Examining the Impact of Growth Hormone on the Collagen Content of Adipose Tissue
in Transgenic Mice
A thesis presented to
the faculty of
the College of Health Sciences and Professions of Ohio University
In partial fulfillment
of the requirements for the degree
Master of Science
Lara A. Householder
December 2013
© 2013 Lara A. Householder. All Rights Reserved.
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This thesis titled
Examining the Impact of Growth Hormone on the Collagen Content of Adipose Tissue in
Transgenic Mice
by
LARA A. HOUSEHOLDER
has been approved for
the School of Applied Health Sciences and Wellness
and the College of Health Sciences and Professions by
Darlene E. Berryman
Professor of Applied Health Sciences and Wellness
Randy Leite
Dean, College of Health Sciences and Professions
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Abstract
HOUSEHOLDER, LARA A., M.S., December 2013, Food and Nutrition Sciences
Examining the Impact of Growth Hormone on the Collagen Content of Adipose Tissue of
Bovine Growth Hormone Transgenic Mice
Director of Thesis: Darlene E. Berryman
Obesity is characterized by insulin resistance, inflammation, and pathologically accelerated white adipose tissue (WAT) remodeling. Although it has not yet been extensively studied, the extracellular matrix (ECM) of WAT may be linked with these key features of obesity. The ECM is the structural framework of WAT and is made primarily of collagen fibers. An excess of these collagen fibers, called fibrosis, has been observed in obese adipose tissue (AT). AT fibrosis is thought to contribute to the metabolic abnormalities and inflammation present in obese individuals. Growth hormone
(GH) has been shown to increase collagen in other tissues and has been reported to impact AT in a depot specific manner. To date, no study has assessed the role of GH in
AT ECM deposition. The use of mouse models with differing GH action may help characterize the role of ECM in adipose function/dysfunction. Bovine GH transgenic mice (bGH) are giant and lean with high serum levels of bGH, insulin-like growth factor
1 (IGF-1), and insulin, and have relatively short lifespans. This contradictory phenotype– unhealthy leanness–allows us to examine WAT fibrosis independent of normal adiposity and question whether the amount of ECM in the WAT is more influential to the health of an individual than the overall amount of WAT. Therefore, the purpose of this study was to evaluate measures of ECM deposition in bGH mouse AT. Six-month-old bGH and 4 littermate control mice were dissected and the adipose tissue samples from inguinal, epididymal, retroperitoneal, and mesenteric depots was processed for both histological and expression analysis. To determine the collagen content of WAT, samples were fixed and embedded in paraffin blocks and stained with picosirius red. When assessing overall collagen content, the bGH mice showed dramatic increases in ECM deposition when compared to controls, especially in the inguinal depot. A significant decrease in adipocyte size and number was also observed in bGH mice. However, when the expression of collagen genes Col1α1, Col3α1, Col4α1, Col5α1, and Col6α1 was examined through quantitative PCR analysis, no significant differences due to genotype were found.
Therefore, we have established that GH increases the collagen content of WAT, but the mechanism is still undetermined.
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Dedication
For my grandparents, Jack and Ruth, for being who I want to be when I grow up,
And for Jake, for loving and feeding me while I get there. 6
Acknowledgments
Financially, this project was supported by a Student Enhancement Award, a
CHSP Student Research and Scholarly Activity Presentation Award, a Graduate Student
Senate Travel Award, and a Growth Hormone Research Society and the IGF Society
Travel Award.
This thesis would not exist without the contributions and support of so many. To everyone in the Kopchick Lab: thank you for your patience and generosity as I worked through my very first research project. I truly feel as though I’ve stumbled into the best gig around and I’m thankful for everyone who has been and is a part of it. Specifically, thank you to Katie Troike and Abigail Thaxton for their contributions to the collagen story; Adam Jara for PCR, ImageJ, and statistics guidance; Dr. Ed List and Kevin Funk for their essential role in providing me with samples to study; Ellen Lubbers for her immeasurable research assistance throughout; and to our peerless leader, Dr. John
Kopchick, for setting the tone with his enthusiasm for research and for serving on my committee.
Thank you to my darling husband for his support and patience while I struggled to find my way. I am so fortunate to have you as my partner.
Last, but far from least, thank you to the best mentor I’ve ever had the pleasure of working with, Dr. Darlene Berryman. Without you, I would not have even thought to get a masters degree and I cannot express what your guidance and support has meant to me.
Thank you for more than I could ever repay. 7
Table of Contents
Page
Abstract ...... 3
Dedication ...... 5
Acknowledgments ...... 6
List of Tables ...... 11
List of Figures ...... 12
Chapter 1: Introduction ...... 14
Obesity ...... 14
Adipose Tissue...... 14
Adipose Tissue Fibrosis ...... 16
Growth Hormone...... 17
Purpose and Significance of the Study ...... 18
Research Aims...... 19
Limitations and Delimitations ...... 20
Definitions...... 20
Chapter 2: Literature Review ...... 23
Overview of Adipose Tissue ...... 23
White Adipose Tissue and Brown Adipose Tissue...... 24 8
Adipose Tissue Depots ...... 24
White Adipocytes...... 27
Other Cell Types in Adipose Tissue ...... 28
Obesity...... 29
Introduction to Collagen ...... 29
Collagen Structure ...... 31
Collagen Synthesis ...... 33
Introduction to Collagen in White Adipose Tissue...... 40
Adipose Tissue Fibrosis...... 41
Introduction to Growth Hormone...... 44
Growth Hormone Secretion and Signaling...... 44
Growth Hormone Function ...... 48
Insights into Physiological Effect of Growth Hormone Action through Examination
of Bovine Growth Hormone Transgenic Mice …………………………………….50
Depot Specific Response to Growth Hormone ...... 52
Conclusion ...... 52
Chapter 3: Methodology ...... 54
Animals...... 54
Body Composition ...... 54 9
Adipose Tissue Samples ...... 54
Immunohistochemistry ...... 55
RNA Isolation and cDNA Synthesis ...... 55
Real Time Polymerase Chain Reaction ...... 56
Statistics ...... 57
Chapter 4: Results ...... 58
Body Weight and Composition ...... 58
Adipose Tissue Depot Weights ...... 61
Quantification of Picosirus Red Staining ...... 63
Adipocyte Size and Number ...... 68
RNA Expression ...... 71
Chapter 5: Discussion ...... 75
Overview ...... 75
Body Composition and Adipose Depot Mass ...... 75
Collagen Content ...... 77
Adipocyte Size...... 78
Collagen Gene Expression ...... 79
Limitations and Future Directions...... 80
Conclusion ...... 84 10
References ...... 86
Appendix A: RNA Isolation Procedure ...... 104
Appendix B: Polymerase Chain Reaction Plate Design ...... 108
Appendix C: Adipose Tissue Weights at Dissection ...... 109
Appendix D: Nonadipose Tissue Weights at Dissection ...... 110
11
List of Tables
Page
Table 1: Collagen Types ...... 35
Table 2: Collagen Subunits and Structure ...... 38
Table 3: Collagen Genes ...... 56
12
List of Figures
Page
Figure 1: Adipose tissue depots ...... 26
Figure 2: Collagen triple helix ...... 32
Figure 3: Collagen synthesis and formation of structures ...... 34
Figure 4: Network forming collagens ...... 39
Figure 5: Collagen VI forms beaded filaments ...... 39
Figure 6: Peri-adipocyte collagen organization ...... 41
Figure 7: Collagen expression is up-regulated in obese state...... 42
Figure 8: Activation of growth hormone receptor...... 46
Figure 9: Simplified diagram representing the mechanism of growth hormone induced signal transduction...... 47
Figure 10: Summary of growth hormone secretion and action...... 49
Figure 11: Overview of bovine growth hormone transgenic mouse phenotype compared to wild type...... 53
Figure 12: Comparison of average body weight wild type and bovine growth hormone transgenic mice at 6 months of age...... 59
Figure 13: Comparison of body composition in wild type and bovine growth hormone transgenic mice at 6 months of age...... 60
Figure 14: Comparison of body composition relative to total body weight in wild type and bovine growth hormone transgenic mice at 6 months of age...... 61 13
Figure 15: Adipose tissue depot weights in 6-month-old male bovine growth hormone transgenic and wild type mice...... 62
Figure 16: Relative adipose tissue depot weights in 6-month-old male bovine growth hormone transgenic and wild type mice...... 63
Figure 17: Collagen content in the subcutaneous and epididymal depots of wild type and bovine growth hormone transgenic mice at 6 months of age ...... 65
Figure 18: Average percentage of picosirus red stained area versus total area of adipose tissue depots ...... 66
Figure 19: Distribution of picosirus red stained area in different depots...... 67
Figure 20: Picosirus red stained white adipose tissue from the bovine growth hormone transgenic transgenic mouse subcutaneous depot at 4X magnification...... 68
Figure 21: Average adipocyte size in 6-month-old male bovine growth hormone transgenic and wild type mice...... 70
Figure 22: Average adipocyte number in 6-month-old male bovine growth hormone transgenic and wild type mice...... 71
Figure 23: Comparison of Delta Ct values between 6-month-old bovine growth hormone transgenic and wild type mice...... 72
Figure 24: Comparison of 2^-Delta Ct values between 6-month-old bovine growth hormone transgenic and wild type mice...... 73
Figure 25: Comparison of the fold change in collagen gene expression between 6-month- old bovine growth hormone transgenic and wild type mice...... 74
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Chapter 1: Introduction
Obesity
Obesity is a major medical issue in the developed world. In the United States, more than one third of adults are obese and another third are overweight (Ogden, 2012).
Obesity is defined as an excess of adipose tissue (AT); however, increases in the number and size of adipocytes are not the only change that occurs in the obese state. During obesity, AT undergoes characteristic structural and functional changes including increased inflammation, pathologically accelerated remodeling, and insulin resistance
(Sun, Kusminski, & Scherer, 2011). These characteristic changes are connected to the comorbidities of obesity such as diabetes and cardiovascular disease (Lee, Wu, & Fried,
2010). To effectively combat obesity, prevention and treatment of obesity must be addressed in addition to prevention and treatment of its comorbidities. Therefore, understanding the change to AT that connect obesity and its related diseases are important.
Adipose Tissue
AT is a complex, multidepot organ well known for its ability to store energy in the form of triglycerides. Although it was once largely overlooked by researchers, the discovery of AT’s endocrine function as well as the obesity epidemic have made understanding this intricate tissue a priority for many. AT is a type of loose connective tissue whose primary functions are energy storage and homeostasis as well as mechanical support and insulation (Trayhurn & Beattie, 2001), and it is now recognized as an endocrine organ (Galic, Oakhill, & Steinberg, 2010). It is found in well-defined depots 15 throughout the body that can be distinguished not only by location but also by composition and function (Smorlesi, Frontini, Giordano, & Cinti, 2012). AT depots are categorized as either subcutaneous or intra-abdominal although there are many different depots within those generic categories. Due to the unique characteristics of depots, it is important to investigate multiple depots when studying AT. Of particular importance to this study are the inguinal subcutaneous depot and the epididymal intra-abdominal depot, because preliminary research has shown them to be the most and least altered by GH action, respectively (Troike, Householder, List, Kopchick, & Berryman, 2012).
AT is not homogenous and is comprised of two distinctly different types–white and brown–that consist of white and brown adipocytes, respectively, and have entirely separate functions. White adipocytes are the characteristic cell type of white AT (WAT) and have a unilocular lipid droplet containing stored triglycerides. In obesity, the lipid droplet expands causing hypertrophy of white adipocytes (Bahceci et al., 2007). The increase in adipocyte volume is associated with metabolic and inflammatory dysregulation in obese AT (Bahceci et al., 2007). Alternatively, brown adipocytes are recognized for their multitude of mitochondria and are important in energy expenditure through nonshivering thermogenesis. Although both types are represented throughout all depots, they are present in varying degrees, thus reinforcing the need to analyze multiple depots (Smorlesi et al., 2012).
In addition, AT contains a variety of other cells types, collectively known as the stromal vascular fraction (SVF) that are important to the overall function of the tissue.
Cells of the SVF include immune cells, preadipocytes, and fibroblasts. These cells can 16 contribute to the endocrine function of AT and the production of inflammatory cytokines, which may be particularly important in the obese state (Wajchenberg, Giannella-Neto, da
Silva, & Santos, 2002). The cells of the SVF can also have an impact on the extracellular matrix and, consequently, AT fibrosis as discussed below.
