levels returned to basal values.

Hormone Production

Production of P and T remained at control concentrations for exposures of trenbolone
concentrations ranging from 0 to 39pg/l. In contrast, E2 concentrations increased rapidly
and significantly at trenbolone concentrations greater than 7,8 x 10'2 pg/l (Figure 3). The
6-fold induction at this concentration was kept up to 0.78 pg/l then started to rise again at
7.8 and 39 pg/l reaching a maximum of almost a lO-fold increase. The dose-response
curve for the production of T was constant and did not change due to EE2 exposure.
Moreover, P production started to increase at 0.15 pg/l of EE2 concentration reaching an
8-fold maximum induction when at 1.5 pg/l EE2 concentrations. P production then
returned to basal at concentrations of 15 pg/l of EE2.

The dose-response curve for hormone production in response to cyproterone
exposure was bimodal through the concentration range of 0 to 45 pg/l (Figure 3.2). P and
T production were slightly greater than control when exposed to 0.09 pg/L of
cyproterone, then decreased at 0.9 pg/l and it was raised again at 9 pg/l remaining

constant up to 45 pg/l cyproterone. E2 production followed the same pattern as P and T

120

 

Dose Response
Gene Expression

1.80 1
1.60 -
1.40 -
1.20 1
1.00 ~
0.80 -
0.60 4
0.40 -
0.20 -

1
0.00 1 f T 1 . . .
O 0.078 0.78 7.8 39 78 780

TRENBOLONE (uglL)

+3BHSD2
+CYP11BZ
+CYP17
—o—CYP19
+17BHSD1

Fold

 

 

 

 

 

 

 

Dose Response

11.0
10.01
9.0 -
8.0 1
7.0 -
6.0 -
5.0 -
4.0 -
3.0 -
2.0 J
1.0 J
0.0 1 1 1 1 1

0 0.078 0.78 7.8 39
TRENBOLONE (uglL)

— — PROGESTBROI‘E
- - - -TESTOSTBRONE
—ESTRAD|OL

Fold

 

 

 

 

 

 

Figure 3.3 Dose-response curve for the expression of steroidogenic genes
and hormone production after 48h exposure with different
concentrations of Ethynylestradiol.

121

but at greater fold values. Maximum increments of E2 production were around 2.5-fold,

while for P and T it reached less than 1.5-fold.

Relationship between gene expression and hormone production

The relationships between gene expression and hormone production were investigated by
correlation analyses with all the chemicals and by group, that is, for the antibiotic group
and the hormone therapy group separately (Tables 3.6-3.8).

A Pearson correlation matrix for all data from individual exposures showed small
positive and negative correlations between the 4 genes studied and between the 3
hormones analyzed. To ascertain the validity of these correlations Bonferroni
probabilities were also calculated. The results of these analyses indicated that by pooling
all treatments together only one correlation was statistically significant and it was the
negative correlation between the responses of the aromatase gene CYP19 and the
aldosterone gene CYP1 1B2. No statistically significant correlations between hormone
production and gene expression were observed for this group of treatments.

Correlations for the group of antibiotics not only showed the correlation
established before between CYP19 and CYP11B2 but also a positive correlation between
the CYP19 and CYP17; both correlations were of statistical significance. Again, no
significant correlations between gene expression and hormone production were observed.
A single correlation was observed between expression of CYP19 and CYP17 for the
group of chemicals used for hormone therapy, but the one correlation between CYP1 1B2

and CYP19 was not observed.

122

DISCUSSION

Previous studies have demonstrated the utility and effectiveness of the H295R assay in
identifying the potential harm that compounds may exert at different points in the
steroidogenic pathway (Hilscherova et al., 2004; Hecker et al., 2006; Zhang et al., 2005;
Gracia et al., 2006; Blaha et al., 2006). With the H295R cell culture system not only is it
possible to analyze gene expression and hormone production, but also to evaluate enzyme
activity. Moreover, this cell system has proven to be usefiil in identifying chemical
mechanisms of action, in establishing patterns of gene and hormone responses, and also
in the analysis of different interactions between chemicals when present in complex
mixtures. Results from the experiments conducted in the present study confirm once
more the effectiveness of the H295R screening system and its capacities when examining

steroid production at environmentally relevant chemical doses.

Pattern of Responses by Group of Chemicals

Antibiotics

The results from the present study demonstrate that pharmaceuticals have the potential to

negatively interfere in the normal pathway of steroid production. Particularly, antibiotics

showed to have a broad range of effects on steroidogenesis.

123

 

Table 3.6 Pearson correlation matrix for steroidogenic genes and steroid
hormones for all chemical treatments.

CYP11B2 CYP17 CYP19 3flHSD2 TEST PROG ESTR
CYP11B2 1.000
CYP17 -0.136 1.000
CYP19 -0.395* 0.276 1.000
3BHSD2 0.061 0.173 0.336 1.000

TEST -0.367 -0.148 -0.040 0.127 1.000
PROG 0.254 -0.079 -0.285 -0.042 0.239 1.000
ESTR -0.065 0.193 0.191 -0.008 -0.207 0.088 1.000

 

Testosterone2TEST, ProgesteronezPROG, EstradioleSTR.
* Indicates statistically significant correlations at p <0.05.

124

Table 3.7 Pearson correlation matrix for steroidogenic genes and steroid hormones
for the antibiotic treatments.

CYP11B2 CYP17 CYP19 3BHSD2 TEST PROG EST

 

R
CYP11B2 1.000
CYP17 -0.353 1.000
CYP19 -0.803 * 0.747* 1.000
3BHSD2 -0.078 0.272 0.191 1.000
TEST -0.408 -0.052 0.299 0.404 1.000
PROG 0.452 -0.511 -0.656 -0.159 -0. 132 1.000

ESTR -0.107 0.121 0.133 -0.382 0.189 0.376 1.00

0
TestosteronezTEST, ProgesteronezPROG, Estradiol:ESTR.

* Indicates statistically significant correlations at p <0.05.

125

Table 3.8 Pearson correlation matrix for steroidogenic genes and steroid hormones
for the hormone therapy treatments.

CYPllBZ CYP17 CYP19 3BHSD2 TEST PROG ESTR
CYP11B2 1.000

CYP17 -0.758 1.000
CYP19 -0.677 0.913* 1.000
3BHSD2 -0.255 0.567 0.728 1.000
TEST -0.504 0.123 0.032 -0.023 1.000
PROG 0.430 -0.222 -0.254 0.1 11 0.062 1.000
ESTR 0.385 0.369 -0.297 0.259 0.191 0.783 1.000

 

Testosterone: TEST, Progesterone: PROG, Estradiol: ESTR.
* Indicates statistically significant correlations at p <0.05.

126

The semisynthetic B-lactam antibiotics amoxicillin and cephalexin, although they have
the same therapeutic mechanism of action, their effects on both steroidogenic gene
expression and hormone production, were quite different. In the case of the semi-
synthetic macrolide antibiotics, erythromycin and tylosin, both caused the same gene
expression profile, but they differed in the hormone production profile. Amoxicillin and
cephalexin have in common the B-lactamic ring in their chemical structures, while
erythromycin and tylosin both have a macrolide ring; all of these chemicals are the result
of small structural modifications of their main structures that have been made in order to
improve their therapeutic properties. These small differences in chemical structure
between chemicals of the same group may be responsible for the differences observed in
gene expression and hormone production profiles since changes in chemical structure
translate into changes in physico-chemical properties that at the end are going to define
their different endocrine disruptive potential.

