Pharmacokinetics and Pharmacodynamics of Protein

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PHARMACOKINETICS AND PHARMACODYNAMICS OF PROTEIN

TURNOVER AND PRODUCTION IN VIVO

DISSERTATION

Presented in Partial Fulfillment of the Requirements for

the Degree Doctor of Philosophy in the Graduate

School of The Ohio State University

Jonghan Kim, M.S.

*****

The Ohio State University

2004

Dissertation Committee: Approved by Dr. William L. Hayton, Advisor

Dr. Clark L. Anderson

Dr. James T. Dalton Advisor

Dr. Duxin Sun Graduate Program in Pharmacy

ABSTRACT

The overall objective of this dissertation was quantitative characterization of the

pharmacokinetics of the proteins albumin and vitellogenin, with a focus on their

biosynthesis. Albumin was studied for the possible role of the receptor FcRn, the major

histocompatibility complex-related Fc receptor, in its biosynthesis. Vitellogenin

biosynthesis was studied as an example of receptor-dependent protein production

controlled by a complex hormonal signaling system.

Albumin was quantified in biological matrices using sodium dodecylsulfate-

polyacrylamide gel electrophoresis and immunoprecipitation for separation and enzyme-

linked immunosorbent assay for quantification. The analytical methods were validated

by high degrees of purity (~100%) and linearity (R2 > 0.999).

Using FcRn-deficient knock-out (KO) mice and radioiodinated albumin as a tracer, FcRn was recently shown to protect albumin from degradation, also indicating indirectly lower albumin production rate in KO compared with control mice. To further explore the role of FcRn in albumin production, the albumin production rate in WT and

KO mice was measured using a kinetic analysis of the plasma appearance of tritiated albumin after intravenous bolus injection of tritiated leucine. An increase in albumin production rate (~20%) in KO compared with WT mice contradicted the indirect evidence based upon iodinated albumin, suggesting that radioiodinated albumin failed to

ii mimic the behavior of endogenous albumin, possibly due to structural changes induced by the iodination and/or purification procedures.

Vitellogenin (Vg), an egg-yolk precursor protein, is synthesized in the fish liver, transported to the ovaries, and incorporated into developing oocytes. The estrogen- receptor complex up-regulates Vg production by binding to its recognition element on nuclear DNA, stimulating mRNA and Vg production. Receptor-mediated up-regulation of Vg biosynthesis was incorporated into a pharmacokinetic/pharmacodynamic model that accurately predicted the plasma concentration of Vg in male rainbow trout after continuous water exposure to the synthetic estrogen 17-α-ethynylestradiol.

Estrogen levels are under control of pituitary-derived gonadotropins which in turn are controlled by hypothalamus-derived gonadotropin releasing hormone after appropriate environmental cues. A biologically-based, mathematical model was developed and integrated the biology of hormone signaling and feedback systems which included key intermediate steps; e.g., sex steroid synthesis, gonadotropin gene induction and peptide synthesis with their control of oocyte maturation and spawning.

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Dedicated to my parents

and

my wife

ACKNOWLEDGMENTS

I would like to express my sincere appreciation and full gratitude to my advisor,

Dr. William L. Hayton, for his intellectual support, guidance, encouragement, inspiration, limitless advice, and patience in correcting my poor understanding towards the science. I truly appreciate the opportunities afforded me to study pharmacokinetics and pharmacodynamics more extensively and to apply them to biochemistry, cell biology, and receptor physiology, which were new areas to me.

I am most grateful to Dr. Clark L. Anderson for support of my research, intelligent ideas, knowledgeable advice, motivation, enthusiasm for science, and patience in correcting scientific, stylistic, and grammatical errors. He led me into the fields of biochemistry and immunology, and made me a more multi-disciplinary and inter- disciplinary scientist (hybrid scientist) who can try to integrate quantitative and qualitative science.

I also thank my committee member, Dr. James T. Dalton, for his helpful guidance and encouragement. As a chairman of the Division of Pharmaceutics, he warmly cared for all students and researchers in a friendly way, from which I learned a pattern of leadership.

I thank Dr. Duxin Sun for his friendship and kind advice, not only as a committee member of my dissertation but as a genuine professor.

I am grateful to Dr. Irvin R. Schultz for sharing his ethynylestradiol and vitellogenin data for the development of a second generation PK/PD model. I thank Dr.

Penny Swanson for sharing her pituitary and steroid hormone data from coho salmon.

I thank Dr. John M. Robinson for his kind guidance in cell biology and physiology. I appreciate Dr. Richard F. Mortensen for sharing his accumulated precious knowledge on the acute-phase reaction. I am grateful to Dr. Theodore Peters, Jr., for his invaluable advice on albumin. I also thank Dr. Valerie K. Bergdall-Costell for her kind advice on experimental animal procedures.

I acknowledge Dr. Myung Gull Lee who was my M.S. advisor in Korea and introduced me to pharmacokinetics and pharmacodynamics 10 years ago. While Dr. Lee conceptually guided me, I learned most of my laboratory research techniques from Dr.

Woo Hyun Yoon (DVM and Ph. D.), whose doctoral studies were guided by Dr. Lee, and who is my life-long friend. He had great patience to teach me many surgery techniques, from mouse to dog, and instrumental skills which provided a strong background for my continued development as a researcher. I owe them a lot.

I especially thank Dr. Arun K. Tewari in the Proteomics Core Lab at Heart and

Lung Research Institute for his instruction and skill in two-dimensional electrophoresis of mouse plasma. I thank Dr. Michael D. Radmacher for his help in statistical analysis. I am also grateful to Dr. Sudhasri Mohanty for her guidance in molecular biology and biochemistry. Three more labmates should be acknowledged: Dr. C. L. Bronson for her helpful feedback on my research; our lab manager, Mr. Manzoor Wani; and graduate student Ms. Chaity Chaudhury.

Kathy Brooks, as a graduate coordinator, always helped me and encouraged me a lot. She was an extremely amiable and extraordinary administrator; I doubt that I will ever encounter such an outstanding person again. I am also indebted to the former division secretary, Karen Lawler, and the current secretary, Carol Camm.

I thank all of the faculty, staff members, and my fellow graduate students and researchers in the College of Pharmacy and at the Davis Heart and Lung Research

Institute, for their instruction, great help, and friendship. I thank all of my friends for their friendship and encouragement.

I express special thanks to my dear Dad, and dear Mom who passed away two years ago. I thank my brother and sister in Korea.

Finally, to my lovely wife, Eunju Hurh, I love to express my thanks for her understanding, patience, and her love.

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VITA

May 4, 1971……………………………… Born – Seoul, South Korea 1995……………………………………….B.S. Pharmacy Seoul National University, Seoul, South Korea 1995-1997…………………………………Graduate Teaching Associate Laboratory in Pharmacology and Pharmacokinetics Seoul National University 1996-1997…………………………………Pharmacist for intravenous preparation of anticancer agents Seoul National University Hospital, Children’s Hospital, Seoul, South Korea 1997……………………………………….M.S. Pharmacy Seoul National University Advisor: Myung G. Lee Thesis: Liver and gastrointestinal first-pass effects of azosemide in rats 1997-1998…………………………………Pharmacist Kun-Kook University Hospital, Seoul, South Korea 1998-2002…………………………………Graduate Research Associate The Ohio State University 2002……………………………….………Graduate Teaching Associate The Ohio State University 2002……………………………….………M.S. in Pharmaceutics The Ohio State University Advisor: William L. Hayton, 2002-present………………………………Graduate Research Associate The Ohio State University

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PUBLICATIONS

Research Publications

1. Dong Li, Seong H. Jang, Jonghan Kim, M. Guillaume Wientjes, and Jessie L.-S. Au, Enhanced drug-induced apoptosis associated with P-glycoprotein overexpression is specific to antimicrotubule agents. Pharm. Res., 20(1): 45-50 (2003)

2. Jonghan Kim, Eun J. Kim, Kye S. Han, Man S. Chang, and Myung G. Lee, Gastrointestinal first-pass effect of YJA-20379-8, a new reversible proton pump inhibitor, in rats. J. Pharm. Pharmacol., 51(9):1031-1036 (1999)

3. Su Y. Chung, Kye S. Han, Ho J. Kim, Jonghan Kim, Man S. Chang, and Myung G. Lee, Gastrointestinal absorption of a new reversible proton pump inhibitor, YJA- 20379-8, and its pharmacokinetics after oral administration in acetic acid-induced gastric ulcer in rats. J. Pharm. Pharmacol., 51(9):1025-1030 (1999)

4. Jonghan Kim, Kye S. Han, Jong W. Lee, and Myung G. Lee, Hepatic and intestinal first-pass effects of a new hepatoprotective agent, YH439, in rats. Res. Commun. Mol. Pathol. Pharmacol., 102(2):125-136 (1998)

5. Jonghan Kim, So H. Kim, and Myung G. Lee, Liver and gastrointestinal first-pass effects of azosemide in rats. J. Pharm. Pharmacol., 49(9):878-883 (1997)

FIELD OF STUDY

Major Field: Pharmacy

TABLE OF CONTENTS

Page

Abstract...... ii

Dedication...... iv

Acknowledgments...... v

Vita...... viii

List of Tables ...... xv

List of Figures...... xvi

Abbreviations...... xix

Chapters:

1. Introduction ...... 1

1.1 Overview...... 1 1.2 Turnover...... 3 1.2.1 Turnover and the Steady-state ...... 3 1.2.2 Clearance, Volume of Distribution, and Half-life ...... 4 1.2.3 Turnover in Multicompartment Systems ...... 6 1.3 Biochemistry of Protein Biosynthesis and Production ...... 7 1.3.1 Transcription ...... 7 1.3.2 Translation ...... 8 1.3.3 Protein Folding, Processing, and Sorting ...... 9 1.3.4 Protein Secretion and Export ...... 10 1.4 Receptor-mediated Biological Processes...... 11

1.4.1 Endocytosis ...... 11 1.4.2 Low-density Lipoprotein (LDL) and Its Receptor...... 11 1.4.3 Transferrin (TF) and Transferrin Receptor (TFR)...... 12 1.4.4 Hormonal Control of Steroid Receptors ...... 12 1.4.5 Summary...... 13 1.5 Model Protein I: Albumin...... 14 1.5.1 Albumin Turnover ...... 14 1.5.2 FcRn...... 16 1.5.3 Tracer for Albumin ...... 17 1.5.4 Problems of Radiolabeled Albumin as a Tracer ...... 19 1.5.5 Albumin Production...... 20 1.5.6 Acute-phase Response and Albumin Turnover ...... 25 1.5.7 Methods for Protein Synthesis...... 26 1.5.8 Separation of Albumin...... 27 1.5.9 Summary...... 32 1.6 Model Protein II: Vitellogenin ...... 33 1.6.1 Pharmacodynamics ...... 33 1.6.2 Indirect Response Model...... 34 1.6.3 Vitellogenin as a Model Protein for Receptor-mediated Protein Production...... 34 1.6.4 Estrogen Receptors as Transcription Factors...... 35 1.6.5 Subtypes of Estrogen Receptors ...... 36 1.6.6 Gene Products of Receptor Activation ...... 37 1.6.7 Regulation of Gene Expression for Receptor and Vg...... 37 1.6.8 Differential Responses in the Gene Expression for R and Vg by ER Complex...... 38 1.6.9 Summary...... 39 1.7 Hypothalamus-Pituitary-Gonad (HPG) Axis and Feedback Control of Hormone Turnover...... 39 1.7.1 Overview of the Endocrine and Reproductive Systems in Fish ... 39 1.7.2 Reproductive Hormones in Fish ...... 41 1.7.3 Feedback Control Mechanism and Hormonal Turnover in Fish .. 42 1.8 Conclusion ...... 43

2. Protein Chemistry: Methods for Separation and Quantification of Albumin and Transferrin ...... 45

2.1 Background...... 45 2.2 Materials and Methods...... 47 2.2.1 Animals...... 47 2.2.2 Purified Proteins...... 48 2.2.3 Sodium Dodecylsulfate-Polyacrylamide Gel Electrophoresis (SDS-PAGE) of Plasma...... 48

2.2.4 Immunoblots of Albumin and Transferrin...... 51 2.2.5 Immunoprecipitation of Albumin and Transferrin ...... 52 2.2.6 ELISA for Albumin and Transferrin...... 53 2.2.7 Two-dimensional Polyacrylamide Gel Electrophoresis (2D-PAGE) ...... 55 2.2.8 ELISA for SAP...... 57 2.3 Results ...... 58 2.3.1 Sodium Dodecylsulfate-Polyacrylamide Gel Electrophoresis (SDS-PAGE) of Plasma...... 58 2.3.2 Immunoblots of Albumin and Transferrin...... 60 2.3.3 Immunoprecipitation of Albumin and Transferrin ...... 61 2.3.4 ELISA for Albumin and Transferrin...... 62 2.3.5 Two-dimensional Polyacrylamide Gel Electrophoresis (2D-PAGE) of Plasma ...... 62 2.3.6 ELISA for SAP...... 63 2.4 Discussion...... 64 2.5 Conclusion...... 69 2.6 Acknowledgment ...... 69

3. Receptor-mediated Recycling of Protein: Albumin Turnover and the Role of FcRn ...... 85

3.1 Background...... 85 3.2 Materials and Methods...... 91 3.2.1 Animals...... 91 3.2.2 Measurement of Production Rates of Albumin and Transferrin in WT and KO Mice...... 92 3.2.3 Liver Protein Synthesis and the Steady-state Concentration of Hepatic Proteins...... 94 3.2.4 Measurement of Radiolabeled and Endogenous Steady-state Concentration of Albumin and Transferrin in the Plasma...... 95 3.2.5 Measurement of SAP in the Plasma...... 96 3.2.6 Calculation of the Clearance Ratio between WT and KO Mice of Albumin and Transferrin...... 96 3.2.7 Statistical Analysis...... 97 3.3 Results ...... 98 3.3.1 Steady-state Plasma Concentration of Endogenous Albumin, Transferrin, and Total Proteins ...... 98 3.3.2 Plasma SAP Level in WT and KO Mice ...... 99 3.3.3 Albumin and Transferrin Production in WT and KO Mice...... 100 3.3.4 Total Protein Synthesis and Protein Concentration in the Liver. 101 3.3.5 Steady-state Plasma Concentration of Biosynthetically-labeled Albumin and Transferrin...... 102

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3.3.6 Turnover of Albumin and Transferrin and the Role of FcRn ..... 103 3.4 Discussion...... 103 3.4.1 Previous Findings...... 103 3.4.2 Production and the Steady-state Concentration of Albumin and Transferrin...... 105 3.4.3 Albumin Turnover and the Role of FcRn: Recycling...... 113 3.4.4 Summary and Implications ...... 116 3.5 Conclusion...... 117 3.6 Acknowledgment ...... 118

4. Receptor-mediated Production of Protein: Pharmacokinetic/Pharmacodynamic Modeling of Estrogen-induced Vitellogenin Expression...... 127

4.1 Background...... 127 4.1.1 Outline...... 127 4.1.2 PK/PD Model for Estrogen-Vg System...... 129 4.1.3 Pharmacodynamic Advantages in the Study of EE2-Vg System...... 130 4.1.4 Objectives of the Study...... 131 4.2 Model development ...... 132 4.2.1 Model Diagram...... 132 4.2.2 Abbreviations and Parameters with Units...... 132 4.2.3 Initial Conditions...... 136 4.2.4 Model Equations...... 137 4.2.5 Model Development...... 138 4.2.6 Working Model...... 145 4.2.7 Working Model-based Differential Equations...... 146 4.3 Results and Discussion...... 147 4.3.1 Pharmacokinetics of EE2...... 147 4.3.2 Characterization of Receptor mRNA and Estrogen Receptor Protein...... 148 4.3.3 Characterization of the Binding of EE2 to R, and the Receptor Dynamics ...... 149 4.3.4 Characterization of mVg and the Biosynthesis of Vg in the Liver...... 150 4.3.5 Characterization of Vg in the Plasma ...... 152 4.4 Conclusion...... 153 4.5 Acknowledgment ...... 154

5. Periodical Turnover of Reproductive Hormones: Pharmacokinetic/Pharmacodynamic Modeling of Hormone-dependent Biological Feedback System ...... 167

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5.1 Background...... 167 5.1.1 Outline...... 167 5.1.2 Objectives...... 168 5.2 Model Development...... 169 5.2.1 Pharmacodynamic Modeling of the HPG Axis ...... 169 5.2.2 HPG Model...... 169 5.2.3 Model-based Equations...... 171 5.2.4 Hypothalamus and Hormonal Regulation...... 172 5.2.5 Pituitary Gland and Hormonal Regulation ...... 172 5.2.6 Oocyte Progression and the Effect of Steroid Hormones ...... 173 5.2.7 Coordination of Pharmacodynamic Feedback Model...... 174 5.3 Results and Discussion...... 175 5.3.1 The Four Reproductive Hormones...... 175 5.3.2 GnRH Released from Hypothalamus...... 175 5.3.3 Messenger RNA for Gonadotropins in the Pituitary Gland...... 176 5.3.4 Oocyte Progression and Maturation, and Spawning...... 177 5.3.5 Gonadotropins in the Pituitary Gland and Plasma...... 177 5.3.6 Secretion of Steroid Hormones by the Gonad ...... 178 5.4 Conclusion...... 179 5.5 Acknowledgment ...... 180

Bibliography ...... 191

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LIST OF TABLES

Table Page

3.1 Total endogenous protein concentration in the liver and total liver protein synthesis in WT and KO mice ...... 125

3.2 Estimation of CL based on the mass balance equation with known Css and Rp values determined by different methods...... 126

4.1 Pharmacokinetic/Pharmacodynamic parameter values for estrogen receptor mRNA and protein during continuous water exposure to EE2...... 164

4.2 Pharmacokinetic/Pharmacodynamic parameter values for vitellogenin mRNA and protein during continuous water exposure to EE2 ...... 165

4.3 Pharmacokinetic parameter values for Vg after intravenous administration of the protein ...... 166

5.1 Pharmacokinetic parameter values associated with the model-based equations ...... 188

5.2 Pharmacodynamic parameter values associated with the model-based equations ...... 189

5.3 Periodical parameter values of oocytes growth in the model ...... 190

LIST OF FIGURES

Figure Page

2.1 SDS-PAGE profile of Coomassie stained proteins in WT and KO plasma ...... 70

2.2 SDS-PAGE profile of purified albumin and the plasma from WT and KO mice...... 71

2.3 SDS-PAGE profile of purified transferrin ...... 72

2.4 Linearity of albumin from the plasma of WT and KO mice by SDS-PAGE ...... 73

2.5 Linearity of transferrin from the plasma of WT and KO mice by SDS-PAGE.... 74

2.6 Immunoblot of purified albumin and plasma albumin in WT and KO plasma .... 75

2.7 Immunoblot of purified transferrin and plasma transferrin in WT and KO plasma ...... 76

2.8 Purity of albumin by immunoprecipitation with the plasma of WT and KO mice...... 77

2.9 Purity of transferrin by immunoprecipitation with the plasma of WT and KO mice...... 78

2.10 Linearity of albumin recovered by immunoprecipitation from the radiolabeled WT plasma using anti-MSA antibody ...... 79

2.11 Linearity of albumin ELISA measured by purified albumin...... 80

2.12 Linearity of transferrin ELISA measured by purified transferrin...... 81

2.13 2D-PAGE of plasma from WT, AK, and BK mice ...... 82

2.14 Linearity of SAP ELISA measured by standard SAP...... 83

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2.15 Basal level of SAP in plasma of untreated WT, AK, and BK mice ...... 84

3.1 Plasma steady-state concentration of albumin, transferrin, and total plasma protein in WT and KO mice...... 119

3.2 Plasma concentration of SAP at 15 and 90 min after administration of radiolabeled leucine in WT and KO mice...... 120

3.3 Plasma appearance of labeled albumin and transferrin after injection of tritiated leucine in WT and KO mice ...... 121

3.4 Radioactivity of albumin and transferrin of WT and KO mice appeared at 90 min after injection of tritiated leucine...... 122

3.5 Average steady-state plasma concentration of albumin and transferrin of WT and KO mice determined either by SDS-PAGE or by ELISA method during 14-days infusion of radiolabeled leucine...... 123

3.6 Proposed model for the biosynthesis and the production of albumin and transferrin with possible involvement of FcRn during albumin turnover...... 124

4.1 Schematic representation of the pharmacokinetic/pharmacodynamic model for estrogen-induced receptor-mediated gene induction and the biosynthesis of Vg during continuous exposure of male rainbow trout to EE2 ...... 155

4.2 Schematic representation of the pharmacokinetic/pharmacodynamic model for estrogen-induced receptor-mediated receptor mRNA induction and the up- regulation of biosynthesis of the receptor during continuous exposure of male rainbow trout to EE2...... 156

4.3 Schematic representation of the pharmacokinetic/pharmacodynamic model for estrogen-induced receptor-mediated Vg mRNA induction and the up-regulation of biosynthesis of Vg during continuous exposure of male rainbow trout to EE2 . 157

4.4 Schematic representation of the pharmacokinetic model for the disposition of Vg after its secretion from the liver where the synthesis occurs ...... 158

4.5 Schematic representation of the pharmacokinetic/pharmacodynamic ‘working’ model for estrogen-induced receptor-mediated gene induction and the biosynthesis of Vg during continuous exposure of male rainbow trout to EE2 . 159

4.6 Pharmacokinetics of EE2 during continuous exposure of male rainbow trout to EE2...... 160

xvii

4.7 Time course of estrogen receptor mRNA and total receptor protein during continuous exposure of male rainbow trout to EE2...... 161

4.8 Time course of vitellogenin in the liver and the plasma during continuous exposure of male rainbow trout to EE2 ...... 162

4.9 Detailed feature of Figure 4.8 for the early time course of vitellogenin in the liver and the plasma during continuous exposure of male rainbow trout to EE2 ...... 163

5.1 Schematic diagram of hormone turnover model...... 181

5.2 Time course of four hormones measured in coho salmon after exposure to the photoperiod ...... 182

5.3 Time course of GnRH release from the hypothalamus after an external stimulus such as a change of daylight ...... 183

5.4 Time course of mRNA for FSH (solid line) and LH (dotted line) induced by GnRH and regulated by E2 in the pituitary gland...... 184

5.5 Time course of oocyte progression and maturation in ovary of female coho salmon...... 185

5.6 Simulated concentration-time profiles of the two pituitary-derived hormones based on the model-based differential equations...... 186

5.7 Simulated concentration-time profiles of the two ovary-derived hormones based on the model-based differential equations ...... 187

xviii

ABBREVIATIONS

2D-PAGE two-dimensional PAGE 2-ME 2-mercaptoethanol Ab antibody AK FcRn-α-chain knockout AVG average BCA bicinchoninic acid BK β2-microglobulin knockout (= b2m-KO) BSA bovine serum albumin bs-MSA biosynthetic MSA by injecting radiolabeled amino acid CL clearance Con A concanavalin A cpm count per minute CRP C-reactive protein Css steady-state concentration DHP 17α, 20β-dihydroxy-4-pregnene-3-one dpm disintegradation per minute E estrogen; estrogenic compound (E2 or EE2, etc) E2 17-β-estradiol (estradiol) EE2 17-α-ethynylestradiol 0.1% E280 extinction coefficient at 280 nm with 0.1% (= 10 mg/mL) of protein ELISA enzyme-linked immunosorbent assay ER endoplasmic reticulum (chapter 1) or estrogen-estrogen receptor complex (chapter 4 and 5) ERE estrogen response element EV extravascular space FCR fractional catabolic rate FcRn Fc receptor of neonatal IgG transport FSH follicle-stimulating hormone FSR fractional synthesis rate HRP horseradish peroxidase HSA human serum albumin IB immunoblot (Western blot) IEF isoelectric focusing IgA immunoglobulin A IgG immunoglobulin G xix

IL-6 interleukin-6 I-MSA radioiodinated MSA IP immunoprecipitation k elimination rate constant KO knockout; mainly means AK in this text, sometimes both AK and BK. L liver Leu leucine LH luteinizing hormone LSC liquid scintillation counting mRNA messenger RNA MRT mean residence time MS mass spectrometry MTT minimum transit time MSA mouse serum albumin OD optical density P plasma PAGE polyacrylamide gel electrophoresis PBS phosphate-buffered saline PD pharmacodynamics PG pharmacogenomics pI isoelectric point PK pharmacokinetics PK/PD pharmacokinetics/pharmacodynamics PS permeability-surface area product Prot protein R FcRn (chapter 2 and 3) or unbound estrogen receptor (chapter 4 and 5) R2 linearity coefficient RER rough endoplasmic reticulum Rin rate-in Rout rate-out Rp production rate RSA rat serum albumin SA serum albumin SAP serum amyloid P sc-I-MSA biologically screened radioiodinated MSA SD standard deviation SDS sodium dodecylsulfate SDS-PAGE SDS-polyacrylamide gel electrophoresis SER smooth endoplasmic reticulum t1/2 terminal half-life TBS Tris-buffered saline TBST 0.05% Tween 20-containing TBS TCA trichloracetic acid TF transferrin (mostly, mouse serum transferrin)

TFR transferrin receptor TNFα tumor necrosis factor α tRNA transfer RNA Vd volume of distribution Vg vitellogenin (= VTG) Vss volume of distribution at steady-state VTG vitellogenin (= Vg) WT wild-type (mostly, FcRn-expressing and normal)

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CHAPTER 1

INTRODUCTION

1.1. Overview

Protein metabolism is a dynamic process with continuous synthesis and breakdown. It is a fundamental biological process in all living organisms [1]. Protein synthesis can be altered by many biological and environmental factors; e.g., a change in hormone level, exposure to pathogenic substances, physical insults (trauma, burn), diet, activity of regulatory proteins, amino acid availability, etc. The breakdown of protein also depends on several factors, including in some instances receptor that recycle proteins, stimulation or inhibition of the catabolic enzyme system, and hormonal control.

The imbalance of protein caused by abnormal synthesis or degradation or both can lead to serious illness. Studying protein turnover using a kinetic approach is useful in understanding how the body regulates a particular protein pool that is in dynamic equilibrium.

Many receptors are involved in protein turnover, either in synthesis or in degradation; for example, steroid hormone receptors and the transferrin receptor. Thus, receptors often regulate the level of a protein in a certain tissue or plasma, resulting in proper homeostasis. Increasingly, more receptors are being identified, and their critical roles in physiology and biology with numerous ligands and cofactors have been elucidated. Rapid progress in molecular biology of receptors has compelled interpretation of receptor-mediated biological processes by a pharmacokinetic/pharmacodynamic approach, in order to understand the roles of receptors in protein turnover kinetics.

In this chapter, I will provide a general background on the pharmacokinetics/pharmacodynamics and the biochemistry of proteins and receptors, and describe two different receptor mechanisms involved in protein turnover to help understand receptor-dependent protein kinetics. As a model of protein recycling by a receptor, the major plasma protein albumin and the role of its protective receptor, FcRn, was studied in chapter 3. A model protein for receptor-mediated protein expression, the yolk-sac protein vitellogenin, in fish and its highly regulated biosynthesis by estrogen receptor-induced gene activation, was studied in chapter 4. In chapter 5, a pharmacokinetic/pharmacodynamic model was developed to characterize periodic behaviors of hormones and peptides involved in brain (hypothalamus)-pituitary-gonad homeostasis under the influence of highly regulated and fluctuating hormones.

1.2. Turnover

1.2.1. Turnover and the Steady-state

The amounts of many body constituents remain fairly constant with time.

However, this does not mean that they are in a static state; in fact, they are continuously

being eliminated and synthesized with a certain rate over time. This is called “turning

over”. The concept of turnover can be applied to plasma proteins, enzymes, hormones,

electrolytes, water, and in fact to virtually every molecule in the body [2].

Turnover implies that a substance is at steady-state status. Steady-state can be

defined as a state or condition where the rate of synthesis or formation equals the rate of

elimination or degradation. This rate is called the “turnover rate”. However, turnover

rate does not indicate how rapidly a steady-state condition of a certain pool is attained;

for this the turnover rate must be related to the amount of substance present; i.e., the pool

size (mg or mmol). The ratio of the turnover rate (Rto) to the pool size (Ass) is called the fractional turnover rate, kto, as expressed in Equation (1.1),

R k = to (Eq. 1.1) to Ass

In the steady-state condition, the fractional turnover rate can be the same as the fractional synthesis rate (FSR) or fractional catabolic rate (FCR), both well-known parameters in protein kinetics.

1.2.2. Clearance, Volume of Distribution, and Half-life

There are three important pharmacokinetic parameters to consider in turnover

kinetics; clearance, apparent volume of distribution, and half-life. Clearance can be

described as the intrinsic ability of the body or organs to remove a substance from the

body or organs. It represents the theoretical volume of blood or plasma of which a

substance is completely and irreversibly cleared in a given period. Therefore, it is

expressed as a volume per unit time. The rate of elimination (dA/dt) depends on the

plasma concentration (CP) and the clearance (CL) as shown in Equation (1.2),

dA = −CL ⋅ C (Eq. 1.2) dt P where a negative sign indicates the loss from the body. Therefore, due to its definition and relationship to elimination rate, clearance is the parameter that characterizes a degradation or elimination of a substance in the body.

The proportionality constant relating the concentration of a substance in blood or plasma to the amount of the substance in the body has been termed the apparent volume of distribution, Vd [3]. There is no obvious relationship between the apparent and real volumes of distribution of a substance. In other words, the apparent volume of distribution (Vd) is the size of a compartment necessary to account for the total amount of a substance in the body if it were present throughout the body at the same concentration found in the plasma [3, 4]. If the volume of distribution is larger than the plasma volume, this indicates that the substance is also present in tissues other than plasma. Therefore, the magnitude of Vd often reflects the relative affinity of a substance

for tissues relative to plasma. The larger the Vd, the greater the distribution of a

substance in the extravascular spaces. For a substance that shows first-order elimination

kinetics, Vd and CL are constant as long as the body maintains normal biological

processes without perturbation.

The elimination rate constant in the terminal phase, k, can be defined as the

fraction or percentage of the total amount of a substance in the body removed per unit

time [4]. It is a function of Vd and CL as shown in Equation (1.3),

CL k = (Eq. 1.3) Vd

k can also be described as the fraction of the volume of distribution of the substance that

will be cleared per unit time. In a turnover system, k equals kto (= FCR). Half-life, t1/2, is the time required for a total amount of a substance in the body or the plasma concentration to decrease by one-half.