Adipose Tissue Fibrosis
Due to its role in energy storage, AT has become well recognized for its plasticity and remodeling capacity (Sun et al., 2011). This requires the coordination of many cell types such as preadipocytes, endothelial precursor cells, and immune cells as well as other tissue components including the extracellular matrix. During obesity, unhealthy tissue expansion can occur and result in reduced vascular density, hypoxia, necrosis, and an influx of immune cells (Cinti et al., 2005; Halberg et al., 2009; Spencer et al., 2010).
Though many cell types, signaling molecules, and tissue components are involved in this expansion, the extracellular matrix has been recently recognized as an important contributor to this process.
The extracellular matrix (ECM), primarily composed of collagen fibers, accumulates in obese AT causing the tissue to become fibrotic (Divoux et al., 2010). AT fibrosis is now recognized as an integral participant in the dysfunctional changes occurring in the tissue (Divoux et al., 2010). Collagens I, III, IV, V, and VI have been identified as the primary collagens altered in this process (Divoux et al., 2010; Khan et al., 2009). Both hypoxia-related and inflammatory cytokines have been shown to increase collagen expression and promote fibrosis; conversely, fibrosis may also contribute to hypoxia and inflammation (Halberg et al., 2009; Pasarica, Sereda, et al., 2009; Spencer et 17 al., 2010). Increased fibrosis is associated with reduced oxygenation as well as fewer small blood vessels (Spencer et al., 2011), suggesting that the ECM may have a role in restricting angiogenesis and thus promoting hypoxia (Spencer et al., 2011). Moreover, increased collagen VI expression has been correlated to a greater influx of immune cell infiltration (Pasarica, Gowronska-Kozak, et al., 2009). AT fibrosis also contributes to the metabolic function of the tissue as demonstrated by the improved glucose and lipid metabolism of obese mice lacking collagen VI (Khan et al., 2009). In addition to its metabolic and inflammatory influence, the ECM also has a direct structural impact on the adipocyte. Adipocytes within areas of fibrosis have decreased size and a more limited lipid storage capacity (Khan et al., 2009). In summary, AT fibrosis is an important newfound contributor to the pathophysiology of obesity though much more research is required to truly understand its development and influence.
Growth Hormone
Growth hormone (GH) is an important manipulator of metabolism and adiposity.
It promotes a variety of physiological effects, often positively related to growth. In AT,
GH has the opposite effect, promoting lipolysis and inhibiting lipogenesis (Garten,
Schuster, & Kiess, 2012; Goodman et al., 1991). Because of the inverse and unique relationship of GH and AT, GH transgenic mice have high serum levels of GH and are not only giant but also extremely lean (Berryman et al., 2004). While we would normally associate leanness with a favorable health status, these mice have shortened lifespans and suffer from insulin resistance as well as increased incidence of cancer (Berryman,
Christiansen, Johannsson, Thorner, & Kopchick, 2008). Similarly, humans with 18 acromegaly, an excess of GH in adulthood, suffer from increased blood glucose and insulin levels although women may be affected to a greater degree than men and may be more susceptible to several types of cancers (Ciresi et al., 2013; Ciresi, Amato,
Pizzolanti, & Giordano Galluzzo, 2012; Dagdelen, Cinar, & Erbas, 2013; Renehan et al.,
2003).
GH not only influences AT, but also has been connected with the development of excess ECM in other tissues such has muscle and bone (Doessing, Heinemeier, et al.,
2010; Doessing, Holm, et al., 2010). However, no research has yet been conducted to determine whether GH has an effect on the ECM of AT. Results from a preliminary study conducted in our lab showed that bovine (b) GH mice appear to have greater ECM deposition than their wild type (WT) littermates that intensifies with age (Troike et al.,
2012). A difference between bGH and WT mice is evident at 6 months of age, and thus a group of 6-month-old male mice were selected for this study.
Purpose and Significance of the Study
Bovine GH transgenic mice provide an interesting perspective from which to observe the ECM of AT. While they lack the increased adiposity that defines the obese state, they share obesity-associated complications, such as insulin resistance, diabetes and cancer, suggesting that their AT may exhibit similar dysfunctional characteristics. Their contradictory phenotype allows us to examine unhealthy AT independent of adiposity and to question whether the quality of AT may be the major factor in the complications of obesity, despite obesity itself being defined by the quantity of AT. Since collagen 19 increases in response to GH in other tissues, AT fibrosis is an ideal characteristic to examine.
Other than preliminary studies conducted in our laboratory, no previous research has examined the collagen content in the AT of bGH mice. Consequently, the purpose of this research is to provide a foundation for future inquiry into this subject. The aims of the study, listed below, focus on overall collagen content, adipocyte size, and collagen gene expression as a way to establish whether the collagen content is affected by GH. By achieving these aims, we will establish if GH changes the collagen concentration of AT, if increased collagen decreases adipocyte size in bGH mice as it does in obese mice, and if changes to the collagen concentration are due to differences in collagen gene expression.
Research Aims
Specific Aim 1. To measure the extent of collagen content in the inguinal and epididymal AT depots of bGH and WT 6-month-old male mice.
Hypothesis 1. The collagen content in bGH AT will be greater than that found in
WT mice.
Specific Aim 2. To compare adipocyte size and number in the inguinal and epididymal AT depots of bGH and WT 6-month-old male mice.
Hypothesis 2. The average adipocyte size will be smaller while the average adipocyte number will be greater in the bGH compared to the WT mice. 20
Specific Aim 3. To determine the mRNA expression of collagen genes 1α1, 3α1,
4α1, 5α1 and 6α1 in the inguinal and epididymal AT depots of bGH and WT 6-month-old male mice.
Hypothesis 3. Transcription of the five collagen genes listed above will be up- regulated in bGH mouse AT.
Limitations and Delimitations
1. The mice in this study are relatively young at 6 months of age and the bGH mice
might not have been exposed long enough to the excess GH for there to be a
significant effect on their AT collagen content.
2. The α1 gene of each collagen can be used as an indicator of that collagen’s
expression level, but it might not give a complete picture of the expression of
each collagen.
3. Both picosirus red staining and adipocyte size will be calculated by an average of
nonoverlapping fields from a small slice of the tissue. This might not be an
accurate representation of the differences between the depots or genotypes.
4. Similarly, mouse strains are limited in their ability to relate to human
characteristics and therefore, any phenomenon discovered in mice might not be
applicable to humans. For example, the epididymal depot does not have an
equivalent human AT depot.
Definitions
Adipocyte. A fat-containing cell of AT. 21
Adipose tissue. Connective tissue in which fat is stored and which has the cells distended by droplets of fat.
Adiposity. The quality or state of being fat.
Collagen. An insoluble fibrous protein of vertebrates that is the chief constituent of the fibrils of connective tissue (as in skin and tendons) and of the organic substance of bones and yields gelatin and glue on prolonged heating with water.
Extracellular matrix. The extracellular substance in which tissue cells (as of connective tissue) are embedded.
Fibrosis. A condition marked by increase of interstitial fibrous tissue.
Growth hormone. A vertebrate polypeptide hormone that is secreted by the anterior lobe of the pituitary gland and regulates growth; also: a recombinant version of this hormone.
Inflammation. A local response to cellular injury that is marked by capillary dilatation, leukocytic infiltration, redness, heat, pain, swelling, and often loss of function that serves as a mechanism initiating the elimination of noxious agents and of damaged tissue.
Insulin resistance. Reduced sensitivity to insulin by the body's insulin-dependent processes (as glucose uptake, lipolysis, and inhibition of glucose production by the liver) that results in lowered activity of these processes or an increase in insulin production or both and that is typical of type 2 diabetes but often occurs in the absence of diabetes.
Lipolysis. The hydrolysis of fat. 22
Phenotype. The observable properties of an organism that are produced by the interaction of the genotype and the environment.
All definitions adapted from Medline Plus unless otherwise noted
(http://www.nlm.nih.gov/medlineplus/mplusdictionary.html).
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Chapter 2: Literature Review
Historically, much of AT research has focused on the main cell type, the adipocyte. However, other cell types and tissue components, such as immune cells and the ECM, make up a significant portion of AT and are increasingly studied for their influence on AT function. The ECM is of particular interest because of its connection to inflammation and tissue remodeling. Additionally, GH is of particular interest in AT research because of its effects on lipid and glucose metabolism. This literature review will survey current knowledge of AT, GH, and collagen in an effort to fully describe AT fibrosis.
Overview of Adipose Tissue
AT is a type of loose connective tissues whose primary functions are energy storage, mechanical support, and insulation (Trayhurn & Beattie, 2001). Though it was once thought to be a simple storage tissue, AT has recently been discovered to be incredibly complex and varied. In addition to the classically recognized functions, AT has been found to have a significant endocrine function and is also a regulator of energy homeostasis (Galic et al., 2010; Trayhurn & Beattie, 2001). While the adipocyte is the main cell type in AT, numerous cell types inhabit the tissue, and the composition of the tissue can vary based on the fat depot (Smorlesi et al., 2012). Obesity is defined as excess
AT, and thus understanding the morphology and physiology of AT is important in order to effectively combat the obesity epidemic. 24
White Adipose Tissue and Brown Adipose Tissue
AT is not homogenous and is comprised of two distinctly different types: white adipose tissue (WAT) and brown adipose tissue (BAT). These two tissue types differ in both morphology and physiology. The main cell type in WAT is the white adipocyte.
White adipocytes feature a large lipid droplet and store energy in the form of triglycerides. Brown adipocytes, on the other hand, are distinguished by their many mitochondria and function in nonshivering thermogenesis, which allows them to produce heat. Brown adipocytes express uncoupling protein-1 (UCP-1) that allows the inner mitochondrial membrane to leak ions back across it and ultimately produce heat through oxidative phosphorylation (Richard & Picard, 2011). In addition to differences in main cell types, these two AT types differ in their vasculature and innervation, because BAT is far more vascularized with significantly more innervation than WAT (Nnodim & Lever,
1988). The focus of this study is WAT; thus, the remainder of this review will focus on
WAT exclusively.
Adipose Tissue Depots
AT is found in different regions of the body called depots, which can be distinguished not only by location but also by composition and function (Vanderburgh,
1992). Depot differences have proved to play a role in the health of obese patients, because the distribution of adiposity is associated with variations in metabolic profiles.
For example, studies have shown that individuals with a central pattern of obesity, or more visceral AT, have greater insulin resistance than individuals with peripheral obesity
(Wajchenberg, 2000). Transplantation studies in which AT depots from donor mice are 25 transplanted into a different depot in recipient mice demonstrate that these differences are not simply due to anatomical location (Tran, Yamamoto, Gesta, & Kahn, 2008).
Recipient mice which had subcutaneous AT transplanted into their visceral fat pads have decreased body fat and adipocyte size and improved glucose homeostasis over a 12-week period following transplantation (Tran et al., 2008). The transplantation of intra- abdominal AT into the same region does not have a similar beneficial effect (Tran et al.,
2008). Tran et al. (2008) concluded that secreted factors varied between depots and that the secretory profile of subcutaneous AT is likely responsible for its beneficial effect.
Important to this project, GH has been shown to affect different depots to varying degrees. For example, List et al. (2009) reported that mice with injected GH had the greatest fat loss in their subcutaneous and mesenteric fat pad.
In rodents there are two subcutaneous depots found just under the skin, and several intra-abdominal depots, which are found within the abdominal cavity. In mice, the subcutaneous depots are located both anteriorly and posteriorly (Cinti, 2005). The posterior depots are considered less complex than the anterior subcutaneous depots
(Cinti, 2005). The subcutaneous depot collected for this study was the inguinal depot found posteriorly under the skin in the groin region. There are several intra-abdominal depots, which are further categorized as visceral and nonvisceral although there is some controversy as to how these are defined. Some researchers define visceral depots more strictly and consider only depots that drain into the portal vein to be visceral. Other researchers refer to all depots in the intra-abdominal and visceral regions as visceral
(Cinti, 2005). The intra-abdominal depot used in this study was the epididymal depot, 26 which surrounds the testes. This depot does not drain into the portal vein and is thus not considered a visceral depot by some. For this study, we will follow the strictest definition and consider the epididymal depot to be intra-abdominal but not visceral. Figure 1 depicts four AT depots including the inguinal and epididymal depots.
Figure 1. Adipose tissue depots. Four major AT depots in a male mouse are depicted. The inguinal depot (bottom left) and the epididymal depot (bottom right) are the two depots investigated in this study. The inguinal depot is located just under the skin in the groin region and it is classified as a subcutaneous depot. The epididymal depot is next to the testes. While it is intra-abdominally located, it is not considered a visceral depot by the strictest definition, as it does not drain into the portal vein. Also shown is the mesenteric depot lining the intestines and the retroperitoneal depot behind the kidney (K). From “Depot-Specific Differences in White Adipose Tissue of Wild-Type and GHR-/- Mice of Different Ages,” by Lucila Sackman-Sala, 2010, Doctor of Philosophy, Ohio University, Athens, OH. And from “Growth Hormone and Adipose Tissue: Beyond the Adipocyte,” by D. E. Berryman, E. O. List, L. Sackmann-Sala, E. Lubbers, R. Munn, and J. J. Kopchick, 2011, Growth Hormone and IGF Research, 21, p. 20. Copyright 2011 by Elsevier. Reprinted with permission.