Since the effects of antibiotics on steroid production have not been previously
studied, the mechanisms by which these compounds exert their effects on steroidogenesis
are unknown. Based on the extensive use of antibiotics and their loadings to the
environment it therefore seems that endocrine effects may also need to be considered
along with the promotion of antibiotic resistance and the potential of these compounds to

influence growth in humans (Temak, 2004) and other non-target organisms.
Hormone Therapy Group

Drugs employed as hormone therapy agents have a broad range of medical uses.

Pharmaceuticals of this group are used in cancer treatment, birth control, for diagnostic,

127

 

and as growth promoters, among other uses. Cyproterone is a steroidal anti-androgen
with weak progestagenic activity used in the treatment of prostate cancer (Wirth et al,
2006). This drug exerts its functions by suppressing androgen action both by binding
directly to the androgen receptor and by inhibiting the positive feedback of androgens on
the pituitary ultimately resulting in reductions in the production of sex steroids (Sharpe et
al., 2004). The anti-androgenic properties of cyproterone were observed in the results for
hormone analysis where concentrations of T were reduced by up to one third. It is
noteworthy that the expression of CYP19 and CYP17 were increased, probably in
response to depletion of T in the medium. Induction of CYP17 would drive
steroidogenesis towards the production of androgens while increments in CYP19 activity
would ensure that E2 was produced despite small concentrations of substrate. Statistical
correlations for these two genes showed a great degree of significance for this group of
pharmaceuticals supporting the idea of a coordinated expression system.

EE2 is the most common and most potent estrogenic compound found in sewage
effluents (Sarmah, 2006). This synthetic E2 analog is used in combination with other
estrogenic substances in the manufacturing of contraceptive pills. Studies have
demonstrated the different effects of EE2 on the survival, sex ratio, gonadal growth,
spawning and sexual differentiation of aquatic organisms especially fish (Scholz and

Gutzeit, 2000). In H295R cells exposed to lpg/l of EE2 the production of P and E2 in

H295R cells were doubled, while T production was greatly reduced. The observed
decrease in T production may be a reaction to the increased production of E2 since T

production may be substrate limited.

128

Trenbolone acetate (TBA) is a synthetic steroid hormone commonly used to
enhance growth in beef cattle. TBA is quickly metabolized to the potent androgen 1713-
trenbolone (Durhan et al., 2006). Decreases in T production in the H295R cells may be
explained by the high affinity of 1713-trenbolone for the human androgen receptor, which
has been established to be similar to that of dihydrotestosterone (Bauer et al., 2001).
Because of this interaction between 17B-trenbolone and the androgen receptor it is
possible that cells responded to an apparent lack of T and induced the expression of the
aromatase gene CYP19 trying to keep E2 concentrations at normal levels.

a-zearalanol is the estrogenic equivalent of 17B-trenbolone; this chemical is the
active metabolite of the mycotoxin, zearalenone, that is obtained from F usarium sp
(Sheehan et al., 1984). a-zearalanol is also used in veterinary medicine as a grth
promoter. Exposure of H295R cells to zearalenone caused reduced E2 production, due
perhaps to the interaction of this estrogenic compound with the estrogen receptor,
mimicking a high abundance of E2. T and P production were not affected by this
chemical nor was the expression of the steroidogenic genes studied, except for 3BHSD2.

Together these results indicate that extensive attention must be directed to the use
and fate of pharmaceuticals with hormonal properties since this is a group of chemicals
that will surely produce significant effects when reaching non-target organisms. This is
especially the case for compounds used for veterinary purposes which may be excreted in
their active forms by treated animals and then reach aquatic ecosystems via runoff (Lange

and Dietrch, 2002).

Other Pharmaceuticals

129

Over the counter analgesics and anti-inflammatory drugs such as acetaminophen and
ibuprofen did not produce significant changes in gene expression or hormone responses.
Acetaminophen increased P production 2-fold, which may be responsible for the
induction of CYP11B2 since P is a precursor for this enzyme. No steroidogenic effects
have been demonstrated for acetaminophen and its exact mechanism of action as an
analgesic is unknown. Antilipidic drugs, such as clofibrate, are commonly used to treat
hyperlipidemia, a condition considered a major risk factor of cardio and cerebro-vascular
diseases. Despite being withdrawn from the market in most countries in Western Europe,
clofibrate concentrations in the ng/l to pg/l range have been reported in several sewage
treatment plant effluents (Koutsouba et al., 2003). In H295R cells clofibrate
concentrations of 3 pg/ml significantly reduced T production. Reduction of T levels by
this drug has also been observed in rat studies where it was suggested that clofibrate may
exert its action through direct effects on the microsomal enzyme systems responsible for
steroid metabolism (Xu et al., 2002).

Of interest where the results from the exposure with the drug salbutamol, a short-
acting, BZ-adrenergic receptor agonist used to treat broncho-spasm and in some cases is
used in obstetrics as a tocolytic to relax the uterine smooth muscle and delay premature
labor (Blanchard et al., 1993). Its mode of action is to bind Bz-adrenergic receptors with
greater affinity than Bl-receptors; the activation of Bz-adrenergic receptors results in
relaxation of smooth muscles. Salbutamol is also used in combination with other drugs
as a growth promoter in livestock. This Bz-adrenergic enhances lipolysis and the rate at
which fatty acids are oxidized producing leaner animals (Hemandez-Carrasquilla, 2003).

Thus, we hypothesized that the lipolytic effects of salbutamol could be responsible for

130

 

the significant decreases of almost 50% in E2 production compared to solvent controls.
The most obvious effect of this agonist compound was the increase in expression of the
androgenic gene CYP17 by more than 10-fold. More specific studies need to be designed
in order to know if this increase in the expression of CYP17 is in some way linked to

depletion of E2.

Effects of Drug Mixtures

 

From the beginnings of their use, pharmaceuticals have been entering the environment
and have been constantly detected at measurable concentrations; mostly they are
ordinarily found in mixtures of active ingredients with a variety of biological activities.
Thus, non-target organisms are being exposed to different biological actions at the same
time. Few toxicological studies have been conducted to address chronic mixture
exposure issues and. the risks associated with the presence of combinations of
biologically active contaminants (Crane et al., 2006). Developing an understanding of
the effects of complex mixtures of compounds acting together must become a priority
when evaluating the potential risks of pharmaceuticals in the environment. One of the
major difficulties in analyzing effects of complex mixtures is the understanding of the
different ways in which compounds in the mixture will interact to produce the final
effects.