Half-life is determined by both Vd and CL:

0.693⋅Vd t = (Eq. 1.4) 1/ 2 CL

The dependence of half-life or fractional catabolic rate (= elimination rate

constant) on Vd and CL is emphasized because the volume of distribution and clearance

for a substance can change independently of one another, and consequently, affect the

half-life or FCR [4]. This kinetic relationship is important in evaluating whether there is

a change in the clearance or the volume of distribution or both when fractional catabolic

rate has been altered.

1.2.3. Turnover in Multicompartment Systems

In multicompartment systems, endogenous compounds show distribution kinetics within the body. After administration of a tracer dose of isotopically labeled substance, one can determine the distribution phase. In the analysis of the tracer data, two major assumptions are often made: first, that the disposition of the tracer is identical to that of the endogenous substance, and second, that the amount of tracer dose is negligible compared with the pool size of the substance so that introduction of the tracer does not perturb the pool size at steady-state.

When the two assumptions above hold, then a tracer molecule, on average, resides in the body the same length of time as a new endogenous molecule. This time is called the mean residence time (MRT). Among several methods to calculate MRT, the most useful method in a tracer experiment would be as follows,

MRT = AUMC*/AUC* (Eq. 1.5) where AUMC represents the area under the first moment of the plasma concentration versus time curve and AUC represents the area under the plasma concentration versus time curve, and * designates these parameters for labeled tracer. It should be pointed out that MRT cannot be directly calculated from the FCR as there is no unique fractional turnover rate in a multicompartment system due to distribution only.

Under steady-state conditions, the elimination rate is equal to the turnover rate. In conventional pharmacokinetics, the rate of elimination is identical to the product of clearance and the steady-state concentration,

dA R = − = CL × Css (Eq. 1.6) to dt

MRT is also the ratio of pool size to turnover rate,

Ass * Vss × Css * MRT = = (Eq. 1.7) Rto CL × Css * where Vss represents the apparent volume of distribution at steady-state and Css* the steady-state concentration of a tracer.

Thus, the following relationship holds:

Vss MRT = (Eq. 1.8) CL

1.3. Biochemistry of Protein Biosynthesis and Production

A brief description of protein synthesis and secretion is presented in this section to help understand the general biochemistry of protein production in eukaryotes.

1.3.1. Transcription

Protein synthesis begins with the synthesis of messenger RNA (mRNA) by RNA polymerase II. To initiate transcription on a DNA template, several other proteins are required along with RNA polymerase II, such as general transcription factors, chromatin- remodeling complexes, and histone acetyltransferases. During the elongation phase of transcription, the nascent RNA undergoes three types of processing events: Capping at

the 5’-end, splicing in the middle of the RNA, and cleavage and polyadenylation at the

3’-end.

1.3.2. Translation

Transcription is followed by translation, which takes place in the cytoplasm on a large ribonucleoprotein assembly called a ribosome. The amino acids used for protein synthesis first attach to a transfer RNA (tRNA) molecule; the activated form of tRNA recognizes its particular sets of three nucleotides in the mRNA (codons) by complementary base-pair interactions. The sequence of mRNA is then read from one end to the other end in sets of three according to the genetic code [5].

For initiation of translation, a small ribosomal subunit binds to the mRNA molecule at a start codon (AUG) which is recognized by a unique tRNA molecule.

Elongation begins with the binding of a large subunit to the ribosome. During the elongation phase, aminoacyl tRNAs carrying specific amino acids bind sequentially to their respective codon in mRNA by forming complementary base pairs with the anticodon in tRNA. Individual amino acids are added to the C-terminal end of the growing polypeptide by means of a cycle of three steps: aminoacyl-tRNA binding, peptide bond formation, and ribosome translation. The termination phase succeeds the elongation phase when the codon-by-codon progress of the mRNA molecule through the ribosome in the 5’-to-3’ direction reaches one of three stop codons. A release factor then binds to the ribosome and terminates the translation, releasing the complete polypeptide.

1.3.3. Protein Folding, Processing, and Sorting

For the last steps of protein synthesis, two molecular chaperones, hsp60 and hsp70, recognize exposed hydrophobic patches on proteins and prevent protein aggregation that would otherwise compete with the folding of newly synthesized proteins into their correct three-dimensional conformations. This protein folding process must also compete with a highly elaborate quality control mechanism that destroys proteins with abnormally exposed hydrophobic patches [5]. Ubiquitin, in this case, is covalently added to a misfolded protein by a ubiquitin ligase, and the resulting ubiquitin chain is recognized by the cap on a proteasome to move the entire protein to the interior of the proteasome for proteolytic degradation.

Protein synthesis occurs on the cytosolic surface of the endoplasmic reticulum

(ER): all proteins destined for secretion, including the ER itself, the Golgi apparatus, the lysosomes, the endosomes, and the plasma membrane are first imported into the ER from the cytosol. Three reactions take place in the lumen of the ER: protein folding and oligomerization, formation of disulfide bonds, and the addition of N-linked oligosaccharides. N-linked glycosylation serves as a marker for indicating the extent of protein folding so that proteins leave the ER only when they are properly folded.

Proteins that do not fold or oligomerize correctly are returned to the cytosol, where they are deglycosylated, ubiquitinylated, and degraded in proteasomes.

Soluble proteins that are destined for secretion or for the lumen of the ER and the other organelles pass completely into the ER lumen whereas membrane proteins are translocated across the ER membrane without being released into the lumen. One or

more membrane-spanning α-helical regions in polypeptide chains help transmembrane proteins in translocating across the membrane and in remaining anchored there.

1.3.4. Protein Secretion and Export

Proteins can be secreted from cells by exocytosis in either a constitutive or a regulated fashion. In the constitutive pathways, proteins are delivered from the trans

Golgi network (TGN) to the plasma membrane. They can be diverted to other pathways or retained in the Golgi apparatus. In polarized cells, a selective pathway exists to ensure that membrane proteins, secreted proteins, and lipids are delivered to the appropriate location or membrane.

In the regulatory pathways, proteins are stored either in secretory vesicles or synaptic vesicles; upon proper stimulation, these vesicles fuse with the plasma membrane and release their proteins. Secretory vesicles, budding from TGN, undergo maturation, which involves protein condensation. Synaptic vesicles, confined to nerve cells and some endocrine cells, are formed from endocytic vesicles and endosomes. These vesicles secrete proteins across the membrane after stimulation of a receptor by its neurotransmitter ligand.

1.4. Receptor-mediated Biological Processes

1.4.1. Endocytosis

Plasma proteins are pinocytosed or endocytosed into the intracellular compartment of endothelial cells and are localized in endocytic vesicles. Additionally, some proteins bind to cell surface membrane receptors and undergo receptor-mediated endocytosis. These endosomes become acidified by ATP-driven proton pumps in the endosomal membrane and become lysosomes where the acidic pH facilitates the degradation of proteins by many hydrolases. Some proteins are diverted back to the plasma membrane and returned to the circulating plasma by means of specific receptors, for example, transferrin and transferrin receptor. Some receptors are involved in the degradation of its ligand as seen with the LDL and LDL receptor.

1.4.2. Low-density Lipoprotein (LDL) and Its Receptor

Receptor-mediated transport or endocytosis has been well characterized by low- density lipoprotein (LDL) and its receptor. LDL particles bind to LDL receptors in the coated pits and the complex is rapidly internalized in coated vesicles. These vesicles deliver their contents to early endosomes near the cell membrane and move further inside the cell to form late endosomes, finally becoming lysosomes, where cholesterol esters are hydrolyzed to free cholesterol. There are three types of receptors based on biological fates: 1) receptor that is recycled (transferrin receptor), 2) receptor that is degraded in the 11

lysosome without recycling (LDL receptor), and 3) receptor that mediates transcytosis as seen for IgA and its receptor.

1.4.3. Transferrin (TF) and Transferrin Receptor (TFR)

The TF-TFR system is somewhat more complex than that of LDL. As an iron carrier, iron-bound TF binds to the membrane TFR at physiological pH, after which the

TF-TFR complex is internalized. In the acidic endosomal pH, transferrin loses iron and becomes apotransferrin; however, it remains bound to TFR in the endocytic membrane, whereas freed iron is available inside the cell. The apotransferrin-TFR complex recycles back to the plasma membrane. Apotransferrin is released into the plasma since there is a low affinity between apotransferrin and receptor at neutral pH. Recycled apotransferrin is available to bind circulating iron again, and transport iron to the cytoplasm by this receptor-mediated process.

1.4.4. Hormonal Control of Steroid Receptors

While receptor-mediated recycling of transferrin increases its life span in the circulating plasma, and thereby increases the steady-state concentration of TF, receptor- mediated protein synthesis may also enhance the expression of protein and thereby elevate the steady-state protein concentration. Typically, hormone-dependent gene activation has been well characterized, as seen for example in the glucocorticoid receptor and the estrogen receptor. Intracellular glucocorticoid receptor binds its intracellular

ligand, for example dexamethasone, and the receptor-ligand complex translocates to the nucleus where its DNA-binding domain binds to response elements, stimulating the transcription of target genes. For some target genes, this complex down-regulates the expression of the protein; e.g., glucocorticoid receptor itself [6]. In contrast, ligand- receptor complex up-regulates the production of other proteins; e.g., tyrosine aminotransferase (TAT) [6]. Estrogen receptor is known to simultaneously stimulate the transcription and inhibit the degradation of mRNA for estrogen receptor, showing positive feedback and up-regulation of estrogen receptor [7].

1.4.5. Summary

Receptors are involved in numerous biological processes. Upon binding of its ligand, whether a protein or a small molecule, the ligand-receptor complex can either transport a target molecule, as seen in iron transport by TF-TFR, or degrade the protein as shown in the LDL system. Therefore, the turnover of the protein ligand is maintained by a receptor-dependent mechanism. Receptors also play an important role in protein dynamics where protein expression is highly regulated. In this case, ligand-induced receptor-mediated gene activation is critical in the expression of a particular protein, and protein turnover is regulated by this receptor-mediated mechanism. These receptor- mediated mechanisms for protein turnover will be discussed in the following chapters.

1.5. Model Protein I: Albumin

1.5.1. Albumin Turnover

For almost 40 years, albumin and IgG have been known to possess relatively longer biological half-lives, 20 and 21 days in human, respectively, compared with other plasma proteins, which show half-lives of 8 days, at the longest, such as transferrin, fibrinogen, haptoglobin, IgA, and IgM [8]. In addition, both albumin and IgG have shown a direct relationship between their serum concentration and fractional catabolic rate (FCR); the more concentrated the protein, the greater FCR; no other plasma proteins show this relationship. The catabolism of the other plasma proteins was either inversely or not related to their serum concentrations. The half-life of infused albumin in analbuminemic patients is as long as 115 days, many fold greater than the 20 days of the normal individual [9]. For example, the catabolism of transferrin has shown an inverse relationship with its serum concentration while fibrinogen showed no relationship of concentration-fractional catabolism. IgG was the first protein extensively investigated to learn the mechanism of this concentration-dependent catabolism. Brambell [10] hypothesized that there could be a receptor that is involved in the protection of IgG from degradation. Consequently, a concentration of IgG saturating receptor binding would lead to an increase in degradation, whereas IgG at a low concentration in the serum would be more efficiently protected by the receptor from catabolism. Despite the progress of IgG biology associated with the receptor-dependent mechanism, albumin – the most abundant protein in serum – was not extensively studied for this purpose mainly 14

because it was difficult to alter the level of albumin, it being the main regulator of plasma osmotic pressure and therefore maintained at a high concentration. Furthermore, pathophysiological events such as infection, edema, or burn can lead to many secondary effects, including an increase in the transcapillary movement of albumin from the plasma space to the extravascular compartment [11] and/or up-regulation or down-regulation of the biosynthesis of albumin [12]. These complex features hindered many researchers from drawing clear conclusions about the nature of albumin metabolism. However, in

1966, Schultze and Heremans conjectured that a mechanism identical to that proposed by

Brambell for protecting IgG from degradation could be applied to albumin as well [13].

It should be noted that Brambell summarized his hypothesis in his review book published in 1970, while the hypothesis was already available prior to Schultze and Heremans’ speculation on albumin.

In 1996, three research papers on IgG metabolism reported that the Fc receptor for neonatal transport of IgG (FcRn) is responsible for the rescue of IgG from degradation

[14, 15, 16]. Although numerous reports on the turnover of albumin had appeared over more than 50 years, the exact mechanism of its protection from catabolism was not known until FcRn, the receptor that prolongs the life-span of IgG, was found to protect albumin as well [17].

1.5.2. FcRn

FcRn, the major histocompatibility complex-related Fc receptor that binds IgG and prolongs its half-life, also protects albumin from degradation [17]. FcRn is an integral, heterodimeric, membrane glycoprotein consisting of β2-microglobulin (b2m) noncovalently bound to a 43 kD α-chain with three extracellular domains, a transmembrane region, and a cytoplasmic tail of about 50 amino acids. The α-chain is a member of the nonclassical MHC-I family of proteins [18]. β2-microglobulin is also associated with several receptors or molecules in the body such as HFE (the hemochromatosis protein) and the CD1 molecule which presents lipid antigens to T cells

[19]. Both albumin and IgG bind FcRn at acidic pH, but not neutral or basic pH where no binding was observed. As expected, IgG showed saturability in its salvation from degradation by receptor-mediated recycling as the serum concentration of IgG is increased [14]. FcRn-α-chain deficient mice (AK; A for alpha-chain (α) and K for knockout [20]) have recently become available [21] whereas b2m-deficient mice (BK; B for beta) have been used in the FcRn-related research for 10 years [22]. Both knockout mice have shown equal effects on the metabolism of IgG and albumin, showing the same clearance and terminal half-life of the proteins between two strains [17]. However, AK would be the animal of choice to study FcRn-associated biology compared with BK since

BK is also deficient in other biological molecules, e.g., HFE. For that reason, in chapter

2 and 3, I will mainly compare the protein kinetics between WT and AK. However, protein kinetics in BK was also studied where necessary. In addition, the convention

“KO” will mean AK rather than BK unless specifically described otherwise. 16

1.5.3. Tracer for Albumin

An important assumption in tracer experiments used to calculate kinetic parameters of endogenous substances is that the tracer molecule should behave the same way as does the endogenous tracee molecule. For small molecules or drugs, labeling with tritium (3H) or carbon-14 (14C) is helpful to study their pharmacokinetics. For proteins and other large molecules, it is difficult to make them radioactive by exchange/substitution reactions. Researchers have introduced isotopes into protein by radioiodination [23] or reductive methylation [24], both of which can modify the configuration and/or conformation of the parent protein. The predominant method for protein radiolabeling is radioiodination. There are several methods to introduce radioactive iodine, including the iodine monochloride (ICl) method [25], the lactoperoxidase method [26], and the Iodogen method [27].

The Iodogen method is universally employed since it is a relatively gentle and simple method by which iodine-125 (125I) is directly incorporated into tyrosine and/or histidine residues of proteins, in the presence of an insoluble oxidizing agent as a solid phase. It was postulated that radioiodinated albumin may not behave exactly the same way as endogenous serum albumin, mainly due to the potential for denaturation by the labeling conditions, usually an oxidation process [28]. Indeed, for more than thirty years, scientists have pointed out that exogenously labeled albumin showed somewhat different kinetics from endogenously and biosynthetically labeled albumin [28].

To improve its tracer quality, ‘screened’ iodinated albumin was used, by which is meant labeled albumin recovered from the plasma of a donor animal infused several hours or days earlier with newly labeled albumin. This strategy simply lets the body clear misconfigured or denatured albumin, leaving only labeled albumin that can behave the same way as endogenous albumin. Unlike endogenous albumin (t1/2 = 40 hr), denatured albumin was cleared very quickly (t1/2 < 25 min) in the mouse (our unpublished observation), which makes ‘screened’ albumin useful for studying albumin turnover. However, the problem is more extensive. As albumin intermediate between defective and native albumin may not be cleared as quickly as defective albumin, this was dealt with by screening albumin for a longer time (for days, not hours) [29, 30], but this usually reduces the recovery of labeled albumin, causing a terminal phase concentration to be beneath the limit of detection. In order to increase the sensitivity in calculating terminal half-life, one can administer a greater amount of radioactive protein.

However, the concentration of radioactive tracer in the plasma should be negligible compared with the concentration of tracee such that the endogenous protein pool is not perturbed by the introduction of radiolabeled protein. Therefore, one cannot easily administer a larger amount of radiolabeled protein to study endogenous protein kinetics.

To summarize, while an extended screening procedure ensures an excellent purity of albumin, subsequent low specific activity of screened albumin lacks quantitative sensitivity, especially in terminal half-life.

1.5.4. Problems of Radiolabeled Albumin as a Tracer

Purified albumin that is used for radioiodination is currently available from many commercial sources. Albumin purification is the multistep process that involves salt fractionation, ion-exchange chromatography, affinity-chromatography, and gel-filtration chromatography (discussed in chapter 2), which may alter the albumin structure to varying degrees. Therefore, it is possible that radioiodinated albumin may be defective not because of the radioiodination process but because of the prior purification procedure.

Additional purification steps may generate albumin with excellent purity from the other plasma proteins but with a likelihood of denaturation of albumin itself. Taken together, these points suggest that the clearance value from the concentration-time profile of radioiodinated protein could be biased due to structural alterations that change the kinetics of the protein. However, it should be pointed out that, compared with its clearance, the terminal half-life of radioiodinated albumin might be relatively accurate and representative of the half-life of endogenous albumin since it is a parameter that was calculated from the terminal phase, which comes a relatively long time after administration of radioactive protein, and not from the entire concentration-time profile.

Although half-life has been used many times in protein kinetics as a parameter for protein degradation, it is not an independent parameter since it is a function of both the volume of distribution and the clearance of the protein. The clearance, rather, is the parameter that purely represents the elimination by degradation and possibly other pathways as well.

In contrast to exogenously labeled protein, endogenously labeled (= biosynthetic) protein has an advantage in that it behaves identically to the endogenous protein. It is made in the body and malformations due to radiolabeling and purification are avoided.

Endogenously labeled protein can be prepared by administration of radiolabeled amino acids, which are used in protein synthesis. Essential amino acids are the precursors of choice because they are not made in the body. However, labeled amino acids in newly synthesized protein will be reutilized within the body after protein degradation.

Therefore, while biosynthetically labeled albumin can be a useful preparation for studying acute kinetics, such as distribution or transport kinetics over a short period during which protein degradation is negligible, it is not recommended for long term experiments as reutilization of labeled amino acids will occur with time. Iodinated amino acids are not reutilized for protein synthesis, so the reutilization problem does not occur with radioiodinated protein tracer.

1.5.5. Albumin Production

It is useful to precisely define and distinguish “biosynthesis” and “production”.

In the whole text, I will define “biosynthesis” as a biological process where an mRNA is transcribed from a gene and a protein is translated from the mRNA; “production” will have a broader meaning for a process where a protein is translated, has undergone proper folding and configuration, and is exported to the circulating plasma (especially for albumin and vitellogenin). Therefore, while biosynthesis takes place in the hepatocytes for two individual proteins (polypeptide might be the better term), production indicates

the biosynthesis plus secretion/export process into plasma. For example, if a receptor is involved in a pre-secretory degradation of a protein in the hepatocyte, biosynthesis might be unchanged while production would be altered with or without the receptor. On the other hand, if a receptor acts as a transcription factor for a protein, both biosynthesis and production would be increased in the presence of receptor compared with its absence.

Albumin follows the one gene-one protein rule and, being a single-chain protein, requires no assembly of chains. Both alleles of the single gene on chromosome 4 are transcribed to form precursor mRNA. The mature mRNA leaves the nucleus and is translated into a peptide chain by a string of ribosomes in the cytoplasm. As a secretory protein, the nascent albumin quickly passes into the cisternae of the secretory channel where it folds to its native configuration and forms its 17 serial disulfide bonds. There is no storage of newly made albumin awaiting a signal for secretion [31]. The liver is the chief organ to synthesize albumin. All lobes of the liver appear to participate evenly for producing albumin.

The rate of albumin production can be regulated in several ways. Translation of albumin requires mRNA, activated transfer RNA (tRNA) bound to amino acids, the ribosomal machinery for assembly, and energy in the form of GTP or ATP. The level of mRNA in the cytoplasm is maintained by the balance of its transcription and its degradation; factors affecting both processes would change the production of albumin.

In the acute-phase reaction, the general response by the body to a stressful insult such as a trauma, a burn, or infection, is to depress the concentration of the albumin mRNA [32, 33]; several other “negative acute-phase proteins” such as transferrin and transthyretin also show the same trend. Conversely, plasma proteins important for

defense, such as fibrinogen and haptoglobin, show an increase in mRNA concentration in the acute-phase reaction (discussed in detail in section 1.5.6).

Insulin, growth hormones, and corticosteroids increase the synthesis of mRNA for albumin whereas estrogen increases the stability of mRNA, thus decreasing the degradation of mRNA. Colloidal osmotic pressure (COP) is a regulator for albumin synthesis, which is indeed stimulated by hypoalbuminemia. Conversely, albumin synthesis is depressed when albumin is given intravenously [34]. Administration of other macromolecules, dextran and globulins, also showed similar effects to the administration of albumin, suggesting that albumin synthesis is regulated by oncotic pressure, not by albumin concentration in the plasma.

Only about 2% of mature albumin mRNA (activity) is detected in the nucleus

[35]. The time for completion of an albumin chain (608 residues in the rat) has been estimated as 1.5~2 min in vivo or by liver perfusion [36]. The number determined chemically by hybridization was reported as about 3500/cell [37]; calculation from the figure of 7.3 µg mRNA/g liver [33], assuming 200 × 106 hepatocytes/g liver and using the molecular mass for albumin mRNA of 770 kD, gives 2852 mRNA molecules/cell [31].

Alternatively, the number of molecules of RSA formed per minute in an adult rat liver cell, calculating from the figure of 0.35 mg/g liver/hr, is 26,554; dividing by 19, the number or ribosomes working on a messenger simultaneously in a polysome, and multiplying by 2, the number of minutes needed to form one RSA molecule, gives 2795 polysomes or mRNA molecules/cell. This indicates that the mRNA molecules must nearly all be at work making albumin [31].

Secretory proteins have a particular pathway even while they are being assembled. A signal peptide has a strongly hydrophobic midsection, which directs the growing chain through the membrane of ER into the lumen, allowing proteins to be segregated from proteins destined for the cytosol or other organelles. A signal peptidase, located in the membrane at the translocation site, recognizes the signal peptide at a stretch more hydrophilic than the midsection, and cleaves it from the protein.

As with other protein syntheses, albumin needs three elements for its synthesis: amino acids, pyrophosphate compounds as an energy source, and the complex ribosomal mRNA structure as a machinery. The level of “translatable” mRNA, the mRNA available for action on ribosomes, is the result of its synthesis by transcription, and its degradation or inactivation. The normal half-life of albumin mRNA in rat liver appears to be about 22 to 26 hr [38]. Factors that accelerate mRNA degradation without altering its synthesis would decrease its level and slow the formation of albumin. A lack of free amino acids appears to be one of these factors. In rats on a low-protein diet the observed

62% decrease in albumin mRNA concentration [39] was due to increased degradation without altered transcription of mRNA. How an increase in the supply of amino acids affects mRNA stability is obscure; a hormonal action or some direct effect are two possibilities [31]. Estrogen produced an increase in albumin mRNA degradation in cockerels [40].

The cleavage product after removal of the signal peptide is proalbumin, which has a six-residue peptide sequence at its N-terminus called the propeptide. Albumin and other plasma proteins are found in large vesicular carriers, whereas proteins destined to reside in the hepatocyte membrane are in small, smooth Golgi vesicles [41]. The nascent

proteins begin to form their disulfide bonds and attain native configuration even before translation is complete [42]. Albumin follows the same path as other plasma proteins through the hepatocyte cytoplasm; it travels sequentially through rough ER (RER), smooth ER (SER), the Golgi apparatus, smooth secretory vesicles, and finally the cell membrane at the sinusoidal face of the cell. A very small amount (~0.3%) of the newly synthesized albumin is secreted into the bile. The last event is the conversion of proalbumin to albumin after removal of propeptide by convertase, taking place either in the TGN or in the secretory vesicles [43].

The amount of albumin found within the secretory pathway is just under 400 µg/g liver in an 8-week-old rat. If the rate of synthesis rises, the channels for albumin production distend with more albumin; the total content rises and falls with the rate of synthesis in a direct manner. The change of albumin synthesis does not appear to affect the secretion kinetics, e.g., the transit time as discussed below [31].

The minimum time required for proteins to be secreted, minimal transit time

(MTT) is ~16 min for albumin in rats measured by the appearance of radiolabeled protein after injection of isotopic amino acid in the tail vein [44]. Transit times for other plasma proteins are usually longer than that for albumin e.g., transferrin (31 min). Transthyretin and retinal-binding protein showed even longer MTT [45]. The lag time appears to occur mainly in the RER, whereas the average time in release from the TGN to membrane was similar among proteins. Interestingly, the number of disulfide bonds, glycosylation, or γ- carboxylation did not affect the MTT [44], and the question of why albumin has a relatively short MTT remains to be solved.

1.5.6. Acute-phase Response and Albumin Turnover

Most organisms respond with a general reaction to injury and inflammation. Part of this response, during the acute-phase of the inflammatory process, is an increase in the concentration of several proteins called “acute-phase reactants” or “acute-phase proteins”

[46]. Positive acute-phase reactants which are synthesized more rapidly include α1- antitrypsin, fibrinogen [47], α1-acid glycoprotein [48], α2-macroglobulin in rat [49], C- reactive protein (CRP) in human [50], serum amyloid protein (SAP) in mouse, and haptoglobin. Proteins, such as albumin, transthyretin, retinol binding protein, and transferrin, whose plasma concentrations fall during the acute-phase are called “negative acute-phase proteins”. During the removal by proteolytic degradation of tissues damaged from inflammation or trauma, there is a profound rearrangement of protein synthesis rates in the liver, leading to dramatic increases in the plasma concentrations of antiproteinase activity, without which the body would be exposed to excessive proteolysis.

Nonetheless, total plasma protein synthesis seems to increase only moderately due to a compensatory down-regulation of negative acute-phase proteins such as albumin. Since the changes in the concentrations of these plasma proteins are very dynamic, it becomes important in measuring protein synthesis, especially of albumin, that experimental maneuvers such as surgery, injection, or bleedings may not influence the synthesis rate by means of the acute-phase reaction.

Acute-phase cytokines are messenger molecules released by monocytes that travel through the circulating blood and alert the defensive organs of the body on injury or acute disease. The major cytokine that affects hepatic protein synthesis is interleukin-6 (IL-6), 25

a mediator of the acute-phase reaction [51]. A 20 h exposure to IL-6 caused a 50% depression of albumin transcription in human hepatocytes in culture [52]. Mice transfected with cells producing tumor necrosis factor (TNFα) showed a marked (90%) drop in albumin synthesis and mRNA level, which were traced to down-regulation of albumin gene transcription [53].

1.5.7. Methods for Protein Synthesis

To study protein synthesis, the method of choice is to administer radiolabeled amino acids. Numerous methods using radiolabeled amino acids are available, including continuous infusion [54], pulse-injection [55], and a flooding dose method [56]. The continuous infusion method is widely applicable because it utilizes the steady-state conditions for the precursor; after the concentration of labeled amino acids arrive at steady-state, protein synthesis can be studied from its plasma appearance, which is generally a linear increase at early times. Using the zero-order input kinetic equations or the slope of ascending limb of the plasma appearance curve and the steady-state concentration of precursors, one can calculate the biosynthesis rate of a particular plasma protein. Albumin, however, is well known for the down-regulation of its biosynthesis during the acute-phase response [57]. Albumin is a negative acute-phase reactant while fibrinogen, α2-macroglobulin, and α1-acid glycoprotein are known to be positive reactants which are up-regulated in their synthesis upon trauma or infection. Simple experimental procedures such as the implantation of an osmotic infusion pump in order to infuse radioactive precursors and repetitive bleeding from the retro-orbital plexus have 26

the potential of causing an acute-phase response since both infusion and blood sampling take about a day, which is the typical time for activation of the acute-phase response

(unpublished data). Therefore, it is not appropriate to use the infusion pump method for studying albumin synthesis. Vascular catheterization, another method for infusion, needs also minor surgery that will cause the acute-phase reaction. The flooding dose method has the advantage that precursor quickly equilibrates with its endogenous counterpart, saturating the endogenous amino acid pool, and setting the specific activity to that found in the large plasma free amino acid pool [56]. Its disadvantage is that an unphysiologically extreme dose often triggers inhibition or stimulation of incorporation of certain amino acids into proteins; e.g., inhibition of leucine by phenylalanine [58] and stimulation of valine by leucine [59]. The pulse-dose method is also of limited use since it is a non-steady-state approach for which one needs to characterize the kinetics of the labeled precursor, especially in the liver for liver-derived protein. However, as these pulse-dose studies can be finished within a few hours, acute-phase reactions can possibly be avoided.

1.5.8. Separation of Albumin

Albumin is not easily separated from the plasma proteins mainly because plasma is a complex mixture. However, researchers have developed numerous methods to purify albumin from other plasma proteins, primarily for medical use but also for laboratory usage as well. The following summarizes the known methods for isolation of albumin.

1) The one commonly used Cold Ethanol Method (also known as the Cohn Method)

involves albumin fractionation at –5 ~ –3°C. By varying pH and ethanol

concentration, other proteins are separated and albumin is the only protein that

remains at 40% ethanol in the fifth step [60]. Other modifications evolved from

the original Cohn method show better yield (> 90%) and purity (> 95%) [61].

2) Ammonium sulfate fractionation utilizes differences in the solubility of albumin

compared with other plasma proteins. Most plasma proteins are precipitated by

the half-saturated concentration of ammonium sulfate (2.05 M at 25°C, pH 6.5).

After this step, albumin is precipitated at 3.1 M of ammonium sulfate (pH 4.5)

[62]. This is a simple technique, and many proteins can be separated from

albumin by this method. However, it does not yield a 100% pure albumin

precipitation, as transferrin and other plasma proteins are also recovered with

albumin. Therefore, it is usually used as a first step during the course of general

multi-step albumin purification procedure.