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White Adipocytes
The white adipocyte is the main cell type in WAT and responsible for much of the physiological functions of the tissue. In particular, the adipocyte is responsible for regulating energy balance, utilizing a specialized organelle called a lipid droplet to store energy in the form of triglycerides (Rosen & Spiegelman, 2006). When energy is needed, the adipocyte can release energy through a process called lipolysis (Lass, Zimmermann,
Oberer, & Zechner, 2011).
Although this storage function was once thought to be the only function of the adipocyte, it is now known that these cells have many functions, which include an important endocrine component. Adipocytes and other cell types in AT can secrete and react to numerous hormones and cytokines such as leptin and adiponectin (Kershaw &
Flier, 2004; Trayhurn & Wood, 2004). These AT hormones and cytokines are collectively referred to as adipokines and can have drastic effects on whole body metabolism and energy homeostasis. For example, the hormone leptin is secreted by adipocytes and regulates energy intake, metabolism, and satiety (Klok, Jakobsdottir, &
Drent, 2007). The significance of leptin’s actions is demonstrated by two different types of leptin deficient mice: ob/ob mice and db/db mice. They have a mutation in either the leptin gene (ob/ob) or the leptin receptor gene (db/db) and thus lack effective leptin- induced intracellular signaling (Chen et al., 1996; Pelleymounter et al., 1995). As a result, the mice are strikingly obese and are used for obesity and diabetes studies (Drel et al.,
2006; Kobayashi et al., 2000; Lindstrom, 2007). In addition to the drastic effect on body composition, leptin has also been shown to play a role in bone growth, reproduction, T 28 cell activity, and surfactant expression (Houseknecht, Baile, Matteri, & Spurlock, 1998).
Leptin and other AT hormones have significant whole-body effects that emphasize the importance of the adipose organ and deepen its complexity.
White adipocytes not only respond to hormone induced signaling, but also are subject to modification by other cell types in the tissue such as macrophages. A now classic example of this is the observation that crown-like structures (CLS) are seen when macrophages surround a dying adipocyte (Cancello et al., 2005; Cinti et al., 2005). This is commonly seen in obese WAT as a result of adipocyte death due to hypoxia. The decrease in nutrients and oxygen cause the adipocytes to starve and eventually die.
During this process, they are surrounded by bone-marrow derived macrophages (Murano et al., 2008). The macrophages form a syncytium around the adipocyte and consume the remnants of the lipid droplet (Murano et al., 2008). The CLS have become a hallmark histological trait of obese WAT.
Other Cell Types in Adipose Tissue
AT consists of a variety of cells types other than adipocytes, collectively known as the stromal vascular fraction (SVF), that have been shown to be important to the overall function of the tissue. Cells of the SVF include immune cells (macrophages and mast cells), preadipocytes, vascular tissue cells, neural tissue cells, and fibroblasts (Fain,
Madan, Hiler, Cheema, & Bahouth, 2004; Kershaw & Flier, 2004; Wajchenberg et al.,
2002). These cells can also contribute to the endocrine function of AT and the production of inflammatory cytokines, which may be particularly important in the modification of the tissue in the obese state (Fain et al., 2004; Wajchenberg et al., 2002). 29
Obesity
Obesity is defined as excess AT resulting from both hypertrophic adipocytes as well as an increase in adipocyte number. AT also undergoes characteristic changes in the obese state, indicating that an increase in AT mass might not be the only factor that contributes to obesity-associated diseases such as diabetes and cardiovascular disease.
Namely, obese AT exhibits metabolic dysregulation such as insulin resistance (Martyn,
Kaneki, & Yasuhara, 2008), inflammation (Strissel et al., 2007; Weisberg et al., 2003), and pathologically accelerated remodeling (Strawford, Antelo, Christiansen, &
Hellerstein, 2004). Another recently discovered alteration to AT that occurs during obesity is fibrosis. Fibrosis, or an excess of extracellular matrix proteins, has been shown to be related to these key characteristics of obesity and may be a causal element for some of the dysfunctional changes that occur in the obese state (Khan et al., 2009). This will be further discussed after an introduction to collagen.
Introduction to Collagen
Collagens are a large family of proteins that are found throughout the body and that contribute to many processes including cell adhesion and transport, tissue structure, and angiogenesis. They are of significant interest to this project, because they are the major component of the extracellular matrix of tissues, including AT. Collagen is the most abundant protein family in vertebrates and 28 different vertebral collagens have been discovered to date (Kadler, Baldock, Bella, & Boot-Handford, 2007; Shoulders &
Raines, 2009). 30
Despite their ubiquity, the term collagen is not clearly defined. Generally, collagens are triple helical proteins that function in tissue architecture, but this is not always the case. Collagen-like proteins, which contain helical portions, and other proteins often fit all or part of that description, but are not termed collagens (Kadler et al., 2007).
Conversely, some collagens are more alike than others. Although the definition is nebulous, collagen I is the prototypical collagen, featuring a helical structure and forming macromolecular fibrils (Kadler et al., 2007).
Collagen nomenclature has been developed and refined following the discovery and characterization of more and more collagens. Unfortunately, it is often imprecise and confusing. First, the word “collagen” may be used to refer to a macromolecular structure of associated collagen units such as a fibril, or it may refer to one molecular unit of collagen. In vertebrates, 28 different collagen types have been identified and are numbered in order of their discovery (I-XXVIII) (Kadler et al., 2007). Their subunits, described further below, are also numbered, though the number of subunits varies between collagen types. A collagen subunit name is composed of the collagen type name
(collagen is often shortened to “col”), followed by the symbol alpha, and then the subunit number. Gene names typically use Arabic numerals for the collagen type and subunit while protein names use Roman numerals. Additionally, the uppercase alpha symbol (Α) is used for human collagen genes and proteins and the lowercase (α) is used for mice. For example, the mouse protein subunit one of collagen VI would be written, “COLVIαI”, with a corresponding gene entitled “Col6α1.” 31
Collagen Structure
The classic structural feature of collagen is the triple helix. Each collagen strand forms a right-handed helix that is comprised of three left-handed helical α subunits. The three subunits associate via hydrogen bonds to form a triple helix monomer commonly called a tropomer (Kadler et al., 2007). Tropomers can be homotrimeric or heterotrimeric and typically associate with subunits of the same collagen (Kadler et al., 2007).
However, collagens can also form associative structures with other collagen types
(Kadler et al., 2007). Figure 2 depicts the triple helical structure of collagen.
32
Figure 2: Collagen triple helix. Three collagen subunits aggregate to form a triple helical structure (a), often referred to as a tropomer. Each subunit is a left-handed helix (b) with a repeated sequence with every third residue located in the center of the matrix. Due to steric hindrance of amino acid side chains, glycine is the only amino acid that can occupy this space. Thus, the primary structure follows a repeated sequence of Gly-X-Y (c) where X and Y are most often proline or hydroxyproline. From "Molecular Packing in Network- Forming Collagens,” by C. Knupp and J. M. Squire, 2005, Advances in Protein Chemistry, 70, p. 559. Copyright 2005 by Elsevier. Reprinted with permission.
The amino acid sequence of collagens follows a consistent pattern throughout the protein family. Collagens are rich in glycine, proline, and hydroxyproline−a nonproteinogenic amino acid resulting from posttranslational modification of proline−due to their repeated amino acid sequence: Gly-X-Y (Gorres & Raines, 2010;
Kadler et al., 2007; Knupp & Squire, 2003). In the sequence, X and Y can be any other amino acid although they are usually proline or hydroxyproline (Kadler et al., 2007).
Collagens differ in their primary structures so that the α1 subunit of collagen I, for 33 example, is different from the α1 subunit of collagen II (Kadler et al., 2007). However, the sequences are highly conserved across species, and all of the collagen subunits investigated in this study are highly homologous in mice and humans.
Collagen Synthesis
Collagen undergoes extensive posttranslational modification both inside and outside of the cell (Mariman & Wang, 2010). One of the first modifications is the conversion of some proline residues to hydroxyproline (Gorres & Raines, 2010). This conversion is catalyzed by prolyl 4-hydroxylase (P4H), which adds a hydroxyl group to the 4R position of proline. This conversion only occurs in protocollagen strands and P4H preferentially converts at the Y residue in the Gly-X-Y sequence. Then, the protocollagen strands are assembled into triple helical monomers called procollagen. These procollagen peptides undergo cleavage at the N-terminal and C-terminal ends to achieve the tropomer form and are then secreted into the extracellular space. There, they are assembled into macromolecular collagen structures depending on their collagen type (Fratzl, 2008). The synthesis and processing of collagens is shown in Figure 3 below.
34
Figure 3. Collagen synthesis and formation of structures. Collagen genes are synthesized to form a protocollagen strand. This is one α subunit of the procollagen triple helix. Three α subunits aggregate to form a procollagen triple helix. Cleavage at the N- and C-terminal propeptide ends results in formation of a mature collagen protein, often called a tropomer or tropocollagen. The tropomer is excreted from the cell and self assembles with other collagens of the same type to form a macromolecular structure. Shown in the figure is the formation of a fibril macromolecular structure. Collagens I, III, and V are examples of fibril forming collagens. Fibrils are made by staggering collagen tropomers as shown. The crosslinks between collagen tropomers in the structure increases tensile strength. From “Collagen Structure and Stability,” by M. D. Shoulders and R. T. Raines, 2009, Annual Review of Biochemistry, 78, p. 25. Copyright 2009 by Annual Reviews. Reprinted with permission.
35
Once outside of the cell, collagens self-associate into a number of structures (Kadler et al., 2007). In addition to fibril-forming collagens, collagens also form networks, act as transmembrane proteins, and form beaded filaments as shown in Figures 3, 4, and 5.
Fibril Associated Collagens with Interrupted Triple Helices (FACIT) are both collagens and proteoglycans. Table 1 below lists all vertebrate collagens, their classifications, and the notes about their distribution (adapted from Kadler et al., 2007). Table 2 lists the collagens studied for this project, their subunits, gene names, and whether they are homo- or heterotrimeric.
Table 1
Collagen Types
Collagen name Classification Distribution/remarks
Collagen I Fibril-forming Non-cartilaginous connective tissues- e.g. tendon, ligament, cornea, bone, skin
Collagen II Fibril-forming Cartilage, vitreous humour and nucleus pulposus
Collagen III Fibril-forming Co-distributes with collagen I, especially in embryonic skin and hollow organs
Collagen IV Network-forming Basement membranes
36
Table 1, continued
Collagen V Fibril-forming Co-distributes with collagen I, especially in embryonic tissues and in cornea
Collagen VI Beaded-filament- Widespread, especially muscle forming Collagen VII Anchoring fibrils Dermal-epidermal junction
Collagen VIII Network-forming Descement’s membrane
Collagen IX FACIT Co-distributes with collagen II, especially in cartilage and vitreous humour
Collagen X Network-forming Hypertrophic cartilage
Collagen XI Fibril-forming Co-distributes with collagen II
Collagen XII FACIT Found with collagen I
Collagen XIII Transmembrane Neuromuscular junctions, skin
XIV FACIT Found with collagen I
XV Endostatins Located between collagen fibrils that are close to basement membranes; found in the eye, muscle and microvessels; a close structural homologue of collagen XVIII
XVI FACIT Integrated into-collagen fibrils and fibrillin-1 microfibils
XVII Transmembrane Localized to epithelia; and epithelial adhesion molecule
XVIII Endostatins Associated with basement membranes; endostatin is proteolytically released from the C-terminus of collagen XVIII; important for retinal vasculogenesis
37
Table 1, continued
XIX FACIT Rare; localized to basement membrane zones; contributes to muscle physiology and differentiation
XX FACIT Widespread distribution, most prevalent in corneal epithelium XXI FACIT Widespread distribution
XXII FACIT Localized at tissue junctions – e.g. myotendinous junction, cartilage- synovial fluid, hair follicle-dermis
XXIII Transmembrane Limited tissue distribution; exists as a transmembrane and shed form
XXIV Fibril-forming Shares sequence homology with the fibril-forming collagens; has minor interruptions in the triple helix; selective expression in developing cornea and bone
XXV Transmembrane CLAC-P – precursor protein for CLAC (collagenous Alzheimer amyloid plaque component)
XXVI Beaded-filament Also known as EMI domain- forming containing protein 2, protein Emo2, Emilin and multimerin domain- containing protein 2
XXVII Fibril-forming Shares sequence homology with the fibril-forming collagens; has minor interruptions in the triple helix; found in embryonic cartilage, developing dermis, cornea, inner limiting membrane of the retina and major arteries of the heart; restricted to cartilage in adults; found in fibrillar- like assemblies
38
Table 1, continued
XXVIII Beaded-filament A component of the basement forming membrane around Schwann cells; a von Villebrand factor A domain- containing protein with numerous interruptions in the triple helical domain
Table 2
Collagen Subunits and Structure
Collagen Type Subunits Genes Trimeric structure Collagen I α1, α2 Col1a1, Col1a2 Hetero- and homotrimeric
Collagen III α1 Col3a1 Heterotrimeric
Collagen IV α1, α2, α3, α4, Col4a1, Col4a2, Heterotrimeric α5, α6 Col4a3, Col4a4, Col4a5, Col4a6
Collagen V α1, α2, α3 Col5a1, Col5a2, Hetero- and homotrimeric Col5a3
Collagen VI α1, α2, α3, α5 Col6a1, Col6a2, Heterotrimeric Col6a3, Col6a5
39
Figure 4. Network-forming collagen. Collagen IV forms networks that are part of the basement membrane. The structure is formed by the interaction at globular regions at the N- and C- terminal domains. Two C-terminal domains (shown in blue) interact followed by the linkage of four N-terminal domains (shown in pink) to form the network structure. From “New Functional Roles for Non-collagenous Domains of Basement Membrane Collagens,” by N. Ortega and Z. Werb, 2002, Journal of Cell Science, 115, p. 4204. Copyright 2002 by The Company of Biologists. Reprinted with permission.