H295R cells were exposed to 4 binary mixtures of different pharmaceuticals.
EE2, the most common component in birth control pills was a common component for 3
of the 4 binary mixtures prepared. Because of the effects of individual compounds on the

4 genes studied, cyproterone, trenbolone and tylosin were chosen as the second

131

component in the mixtures with EE2. In addition, due to the effects of cyproterone on
gene expression and salbutamol on hormone production, H295R cells were also exposed
to a mixture of these two compounds. Gene responses suggested that the chemicals
present in these mixtures interact mostly by antagonistic mechanisms, although agonism
was also observed in some cases. The dominant effects of EE2 were observed when in
mixtures with trenbolone, cyproterone, and tylosin. In particular, when expression values
produced by individual exposures of EE2 where greater than those produced by the
second component in the mixture, the joint effects observed were expression values
similar to those caused by the second component or the one who produced lower fold
inductions.

Different to gene expression, several type of interactions were observed for the
hormone production responses to the mixture treatments. For instance, for P the binary
mixtures produced the same effects produced by EE2, which was more than a 2 fold
induction in the production of this hormone, an indication that the EE2 effects prevail in
the mixture. On the other hand T production was down-regulated by all the individual
treatments but the mixtures did not produce significant changes in the concentration of
this hormone showing that these chemicals block each other’s antagonistic effects respect
to T production. On the contrary, the results of E2 showed that an additive effect was
produced by the mixture of EE2 and trenbolone; such a response is due to the affinity that
both of these compounds have for the ER. From these results it can be observed that the
steroidogenic effects exerted by the binary mixture exposures could not be predicted
from the results of exposures of the individual chemicals in question. As for an example,

cyproterone significantly up-regulated the expression of the aromatase gene while

132

 

salbutamol did not produced significant changes in the expression of this gene, when
together in a mixture, the expression of aromatase was completely down-regulated. This
corroborates the belief that not only do interactions between compounds occur but also
that their effects are usually different to individual responses. The results show that
pharmaceuticals and their mixtures act through additional unknown modes of toxic action
that have to be understood in order to truly assess their potential effects as environmental

contaminants.

Dose-Response Analysis
Three pharmaceuticals used in hormone therapy were selected to conduct dose-response
studies. The results showed that the dose-dependent changes in gene expression behaved
differently for each chemical. Exposure to EE2 affected only CYP11B2 expression. Of
the hormones, only T production was not affected by exposure to EE2. E2
concentrations were proportional to the concentration of EE2. Changes were observed
even at EE2 concentrations as small as 0.15 pg/l. The positive relationship between E2
production and EE2 in the medium is consistent with the great affinity of EE2 to for the
ER. Despite the continuous induction of CYP11B2 by EE2, P production was not
affected in the same manner. Increases in the production of this hormone were only
observed between 0.15 and 1.5 pg/l before returning to basal levels.

The anti-androgen cyproterone prevents dihydrotestosterone, the active form of T
in mammals, from binding to receptors in carcinoma cells. Thus, induction of CYP17
may be a response to the presence of the anti-androgen that results in an increase in the

production of active T to compete for the receptors. E2 was the only hormone to increase

133

proportionally with cyproterone concentration. The mechanisms by which this process
occurred are unknown.

Changes in trenbolone concentrations did not produce mayor effects on the
expression of any of the steroidogenic genes, or hormone production except for its effects
in E2. The production of E2 was greater than that in the control at all trenbolone
concentrations tested, although the expression of the aromatase gene CYP19 was not
increased, instead, T production stayed within the basal concentration range. These
results suggest the possibility that trenbolone induced the activity of the aromatase
enzyme by the activation of other pathways.

Chemicals with the same “mechanism of action” may have different effects on the
expression of steroidogenic genes and the production of steroid hormones. For instance,
although cyproterone and trenbolone both interact with the androgen receptor, each
caused different effects on gene expression and hormone production. Thus, it appears
that each of these chemicals, in addition to it’s interaction with the androgen receptor,
may induce, or inhibit other points in the pathway resulting in the observed differences in

the effects.

CONCLUSIONS

The versatility of the H295R assay system was proven to be useful in the evaluation of
the potential effects that commonly found environmental contaminants may exert on
steroidogenesis. For the first time the H295R cell system has shown how several
biologically active compounds such as pharmaceuticals, even at trace concentrations have

the potential to significantly affect the normal functioning of the endocrine system in

134

non-target organisms. Also, this system allowed the evaluation of the joint effects

 

produced by combinations of bioactive compounds in binary mixtures, mostly
antagonistic interactions were observed after exposures with binary mixtures of hormonal
therapy drugs. The construction of dose-responses curves provided valuable information
to identify genes and hormones that may be susceptible to changes in concentrations of
chemical exposure. It may be concluded, that the H295R cell bioassay is a very quick, .1
practical, and sensitive pre-screening method by which the endocrine disruptive effects of

environmentally relevant chemicals may be evaluated.

Acknowledgements

This study was funded by USEPA, 0RD Service Center/NHEERL, contract GS-10F-
0041L and supported by the Area of Excellence Scheme under the University Grants

Committee of the Hong Kong Special Administration. Region, China (Project No. AoE/P-

04/2004).

 

135

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141

Chapter 4
IN VITRO MODULATION OF ENDOCRINE FUNCTION IN H295R CELLS BY

EXTRACTS OF WATERS FROM THE VICINITY OF HONG KONG, S.A.R., CHINA

ABSTRACT

Recently Hong Kong has installed a sewage interceptor system for areas adjacent to
Victoria Harbor and treats the sewage and surface runoff at the Stonecutter’s Island
treatment facility. As part of an on-going evaluation of the effectiveness of this treatment
system, the H295R cell bioassay was used to evaluate the effects of methanol extracts of
marine waters taken at 22 points of suspected pollution in Hong Kong, China. Treated
and non-treated effluents from 2 major wastewater treatment plants were also assessed.
Modulation of expression of the steroidogenic genes CYP19, CYP17, 3BHSD2 and
CYP11B2 and production of the hormones progesterone (P), estradiol (E2) and
testosterone (T) were evaluated. No significant modulation of gene expression or
hormone production was caused by extracts of water collected from the wastewater
treatment plant (WWTP) effluents. Thus, it was determined that the waste water
effluents were treated to a level that should no result in endocrine modulation of marine
animals, including fish. Extracts from 2 fish culture sites were toxic to the H295R cells.
The expression of CYP19 was the most sensitive steroidogenic response observed.
CYP19 was down-regulated by extracts of water samples collected from areas receiving

effluents from older WWTPs and public filling areas.