3) Chromatography is a very efficient method to isolate not only high-purity protein

but also other small molecules. Ion-exchange chromatography basically separates

different proteins according to their electrical charges. As albumin is highly

negatively charged, it is eluted late during the course of anion-exchange

chromatography whereas it is one of the first proteins eluted by cation-exchange

chromatography. However, this method is not suitable as a single step method

because there are many negatively charged proteins in the plasma, such as α1-

antitrypsin and α1-acid glycoprotein. Therefore, ion-exchange chromatography

must be applied as one of the steps in a series of purification methods. 28

4) Affinity chromatography takes advantage of the high affinity and specificity of

the reversible binding between a protein and its binder. A good example is IgG

separation from the serum by protein-G or protein-A based affinity

chromatography. Protein G binds the Fc-portion of IgG and albumin very tightly

while it has no significant affinity for other proteins. Protein-G mutated in the

albumin binding site binds IgG exclusively. After extensively washing the

affinity adsorbent, IgG can be eluted using high salt or chaotropic agents.

Likewise, to apply affinity chromatography to albumin purification, it is very

important to find an excellent binder for albumin. As a transporter, albumin has

many ligands with high affinities such as bilirubin or fatty acids. However, they

are not adequate for affinity chromatography because most of them can also bind

other plasma proteins. One can certainly use albumin antibody; while it often

shows very high binding affinity and specificity as expected of antigen-antibody

complex [63], it is, however, very difficult to dissociate the complex into

individual proteins; specifically, separation of albumin from albumin-antibody

complex needs 1 M of NH4OH, which will in turn alter the structural property of

albumin, leading to albumin denaturation. This is a good example of efficient

separation of a protein in the face of alteration of the nature of a protein.

Cibacron blue, a dye that binds at the bilirubin binding site on HSA, has been

developed as a binder in an albumin separation procedure [64]. It showed a high

affinity to HSA while the albumins of other species did not show an equivalent

specificity and affinity [65]. Therefore, cibacron blue can be used to purify a

specific protein of interest at low concentration in the plasma by removing

albumin which is the usual contaminator present at its high concentration. For

example, people have been using cibacron blue-based albumin depletion in order

to obtain better electrophoresis results. Recently, a derivative of cibacron blue

(Montage Albumin Deplete Kit; Millipore Corporation) was made available,

which has higher affinity for the albumins of species other than human, such as

bovine, rat and mouse. However, even though the specificity was relatively high,

this reagent cannot be used as a single purification method for albumin. Rather, it

is more appropriately used for specific albumin depletion from plasma of other

species. Nonetheless, it can be employed as part of a multistep purification

procedure for albumin.

5) TCA precipitation followed by reconstitution by ethanol can be used under the

principle that TCA can precipitate almost every protein while 96% ethanol can

recover only albumin [66]. This provides relatively good recovery and purity;

however, it is not known whether it disturbs the albumin structure.

6) Molecular size is always an important property by which a protein can be

separated using size-exclusion (gel filtration) chromatography. Since this is a

method mainly for separating proteins by their hydrodynamic size, it is often

applied as the last step of protein purification from the mixture of small ionic

substances that were involved during the procedure.

7) Sodium dodecylsulfate-polyacrylamide gel electrophoresis (SDS-PAGE) is a

powerful tool for separating many plasma proteins. Separation is based on the

molecular weight. Highly negatively charged sodium dodecylsulfate (SDS)

saturates all variously charged proteins with negative sulfate charges. By doing

so, proteins in the sample, all highly negatively charged, move very rapidly

through the electrophoretic field based only upon their molecular weight. Even

though this is the most specific method of separation, it is hard to recover the

protein from the gel. It was already denatured by SDS and 2-mercaptoethanol. It

can sometimes be renatured, but it is usually not fully renatured. However, it is

an excellent choice for the separation, quantification, and analysis of protein

rather than the purification of native protein.

8) Based on a protein’s charge, isoelectric focusing (IEF) is also an efficient tool for

separating proteins. All proteins have their own isoelectric point (pI) where a

proteins net charge is zero such that the protein would not move in an electrical

field. Under the influence of the electrical force, the pH gradient will be

established by the carrier ampholytes, and the protein species migrate and focus

(concentrate) at their pIs. The focusing effect of the electrical force is

counteracted by the diffusion which is directly proportional to the protein

concentration gradient in the zone. Eventually, a steady state is established where

the electrokinetic transport of protein into the zone is exactly balanced by the

diffusion out of the zone. In other words, if a protein diffuses away from its pI, it

would gain a charge and migrate back, which is the focusing effect. Two-

dimensional gel electrophoresis (2D-GE) which combines IEF and SDS-PAGE, is

a high-performance separation tool, which can separate more than 2,000 different

proteins. It is widely used for the identification of certain proteins rather than for

preparative use. Recently, mass spectrometry (MS) was combined with 2D-GE;

excellent purification (by 2D-GE) and specific identification/sensitive

quantification of trace amounts of protein (by MS) were achieved.

9) Since albumin is not glycosylated, which is unusual for the plasma proteins,

concanavalin A that binds glycosylated residues of proteins can be used to remove

most protein other than albumin. This method is called “negative affinity

chromatography” since unbound protein would be the starting material for

albumin purification [67].

Several additional methods have been developed over the past couple of decades, including polyethylene glycol fractionation [68] and a microporous silica method [69], but they have not found extensive use in the laboratory.

In summary, as aforementioned, albumin preparation for purity cannot be a single simple step; rather, it should be a multistep procedure. Feldhoff et al., achieving the highest purity reported, devised a five-step purification method for mouse albumin and transferrin. This method includes ammonium sulfate fractionation, cation-exchange, anion-exchange, cibacron blue-affinity chromatography, and finally gel permeation chromatography with mouse ascites. By SDS-PAGE, there was no significant band other than albumin, indicating ~100% purity [70].

1.5.9. Summary

I have described the general background and methods for studying albumin, an important protein osmotic pressure regulator. The methods can be applied to study albumin turnover and the role of FcRn. Mass balance can be used since albumin is

continuously maintained at a high and stable plasma concentration. Using mass balance considerations, the effect of FcRn on albumin turnover can be evaluated with biosynthetically labeled albumin. We can also appreciate how the body can accommodate a low albumin level without FcRn to maintain the body homeostasis.

1.6. Model Protein II: Vitellogenin

1.6.1. Pharmacodynamics

Pharmacodynamics refers to the relationship between drug concentrations at the site of action (receptor) and pharmacological response or effect, including biochemical and physiologic effects that influence the interaction of drug with the receptor [71].

Receptor theory is generally employed in pharmacodynamics, the phenomenon that pharmacologic effects of many drugs lag behind drug concentrations in plasma has been explained by the appropriate pharmacodynamic model such as linked sigmoid maximum effect model [72] and indirect response model [73]. The type of relationship that exists between the plasma concentration of a drug and an associated response is generally determined by two factors: whether concentration is directly or indirectly related to response, and whether the drug interacts with the receptor in a reversible or irreversible manner.

1.6.2. Indirect Response Model

Although the link model (= effect compartment model) accommodates certain linear mechanisms of pharmacologic responses, it usually assumes that the lag in the pharmacologic effect is mainly caused by the distribution of a drug from the central compartment to the effect compartment [20, 72]. In other words, this hypothetical effect compartment model describes the rate of onset and offset of effect is governed by the rate of drug distribution to and from a hypothetical “effect site” [20]. However, many drug- induced pharmacological effects may show delay due to mechanisms other than the slow distribution effect; factors involved in the stimulation or inhibition of the production or elimination of the target molecules can regulate the kinetics of pharmacologic effect and may account for the lag time of the responses. Pharmacodynamic indirect response models deal with mainly four basic physiologic factors that are involved in controlling the response variables: inhibition of the response in the input (type I) or output step (II), or stimulation of the response in the input (III) or output step (IV) [20]. Therefore, indirect response models may be more appropriate for diverse drugs which show lag times between the plasma or biophase drug concentrations and the time course of their pharmacodynamic responses.

1.6.3. Vitellogenin as a Model Protein for Receptor-mediated Protein Production

Vitellogenin (Vg) is an egg-yolk precursor protein that is synthesized in the liver of fish (as in other egg-laying vertebrates) prior to its transport to the ovaries and 34

incorporation into developing oocytes. Synthesis of Vg is under estrogen control mediated by estrogen receptors in the liver. Both male and female fish can be induced to synthesize Vg after estrogen exposure or after exposure to estrogen-mimics. Vitellogenin can also be induced in both juvenile and adult individuals, and detection of Vg synthesis has become the most widely studied biomarker of exposure to endocrine-active compounds. In many fish, induction of Vg is extremely sensitive to estrogen exposure.

For example, the estrogenic compound ethynylestradiol induced significant increase in the vitellogenin expression in the liver and plasma by dose-dependent manner [74].

Many drugs elicit their pharmacological effects via receptor-mediated gene induction processes and subsequent up-regulation or down-regulation of protein biosynthesis. Thus, a complete understanding of their pharmacodynamics should include receptor regulation and activation, signal transduction and protein synthesis as well as drug-receptor interaction.

1.6.4. Estrogen Receptors as Transcription Factors

All estrogen receptors are transcription factors that, once bound to estrogen such as estradiol (E2) in the cell nucleus, form dimer complexes that interact with specific

DNA regions called the estrogen responsive elements (ERE). The binding to the ERE appears to be facilitated by several additional proteins, and eventually leads to the transcription of specific genes [75]. This is the classical ligand-dependent mechanism of action, but two other genomic pathways are known; i.e., ligand-independent and DNA-

binding dependent, as well as a non-genomic pathway utilizing cell-surface signaling

[76]. Little information is available on these latter three pathways in fish and we have assumed throughout this chapter that estrogen signaling in trout is confined to the ligand- dependent mechanism of action.

1.6.5. Subtypes of Estrogen Receptors

In this text, I will use the convention “R” to represent estrogen receptor as an unbound form to estrogen while “ER” will mean the estrogen-receptor complex. In both fish and mammalian species, the predominant effects of estrogen are regulated by intracellular estrogen receptors. There are two distinct R subtypes, Rα and Rβ [77, 78].

However, due to duplication events within the genomes of fishes [79], more than one form of the Rβ subtype (i.e., Rβ1, Rβ2) has been reported in some fish species [80, 81].

At this time the biological function(s) of the different R subtypes or forms is not known for any fish species. However, at least 48 genes are believed to be regulated by estrogen in the fish liver [82]. Many of the estrogen responsive genes in trout, including the Vg gene, appear to be controlled by Rα [83]. It appears that Rα is the principal R in the liver

[84].

1.6.6. Gene Products of Receptor Activation

Arguably the best-studied gene product of R activation is Vg. In addition to the yolk-forming Vg, several eggshell envelope proteins, collectively called zona radiata proteins (ZRP), are also are also regulated by the ER in fish [85]. ZRPs are synthesized in the liver and ovaries and incorporated into the developing oocytes in a manner analogous to Vg. A third estrogen responsive gene product is the R itself. Estrogen receptors are auto-regulated in rainbow trout [7], and E2 is involved in a positive feedback loop to up-regulate its own receptor. A number of studies have demonstrated in rainbow trout that liver R mRNA and protein are up-regulated by E2 treatment [86]. The modeling in this text will focus on R and Vg as the inducible gene products of the exposure to synthetic estrogen, 17-α-ethynylestradiol (EE2). However, the existence of the ZRPs will allow the option of future versions of the proposed model to expand into characterizations of additional estrogen responsive gene products.

1.6.7. Regulation of Gene Expression for Receptor and Vg

Both estrogen receptor (R) and Vg gene expression were significantly up- regulated in the liver of male trout upon their exposure to estrogens [7]. There are several points of regulation by steroid receptor gene expression such as transcriptional, post-transcriptional, translational, and/or post-translational levels [7]. The estrogen- receptor complex (ER) induced not only increases in the transcription of mRNA for both

R and Vg (transcriptional level) but also the stabilization for both mRNAs (post- transcriptional level), leading to a significant increase in both mRNA levels. As seen in the glucocorticoid model, mRNA for Vg can increase the efficiency of Vg translation by an amplification factor (translational level). Consequently, both R and Vg biosynthesis were considerably enhanced, showing that estradiol-induced stabilization of mRNA for R was dependent on both the dose and the duration of the estrogen treatment [7].

1.6.8. Differential Responses in the Gene Expression for R and Vg by ER Complex

An interesting model was suggested for differential responses between R and Vg genes by activated ER complex [83]. According to this model, the R gene exhibits a low threshold response to loaded estrogen receptor, and increasing amounts of ER do not affect the transcriptional response of this gene during estrogenic stimulation. In contrast,

Vg gene expression requires the presence of a relatively highly loaded estrogen receptor level, and its transcriptional response is directly proportional to the amount of synthesized R [83]. The differential responses of R and Vg genes to increasing amounts of E2-receptor complex may be related to different affinities of the ER complex for the estrogen response element (ERE) of the two genes: with a high affinity, a low complex concentration should immediately saturate the ERE of the R-gene promoter, leading to a rapid and maximal response of the R gene. At the same time, low affinity of the complex for the ERE of the Vg promoter would require an elevated ER concentration before the

Vg gene promoter functioned. An increase in the ER level after E2 stimulation would

favor the interaction between the complex and the ERE, leading to a progressive and proportional activation of the Vg gene promoter [83].

1.6.9. Summary

Unlike constitutive plasma protein such as albumin, vitellogenin biosynthesis and turnover are highly regulated by the receptor-mediated mechanism induced by hormone.

A biological feedback (positive and/or negative) can be mathematically expressed by a pharmacokinetic/pharmacodynamic modeling of ligand-induced receptor-mediated gene induction and associated protein expression, which will give us a better understanding how a body controls and deals with the stimulation induced by the presence of endogenous and/or exogenous ligands that will trigger receptor-dependent pharmacologic effects.

1.7. Hypothalamus-Pituitary-Gonad (HPG) Axis and Feedback Control

of Hormone Turnover

1.7.1. Overview of the Endocrine and Reproductive Systems in Fish

In fish, as with other vertebrates, reproduction requires the coordination of a variety of physiological and biochemical processes that finish with the release of viable gametes and fertilization. While the gonads undergo a period of rapid growth before the spawning, a seasonal reproductive cycle exists in many fish species. 39

Communication between cells and tissues can occur via the central nervous system and/or through the release of chemical messengers or signals. The endocrine system can be defined as any tissue of cells that release a chemical messenger (hormone) directly into the blood that signals or induces a physiological response in some target tissue. The endocrine system is involved with all phases of maintenance of homeostasis as well as the seasonal regulation of many biological responses to the external stimuli.

Many endocrine systems are in fact a neuroendocrine system that is integrated with the central nervous system (CNS). Therefore, it is helpful to form a link between

CNS and the reproductive systems, followed by control processes involved in the regulation of these systems.

Neuroendocrine control in the reproduction is exerted though actions of the brain

(hypothalamus), pituitary gland, and gonads, which are often called the hypothalamus- pituitary-gonad axis (HPG axis). External stimuli such as changes in the temperature, photoperiod, and length of daylight can be processed by the hypothalamus which triggers the secretion of gonadotrophic hormones (gonadotropins) from the pituitary gland.

Internal stimuli, including basal metabolism or growth and chemical secretions from the peripheral tissues, can also turn on the signal to the hypothalamus. The secretion of neurohormones from the hypothalamus influences the release of pituitary hormones. The pituitary gland in fish as in other vertebrates consists of separate tissues called the neurohypophysis and adenohypophysis [87]. The pituitary gland secretes several hormones including thyrotropin (TSH) and gonadotropins (FSH and LH) which are most important in the reproduction system.

Certainly, the most important peripheral tissue involved in the neuroendocrine control of reproduction is the gonad which consist of the ovaries and testes. The process of egg development, oogenesis, occurs within the lamellae and can be divided into several discrete stages such as pre-vitellogenesis phase, vitellogenesis, maturation, and ovulation, as observed in zebra fish [88].

1.7.2. Reproductive Hormones in Fish

Gonadotropin releasing hormone (GnRH) is a decapeptide released from the hypothalamus, and mostly conserved in fish, differing only in one or two amino acids

[89]. One or possibly two distinct GnRH receptors are found in fish [89], all of which are cell surface proteins.

Gonadotropins are synthesized within the adenohypophysis of the pituitary which is directly innervated with neurosecretory fibers originating in the hypothalamus [90].

Gonadotropins are heterodimer glycoproteins possessing a common, species-specific α- subunit and a hormone-specific β-subunit. Two gonadotropins are produced in fish; they are often referred to as GTH-I and GTH-II. Since they are functionally similar to mammalian follicle stimulating hormone (FSH) and luteinizing hormone (LH), respectively, FSH and LH will be used instead of GTH-I and GTH-II in this text. The primary target cells of the two gonadotropins are the granulosa and theca cells surrounding the oocytes within the ovarian follicle and Sertoli and Leydig cells in the testes. Upon stimulation by gonadotropins, theca cells convert cholesterol to testosterone through a series of reactions that also produce 17α-hydroxyprogesterone, a precursor for 41

17α, 20β-dihydroxy-4-pregnene-3-one (DHP). The granulosa cells then convert testosterone into estradiol and synthesize DHP [91]. LH appears to stimulate granulosa cells to produce estradiol (E2) and DHP [92] while FSH seems to be the primary gonadotropin responsible for directing growth of the gonads and the progression of the oocytes in the reproductive cycle. Receptors for FSH are found in both theca and granulosa cells whereas the LH receptors are only expressed in granulosa cells [91].

The sex steroid hormones are derivatives of cholesterol and possess a fused four- ring structure. Estrogens are C18 steroids, including estradiol and estrone, primarily synthesized in ovary. Androgens are C19 steroids with the 11-oxygenated derivatives, such as 11-ketotestosterone being the most important in male sexual development in fish

[93], which contrasts with other vertebrates where testosterone is the more biologically active androgen. Progesterones are C21 steroids, formed in the gonads of most fish species, the most important of which is DHP, a hormone involved in oocyte maturation and spermiation.

1.7.3 Feedback Control Mechanism and Hormonal Turnover in Fish

Gonadotropins stimulate the synthesis and the release of sex steroid hormones from the gonads, which in turn alters the release of gonadotropins by the pituitary gland.

Both positive and negative feedback loops exist in fish. Salmonids are the fish best characterized in their hormonal feedback control mechanisms. In coho salmon, exposure to testosterone or estrogen showed a negative feedback effect on FSH secretion [94] while DHP did not show any effect. Sex steroid displayed a negative effect on the

release of LH from the pituitary gland. In contrast, it showed a positive effect on the synthesis of LH [94].

Both FSH and LH stimulate in vitro production of E2 in salmon model [95, 96].

In salmon and trout, plasma FSH increases early in oogenesis; it specifically influences the progression from primary to early secondary oocyte growth whereas plasma LH appears to regulate final oocyte maturation (FOM).

These differential feedbacks of steroids onto the gonadotropins are mathematically characterized in chapter 5 using a pharmacodynamic model for a synchronous spawning fish, the female coho salmon. This quantitative model predicts successfully the plasma turnovers of four major hormones, FSH, LH, E2, and DHP, by periodical feedback controls and an indirect-type response system.

1.8. Conclusion

Biologically active and endogenous molecules are continuously renewed and degraded. Some molecules have longer half-lives and other molecules are catabolized more rapidly. There could be certain mechanisms involved in the biological fate of endogenous molecules; particular molecules may be recycled from the degradation, a group of molecules may be degraded more rapidly by their cofactors or receptors, and others may be manufactured or induced more or less by the complex biological and biochemical processes of the cellular and organ physiology.

Biochemistry-based approaches have revealed a lot of qualitative relationships for certain biological molecules and associated responses, assisted by modern molecular 43

biology techniques. However, there has accumulated a great need for quantifying these important molecular events and relating them via mathematical expressions.

Pharmacokinetics/Pharmacodynamics (PK/PD) is the tool for evaluating these endogenous complex biochemical events with proper mathematical models that explain the possible mechanisms involved in a quantitative way. In this text, kinetic approaches were used for the investigation of the very important plasma constitutive protein, albumin, and its receptor-dependent turnover mechanism. Dynamic modeling helped in understanding more complex periodical reproductive hormonal alterations and turnover via feedback mechanisms. PK/PD modeling accounted for the receptor-mediated gene induction and protein expression/up-regulation induced by environmental xeno-estrogen or periodical expression of estrogen.

Therefore, PK/PD modeling provides an excellent tool for studying not only xenobiotics such as a drug but also endogenous biomolecules, especially in the receptor biology, and further generations of more evolved and more intelligent PK/PD models along with pharmacogenomics are warranted to better understand and characterize complicated and regulated biological processes.

CHAPTER 2

PROTEIN CHEMISTRY: METHODS FOR SEPARATION AND

QUANTIFICATION OF ALBUMIN AND TRANSFERRIN

2.1. Background

Albumin is an acidic protein, having a net negative charge at pH 7 of –15 (human serum albumin; HSA) or –17 (bovine serum albumin; BSA). Its pI, pH at which the net charge including any bound ion is zero, is 4.7. Its molecular weight is 66,438 Da (HSA) from the amino acid composition. From its crystal structure, HSA is in the shape of a heart or an equilateral triangle, consisting of three domains. Albumin is highly stable in plasma; specimens can be stored for several weeks at 4°C or several days at room temperature if evaporation is prevented. Protease inhibitors in the plasma appear to protect against its breakdown [31].

Since albumin turnover is being studied and particularly the role of a protective receptor, FcRn, as introduced in chapter 1, there are two demands made on the isolation methods chosen:

1) The radioactivity of albumin biosynthesized after administering labeled amino

acids must be measured in the presence of other biosynthetically labeled plasma

proteins.

2) Infused radiolabeled albumin (usually radioiodinated albumin) must be native,

without any other protein contamination or denatured albumin.

For the first demand, the albumin separation method does not have to preserve the native state because albumin is used for quantitative assay, not for administration or radiolabeling. In this case, immunoprecipitation or SDS-PAGE can be used to take advantage of their specificity, purity, and high recovery, even though they do not generally produce native albumin.

Considering the second demand, recovery is not an important issue; rather, purity and native conformation are key factors. Therefore, multistep purification can be applied at the expense of recovery such that the purified albumin preparation is ultimately free of contaminants of other plasma proteins and degraded or denatured albumin. These steps should be gentle so that purified albumin is not denatured. In this case, irreversible purification methods, such as immunoprecipitation or SDS-PAGE cannot be applied, but a combination of various chromatographic methods proved to be satisfactory.

In this chapter, methods were established for the separation and quantification of albumin and transferrin. Several quantitative and qualitative methods for the characterization of albumin and transferrin were developed; i.e., SDS-PAGE,

immunoblot, immunoprecipitation, and ELISA. Plasma from WT and KO mice were compared to see whether profiles of plasma proteins were different with or without FcRn.

Lastly, as albumin is a negative acute-phase reactant, we measured the concentration of a well-known positive reactant in the mouse, serum amyloid P (SAP), by ELISA. SAP was used as a marker of acute-phase-dependent influence on albumin synthesis (Chapter 3).

In summary, the current chapter provides general albumin and transferrin assay methods that can be used in studies of albumin biology and physiology.

2.2. Materials and Methods

2.2.1. Animals

Control wild-type mice (C57BL/6J; WT) and two FcRn-knockout mice, β2- microglobulin (B6.129P2-B2mtm1Unc; BK) and FcRn-α-chain knockout

(B6.129X1/SvJFcgrtTm1Dcr; AK; [21]) were kindly donated by Dr. Derry Roopenian of the Jackson Laboratories, ME. Fresh blood was obtained after exsanguination under isoflurane-induced anesthesia. Plasma was harvested by centrifugation at 12,000 rpm for

10 min at 4°C. Tritium-labeled plasma was obtained by exsanguination from the inferior vena cava under the isoflurane-induced anesthesia at 90 min after intravenous bolus injection of [3H]-leucine (156 Ci/mmol; 50 µCi/25 g body weight; Amersham,

Pistacaway, NJ) via the tail vein. All plasmas were stored at –80°C.

2.2.2. Purified Proteins

Purified mouse plasma proteins were commercially available, and provided with documentation on their methods of purification and characterization; mouse serum albumin (MSA) and transferrin (TF) were purchased from Intercell (Hopewell, NJ) and

ICN (Cappel, Chillicothe, OH), respectively. Multi-step purification was performed for

MSA including ammonium sulfate fractionation, ion-exchange chromatography, affinity chromatography, and gel-filtration chromatography. TF purification included salt fractionation, gel-filtration chromatography, ion-exchange chromatography and immunoabsorption.

2.2.3. Sodium Dodecylsulfate-Polyacrylamide Gel Electrophoresis (SDS-PAGE) of

Plasma

For SDS-PAGE of plasma, a 10% uniform resolving gel was prepared with 30% acrylmide/bisacrylmide (29:1; Bio-Rad, Hercules, CA), followed by a 5% stacking gel.

Untreated (= unlabeled), serially diluted plasmas were loaded into individual wells (10 wells/gel) of the gel, with plasma amounts of 0.2, 0.1, 0.05, 0.025, and 0.0125 µL (WT) and with 0.2, 0.1, 0.05, and 0.025 µL (KO) [20]. Plasma was serially diluted with phosphate-buffered saline (pH 7.4; PBS) and 2X SDS-PAGE sample buffer (100 mM

Tris, 4% SDS, 0.02% bromphenol blue, 20% (v/v) glycerol, 2% (v/v) 2-mercaptoethanol

(2-ME), pH 6.8) under reducing conditions. Some experiments were done under non- reducing conditions without 2-ME. Sample mixtures were subjected to boiling at 95°C 48

for 5 min followed by centrifugation, in preparation for loading into the well. The total volume loaded was 20 µL/well. A molecular weight marker (Amersham) was also loaded into the last well. Samples were run for 1.5 hr with running buffer (20 mM Tris,

150 mM glycine, 0.1% SDS, pH 8.6) under 25 mA/gel at room temperature after which the gel was subjected to Coomassie blue staining (50% (v/v) methanol, 10% (v/v) acetic acid, 0.05% Coomassie brilliant blue G-250) for 2 hr followed by destaining with 10% acetic acid overnight.

In order to see if a particular assay or method is quantitative, the best approach would be to test whether the method gives a linear relationship between the concentration of specimen and the observed and measured values, such as optical density. A high concentration tends to quench the optical density whereas a low concentration might be below the limit of detection. Failure to show a linear relationship between an increase in the concentration and optical density may lead to inaccurate estimation of the sample concentration. To determine the linearity of albumin detection by SDS-PAGE, a 10% uniform gel was prepared with two wells per gel. This wide well was used to load a larger volume of plasma. One well can load up to 4 µL of WT plasma or 8 µL of KO plasma, above which albumin was not resolved into its 67 kD band. Tritium-labeled plasmas (one WT and one KO) prepared in section 2.3.1 were diluted with unlabeled plasma (WT and KO) in order to maintain the same plasma protein contents in diluted samples. Specifically, 15 µL of labeled plasma from WT mice (= 100% labeled plasma) as mixed with 5 µL of unlabeled plasma from WT to make 75% of labeled plasma of WT

(3:1 ratio of labeled to unlabeled plasma). Diluted labeled plasmas were also prepared for 50% (1:1) and 25 % (1:3). Unlabeled KO plasma was used for dilution of labeled KO 49

plasma. The plasma sample was applied on the well in 120 µL (total volume) containing

3 µL of mixed plasma also diluted by PBS (57 µL) and 2-ME-containing 2X sample buffer (60 µL). After running for 1.5 hr at 25 mA/gel, the gel was subjected to Coomasie blue staining for 15 min followed by destaining with 10% acetic acid for 30 min. After washing with water for 5 min, gel was placed onto transparency film where albumin and transferrin bands were excised carefully by scalpel and blade followed by overnight digestion with 2 mL of tissue gel solubilizer (NCS tissue solubilizer; Amersham) at room temperature. Two milliliters of Ecolite (ICN), 14 mL of BCS (Amersham), and 80 µL of acetic acid were added sequentially to the digested bands, and the radioactivity was counted by liquid scintillation counting (Beckman, Fullerton, CA). Specifically, scintillation counting was performed for 10 min/sample in the tritium channel. Unlabeled albumin and transferrin gel bands were used as a background radioactivity. There was no significant chemiluminiscence (< 0.05%) during the procedure with consistent counting efficiency of ~50%. The detection limit was set to be ~50 dpm/sample, under which the counting standard error was greater than 10%. Radioactivity was plotted against volume applied to the beads from which slope, intercept, and linearity coefficient (R2), were calculated by a linear regression method. Three independent gels were made and run with the same plasma sample to check the linearity and reproducibility of SDS-PAGE (n

= 3).

2.2.4. Immunoblots of Albumin and Transferrin

For immunoblots of MSA and TF, plasmas of untreated WT and KO mice were serially diluted with PBS and SDS-PAGE sample buffer and 20 µL volumes were loaded into wells of a 10-well gel consisting of a uniform 10% polyacrylamide gel. The gel was electrophoresed for 1.5 hr at 25 mA/gel under both reducing and non-reducing conditions

(MSA) or non-reducing condition (TF). Electrophoretic transfer was done using nitrocellulose membrane (Amersham) with transfer buffer (20 mM Tris, 150 mM glycine, pH 8.6) for 1.5 hr at 180 mA/unit. Membrane was removed and placed in a blocking solution (5% non-fat milk dissolved in 0.05% (v/v) Tween 20-containing Tris-buffered saline, pH 7.5) for 1 hr at room temperature. After washing three times for 5 min each time with washing solution (0.05% Tween 20 in Tris-buffered saline, pH 7.5; TBST), the membrane was incubated for 1 hr with a 1/5,000 dilution of anti-MSA goat antibody

(Bethyl, Montgomery, TX) or 1/5,000 of anti-TF goat antibody (Bethyl), both of which were conjugated to horseradish peroxidase (HRP) diluted in blocking buffer. After washing three times for 10 min each time with TBST, chemiluminescence was induced by incubation with 0.5 mL of luminol and 0.5 mL of oxidizing reagent (Amersham) for 5 min at room temperature. The image was developed and visualized after exposing the membrane for 15 sec.