Figure 5: Collagen VI forms beaded-filaments. Collagen VI monomers assemble into dimers and then tetramers before forming a long molecular chain. These chains are sometimes referred to as microfibrils and have beaded repeats of 105 nm. Collagen VI also features large globular domains at their N and C terminal ends and shown by the red and blue beads in the figure. From "Molecular Packing in Network-Forming Collagens,” by C. Knupp and J. M. Squire, 2005, Advances in Protein Chemistry, 70, p. 559. Copyright 2005 by Elsevier. Reprinted with permission. 40
Introduction to Collagen in White Adipose Tissue
Collagen is an important tissue component of WAT, making up a considerable portion of noncell mass (Mariman & Wang, 2010). Although collagen is produced by fibroblasts in WAT, evidence also shows that it is partially produced by the adipocytes themselves (Mariman & Wang, 2010). Other cells in the stromal vascular fraction (SVF) can also contribute to the collagen produced in WAT. These cells include preadipocytes, capillary endothelial cells, infiltrated monocytes and macrophages, as well as a population of multipotent stem cells (Mariman & Wang, 2010). While WAT has many of the same collagen proteins as other types of tissue, the relative quantities of these proteins are unique to WAT, and their composition can be affected by developmental stage and depot. Collagens I-VI are represented in WAT ECM although there is very little collagen
II (Mariman & Wang, 2010). In contrast, collagen VI has been identified as preferentially expressed in WAT as compared to other tissues, and as such, collagen VI is of particular importance to WAT fibrosis research as will be discussed below (Khan et al., 2009).
Figure 6 shows the pericellular organization of collagens around an adipocyte.
41
Figure 6. Peri-adipocyte collagen organization. Collagen VI forms a basement membrane, shown above as a thick purple line, encircling each adipocyte. A fibular structure is formed primarily of collagen I with collagens V and VI forming cross-links between fibrils of collagen I as well as between collagen I and cell surface proteins. Other ECM components such as fibronectin, thrombospondin, and SPARC regulate the ECM formation as well as cell shape. From "Peri-adipocyte ECM Remodeling in Obesity and Adipose Tissue Fibrosis,” by T. Chun, 2012, Adipocyte, 2, p. 90. Copyright 2012 by Landes Bioscience. Reprinted with permission.
Adipose Tissue Fibrosis
AT fibrosis has recently been recognized as an architectural change occurring in obese AT (Divoux & Clement, 2011). Although it has not yet been extensively studied, the ECM of WAT may be intimately linked with the key characteristics of obesity, such as metabolic dysregulation, inflammation, and pathologically accelerated remodeling, as will be more thoroughly described below (Sun et al., 2011). Because of its interactions with many tissue processes, the development and influence of WAT fibrosis is complex and not yet fully understood. However, research has shown that collagens are up- 42 regulated in obesity, that fibrosis develops in obese WAT, and that WAT fibrosis may initiate and/or propagate obese WAT dysfunctions such as hypoxia and inflammation
(Divoux et al., 2010; Khan et al., 2009; Sun et al., 2011).
The up-regulation of collagen genes in obesity is clearly demonstrated in db/db mice and ob/ob mice, mutant mice with altered leptin signaling often used as a model for obesity and diabetes. Figure 7 is a graph showing the change in gene expression of major
AT expressed collagens in db/db mice compared to wild type mice (Khan et al., 2009).
Figure 7. Collagen expression up-regulated in obese state. Gene expression of several AT collagens was analyzed in db/db vs. WT mice using microarray analysis. Only the epididymal depot was analyzed. The fold change results show that many collagens were significantly up-regulated in the obese mice (db/db) and that collagen 6a3 was the most effected. Adapted from “Metabolic Dysregulation and Adipose Tissue Fibrosis: Role of Collagen VI,” by T. Khan, E. S. Muise, P. Iyengar, Z. V. Wang, M. Chandalia, N. Abate, . . . P. E. Scherer, 2009, 29, p. 1578. Copyright 2009 by American Society for Microbiology. Reprinted with permission.
These results clearly demonstrate that many collagen genes are significantly up-regulated in the obese state. Ob/ob mice show the same pattern of collagen expression and Col
VIa3 was shown to be the most significantly up-regulated (Khan et al., 2009). Similarly, 43 obese humans also have increased expression of many collagens, as shown in Figure 7, and other ECM-associated genes in both subcutaneous and visceral WAT depots (Divoux et al., 2010; Henegar et al., 2008). However, collagen VI may be less important in the development of AT fibrosis in humans than it is in rodents (Tam, Tordjman, Divoux,
Baur, & Clement, 2012).
As previously mentioned, AT features many of the same collagen types as other connective tissues. However, collagens I, III, IV, V, and VI have been identified as particularly important ECM components implicated in the process of AT fibrosis in both humans and mice (Divoux et al., 2010; Mariman & Wang, 2010; Spencer et al., 2011).
Collagens I and III are abundant throughout the body, have increased expression in WAT during obesity, and contribute to WAT fibrosis (Mariman & Wang, 2010). Collagen IV provides a thick basal lamina that surrounds each adipocyte and may be necessary for the survival of the cell by aiding in the mechanical support of the lipid droplet and preventing disruption in the obese state (Mariman & Wang, 2010). Additionally, collagen V has been implicated in angiogenesis in WAT, and an increase of this collagen is associated with fewer small vessels resulting in hypoxia (Spencer et al., 2011).
Of particular importance, collagen VI has been of interest in many studies on
WAT fibrosis as it is preferentially expressed in WAT (Khan et al., 2009; Mariman &
Wang, 2010). Collagen VI binds strongly to collagen IV suggesting that it may be important in anchoring the basement membrane; can interact with other matrix proteins such as proteoglycans and fibronectin; and, is up-regulated during metabolic challenges in both mice and humans. Transgenic mice lacking collagen VI (ob/ob ColVIKO mice) 44 have improved metabolic phenotypes despite their severely obese phenotype and larger adipocyte size. Specifically, the study shows that the elimination of collagen VI decreases inflammation and increases insulin sensitivity in the mice (Khan et al., 2009). This improved metabolic phenotype despite increased adiposity suggests that collagen VI is an important ECM component of WAT and may have a role in the metabolic regulation of that tissue.
Introduction to Growth Hormone
Growth hormone (GH) is a peptide hormone generally recognized for its anabolic functions as it encourages cell growth and repair in most tissues (Isaksson, Eden, &
Jansson, 1985; Kasukawa, Miyakoshi, & Mohan, 2004). GH is comprised of a 191 amino acid chain and is secreted by somatotrophs in the anterior pituitary gland (Tannenbaum &
Ling, 1984). The protein exists in several forms with the 22 kDa and 20 kDa being most predominant. Most refer to GH as the 22 kDa form (Chawla, Parks, & Rudman, 1983). It acts through interaction with the GH receptor (GHR) (Brooks & Waters, 2010). GH gene expression is influenced by other hormones and has a complex regulatory system as will be discussed below.
Growth Hormone Secretion and Signaling
GH secretion from the anterior pituitary is neurally controlled by hormonal signals from the hypothalamus, and the secretion occurs in a pulsatile manner
(Tannenbaum & Ling, 1984). The hypothalamus secretes GH releasing hormone
(GHRH), somatostatin or somatotropin-release inhibiting factor (SRIF), and ghrelin, which is also secreted from the stomach. GHRH is released from the hypothalamus into 45 the pituitary portal system and signals through the growth hormone releasing hormone receptor (GHRH-R). Through its interaction with the GHRH-R, GHRH increases the release of GH from secretory granules in the somatotroph cells and increases GH transcription (Karin, Theill, Castrillo, McCormick, & Brady, 1990; Mayo, 1992).
Alternatively, SRIF works to inhibit the release of GH from somatotrophs. SRIF is also secreted by the hypothalamus and interacts with the somatotropin-release inhibiting factor receptor (SRIF-R) (McCormick, Brady, Theill, & Karin, 1990). This G- coupled receptor works to inhibit GH secretion by blocking cAMP activity (McCormick,
Brady, Theill, & Karin, 1990).
Ghrelin and other GH releasing peptides (GHRPs) work similarly to GHRH and bind to the GH secretagogue receptor (GHS-R) (Pong et al., 1996). Ghrelin is primarily secreted by the stomach but is also produced by other tissues such as the hypothalamus, the pancreas, and the pituitary itself (Kojima et al., 1999). Uniquely, ghrelin is also influenced by food intake and is involved in energy homeostasis (Fukushima et al.,
2005).
GH signals by binding to the GHR, which is expressed in many tissues throughout the bodies of mice and humans including liver, AT, kidney, and muscle (Ballesteros,
Leung, Ross, Iismaa, & Ho, 2000; Oppenheim, Feldman, & Durum, 2001). GHR is a glycoprotein that spans the cell membrane and has both extracellular and intracellular domains (Oppenheim et al., 2001). It exists in the cell membrane as a preformed dimer
(Yang, Wang, Jiang, & Frank, 2007). When activated by GH binding, the receptor 46 subunits realign to initiate a signaling cascade (Brooks & Waters, 2010). Figures 8 and 9 demonstrate the activation of GHR and the subsequent signaling cascade.
Figure 8. Activation of the growth hormone receptor. GHR exists in the cell membrane as a preformed dimer. The receptor is shown in the absence of GH on the left and after GH (shown in blue) binds on the right. When GH binds to both subunits of the extracellular domain of GHR, the receptor subunits realign themselves. Fluorescence resonance energy transfer experiments have shown that the box 1 portions of the intracellular domain move away from one another and permit initiation of the intracellular signaling cascade. From "The Growth Hormone Receptor: Mechanism of activation and Clinical Implications,” by A. J. Brooks and M. J. Waters, 2010, Nature reviews. Endocrinology, 6(9), p. 520. Copyright 2010 by Nature Publishing Group. Reprinted with permission.
The extracellular domain of GHR is also found independent of the rest of the receptor and is known as GH binding protein (GHBP) (Baumann, 2002; Baumann,
Stolar, Amburn, Barsano, & DeVries, 1986). GHBP binds to some of the GH in plasma, 47 increases half-life of GH, and acts as a buffer against the surges of GH due to its pulsatile release (Baumann, 2002; Baumann et al., 1986).
After GH binds to the GHR, the receptor transmits an intracellular signal through a signaling cascade. The first cellular response to GH binding is the binding of Janus kinase 2 (JAK2) to the intercellular domain of the GHR (Zhu, Goh, Graichen, Ling, &
Lobie, 2001). JAK2 then initiates a tyrosine phosphorylase cascade. The signaling cascade begins with JAK2 itself and continues with a number of other signaling proteins through various signaling pathways (Zhu et al., 2001). These pathways include STATs,
IRSs, and GTPase pathways as shown in Figure 9.
