University of Kentucky UKnowledge
Theses and Dissertations--Animal and Food Sciences Animal and Food Sciences
2019
FORMS OF SUPPLEMENTAL SELENIUM IN VITAMIN-MINERAL MIXES DIFFERENTIALLY AFFECT SEROLOGICAL AND HEPATIC PARAMETERS OF GROWING BEEF STEERS GRAZING ENDOPHYTE-INFECTED TALL FESCUE
Yang Jia University of Kentucky, [email protected] Digital Object Identifier: https://doi.org/10.13023/etd.2019.028
Right click to open a feedback form in a new tab to let us know how this document benefits ou.y
Recommended Citation Jia, Yang, "FORMS OF SUPPLEMENTAL SELENIUM IN VITAMIN-MINERAL MIXES DIFFERENTIALLY AFFECT SEROLOGICAL AND HEPATIC PARAMETERS OF GROWING BEEF STEERS GRAZING ENDOPHYTE- INFECTED TALL FESCUE" (2019). Theses and Dissertations--Animal and Food Sciences. 97. https://uknowledge.uky.edu/animalsci_etds/97
This Doctoral Dissertation is brought to you for free and open access by the Animal and Food Sciences at UKnowledge. It has been accepted for inclusion in Theses and Dissertations--Animal and Food Sciences by an authorized administrator of UKnowledge. For more information, please contact [email protected]. STUDENT AGREEMENT:
I represent that my thesis or dissertation and abstract are my original work. Proper attribution has been given to all outside sources. I understand that I am solely responsible for obtaining any needed copyright permissions. I have obtained needed written permission statement(s) from the owner(s) of each third-party copyrighted matter to be included in my work, allowing electronic distribution (if such use is not permitted by the fair use doctrine) which will be submitted to UKnowledge as Additional File.
I hereby grant to The University of Kentucky and its agents the irrevocable, non-exclusive, and royalty-free license to archive and make accessible my work in whole or in part in all forms of media, now or hereafter known. I agree that the document mentioned above may be made available immediately for worldwide access unless an embargo applies.
I retain all other ownership rights to the copyright of my work. I also retain the right to use in future works (such as articles or books) all or part of my work. I understand that I am free to register the copyright to my work.
REVIEW, APPROVAL AND ACCEPTANCE
The document mentioned above has been reviewed and accepted by the student’s advisor, on behalf of the advisory committee, and by the Director of Graduate Studies (DGS), on behalf of the program; we verify that this is the final, approved version of the student’s thesis including all changes required by the advisory committee. The undersigned agree to abide by the statements above.
Yang Jia, Student
Dr. James C. Matthews, Major Professor
Dr. David L. Harmon, Director of Graduate Studies
FORMS OF SUPPLEMENTAL SELENIUM IN VITAMIN-MINERAL MIXES DIFFERENTIALLY AFFECT SEROLOGICAL AND HEPATIC PARAMETERS OF GROWING BEEF STEERS GRAZING ENDOPHYTE-INFECTED TALL FESCUE
______
DISSERTATION ______A dissertation submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy in the College of Agriculture, Food and Environment at the University of Kentucky
By Yang Jia Lexington, Kentucky Director: Dr. James C. Matthews, Professor of Animal and Food Sciences Lexington, Kentucky 2019
Copyright © Yang Jia 2019
ABSTRACT OF DISSERTATION
FORMS OF SUPPLEMENTAL SELENIUM IN VITAMIN-MINERAL MIXES DIFFERENTIALLY AFFECT SEROLOGICAL AND HEPATIC PARAMETERS OF GROWING BEEF STEERS GRAZING ENDOPHYTE-INFECTED TALL FESCUE
Consumption of endophyte-infected tall fescue results in a syndrome of negatively altered physiological systems, collectively known as fescue toxicosis. Another challenge to endophyte-infected tall fescue -based beef cattle operations is that the soils often are selenium (Se) poor, necessitating the need to provide supplemental Se. To test the general hypothesis that different forms of supplemental Se would ameliorate the negative effects of fescue toxicosis, predominately-Angus steers (BW = 183 ± 34 kg) were randomly selected from herds of fall-calving cows grazing an endophyte-infected tall fescue pasture and consuming vitamin-mineral mixes that contained 35 ppm Se as sodium selenite (ISe), SELPLEX (OSe), or an 1:1 blend of ISe and OSe (MIX). Steers were commonly weaned and depleted of Se for 98 d. Steers were assigned (n = 8 per treatment) to the same Se-form treatments upon which they were raised and subjected to summer-long common