2.2.5. Immunoprecipitation of Albumin and Transferrin

The procedure for immunoprecipitation of albumin and transferrin was modified from a published method [97]. To purify by immunoprecipitation, 100 µL of protein G-

Sepharose (Amersham; ~18 mg human IgG/mL drained beads) was pre-equilibrated with

Tris-buffered saline (50 mM Tris, 140 mM NaCl, pH 7.5; TBS) and incubated with 100

µL (1 mg/mL) of affinity-purified goat IgG against MSA or TF (Bethyl) diluted in 200

µL of TBS for 1 hr at 4°C in an Ultrafree-MC centrifugal filter unit (Millipore, Bedford,

MA) with gentle rocking. After washing the beads four times with TBS containing

0.05% Tween 20 (TBST), 1 µL (for MSA) or 5 µL (for TF) of tritium-labeled plasmas from WT and KO mice diluted in TBST (300 µL) were added to the beads and the spin column followed by incubation for 3 hr at 4°C with gentle rocking. Previously, we found that a preclearing step was not necessary since there was no significant precipitation using irrelevant antibody (rabbit anti-ovalbumin antibody), suggesting that non-albumin protein in the plasma would not be co-precipitated by MSA immunoprecipitation. After washing with TBST four times and with TBS twice, the beads were resuspended in SDS-

PAGE sample buffer containing 2% (v/v) 2-ME and boiled at 95°C for 5 min. After centrifugation at 3,000 rpm for 3 min, the flow-through was subjected to 10% SDS-

PAGE using a two-well/gel system after which gel bands were excised as described in section 2.2.3 for the linearity of albumin SDS-PAGE. Whole gel was divided into nine gel slices with different band widths from the top (loading zone; band-1) to the bottom

(end of running; band-9), including transferrin (band-3) and MSA (band-4), heavy chain of antibody (band-5), and light chain of antibody (band-8). The band width did not 52

influence the counts recovered by LSC as long as radioactivity was negligible. In other words, additional gel content did not generate significant chemiluminiscence or quenching effects. All bands were digested with gel solubilizer overnight. Scintillation cocktail with acetic acid was added to the samples, and the radioactivity was measured by liquid scintillation counting (LSC) as shown in section 2.2.3. The radioactivity (dpm) recovered by immunoprecipitation was plotted against the individual band fractions.

Albumin purity was calculated as albumin dpm divided by total dpm of all nine fractions which had a significant amount of radioactivity (> 50 dpm). TF purity was expressed by the same calculation. Three independent immunoprecipitations were performed with the same plasma sample in order to see the purity and reproducibility of the method.

For the linearity of immunoprecipitation of albumin, different volumes of tritium- labeled WT plasma (1, 0.5, 0.25, and 0.125 µL) were incubated with Protein G-Sepharose and the antibody mixtures as described above. After the final wash, beads were transferred into the scintillation counting vial and 2 mL of tissue solubilizer was added.

After overnight incubation, 14 mL of BCS cocktail, 2 mL of Ecolite, and 80 µL of acetic acid were added, and the radioactivity was measured by liquid scintillation counting.

Radioactivity was plotted against the volume applied to the beads, from which slope, intercept, and linearity coefficient (R2), were calculated by a linear regression method.

2.2.6. ELISA for Albumin and Transferrin

ELISA for albumin and IgG was previously described [17]. The current ELISA for albumin and transferrin is based on the same protocol, but slightly modified for more 53

reliable quantification. Specifically, goat IgG (Bethyl) against mouse serum albumin

(MSA) or transferrin (TF) diluted in coating buffer (50 mM sodium carbonate, pH 9.6) was incubated in wells of an immunoplate (Nalgene Nunc International, Rochester, NY) for 1 hr at room temperature. After washing the wells with wash buffer (300 µL/well, 50 mM Tris, 140 mM NaCl with 0.05% Tween 20, pH 8.0), 200 µL of blocking buffer (1%

BSA, 50 mM Tris, 140 mM NaCl, pH 8.0) was incubated in each well for 30 min at room temperature. Purified MSA or TF standards were serially diluted with dilution buffer

(TBS with 0.05% Tween 20 and 1% BSA, pH 8.0) to make 100, 50, 25, 12.5, 6.25, 3.125, and 1.56 ng/mL of standard solution. The absolute concentration of standard protein was calculated from the measured optical density at 280 nm using a UV spectrophotometer

0.1% [19] and the reference extinction coefficients of mouse serum albumin (E280 = 0.58)

0.1% and mouse transferrin (E280 = 1.08) [70]. Protein standard solutions were added to the wells of the plate, 100 µL/well, and were incubated for 1 hr at room temperature.

Dilution buffer was added, 100 µL/well, to serve as a blank. After five washes, horseradish peroxidase (HRP)-conjugated goat IgG against MSA or TF (Bethyl) was added to the wells, 100 µL/well. The antibody was diluted as 1/60,000 (for MSA; from 1 mg/mL) or 1/30,000 (for TF; from 1 mg/mL) and was incubated for 1 hr at room temperature. After five washes with wash buffer, the substrate reaction was started by the addition of 100 µL to each well of the 1:1 mixture of TMB peroxidase substrate and hydrogen peroxide (KPL, Gaithersburg, MD) for 15 min at room temperature, and was stopped by the addition of 2 M H2SO4 (100 µL/well). Optical density (OD) was measured using an ELISA plate reader (Kjunior; Bio-tek, Winooski, VT) at 450 nm and plotted against the standard concentrations of the protein. A linear standard curve was 54

made with measured OD values from the four independent replicates. The slope, intercept, and linearity coefficient (R2) were calculated by a linear regression method.

2.2.7. Two-dimensional Polyacrylamide Gel Electrophoresis (2D-PAGE)

2.2.7.1. Sample Preparation

The proteins in 10 µL of plasma from WT, AK, and BK mice were individually precipitated by 5% TCA (= addition of 0.5 µL of 100% TCA, w/v) in order to remove salts and other soluble substances in the plasma. After thorough mixing, the mixtures were incubated on ice for 15 min and centrifuged at 10,000 rpm for 10 min, the supernatant was discarded without disturbing the protein pellets. Pellets were washed three times with 100 µL of ice-cold acetone, discarding the supernatants. The final pellet was air-dried for 2~3 minutes at room temperature, resuspended and solubilized in 200

µL of rehydration buffer (7 M urea, 2 M thiourea, 4% CHAPS, 2 mM tributyl phosphine

(TBP), 0.2% (v/v) carrier ampholytes of pH 3~10, 0.002% bromphenol blue and supplemented with protease inhibitors cocktail). Finally, 10 µL from the 200 µL soluble fraction was further diluted to 200 µL in the same rehydration buffer. The diluted fraction was used for rehydration.

2.2.7.2. Rehydration

In each case a total of 185 µL of sample was loaded onto 11 cm, pH 3~10 immobilized pH gradient (IPG) strips (Bio-Rad). Passive rehydration was performed at room temperature for 16 hr.

2.2.7.3. First Dimension: Isoelectric focusing (IEF)

IEF was performed at 20°C for a total of 80,000 volt-hours at a maximum of 8000 volts using a Protean IEF Cell (Bio-Rad).

2.2.7.4. Equilibration

For the second dimension, IPG strips were equilibrated for 10 minutes sequentially by rocking in buffer 1 (6 M urea, 2% SDS, 0.05 M Tris/HCl with pH 8.8,

20% (v/v) glycerol and 2% DTT) and buffer 2 (6 M Urea, 2% SDS, 0.05 M Tris/HCl with pH 8.8, 20% (v/v) glycerol and 2.5% iodoacetamide) at room temperature.

2.2.7.5. Second Dimension: Electrophoresis

The second dimension was done on precast 4~20% gradient Criterion gels (Bio-

Rad) at 200 V for 60 min at room temperature. Afterwards, the gels were fixed with a fixing solution for 12 hr that contained 50% (v/v) ethanol and 2% (v/v) phosphoric acid. 56

The gels were stained with Colloidal Coomassie Blue G-250 for 24 hours followed by destaining with water. The gel images were taken on a Versadoc 3000 gel imaging system (Bio-Rad). Densitometry was performed by the Gel-Doc program (Bio-

Rad).

2.2.8. ELISA for SAP

The ELISA method for SAP was adapted from the method developed by Du Clos et al. [98]. An immunoplate (Nalgene Nunc) was coated for 1 hr at room temperature with 100 µL/well of 2 µg/mL of affinity-purified sheep anti-mouse SAP (Calbiochem-

Novabiochem, La Jolla, CA) diluted in coating buffer (10 mM Tris, 140 mM NaCl, pH

7.4, preserved with 0.01% thimerosal; TN buffer). After washing the plate twice with

300 µL/well of wash buffer (0.05% Tween 20 in TN buffer), 200 µL/well of 0.1% gelatin in TN buffer was added and incubated at room temperature for 30 min to prevent any free protein-binding sites. After washing the plate twice, standard reference serum (100

0.1% µg/mL of SAP; E280 = 1.76 [99]; Calbiochem) was serially diluted with dilution buffer

(1% BSA and 0.05% Tween 20 in TN buffer) to make 20, 10, 5, 2.5, 1.25, 0.625, and

0.3125 ng/mL of SAP, and 100 µL/well was added to the plate and incubated for 1 hr at room temperature, after which five washes were done with wash buffer. Dilution buffer was added, 100 µL/well, to serve as a blank. The bound SAP was reacted with 100

µL/well of rabbit anti-mouse SAP (Calbiochem) at 1/25,000 dilution with dilution buffer and incubated for 1 hr. After five washes, 100 µL/well of horseradish peroxidase (HRP)- conjugated goat anti-rabbit IgG (Calbiochem), diluted 1/4,000 with dilution buffer, was 57

added and the mixture was incubated for 1 hr at room temperature. After five washes, the substrate reaction was done with 100 µL/well of the 1:1 mixture of TMB peroxidase substrate and hydrogen peroxide (KPL) for 15 min at room temperature followed by the addition of 2 M H2SO4 (100 µL/well). Optical density (OD) was measured by an ELISA plate reader (KCjunior) at 450 nm and plotted against the standard concentrations of the protein. A linear standard curve was made with measured OD values from three independent replicates. The slope, intercept, and linearity coefficient (R2) were calculated by a linear regression method.

2.3. Results

2.3.1. Sodium Dodecylsulfate-Polyacrylamide Gel Electrophoresis (SDS-PAGE) of

Plasma

The profiles of plasma proteins are shown in Figure 2.1 with serially diluted plasma of WT and KO mice. A pilot study showed that each well in a 10-well system seemed unable to accommodate more than 1.0 µL of WT plasma or 2 µL of KO plasma, which accords with published data [100]. Larger volumes appeared to force the most abundant protein, albumin, to migrate into the other bands simply because the amount of albumin exceeded the capacity of the 67 kD region. The amount of albumin in WT plasma was larger than that in KO plasma based on the densitometry, in accordance with the published results of ELISA for steady-state concentration of albumin which showed higher albumin concentration in WT plasma [17]. 58

Protein profiles of purified albumin (Intercell) and plasmas of WT and KO mice by SDS-PAGE are shown in Figure 2.2. Purified albumin appeared to have been degraded severely as judged by the presence of several protein bands under the 67 kD region, either under a reducing or a non-reducing condition. The band that appeared near

~130 or 140 kD in (A) seemed to be an albumin dimer as was also seen in intact plasma under a non-denaturing condition, supported by the doubled molecular weight (2 × 67 kD) of the albumin monomer. The band in the buffer front (< 30 kD) with purified albumin appeared to be fragmented albumin. Intact plasma did not show these protein bands, especially in the 45 and 35 kD region, suggesting that these proteins are not plasma proteins other than albumin; they were possibly degradation products that resulted from extensive purification or improper storage.

Protein profiles of purified transferrin by SDS-PAGE either in a non-reducing or in a reducing condition are shown in Figure 2.3. Unlike albumin, purified transferrin appeared to be intact without any significant degradation during the purification steps in both non-reducing and reducing conditions.

Figure 2.4 shows the linearity of albumin recovery by SDS-PAGE using biosynthetically labeled plasma of both WT and KO mice. The radioactivities of SDS-

PAGE-detected albumin in WT and KO plasma were linear (R2 = 0.9998 in WT and

0.9994 in KO mice, n = 3 in each group) in relation to the plasma volume loaded. By this satisfactory linearity, we can quantify and compare radioactivities of albumin between the two strains. Since radioactive plasma was collected at 90 min after administration of radiolabeled leucine, a precursor for radiolabeled proteins, a greater slope in KO plasma compared with WT would suggest a greater rate of synthesis of radiolabeled albumin in

KO mice. However, the number of labeled plasma applied in this experiment was one (n

= 1) and this labeled plasma was used as a source for measurable radioactivity, whereas the linearity was assessed using three independently run gels with the same plasma sample (n = 3). As the purpose of SDS-PAGE in this chapter was not to compare the radioactivities of the two strains, but to establish a quantitative method, we did not pursue the difference in the albumin radioactivity between the two strains, which is, in fact, intensively discussed in chapter 3.

Transferrin also showed linearity of recovered to loaded protein by SDS-PAGE using biosynthetically labeled plasma of both WT and KO mice as shown in Figure 2.5

(R2 = 0.9997 in WT and 0.9996 in KO mice, n = 3 in each group). Again, a greater slope in KO plasma compared with WT may imply the greater synthesis of radiolabeled transferrin in KO mice (also discussed in chapter 3).

2.3.2. Immunoblots of Albumin and Transferrin

Immunoblot profiles of albumin from the plasma of WT and KO mice and purified albumin are shown in Figure 2.6. The reducing condition showed one clear band in the 67 kD region, indicating the high specificity of antibody against MSA, while several antibody-positive bands were observed under the non-reducing condition, suggesting that albumin dimer may exist in both plasmas or that albumin had not migrated fully under this condition (albumin has 17 disulfide bonds). Purified albumin showed multiple bands moving faster than 67 kD both under non-reducing and reducing conditions, signifying that there could be albumin fragmentation during the purification

steps, which was found in the results of the SDS-PAGE determinations as well. There are three prominent non-native albumin bands in the ~45 kD, ~30 kD, and ~20 kD regions. However, there was no significant fragment in either WT or KO plasma, indicating that these fragments are unique in the purified albumin, which supports the previous suggestion that these fragments arose during the purification. The fact that these bands were detected by anti-albumin antibodies also supports the possibility that these are albumin fragments. Taken together, these fast moving bands are not likely to be plasma protein contaminants other than albumin. The band intensity of albumin in WT plasma was greater than that in KO plasma, which accorded with the results of SDS-

PAGE (Figure 2.1).

Immunoblot profiles of transferrin from the plasmas of WT and KO mice, and purified transferrin are shown in Figure 2.7 with serial dilutions of the samples under a non-reducing condition. Anti-TF-antibody was specific in binding TF and showed only one clear band in both WT and KO plasma. Unlike albumin, purified TF showed only one band under non-reducing conditions, suggesting that TF was not degraded during the purification step.

2.3.3. Immunoprecipitation of Albumin and Transferrin

Figures 2.8 and 2.9 show the purity of proteins in radiolabeled plasma by the immunoprecipitation method using anti-MSA and anti-TF antibodies, respectively (n = 3 in either WT or KO mice). Since MSA and TF were recovered in their own bands with no significant radioactivity in other bands (under the 50 dpm detection limit),

immunoprecipitation for both proteins gave almost 100% purity. The high specificity of antibody against MSA and TF was also shown in the immunoblots (Figures 2.6 and 2.7).

Figure 2.10 shows the linearity of immunoprecipitation of albumin from WT and

KO plasma using anti-MSA antibody. Radioactivity of albumin was linearly increased by increasing the volume of labeled plasma up to 1 µL of WT plasma.

2.3.4. ELISA for Albumin and Transferrin

Figure 2.11 shows the linearity of ELISA determination of albumin using purified mouse serum albumin. Antibody binding was linear up to 100 ng/mL of albumin (slope

= 0.00829, intercept = 0.00418, and R2 = 0.9971, n = 4). Plasma albumin can be diluted for quantification in this linear range of standard concentration.

Figure 2.12 shows the linearity of ELISA determination of transferrin using purified mouse transferrin. Antibody binding was linear up to 25 ng/mL of transferrin (In

Figure (B), slope = 0.00971, intercept = 0.00231, and R2 = 0.9994, n = 4). Plasma transferrin can be diluted for quantification in this linear range of standard concentration.

2.3.5. Two-dimensional Polyacrylamide Gel Electrophoresis (2D-PAGE) of Plasma

The profiles of plasma proteins by 2D-PAGE using the plasma of WT, AK, and

BK are shown in Figure 2.13, separated by their charge and size. Albumin spots were located at pH 5.8 and at 67 kD region while the more basic and larger transferrin spots were located in the right-upper position from the albumin spots in all three plasma. It

should be noted that pI is 5.8 for defatted albumin which occurs during the plasma processing for 2D-PAGE whereas the pI of native albumin is 4.7 [101]. It should also be pointed out that the plasmas of AK and BK qualitatively and semi-quantitatively yielded more protein spots, and sometimes larger spots, other than albumin, possibly due to the colloidal osmotic pressure (COP)-compensatory mechanism for lower albumin concentration in the KO plasmas. The spots at the right side of each gel (most basic portion with pH~10) seem to be an unresolved protein mixture which was separated in the second direction by SDS-PAGE, but was not separated well in the first direction by

IEF. The spot located in the pH 7.5~8 region is typically attributed to the α- and β- chains of fibrinogen, 70 kD and 60 kD, respectively. Specifically, these three prominent bands at pH~10 appear to reflect three main spots in the plasma – transferrin (higher band), albumin (middle), and 50 kD bands including α1-antitrypsin and α1-acid glycoprotein (bottom) – which were not resolved clearly, and therefore, remained unfocused. There is no report on the plasma protein recovered at pH~10 in mouse, rat, and human, not even beyond pH~8, supporting the supposition that these spots are artifacts due to sample overload.

2.3.6. ELISA for SAP

Figure 2.14 shows the linearity of the SAP ELISA, which showed excellent linearity up to 2.5 ng/mL (In Figure 2.14 (B), slope = 0.114, intercept = 0.00201, R2 =

0.9992, triplication), while it indicated quenching effect above that concentration (Figure

2.14 (A)). 63

Figure 2.15 shows the basal level of SAP in untreated plasma of WT (n = 7), AK

(n = 7), and BK mice (n = 5). WT and AK showed no significant difference in the basal concentration of SAP while BK showed a 33.6% increase in the SAP level compared with SAP concentrations of WT and AK mice. Nonetheless, those values were within the reported range [98], and the concentration change of SAP upon treatment is more important than absolute concentration.

2.4. Discussion

One of the advantages of SDS-PAGE is that it can separate many plasma proteins by their molecular weights with almost 100% recovery. However, SDS-PAGE cannot be used in more complex biological samples such as cell extracts or liver homogenate since these biological matrices contain too many proteins to be separated by SDS-PAGE. In this case, immunoprecipitation is the method of choice because of its excellent specificity and recovery. Based on those advantages, SDS-PAGE and immunoprecipitation have been preferentially used in protein turnover studies for many years [97, 100].

We first tested whether SDS-PAGE was a reliable method for quantifying labeled protein in plasma after injection of radioactive amino acid. Based on the gel excision method, a high degree of linearity was achieved for both albumin and transferrin without quenching effects (Figures 2.4 and 2.5). This validates the SDS-PAGE method for quantification of albumin and transferrin radioactivity. When purified by SDS-PAGE, albumin (67 kD) and transferrin (78 kD) bands are thought to be >95% pure, based on the densitometry of 2D-PAGE in the first dimension; i.e., <5% of focused spots have 64

different pIs (Figure 2.13). Therefore, SDS-PAGE appears suitable for the measurement of labeled protein from the plasma of WT and KO mice in protein turnover studies. From the slope of albumin radioactivity recovered by SDS-PAGE (Figure 2.4), albumin in KO plasma seemed to be produced in greater amounts at 90 min compared with WT plasma.

Purified albumin and transferrin were tested to ascertain whether these standard proteins are indeed pure. Albumin showed multiple bands (Figure 2.2 and 2.6) whereas transferrin appeared to be pure (> 90%) as shown by either SDS-PAGE (Figure 2.3) or immunoblot (Figure 2.7). Albumin fragments did not appear in intact WT and KO plasma tested by either SDS-PAGE or immunoblot, suggesting that these multiple bands are albumin fragments that still possess antigenic properties. Therefore, these proteins can be used for quantifying protein concentration by ELISA since they are all antigenic.

However, albumin may not be used for radioiodination since it is fragmented and may not behave as endogenous albumin; biologically screened radioiodinated albumin may work (discussed in chapter 3).

Antibody against MSA was specific for albumin in that it showed a single band in the plasma under reducing condition (Figure 2.6). Anti-transferrin antibody also showed a single band in either WT and KO plasma (Figure 2.7). There were multiple bands in non-reducing condition with albumin antibody, suggesting that albumin dimer or albumin not fully migrating may exist in the plasma. As non-reducing condition does not allow full denaturation of protein, the protein may not migrate as well as in reducing condition

– albumin has 17 disulfide bonds – where only the size of the protein influences migration of protein. However, densitometry showed the intensity of the albumin band

of WT plasma to be greater than the same band in KO plasma either by reducing or non- reducing condition, which accords with our previous ELISA results [17].

Immunoprecipitation was also tested as an alternative method for measuring biosynthetically radiolabeled albumin and transferrin. It gave almost ~100% purity using both WT and KO plasma with ~85% recovery. Also, it showed a high linearity (R2 =

0.9979) by serial dilution of labeled plasma.

ELISA results showed a high linearity for both albumin (R2 = 0.9971, Figure

2.11) and transferrin (R2 = 0.9994, Figure 2.12). Since the antibody used in ELISA was the same as that used in immunoblot and immunoprecipitation and the specificity of antibody proved high in both techniques, ELISA effectively quantified pure protein concentration in the plasma.

For specificity, the ratio of radiolabeled albumin plasma concentration between

WT and KO mice measured by SDS-PAGE at steady-state was significantly different from the ratio of endogenous plasma albumin concentration between the two strains determined by ELISA by 17.8% (1.48 vs. 1.80), suggesting at least two possibilities: 1) a contamination by non-albumin protein in the 67 kD band (SDS-PAGE) and/or 2) less specific antibody raised against relatively less pure albumin preparation (ELISA). The ratio of plasma transferrin concentration between the two strains did not show any difference between the two methods of measurement. Therefore, it is recommended that both methods be used for the quantification of protein (discussed in chapter 3).

2D-PAGE revealed possible up-regulation of plasma proteins by compensating mechanisms for low oncotic pressure caused by low albumin concentration in KO plasma. If the degradation rate of non-albumin proteins in KO mice is equivalent to that

in WT mice, then a greater synthetic rate is expected to occur in KO compared with WT mice since a greater number and larger protein spots other than albumin were observed in

KO plasma. However, it is difficult to quantify the level of protein concentration in 2D-

PAGE; it provides qualitative rather than quantitative protein profiles. Nevertheless, it should be emphasized that more spots appear in KO plasma compared with WT plasma

(discussed further in chapter 3).

Since albumin is a known negative acute-phase reactant, we had to ensure that albumin turnover was not disturbed or influenced by the acute-phase response, which may be turned on during the experimental procedures in albumin turnover studies. Thus, it was worthwhile to find a very sensitive marker for the acute-phase reaction. In the mouse, serum amyloid P (SAP) is the major acute-phase protein that is up-regulated during the acute-phase response [99]. It is dependent on strain of mouse, but generally the resting SAP level is less than 100 µg/mL while it shows more than 13-fold increase in the serum upon stimulation [98]. C-reactive protein (CRP) is the main acute-phase response protein in human with levels increasing from less than 5 µg/mL to 200 µg/mL or more during the acute phase response. These proteins (SAP, CRP) are pentraxins that show calcium-dependent ligand binding activity and cyclic pentameric structure [102].

The method for measuring SAP level in the plasma was developed to test if there was acute-phase response involved in our experiments measuring albumin turnover. SAP

ELISA showed good linearity (R2 = 0.9992) up to 2.5 ng/mL of SAP (Figure 2.14).

Since the change in SAP concentration during the experimental procedure is the most important feature for assessing acute-phase response, it is necessary to measure the basal level of SAP without any treatment of these mouse strains for further comparisons with 67

the basal level after treatment. Figure 2.15 showed a basal level of SAP in three strains

(3.28 for WT, 3.26 for AK, and 4.37 µg/mL for BK mice). BK showed a ~33% higher resting SAP concentration compared with WT or AK mice, suggesting that the presence of β2-microglobulin might be somehow involved in controlling the low expression of

SAP. Nonetheless, SAP basal levels of three strains were less than reported values for

C57BL/10J (26 µg/mL; [98]). The dramatic increase (> 10-fold) in the plasma concentration of SAP upon stimulation is a decisive factor for the presence of the acute- phase response.

Overall, it should be noted that the establishment of biochemical methods for separating and purifying proteins is important in studies of protein turnover. Since biological fluids contain numerous endogenous proteins, the inadequate refinement of methods for the isolation of a particular protein would sometimes mislead the researchers to the wrong conclusion. Rigorous chemical evaluation of the protein, avoiding relatively impure proteins, is necessary to estimate the kinetic parameters of the protein of interest.

As all proteins, especially in the plasma, have somewhat common features such as peptide bonds, relatively negative charges, and large shape and molecular weight, it is sometimes more difficult to separate a protein from the endogenous pool of proteins compared with detection or measurement of exogenous small compound administered to the body. The current chapter, existing for this reason, has tried to document the validity of the methods developed to further study albumin turnover and production and to evaluate the possible involvement of FcRn in albumin production or in the protection of albumin from degradation (chapter 3).

2.5. Conclusion

In this chapter, methods in protein chemistry were established for the separation and quantification of albumin and transferrin as related to our specific problem.

Antibody against mouse serum albumin or transferrin was specific in its binding to albumin or transferrin. Radiolabeled albumin and transferrin were separated by SDS-

PAGE and immunoprecipitation with a high recovery and purity. Linearity of recovered radioactivity was tested for two quantitative methods. An ELISA protocol was developed for the quantification of plasma albumin, transferrin, and serum amyloid P protein. Two-dimensional gel electrophoresis was done with the plasmas of WT, AK, and BK mice, and there was an indication of an increase in the expression of non-albumin plasma proteins, suggesting there could be an up-regulation of proteins possibly to compensate for hypoalbuminemia-induced low colloidal osmotic pressure of KO plasma.

2.6. Acknowledgment

I thank Dr. Arun K. Tewari in the Proteomics Core Lab of The Ohio State

University for his excellent performance of two-dimensional gel electrophoresis of mouse plasma. I also appreciate his helpful comment on the procedures, analysis, and interpretation of the data.

Lane 1 2 3 4 5 6 7 8 9 10

220 kD

97 kD 66 kD

45 kD

30 kD

Figure 2.1: SDS-PAGE profile of Coomassie stained proteins in WT and KO plasma. Each lane was loaded with 20 µL of sample containing a different volume of plasma by serial dilution; WT plasma 200 nL (lane 1), 100 nL (2), 50 nL (3), 25 nL (4), 12.5 nL (5), KO plasma 200 nL (6), 100 nL (7), 50 nL (8), 25 nL (9), and molecular weight marker 5 nL (10) under reducing condition with the addition of 2-ME. Arrows indicate the protein bands showing reference molecular weights.

(A) 1 2 3 4 5 6 7 8 9 10

220 kD

97 kD

66 kD 45 kD

30 kD

(B)

1 2 3 4 5 6 7 8 9 10

220 kD

97 kD 66 kD

45 kD

30 kD

Figure 2.2: SDS-PAGE profile of purified albumin (Intercell) and the plasma from WT and KO mice. Each lane was loaded with the same 20 µL of sample containing a different amount of albumin or volume of plasma; purified albumin 5 µg (lane 1), 2.5 µg (2), 1.25 µg (3), 0.625 µg (4), WT plasma 100 nL (5), 50 nL (6), 25 nL (7), KO plasma 100 nL (8), 50 nL (9), and molecular weight marker 5 nL (10). (A): Non-reducing, (B): Reducing condition with the addition of 2-ME.

(A)

1 2 3 4 5

220 kD 97 kD

66 kD

45 kD

30 kD

(B)

1 2 3 4 5

220 kD

97 kD

66 kD 45 kD

30 kD

Figure 2.3: SDS-PAGE profile of purified transferrin (ICN). Each lane was loaded with the same 20 µL of sample containing different amount of purified transferrin; transferrin 2.4 µg (lane 1), 1.2 µg (2), 0.6 µg (3), 0.3 µg (4), and molecular weight marker 5 nL (5). (A): non-reducing condition, (B): reducing condition under 10% uniform gel.

1600

L plasma) 1200 µ

800

400

Concentration (dpm/3

0 0 0.2 0.4 0.6 0.8 1

Fraction of radiolabeled protein

Figure 2.4: Linearity of albumin from the plasma of WT (closed circle) and KO (open circle) mice by SDS-PAGE. Different volumes of radiolabeled plasma (but the same volume of total plasma by the addition of unlabeled plasma) were loaded onto the well; the albumin band was excised and the radioactivity was measured. For WT mice, slope = 1,267, intercept = – 6.80, and R2 = 0.9998. For KO mice, slope = 1,399, intercept = – 0.368, and R2 = 0.9994. T represents one standard deviation (SD) with three independent experiments.

250

200

L plasma) µ 150

100

Concentration (dpm/3

0 0.2 0.4 0.6 0.8 1 Fraction of radiolabeled protein

Figure 2.5: Linearity of TF from the plasma of WT (closed circle) and KO (open circle) mice by SDS-PAGE. Different volumes of radiolabeled plasma (but the same volume of total plasma by the addition of unlabeled plasma) were loaded onto the well; the TF band was excised and the radioactivity was measured. For WT mice, slope = 170, intercept = – 1.05, and R2 = 0.9997. For KO mice, slope = 186, intercept = – 0.809, and R2 = 0.9996. T represents the standard deviation (SD) with three independent experiments.

(A)

1234 5678910

220 kD

97 kD

66 kD 45 kD

30 kD

(B)

1234 5678910

220 kD 97 kD 66 kD

45 kD

30 kD

Figure 2.6: Immunoblot of purified albumin and plasma albumin in WT and KO plasma. Each lane was loaded with 20 µL of sample containing a different amount of purified albumin or volume of plasma; purified albumin 5 µg (lane 1), 2.5 µg (2), 1.25 µg (3), 0.625 µg (4), WT plasma 50 nL (5), 25 nL (6), KO plasma 100 nL (7), 50 nL (8), 25 nL (9), and molecular weight marker 5 nL (10) under non-reducing condition (Figure A) or reducing condition (Figure B) with the addition of 2-ME.

123 4 5678 910

97 kD

66 kD 45 kD

30 kD

20 kD

Figure 2.7: Immunoblot of purified transferrin and plasma transferrin in WT and KO plasma. Each lane was loaded with 20 µL of sample containing different amount of purified transferrin or volume of plasma; purified transferrin 5 µg (lane 1), 2.5 µg (2), 1.25 µg (3), 0.625 µg (4), WT plasma 100 nL (5), 50 nL (6), KO plasma 200 nL (7), 100 nL (8), 50 nL (9), and molecular weight marker 5 nL (10, not detected and designated with arrows) under non-reducing condition.