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INTRODUCTION

A broad variety of detrimental reproductive disorders has been observed in wildlife
and possibly humans during the past decades. These occurrences have been linked to the
increasingly broad spectrum of environmental contaminants including both, natural and
synthetic compounds (Kavlock et al., 1996; EDSTAC Final Report, 1998). Although
there is still insufficient data to demonstrate specific associations between environmental
exposure and endocrine-mediated adverse effects, the continuous presence in the
environment of such compounds may represent a threat to the normal development of
organisms living in exposed aquatic ecosystems (Committee on Restoration of Aquatic
Ecosystems, 1992). For example, PAHs, pesticides, phthalate plasticizers, PBDEs,
dioxins, alkylphenols and steroids can be considered potential endocrine disrupting
chemicals (EDCs). Thus, there is a considerable body of evidence suggesting that most
of the contaminants frequently found in Hong Kong waters have the potential to produce
adverse effects on endocrine functions. EDCs can exert their disrupting effects by
different mechanisms but at present most of the bioassays to evaluate endocrine
disruption are designed to analyze only the interaction of individual chemicals with the
different hormone receptors. The need to evaluate endocrine disruption exerted by
pathways other than receptor-mediated mechanisms and the effects of EDCs mixtures has
resulted in development of new bioassays such as the H295R cell system (Gazdar et al.,
1990; Hilscherova et al., 2004). This in vitro system has been proved to be effective in
characterization of endocrine disruptive effects of individual chemicals, pharmaceuticals,
pesticides and their mixtures (Zhang et al., 2005; Gracia et al., 2006; Sanderson et al.,

2000; Blaha et al., 2006; Xu et al., 2006). As well as evaluating the expression of

143

steroidogenic genes, this assay also permits evaluation of hormone production and

enzyme activity.

Some of the causes of deterioration of water quality of the coastal marine
environment are lack of adequate sewage infrastructure, growing population, untreated
livestock waste, discharges of untreated sewage, industrial effluents and agricultural
runoff. Relatively great levels of pollution have been identified in Asian waters (Connell
et al., 1998; Monfils et al., 2006). In Hong Kong, SAR, China, for example, water
quality has significantly deteriorated over the last decade as a consequence of the
growing industrial activities and population increases (Wong et al., 1995; Yung et al.,
1999). Large amounts of bacteria, total nitrogen and poor levels of dissolved oxygen
have been identified in the most polluted spots in Hong Kong such as Victoria Harbor,
where 65% of the regions population live. Furthermore, pollution from the harbors
seems to be spreading to adjacent sensitive water bodies. The lower sections of the East
River (Dongjiang), which provides approximately 80% of the drinking water for Hong
Kong, is contaminated by organic and inorganic pollutants (Ho et al., 2003), including
metals such as cadmium, copper and zinc (lp et al., 2003; Hung, et al., 2006) and
persistent organic pollutants including polybrominated diphenyl ethers (PBDEs) (Liu et
al., 2005; Ramu et al., 2005), organochlorine pesticides and dioxin-like compounds (So et
al., 2005). Low levels of contamination of PBDEs have been also found in Hong Kong
marine waters, the concentrations found in a recent study ranged from 31 to 1.2x102 pg/l
(Wurl et al., 2006). It has been suggested that the presence of these compounds may
arise from the disposal of electronics industry waste in southern China, as well as the

discharge of untreated wastewater of local origin. Moreover, residual levels of DDTs and

144

 

polycyclic aromatic hydrocarbons (PAHs) have been found in freshwater and marine fish
sold in Hong Kong markets (Cheung et al., 2006).

Everyday in Hong Kong a population of almost 7 million people produces some
2.2 million cubic meters of sewage. Hong Kong has about 1,320 kilometers of sewerage
network running through it which all feed into some 200 sewage treatment plants. These
plants range from preliminary (screening) treatment plants to secondary (biological)
treatment plants treating sewage from residential, commercial and industrial premises in
the territory prior to disposal to the sea for dilution and dispersion through submarine
outfalls. About 95% of Hong Kong's population is now served by the public sewerage
system with over 98% of the sewage produced being collected and treated. All new
towns in the New Territories have been designed and developed with modern secondary
sewage treatment works, however older urban areas still have a very poor sewage
infrastructure that does not cater for their needs and has in the past not provided world-
class sewage treatment. In order to meet and manage development demands throughout
Hong Kong and the rise in people's living standards, Hong Kong's sewage infrastructure
is gradually being upgraded under a scheme referred to as the Strategic Sewage Disposal
Scheme (SSDS) - a sewerage rehabilitation and improvement program (Water Quality
Report, 2005). The whole scheme comprises a series of deep tunnels to collect and
transfer sewage from the central urban areas of Hong Kong and Kowloon to a centralized
treatment works at Stonecutters Island, were samples for this study were collected, and
then after treatment waters are sent to a submarine outfall south east of Lamma Island, a

point also sampled.

145

 

The present study was conducted to measure the potential for coastal marine waters
and effluents of the WWTPs of Hong Kong to contain mixtures of EDCs that can
modulate steroidogenesis in H295R cells (Figure 4.1). The areas selected for study were
considered to be impacted by contamination from human, industrial, and agricultural
wastewater. The sampling points for this study included STW influents and effluents,
fish culture zones, marine disposal and STW discharge areas, and public filling areas
which are very common in Hong Kong; these areas are designated as part of a
development project that accepts public fill for reclamation purposes and disposal of
public fill in a public filling area which requires a license issued by the director of civil
engineering department. The methodology involved the extraction of the water samples
using SPE techniques and exposure of the H295R cells to the extracts. Afier exposure
the expression of the steroidogenic genes CYP19, CYP17, 3BHSD2 and CYP11B2 was
evaluated using PCR protocols. Furthermore, the production of the hormones
progesterone (P), estradiol (E2) and testosterone (T) was evaluated using ELISA

methods.

MATERIALS AND METHODS

Sample Collection

Water samples were collected in July 2005 from 22 coastal marine areas and from 2
major waste water treatment plants in Hong Kong (Figure 4.2; Table 4.1). In addition to

areas known to receive sewage effluents, areas with intensive aquaculture and marine

146

 

CYP11A Cholesterol

 

 

 

 

17a-OH- C YP17 .
Pregnenolone Pregnenolone ' DHEA
l 3,6HSD2 1 3 BHSDZ 138HSD2
CYP17 CYP17 .
Progesterone T- 17a-OH- > Androstenedrone
Progesterone
CYP21 l CYP21 ll7BHSD1
1 l-Deoxy- 1 l-Deoxy- Testosterone
Corticosterone Corticosterone
l CYPllBl l CYPllBl l CYP19
Corticosterone Cortisol l7B-Estradiol
CYPIIBZ
Aldosterone
Zona Glomerulosa Zona F asciculata Zona Reticularis

Figure 4.1 Enzymes, substrates and products of the steroidogenic pathway in the
different zones of the human adrenal cortex.

147

disposal activities were also included. Water samples were collected using standard
depth and width integrating techniques designed to obtain a representative sample
(Shelton, L.R., 1994). Composite samples collected at each site were split into two pre-
cleaned amber glass bottles. Measurements of the collected water samples included pH,
dissolved oxygen (DO), conductivity, and temperature and were conducted with
calibrated instruments. Samples were immediately chilled and sent to the laboratory
where they were stored at 4 °C until they were filtered and prepared for extraction, within
24 h to keep degradation to a minimum and to avoid the need for addition of chemical

preservatives.
Extract preparation

Prior to extraction, each sample was vacuum filtered through a 70 mm glass fiber GF/F
filter (Whatman, Maidstone-UK) with a pore size of 0.7 pm and the retained particulate
material was washed with 0.5 mL of methanol which was added to the aqueous sample.
Following filtration, 1 mL of 200mg/mL NazEDTA was added to each liter of sample to
prevent compounds (such as the tetracycline antibiotics) from forming complexes with
divalent ions such as Ca2+ and Mg”. The pH of water samples was then adjusted to 3
using glacial acetic acid. To determine extraction efficiencies a trace amount of 3H-
testosterone was added to each one liter sample prior to extraction. Quantities of the 3H-
testosterone recovered were measured by scintillation counting. Solid phase extraction
cartridges, 200 mg Strata X (Phenomenex, Torrance, CA,USA) were washed twice using
2 mL of methanol, followed by conditioning with 3 aliquots of 2mL distilled water. One

liter of the prepared samples was pulled through the each washed and conditioned

148

 

 

Figure 4.2
Marine water monitoring stations in Hong Kong

 

 

Sampling points in a circle are those producing high toxicity to H295R cells
Water treatment plants

149

cartridge at lOmL/min using a vacuum pump. The cartridges were taken to dryness and
the retained compounds were eluted with 3 portions of 2 mL of methanol. In a
thermostatic bath set at 30 0C the extracts were then concentrated up to 1 mL final
volume under a gentle nitrogen stream. Finally, extracts were stored at -20 °C until

used for the exposures.