grazing of an endophyte-infected tall fescue pasture (0.51 ppm ergot alkaloids: ergovaline plus ergovalinine; 10.1 ha). Selenium treatments were administered by daily top-dressing 85 g of vitamin-mineral mix onto 0.23 kg soyhulls, using in-pasture Calan gates. The first project objective was to determine the effect of forms of supplemental Se on whole blood Se, serum prolactin, liver glutamine synthetase (GS) activity, carcass parameters, and growth performance (Experiment 1). In Experiment 1, whole blood Se increased for all treatments from day 0 to 22 and then did not change. Across periods, MIX and OSe steers had greater whole blood Se than ISe steer. Compared to ISe steers, MIX and OSe steers had more serum prolactin. Liver GS mRNA, protein content, and activity were greater in MIX and OSe steers than ISe steers. However, the ADG and carcass parameters were not affected by Se treatments. The second project objective was to determine the effect of forms of supplemental Se on serum clinical parameters of Experiment 1 steers (Experiment 2). In Experiment 2, across periods, MIX steers had more serum albumin than OSe, and ISe steers, respectively. Serum alkaline phosphatase (ALP) activity was greater in MIX and OSe steers. In addition, blood urea nitrogen (BUN), serum sodium, phosphorus, and magnesium concentration were affected by Se treatments. Partial correlation analysis revealed that serum albumin, BUN, and ALP activity were correlated with whole blood Se concentration. The third project objective was to evaluate the hepatic transcriptome profiles of Experiment 1 steers using microarray and targeted RT-PCR analyses (Experiment 3). In Experiment 3, bioinformatic analysis of microarray data indicated that hepatic glutamate/glutamine, proline, arginine, and citrulline metabolism was affected by different forms of supplemental Se. The mRNA expression of critical proteins involved in glutamate/glutamine (GLS2, GLUD1, GLUL), proline (PYCR1, ALDH18A1), and urea (ARG1, ARG2, OAT, NAGS, OTC, ORNT1) metabolism were differentially expressed by Se treatments. Collectively, we conclude that consumption of 3 mg Se/d as OSe or MIX forms of Se in vitamin-mineral mixes 1) increased whole blood Se content, an indicator of greater whole-body Se assimilation; 2) increased serum prolactin, albumin, and ALP, the reduction of which are hallmarks of fescue toxicosis; and 3) altered hepatic nitrogen metabolism, as indicated by changes in key enzymes of glutamate/glutamine, proline, and urea metabolism. However, 4) these positive effects on metabolic parameters were not accompanied by increased growth performance.
KEYWORDS: Fescue toxicosis, Selenium supplementation, Prolactin, Alkaline phosphatase, Glutamine synthetase
Yang Jia (Name of Student)
3/11/2019 Date
FORMS OF SUPPLEMENTAL SELENIUM IN VITAMIN-MINERAL MIXES DIFFERENTIALLY AFFECT SEROLOGICAL AND HEPATIC PARAMETERS OF GROWING BEEF STEERS GRAZING ENDOPHYTE- INFECTED TALL FESCUE
By Yang Jia
Dr. James C. Matthews Director of Dissertation
Dr. David L. Harmon Director of Graduate Studies
3/11/2019 Date ACKNOWLEDGEMENTS I would like to extend my sincere appreciations and best wishes to all the people who I benefited from in the process of completing this dissertation. First of all,
I would like to express my deepest gratitude to my major professor, Dr. James C.
Matthews, for his intellectual guidance, constructive suggestions, and patience throughout my graduate career. Words cannot justify my appreciations to your support and inspirations as a mentor, as well as a scientist. These experience working with you makes me a better student, scientist, and man. Next, my grateful appreciations also extend to Dr. Amanda A. Adams, Dr. Phillip J. Bridges, Dr. James
L. Klotz, and Dr. Karen J. McDowell for serving on the advisory committee, and to
Dr. Bin-Tao Pan for serving as an outside examiner. I am really grateful about each individual for providing valuable insights, guiding and challenging my thinking during every stage of the dissertation process. Moreover, I also want to extend my gratitude to the support and help from other professors of the beef nutrition group, Dr.
Walter R. Burris, who provides critical guidance and support on the animal management part of the dissertation. I would like to thank all the help and support through the years from Dr. David L. Harmon, Dr. Eric S. Vansant, and Dr. Kyle R.
McLeod.