Figure 9. Simplified diagram representing the mechanism of growth hormone signal transduction. GH binding to the predimerized receptor results in the association of JAK2 to the GHR and a subsequent signaling cascade. JAK2 can activate a number of signaling molecules. This figure represents the major groups activated by JAK2 including STATs, IRSs, PI-3 K, GTPases, and MAPKs. From “Signal Transduction Via the Growth Hormone Receptor,” by T. Zhu, E. L. Goh, R. Graichen, L. Ling, and P. E. Lobie, 2001, Cellular Signaling, 13(9), p. 602. Copyright by Elsevier 2001. Reprinted with permission. 48
Growth Hormone Function
The importance of GH and its general functions have long been appreciated and researched. GH is best known for its role in promoting postnatal somatic growth of most tissues through promoting differentiation of bone and AT and in increasing both cell size and the number of cells (Isaksson et al., 1985; Kasukawa et al., 2004). However, in AT,
GH takes on an additional role by mediating lipid metabolism. GH increases the release of free fatty acids (FFAs) from AT by stimulating lipolysis and inhibiting lipogenesis
(Christiansen et al., 1990; Moller & Jorgensen, 2009). GH also has a role in glucose metabolism. It is a counter-regulatory hormone and works in opposition to insulin to increase blood glucose levels (Jeffcoate, 2002; Rabinowitz & Zierler, 1963).
Another key role of GH is the simulation of insulin-like growth factor-1 (IGF-1) production. This hormone is primarily secreted by the liver but can also be involved in autocrine and paracrine signaling in peripheral tissues (Isaksson, Lindahl, Nilsson, &
Isgaard, 1987). Like GH, it is a potent growth factor that stimulates somatic growth.
However, unlike GH, IGF-1 does not affect lipolysis or lipogenesis in AT (Jones &
Clemmons, 1995; Yuen & Dunger, 2007). In fact, counter to GH, IGF-1 has an insulin- like effect in AT and is insulin sensitizing (Jones & Clemmons, 1995; Yuen & Dunger,
2007). IGF-1 is also an important component of the GH signaling feedback loop. A summary of GH secretion, action, and feedback is shown in Figure 10. 49
Figure 10. Summary of growth hormone secretion and action. GH secretion from the anterior pituitary is stimulated GHRH and suppressed by SST. The release of GH is pulsatile as shown in the GH/Time graph. After secretion, GH travels through the blood stream to its target tissues including liver, bone, muscle, heart, kidney, and fat (AT). GH signaling via GHR on target tissues causes an increase in IGF-1 serum concentrations. This increase feeds back both to the target tissues inducing further growth promotion and to the hypothalamus and pituitary where it inhibits GHRH and GH release. Adapted from “Growth Hormone (GH), GH Receptor, and Signal Transduction,” by J. J. Kopchick and J. M. Andry, 2000, Molecular Genetics and Metabolism, 71, p. 295. Copyright Elsevier 2000. Reprinted with permission.
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Insights into Physiological Effect of GH Action through Examination of GH
Transgenic Mice
Altered levels of GH can drastically affect body composition through both GH’s anabolic activity and its lipolytic activity (Christiansen et al., 1990; Moller & Jorgensen,
2009; Nam & Lobie, 2000). Numerous studies have demonstrated that GH deficient adults and children have increased adiposity and that GH treatment decreases adiposity
(Abrahamsen et al., 2004; Carroll et al., 2004; Chihara, Fujieda, Shimatsu, Miki, &
Tachibana, 2010; Collipp et al., 1973). The connection between adiposity and GH signaling is clearly demonstrated by bovine (b) GH transgenic mice (Berryman et al.,
2004).
BGH mice were created by inserting bGH DNA into C57BL/6J embryos through pronuclear injection (Berryman et al., 2004). Thus, they express bGH endogenously.
Bovine GH was chosen because it does not bind to the prolactin receptor, thus simplifying interpretation of their phenotype. The characteristic phenotype of these animals includes high plasma levels of both GH and IGF-1 (Dominici, Cifone, Bartke, &
Turyn, 1999). They also have greater expression of both GHR and GHBP (Sotelo et al.,
1995). BGH mice are characterized by increased body size, increased lean body mass, and decreased fat mass when compared to wild type mice (Yang, Striker, Pesce, et al.,
1993). BGH mice are analogous to acromegalic humans who overproduce GH, often due to a GH secreting pituitary tumor. These individuals also have a lean body composition with decreased fat mass and increased lean mass (Katznelson, 2009). By studying the 51 phenotypes of bGH mice, researchers can gain insight into the effects of excess GH on growth, metabolism, and disease processes in vivo.
GH is a diabetogenic molecule and is known to influence both lipid and carbohydrate metabolism (Moller & Jorgensen, 2009; Nam & Marcus, 2000). Thus, bGH mice experience decreased insulin sensitivity, although they have normal plasma insulin levels, as well as other alterations to metabolic parameters (Balbis, Dellacha, Calandra,
Bartke, & Turyn, 1992). Notably, lipid and lipoprotein metabolism is altered. BGH mice have high levels of total cholesterol, HDL, and LDL but low levels of VLDL (Olsson et al., 2005). All of these altered metabolic parameters exhibited by bGH mice are mirrored in acromegalic patients (Hansen et al., 1986).
In addition to the drastic alterations to body composition and metabolism, both humans and mice with excess GH suffer from a number of negative health outcomes.
High levels of GH lead to extensive kidney damage and may result in renal disease, glomerulosclerosis, and glomerulonephritis (Yang, Striker, Pesce, et al., 1993). In bGH mice, glomerulosclerosis increases with age and fibrotic areas are rich in collagens I and
IV (Doi et al., 1991). High levels of GH have also been shown to impair cardiovascular function (Bollano et al., 2001). In addition, GH is associated with a shortened lifespan in both transgenic mice and untreated acromegalic humans (Orme, McNally, Cartwright, &
Belchetz, 1998; Wolf et al., 1993). However, it is not apparent whether the altered lifespan is due to the excess GH or due to other factors such as IGF-1 levels and body size (Bartke, 1998; Bartke et al., 1998). A summary bGH and WT mouse phenotypic characteristics is shown in Figure 11. 52
Figure 11. Overview of bovine growth hormone transgenic mouse phenotype compared to wild type.
Depot Specific Response to Growth Hormone
GH does not affect all depots equally, and research suggests that the subcutaneous depot may be more significantly affected by GH induced signaling (Berryman et al.,
2010). This is most apparent when examining mice with little to no GH signaling such as
GHR -/- mice. These mice are obese but their fat mass is not increased equally among depots (Berryman et al., 2010). Rather, the largest accumulation of fat occurs in the subcutaneous fat pad. This finding emphasizes the importance of examining more than one depot when examining the AT in these mouse models.
Conclusion
AT fibrosis has been recognized as a key contributor to the dysfunction of obese
AT. The unique phenotype of bGH mice–unhealthy leanness–allows us to examine this characteristic of obese AT independent of adiposity. GH’s promotion of collagen 53 deposition in other tissues makes AT fibrosis an ideal characteristic to evaluate in these animals. As has been established in this literature review, collagens I, III, IV, V and VI have been identified as important in the development of AT fibrosis and thus will be investigated in this project. In addition, adipocyte size will be examined as fibrosis has been shown to decrease adipocyte size. Lastly, previous research has shown that differences in AT is not consistent across depots. Therefore, multiple depots were be examined in this project.
54
Chapter 3: Methodology
Animals
Development and breeding of bGH transgenic mice has been described previously
(Berryman et al., 2004). For this study, 8 bGH 6-month-old male mice and 8 male littermate control WT mice were used. All mice were housed in the facility at the Edison
Biotechnology Institute, kept on a 14-hour light/10-hour dark cycle, and had ad libitum access to water and normal chow. The Ohio University Institutional Animal Care and Use
Committee approved all procedures.
Body Composition
Body composition and body weight were measured the day before dissection.
Body weight was measured using a Mettler Toledo PL 202-S balance and body composition was measured using the Minispec mq Benchtop Nuclear Magnetic
Resonance (NMR) analyzer (Bruker Instruments, minispec ND2506). The fat, liquid, and lean masses of the mice were measured in grams as well as percentages of total body weight.
Adipose Tissue Samples
Mice were sacrificed by cervical dislocation. Four distinct AT depots were gathered and weighed: subcutaneous (using the inguinal pad), epididymal, mesenteric, and retroperitoneal. The right and left portions of each AT depot were dissected separately. One was flash frozen in liquid nitrogen and stored at -80 °C; this portion was used for mRNA studies. The other portion was fixed in a 10% formalin solution, then 55 rinsed and stored in a 70% ethanol solution after 24 hours. This portion was used for histological measurements.
Immunohistochemistry
Formalin-fixed tissues from the subcutaneous and epididymal depots were sent to
AML Labs (Baltimore, MD) for paraffin embedding, sectioning, and staining. Sample slices were stained with picosirus red, which stains for all collagens. Slides were analyzed using a Nikon Eclipse E600 microscope. Images for both collagen staining and cell size were obtained using a Spot RT digital camera at 200X magnification. For collagen staining, pictures of 20 nonoverlapping fields were taken per depot and then analyzed using ImageJ (Carriel et al., 2011). To quantify collagen staining, a threshold was set to identify the amount of stained area in each picture and ImageJ calculated the ratio of stained area vs. total area. Cell size and number were analyzed as previously described (Chen & Farese, 2002; Tchoukalova et al., 2010).
RNA Isolation and cDNA Synthesis
Frozen AT from the subcutaneous and epididymal depots was homogenized using the Fisher brand Disposable Pestle Grinder System with disposable pestles (Fisher
Scientific). RNA was then isolated using Trizol (Invitrogen) reagent according to the manufacturer’s instructions and then purified using the RNeasy mini kit (Qiagen). The isolation procedure is detailed in Appendix A. The RT2 First Strand kit (SA Biosciences) was used for cDNA synthesis following the manufacturer’s protocol. 56
Real-time Polymerase Chain Reaction
Custom Profiler RT2 PCR Array plates (SA Biosciences) were designed using a
96-well plate format. The plate design included 5 collagen genes, 3 housekeeping genes, and 2 plate controls listed below in Table 3. The housekeeping genes were selected for their stability in both WAT depots (Wang, 2012). The primer sequences are proprietary information and not released by SA Biosciences. The full plate design is shown in
Appendix B.
Table 3 Collagen Genes
Gene Name Abbreviation Relationship to obesity
Collagen 1a1 NM_007742.3 Significantly up-regulated in obesity
Collagen 3a1 NM_009930.2 Significantly up-regulated in obesity Collagen 4a1 NM_009931.2 Significantly up-regulated in obesity Collagen 5a1 NM_015734.2 Significantly up-regulated in obesity Collagen 6a1 NM_009933.4 Significantly up-regulated in obesity Eif3f NM_025344.2 Housekeeping gene Rps3 NM_012052.2 Housekeeping gene B2m NM_009735.3 Housekeeping gene
The plates were prepared by the manufacturer using RT2 Primer Assays. Each plate was then loaded with the cDNA from one bGH and one WT sample repeated in triplicate as well as SYBR Green Master Mix (Invitrogen). Gene expression was determined by RT qPCR performed on an Mx3000p PCR instrument (Stratagene).
Cycling conditions were performed according to the manufacturer’s instructions for the 57
Stratagene machine. The first cycle ran for 10 minutes at 95 ºC. This was followed by 40 cycles of heating to 95 ºC for 15 seconds followed by a minute at 60 ºC which fluorescence data collection occurred.
Statistics
Statistics were analyzed using Statistical Package for the Social Sciences (SPSS version 17.0, 2008; IBM, Armonk, NY). Data are shown as mean ± SEM. Genotype and depot differences for body weight, composition, tissue weight, staining, cell size, and cell numbers were subjected to a univariate analysis of variance (two-way ANOVA). Within- and between-group comparisons were then analyzed using a one-way analysis of variance followed by contrast tests. Corrected degrees of freedom were used if the groups failed
Levene’s test for homogeneity of variance (p < .05). Gene expression data were analyzed using the Sabio Sciences web-based PCR data analysis according to the manufacturer’s instructions. Differences were considered to be statistically significant at p < .05.
58
Chapter 4: Results
The purpose of this study was to compare collagen content and collagen gene expression in the WAT of bGH and WT mice. Preliminary research suggested that bGH mice had greater WAT collagen content than the WT controls, which continued to increase with age in both mouse group. The difference between bGH and WT mice in collagen content was evident by 6 months of age. Therefore, 8 bGH and 8 WT male, 6- month-old mice were used for this study. To confirm that the giant, lean phenotype associated with bGH mice was consistent in the mice used for this study, total body weight and body composition were measured the day before dissection. Also, depot weights were measured during dissection. Then, multiple measures were obtained to determine whether GH had an effect on collagen content in the WAT of the mice.