H295R cell bioassay

Protocols for culturing and exposure of H295R cells have been previously established
and validated (Hilscherova et al., 2004; Zhang et al., 2005; Hecker et a1, 2006).
Briefly, H295R cells were cultivated in an incubator at 37 0C in a 5% C02 atmosphere.
Cells were fed with supplemental media containing Dulbecco’s modified Eagle’s
medium, Nu Serum and ITS+ premium (BD Bioscience, San Jose, CA, USA). For
exposure, cells were cultivated in 25 cm2 flasks. After rinsing, cells were trypsinized
with 1.2 mL of trypsin per flask and incubated for 3 min maximum, then harvested and
mixed with supplement media to deactivate trypsin; 3 ml of cell suspension, containing

approximately 1x106 cells/ml, were placed in each well of a 6 well test plate.

To establish the range of extract concentrations that could be used without
causing cytotoxicity to the cells, a Live/Dead cell viability kit (Molecular Probes,
Eugene, OR, USA) was used. In instances where exposure resulted in cell death or
decreased viability the data were not used to evaluate gene expression or hormone
production. Exposures to the extracts were done at least 24 h of plating. Dosing
solutions of the extracts were prepared in medium by adding 10 pL of extract to 10 mL
medium to make methanol concentrations of 0.1%. A solvent control dose solution

was prepared adding 10 pL of methanol into 10 mL of medium. Cells were checked

150

under a microscope to assure good cell condition prior to dosing. The culture medium
was removed and cells were exposed to 3 mL of dosing solutions.

After 48 h of exposure, medium was removed and saved for hormone analysis.
RNA was extracted from the cells using Absolutely RNA RT-PCR miniprep kits
(Stratagene, La Jolla, CA, USA). Before nucleic acid isolation and hormone analysis,
cell viability was determined. Cells were visually inspected under a microscope to
evaluate viability and cell number. Quantity and quality of the extracted mRNA was
measured using spectrophotometric methods. After RNA extraction, reverse
transcription was conducted with the Cloned AMV First-Strand cDNA synthesis kit
(Invitrogen, Carlsbad, CA, USA). cDNA dilutions were prepared and qPCR conducted
using previously published methods by Hilscherova et al. in a Smart Cycler System
(Cepheid, Sunnyvale, CA, USA) in 25 pL sterile tubes using SyBr Green as
quantification dye. The steroidogenic genes analyzed by PCR were 3BHSD2,
CYP11B2, CYP17 and CYP19. For quantification of gene expression Ct values from
the PCR reactions were used to express the results as fold difference with respect to the
appropriate solvent control. Gene expression data was standardized to the expression

of B-actin.

Hormone quantification

Hormone extraction and quantification by ELISA were conducted as previously
described (Hecker et al., 2006). Briefly, frozen media samples were thawed on ice, and
the hormones were extracted twice with diethyl ether (5 ml) in glass tubes. To
determine extraction efficiencies a trace amount of 3H-testosterone was added to each

sample prior to extraction. Concentrations of hormones in media were measured by

151

competitive ELISA using Cayman Chemical® hormone EIA kits (Cayman Chemical
Company, Ann Arbor, MI, USA) for progesterone [Cat # 582601], testosterone [Cat #
582701], estradiol [Cat # 582251]. Because the antibody to progesterone exhibits
cross-reactivity with pregnenolone (P) of 61% and the method does not allow for the
separation of these two hormones, progesterone concentrations are expressed as the
sum of progesterone and pregnenolone. The working ranges of these assays for the
determination of steroid hormones in H295R media were detennined to be: progesterone
(P): 7.8 - 1000 pg/mL; testosterone (T): 3.9 - 500 pg/mL; 1713-estradiol (E2): 7.8 - 1000
pg/mL. Extracts were diluted 1:25 and 1:100 for T while for P and E2 dilutions were

1:50 to 1:100 and 1:2 to 1:10, respectively.

Statistical Analysis

Statistical analyses of gene expression and hormone production were conducted using
SYSTAT (SYSTAT Software Inc., Point Richmond, CA, USA). Differences in gene
expression were evaluated by ANOVA followed by Tukey’s Test. Differences with

p<0.05 were considered significant

RESULTS

Values for the physical and chemical characteristics varied among locations (Table
4.1). In general, the lowest pH values were measured in waters from the STPs, where
values were approximately 7.5. However, untreated waters from the Sha Tin treatment
plant had a pH of 8.34. The greatest pH value (8.76) was measured in the vicinity of

the effluents from San Wa system treatment works (STW). Salinity values ranged from

152

1 1.5 to 36 %o, among locations. The minimum and maximum salinities were observed
in samples of treated effluents from the Sha Tin WWTP and the public filling area
Tseung Kwan (HK17), respectively. Dissolved oxygen ranged from a minimum of 0.2
mg/L in untreated sewage from the Sha Tin WWTP to 0.8 mg/L in treated waters from
the Stonecutters Island WWTP. Dissolved oxygen concentrations in coastal marine
waters ranged from 3.8 to 9.6 mg/L.

Extracts from neither the Sha Tin nor Stonecutters Island WWTP produced
significant changes in the expression of any of the 4 steroidogenic genes (Figure 4.3)
and only extracts from the non-treated water from the Sha Tin WWTP affected the
production of E2. Treatment with the extract of effluent from the Sha Tin WWTP
caused a 30% reduction in E2 release compared to the solvent control. P production
was increased significantly by extracts of non-treated waters from the Stonecutters
Island treatment plant. T production was not affected significantly by any of the
extracts from the treatment plants. None of the extracts from water samples taken after
treatment significantly affected the expression of the steroidogenic genes nor the

production of any of the hormones studied.

Extracts from samples taken from 2 of the major fish culture zones, Yim Tin
Tsai (HK04) and the L0 Tik Wan open-water fishing zone (HK09) were very toxic to
H295R cells even at 104 — 105 dilutions, to the point of inhibiting cell growing and
proliferation with consequent death. This effect suggests the presence of extremely

toxic compounds.