400

300

200

100 Radioactivity (dpm)

0 B1 B2 B3 B4 B5 B6 B7 B8 B9

Figure 2.8: Purity of albumin by immunoprecipitation with the plasma of WT (empty bar) and KO (hatched bar) mice. Radiolabeled plasma (1 µL) was immunoprecipitated using anti-MSA antibody to isolate radiolabeled MSA. The antibody-bound fraction was subject to SDS-PAGE from which nine gel fractions were obtained and radioactivities were measured by liquid scintillation counting. All bands are shown by band 1 (top of the gel) to 9 (the bottom of gel running) from left to right including transferrin (band 3), albumin (band 4), heavy chain of antibody (band 5), and light chain of antibody (band 8). Averaged values are shown with T representing one SD, from three independent experiments.

250

200

150

100

50 Radioactivity (dpm)

B1 B2 B3 B4 B5 B6 B7 B8 B9

Figure 2.9: Purity of transferrin by immunoprecipitation with the plasma of WT (empty bar) and KO (hatched bar) mice. Radiolabeled plasma was immunoprecipitated using anti-TF antibody to isolate radiolabeled TF. The antibody-bound fraction was subject to SDS-PAGE from which nine gel fractions were obtained and radioactivities were measured by liquid scintillation counting. All bands are shown by band 1 (top of the gel) to 9 (the bottom of gel running) from left to right including transferrin (band 3), albumin (band 4), heavy chain of antibody (band 5), and light chain of antibody (band 8). Averaged values are shown with T representing the SD, from three independent experiments.

500

400

300

200

Radioactivity (dpm) 100

0.0 0.2 0.4 0.6 0.8 1.0

Volume of radiolabeled plasma (µL)

Figure 2.10: Linearity of radiolabeled albumin recovered by immunoprecipitation from radiolabeled WT plasma using anti-MSA antibody. Different volumes of radiolabeled WT plasma were subjected to immunoprecipitation. The radioactivity recovered from the bound fraction was measured. R2 = 0.9979 (n = 1).

1.0

0.8

0.6

0.4

Optical density at 450 nm 0.2

0 0 20 40 60 80 100

Concentration (ng/mL)

Figure 2.11: Linearity of albumin ELISA measured by ELISA reader at 450 nm (R2 = 0.9971), using purified albumin of which concentration was determined by UV absorption method at 280 nm and by the known extinction coefficient of MSA. T represents one SD from four independent experiments.

1.0 (A)

0.8

0.6

0.4

0.2 Optical density at 450 nm

0.0 0 20406080100

(B) 0.30

0.25

0.20

0.15

0.10

Optical density at 450 nm 0.05

0.00 0 5 10 15 20 25

Concentration (ng/mL)

Figure 2.12: Linearity of transferrin ELISA measured by ELISA reader at 450 nm, using purified TF of which concentration was determined by UV absorption method at 280 nm and by the known extinction coefficient of TF. (A): plotted up to 100 ng/mL of transferrin, (B): plotted up to 25 ng/mL where the high linearity exists (R2 = 0.9994). T represents one SD from four independent experiments.

IEF

pH 3 pH 6 pH 10

75 kD PAGE 50 kD

25 kD

75 kD

50 kD

25 kD

75 kD

50 kD

25 kD

Figure 2.13: 2D-PAGE of plasma from WT, AK, and BK mice.

1.5 (A)

1.2

0.9

0.6

0.3

Optical density at 450 nm

0 0 5 10 15 20

0.30 (B)

0.25

0.20

0.15

0.10

Optical density at 450 nm 0.05

0.00 0.0 0.5 1.0 1.5 2.0 2.5

Concentration (ng/mL)

Figure 2.14: Linearity of SAP ELISA measured by ELISA reader at 450 nm, using standard SAP in reference serum of which concentration was determined by the known SAP extinction coefficient. (A): plotted up to 20 ng/mL of SAP, (B): plotted up to 2.5 ng/mL where the high linearity exists (R2 = 0.9992). T represents one SD from three independent experiments.

8 g/mL) µ 6

Concentration ( 0 WT AK BK

Figure 2.15. Basal level of SAP in plasma of untreated WT, AK, and BK mice (n = 7 for WT and AK, and n = 5 for BK). Average values were plotted with SD shown as T.

CHAPTER 3

RECEPTOR-MEDIATED RECYCLING OF PROTEIN:

ALBUMIN TURNOVER AND THE ROLE OF FCRN

3.1. Background

In chapter 1, two major plasma proteins, albumin and IgG, were described and discussed, with a focus on their in vivo kinetics. Both proteins show robust binding to

FcRn in a pH-dependent fashion and are rescued from lysosomal degradation by an

FcRn-mediated process. Neither protein affects FcRn binding by one another as they have different binding sites on FcRn. The half-lives of both albumin and IgG are greatly decreased in the absence of FcRn in mouse whereas in its presence their steady-state plasma concentrations are significantly higher. Thus, FcRn was proposed to play a key role in protection of albumin from in vivo degradation [17], and to account for the prolonged albumin half-life seen in hypoalbuminemic patients and analbuminemic rats

[8]. 85

Radioiodinated mouse serum albumin (I-MSA) and mouse IgG (I-IgG) [17] had decreased terminal half-lives in both FcRn-α-chain knockout (AK) and β2- microglobulin-knockout (BK) mice (t1/2 = 24 hr for both knockout strains) compared with wild-type (WT) mice (t1/2 = 40 hr). IgA, a control protein that is not an FcRn substrate, did not show any difference in t1/2, which was 24 hr in all three strains [17]. The albumin clearance was ~20% higher in KO (0.118 mL/hr/25 g body weight) compared with WT mice (0.101 mL/hr/25 g) whereas the half-life was 40% lower (24 vs. 40 hr) [Bronson, unpublished; [17]]. On the other hand, in KO compared with WT mice, IgG showed a two-fold higher clearance (0.045 vs. 0.015 mL/hr/25 g) and a 4-fold shorter half-life (19 vs. 95 hr) [17]. It was not surprising to see more efficient FcRn-mediated protection of

IgG from degradation compared with albumin, based on concentration-catabolism relationships, because the endogenous plasma level of IgG (~140 µg/mL) was significantly lower than the normal serum level of IgG (~5 mg/mL) since these mice had been reared under non-pathogenic conditions. However, the albumin level (~40 mg/mL) of these mice is identical to that of normal mice. Since the 20% difference in albumin clearance between the two strains was relatively small compared with the IgG clearance difference, the much higher endogenous albumin concentration was thought to nearly saturate FcRn. Therefore, compared with IgG, receptor-mediated protection of albumin from degradation appeared to be relatively inefficient.

Albumin biosynthesis is regulated by many factors; e.g., colloidal osmotic pressure, acute-phase response [32], trauma [33], liver disease, infection [103], and albumin loss. Generally, it is believed that the synthesis of albumin is transcriptionally controlled [104], and that the hepatocyte is the only biosynthesis site (described in 86

chapter 1 in detail). Reduced albumin biosynthesis leads to a reduction in the steady- state plasma concentration of albumin in the plasma and the associated low oncotic pressure triggers enhanced expression of albumin mRNA, which increases albumin biosynthesis [105]. Insulin [106] and growth hormone [107] also up-regulate albumin biosynthesis. Acute-phase responses to burns or infections suppress albumin biosynthesis, due to a cytokine-dependent mechanism requiring interleukin-6 (IL-6), a mediator of the acute-phase reaction [51]. Tumor necrosis factor (TNFα) also plays a role in the inhibition of albumin synthesis [53]. In contrast, acute-phase reactants

(fibrinogen, CRP in human, SAP in mouse, and α1-acid glycoprotein) are concomitantly up-regulated [104].

As the body maintains a protein, such as albumin, at a static level as a result of balanced biosynthesis and degradation rates, a mass balance equation for a protein can be expressed as follows:

At steady-state, “Rate-in” equals “Rate-out”.

Rate-in = Rate of production of protein (Rp)

Rate-out = Rate of degradation of protein

= Clearance (CL) × Steady-state concentration (Css)

Therefore, Rp = CL × Css, and

Rp (WT) = CL (WT) × Css (WT) = 0.101 mL/hr/25 g × 40 mg/mL

= 4.04 mg/hr/25 g, and

Rp (KO) = CL (KO) × Css (KO) = 0.118 mL/hr/25 g × 20 mg/mL

= 2.36 mg/hr/25 g,

where the clearances were calculated from the plasma disappearance profiles of screened radioiodinated albumin after intravenous injection (Bronson, unpublished data) and Css was determined using an ELISA method [17].

Based on the mass balance equation and using radioiodinated albumin clearance and plasma steady-state concentration of albumin in both WT and KO strains, the albumin production rate appeared to be 40% lower in FcRn-deficient mice compared with wild-type mice [17]. Since the two strains differed only in FcRn expression, this difference in albumin production was postulated to be FcRn-dependent. Specifically, albumin clearance was increased by 20% whereas its Css was 50% lower in KO compared with WT mice; Rp (in KO) = 1.2-fold (CL) × 0.5-fold (Css) = 0.6-fold of WT

= 40% decrease from WT mice as shown in the above equations. This indicated that a low Css of albumin in KO (50%) was not entirely explained by only the small difference in the clearance (20%); in other words, the observed Css and CL should be accompanied by a greater production rate of albumin (60%) in WT mice to achieve one-fold increase in

Css. This prediction also suggested that FcRn might be responsible for the greater production of albumin, presumably by diverting albumin from a possible ‘presecretory’ degradation pathway at the exocytosis stage of albumin in the liver.

Several factors can lead to over- or underestimation of the biosynthesis rate of a protein. If the clearance of radiolabeled protein does not reflect the true clearance of endogenous protein, Rp would be mis-estimated. Either radioiodination or harsh purification or both could cause a defect in radiolabeled protein that would cause it to misbehave as native protein after being introduced into the body. Although screened albumin kinetics has been regarded as identical to those of native albumin, this apparently

has never been tested intensively by the mass balance approach. The steady-state concentration, which appears in the mass balance equation along with CL, was measured by ELISA, which utilized the principle of antibody-antigen reaction; both endogenous albumin and radiolabeled albumin bind to albumin antibody. Therefore, the concentration determination by ELISA is less likely to show large deviation from the true steady-state level of albumin compared with CL. Consequently, the over- or underestimation of Rp, if any, would not be as likely to come from an incorrect Css value as from an incorrect CL value.

While receptor-mediated enhancement of albumin production is an attractive model, there is another factor that can alter the production rate of albumin. The 50% lower steady-state concentration of albumin in KO mice could be a driving force to increase the production of albumin in order to compensate for the lowered colloidal osmotic pressure. Hypoalbuminemia provoked up-regulation of the production of not only albumin but other plasma proteins to correct the low oncotic pressure; otherwise, fluid effuses out of vascular space into extravascular space, leading to swelling and edema, and secondary pathologic events [11]. By responding in this manner, the body attempts to maintain an adequate colloidal pressure even with a significantly lowered albumin. About 25 years ago, the development of analbuminemic rats illustrated the amazing adaptability of blood physiology. Specifically, the absence of albumin stimulated the increased production of several of the plasma proteins to increase total plasma protein concentration to near or slightly lower than normal levels [108]. Taken together, these observations indicate that the synthesis of both albumin and other plasma proteins can be enhanced in response to the lowered plasma oncotic pressure in the

absence of FcRn. Therefore, two possible opposing effects on albumin production appear to exist; receptor-dependent increase in the biosynthesis/production and up-regulation of biosynthesis in response to hypoalbuminemia/low oncotic pressure. Since the two strains are from the same genetic background, there is reason to believe that both livers are identically manufacturing proteins. Moreover, as mentioned above, since two opposite effects can co-exist, we must hypothesize as a null hypothesis that there is no difference in the production of albumin between the two strains.

HYPOTHESIS

The null hypothesis (H0): Albumin production is not different between the two strains.

Alternative working hypotheses would then be either 1) Ha1: albumin production is decreased in the absence of FcRn or 2) Ha2: albumin production is increased in the absence of FcRn. The first alternative hypothesis appears to be favored with respect to the aforementioned calculation of biosynthetic rate from a radioiodinated albumin decay experiment and the steady-state concentration of albumin. However, the up-regulation of albumin synthesis in response to low albumin levels by a feedback mechanism is also well characterized in analbuminemic rats and hypoalbuminemic patients. These two opposing effects may not be distinguishable from the null hypothesis. However, it is possible for one to dominate the other. We therefore experimentally tested whether FcRn is involved in albumin production by comparing the time course of the plasma concentration of biosynthetically labeled, newly synthesized albumin between the two mouse strains after an intravenous bolus injection of tritiated leucine. This would provide

a direct, rather than an inferred, measure of the effect of FcRn on albumin production.

Transferrin was chosen as a control protein, playing two roles: it is a negative control protein for FcRn-mediated process but a positive control protein for hypoosmotic pressure-induced upregulation/compensation process, mainly caused by low plasma albumin concentration in KO mice. Therefore, the transferrin production rate was also measured and compared between the two strains.

Overall, this chapter achieved two objectives. First, I calculated the difference in the albumin production rate between the two strains to discover whether FcRn is involved in albumin production. Second, I computed credible albumin and transferrin CL values based on the mass balance equation under the steady-state condition using already- determined albumin steady-state concentrations and measured albumin production rates.

Therefore, the actual contribution of FcRn-mediated albumin recycling from its degradation could be quantified by the difference in CL between the two strains. Finally, the role of FcRn in albumin turnover kinetics was evaluated.

3.2. Materials and Methods

3.2.1. Animals

FcRn-α-chain KO strain (B6.129X1/SvJFcgrtTm1Dcr; AK) [21], their control wild- type strain (C57BL/6J; WT), and β2-microglobulin (b2m) KO strain (B6.129P2-

B2mtm1Unc; BK) were kindly provided by the Roopenian laboratory at The Jackson

Laboratory (Bar Harbor, Maine). Mice were housed in individual cages with free access 91

to water and food during the experimental procedures. All mice were male, 10-weeks old, and weighed ~25 g. All animal studies were approved by the Institutional Review

Board.

3.2.2. Measurement of Production Rates of Albumin and Transferrin in WT and KO

Mice

For albumin and transferrin production, WT and KO mice were weighed and injected via the tail vein with [3H]-leucine (4,5-3H-leucine; 156 Ci/mmol; dissolved in

0.9% isotonic normal saline; Amersham) with a dose of 50 µCi/mouse. Approximately

30 µL of blood was sampled using heparinized capillary tubes from the retro-orbital plexus at 15, 30, 45, and 60 min after the intravenous bolus injection of radioactive leucine. Two 5-µL aliquots of plasma were harvested and stored at -80°C. At 90 min after dose administration, most of blood was collected under isoflurane anesthesia from the inferior vena cava using heparinized syringes, and plasma was stored at -80°C.

Three microliters of plasma collected at each time point was subjected to SDS-

PAGE under reducing condition with 2% (v/v) 2-mercaptoethanol (2-ME). Uniform gel

(10%) was prepared, each gel containing two plasma samples (two wells/gel). The gel was run for 1.5 hr, stained with Coomassie blue G for 20 min, and destained for 30 min under 10% acetic acid. After washing the gel with water, the albumin and transferrin bands were excised carefully by scalpel and blade followed by digestion with 2 mL of tissue gel solubilizer (NCS tissue solubilizer; Amersham) at room temperature overnight.

Two milliliters of Ecolite (ICN), 14 mL of BCS cocktail (Amersham), and 80 µL of 92

acetic acid were added sequentially to the digested bands, and the radioactivity was counted by liquid scintillation counting (LSC; Beckman Co.). Radioactive protein concentrations in the plasma were normalized to 25 g of body weight.

Immunoprecipitation was employed as an additional method for measuring the production rate of albumin and transferrin in order to see whether consistent results could be obtained by both methods. Labeled plasma (0.5 µL for albumin or 2.5 µL for transferrin) at 90 min after administration of radiolabeled leucine was exposed to antibody-attached Sepharose beads and the radioactivity was counted by LSC (described in chapter 2 in detail).

Steady-state plasma concentrations of endogenous mouse serum albumin and transferrin were measured using sandwich enzyme-linked immunosorbent assay (ELISA) kits (described specifically in chapter 2) with reference to standard concentrations of purified proteins for albumin and for transferrin. Absolute standard concentration was determined by UV absorption at 280 nm using the known extinction coefficient of the

0.1% 0.1% proteins (E280 = 0.58 for mouse serum albumin and E280 = 1.08 for mouse transferrin; [70]). Plasma obtained at 15 min after tritiated leucine injection to WT and

KO mice was used for ELISA of both proteins in the experiment after dilution by

1/2,000,000 (WT) or 1/1,000,000 [20] in a dilution buffer (50 mM Tris, 140 mM NaCl,

1% BSA, 0.05% Tween 20, pH 8.0).

Total protein concentrations of the plasma were estimated by the BCA assay

0.1% (Pierce) against bovine serum albumin standard solution (2 mg/mL; E280 = 0.667) by serial dilutions with Tris-buffered saline (pH 7.5).

3.2.3. Liver Protein Synthesis and the Steady-state Concentration of Hepatic Proteins

For liver protein synthesis, WT and KO mice were weighed and injected via the tail vein with the same amount (50 µCi/mouse) of radioactive leucine. At 30 min after the injection, mice were anesthetized and exsanguinated from the inferior vena cava.

Liver was excised quickly, washed one time with ice-cold phosphate-buffered saline to remove superficial blood, blotted, weighed, transferred to liquid nitrogen, and finally stored at -80°C. Special care was taken to reduce the time obtaining the liver. The time spent in collecting liver from exsanguinations to the actual last step was ~30 sec. Plasma was obtained by centrifugation and stored at -80°C.

Liver was homogenized with a tissue homogenizer (Polytron) in 4 volumes of ice- cold homogenization buffer containing 1.25% protease inhibitor cocktail (104 mM aminoethyl benzenesulfonyl fluoride hydrochloride, 80 µM aprotinin, 2 mM leupeptin, 4 mM bestatin, 1.5 mM pepstatin, 1.4 mM E-64; Sigma) dissolved in Tris-buffered saline

(50 mM Tris, 140 mM NaCl, pH 7.5). Two hundred microliters of 20% TCA was added to 200 µL of liver homogenate and the mixture was incubated for 10 min at 4°C to precipitate the liver proteins. This mixture was centrifuged at 12,000 rpm for 10 min at

4°C and the supernatant was discarded. Finally, the pellet was washed once with 200 µL of 10% TCA, and dissolved in 400 µL of 0.1 N NaOH overnight. Ecolite (14 mL) was added and the radioactivity was measured by LSC. The radioactivity of newly synthesized liver protein was measured by the trichloroacetic acid (TCA) precipitation method.

Total protein concentrations in liver homogenates were estimated by the BCA assay (Pierce) as described in section 3.2.2.

3.2.4. Measurement of Radiolabeled and Endogenous Steady-state Concentration of

Albumin and Transferrin in the Plasma

Steady-state plasma concentrations of biologically-radiolabeled albumin and transferrin in WT and KO mice were also determined by sodium dodecylsulfate polyacrylamide gel electrophoresis (SDS-PAGE). Tritiated leucine (250 µCi/mouse) was infused for 2-weeks via a subcutaneously implanted osmotic pump (100 µL size, Alzet) in WT and KO mice to establish near-to-steady-state concentration of biosynthetically- radiolabeled albumin and transferrin. Osmotic pumps were pre-equilibrated for 4 hr in

0.9% isotonic saline solution at 37°C to release leucine at a constant rate and implanted subcutaneously between the scapulae of mice by aseptic technique. Dosing solution and the pre-equilibrated solution were collected and stored at -80°C. Blood (~30 µL) was taken at day 7, 10, 11, 12, 13, and 14 from the retro-orbital plexus under light isoflurane anesthesia, and most of blood was obtained from the inferior vena cava at day 14.

Plasma was collected by centrifugation and liver was excised quickly. Plasma and liver samples were stored at -80°C. Osmotic pumps were recovered after the experiment and remaining leucine was collected. The pump was rinsed for 5 times with 0.9% isotonic saline solution, and combined with the remaining leucine. Aliquots of combined solution, dosing solution, and pre-equilibrated solution were subjected to LSC to check whether there was inadequate release of leucine over the experimental time. 95

Radioactivities of albumin and transferrin in the plasma were measured by SDS-PAGE followed by LSC and endogenous steady-state plasma concentrations of the proteins were determined by ELISA as described in the section 3.2.2. The radioactivity of newly synthesized liver protein was measured by the trichloroacetic acid (TCA) precipitation method as discussed in section 3.2.3. Radiolabeled albumin and transferrin concentrations were normalized to the same radioactive liver protein synthesis at day 14.

3.2.5. Measurement of SAP in the Plasma

SAP was measured by sandwich ELISA using goat antibody against mouse SAP

(Calbiochem) [98]. The specific procedure is described in chapter 2. Briefly, plasma collected at 15 and 90 min from WT and KO mice was diluted in a dilution buffer by two dilution factors (1/5,000 and 1/2,000) for both WT and KO plasma and subjected to SAP

ELISA.

3.2.6. Calculation of the Clearance Ratio between WT and KO Mice of Albumin and

Transferrin

Clearance was calculated by rearrangement of the mass balance equation:

CL = Rp / Css

Since Rp was a relative value in the absence of an absolute value for the precursor pool, which was identical and can be cancelled between the two strains (discussed in the

Results), the calculated CL was also a relative value that can be compared between the

two strains. The ratio of CL between WT and KO mice was considered to be FcRn- mediated protection of albumin. Transferrin CL was also compared as a control.

3.2.7. Statistical Analysis

The two-tailed Student’s t-test was applied to compare the protein concentrations and kinetic parameters between WT and KO mice. Differences between the two strains were considered statistically significant at P, a measure of probability that the difference between groups during the experiment happened by chance, less than 0.05. Data were presented as the average ± standard deviation (SD).

The ratios of steady-state plasma concentration of protein (albumin or transferrin) between WT and KO mice were assessed by the Bootstrap method [109, 110] to see whether there was a statistical difference between the two different methods (SDS-PAGE and ELISA). The Bootstrap procedure used a resampling with replacement technique to compare the ratio of the plasma steady-state concentrations of albumin or transferrin between WT and KO mice measured by SDS-PAGE and ELISA methods. Specifically, a ratio of plasma radiolabeled albumin concentration between WT and KO mice measured by SDS-PAGE was divided by a ratio of plasma endogenous albumin concentration between the two strains measured by ELISA, being a ratio of ratio (RR), which would be

1.0 if the two methods provide the same results. Based on the distribution of the RR, generated by a Bootstrap process that was repeated 4,000 times for each protein, the RR values for albumin and transferrin were outside their 95% confidence intervals for RR and were therefore considered to be significantly different from 1.0.

3.3. Results

3.3.1. Steady-state Plasma Concentration of Endogenous Albumin, Transferrin, and

Total Proteins

Endogenous plasma concentrations of albumin, transferrin, and total protein at steady-state in WT and KO mice are shown in Figure 3.1. The plasma albumin concentration was nearly twice as high in WT compared with KO mice (33.3 vs. 17.5 mg/mL). This difference has been observed consistently in previous experiments in our lab [17]. One alternative working hypothesis is that this nearly one-fold higher steady- state concentration of albumin is achieved by an FcRn-mediated albumin recycling mechanism [17]. We considered transferrin to be a negative control. Since transferrin did not show any significant difference between WT and KO mice (Mehnaz, unpublished data) in the terminal half-life after administration of radioiodinated transferrin, it was thought that transferrin would have an identical plasma concentration if the synthesis of transferrin was equal between the two strains. However, transferrin, which is not a substrate for FcRn but is another liver-derived plasma protein, showed a lower steady- state concentration by ~20% in WT compared with KO mice (8.47 vs. 10.2 mg/mL), suggesting that there could have been a general up-regulation of plasma protein synthesis in KO mice due to low oncotic pressure, mainly caused by the low albumin concentration. The total plasma protein concentration was higher by ~20% in WT compared with KO mice (58.6 vs. 48.3 mg/mL) whereas the albumin concentration was 98

almost one-fold higher in WT mice, suggesting that there may also be a compensatory up-regulation of biosynthesis of many plasma proteins.

3.3.2. Plasma SAP Level in WT and KO Mice

Serum amyloid P (SAP) concentration in the plasma is shown in Figure 3.2. The basal level of plasma SAP is generally < 25 µg/mL in the plasma of normal mice without any stimulation or treatment. Its level increases more than 10-fold and up to 100-fold upon stimulation [98, 111, 112]. There was a significant statistical difference in SAP level between WT and KO mice at both 15 min and 90 min after radioactive leucine, which is somewhat different from the observation that untreated WT and KO mice did not show a difference in basal SAP level (discussed in chapter 2). This may mean that radioactive leucine injection may have caused a slight acute-phase reaction, and this reaction may have been more pronounced in KO compared with WT mice. Nevertheless, it should be pointed out that the increases in SAP concentrations were still within the normal range (< 25 µg/mL) in both WT and KO mice [98], suggesting that there would be no significant acute-phase response. More importantly, there was no significant difference between the two time points (from 15 min to 90 min) either in WT or in KO mice, and SAP concentrations in WT and KO mice were still less than the reported basal level throughout the experimental time. This suggests that the possible acute-phase response that would consequently depress albumin synthesis was not significantly turned on over the 90 min time course. Moreover, the time frame of 90 min for the current production study is too early to induce any significant acute-phase reaction [113]. For 99

those two reasons, the acute-phase reaction should not have played a role in the current study, indicating that a comparison of albumin and transferrin synthesis between two strains would not be affected by the acute-phase reaction.

3.3.3. Albumin and Transferrin Production in WT and KO Mice

The appearance of newly synthesized albumin and transferrin in the plasma of

WT and KO mice after injection of radiolabeled leucine is shown in Figure 3.3 as measured by SDS-PAGE. At the early time points, 15 and 30 min, albumin and transferrin did not show any differences in the plasma appearances of the proteins whereas both proteins showed significant differences between the two strains beginning at 45 min after radioactive leucine injection, indicating that a greater production of both albumin and transferrin was seen in KO compared with WT mice. WT mice seemed to reach a plateau level in both albumin and transferrin production at 60 to 90 min whereas

KO mice still showed continuing appearance of albumin and transferrin in the plasma.

However, both proteins showed a plateau at 3 hours after injection of radioactive leucine in both WT and KO mice (not shown), and the ratio of albumin at 3 hr between the two strains was identical to the ratio at 90 min, both of which showed ~25% higher concentration in KO compared with WT mice. Transferrin showed the same kinetics and magnitude of increase in the ratio (~25%). Therefore, it is very likely that endogenous albumin and transferrin production rate in the absence of FcRn was increased by ~25% compared with the presence of FcRn.

100

Figure 3.4 shows radioactivity recovered by immunoprecipitation of albumin and transferrin at 90 min after tritiated leucine injection into WT and KO mice. The radioactivity of both proteins was also increased in KO compared with WT plasma at 90 min after administration of radiolabeled leucine. The radioactivity of albumin was higher in KO plasma (579 kdpm/mL) compared with WT plasma (494 kdpm/mL), showing a

17% increase in the albumin production in KO mice. Transferrin immunoprecipitation showed the same trend to that of SDS-PAGE; KO mice showed greater production of transferrin (67.4 vs. 58.7 kdpm/mL) compared with WT mice. The two methods did not give the same magnitude of production rate of albumin and transferrin. However, albumin and transferrin production rates were significantly increased in KO mice compared with WT mice by both methods. Therefore, two approaches using different separation principles (size and affinity) gave consistent results, minimizing the possibility that the differential protein production rate between the two strains was an artifact of the method of protein isolation.

3.3.4. Total Protein Synthesis and Protein Concentration in the Liver

Table 3.1 shows total liver protein synthesis and steady-state liver protein concentration in WT and KO mice 30 min after intravenous bolus injection of radiolabeled leucine. Total liver protein concentration showed no difference between two strains (230 vs. 225 mg/g liver), suggesting that livers of WT and KO mice are identical in terms of protein concentration. Since the blood retention is about ~25% in total wet liver [114, 115], the plasma contribution would be ~14% as the hematocrit of mice is

101

typically ~45% [116]. Therefore, although the greatest mass of plasma proteins is produced by the liver, the contribution of plasma protein concentration to the total liver protein concentration is minor (58.6 mg/mL vs. 230 mg/g liver in WT and 48.3 mg/mL vs. 225 mg/g liver in KO). Total liver protein synthesis was also not different between the two strains (1,167 vs. 1,168 kdpm/g liver) 30 min after tritiated leucine injection, which mainly excludes the possibility that radioactive leucine was differentially available in the liver between two strains. In other words, the precursor pool for albumin and transferrin synthesis was identical between the two strains. Therefore, it can be concluded that the increase in albumin and transferrin synthesis in KO compared with

WT mice is due to the enhancement of intrinsic synthesis, not due to an increased availability of the precursors.

3.3.5. Steady-state Plasma Concentration of Biosynthetically-labeled Albumin and

Transferrin

Figure 3.5 shows the steady-state plasma concentration of radiolabeled and endogenous albumin and transferrin during 14-days infusion of tritiated leucine. After day 11, both strains appeared to reach the steady-state plasma concentration of both radiolabeled proteins. The ratio of steady-state radiolabeled albumin concentration between WT and KO mice measured by SDS-PAGE was 1.52 at day 14, slightly lower than the ratio of endogenous albumin concentration (1.70) by ELISA method. The averaged concentration ratios between WT and KO mice of radiolabeled and endogenous albumin between WT and KO mice from day 11 to day 14 were 1.48 and 1.80,

102

respectively. Transferrin showed the almost identical WT/KO ratio of steady-state concentration between SDS-PAGE (0.87) and ELISA (0.89). These results suggest that the significant differences in the steady-state concentrations between WT and KO mice of albumin and transferrin measured by ELISA were also reproducibly observed by the other method, SDS-PAGE.

3.3.6. Turnover of Albumin and Transferrin and the Role of FcRn

Table 3.2 shows the ratio in the CL value between WT and KO mice calculated by two different methods of protein isolation. Both methods indicated the similar clearance values; approximately one-fold faster albumin clearance in the absence of

FcRn, suggesting a high capacity of FcRn-mediated recycling of albumin from degradation. Transferrin, a negative substrate for FcRn, did not show a difference in CL between the two stains.

3.4. Discussion

3.4.1. Previous Findings

Albumin has been well-studied for more than 50 years. Even though albumin biosynthesis and its physiological steady-state plasma concentration have been extensively studied, the degradation of albumin has by comparison been neglected. It is

103

known that albumin degradation is an apparent first-order process, and endothelial cells between the plasma and extravascular spaces are likely the main metabolic sites for albumin degradation [117]. Experiments with residualizing iodine labels, that are trapped in the lysosomes without considerable degradation, and later studies with the electron microscope supported the presumption from earlier studies that plasma proteins are degraded in endothelial cells by uptake into endocytic vesicles that fuse with lysosomes to form secondary lysosomes, where the degradation proceeds most rapidly at pH 5~5.5

[31, 118]. This conclusion was consistent with that of the kineticists who showed that albumin degradation “occurred in a compartment kinetically indistinguishable from the plasma” [117].