Specifically, quantification of collagen staining was measured using picosirus red-stained histological WAT samples and compared between genotypes and depots. In addition, adipocyte cell size was measured to determine the relationship between adipocyte size and collagen concentration, and cell number was calculated. RNA expression was assessed using RT-qPCR to determine if differences in collagen concentration were due to differences in collagen gene expression.
Body Weight and Composition
A comparison of average body weight and body composition of WT and bGH mice is shown in Figures 12 and 13. As expected, total body weight and lean and fluid weights were significantly greater in the bGH mice, while the WT mice had greater fat tissue weight. 59
Relative tissue weights were also calculated as a percentage of total body weight.
These relative tissue weights are shown in Figure 14. There was not a significant main effect of genotype on relative tissue weights. However, a significant difference due to tissue type and to the interaction of genotype and tissue type was found. When genotype differences were compared between each tissue type with one-way ANOVA, there was a significantly lower percentage of fat and significantly higher percentage of lean in the bGH mice when compared to WT mice. There was not a significant difference in the percentage of fluid between genotypes.
60 * 50
40
30 WT bGH 20 Average Body Weight (g) Weight Body Average 10
0 WT bGH
Figure 12. Comparison of average body weight wild type and bovine growth hormone transgenic mice at 6 months of age. Body weight was significantly different between genotypes when compared using a two-way ANOVA (F1,14 = 141.083, p = 1.1 x 10-8) as denoted by the asterisk.
60
45
40 *
35
30
25 WT
20 bGH Weight (g) Weight 15 10 * 5 * 0 Fat (g) Lean (g) Fluid (g)
Figure 13. Comparison of body composition in wild type and bovine growth hormone transgenic mice at 6 months of age. Fat, lean, and fluid weights were significantly different between genotypes when compared by univariate analysis (F1,42 = 247.993, p = -19 3.1 x 10 ). Differences were also significant between tissue types (F2,42 = 22599.153, p -45 = 9.6 x 10 ) as well as the interaction of depot and genotype (F2,42 = 249.522, p = 4.9 x 10-24). A one-way ANOVA with contrast tests was used to further analyze differences between genotypes and found that the effect of genotype was significant in fat (t = 3.939, p = 0.004), lean (t = 20.493, p = 1.1 x 10-11), and fluid weights (t = 11.738, p = 1.3 x 10-8) as denoted by the asterisk.
61
90 * 80 70 60
50 WT
40 bGH 30 20 Relative Body Composition (%) Body Composition Relative 10 * 0 % Fat % Lean % Fluid
Figure 14. Comparison of body composition relative to total body weight in wild type and bovine growth hormone transgenic at 6 months of age. When compared using univariate analysis, the main effect of genotype was not significant (F1,42 = 0.600, p = 0.443) but significant differences were found between tissue type (F2,42 = 3179.152, p = -46 - 1.4 x 10 ) and the interaction of genotype and tissue type (F2,42 = 44.150, p = 4.7 x 10 11). A One-way ANOVA followed by contrast tests found that there was significantly less percent fat (t = 7.454, p = 3.3 x 10-9) and significantly greater percent lean (t = 5.763, p = 8.7 x 10-7) in the bGH mice when compared to WT mice as indicated by asterisks. There was not a significant difference in percent fluid between genotypes (t = 0.350, p = 0.728).
Adipose Tissue Depot Weights
The average subcutaneous, epididymal, retroperitoneal, and mesenteric adipose tissue weights at dissection are shown in Figure 15. Depot weight differed significantly between genotypes. Weights were also significantly different between depots, but the interaction of genotype and depot did not have a significant effect.
Average relative depot weights as percentages of total body weight are shown in
Figure 16. As with the average depot weights, the relative depot weights differed 62 significantly between depots and between genotypes. In contrast to actual tissue weight, there was also a significant effect of the interaction between genotype and depot.
1.2
1
0.8 * 0.6 WT 0.4 bGH * Actual Tissue Weight (g) Weight Tissue Actual 0.2 * * 0 SubQ Epi Retro Mes Depot
Figure 15. Adipose tissue depot weights in 6-month-old male bovine growth hormone transgenic and wild type mice. bGH tissue weights were significantly lower when -6 analyzed by univariate analysis (F1,56 = 26.3232, p = 3.7 x 10 ). When genotype was compared between depots using one-way ANOVA followed by contrast tests, all depots were significantly lower in the bGH mice as indicated by an asterisk (subq: t = 2.221, p = 0.050; epi: t = 2.635, p = 0.027; retro: t = 3.634, p = 0.007; mes: t = 3.974, p = 0.004). Relative depot weights were also significantly different between depots (F3,56 = 43.283, p = 1.3 x 10-14) but the interaction of genotype and depot was not significantly different (F3,56 = 1.958, p = 0.131).
63
3.5
3
2.5
2
1.5 WT * bGH 1
Relative Tissue Weight (%) Weight Tissue Relative 0.5 * * * 0 SubQ Epi Retro Mes Depot
Figure 16. Relative adipose tissue depot weights in 6-month-old male bovine growth hormone transgenic and wild type mice. Differences in relative weight were significant -11 -16 between genotype (F1,56 = 72.831, p = 1.0 x 10 ), depot (F3,56 = 51.048, p = 4.9 x 10 ), and the interaction of genotype and depot (F3,56 = 7.505, p = 0.0003) when analyzed by two-way ANOVA. One-way ANOVA followed by contrast tests was run and showed that genotype differences were significant within each depot as indicated by the asterisks (subq: t = 4.448, p = 0.002; epi: t = 4.889, p = 0.001; retro: t = 4.603, p = 0.002; mes: t = 5.520, p = 0.001).
Quantification of Picosirus Red Staining
The percentage of stained image area to total image area was calculated for both the subcutaneous and epididymal depots in 6-month-old WT and bGH male mice using
Image J. Examples of images from picosirus red stained WAT are shown in Figure 17.
To calculate the percentage of stained area in each image, upper and lower color saturation thresholds were set in Image J to establish selection criteria for the picosirus red staining. The thresholds were then applied to each image and the software calculated the area that the selected area (i.e., stained area) filled as a percent of the total area of the image. The average percentage for each depot in both the WT and bGH mice is shown in 64
Figure 18. There was a significant difference between genotype, depot and the interaction between genotype and depot.
The percentage of stained area for each depot is also shown as a distribution in
Figure 19. In addition to having a greater average percentage stained area, the bGH subcutaneous samples had much more irregular staining, with images varying in stained area from < 10% to < 70%. Figure 20 shows a low magnification image that further demonstrates the variability of collagen distribution throughout the bGH subcutaneous depot.
65
Figure 17. Collagen content in the subcutaneous and epididymal depots of wild type and bovine growth hormone transgenic mice at 6 months of age. Picosirus red stain, which stains for all collagens, appears higher in bGH mice compared to WT littermates, especially the subcutaneous depot. Smaller adipocytes are also visibly evident in the subcutaneous depot of bGH mice.
66
30 * 25
20
15 WT 10 * bGH
5 Average Percent Total Area (%) Area Total Percent Average 0 SubQ Epi Depot
Figure 18. Average percentage of picosirus red stained area versus total area of adipose tissue depots. There was a significant difference between genotype (F1,28 = 22.818, p = -5 -6 5.1 x 10 ), depot (F1,28 = 36.259, p = 1.7 x 10 ), and the interaction of genotype and depot (F1,28 = 11.494, p = 0.002) when analyzed with a two-way ANOVA. One-way ANOVA followed by contrast tests showed that these relationships were maintained when comparing genotypes and depots separately. The bGH mice had significantly greater average stained area when compared to WT mice in both the subcutaneous (t = 4.241, p = 0.003) and epididymal depots (t = 2.565, p = 0.023) as indicated by asterisks. In addition, there were depot differences between both the bGH (t = 4.998, p = 0.001) and WT mice (t = 3.906, p = 0.002).
67
180 160 140 120 100 WT SubQ 80 bGH SubQ 60 WT Epi Number of Images Number 40 bGH Epi 20 0 <10% <20% <30% <40% <50% <60% <70% Percent Stained Area (%)
Figure 19. Distribution of picosirus red stained area in different depots. Both WT depots and the bGH epididymal depot show very little variation in stained area percentage and no samples have greater than 20% staining. Alternatively, the bGH subcutaneous depot staining varies greatly from < 10% to < 70% picosirus red stained area.
68
Figure 20. Picosirus red stained white adipose tissue from the bovine growth hormone transgenic mouse inguinal depot at 4X magnification. The varied distribution of collagen content throughout the depot is evident. Some areas, such as the top center and middle left, have a large concentration of collagen and small adipocytes. Other areas, such as the bottom left, have much less collagen and larger adipocytes.
Adipocyte Size and Number
Adipocyte size was also measured and is shown in Figure 21. There was a significant main effect of genotype on cell size with bGH mice having a smaller average adipocyte size in all depots. Depot and the interaction of genotype and depot differences were also significant. 69
In addition, adipocyte number within a depot was estimated by a calculation based on adipocyte size and depot weight. Average adipocyte number for the subcutaneous and epididymal depots is shown in Figure 21. Significant main effects of genotype, depot, and the interaction of genotype and depot are seen. However, further analysis with contrast tests revealed that this relationship was maintained in the subcutaneous, mesenteric, and retroperitoneal depots but not in the epididymal depot. In addition, the three significant bGH depots have greater cell numbers than WT, while the epididymal depot, though not significant, showed a trend toward fewer cells than WT.
70
30000
25000
20000
15000 WT * * bGH 10000 * Adipocyte Size (µm2) (µm2) Adipocyte Size 5000 *
0 SubQ Epi Retro Mes
Figure 21. Average adipocyte size in 6-month-old male bovine growth hormone transgenic and wild type mice. A two-way ANOVA compared adipocyte size among genotypes and depots. Significant main effects were found for genotype (F1,302 = 130.693, -25 -38 p = 2.2 x 10 ), depot (F3,302 = 79.220, p = 7.9 x 10 ), and the interaction of genotype -7 and depot (F3,302 = 11.962, p = 2.0 x 10 ). A one-way ANOVA was also completed to further analyze the effect of genotype. A significant difference was found between bGH -54 and WT cell size (F7,302 = 61.238, p = 2.7 x 10 ). Contrast tests were used to determine the nature of the differences and found that adipocyte size was significantly smaller in the bGH mice in all depots (subq: t = 3.033, p = 0.004; epi: t = 3.670, p = 0.001; retro: t = 7.695, p = 1.1 x 10-10; mes: t = 10.404, p = 2.5 x 10-13).
71
1200000 *
1000000 *
800000
600000 WT bGH 400000 Adipocyte Number Adipocyte Number
200000 *
0 SubQ Epi Retro Mes
Figure 22. Average adipocyte number in 6-month-old male bovine growth hormone transgenic and wild type mice. Significant differences were found between genotypes -19 (F1,302 = 9.255, p = 0.003), depot (F3,302 = 34.514, p = 3.3 x 10 ), and the interaction of -7 genotype and depot (F3,302 = 11.842, p = 2.4 x 10 ) when comparing cell size by univariate analysis. A one-way ANOVA was performed to further analyze the genotype -23 differences and found significance between groups (F7,302 = 21.616, p = 1.3 x 10 ). Subsequent contrast tests found significant differences between genotypes in the subcutaneous (t = 2.390, p = 0.020), retroperitoneal (t = 2.182, p = 0.035), and mesenteric (t = 6.732, p = 9.3 x 10-9) depots but not in the epididymal depot (t = 1.591, p = 0.118).
RNA Expression
The expression levels of collagen genes Col1a1, Col3a1, Col4a1, Col5a1, and
Col6a1 were measured through RT-qPCR using an n = 6 for each group. The Ct values were analyzed using RT2 Profiler PCR Array Data Analysis software provided by the manufacturer. The average delta CT, 2^-delta Ct, and fold change are shown in Figures
23, 24, and 25 respectively. The Sabio Sciences does not offer the types of analyses we performed on the other data, and its output is inconsistent. Thus, though the three figures are all based on the same set of raw data, each type of calculation provides different important analytical information for the interpretation of the data. 72
Delta Ct values are shown to illustrate the variability in our data (see Figure 23).
These are the only figures with error bars available. The software does not provide error calculations for the other measures and it cannot be calculated independently, because raw values are not given. The 2^-delta Ct values are analyzed for significance (see Figure
24). There was not a significant effect of genotype; however, the effect of depot seems to create a trend toward higher expression in the epididymal depot with Col6a1 expression significantly greater in both bGH and WT mice. This depot effect is seen even more clearly in the fold change data (see Figure 25).