153

 

 

Gene Expression

21x1-
L80-1
160-1 _
1'40 _ 3% EJCYP19

133- ICYP17

030- 1 T i 8 ‘3 §3BHSD2
0.50 - " " " BCYPIIBZ
040-«ifi
1120—«§§
(too-«‘7

     

Fold

 

 

uuuunuunuuuufifii

 

 

 

 

 

   

I

MeOH WTPl-NT WTPl-TT WTPZ-NT WTPZ-TT
Sites

 

 

 

 

 

Hormone Production

1.80 -
1.60 r
1.40 r
1.20 r
1.00 r
0.80 r
0.60 r
0.40 r
0.20 n
0.00

PROG
[1]] TEST
ESTR

Fold

 

 

 

 

 

 

 

 

 

 

 

 

WTPl-NT WTPl-TT WTPZ-NT WTP2-TT
Sites

 

 

 

Figure 4.3. Gene expression and hormone production for methanolic extracts from
water samples from major water treatment plants in Hong Kong, SAR, China. WTPl:
Shatin; WTP2: Stonecutters; NT: Before treatment; TT: After treatment. All exposures
were conducted for 48 h under standard conditions. All values are expressed as fold
change relative to control. * Indicates statistically significant differences at p <0.05.

154

Table 4.1. Sampling points for marine waters in Hong Kong, SAR, China

 

 

Sample Name Activity Temperature pH D0 a Salinity
0(3 mo %
HK01 Tung Ping Chau Reference Site 29.6 8.29 6.7 16.0
HK02 Ap Chau, Kat 0 Fish culture 28.3 8.60 8.1 34.0
HK03 Sai Lau Kong Fish culture 29.1 8.63 8.6 35.0
HK04 Yim Tin Tsal Fish culture 27.8 8.63 8.0 30.8
HK05 Young Shue Au Fish culture 26.6 8.46 7.2 34.0
HK06 Tap Mun, Kau Lau Fish culture 27.2 8.44 6.9 34.2
HK07 Ma Nam wat Fish culture 29.5 8.38 6.6 35.2
HK08 Leung ShuenWan Fish culture 26.5 8.39 6.6 33.0
HK09 Sok Kwi Wan Fish culture 26.8 8.17 5.4 31.2
HK10 Oyst Oyster Production 29.4 8.04 5.4 16.0
HKll Mai Po Marine Reserve 24.8 8.33 6.5 28.5
HK12 Tuen Mun Public filling area 28.6 8.61 8.7 23.2
HK13 Sha Chau (East) Marine disposal 26.2 8.43 6.0 28.0
HK14 Tsin Yi (South) Marine disposal 24.4 8.40 5.5 30.2
HKIS Cheung Chau (South) Marine disposal 26.0 8.56 8.0 31.8
HK16 Wan Cha (East&East) Disch.STWb 24.2 8.25 5.5 25.0
HK17 Tseung Kwan Major reclamation s. 26.8 8.37 5.3 36.0
HK19 Stonecutters lsland Disch. STW 24.7 8.36 6.4 28.2
HK20 Pennys Bay Major reclamation s. 25.5 8.52 7.5 33.2
llKZl Mu Wo Disch. STW 27.0 8.59 8.3 32.2
HK22 Aberdeen & Ao Lei STW & Fish culture 26.6 8.21 4.9 30.0
HK23 Tolo Harbor Disch.. STW 26.7 8.37 5.7 34.0
HK24 North Poing Disch..STW 26.1 7.97 3.8 27.2
HKZS San Wa Disch..STW 27.6 8.76 9.6 31.0
HK26 Pilaf Port Disch.. STW 29.0 8.60 8.6 20.8
HK27 Cogeneration Plant Power plant 29.6 8.29 6.7 16.0
HK28 Shatin-untreated STW 29.3 8.34 0.2 13.2
HK29 Shatin- treated STW 30.2 7.48 6.7 l 1.5
HK30 Stonecutters untreated STW 28.8 7.94 1.4 13.8
_Fl;_(31 Stonecutters- treated STW 28.8 7.56 0.8 13.8

 

a b
DO: Dissolved Oxygen; STW: Sewage Treatment Works

155

 

The expression of the aromatase gene (CYP19) was the most affected of the 4 studied,
genes (Table 2). CYP19 expression was significantly decreased by sample extracts
from 2 of the 8 fishing culturing zones sampled (HKOS and HK08). A sample from a
small fish culture zone, known as Wong Wan (HK03), did not produce significant
changes in the expression of the aromatase gene but increased the expression of
3BHSD2 and CYP1 182. Only increments in CYP11B2 were statistically significant
and no changes in hormone production were exerted by this sample. The extract from
one particular sample, HK22, taken close to the Aberdeen and A0 Lei Chao sewage
treatment works, not only decreased significantly the expression of the aromatase gene
but also the expression of the androgenic gene CYP17. Although extracts from this
sample also increased by more than 2-fold the production of P and E2 hormones, the

increases were not statistically significant when compared to solvent control values.

Extracts of waters from the Central reclamation site (HK16) located between
Kowloon and Hong Kong Island, not only suppressed the expression of the aromatase
gene, but also induced by almost lO-fold the expression of the aldosterogenic gene
CYP11B2. Sample HK25 corresponding to the extract of waters receiving effluents
from the old STW from San Wa, with a flow of 36000 x 1000 m3/yr and 7300 ton/yr of
suspended solids, not only suppressed the expression of CYP19 but also increased
significantly, by almost 4—fold, the production of E2 (Table 3). CYP19 was also
decreased by several sample extracts taken from sites affected by effluents of major
public sewage treatment works. Despite the decrease in the expression of the
aromatase gene, no consequent significant alterations on E2 production were observed

for samples affecting CYP19 expression.

156

 

 

Table 4.2 Gene expression results for methanolic water extracts.

 

 

 

Gene
CYP19 CYP17 3BHSD2 CYP11B2
Sample Mean STD Mean STD Mean STD Mean STD
Blank 1.08 0.57 1.37 1.38 1.20 0.18 1.03 0.03
MeOH 1.00 0.02 0.96 0.05 1.07 0.10 1.00 0.01
HK01 1.04 0.12 1.36 0.21 1.87 0.28 1.56 0.32
HKll 0.03* 0.00 0.68 0.14 0.92 0.11 2.29 0.19
HK02 1.13 0.10 1.09 0.06 2.08 0.27 4.53 1.67
HK03 1.03 0.04 0.97 0.13 2.60 1.34 5.31* 0.10
HK05 0.04* 0.01 0.76 0.21 0.80 0.07 3.52 0.36
HK06 1.16 0.09 1.48 0.35 0.89 0.41 2.64 0.35
HK07 0.97 0.10 0.97 0.03 ND ND ND ND
HK08 004* 0.00 0.59 0.05 0.96 0.05 2.30 0.21
HK10 0.93 0.02 0.95 0.14 1.55 0.69 4.57 0.28
HK12 1.02 0.01 0.92 0.03 1.72 0.41 1.19 0.38
HK13 1.08 0.20 1.02 0.11 1.31 0.44 2.80 0.52
HK14 0.02* 0.01 0.35 0.43 0.64 0.52 2.28 0.40
HK15 0.96 0.01 0.89 0.01 0.73 0.05 1.80 0.39
HK16 0.01* 0.00 0.53 0.05 0.40 0.00 9.87* 0.54
HK17 0.01* 0.00 1.10 0.07 0.38 0.03 3.48 0.33
HK19 1.12 0.05 0.94 0.14 0.87 0.30 1.89 0.44
HK20 0.01* 0.00 0.90 0.01 0.32 0.02 3.90 0.35
HK21 1.07 0.08 1.02 0.06 1.11 0.32 3.02 0.82
HK22 0.01* 0.01 0.09* 0.07 0.37 0.18 2.48 0.19
HK23 0.17* 0.18 0.42 0.05 0.34 0.13 0.62 0.09
HK24 0.01* 0.00 0.66 0.02 0.41 0.00 3.29 0.65
HK25 0.03* 0.03 0.48 0.62 0.57 0.58 2.81 0.28
HK26 0.01* 0.00 0.78 0.02 0.36 0.03 2.58 0.18
HK27 2.53 0.28 1.82 0.01 0.62 0.09 1.93 0.16