Since the radioactive protein dose was a trace amount and was assumed to behave as the endogenous molecule, the mass balance equation should apply for a particular endogenous steady-state concentration, even though albumin undergoes concentration- dependent catabolism (= nonlinear concentration-catabolism relationship). Using the mass balance equation, we estimated that the biosynthesis rate of albumin should be increased in WT mice by ~60% (4.04 vs. 2.36 mg/hr/25 g), compensating for the 20% decrease in the clearance, in agreement with the observed one-fold increase in the steady- state albumin concentration, which was one of the alternative working hypotheses. On the other hand, the lower steady-state concentration of albumin in KO mice causes the plasma to become hypoosmotic, which can provide a stimulus for protein synthesis in the liver, to increase the biosynthesis of albumin and other plasma proteins; this was considered to be an up-regulation, described in the second alternative working hypothesis.

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3.4.2. Production and the Steady-state Concentration of Albumin and Transferrin

3.4.2.1. Different Methods of Measurement Did Not Influence the Results.

We have shown that the production rates of both albumin and transferrin were increased in KO compared with WT mice. Before concluding that the synthesis of both proteins was up-regulated as supported by the alternative hypothesis, other possibilities that might create the above results were considered. It was possible that the method for protein isolation (SDS-PAGE) was not adequately quantitative to measure the radioactivities of albumin and transferrin. The SDS-PAGE method for quantification of labeled proteins was validated by testing its linearity and recovery (chapter 2), excluding the possibility that SDS-PAGE was inadequately quantitative.

Since two parts of the mass balance equation were measured by different methods, ELISA for Css and radioactivity for CL, we also tested whether the use of the different methods might generate altered values. To test this possibility, we employed immunoprecipitation using antibodies used in ELISA to bind native albumin and transferrin. As this is the same principle exploited in ELISA, both Css and Rp were measured by the same principle, namely, by antibodies. Immunoprecipitation also showed that the radioactivity of both albumin (17%) and transferrin (15%) at 90 min after radioactive leucine injection was significantly increased in KO compared with WT mice, just as when the ratio was calculated from the SDS-PAGE method (27% for albumin and

105

25% for transferrin). These results confirm that the increase in production rate of albumin and transferrin was not due to different methods of measurement.

Steady-state concentrations of biosynthetically-labeled albumin and transferrin after 14-days infusion of tritiated leucine in WT and KO mice showed results similar to those measured by ELISA. Statistical analysis showed that the ratio in albumin Css between the two strains measured by SDS-PAGE was significantly different from the ratio measured by ELISA (1.48 vs. 1.80). This means that two methods are not identical in terms of assay specificity and selectivity for albumin; transferrin did not show any differences between the two methods of measurement. However, both assays did show a significant increase in albumin production rate in KO compared with WT mice by 27%

(SDS-PAGE) and 17% (antibody). Therefore, while the absolute magnitude of albumin production and Css might be different between assays, the direction of increase is still the same: KO > WT. Moreover, the calculated CL based on the same measurement was approximately 100% faster in KO compared with WT mice (1.88 arbitrary units by SDS-

PAGE and 2.11 arbitrary units by the antibody-based method), suggesting that the different assays provided consistent estimations of CL. Table 3.2 summarized the ratio between WT and KO mice of production rate and the steady-state plasma concentration of albumin and transferrin.

Taken together, it is very likely that in the absence of FcRn production of albumin and transferrin was increased and the steady-state plasma concentration of albumin was greatly decreased whereas the Css of transferrin was increased, no matter which method of protein separation was applied.

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3.4.2.2. Disposition of Albumin and Transferrin Did Not Affect the Difference in the

Plasma Appearance of Labeled Proteins.

As the plasma appearance of biosynthetic proteins reflects their production and disposition (= distribution + degradation), whether strain differences in the disposition of albumin and transferrin caused a difference in the labeled protein appearance in the plasma was considered. The complete equation for the calculation of production rate of protein is expressed in Equation (3.2) [119, 120].

⎛ T ⎞ 60 ⎜CT + k Ct dt⎟ V1 ∫0 R = ⎝ ⎠ (Eq. 3.2) P T ⎛ * ⎞ n ⎜ L t dt ⎟ Lw ⎝ ∫0 ⎠

-1 -1 where RP (mg g liver h ) represents the production rate of proteins (albumin or transferrin), Ct (kdpm/mL plasma) represents the plasma concentration of labeled protein at time t, T (min) is the time at which the maximum concentration of labeled protein is achieved, k is the fractional rate of loss of protein (0.00167 min-1 in all animals) [121,

122], V1 is the initial distribution space of protein, approximately the plasma volume

(3.75 mL/100 g body weight), Lt* (kdpm/mg free hepatic leucine) is the hepatic concentration of labeled leucine over time t (min), n is mg leucine per mg albumin, Lw is liver weight (g/100 g body weight), and 60 is the conversion factor from minutes to hours. Liver weights are similar in WT and KO mice.

Assuming that the radioactive precursor pool shown in the denominator

(discussed in the following section) was the same in the two strains, the numerator describes the newly synthesized protein appearing in the plasma plus the protein that was

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lost during the experimental period. The disappearance rate constants of albumin and transferrin in both WT and KO mice were calculated from the albumin and transferrin disappearance curve after an intravenous bolus injection of biosynthetically labeled plasma, showing no considerable difference in the disappearance rate constants of albumin and transferrin between the two strains in the first 3 hr (unpublished data). The disappearance rate constants (0.00167 min-1) were in agreement with the known value as mentioned above. In the numerator, the plasma volume (V1) was identical between the two strains (Bronson, unpublished) and 60 is a constant. Therefore, the production rate is proportional to the sum of the labeled concentration of protein that had appeared in the plasma (CT) and the labeled concentration lost from the plasma (k⋅∫Ctdt). Based on

Equation (3.2), albumin Rp can be calculated as follows;

Rp = 757 kdpm/mL × 60 × V1 ÷ denominator in WT mice,

Rp = 958 kdpm/mL × 60 × V1 ÷ denominator in KO mice, and the ratio of Rp of WT to that of KO (WT/KO) = 0.790 = 79.0% assuming that the denominator is identical in the two strains. This ratio of Rp for albumin between the two strains is similar to the actual ratio of labeled concentration difference between the two strains at 90 min, 80.3%. Specifically, the magnitudes of CT term and integral part were

688 and 69 kdpm/mL, respectively, in WT mice, and the corresponding values in KO mice were 877 and 81 kdpm/mL. Consequently, the contribution of the protein by disposition was 69/688 (WT) and 81/877 [20], both of which were ≤ 10%. Transferrin showed the same pattern.

Therefore, the disposition of albumin or transferrin does not seem to play a role in the difference in the plasma appearance of newly synthesized labeled albumin and 108

transferrin, so this possibility is denied. In other words, the increase in the labeled albumin and transferrin in the plasma was not caused by strain differences in the disposition of the proteins.

3.4.2.3. Radioactive Precursor Pool Was Not Different Between Two Strains.

As for all proteins, albumin synthesis may be affected by a change in the precursor pool. The production rate (Rp) of a protein can simply be expressed as follows:

Rp = biosynthesis rate constant × [amount of precursor]

It had been assumed that labeled precursor would be available to the same extent in both strains; i.e., both strains received the same dose of radioactive precursor normalized to body weight (25 g). If the labeled precursor was identically available for biosynthesis of albumin and transferrin, Rp would be proportional to the extent of labeled protein appearing in the plasma over time. Therefore, we considered whether there was a preferential availability of precursor in the liver between the two strains due to a strain difference in the uptake of radioactive leucine or leucine metabolism. A strain difference in the availability of radioactive leucine would result in a similar strain difference in the amount of radioactive liver-derived plasma proteins in the plasma, such as albumin and transferrin, while the actual Rp would be unchanged. In our experimental system, where the relative biosynthesis rate between WT and KO mice was important, the precursor kinetics did not have to be fully characterized as long as the precursor was equally available to both strains. The concentration of amino acid in the plasma and the liver can be measured by either ion-exchange HPLC or reversed-phase HPLC after pre- or post-

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derivatization methods. However, the true precursor for protein synthesis is not the amino acid itself, but an aminoacyl-tRNA, the transfer RNA conjugated form of amino acid, which is even more difficult to characterize. Therefore, we decided to look for a more easily testable marker for the precursor-protein relationship. Since we were interested more in the relative biosynthesis rate between the two strains we looked for an easily measurable surrogate of precursor availability. As plasma albumin and transferrin are produced exclusively in the liver, liver total protein would share the same precursor with albumin and transferrin; thus, the magnitude of liver total protein synthesis would be a suitable surrogate marker for precursor availability for albumin and transferrin production. We found that at 30 min, the hepatic total protein synthesis was identical between the two strains (Table 3.1). However, it should be pointed out that albumin or transferrin production was also the same (at least, statistically not different) at that time point in the plasma between two strains (Figure 3.3). The significance of this is as follows.

First, the total liver protein concentration at steady-state was identical in the two strains (Table 3.1) while the plasma steady-state concentrations were different (Figure

3.1), indicating that liver protein synthesis was not up-regulated whereas the rate of production of both albumin and transferrin was increased in KO mice. Differential synthesis of albumin in the liver between the two strains is minor since the albumin synthesis in the liver is less than 10% of total liver protein synthesis at 30 min after administration of radioactive leucine in the rat [120, 123]. Therefore, liver protein synthesis can be a negative control for an up-regulation of plasma protein because the liver protein synthesis seems insensitive to the oncotic pressure. In contrast, transferrin is

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a negative control protein for an FcRn-dependent protein production but can be a positive control for the up-regulation of plasma protein in response to low osmotic pressure as reported elsewhere [108].

Secondly, in the rat, 16 min pass after initiation of labeled albumin synthesis before it appears in the plasma [123]; this is referred to as the minimum transit time

(MTT). The MTT for transferrin is approximately 30 min [120]. Considering the MTT of the proteins, the newly synthesized labeled albumin in the liver at 30 min would appear in the plasma at ~45 min, at which time KO mice showed the greater amount of albumin production compared with WT mice. Therefore, the 30-min data in the liver correspond to the data of 45-min for plasma albumin and that of 60-min for plasma transferrin both of which showed significant increase in their associated radioactivity in

KO compared with WT mice at those time points (Figure 3.3). However, the liver total protein synthesis was the same in the two strains, assuring that radiolabeled leucine was identically available at this time point and suggesting that there was no preferential precursor availability in the liver of either WT or KO mice in spite of the increase in the amount of albumin and transferrin production. Steady-state concentration of endogenous leucine was identical between WT and KO mice (not shown). This consideration rules out the possibility of differential hepatic availability of precursors between the two strains.

By this reasoning, it is unlikely that the liver of KO mice would utilize more radiolabeled leucine in producing albumin and transferrin; the increase in the production rate of albumin and transferrin in KO mice is caused neither by preferential hepatic uptake nor increased hepatic availability of radioactive precursors.

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3.4.2.4. Acute-phase Response Did Not Affect the Production.

The acute-phase response inhibits the synthesis of both albumin and transferrin.

To test whether this inhibitory reaction takes place differentially between the two strains, we measured during the experiment the positive marker for the acute-phase response, the plasma level of SAP. No change in SAP concentration at 15 and 90 min was found

(Figure 3.2), eliminating the possibility that the acute-phase response played a significant negative role in the production experiment and supporting the conclusion that the difference in the plasma albumin and transferrin radioactivity between the two strains was not caused by a differential influence of the acute-phase reaction.

3.4.2.5. Up-regulation of Albumin Production in KO Mice Remains.

After excluding all other possibilities above, only one possibility seems to remain, and that is intrinsic production of albumin and transferrin in the liver is increased in KO mice, probably to compensate for the hypoosmotic pressure of the plasma.

Overall, the null hypothesis, that the livers of both strains produce albumin equivalently, was discarded by showing significant differences in the rates of production.

One of the alternative hypotheses, that FcRn is involved in the production, was also rejected by observing the opposite prediction and by the simultaneously increased production rates of albumin (an FcRn substrate) and transferrin (a non-substrate for

FcRn) in the absence of FcRn. The remaining alternative hypothesis, that hypoosmotic

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conditions stimulate the rates of production of both albumin and transferrin was supported based on the results herein.

3.4.3. Albumin Turnover and the Role of FcRn: Recycling

The result showing that both proteins were produced at greater rate in KO mice by

~20% compared with WT mice lead us to realize that we might have overestimated the albumin clearance in WT mice or underestimated the albumin clearance in KO mice, whereas that of transferrin was accurately estimated; both steady-state concentration and production rate of transferrin were increased by 20% in KO mice while there was no apparent difference in the degradation, satisfying well the mass balance equation. The failure to estimate the biosynthesis of albumin raised the question whether radioiodinated albumin was truly behaving like endogenous albumin. Since the leucine-based biosynthesis approach incorporates amino acids into the nascent protein, there is no doubt that labeled synthesized albumin is identical to endogenous albumin except for 3H in place of 1H; thus, the production rates are credible. Then, the clearance difference between the two strains based on radioiodinated albumin (20% lower in WT compared with KO mice) may not represent the true ratio of albumin clearance. Table 3.2 lists the calculated CL values for albumin and transferrin and the contribution of FcRn in albumin recycling from its degradation. Applying our observation that the KO mice showed 22%

(averaged value between SDS-PAGE and immunoprecipitation; 17~27%) greater production of albumin but only 62% (56~67%) of the concentration of albumin at steady- state, compared with WT, we can estimate the clearance ratio between KO and WT as a

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value of 2.0 (1.88~2.11; CL = Rp/Css). This means that an animal expressing FcRn saves 100% as many moles of albumin than an animal deficient in FcRn, per unit time.

In terms of amount per unit time, WT mice produce 100 molecules of albumin from the liver, while degrading the same 100 molecules and recycling 100 additional molecules by

FcRn; while KO mice produce and degrade 122 molecules, saving none by FcRn. This amount of albumin loss in hypoalbuminemic KO mice is considerable. To compensate for this large loss of albumin, KO mice should be able to produce more albumin and other plasma proteins; otherwise they would suffer hypoosmotic shock and associated diseases. It seems that KO mice solve this problem by simply making more plasma proteins, including albumin and transferrin. Recycling the albumin may have a significant homeostatic meaning; albumin recycling could be more economical than manufacturing albumin in terms of energy expenditure of biochemistry.

According to this interpretation, FcRn seems to be a recycler for albumin and

IgG, the two major plasma proteins in the body. Over the course of evolution, the body might have developed this machinery to maintain high plasma concentrations for them to serve their important roles in survival. For example, albumin acts as an oncotic pressure mediator and transporter of numerous molecules while IgG is the major class of protective antibody. Moreover, the existence of FcRn might also reduce the biosynthesis burden of the liver (albumin) and the immune cells (IgG), by simply recycling the proteins, meeting the demands for large amounts of the proteins to maintain high plasma steady-state concentrations.

Based upon the data and interpretation described above, we now propose the albumin turnover model shown in Figure 3.6. In this context, for a better understanding

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of protein turnover, synthesis and production have different meanings: synthesis is the protein biosynthesis that takes place in the hepatocytes after protein translation whereas production refers to the actual secretion of newly biosynthesized protein from hepatocytes into the plasma (described in chapter 1). Therefore, production has two steps: biosynthesis plus secretion. Albumin and transferrin are synthesized (A and B,

Figure 3.6) from amino acid pools in the liver and secreted (C and D) into the circulating plasma. It is postulated that there could be hypothetical ‘presecretory’ degradation (K and L) before secretion during which FcRn may play a role in saving albumin from its presecretory degradation (shown in dotted, curved open arrow) whereas transferrin, not a substrate, is not saved by FcRn. Hypothetical fluxes are shown as dotted arrows.

Although this recycling from the hypothetical presecretory degradation may not play a significant role since KO mice produced more albumin by ~20% compared with WT mice, it is still possible that the ratio of the amount of hepatic albumin synthesis in KO mice to the amount of albumin secretion into the plasma is greater than the synthesized vs. secreted amounts of albumin in WT mice; the difference between synthesis and secretion of albumin could be the amount of presecretory degradation. Further study is warranted for this prediction.

Secreted albumin and transferrin distribute into the extravascular space (E and F).

Both compartments can be the sites for protein degradation (G, I, H, and J) where FcRn can recycle only albumin (curved open arrows) even though WT mice may have negligible extravascular degradation of albumin with relatively large extravascular availability of FcRn. FcRn can facilitate transendothelial flux from plasma to extravascular space as shown with the open arrow [Bronson, unpublished]. Hatched

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arrows indicate the observed up-regulation of albumin and transferrin synthesis in the absence of FcRn which is not necessary in the presence of the receptor.

We illustrate the magnitude of the influence of FcRn on albumin recycling with the following calculation; as mentioned earlier, 100 molecules would be recycled by

FcRn while 100 molecules are produced and degraded per unit time in WT mice. This would mean that an FcRn-dependent protection mechanism recycles as much albumin as is made in the liver; the same is recycled as produced. FcRn functions as if it were another liver, as big as the normal liver. Considering the weight of the human liver ~1.8 kg/70 kg man [116], a body has to have additional liver as big as ~1.8 kg/70 kg to maintain normal level (~40 mg/mL) of albumin in the absence of FcRn.

3.4.4. Summary and Implications

In summary, we found no augmenting effect of FcRn on albumin biosynthesis and also found that the difference in albumin clearance between WT and KO mice was larger than what was previously reported using radioiodinated albumin decay. This is an important finding for the following two reasons;

1) The presence of FcRn saved albumin from degradation yielding a clearance of

one-half (50% = 1.0/2.0) of the clearance without receptor.

2) The normal physiological plasma concentration of albumin (~40 mg/mL = 600

µM) does not saturate FcRn, implying the large capacity of FcRn-mediated

recycling.

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3.5. Conclusion

Albumin production was increased in FcRn-deficient mice by 20% compared with

WT mice. Transferrin, a non-substrate for FcRn, also showed a 20% increase in its production in KO mice. Rates of liver protein synthesis were identical between the two strains, which assumes that the precursor pool for the liver-derived protein synthesis is the same. Taken together, FcRn expression was not directly involved in the production of albumin. The lower albumin plasma concentration in KO mice was caused by the lack of an FcRn-mediated mechanism of protection of albumin from degradation. The increase in albumin and transferrin production in KO compared with WT mice was probably due to a compensatory mechanism in response to the lower plasma oncotic pressure that mainly derived from the lower albumin concentration. A 20% increase in the steady-state concentration of transferrin in KO mice was attributed to a 20% increase in the production rate while there was no significant difference in the degradation rate between the two strains. A nearly 50% lower concentration of plasma albumin was maintained in KO mice along with a 20% increase in albumin production, suggesting that there was a 100% increase in albumin degradation in the absence of FcRn.

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3.6. Acknowledgment

I thank Dr. Michael D. Radmacher in the Center for Biostatistics of The Ohio

State University for his statistical approach using the Bootstrap method. I also appreciate his helpful comments on the statistical analysis and interpretation of the data.

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P < 0.001 P < 0.001 P < 0.001 70

Plasma concentration (mg/mL) 10

0 Albumin Transferrin Total Protein

Figure 3.1: Plasma steady-state concentration of albumin, transferrin, and total plasma protein in WT (empty bars) and KO (hatched bars) mice. Endogenous levels of albumin and transferrin in the plasma were measured by an ELISA method using goat polyclonal antibodies against mouse serum albumin and mouse transferrin. The concentration of total endogenous plasma protein was estimated by the bicinchoninic acid (BCA) method. P values, a measure of probability that the difference between groups during the experiment happened by chance, show the statistical difference between strains by Student’s t-test. T represents one standard deviation (SD), with seven mice in each group.

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P < 0.05 P < 0.05

8 g/mL)

Plasma concentration (

15 min 90 min

Figure 3.2: Plasma concentration of SAP at 15 and 90 min after administration of radiolabeled leucine in WT (empty bars) and KO (hatched bars) mice. Note that the absence of change between two time points in a given strain indicates the absence of an acute-phase response. SAP in the plasma was measured by an ELISA method using goat polyclonal antibodies against mouse serum SAP. P values show the statistical difference between strains from Student’s t-test. T represents one SD. Seven mice were in each group.

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(A) (B)

1000 150 *** *** ** 800 120 * *

600 90 **

400 60

200 30

Plasma concentration (kdpm/mL) 0 0 0306090 0306090

Time (min)

Figure 3.3: Plasma appearance of labeled albumin (A; circle) and transferrin (B; triangle) after injection of tritiated leucine in WT (open) and KO (filled) mice. Plasma collected at the indicated times was subject to SDS-polyacrylamide gel electrophoresis (SDS-PAGE) for the separation of albumin and transferrin. Excised protein bands were digested by tissue solubilizer and the radioactivities of bands were measured by LSC. Plasma concentrations of albumin and transferrin were normalized to the radioactive dose per body weight (50 µCi/25 g). Significant statistical differences between two strains were designated with * (p < 0.05), ** (p < 0.01), and *** (p < 0.001). I represents ± one SD. Seven mice were in each group.

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P < 0.05 P < 0.05 750 80

600 60

450

40 300

20 150

Plasma concentration (kdpm/mL) 0 0

MSA TF

Figure 3.4: Radioactivity of albumin and transferrin in the plasma from WT (empty bars) and KO (hatched bars) mice at 90 min after injection of tritiated leucine. Plasma collected at 90 min was subject to immunoprecipitation using anti-MSA antibody (for MSA) or anti-TF-antibody (for TF) attached to Protein G-Sepharose beads for the separation of albumin and transferrin. Bound mixtures were digested by tissue solubilizer and the radioactivities were measured by LSC. P values show the statistical difference between strains from Student’s t-test. T represents one SD. Seven mice were in each group.

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(A)

1000

100

(kdpm/mL)

Plasma Concentration 10

6 8 10 12 14

(B)

100

(mg/mL)

Plasma Concentration 1 6 8 10 12 14

Time (day)

Figure 3.5: Average steady-state plasma concentration of albumin and transferrin of WT (n = 7) and KO (n = 10) mice determined either by SDS-PAGE or by ELISA method during 14-days infusion of radiolabeled leucine via an osmotic pump. (A): Radioactivity of albumin (circle) and transferrin (triangle) of WT (open) and KO (filled) mice in the plasma. The steady-state concentrations of radiolabeled MSA and TF were considered to be achieved at day 11 through 14. (B): Endogenous plasma concentration of albumin and transferrin of WT and KO mice. I represents ± one SD.

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Amino Acids

(A) (B) Liver

(K) Albumin Transferrin (L)

Plasma (G) Albumin Transferrin (I)

(E) (F)

Extravascular (H) Albumin Transferrin (J) space

Figure 3.6: Proposed model for the biosynthesis and the production of albumin and transferrin with possible involvement of FcRn during albumin turnover. Biosynthesis (A and B) is different from production (C and D), which is a composite of biosynthesis and secretion and was measured in the current study.

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WT (n = 7) KO (n = 7)

Total liver protein 230 ± 9.19 225 ± 7.33 concentration (mg/g liver)

Total liver protein 1,167 ± 123 1,168 ± 205 synthesis (kdpm/g liver)

Table 3.1: Total endogenous protein concentration in the liver and total liver protein synthesis in WT and KO mice. Liver was excised and quickly frozen 30 min after injection of tritiated leucine, then homogenized. Endogenous protein concentration of liver homogenate was measured by BCA method. Total liver protein synthesis was calculated after TCA precipitation of the liver homogenates followed by LSC. Average values ± SD are expressed of seven mice in each group.

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Units WT KO KO/WT

Rp U1 757 958 1.27

PAGE Css kdpm/mL 323 218 0.675

CL 2.34 4.39 1.88 Albumin Rp U2 543 636 1.17

Antibody Css mg/mL 38.5 21.4 0.556

CL 14.1 29.7 2.11

Rp U3 106 132 1.25

PAGE Css kdpm/mL 48.5 55.8 1.15

CL 2.19 2.37 1.08 Transferrin Rp U4 64.5 74.1 1.15

Antibody Css mg/mL 9.86 11.0 1.11

CL 6.54 6.74 1.03

Table 3.2: Estimation of CL based on the mass balance equation with known Css and Rp values determined by different methods (SDS-PAGE and antibody-based method). Rp divided by Css is the calculated CL values. Note that Rp was computed by the appearance of radiolabeled protein up to 90 min plus correction by plasma disappearance (C90 min + k⋅∫Ctdt) by equation 3.2 during the time after intravenous bolus injection of radiolabeled leucine as all other parts are identical between the two strains, whereas Css was determined during 14-days subcutaneous infusion of labeled leucine. Since Rp was measured as a ratio between WT and KO mice, arbitrary units (U1, U2, U3, and U4) are given for Rp. Hence, CL would be appreciated as a relative value between the two strains, rather than an absolute value. The clearance ratio (KO/WT) indicates the contribution of FcRn in the CL, a parameter for degradation of a protein.

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CHAPTER 4

RECEPTOR-MEDIATED PRODUCTION OF PROTEIN:

PHARMACOKINETIC/PHARMACODYNAMIC MODELING OF

ESTROGEN-INDUCED VITELLOGENIN EXPRESSION

4.1. Background

4.1.1. Outline

The glycoprotein vitellogenin (Vg) is synthesized in the liver of female oviparous vertebrates [124], secreted into the blood circulation, sequestered by the growing oocyte, and cleaved to yield the main egg yolk proteins [125]. While the Vg gene is also present in male fish, it is negligibly expressed, probably due to a low concentration of estrogens in the blood [125]. However, exposure of male fish to estrogenic substances such as estradiol or ethynylestradiol causes a significant increase in the expression of mRNA for

Vg and the production in the liver of male trout of Vg protein which is secreted into the

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plasma. These features have made the presence of vitellogenin in males a sensitive and specific biomarker for the evaluation of environmental exposure to estrogenic substances.

Furthermore, that male fish can produce Vg after exposure to estrogens has made this a sentinel for assessing the exposure of organisms to environmental estrogenic compounds in the aquatic environment. These features of Vg production also make male trout an excellent animal model for the development of quantitative pharmacokinetic/pharmacodynamic (PK/PD) models of ligand/receptor-initiated and gene-mediated protein biosynthesis.

The recent characterization of the pharmacokinetics of the synthetic estrogen ethynylestradiol (EE2) and its rapid induction of Vg synthesis in male rainbow trout [74] have permitted the development of an indirect-response-type of PK/PD model of receptor-mediated stimulation of protein biosynthesis [20]. The model is based on the normal biology of the estrogen signaling system, and key intermediate steps and molecules in the signaling pathway are included in the model; i.e., the estrogen receptor, mRNA for the estrogen receptor, and mRNA for the vitellogenin protein. The model, described in this chapter, will be a useful tool for exploration of mechanisms related to estrogen-dependent signaling, including estrogen receptor antagonists, modulators of down-stream signaling pathways, and so forth. It is also helpful for quantification of the relationship between Vg and estrogenic responses.

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4.1.2. PK/PD Model for Estrogen-Vg System

The unnatural expression of Vg in male trout is regulated by hepatic estrogen receptors. Estrogen receptor activation triggers the expression of Vg mRNA and subsequent synthesis of the Vg protein. The concentrations of key intermediates in this signaling system were determined and used to mathematically describe Vg levels in plasma that result from estrogen exposure. An indirect response model was selected as it permitted inclusion of the key biological events in the Vg response; i.e., binding of estrogen to its receptor and expression of mRNA for Vg. These modeling details are important for understanding the time lag between estrogen exposure and Vg appearance in plasma. The model also permits quantitative characterization of the up-regulation of the receptor in the presence of estrogen. Up-regulation will likely be very important in understanding Vg production during chronic estrogen exposure. Given the inherent nonlinearities in the estrogen-Vg system, it is unlikely that a less detailed modeling strategy could successfully mimic the acute and chronic dose-response relationships. A further advantage of the biologically based modeling approach is its utility beyond the experimental system upon which it is based.

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4.1.3. Pharmacodynamic Advantages in the Study of EE2-Vg System

The EE2-Vg relationship has five advantages for studying the pharmacodynamics of receptor-mediated gene induction systems. First, this system utilizes conventional ligand-receptor binding followed by particular gene expression and regulation of protein synthesis. Second, the induced gene product (Vg protein) can be sampled repetitively from the blood circulation of individual animals since it is readily secreted from the liver into the plasma. In contrast, organ- or tissue-specific proteins have to be collected once per animal, which requires a ‘giant’ animal study plan that involves sacrifice of animals at several time points. Third, exposure to estrogenic compounds induces large amounts of gene products in the male fish, which normally lack Vg gene expression and, which makes Vg a good biomarker for environmental contamination of aquatic environment by xeno-estrogens. Vg levels in male trout plasma are normally negligible (< limit of detection, 6 ng/mL) while levels in estrogen exposed fish can be as high as 2.4 mg/mL

[74]). Fourth, the male rainbow trout is an excellent animal model for both evaluation of environmental estrogenicity in conjunction with biomonitoring of Vg in fish and the development of a PK/PD model for ligand-induced receptor-mediated gene expression with protein regulation. Finally, a fish animal model can use continuous water exposure rather than a constant-rate intravenous (i.v.) infusion for achievement of steady-state estrogen exposure. Water exposures can be stably maintained for months if necessary, to allow all measured variables to reach their steady-state levels. EE2 is rapidly absorbed from the water by trout, with plasma equilibrium concentrations reached within 24 hours; stable plasma concentrations have been maintained for at least 60 days. Therefore, one

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can utilize this feature of fish to measure the rise to steady-state of model variables and their change when the exposure rate is adjusted by a factor of 10 upwards and downwards.

We have chosen 17-α-ethynylestradiol (EE2) as our model xeno-estrogen for development of the PK/PD model. EE2 is a synthetic estrogen used in oral contraceptives and is known to occur in surface waters via municipal sewage discharges

[86, 126]. EE2 is more potent than natural estradiol (E2) in stimulating Vg synthesis in trout. However, a similar set of genes is induced in the fish liver by both EE2 and E2 treatments [82]. The metabolism of EE2 is qualitatively similar in trout and mammals in that extensive conjugation to glucuronide occurs [74, 127]. Recently, EE2 (along with

E2) has been implicated as the primary contaminant contributing to the estrogenic activity in surface waters from both the U.K. and U.S.A. [128, 129]. In lengthy exposure experiments, an important advantage of EE2 over E2 is its greater stability [130]. Thus, for PK/PD model development, EE2 offers the advantage of being a potent inducer of

Vg, while it is also relatively easy to maintain stable water concentrations over an extended time.