8
6 WT SubQ
4 bGH SubQ
WT Epi 2 bGH Epi 0 RNA Expression (Delta Ct) Ct) (Delta Expression RNA
-2 Col1a1 Col3a1 Col4a1 Col5a1 Col6a1
Figure 23. Comparison of Delta Ct values between 6-month-old bovine growth hormone transgenic and wild type male mice. Average delta Ct values are calculated relative to control genes. Greater Ct values are associated with lower expression levels. Error bars are shown to demonstrate the data variability.
73
2.5 ) 2
1.5 WT SubQ bGH SubQ
1 WT Epi bGH Epi 0.5 RNA Expression (2^-DeltaCt Expression RNA * * 0 Col1a1 Col3a1 Col4a1 Col5a1 Col6a1
Figure 24. Comparison of 2^-Delta Ct values between 6-month-old bovine growth hormone transgenic and wild type male mice. Differences between values were not significant for most genes when compared to the WT subcutaneous depot. However, collagen6a1 was significantly more expressed in both the WT and bGH epididymal depot (p < .05).
74
3
2.5
2 WT SubQ
1.5 bGH SubQ WT Epi Fold ChnageFold 1 bGH Epi
0.5
0 Col1a1 Col3a1 Col4a1 Col5a1 Col6a1
Figure 25. Comparison of the fold change in collagen gene expression between 6-month- old bovine growth hormone transgenic and wild type male mice. Fold change is shown relative to the expression in the WT subcutaneous depot. Though the Sabio Sciences software did not provide statistical analysis to test for significance in fold change, there does appear to be a significant effect of depot. Expression of collagens 3a1, 4a1, 5a1 and 6a1 in seem greater in the epididymal depot in both bGH and WT mice.
75
Chapter 5: Discussion
Overview
The unique phenotype of bGH mice, unhealthy leanness, allows us not only to analyze GH’s influence on WAT, but also to put our findings within the context of obese
WAT. The purpose of the present study was to analyze the influence of GH on the collagen content of WAT, and its outcomes are relevant to both the GH and obesity fields. The major findings of this study reveal significant differences between genotypes in collagen staining as well as cell size. However, our gene expression data showed that these differences were not due to changes in gene expression levels, but might be due to posttranscriptional modifications or enzymatic changes. We conclude that GH increases the collagen content of WAT, but the mechanism is still unclear.
Body Composition and Adipose Depot Mass
GH has long been recognized to have a potent effect on body composition. The animals used in this study had the same pattern of body composition changes as previously described in bGH mice at similar ages (Berryman et al., 2004, 2006; Palmer et al., 2009; Yang, Striker, Kopchick, et al., 1993). However, our results revealed more pronounced differences between the two genotypes than prior studies. In the current study, the bGH mice had greater overall body mass, more lean mass, and less fat mass than their WT littermates; all measures reached statistical significance. In contrast, previous studies on bGH male mice have not found statistically significant differences when comparing absolute fat mass at 6 months (Berryman et al., 2004, 2006, 2010). A longitudinal body composition study found that whole body mass as well as lean and 76 fluid masses were significantly greater in the bGH mice from 6-52 weeks (Berryman et al., 2010). However, absolute fat mass was greater in the bGH mice until 16 weeks of age and was not statistically lower than WT mice until 36 weeks of age. Relative fat mass followed the same pattern but the percent fat mass was significantly lower in the bGH male mice at 24 weeks. Another study conducted on 6-month-old bGH and WT male mice did not find a significant difference in absolute fat mass but relative fat mass did reach significance (Berryman et al., 2004). However, the sample size for Berryman’s
2004 study was small (n = 3) and might have been a factor in reaching significance.
Individual tissue weights are typically measured at dissection and compared both as absolute weights and as a percentage of body weight, especially when there are differences in overall body size as seen with bGH mice relative to controls. In our study, both methods of analysis found that bGH mice had significantly less subcutaneous, epididymal, retroperitoneal, and mesenteric tissue mass when compared to WT controls.
Berryman et.al. (2004) did not find a significant difference in either absolute or relative depot weights, but they did see a similar pattern with bGH mice trending toward smaller depots. Once again, the small sample size could have precluded significance.
In comparison to both previous studies, our results showed a more drastic body composition and depot mass difference between bGH and WT mice at the 6-month age point. However, the pattern of body composition and tissue weight differences were the same as previous studies; therefore, our results are not a divergence but merely a more pronounced report of the same GH effect on body composition.
77
Collagen Content
Analysis of picosirus red-stained WAT revealed a striking increase in the collagen content of bGH mice. Though previous studies have shown that GH increases collagen content in other tissues (Doessing, Heinemeier, et al., 2010; Doessing, Holm, et al.,
2010), this study provides the first evidence that GH increases the collagen content of
WAT. Importantly, our study also showed that GH had the greatest influence on collagen content in the subcutaneous depot. This reinforces conclusions from previous research showing that the subcutaneous depot is the most affected by GH signaling (Berryman et al., 2010). Unfortunately, it is impossible to compare our results to WAT fibrosis in obesity, because few studies have compared multiple depots; of these, none have compared the collagen content among depots (Khan, 2009). To further hinder insight into potential depot differences, human and animal studies are often conducted on different depots. In human studies, often the subcutaneous depot is biopsied and visceral depots are not taken, while in mouse studies only the epididymal depot is examined. While this is more convenient for the researcher, our results show that collagen content could be different among depots, and thus multiple depots should be compared in future studies.
The potent effect of GH on collagen content may also relate to studies comparing immune cells in bGH mice. WAT fibrosis has been associated with other characteristics of obese WAT, including increased immune cell infiltration (Pasarica, Gowronska-
Kozak, et al., 2009). A study conducted in our laboratory compared changes in macrophage number and type between 5-month-old bGH and WT mice (Harshman,
2012). In addition to an overall increase in immune cell concentration, a substantial shift 78 toward an M2 macrophage phenotype was seen in the bGH mice, particularly in the subcutaneous depot. M2 macrophages, also known as alternatively activated macrophages, have been associated with increased ECM remodeling and decreased insulin sensitivity in subcutaneous WAT from obese human subjects (Spencer et al.,
2010). Results from the present study indicates that this relationship is also present in bGH animals; that is, increased ECM deposition appears to be associated with increased
M2 macrophages. This strengthens the argument that bGH WAT has comparable characteristics to obese WAT.
Adipocyte Size
The strength of the ECM appears to have a direct effect on adipocyte size (Khan et al., 2009). When adipocyte size is compared in the epididymal and mesenteric depots of transgenic obese mice lacking collagen VI (ob/ob ColVIKO mice) and their ob/ob controls, the ColVIKO mice have larger adipocytes (Khan et al., 2009). Khan et al. 2009 theorized that the ECM lacking collagen VI allowed for unhindered expansion of the adipocytes. Results from the present study show that this inverse relationship is maintained, although in the opposite roles, in that bGH mice have greater collagen deposition and subsequently, smaller adipocytes. Although not directly comparable, it is notable that bGH mice and ColVIKO mice have opposite phenotypes. While bGH mice are lean and insulin resistant with fibrotic WAT and small adipocytes, ColVIKO mice are obese and insulin sensitive with loose WAT ECM and large adipocytes. The possibility that the ECM could directly influence adipocyte size could be an important new insight into the effect of GH on WAT. GH has long been known to have an inverse relationship 79 with WAT that has been attributed to GH’s effect on lipolysis and lipogenesis (Garten et al., 2012; Goodman et al., 1991). Additionally, bGH mice are partially protected from diet-induced obesity, and gain less fat mass than their WT littermates when on a high-fat diet (Berryman et al., 2006). Results from the present study suggest that the increased fibrosis due to GH could also contribute to the decrease in fat mass and resistance to obesity seen in bGH mice by limiting the storage capacity of the adipocytes.
Collagen Gene Expression
Obesity is associated with fibrosis due to increased expression of most WAT collagens (Khan et al., 2009) and other tissues such as muscle and bone up-regulated collagens in response to GH (Doessing, Heinemeier, et al., 2010), leading us to hypothesize that the bGH mice would have increased collagen gene expression levels.
However, our results showed no significant differences when comparing WT and bGH expression of collagen genes 1α1, 3α1, 4α1, 5α1, and 6α1. While this was unexpected, it is not entirely surprising. As discussed in Chapter 2, collagen undergoes complicated intra- and extracellular processes in order to form collagen fibrils and, ultimately, macromolecular collagen structures. Changes to posttranscriptional modification, secretion, or degradation enzymes could all potentially cause the increase in collagen content reflected in our histological data. For example, insulin increases the secretion of collagens from cultured adipocytes without altering the regulation of the corresponding collagen genes (Wang et al., 2006). Analyses show that insulin functions at the level of modification and secretion of collagen by up-regulating collagen processing enzyme 80 genes. Thus, GH could be acting similarly and alter collagen levels without altering collagen gene expression.
However, the increased collagen in bGH WAT may be attributable to the actions of insulin and IGF-1, not GH itself. bGH mice have high serum levels of IGF-1 and insulin in addition to GH. Both hormones have been shown to increase collagen, both in cultured adipocytes (Mariman & Wang, 2010) and in other tissues in vivo (Fruchtman et al., 2005). Further research will be necessary to determine the cause of excess collagen in bGH WAT.
Limitations and Future Directions
This study is the first to examine GH’s effect on the collagen content of WAT.
Further research is necessary to determine specific alterations to the tissue and the mechanisms causing them. Below is an analysis of the limitations of the current study and future directions that could ameliorate these as well as build on the results of this thesis.
1. Our gene expression results had a great deal of plate-to-plate variation in both
housekeeping and target genes. Though no significant differences were seen, it is
difficult to report this conclusively when the variation was so great between
control genes. In order to confirm our superarray results, RNA analysis could be
repeated with another method such as RNAseq or qRT-PCR using primers that we
designed and optimized.
2. For this study, only the α1 subunit gene was analyzed and the results are assumed
to reflect the expression level of other subunits of each collagen assessed. Though 81
this assumption is made in other papers looking at WAT fibrosis (Divoux et al.,
2010; Khan et al., 2009), it is possible that the α1 subunit gene expression is not
necessarily representative of the expression level of other subunit genes and, thus,
the collagen expression level. Thus, RNA analysis of other collagen subunits
should be completed.
3. In addition to the five collagen genes analyzed in this study, many other genes for
both ECM components and proteins that alter the secretion or formation of
collagen could be studied. In particular, increased expression procollagen C-
endopeptidase enhancer protein (PCOLCE), sulfatase 2 and prolyl hydroxylase
have been observed in response to insulin and shown to alter secretion of mature
collagens without changes in the expression of the collagen genes (Wang et al.,
2006). Their genes, as well as genes for matrix degradation enzymes (MMPs) and
their inhibitors (TIMPs), should be analyzed. Due to the number of potential
influential genes, utilizing microarray or RNAseq instead of PCR could be
advantageous as this method allows for the simultaneous analysis of all mRNAs.
4. Our histological data clearly show a difference in collagen concentration between
genotypes. Because picosirus red is a general stain for all collagens, our results
cannot determine what specific collagens are present and if there is a particular
arrangement of collagens. Immunohistochemistry could be conducted to stain for
specific collagens as well as other components of WAT, such as blood vessels, to
determine if there is a pattern of collagen deposition. In addition, protein analysis,
such as a western blot, could be completed to confirm the collagen protein 82
differences seen in our histological data as well as determine which specific
collagen types are affected.
5. WAT is not homogenous and contains many cell types. To compare gene
expression for this study, whole tissue was homogenized and the RNA extracted
thus, the gene expression results of our experiment only reflected expression
changes in the whole tissue. Though we did not see differences at the whole tissue
level, it is unclear whether those results are representative of all cell types or if
particular cell types are more effected. Notably, in obese human WAT, the
expression of collagens 1α1, 3α1, and 6α1 is significantly greater in the SVF cells
when compared to the expression of mature adipocytes (Divoux et al., 2010)
however, this comparison has not been done in mice. Furthermore, GH is known
to affect the SVF as bGH mice have been shown to have higher SVF than control
adipose tissue (Harshman, 2012); thus, RNA isolated from the WAT in these two
genotypes will reflect a different population of cells and, potentially, a different
expression profile. Therefore, separation of mature adipocyte and cells of the
stromal vascular fraction before RNA or protein analysis could provide valuable
insight to both the WAT field generally and to the effect of GH on these fractions
specifically. In addition, adipocytes are known to change their expression patterns
of various collagens during differentiation (Aratani & Kitagawa, 1988; Molina et
al., 2009). In order to study the effect of GH on collagen secretion during
differentiation, pre-adipocytes could be isolated from the SVF via fluorescence 83
activated cell sorting (FACS) and cultured. Then, secretory proteins from the
culture medium could be collected and measured throughout differentiation.