 

All exposures were conducted for 48 h under standard conditions. All gene
expression values for fold change relative to control given as means and standard
deviations. * Indicates statistically significant differences atJ)<0.05

 

157

Table 4.3 Hormone Production in H295R cells exposed to methanolic
extracts of marine waters from Hong Kong. a

 

 

 

Hormone
PROG TEST ESTR

Sample Mean STD Mean STD Mean STD
Blank 1.88 1.13 0.95 0.37 1.24 0.51
MeOH 1.00 0.21 1.00 0.13 1.00 0.02
HK-Ol 2.57 0.66 0.96 0.46 2.29 1.05
HK-02 2.86 1.24 1.10 0.24 2.97 0.90
HK-03 { 1.58 0.33 1.01 0.23 2.43 0.04
HK—05 1.88 0.43 1.34 0.23 2.76 1.06
HK—06 1.13 0.42 0.73 0.10 0.92 0.05
HK-07 2.90 1.92 1.01 0.08 2.48 0.15
HK-08 1.31 0.34 0.91 0.09 2.67 0.12
HK—lO 0.77 0.02 0.68 0.09 0.83 0.18
HK-12 1.66 0.88 0.69 0.14 2.22 0.81
HK-13 1.72 1.10 0.80 0.04 1.03 0.25
HK-l4 3.01 0.72 1.04 0.07 2.32 0.13
HK-15 0.58 0.38 0.32 0.06 0.84 0.07
HK-l9 1.96 0.83 0.77 0.15 1.15 0.16
HK-Zl 1.86 1.15 0.99 0.19 1.14 0.38
HK-22 2.26 1.29 0.99 0.20 3.04 0.57
HK-25 3.11 1.30 1.32 0.15 3.61 * 0.57
HK-27 1.14 0.05 0.95 0.08 0.89 0.10
HK-16 0.93 0.15 0.87 0.06 0.84 0.12

 

aAll exposures were conducted for 48 h under standard conditions. All
hormone production values are expressed as fold change relative to
control given as means and standard deviations. PROGzProgesterone;

TESTzTestosterone; ESTR:Estradiol
* Indicates statistically significant differences at p <0.05.

158

DISCUSSION

Results from this study strongly suggest that treatment used in both plants, Sha Tin and
Stonecutters Island are effectively removing most of the compounds and metabolites
present in raw waters that may exert significant changes in endocrine functions such as
steroid production. Moreover, it may suggest that effluents from these water treatment
plants reaching the aquatic environment may not represent a threat for endocrine

activities of living organisms in the surrounding areas.

The cause of the cytotoxicity provoked by 2 of the extracts from marine waters
from areas used as fish culture zones (HK04 and HK09) remains unknown. The
compounds causing the toxicity of these extracts may be of industrial origin; moreover
their presence in such a complex mixture may provoke interactions that may be
responsible for the extreme toxicity caused in the H295R cells. Further evaluation of
these 2 samples must be conducted because the high toxicity, and probable unwanted
effects, may be transmitted through the food chain and may be reaching

microorganisms and wildlife from other ecosystems and most importantly, humans.

The aromatase gene CYP19 regulates the production of the aromatase enzyme
responsible for converting T to E2. Several of the Hong Kong sample extracts were
capable of decreasing significantly the expression of the CYP19 gene although no
significant changes were observed in E2 production. Moreover, some samples (HK25)
even showed an increase E2 production. This probably indicates the presence of
mixtures of compounds that may affect aromatase gene expression but do not affect the
activity of the aromatase enzyme per se, or that are capable of increasing E2 production

by other unknown mechanisms.

159

Studies conducted in the northwestern waters of Hong Kong have indicated the
continued presence of polychlorinated biphenyls (PCBs) and organochlorine pesticides
together with considerable bioaccumulation of metals in marine mammals native to the
region (Ip et al., 2003; Tam and Yao, 2002). Results of exposure of H295R cells to
PCBs have previously demonstrated the down-regulation of the androgenic gene
CYP17 by these chemicals (Li and Wang, 2005), thus, the presence of these
compounds in the samples collected in the Aberdeen and A0 Lei area (HK22) may be
responsible for the observed decreases in the expression of this gene.

To assess realistically the significant up-regulation of the CYP1 lBZ expression
and E2 production observed in these results, and most of all, the significant decreases in
the expression of CYP19 and CYP17 and the severe toxicity caused by several of the
water extracts further investigation must be conducted. Chemical analysis is required

to formally link the effects to known EDCs.

CONCLUSIONS

The results from this study confirm that the H295R cell bioassay is a reliable method to
identify the potential endocrine disruptive effects of environmental contaminants.
Although the constant upgrade in the infrastructure of the newly constructed WWTPs
in Hong Kong together with the new strategies established for sewage disposal in the
region provide good results in terms of the elimination of EDCs from waste waters, the
significant endocrine disrupting effects caused by complex environmental samples from
marine and other surface waters are a clear indication of the presence of pollutants in

the different aquatic ecosystems in Hong Kong waters. These pollutants possibly come

160

from sources other than the effluents coming from the modern WWTPs. Chemical
analysis to identify and quantify compounds present in the marine water extracts may
provide more specific information about the chemical complexity of the samples to
which cells were exposed. Based on results from this study, additional in vitro and in
vivo experiments should be conducted to determine the physiological effects that may
indicate the molecular changes of gene expression and hormone production observed
after exposure with compounds extracted from the water samples.

The development of tools such as the H295R bioassay helps considerably not
only to identify the potential effects that these contaminants may exert on living
organisms, but also to elucidate some aspects of their chemical origin when it is
unknown. The H295R cell bioassay may be a useful tool for the identification of areas
where the presence of environmental pollutants is suspected. Moreover, this rapid,
sensitive, and cost-effective cell bioassay may be also used to evaluate the endocrine

toxicity of residual waters, industrial or STW effluents entering aquatic environments.

Acknowledgements

The work described in this paper was supported by the Area of Excellence Scheme
under the University Grants Committee of the Hong Kong Special Administration
Region, China (Project No. AoE/P-O4/2004) and supported by USEPA, ORD Service
Center/NHEERL, contract GS-lOF-0041L. The authors gratefully acknowledge the
invaluable help of Mr and Mrs Kwok on the journeys of sample collection. Many

thanks to Eric Ching and James Lam from City University of Hong Kong for their

161

excellent job on the planning and execution of the field sampling strategies required for

this study. Special thanks to Alice Chang for all the helpful discussions.