4.1.4. Objectives of the Study

In this chapter, we report the development of an integrated PK/PD model patterned after a glucocorticoid pharmacodynamic model [6], which was modified to quantitatively describe the synthesis of vitellogenin, its secretion into blood, and its

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subsequent elimination from male rainbow trout. During continuous EE2 exposure, the concentration-time profiles of EE2 and the Vg protein in both blood plasma and liver tissues were characterized. We also characterized the positive influence of estrogen receptor Rα on the mRNA of both receptor and Vg. Thus, an integrative PK/PD model based on an estrogen-induced, receptor-mediated, gene-induction mechanism was developed to predict the induction of Vg protein in male rainbow trout.

4.2. Model development

4.2.1. Model Diagram

A schematic representation of the pharmacokinetic/pharmacodynamic model for receptor-mediated gene induction and Vg production is presented in Figure 4.1.

4.2.2. Abbreviations and Parameters with Units

E0 17-α-Ethynylestradiol (EE2) concentration in exposure water (ng/L)

E1 EE2 concentration in central compartment including plasma (ng/mL)

E2 EE2 concentration in peripheral compartment (ng/mL)

EL unbound EE2 concentration in the liver (ng/g liver)

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mR liver concentration of messenger RNA (mRNA) for estrogen receptor (pg

mRNA/µg total RNA)

R unbound concentration of estrogen receptor in the liver (fmol/g liver).

ER liver concentration of EE2-estrogen receptor complex (fmol/g liver).

This is a bound receptor concentration in the liver which is not bound to

estrogen receptor response element (ERE) of DNA promoter region.

ERN liver concentration of EE2-estrogen receptor complex bound to ERE

which will activate transcription of mR and mVg (fmol/g liver) mVg liver concentration of messenger RNA (mRNA) for vitellogenin (pg

mRNA/µg total RNA)

VgL liver concentration of vitellogenin (µg/g liver)

Vg1 vitellogenin concentration in central compartment (µg/mL)

Vg2 vitellogenin concentration in shallow peripheral compartment (µg/mL)

Vg3 vitellogenin concentration in deep peripheral compartment (µg/mL)

CLE total body clearance of EE2 (mL/hr/kg)

CL12,E intercompartmental clearance of EE2 between central and peripheral

compartment (mL/hr/kg body weight)

CL1H intercompartmental clearance of EE2 between central compartment and

the liver (mL/hr/kg)

CLvg total body clearance of vitellogenin (mL/hr/kg)

CL12,vg intercompartmental clearance of vitellogenin between central and shallow

peripheral compartment (mL/hr/kg body weight)

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CL13,vg intercompartmental clearance of vitellogenin between central and deep

peripheral compartment (mL/hr/kg body weight)

Vwt volume of water tank containing EE2 (L)

V1,E volume of distribution of EE2 in central compartment (mL/kg)

V2,E volume of distribution of EE2 in peripheral compartment (mL/kg)

V1,vg volume of distribution of vitellogenin in central compartment (mL/kg)

V2,vg volume of distribution of vitellogenin in shallow peripheral compartment

(mL/kg)

V3,vg volume of distribution of vitellogenin in deep peripheral compartment

(mL/kg)

VH liver weight of rainbow trout (g/kg)

-1 k0 uptake rate constant of EE2 (hr ) ks,mr synthesis rate constant of mR (pg mRNA/hr/µg total RNA)

-1 ke,mr elimination rate constant of mR (hr ) ks,r synthesis rate constant of R (fmol/hr/g liver)

-1 ke,r, elimination rate constant of R (hr ) kon association rate constant of binding between EE2 and R (g liver/ng/hr)

-1 koff dissociation rate constant of binding between EE2 and R (hr ) k'on association rate constant of EE2-R complex into the ERE (g liver/fmol/hr);

two receptors are dimerized and bind to ERE.

-1 k'off dissociation rate constant of EE2-R from the ERE (hr )

-1 kdeg degradation rate constant of ERE-bound EE2-R (hr )

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Smr maximal stimulation effect by ERN to increase R mRNA synthesis

(unitless)

Kmr liver concentration of ERN that shows half-maximal effect of mR

synthesis (fmol/g liver)

Imr liver concentration of ERN that shows half-maximal inhibition of mR

elimination (fmol/g liver)

Smvg maximal stimulation effect by ERN to increase Vg mRNA synthesis (g

liver/fmol)

Imvg hepatic concentration of ERN that shows half-maximal inhibition of mVg

elimination (fmol/g liver) ks,mvg synthesis rate constant of mVg (pg mRNA/hr/µg total RNA)

-1 ke,mvg elimination rate constant of mVg (hr ) ks,vg synthesis rate constant of Vg (fmol/hr/g liver)

γ exponent term for the amplification of the synthesis for Vg protein

-1 ksec secretion rate constant of Vg into central compartment (hr )

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4.2.3. Initial Conditions

E0(0) = 100 ng/L

E1(0) = E2(0) = EL(0) = 0 ng/mL mR(0) = 0.4275 pg mRNA/µg total RNA

R(0) = 10.4 fmol/g liver

ER(0) = ERN(0) = 0 fmol/g liver mVg(0) = 0.001 fg mRNA/µg total RNA (arbitrary value and unit)

VgL(0) = 0.1 µg/g liver

Vg1(0) = Vg2(0) = Vg3(0) = 0.009 µg/ml

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4.2.4. Model Equations

dE k ⋅ E ⋅V + CL ⋅ E − (CL + CL )⋅ E − k ⋅ E ⋅ R + k ⋅ ER 1 = 0 0 wt 12,E 2 E 12,E 1 on 1 off dt V1,E dE CL ⋅ E − CL ⋅ E 2 = 12,E 1 12,E 2 dt V2,E dE CL ⋅ ()E − E L = 1H ,E 1 L dt VH dmR ⎛ S ⋅ ERN ⎞ ⎛ I ⎞ ⎜ mr ⎟ ⎜ mr ⎟ = ks,mr ⋅⎜1+ ⎟ − ke,mr ⋅ mR ⋅⎜ ⎟ dt ⎝ Kmr + ERN ⎠ ⎝ Imr + ERN ⎠ dR = k ⋅ mR − k ⋅ R − k ⋅ E ⋅ R + k ⋅ ER dt s,r e,r on L off dER = k ⋅ E ⋅ R − ()k + k' ⋅ ER + k' ⋅ERN dt on L off on off dERN = k' ⋅ER − ()k' +k ⋅ ERN dt on off deg dmVg ⎛ I ⎞ = k ⋅ 1+ S ⋅ ERN − k ⋅ mVg ⋅⎜ mvg ⎟ s,mvg ()mvg e,mvg ⎜ ⎟ dt ⎝ Imvg + ERN ⎠ dVg L = k ⋅ ()mVg γ − k ⋅Vg dt s,vg sec L dVg k ⋅Vg ⋅V + CL ⋅Vg + CL ⋅Vg − ()CL + CL + CL ⋅Vg 1 = sec L H 12,vg 2 13,vg 3 12,vg 13,vg vg 1 dt V1,vg dVg CL ⋅Vg − CL ⋅Vg 2 = 12,vg 1 12,vg 2 dt V2,vg dVg CL ⋅Vg − CL ⋅Vg 3 = 13,vg 1 13,vg 3 dt V3,vg

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4.2.5. Model Development

4.2.5.1. Characterization of EE2 in the Plasma and the Liver

The PK/PD model was initiated by the characterization of EE2. Male rainbow trout were exposed to a constant concentration of 100 ng/L of EE2 in the water for 90 days [Schultz, unpublished data]. Five individual trout were fitted with an intra-arterial cannula and placed in the 1200 L exposure water tank. Each trout was placed in a 120 L floating cage that had been perforated to allow water exchange with the exposure tank.

The exposure water was prepared using a concentrated stock solution of EE2, dissolved in methanol, that was slowly added to the exposure tanks using a peristaltic pump.

Control tanks had methanol only added and no EE2 or Vg was observed in control fish.

All exposure tanks were allowed to equilibrate with the EE2 dosing system for 14 days prior to the addition of trout. EE2 concentrations were monitored every 7-14 days during the exposures to quantify actual levels. The measured mean concentration was 131 ± 23 ng/L in the water tank [Schultz, unpublished data]. At this exposure rate, plasma concentrations of EE2 closely approached the 90 days equilibrium level within 16 hrs of the exposure. The concentration ratio between EE2 in plasma and exposure water was approximately 634 : 1, reflective of high plasma protein binding. Binding would exceed

99% to account for this ratio, consistent with 97~98% binding of EE2 to plasma albumin

[131]. Chemicals with these characteristics are typically rapidly absorbed across the gills in a ventilation-volume limited manner [132]; thus, EE2 absorption was assumed to be a zero-order input.

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By two-compartmental analysis with zero-order input (Winnonlin 4.0, Pharsight), the EE2 plasma concentration-time profile was mathematically addressed as follows:

−α⋅t −β ⋅t E1 = ()A + B − (A⋅ e + B ⋅ e ) (Eq. 4.1)

The concentration of EE2 in the liver was described by its hepatic uptake and redistribution to the plasma. The measured hepatic EE2 concentration consisted of the free hepatic EE2 concentration plus the tissue bound EE2 concentration, which included

EE2 bound to estrogen receptor. Since the total body clearance of EE2 in the rainbow trout is 13.0 mL/hr/kg [74] and the hepatic blood flow is 60.0 mL/hr/kg [133], EE2 is a low hepatic extraction compound. Then, it can be assumed that the free plasma EE2 concentration is the same as the free hepatic EE2 concentration which will bind to the estrogen receptor to show a pharmacodynamic effect.

4.2.5.2. Receptor Binding

Free hepatic EE2 (EL; ng/g liver) was assumed to bind to its unbound nuclear estrogen receptor (R; fmol/g liver) according to a simple Emax binding model:

kon

EL + R ER koff

E ⋅ R Kd = L (Eq. 4.2) ER

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ER ⋅ E ER = max L (Eq. 4.3) Kd + EL

where ERmax (fmol/g liver) is the total (maximal) concentration of bound receptor (bound and unbound) and Kd (ng/g liver), the dissociation constant that equals the concentration of E that half saturates the receptor population. Bound ER complex (fmol/g liver) is known to form a homodimer or ER complex; other configurations are also known such as a heterodimer of ER/R and even a homodimer of free receptors [134]. Several molecules are involved in the binding of the ER complex to the estrogen response element of the

DNA (ERE) [78, 135]. In the present model, we assumed that only ER homodimers can bind to ERE as this configuration is known with certainty while the others are debatable observations [136].

In comparative studies, the estrogen-binding domain of the receptor of rainbow trout displayed only a 60% homology with the human receptor [137]. However, it was reported that the key amino acid residues and sequences are conserved in the estrogen- binding domains of the receptors from 13 different vertebrates including fish to mammals, implying similar binding characteristics [138]. Based on the binding study between purified human activated estrogen receptor (Rα) and the ERE region, the

-2 -1 dissociation rate constant of ER dimer to ERE (k’off) was measured to be 1.48 × 10 sec

-1 6 -1 = 53.3 hr whereas the association rate constant (k’on) was calculated as 7.0 × 10 M sec-1 = 25.2 nM-1 hr-1 = 25.2 g liver/pmol/hr using Kd = 2 nM [134]. This suggests that the binding of activated ER complex to the ERE was much faster than the binding of EE2

-1 to receptor (0.826 g liver/ng/hr as kon and 0.347 hr as koff; discussed in the Results and

140

Discussion section), so that ER may represent the concentration of activated ER complex in the nucleus. Therefore, activated bound ER in this model is assumed to represent ER complex bound to ERE (= ERN; fmol/g liver).

4.2.5.3. Auto-up-regulation of Estrogen Receptor

To characterize the binding of EE2 to R, an association rate constant (kon; g

-1 liver/fmol/hr) and a dissociation rate constant (koff; hr ) were used, rather than an equilibrium constant (Kd); these constants are available in the literature (discussed in the

Results and Discussion section). The local representation of receptor-mediated up- regulation of mRNA for receptor is shown in Figure 4.2, and model-based differential equations were derived:

dR = k ⋅ mR − k ⋅ R − k ⋅ E ⋅ R + k ⋅ ER (Eq. 4.4) dt s,r e,r on L off dER = k ⋅ E ⋅ R − k ⋅ ER − k ⋅ ER (Eq. 4.5) dt on L off deg dmR ⎛ S ⋅ ER ⎞ ⎛ I ⎞ ⎜ mr ⎟ ⎜ mr ⎟ = k s,mr ⋅⎜1+ ⎟ − ke,mr ⋅ mR ⋅⎜ ⎟ (Eq. 4.6) dt ⎝ K mr + ER ⎠ ⎝ I mr + ER ⎠

The receptor is synthesized at a rate controlled by its first-order synthesis rate

-1 -1 constant (ks,r; (pg/µg total RNA) hr ) from its mRNA and its degradation follows first-

-1 order kinetics controlled by the elimination rate constant (ke,r; hr ). After binding to EE2 in the nucleus, the ER complex is degraded at a rate controlled by its first-order 141

-1 degradation rate constant (kdeg; hr ). A fifth-generation model for glucocorticoid- receptor PK/PD [6] was adapted in the present model to introduce indirect-response-type dynamics. While the glucocorticoid receptor down-regulates its mRNA, estrogen receptor, in contrast, induces its own synthesis. To account for receptor up-regulation, a positive feedback loop was introduced in the present model. As has been demonstrated for estradiol in cultured trout hepatocytes [83], two positive feedback mechanisms were used in our model. First, the ER complex increases the half-life of mRNA for R (e.g. mRNA stabilization) by an indirect-response-type inhibition model with the level of inhibition set by the ER concentration that produces half maximal inhibitory feedback

(Imr; fmol/g liver). Second, the ER complex enhances the transcription rate of mRNA for

R by an Emax saturable-type kinetics with the degree of enhancement controlled by a maximum fold increase (Smr; unitless) and the concentration of ER that produces one-half the maximum feedback (Kmr; fmol/g liver). Messenger RNA for receptor (mR) is synthesized at a constant rate (ks,mr; pg/µg total RNA/hr) and degraded according to first-

-1 order kinetics at a rate controlled by an elimination rate constant (ke,mr; hr ). The hepatic mRNA level was measured by quantitative RT-PCR [Schultz, unpublished data] and the level of hepatic estrogen receptor at each time point was individually estimated from the measured concentration of mRNA using the published relationship between the mRNA and R [139].

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4.2.5.4. Biosynthesis of Vg

Activated estrogen-receptor complex bound to DNA (ER; fmol/g liver) is also known to increase the level of mRNA for vitellogenin by the same mechanism as was seen in ER auto-up-regulation [7, 83]; an increase in the transcription of mRNA for Vg and inhibition of degradation of its mRNA. The local representation of receptor- mediated up-regulation of production of Vg mRNA and Vg protein is shown in Figure

4.3, and model-based differential equations were derived:

dmVg ⎛ I ⎞ = k ⋅ 1+ S ⋅ ER − k ⋅ mVg ⋅⎜ mvg ⎟ (Eq. 4.7) s,mvg ()mvg e,mvg ⎜ ⎟ dt ⎝ I mvg + ER ⎠ dVg L = k ⋅ mVgγ − k ⋅Vg (Eq. 4.8) dt s,vg sec L

Messenger RNA for Vg (mVg) was synthesized at a constant (zero-order) rate

(ks,mvg; fg/µg total RNA/hr) and degraded by a first-order process at a rate controlled by

-1 its elimination rate constant (ke,mvg; hr ). Smvg is the linear-fold increase (g liver/fmol) of gene transcription for Vg mRNA and Imvg is the concentration of ER that produces one- half the maximum inhibition feedback (fmol/g liver).

As was seen in the other steroid model [6], Vg is synthesized according to its synthesis rate (ks,vg) and its amplification factor (γ; unitless), indicating that on average a single mRNA transcript can be used to translate multiple copies of Vg protein, which is

143

then secreted into the plasma at a rate controlled by its first-order secretion rate constant

-1 (ksec; hr ).

4.2.5.5. Secretion and Disposition Kinetics of Vg

The appearance of Vg in plasma occurred slowly, and an apparent steady-state was reached at 600 hrs of exposure, indicating that EE2 was rapidly absorbed from the water and continuous exposure of 600 hrs duration was sufficient to bring Vg biosynthesis to steady-state conditions. The concentration of Vg in plasma and the liver was measured by an ELISA method [Schultz, unpublished data].

Newly synthesized Vg is secreted from the liver into the plasma where its degradation may occur at a rate controlled by its total body clearance (CLvg; mL/hr/kg body weight). The plasma concentration-time profile of Vg after intravenous injection of purified Vg showed a tri-exponential decay, suggesting that a three-compartment model would be appropriate for characterizing the pharmacokinetics of Vg [74].

A clearance-volume compartmental model was used to analyze the individual plasma profiles of Vg. CL12,vg (mL/hr/kg body weight) and CL13,vg (mL/hr/kg body weight)

are intercompartmental distributive clearance constants that control the rates of Vg exchange between central compartment (plasma) and a shallow peripheral compartment and a deep peripheral compartment, respectively. V1,vg (mL/kg), V2,vg (mL/kg), and V3,vg

(mL/kg) are apparent volumes of distribution of the central, shallow, and deep compartments, respectively. VH (g/kg) represents its anatomical liver weight of rainbow trout [133].

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Figure 4.4 shows the schematic representation of the conventional three- compartment pharmacokinetic model for the disposition of Vg, and model-based differential equations are as follows:

dVg V ⋅ 1 = k ⋅V ⋅Vg + CL ⋅ ()Vg −Vg + CL ⋅ (Vg −Vg )− CL ⋅Vg 1,vg dt sec H L 12,vg 2 1 13,vg 3 1 vg 1 (Eq. 4.9)

dVg V ⋅ 2 = CL ⋅ (Vg −Vg ) (Eq. 4.10) 2,vg dt 12,vg 1 2

dVg V ⋅ 3 = CL ⋅ (Vg −Vg ) (Eq. 4.11) 3,vg dt 13,vg 1 3

4.2.6. Working Model

The previous model scheme shown in Figure 4.1 was changed to adapt the

‘working’ model schematic diagram which is shown in Figure 4.5. The major change is that activated estrogen-receptor complex, rather than ERE to which it is directly related, induces the pharmacodynamic responses.

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4.2.7. Working Model-based Differential Equations

The ‘working’ model-based differential equations are as follows:

−α ⋅t −β ⋅t E1 = ()A + B − ()A⋅ e + B ⋅ e dmR ⎛ S ⋅ ER ⎞ ⎛ I ⎞ ⎜ mr ⎟ ⎜ mr ⎟ = ks,mr ⋅⎜1+ ⎟ − ke,mr ⋅ mR ⋅⎜ ⎟ dt ⎝ Kmr + ER ⎠ ⎝ Imr + ER ⎠ dR = k ⋅ mR − k ⋅ R − k ⋅ E ⋅ R + k ⋅ ER dt s,r e,r on L off dER = k ⋅ E ⋅ R − ()k + k ⋅ ER dt on L off deg dmVg ⎛ I ⎞ = k ⋅ 1+ S ⋅ ER − k ⋅ mVg ⋅⎜ mvg ⎟ s,mvg ()mvg e,mvg ⎜ ⎟ dt ⎝ Imvg + ER ⎠ dVg L = k ⋅ mVgγ − k ⋅Vg dt s,vg sec L dVg k ⋅Vg ⋅V + CL ⋅Vg + CL ⋅Vg − ()CL + CL + CL ⋅Vg 1 = sec L H 12,vg 2 13,vg 3 12,vg 13,vg vg 1 dt V1,vg dVg CL ⋅Vg − CL ⋅Vg 2 = 12,vg 1 12,vg 2 dt V2,vg dVg CL ⋅Vg − CL ⋅Vg 3 = 13,vg 1 13,vg 3 dt V3,vg

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4.3. Results and Discussion

4.3.1. Pharmacokinetics of EE2

The plasma concentration-time profile after continuous exposure of male rainbow trout to EE2 in the water was characterized as follows:

−α⋅t −β ⋅t E1 = ()A + B − (A⋅ e + B ⋅ e ) (Eq. 4.1)

A = 37.6 ng/mL

B = 46.1 ng/mL

α = 4.54 hr-1

β = 0.0229 hr-1

It was assumed that only unbound EE2 in plasma freely diffused across the hepatocyte membrane, and that the liver was a well-perfused organ. Plasma protein binding was estimated to be > 99%. Compared with estradiol, EE2 showed slower metabolism [86], reduced hepatic elimination, and increased urinary excretion [131].

Considering that EE2 is a low hepatic extraction drug, its free hepatic concentration would be nearly the same as its free plasma concentration. Therefore, we used the measured plasma concentration of EE2 to reflect the receptor-unbound hepatic

147

concentration of EE2. The observed and predicted (by the model-based differential equation) concentration-time profile of EE2 in the plasma is shown in Figure 4.6.

4.3.2. Characterization of Receptor mRNA and Estrogen Receptor Protein

After characterizing plasma and hepatic receptor-unbound EE2 kinetics, we used a steady-state approach with the basal levels of mR and R in order to obtain the relationship between synthesis rate constants for mR and R (ks,mr and ks,r) and the elimination rate constants (ke,mr and ke,r). The basal steady-state concentrations of mR and

R were as follows [Schultz, unpublished]: mR(0) = 0.4275 pg/µg total RNA,

R(0) = 10.4 fmol/g liver

At steady-state, Rate-in (pg/µg RNA or fmol/g liver) = Rate-out.

Rate-in (pg/µg RNA/hr) = ks,mr

Rate-out (pg/µg RNA/hr) = ke,mr × mR

Therefore, ks,mr = ke,mr × mR(0) (Eq. 4.12)

The same relationship holds for the receptor:

Rate-in (fmol/g liver/hr) = ks,r × mR(0)

Rate-out (fmol/g liver/hr) = ke,r × R(0)

Therefore, ks,r × mR(0) = ke,r × R(0) (Eq. 4.13)

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The elimination half-life of mR was 4 hr from the experiment using primary hepatocytes of rainbow trout [83]. As the elimination rate constant is ln(2)/half-life, ke,mr would be 0.173 hr-1.

From Equation (4.12),

-1 ks,mr = 0.173 hr × mR(0) = 0.0740 pg/µg RNA/hr.

The elimination of R has not been characterized, so the relationship of Equation (4.13) was used; ks,r = 24.3 × ke,r (Eq. 4.14)

4.3.3. Characterization of the Binding of EE2 to R, and the Receptor Dynamics

The Kd value for R binding to EE2 in male rainbow trout is estimated to be 1.4 nM [140, 141] or 0.42 ng/mL. From the literature, koff for estradiol was estimated to be

0.347 hr-1 [142]. Then, kon = koff /Kd = 0.826 mL/ng/hr

The maximal fold increase of mR synthesis (Smr) is known to be 4.0 from hepatocyte culture experiments where treatment with estradiol from 100 nM to 1 µM showed mR synthesis to be consistently 5-times the control, indicating that the pre- existing estrogen receptor is sufficient for a maximal increase in mR synthesis [7]. Since the steady-state EE2 concentration was ~300 nM, it was likely that mR synthesis was maximally stimulated. Therefore, we set Smr to 4.0. In addition, the EE2 concentration that shows the half-maximal effect on mR synthesis (Kmr) would be so low that the basal level of estrogen receptor was already at a saturable concentration for mR synthesis. As 149

the basal concentration of R was 10.4 fmol/g liver, we set Kmr to an arbitrary value of 0.1 fmol/g liver.

It was assumed that activated ER complex would be degraded or dissociated to become a free receptor and a ligand. After fitting the concentration-time profiles of mR and R, values for three unknown kinetic parameters (receptor elimination rate constant

(ke,r), ER complex degradation rate constant (kdeg), and ER concentration that shows half- maximal inhibition of mR degradation (Imr)) were estimated by a nonlinear least squares method; their values are shown in Table 4.1. Subsequently, ks,r was calculated from

Equation (4.14). All kinetic/dynamic parameter values associated with estrogen binding and up-regulation of receptor are also shown in Table 4.1. The concentration-time profiles of mR and R are shown in Figure 4.7.

4.3.4. Characterization of mVg and the Biosynthesis of Vg in the Liver

Since we have not measured mRNA for vitellogenin (mVg) which is negligibly expressed in the absence of estrogenic substances, the basal level of mVg was chosen to be 0.001 pg/µg total RNA, which is under the limit of detection, as an arbitrary value connecting the activated ER complex and Vg production. Therefore, all the values for mVg in this model would be a relative fold increase from the basal level of mVg, rather than an actual concentration. When the concentration of mVg becomes available, it can be applied in a second generation PK/PD model for vitellogenin. The projected basal concentration of mVg and the measured Vg in the liver and the plasma were as follows:

150

mVg(0) = 0.001 pg/µg total RNA

VgL(0) = 0.1 µg/g liver

At steady-state condition, Rate-in (fg/µg RNA or µg/g liver) = Rate-out.

Rate-in (fg/µg RNA/hr) = ks,mvg

Rate-out (fg/µg RNA/hr) = ke,mvg × mVg

Therefore, ks,mvg = ke,mvg × mVg(0) (Eq. 4.15)

The same relationship holds for Vg:

γ Rate-in (µg/g liver/hr) = ks,vg × mVg(0)

Rate-out (µg/g liver/hr) = Rate of secretion (µg/g liver/hr) = ksec × VgL(0)

Therefore,

γ ks,vg × mR(0) = ksec × VgL(0) (Eq. 4.16)

The elimination half-life of mVg was known to be 10 hr from the experiment using primary hepatocytes of rainbow trout [7]. As the elimination rate constant is

-1 ln(2)/half-life, ke,mvg would be 0.0693 hr .

From Equation (4.15),

-1 -5 ks,mr = 0.0693 hr × 0.001 pg/µg RNA = 6.93 × 10 pg/µg RNA/hr.

Since the exponent term γ was involved in the equation, it was considered better to estimate ks,vg, γ , and ksec by fitting the model-based equations rather than to use the relationship from Equation (4.16).

Smvg can be estimated from the literature [7] where the transcription rate of Vg mRNA (mVg synthesis rate) was 80 units (arbitrary units) while receptor mRNA

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synthesis was 30 units after incubation with 1 µM of estradiol for 48 hrs. This value of

30 units for mR can be related to the synthesis rate of mR, which was km,r × (1 + Smr) =

0.0740 pg/µg RNA/hr × (1 + 4) = 0.370 pg/µg RNA/hr. A four-fold increase in the synthesis rate of mR was constantly observed at estradiol concentrations between 100 nM and 1 µM. Therefore, the factor to relate the transcription rate and the actual synthesis rate (f), can be calculated as follows:

30 unit = f × 0.370 pg/µg RNA/hr

Therefore, f = 81.1 units (pg/µg RNA/hr)-1

Since the steady-state ER concentration (ERss) was estimated by the previous receptor dynamics to be 41.8 fmol/g liver, the synthesis rate of mVg would be as follows: ks,mvg × (1 + Smvg × [ER]ss) × f = 80 units

-1 0.0693 fg/µg RNA/hr × (1 + Smvg × 41.8 fmol/g liver) × 81.1 unit (pg/µg RNA/hr)

-3 = 5.62 × 10 units × (1 + Smvg × 41.8 fmol/g liver) = 80 units

Then, (1 + Smvg × 41.8 fmol/g liver) = 14235.

So, Smvg = 341 g liver/fmol.

The half-maximal inhibitory concentration of mVg degradation (Imvg) was also estimated by fitting and all kinetic parameter values are summarized in Table 4.2.

4.3.5. Characterization of Vg in the Plasma

After intravenous administration of a single bolus dose of EE2, Vg kinetic parameters were obtained for a conventional, three-compartment open model [74]. ksec

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was estimated from the concentration-time profiles of Vg in the liver and plasma. Fitting was done by 1/Y2 weighting of model-based equations; pharmacokinetic parameter values for Vg are listed in Table 4.3. The model-predicted and observed concentration- time profiles of Vg in the liver and the plasma are shown in Figures 4.8 and 4.9.

4.4. Conclusion

A pharmacokinetic/pharmacodynamic model was introduced to quantitatively characterize the estrogen-induced receptor-mediated gene induction and associated protein expression in this chapter. This first-generation PK/PD model for the EE2-Vg system described the receptor-dependent positive feedback loop between ligand-activated receptor (= transcription factor) and the enhancement of the expression of its mRNA, amplifying the subsequent expression of the receptor. Moreover, the activated estrogen- receptor complex stabilized the existing receptor mRNA, also providing a positive feedback effect on the receptor pool. The expression of mRNA for vitellogenin and vitellogenin protein was increased dramatically, by several orders of magnitude, by the activated estrogen receptor-dependent positive feedback mechanism. An indirect- response model was employed to account for the lag time between the appearance of vitellogenin and the induction of estrogen receptor. It also predicted successfully the turnover of both mRNA and protein level of both receptor and vitellogenin. A second- generation PK/PD model would elucidate the more detailed biology of receptor-mediated gene; e.g., mRNA for Vg and pharmacogenomic information of the receptor. Nonlinear

153

plasma appearance of Vg after various intravenous bolus doses of EE2 will also be available in the later version of PK/PD model.

4.5. Acknowledgment

I thank Dr. Irvin R. Schultz in the Molecular Biosciences Division, Battelle PNNL, for sharing his valuable data with me. I also appreciate his helpful comments and additional data used for further development of the second generation PK/PD model of vitellogenin.

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Water

Smr Liver Plasma Kmr k s,mr + − Imr

k0 mR ke,mr ks,r

CL12,E kon k'on kdeg

E2 E1 EL + R ER ERN CL1H,E koff k'off

CLE ke,r

S mvg k Vg2 s,mvg + CL12,vg γ CL13,vg Vg1 VgL mVg ksec ks,vg

Vg3 ke,mvg − CLvg Imvg

Figure 4.1: Schematic representation of the pharmacokinetic/pharmacodynamic model for estrogen-induced receptor-mediated gene induction and the biosynthesis of Vg during continuous exposure of male rainbow trout to synthetic estrogen 17-α-ethynylestradiol (EE2) in water. Abbreviations, initial conditions, and associated differential equations are described in sections 4.2.2, 4.2.3, and 4.2.4, respectively.