6. Our preliminary study shows that collagen content is greater in the bGH animals
at all time points, but that it continues to increase with age. We chose 6 months of
age as the time point for this study; however, arguments could be made that both
younger and older time points could be more revealing. When comparing gene
expression, younger time points might reveal the initiation of the process while an
older time point might show significant differences not revealed in the 6-month
time point. In addition, bGH and WT mice do not have the same body
composition relationship over time with bGH mice having greater fat mass at
younger ages and less fat mass at older ages than their WT controls (Palmer et al.,
2009). Therefore, studying younger ages would allow us to compare the
genotypes when they have similar fat masses while studying older ages would
reveal comparisons with drastically different fat masses.
7. Our results show clear genotype and depot differences in the collagen content of
WAT. These differences in collagen content could have implications for the use
of collagenase. Collagenase digestion is commonly used in studies with adipose
tissue to digest the ECM so that the SVF can be isolated from adipocytes. If
collagen content varies with different depots or under different physiological
conditions (such as overexpression of GH in bGH mice), then consistent digestion
procedures could result in very different results. For example, over digestion of a
tissue could alter results and affect the viability of cells. A study could be 84
conducted to set recommendations for the amount and concentration of
collagenase to use on a sample based on tissue mass and collagen concentration.
8. While our study does provide insight into the effect of GH action on WAT
fibrosis, it only shows the positive, chronic effect of GH. WAT fibrosis could also
be assessed in other mice with altered GH action. Growth hormone receptor
knockout mice (GHR -/-) have no GH action and are consequently dwarf and
obese (Berryman et al., 2010). However, they are also long lived and insulin
sensitive, providing us a model for healthy obesity. Assessment of collagen
content and cell size could also be conducted in these mice to assess whether they
experience decreased collagen and increased cell size. In addition, injection
studies on WT mice could reveal acute effects of GH on the WAT ECM. Injection
of GH in high-fat fed mice dramatically alters their body composition, decreasing
fat mass and increasing lean mass in a dose dependent manner (List et al., 2009).
Examination of collagen mRNA and protein changes during administration of
exogenous GH could highlight differences in the acute and chronic effect of GH
and as well as show how the ECM responds to rapid WAT remodeling.
Conclusion
The obesity epidemic has thrust adipose tissue research into the limelight, greatly increasing our interest in and knowledge of this tissue. Our laboratory has a unique perspective in that we are able to study hallmarks of obese WAT in a lean, unhealthy mouse model, essentially examining unhealthy WAT independent of adiposity. This study has revealed genotypic and depot differences in collagen content and cell size, 85 strengthening the argument that the unhealthy adipose tissue has similar characteristics in both obese and lean states. Thus, associated diseases of obesity may be attributed to the health of the tissue, not the amount of tissue. This could have implications for potential therapeutics to focus on increasing the health of WAT, rather than decreasing the amount of WAT.
Importantly, our research and results are relevant not only to obesity, but also to the influence of GH on adipose tissue. This study revealed that GH increased fibrosis in
WAT and decreased adipocyte size. In obese WAT, fibrosis has been associated with limiting the storage capacity of adipocytes, leading us to question whether this is also true in GH influenced WAT. GH is known to decrease fat mass by increasing lipolysis and decreasing lipogenesis. If fibrosis does in fact limit the storage capacity of adipocytes, it could be a contributing factor to the decreased fat mass caused by GH. Thus, these results provide a novel mechanism by which GH may reduce fat mass beyond the ability to directly alter lipogenesis or lipolysis.
86
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Appendix A: RNA Isolation Procedure
1. Add about 80-100mg frozen tissue to 200ul Trizol reagent (alternatively, Trizol can
be added directly to tube, if the tissue is needed for nothing else)
2. Homogenize with small probe homogenizer until there are no pieces left (Do not let
tissue get too warm while homogenizing)
3. Wash down the blue plastic pestle with an additional 800ul Trizol to bring total
volume to 1mL.
4. Mix by inverting 10 times.
5. Incubate homogenized tissue in TRISOL reagent for 5 minutes at room temperature.
6. Spin at max speed (~17g) for 5 minutes at 4˚C
7. Use pipette to remove most of the lipid layer on the top without disturbing the Trizol
layer and put into new tube
8. Add 200 µL of choloroform.
9. Vortex and incubate for 2-3 minutes.
10. Spin at max speed (~17g) for 15 minutes at 4˚C
11. Transfer top 50% of aqueous phase to a NEW RNase-free 1.5mL eppendorf tube.
12. Add 700 µL of 100% room temperature ethanol.
13. Mix by inverting 10 times.
14. Transfer up to 700 ul of sample, including any precipitate that may have formed, to
an RNeasy spin column placed in a 2ml collection tube (supplied with kit). Close the
lid gently and centrifuge for 15 s at >8,000 g. Discard the flow-through. 105
(Reuse the collection tube in the next step. If the sample volume exceeds 700 ul,
centrifuge successive aliquots in the same RNeasy spin column. Discard the flow-
through after each centrifugation.)
15. Add 500 µL of 70% ethanol to the RNeasy spin column. Close the lid gently, and
centrifuge for 15 s at >8,000 g to wash the spin column membrane. Discard the flow-
through
(Reuse the collection tube in the next step. Note: After centrifugation, remove the
RNeasy spin column from the collection tube so that the column does not contact the
flow-through. Be sure to empty the collection tube completely.)
16. Add 700 ul of buffer RW1 to the RNeasy spin column. Close the lid gently, and
centrifuge for 15 s at >8,000 g to wash the spin column membrane. Discard the flow-
through
(Reuse the collection tube in the next step. Note: After centrifugation, remove the
RNeasy spin column from the collection tube so that the column does not contact the
flow-through. Be sure to empty the collection tube completely.)
Buffer RW1 is washing buffer and contains a small amount of guanidine
thiocyanate.
17. Add 500 ul of buffer RPE to the RNeasy spin solumn. Close the lid gently, and
centrifuge for 15 s at >8,000 g to wash the spin column membrane. Discard the flow-
through.
(Reuse the collection tube in the next step. Note: Buffer RPE is supplied as a
concentrate. Ensure that ethanol is added to it before use. ) 106
18. Add 500 ul of buffer RPE to the RNeasy spin solumn. Close the lid gently, and
centrifuge for 2 min at >8,000 g to wash the spin column membrane.
(After centrifugation, carefully remove the RNeasy spin column from the collection
tube so that the column does not contact the flow-through. Otherwise, carryover of
ethanol will occur and may interfere with downstream reactions.)
19. Optional: place the RNeasy spin column in a new 2ml collection tube (supplied with
kit), and discard the old collection tube with the flow-through. Close the lid gently
and centrifuge at full speed for 1 min.
(Perform this step to eliminate any possible carryover of buffer RPE, or if residual
flow-through remains on the ouside of the RNeasy spin solumn after the previous
step).
20. Place the RNeasy spin column in a new 1.5 ml collection tube (supplied with kit).
Add 30-50 ul of RNase-free water directly to the spin column membrane. Close the
lid gently, and centrifuge for 1 min at >8,000 g to elute the RNA.
21. If the expected RNA yield is > 30 ug, repeat the previous step using another 30-50 ul
RNase-free water, or using the eluate from the previous step.
(If using the eluate from step 18, the RNA yield will be 15-30% less than that
obtained using a second volume of RNase-free water, but the final RNA
concentration will be higher.)
22. Measure concentration of all samples using the NanoDrop.
23. Aliquot ~5 ul of each sample into a new tube properly labeled and take to genomics
facility for quality check using the bioanalyzer (need to fill out a form online also). 107
24. Store the remaining RNA samples at -20°C or -80°C. In these conditions, no
degradation is detectable after 1 year.
108
Appendix B: Polymerase Chain Reaction Plate Design
In addition to the genes investigated for this thesis, genes for three additional
ECM components, three inflammatory markers, three housekeeping genes, and to controls were included in the plate design. Each plate was loaded with two samples - one from a bGH mouse and one from a WT mouse - in triplicate.
1 2 3 4 5 6 7 8 9 10 11 12
Col1a1 Emr1 Col1a1 Emr1 Col1a1 Emr1 Col1a1 Emr1 Col1a1 Emr1 Col1a1 Emr1 A 1 9 1 9 1 9 1 9 1 9 1 9 Col3a1 Tgfb1 Col3a1 Tgfb1 Col3a1 Tgfb1 Col3a1 Tgfb1 Col3a1 Tgfb1 Col3a1 Tgfb1 B 2 10 2 10 2 10 2 10 2 10 2 10 Col4a1 Hif1a Col4a1 Hif1a Col4a1 Hif1a Col4a1 Hif1a Col4a1 Hif1a Col4a1 Hif1a C 3 11 3 11 3 11 3 11 3 11 3 11 Col5a1 Eif3f Col5a1 Eif3f Col5a1 Eif3f Col5a1 Eif3f Col5a1 Eif3f Col5a1 Eif3f D 4 12 4 12 4 12 4 12 4 12 4 12 Col6a1 Rps3 Col6a1 Rps3 Col6a1 Rps3 Col6a1 Rps3 Col6a1 Rps3 Col6a1 Rps3 E 5 13 5 13 5 13 5 13 5 13 5 13 Eln B2m Eln B2m Eln B2m Eln B2m Eln B2m Eln B2m F 6 14 6 14 6 14 6 14 6 14 6 14 Dcn RTC Dcn RTC Dcn RTC Dcn RTC Dcn RTC Dcn RTC G 7 15 7 15 7 15 7 15 7 15 7 15 Lum PPC Lum PPC Lum PPC Lum PPC Lum PPC Lum PPC H 8 16 8 16 8 16 8 16 8 16 8 16
109
Appendix C: Adipose Tissue Weights at Dissection
Mouse # Genotype Cage Age SubQ Epi Retro Mes BAT 4156 GP A 6.64 0.123 0.392 0.002 0.036 0.062 4155 GP B 6.64 0.18 0.493 0.091 0.068 0.088 4154 GP C 6.64 0.171 0.624 0.081 0.121 0.076 4153 - D 6.64 0.157 0.381 0.052 0.11 0.049 4152 GP E 6.64 0.201 0.557 0.052 0.075 0.092 4140 - F 6.67 0.233 0.878 0.235 0.241 0.065 4139 - F 6.67 0.32 0.936 0.216 0.266 0.093 4138 - F 6.67 0.3 0.956 0.257 0.223 0.068 4137 GP G 6.67 0.115 0.554 0.063 0.101 0.072 4130 GP H 6.67 0.232 0.664 0.106 0.094 0.087 4129 - I 6.67 0.254 0.946 0.277 0.303 0.079 4128 GP I 6.67 0.156 0.382 0.032 0.099 0.081 4124 GP J 6.67 0.301 0.835 0.111 0.133 0.067 4123 - J 6.67 0.474 1.47 0.528 0.479 0.094 4122 - J 6.67 0.471 1.52 0.364 0.467 0.1 4116 - K 6.67 0.146 0.55 0.135 0.164 0.054
110
Appendix D: Nonadipose Tissue Weights at Dissection
Mouse # Genotype Cage Age Quad Gas Sol Brain Heart 4156 GP A 6.64 0.811 0.319 0.031 0.488 0.259 4155 GP B 6.64 0.802 0.293 0.027 0.49 0.296 4154 GP C 6.64 0.838 0.299 0.029 0.475 0.321 4153 - D 6.64 0.632 0.246 0.016 0.392 0.111 4152 GP E 6.64 1.09 0.366 0.032 0.479 0.268 4140 - F 6.67 0.888 0.271 0.017 0.434 0.134 4139 - F 6.67 0.752 0.294 0.018 0.434 0.179 4138 - F 6.67 0.917 0.289 0.016 0.405 0.126 4137 GP G 6.67 0.816 0.307 0.025 0.441 0.291 4130 GP H 6.67 0.921 0.332 0.033 0.465 0.299 4129 - I 6.67 0.793 0.276 0.018 0.43 0.178 4128 GP I 6.67 0.922 0.299 0.025 0.476 0.267 4124 GP J 6.67 0.882 0.33 0.03 0.49 0.273 4123 - J 6.67 0.779 0.285 0.018 0.45 0.169 4122 - J 6.67 0.756 0.292 0.021 0.441 0.147 4116 - K 6.67 0.76 0.264 0.013 0.453 0.132
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