162

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SUMMARY AND CONCLUSIONS

The studies in this dissertation are centered on the validation and evaluation process of
the novel H295R cell bioassay recently developed as a pre-screening system for the
analysis of the potential endocrine disruptive effects of compounds. Chapter 1
described briefly the functions of the endocrine system and more in detail the steps of
the steroidogenic pathway; it also described the different mechanisms by which
thousands of compounds may interfere with the normal functions of the endocrine
system in humans and wildlife, emphasizing the importance of the continuous
development of practical tools for the early detection of the different endocrine
disruptive properties of compounds. Since hormones, the main executors of endocrine
functions, exert their actions through receptor mediate mechanisms, most of the assays
available for the evaluation of endocrine disruptive properties of compounds are based
on chemical-receptor interactions; since several studies have demonstrated that
endocrine disruptive effects are not only exerted via receptor interaction, but others
such as inhibition of hormone synthesis, transport or metabolism, new methodologies
are urgently required to complete the evaluation of the potential endocrine disruptive
properties of substances. The H295R cell line, a human cell line derived from
carcinogenic tissue of the adrenal glands, represents the ideal system for the evaluation

of chemical effects on steroidogenesis. The ability of this cell line of produce most of

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the steroidogenic hormones synthesized in the 3 different zones of a normal adrenal
gland, allows the evaluation of the potential modulative effects of compounds on
steroidogenesis at the level of gene expression, enzyme activity and steroid production.
The versatile method developed during the execution of this thesis uses the
H295R cell line as the exposure system. Exposure and Q-RT-PCR methods were
developed for the analysis of the expression of genes encoding for 10 of the most
important enzymes controlling the steroidogenic pathway. Chapter 2 of this
dissertation focused on the validation of the developed molecular methods using model
chemicals which are well known for their inductive or down-regulative properties.
Dose response curves and time course experiments using the developed exposure and
PCR methods were conducted to evaluate their validity and versatility in identifying
concentration changes and exposure times. The model chemical with inductive effects
chosen for the validation study here described was forskolin, a compound capable of
resensitizing cell receptors by activating the enzyme adenylcyclase and increasing the
levels of cyclic AMP in cells, which is an important signal carrier that is necessary for
the proper biological response of cells to hormones. Among the inhibitory chemicals
analyzed were aminoglutethimide, because of its properties as an aromatase inhibitor;
ketoconazol and metyrapone were also included for its inhibitory effects on the
enzymes l4-a-desmethylase, and ll-B-Hydrolase which is responsible for the
conversion of deoxycortisone to corticosterone. In addition, the H295R cell bioassay
was tested in its effectiveness identifying interactive effects when exposed to mixture
of inducers and inhibitory chemicals, as the real EDCs are present in the environment

when they exert their disruptive effects. Furthermore, quantification of hormone

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production after exposure to individual chemicals and binary mixtures was conducted.
Progesterone, testosterone and estradiol were the steroidogenic hormones analyzed by
the ELISA methods described in Hecker, et al. The results from the dose response and
time course experiments, proved the versatility of the H295R cell bioassay to show that
not only genes respond differently to the changes of chemical concentration, but also
that groups of genes react in similar manner to these concentration changes, which may
suggest a mechanistic linkage in the gene regulation process. Gene expression data
also showed that the most affected genes were those encoding for enzymes regulating
final hormone production rather than those involved in substrate production which may
be an indication of the sensitivity of the final reactions leading to the final products.
The differences in effects on gene expression at different exposure times indicate that
time is an important factor when evaluating steroidogenic gene expression. The data
collected after the exposures with mixture of chemicals with inductive and inhibitory
activity showed the complexity of the mechanistic effects taking place when chemicals
with such difference in properties interact. Moreover, it was clearly observed that
individual responses can not always predict interactive effects. One important
conclusion reached after correlating gene expression and hormone data was that
hormone production is not necessarily directly affected by changes in gene expression.
After the results from the validation process detailed in chapter 2, the
effectiveness of the H295R cell bioassay was tested through exposures with real
environmental contaminants with high potential for endocrine disruptive effects.
Because of their uncontrolled and demanding use, and their continuous presence in

aquatic environments, 18 of the pharmaceuticals most used in the United States where

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chosen for the evaluation process. Prescription and over the counter drugs of different
therapeutic groups and of known and unknown endocrine disruptive properties were
chosen for the evaluation process of the H295R cell system. Antibiotics, grth
promoters, analgesics, anti-inflammatory compounds, anti-lipidics, cancer therapy
drugs were among the chemicals evaluated. The H295R cells were exposed to high and
environmentally relevant concentrations of the pharmaceuticals chosen. Gene
expression and hormone production was evaluated by therapeutic groups and statistical
correlations between gene expression and hormone data were established. Dose-
response curves were constructed and interactive effects were evaluated through
exposures to several binary mixtures of drugs. Results demonstrated that compounds
different to those already classified as EDCS may produce changes in steroidogenic
gene expression and hormone production. Although compounds with the same
mechanism of action may show similar gene expression profiles, the hormone
production effects may be different. Not all the genes evaluated reacted to changes in
concentrations of the drugs. No statistical correlations between gene expression and
hormone production were observed, but correlations among genes were shown to be
significant. Perhaps the main conclusion of this part of the study was that the H295R
cell bioassay is capable of detecting the steroidogenic effects of real environmental
contaminants, individually and when present in complex mixtures.

The applicability of the H295R cell bioassay was proven by the results detailed
in chapter 4. The endocrine disruptive properties of marine water samples collected all
around the Hong Kong, SAR, China were evaluated using the H295R cell bioassay.

Knowing the high levels of pollution found during the last decade the Hong Kong

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government through the Environmental Protection Department has established a marine
water quality monitoring program that yearly collect data that allows establishing the
pollution levels of Hong Kong waters. In total 30 water samples were collected, 4 of
which correspond to influents and effluents from 2 of the most important STW in Hong
Kong. After extracting 1 liter of each of the samples using phase extraction cartridges,
the H295R cells were exposed to the methanolic extracts. The responses of gene
expression and hormone production after the exposures confirmed the presence of
EDCS in Hong Kong marine waters. Moreover, areas with possible presence of
pollutants lethal to the cells were identified since. Extracts from effluents of the 2
water treatment plants sampled did not produce significant changes on gene expression
or hormone production suggesting the effectiveness of the treatments used in the plants.

Overall, results from the experiments conducted in this dissertation corroborate
once more how this novel pre-screening cell system, the H295R cell bioassay, which
allows simultaneous analysis of the expression of genes encoding for key enzymes
involved in steroidogenesis, is a powerful, practical, sensitive and integrative tool for
environmental toxicology and risk assessment studies of endocrine disruptive effects.
The H295R cell bioassay is now being validated for use in a tiered screening approach
by the US-EPA in order to be considered to replace several currently used assays for

determination of endocrine effects.

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