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Smr Kmr Imr + – mR ks,mr ke,mr

ks,r kon EL + R ER koff kdeg ke,r

Figure 4.2: Schematic representation of the pharmacokinetic/pharmacodynamic model for estrogen-induced, receptor-mediated estrogen receptor mRNA induction and the up- regulation of biosynthesis of the receptor during continuous exposure of male rainbow trout to EE2 in water. Messenger RNA for the receptor is considerably up-regulated via two positive feedback effects: acceleration of the biosynthesis of mRNA and increase in the stability of mRNA.

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Smvg Imvg + – mVg

ks,mvg ke,mvg

ks,vg

VgL ER

ksec

Figure 4.3: Schematic representation of the pharmacokinetic/pharmacodynamic model for estrogen-induced receptor-mediated Vg mRNA induction and the up-regulation of biosynthesis of Vg during continuous exposure of male rainbow trout to EE2 in water. Messenger RNA for Vg is considerably up-regulated via two positive feedback effects: accelerated biosynthesis of mRNA and increased stability of mRNA.

157

VgL

ksec

CL CL 12,vg 13,vg Vg2 Vg1 Vg3

V2,vg V1,vg V3,vg

CLvg

Figure 4.4: Schematic representation of the pharmacokinetic model for the disposition of Vg after its secretion from the liver where the synthesis occurs.

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Water

Smr Liver Plasma Kmr ks,mr + I − mr mR k0 ke,mr

k s,r

CL12,E kon E2 E1 EL + R ER kdeg koff CLE ke,r

Smvg k Vg2 s,mvg +

CL12,vg γ

CL13,vg Vg1 VgL mVg ksec ks,vg Vg 3 ke,mvg − CL vg I mvg

Figure 4.5: Schematic representation of the pharmacokinetic/pharmacodynamic ‘working’ model for estrogen-induced receptor-mediated gene induction and the biosynthesis of Vg during continuous exposure of male rainbow trout to EE2 in water. This figure differs from Figure 4.1 in that activated ER complex is a surrogate for ERE and induces the pharmacodynamic responses.

159

1000

n o i

t a r

n 100

e c

o 120

C 90 2 E 60

E 10

a 30 (ng/mL plasma) m 0 s a

l 0 20406080100

1 0 400 800 1200 1600

Time (hr)

Figure 4.6: Pharmacokinetics of plasma EE2 during continuous exposure of male rainbow trout to EE2. Solid circle (●) indicates measured EE2 concentration in the plasma and solid line indicates predicted plasma concentration of EE2 by model fitting. Insert shows the plasma pharmacokinetics of EE2 in early time points with a linear scale in the y-axis. I represents ± one standard deviation (SD) among three male rainbow trout.

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100

1 Concentration

g RNA or fmol/g liver) µ

(pg/ 0.1

0 100 200 300 400 500 600

Time (hr)

Figure 4.7: Time course of estrogen receptor mRNA and total receptor protein during continuous exposure of male rainbow trout to EE2. Circles indicate measured concentration of mRNA (closed; ●; pg/µg RNA) and total receptor (open; ○; fmol/g liver), and lines indicate predicted concentration of mRNA (solid) and total receptor (dotted). Note that receptor concentration was individually estimated from the measured concentration of mRNA using the published relationship between the mRNA and receptor (described in Model Development). Predicted values were simulated concentrations of mRNA and receptor from the model fitting. I represents ± one SD (n = 3).

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100000

10000

1000

100

g/mL plasma) µ 10

Vg Concentration 0.1

g/g liver or

µ 0.01 ( 0.001

0 400 800 1200 1600 2000 2400

Time (hr)

Figure 4.8: Time course of vitellogenin in the liver and the plasma during continuous exposure of male rainbow trout to EE2. Circles indicate measured Vg concentration in the liver (closed; ●) and the plasma (open; ○), and lines indicate predicted concentration of Vg in the liver (solid) and the plasma (dotted). Predicted values were simulated concentrations of Vg from the model fitting. I represents ± one SD (n = 3 for hepatic Vg concentrations and n = 5 for plasma Vg concentrations).

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100000

10000 1000

100

g/mL plasma) µ 10

Vg Concentration 0.1 g/g liver or

µ ( 0.01

0.001 0 200 400 600 800

Time (hr)

Figure 4.9: Detailed feature of Figure 4.8 for the early time course of vitellogenin in the liver and the plasma during continuous exposure of male rainbow trout to EE2. Circles indicate measured Vg concentration in the liver (closed; ●) and the plasma (open; ○), and lines indicate predicted concentration of Vg in the liver (solid) and the plasma (dotted). Predicted values were simulated concentrations of Vg from the model fitting. I represents ± one SD (n = 3 for hepatic Vg concentrations and n = 5 for plasma Vg concentrations).

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Parameters Abbreviation Units Value

Rate of mR synthesis ks,mr pg/µg RNA/hr 0.0740 -1 Rate constant for mR degradation ke,mr hr 0.173

Maximal stimulatory fold-increase Smr unitless 4.0 in mR synthesis

Median stimulatory ER concentration Kmr fmol/g liver 0.1 in mR synthesis

Median inhibitory ER concentration Imr fmol/g liver 131 in mR degradation -1 Rate constant for R synthesis ks,r (pg/µg RNA) fmol/g liver/hr 1.13 -1 Rate constant for R degradation ke,r hr 0.0466 -1 -1 Association rate constant (on-rate) kon (ng/g liver) hr 0.826 -1 Dissociation rate constant (off-rate) koff hr 0.347 -1 Rate constant for degradation of kdeg hr 0.0766 activated ER complex Initial concentration of mR mR(0) pg/µg RNA 0.428 Initial concentration of R R(0) fmol/g liver 10.4 Initial concentration of ER ER(0) fmol/g liver 0

Table 4.1: Pharmacokinetic/Pharmacodynamic parameter values for estrogen receptor mRNA and protein during continuous water exposure to EE2.

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Parameters Abbreviation Units Value

-5 Rate of mVg synthesis ks,mvg pg/µg RNA/hr 6.93 × 10 -1 Rate constant for mVg degradation ke,mvg hr 0.0693 -1 Stimulatory fold-increase Smvg (fmol/g liver) 341 in Vg synthesis

Median inhibitory ER concentration Imvg fmol/g liver 1.49 in Vg degradation -1 -4 Rate constant for Vg synthesis ks,vg (pg/µg RNA) µg/g liver/hr 8.48 × 10 -1 Rate constant for Vg secretion ksec hr 0.0787 Amplification factor on the γ unitless 2.48 translation of Vg

Liver weight VH g/kg 15.0 Initial concentration of mVg mVg(0) pg/µg RNA 0.001

Initial concentration of VgL VgL(0) µg/g liver 0.1

Table 4.2: Pharmacokinetic/Pharmacodynamic parameter values for vitellogenin mRNA and protein during continuous water exposure to EE2.

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Parameters Abbreviation Units Value

Total body clearance CLvg mL/hr/kg 29.3

Intercompartmental clearance between CL12,vg mL/hr/kg 42.2 central and shallow compartment

Intercompartmental clearance between CL13,vg mL/hr/kg 5.15 central and deep compartment

Volume of distribution V1,vg mL/kg 240 of central compartment

Volume of distribution V2,vg mL/kg 318 of shallow compartment

Volume of distribution V3,vg mL/kg 638 of deep compartment

Initial concentration of Vg Vg1(0) µg/mL 0.009 in the central compartment

Initial concentration of Vg Vg2(0) µg/mL 0.009 in the shallow compartment

Initial concentration of Vg Vg3(0) µg/mL 0.009 in the deep compartment

Table 4.3: Pharmacokinetic parameter values for Vg after intravenous administration of the protein.

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CHAPTER 5

PERIODICAL TURNOVER OF REPRODUCTIVE HORMONES:

PHARMACOKINETIC/PHARMACODYNAMIC MODELING OF

HORMONE-DEPENDENT BIOLOGICAL FEEDBACK SYSTEM

5.1. Background

5.1.1. Outline

Particularly useful modeling approaches combine traditional methods for estimating chemical absorption and internal distribution with the increasingly available knowledge base of receptor binding, signal transduction, and gene activation. Such modeling tools can be used to estimate the functional extent of receptor activation and, if developed in sufficient detail, are useful for investigation of endocrine system response to a variety of perturbations [143]. Besides their use in risk assessment,

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biologically based dose-response models of the receptor-gene type can be helpful in clinical pharmacology as an aid in dose optimization [144]. This application of PK/PD models will definitely assume greater importance as the development of drugs that elicit pharmacological effects via receptor-mediated gene induction processes increases. Thus, confirmed study and refinements in the understanding of the kinetics of receptor regulation and activation, signal transduction and protein synthesis of model systems is warranted.

5.1.2. Objectives

This chapter focuses on the development of a biologically based pharmacodynamic model for the Hypothalamus-Pituitary-Gonad (HPG) system that is periodically (annually) cycled. A mathematical model was proposed to quantitatively characterize the pharmacodynamics of the female HPG axis in the female coho salmon.

The biologically relevant model is based on the normal biology of gonadotropin, estrogen, progesterone, and maturational hormone signaling systems. The validated HPG model can become a useful tool for exploration of mechanisms related to hormone signaling, including receptor agonists / antagonists and modulators of down-stream signaling pathways.

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Hypothesis

An integrated pharmacodynamic (PD) model of the hypothalamus-pituitary-gonad

(HPG) axis can be developed to describe the changes in hormone profiles and oocyte

growth in the female coho salmon.

5.2. Model Development

5.2.1. Pharmacodynamic Modeling of the HPG Axis

A model was developed that described the HPG axis in female coho salmon.

This fish species was chosen for development of a first generation model as data sets describing both pituitary and gonad activities were readily available. Unlike species such as the fathead minnow, which spawn repeatedly, salmon spawning occurs on an annual cycle, which is synchronized with levels of pituitary and gonadal hormones. Therefore, the model was based on the annual spawning cycle, which was reduced to mathematical expressions of a periodical nature. Measured data [Swanson, unpublished] guided development of the HPG axis model and they also permitted validation of the model.

5.2.2. HPG Model

The first-generation model was informed by measured plasma concentrations of pituitary- and ovary-derived hormones measured in female coho salmon over the March-

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December period [Swanson, unpublished]. The four hormones are two pituitary-derived hormones, i.e., follicle stimulating hormone (FSH) and luteinizing hormone (LH), and two ovary-derived hormones, i.e., estradiol (E2) and 17α, 20β-dihydroxy-4-pregnene-3- one (DHP). The model adopted features of published, biologically based mammalian models [145] and indirect response pharmacodynamic models [20, 146]. Relationships among model variables are depicted qualitatively in the diagram as shown in Figure 5.1.

Solid, thin arrows represent transfer among variables, solid, thick arrows indicate a stimulatory influence, and dotted arrows indicate an inhibitory influence. Four important compartments are indicated, including hypothalamus, pituitary gland, blood (plasma), and gonad (ovary). Model-based differential mass balance equations (Equations developed in 5.1 to 5.7 and 5.9) and five descriptive equations on the oocyte progression

(Eq. 5.8, n = 1~5) are developed in the following section 5.2.3.

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5.2.3. Model-based Equations

If 75 ≤ t ≤ 250 days, then G = 50 (Unitless), otherwise, G = 0 dmF ⎛ I ⎞ = k ⋅⎜1+ E,mF + S ⋅G⎟ − k ⋅ mF (Eq. 5.1) s,mF ⎜ G,mF ⎟ e,mF dt ⎝ I E,mF + E2P ⎠

dFP 1 = ⋅ (k s,F ⋅ mF − CLF ⋅ FP ) (Eq. 5.2) dt Vd F dmLH = k ⋅ ()1+ S ⋅G + S ⋅ E2 − k ⋅ mLH (Eq. 5.3) dt s,mLH G,mLH E,mLH P e,mLH dLH ⎛ (I )2 ⎞ = k ⋅ mLH − k ⋅ LH − k ⋅⎜ E,LH ⎟ ⋅ LH (Eq. 5.4) dt s,LH e,LH r,LH ⎜ 2 2 ⎟ ⎝ ()I E,LH + (E2P ) ⎠ dLH 1 ⎛ ⎛ K 2 ⎞ ⎞ P = ⋅⎜k ⋅⎜ i ⎟ ⋅ LH − CL ⋅ LH ⎟ (Eq. 5.5) dt Vd ⎜ r,LH ⎜ 2 2 ⎟ LH P ⎟ LH ⎝ ⎝ K i + (E2 P ) ⎠ ⎠

dE2 P 1 = ⋅ ()E2(0) + SO2,E 2 ⋅O2 + SO3,E 2 ⋅O3 + SO4,E 2 ⋅O4 − CLE 2 ⋅ E2 P (Eq. 5.6) dt Vd E 2

dPP 1 = ⋅ ()P(0) + SO4,P ⋅O4 + S FOM ,P ⋅ FOM − CLP ⋅ PP (Eq. 5.7) dt Vd P

2 ⎛ ⎛ t − t ⎞ ⎞ O = O (0) + a ⋅ exp⎜− ⎜ n ⎟ ⎟ where n = 1, 2, 3, 4, and 5 (FOM ) (Eq. 5.8) n n n ⎜ ⎜ W ⎟ ⎟ ⎝ ⎝ n ⎠ ⎠ dSPWN = k ⋅ (FOM + S ⋅ P )− k ⋅ SPWN (Eq. 5.9) dt f ,SPWN P,SPWN P e,SPWN

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5.2.4. Hypothalamus and Hormonal Regulation

Gonadotropin releasing hormone (GnRH; G) is synthesized in the hypothalamus and secreted into the pituitary gland. While GnRH synthesis and release are controlled by the environmental variables such as photoperiod length, water temperature, and nutrient levels, GnRH was modeled at a constant level of 50 arbitrary units between days

75 and 250 of the calendar year, due to a lack of quantitative relationships between

GnRH and environmental cues. GnRH introduced a periodical function in the biological system, which can be further expressed by trigonometry using cosine or sine functions and a related threshold level. However for a relatively simple first-generation model, an all-or-none response was set in the GnRH level. To permit a more biologically realistic characterization of GnRH, its quantification is warranted in the next generation pharmacodynamic model.

5.2.5. Pituitary Gland and Hormonal Regulation

GnRH stimulated the biosynthesis of messenger RNA for FSH (mF; ng) and LH

(mLH; ng), as shown in Equations 5.1 and 5.3, which were also influenced by estradiol concentration in plasma (E2P; ng/mL). The FSH mRNA biosynthesis was inhibited by

E2P while the LH mRNA biosynthesis was stimulated by E2P. The proportionality constant (SG,mF) that related the mF biosynthesis to GnRH was reduced in the presence of

E2P, with the IE,mF being the E2P value that reduced mF biosynthesis by half. Both

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mRNAs underwent degradation at a rate that was the product of a first-order elimination rate constant (ke,mF or ke,mLH) and the amount of mRNA.

The FSH synthesized in the pituitary gland was assumed to immediately distribute into its plasma-referenced volume of distribution, VdF (mL), and to be cleared at a rate controlled by its plasma clearance, CLF (mL/day).

The LH was synthesized and stored in the pituitary gland (LH; ng) before its release (LHP; ng/mL) into its plasma-referenced volume of distribution, VdLH (mL), as shown in Equations 5.4 and 5.5. The LH synthesis was proportional (ks,LH) to the amount of mLH and degraded by a first-order process controlled by elimination rate constant,

-1 ke,LH (day ). The LH was released from the pituitary pool into plasma at a rate that was controlled by rate constant kr,LH, the value of which varied inversely to the plasma concentration of E2 according to a Hill-type term [147]. LH appeared in plasma at a rate equal to its release rate from the pituitary pool and was cleared from plasma at a rate proportional to its plasma clearance, CLLH (mL/day). Therefore, E2 had a biphasic effect.

It stimulated synthesis of mRNA for LH and inhibited release of LH into plasma. A high concentration of E2 favored LH synthesis without stimulation of significant LH release.

As the E2 level decreased, LH synthesis was reduced along with a burst of LH secretion into plasma.

5.2.6. Oocyte Progression and the Effect of Steroid Hormones

The level of estradiol in the plasma (E2P) was regulated by the oocytes, which moved along a maturation progression. E2 was synthesized at a basal rate (E2(0)), and

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as oocytes matured, stimulation of E2 biosynthesis occurred; i.e., the synthesis rate by each subsequent maturation level increased, as shown in Equation 5.6. E2 was cleared according to the plasma clearance, CLE2 (mL/day).

Oocytes progressed by a periodical function of time with basal levels (O1(0),

O2(0), O3(0), O4(0), and FOM(0)), amplitudes (a1, a2, a3, a4, and aFOM), widths (W1, W2,

W3, W4, and W5; days), and peak times (t1, t2, t3, t4, and t5; days). In the current first- generation model, actual oocyte progression was not identified, so it was assumed to be a periodic movement of the biological processes.

The oocyte progression begins with the stimulation induced by the plasma level of

FSH. Therefore, early oocyte progression is governed by FSH rather than LH. However, as oocyte progressed, the influence of FSH becomes weaker and LH starts to play a more important role in regulating the maturation of oocytes as depicted in Figure 5.1.

The level of progesterone (DHP) in the plasma (PP) was also periodically regulated by the oocytes maturation process with its basal synthesis level (P(0)), stimulatory factors from sub-compartments of individual oocytes 4 and FOM (SO4,P and

SFOM,P), and clearance of DHP (CLP). Spawning (SPWN) was caused by FOM progression and the stimulatory effect by DHP (SP,SPWN) at a rate controlled by formation

(kf,SPWN) and elimination (ke,SPWN) rate constant of spawning.

5.2.7. Coordination of Pharmacodynamic Feedback Model

The set of 8 model-based differential equations, and the 5 equations that described oocyte maturation were used in WinNonlin 4.0 (Pharsight) to simulate the temporal

174

profile of each variable in the model. The four measured hormones (FSH, LH, E2, and

DHP) in the plasma and their model predicted values were plotted over time.

5.3. Results and Discussion

5.3.1. The Four Reproductive Hormones

Figure 5.2 shows the time course of the plasma concentration of four hormones measured in female coho salmon after exposure to the photoperiod. Smooth connection between observed values were made by spline curves provided in the EXCEL program.

FSH increased slowly from day 75 to 200 where an apparent plateau was observed after which a rapid drop occurred. In contrast, the other gonadotropin, LH remained at a negligible level for more than 250 days, when it started rising modestly and then showed a rapid increase after day 300. The concentration of E2 was very low up to day 160.

When a FSH reached its apparent plateau, the level of E2 seemed to quickly increase. Its elimination was also rapid; it took less than a month to restore its low basal level, followed by the onset of DHP, and a burst of LH. Based on the measured plasma concentration of four reproductive hormones, the PK/PD modeling was developed.

5.3.2. GnRH Released from the Hypothalamus

The GnRH was simulated by the model-based setting that gives an all-or-none phenomenon as shown in Figure 5.3. Among many environmental cues such as an 175

alteration in the temperature and food availability, the daylight-dependent photoperiod was chosen as a major driving force for the synthesis and release of GnRH from the hypothalamus of the female coho salmon. While photoperiod changes follow a cosine function, our first-generation model assumed a rapid burst of a GnRH due to a small increase above the threshold in the duration of daylight. This unique property of GnRH release provides the four reproductive endocrine molecules with a periodic function.

5.3.3. Messenger RNA for Gonadotropins in the Pituitary Gland

The time course of mRNA for FSH and LH induced by the periodical action of

GnRH is demonstrated in Figure 5.4. The turnovers of two gonadotropins were regulated by the presence of E2 in the plasma. The synthesis of mRNA for FSH was stimulated in the presence of GnRH but inhibited by the presence of plasma E2, induced from the oocyte progression. There was no point of regulation reported in the elimination of FSH.

Therefore, in the early period, mRNA for FSH increased with a similar pattern of zero order input kinetics. However, at later stage of oocytes progression where the rapid increase in plasma E2 was observed, the synthesis of FSH mRNA was significantly inhibited by the low value of IE,mF by E2, resulting in the considerable decrease in the

FSH mRNA level with its rapid elimination rate constant (0.1 day-1).

In contrast, mRNA level of LH was maintained at a negligible basal level. Its synthesis increased with the action of both GnRH and E2; but the contribution of GnRH to the synthesis of mLH was small compared with that to mFSH synthesis. Thus, the synthesis of mLH became plasma E2-dependent. As oocytes matured, E2 level increased

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which induced the synthesis of mRNA for LH. By its rapid elimination rate constant

(0.25 day-1), the mRNA for LH went back to its basal level quickly after its peak.

5.3.4. Oocyte Progression and Maturation, and Spawning

Time course of oocyte progression and maturation in the gonad, ovary, of the female coho salmon was simulated by the model-based equations. Periodical parameter values used in the simulation for oocyte growth are listed in Table 5.3. Since there was no quantitative data available for oocyte progression, Gaussian distributive functions were introduced to represent cell progressions. FSH induced the first progression of oocyte (O1) followed by series of empirical progressions; sub-compartments of O2, O3, and O4 were assumed to influence E2 production in the ovary, which in turn regulated the turnover of FSH and LH by transcriptional (FSH and LH) and post-translational (LH) feedback mechanisms. Later stages of oocyte progression were responsible for the production of DHP, which facilitated spawning, the last step of oocyte maturation.

5.3.5. Gonadotropins in the Pituitary Gland and Plasma

While biosynthesized FSH from its mRNA was exported to the plasma immediately, LH was stored in the pituitary gland until a second stimulus was engaged.

Time courses of mRNA for FSH and LH induced by the periodical action of GnRH are demonstrated in Figure 5.4.

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The turnovers of two gonadotropins were explicitly different; E2 had two differential effects on the two major gonadotropins. Oocyte progression-induced E2 inhibited the synthesis of FSH by inhibiting its mRNA synthesis while E2 stimulated LH biosynthesis by enhancing its mRNA synthesis. Moreover, E2 inhibited the secretion of

LH from the pituitary gland to the plasma by the Hill-type cooperativity (Hill coefficient

= 2) which generally gives a powerful control effect with low IE,LH value (5 ng/mL).

After E2 was rapidly cleared from the plasma, LH surge occurred in the plasma by the burst of secretion of accumulated LH in the pituitary gland.

5.3.6. Secretion of Steroid Hormones by the Gonad

The production of E2 was stimulated by the middle stages of oocyte maturation whereas the production of DHP was enhanced by the late stages. The simulated concentration-time profiles of the two ovary-derived gonad hormones are shown in

Figure 5.7. Pharmacokinetic and pharmacodynamic parameter values of FSH, LH, E2, and DHP are listed in Table 5.1 and 5.2, respectively.

These two steroid hormones showed differential influences on the reproductive system; E2 was responsible for feedback regulation of FSH and LH. In contrast, oocyte progression-dependent DHP was involved in the spawning, the last stage of oocyte maturation. Annual (synchronous) spawning started by the periodical stimulation of

GnRH and ended up with the stimulatory effect of DHP on the spawning.

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5.4. Conclusion

In fish, the sex steroids can exert both positive and negative feedback control of gonadotropin secretion, which provides researchers with an excellent biological system for studying the biological feedback mechanisms even with higher orders of regulatory processes. We have studied receptor-dependent protein turnover in chapters 3 and 4.

Now, we are compelled to apply these concepts and techniques to the biological feedback-dependent hormone turnovers in order to better understand an endocrine system. In this case, both receptors (for gonadotropins) and enzymes such as aromatase

(for sex steroid hormones) are control points for the regulation of reproductive hormones.

Pharmacogenomics may be actively included in understanding the whole picture of the entire reproductive endocrine system as well as a quantitative approach made by PK/PD modeling. Future work could augment the PK/PD model with PG (Pharmacogenomics), which would identify specific genes and their temporal activity profiles.

The focus of this chapter was the development of an integrated biologically based

PD model for the female coho salmon HPG axis. As pointed out in chapter 4, due to the importance of vitellogenesis in normal oocyte growth and maturation, the model can include description of E2 regulation of hepatic synthesis of Vg. The combined model would provide a scientifically credible approach for linking results of genomic studies with traditional models of chemical exposure to fish.

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5.5. Acknowledgment

I thank Dr. Penny Swanson, at Northwest Fisheries Science Center, for sharing with me her valuable data – plasma concentrations of four reproductive hormones in female coho salmon.

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Environmental triggering

GnRH

Hypothalamus

ke,mF SG,mF SG,mLH ke,mLH

mFSH mLH LH ks,mF ks,mLH ks,LH

k I S k Pituitary Gland s,F E,mF E,mLH r,LH I E,LH FSH E2 LH E2(0) Blood CLE

CLLH CLF SO2,E2 SO3,E2 SO4,E2

kf,SPWN 1 2 3 4 FOM Spawning Oocytes

Oocytes maturation k SO4,P SFOM,P SP,SPWN e,SPWN

DHP P(0) CLP Blood

Figure 5.1: Schematic diagram of hormone turnover model.

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70 80 60 40 60 20

0 50 280 300 320 340

Plasma Concentration (ng/mL) 10

0 0 100 200 300 400

Time (day)

Figure 5.2: Time course of four hormones measured in coho salmon during the annual spawning cycle. Time = 0 corresponds to the start of the calendar year (Jan. 1). Symbols represent FSH (solid circle), LH (open circle), E2 (solid triangle), and DHP (open triangle). Spline curves (dotted line) were introduced to connect the individually measured values. Inset figure is the enlarged view from day 280 to 340.

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100

Plasma Concentration (unitless) 0

0 100 200 300 400

Time (day)

Figure 5.3: Time course of GnRH release from the hypothalamus after an external stimulus such as a change of daylight. Photoperiod-dependent GnRH release was assumed in the current model. Simulated values by model-based differential equations were plotted over time.

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250

200

150

100

Amount in Pituitary Gland (ng)

0 0 100 200 300 400

Time (day)

Figure 5.4: Time course of mRNA for FSH (solid line) and LH (dotted line) induced by GnRH and regulated by E2 in the pituitary gland. Simulated values by model-based differential equations were plotted over time.

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15 FOM

SPWN O1 O2 O3 O4

Amplitude (unitless) 5

0 0 100 200 300 400

Time (day)

Figure 5.5: Time course of oocyte progression and maturation in ovary of female coho salmon. Simulated values by model-based equations were plotted over time. Solid lines represent oocyte stage 1 (O1), 2 (O2), 3 (O3), 4 (O4), and final oocyte maturation (FOM). Dotted line indicates irreversible spawning (SPWN). The associated pharmacokinetic/pharmacodynamic parameters are shown in Table 5.3.

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Plasma Concentration (ng/mL) 5

0 0 100 200 300 400 500

Time (day)

Figure 5.6: Simulated concentration-time profiles of the two pituitary-derived hormones based on the model-based differential equations. The measured concentrations for FSH (solid circle) and LH (open circle) were plotted simultaneously with the predicted values by the model-based equations for FSH (solid line) and LH (dotted line). The associated pharmacokinetic/pharmacodynamic parameters are shown in Table 5.1.

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Plasma Concentration (ng/mL) 10

0 100 200 300 400 500

Time (day)

Figure 5.7: Simulated concentration-time profiles of the two ovary-derived hormones based on the model-based differential equations. The measured concentrations for E2 (solid triangle) and DHP (open triangle) were plotted simultaneously with the predicted values by the model-based equations for E2 (solid line) and DHP (dotted line). The associated pharmacokinetic/pharmacodynamic parameters are shown in Table 5.1.

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Parameters Abbreviations Units Value

Rate of mF synthesis ks,mF ng/day 40 -1 Rate constant for mF elimination ke,mF day 0.1 -1 Rate constant for FSH synthesis ks,F day 0.002

Rate of mLH synthesis ks,mL ng/day 10 -1 Rate constant for mLH elimination ke,mL day 0.25 -1 Rate constant for LH synthesis ks,L day 0.004 -1 Rate constant for LH elimination ke,L day 0.1 -1 Rate constant for LH release into plasma kr,L day 0.3

Plasma clearance of FSH CLF mL/day 4

Plasma clearance of LH CLLH mL/day 10

Plasma clearance of E2 CLE2 mL/day 800

Plasma clearance of DHP CLP mL/day 800

Volume of distribution of FSH VdF mL 200

Volume of distribution of LH VdLH mL 200

Volume of distribution of E2 VdE2 mL 800

Volume of distribution of DHP VdP mL 800

Table 5.1: Pharmacokinetic parameter values of four hormones associated with the model-based equations.

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Parameters Abbreviations Units Value

Fold-increase in mF synthesis by GnRH SG,mF Unitless 3

Fold-increase in mLH synthesis by GnRH SG,mL Unitless 0.04

Fold-increase in mLH synthesis by E2 SE,mL mL/ng 100

Fold-increase in E2 synthesis by O2 SO2,E2 ng/day 800

Fold-increase in E2 synthesis by O3 SO3,E2 ng/day 2,400

Fold-increase in E2 synthesis by O4 SO4,E2 ng/day 4,000

Fold-increase in DHP synthesis by O4 SO4,P ng/day 80

Fold-increase in DHP synthesis by FOM SFOM,P ng/day 4,800

Fold-increase in Spawning by DHP SP,SPWN mL/ng 100 Median inhibitory concentration of E2 in I ng/mL 10 the mF synthesis E,mF Median inhibitory concentration of E2 in I ng/mL 5 the LH release E,LH

Basal synthesis rate of E2 E2(0) ng/day 2

Basal synthesis rate of DHP P(0) ng/day 2

Table 5.2: Pharmacodynamic parameter values of four hormones associated with the model-based equations.

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Parameters Abbreviations Units Value

Basal level of O1 O1(0) Unitless 0.1

Basal level of O2 O2(0) Unitless 0.1

Basal level of O3 O3(0) Unitless 0.1

Basal level of O4 O4(0) Unitless 0.1 Basal level of FOM FOM(0) Unitless 0.1 Basal level of SPWN SPWN(0) Unitless 0.1 -1 SPWN formation rate constant kf,SPWN day 0.001 -1 SPWN elimination rate constant ke,SPWN day 0.5

Amplitude of O1 a1 Unitless 10

Amplitude of O2 a2 Unitless 10

Amplitude of O3 a3 Unitless 10

Amplitude of O4 a4 Unitless 10

Amplitude of FOM a5 Unitless 10

Peak time of O1 t1 day 225

Peak time of O2 t2 day 255

Peak time of O3 t3 day 280

Peak time of O4 t4 day 305

Peak time of FOM t5 day 325

Width of O1 W1 day 17.5

Width of O2 W2 day 17.5

Width of O3 W3 day 17.5

Width of O4 W4 day 17.5

Width of FOM W5 day 7.5

Table 5.3: Periodical parameter values of oocytes growth and maturation generated by the model-based equations.

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