Next, I would like to appreciate Mr. Kwangwon Son, Mr. Hugo Hamilton, and Mrs. Susan Hayes for their technical and instrumental support on laboratory assays and sample analysis. Appreciation is also extended to Mrs. Blair Knight and the crew in UKREC, Princeton for their countless assistance and management on the beef steers used in the dissertation. My sincere gratitude is also extended to Qing Li,
Jing Huang, Alex Altman, and Ning Lu for their help and friendship.
Last but not least, I am always thankful for my parents and family for their unconditional love and support to me. No matter what I do and where I go, their iii blessings have always been around me and continuing to encourage me for the rest of my life. I cannot express my gratitude to my wife, who has been a phenomenal role model for me and sacrificing a lot to make our marriage life and graduate student life such a great success. I would never have been able to finish my graduate career without the love and contribution from you.
iv TABLE OF CONTENTS
ACKNOWLEDGEMENTS ...... iii TABLE OF CONTENTS ...... v LIST OF TABLES ...... ix LIST OF FIGURES ...... xi CHAPTER 1. Introduction...... 1 CHAPTER 2. Literature Review ...... 4 2.1 Fescue Toxicosis ...... 4 2.1.1 Tall Fescue ...... 4 2.1.2 Definition, Clinical Symptoms, and Economic Impacts ...... 5 2.1.3 Ergot Alkaloids ...... 8 2.1.3.1 History...... 8 2.1.3.2 Chemistry of Ergot Alkaloids ...... 9 2.1.4 Physiological Impacts of Consuming Ergot Alkaloids ...... 11 2.1.4.1 On Serological Parameters ...... 11 2.1.4.1.1 Prolactin ...... 11 Introduction ...... 11 Prolactin structure, isoform, expression, and biology ...... 12 Regulation of prolactin expression and secretion ...... 15 Biological functions of prolactin ...... 16 Suppression of prolactin, a hallmark of fescue toxicosis ...... 19 2.1.4.1.2 Alkaline Phosphatase ...... 21 Introduction ...... 21 Isoenzymes and isoforms ...... 21 Function and distribution ...... 22 Serum alkaline phosphatase ...... 23 Serum indicator of fescue toxicosis ...... 24 2.1.4.1.3 Albumin...... 26 Introduction ...... 26 Function ...... 27 Fescue toxicosis and serum albumin...... 28 2.1.4.2 On Liver Metabolic Physiology and Function ...... 29 2.1.4.2.1 Liver Metabolic Zonation and Glutamate/Glutamine Cycle ...... 33 2.2 Selenium Supplementation in Cattle ...... 40 2.2.1 Selenium Overview ...... 40 2.2.2 Nutritional Sources of Se ...... 41 2.2.3 Selenoprotein Synthesis ...... 43 2.2.4 Selenium Absorption ...... 44 2.2.5 Selenium Metabolism ...... 45 2.2.6 Effects of Forms Supplemental Selenium on Cattle ...... 47 2.2.6.1 On Blood and Tissue Selenium Assimilation ...... 47
v 2.2.6.2 On Hepatic Gene Expression Profiles...... 49 2.3 Summary ...... 51 CHAPTER 3. Dissertation Objectives ...... 66 CHAPTER 4. Forms of selenium in vitamin-mineral mixes differentially affect serum prolactin concentration and hepatic glutamine synthetase activity of steers grazing endophyte-infected tall fescue ...... 68 4.1 Abstract ...... 68 4.2 Introduction ...... 70 4.3 Materials and Methods ...... 71 4.3.1 Animals ...... 71 4.3.2 Pasture Sampling and Analysis ...... 73 4.3.3 Blood Collection ...... 74 4.3.4 Slaughter, Tissue Collection, and Carcass Evaluation ...... 74 4.3.5 Analysis of GS Activity in Hepatic and LM Tissue Homogenates ...... 75 4.3.6 Caudal Artery Area Measurement ...... 77 4.3.7 RNA Extraction and Analysis ...... 77 4.3.8 Real-time RT-PCR Analysis ...... 78 4.3.9 Immunoblot Analysis ...... 79 4.3.10 Statistical Analysis ...... 81 4.4 Results ...... 82 4.4.1 Nutrient and Ergot Alkaloid Profiles of Forages ...... 82 4.4.2 Whole Blood Se Concentration ...... 82 4.4.3 Serum Prolactin Concentration ...... 83 4.4.4 GS Activity and Expression ...... 83 4.4.5 Caudal Artery Area ...... 84 4.4.6 Animal Performance ...... 85 4.5 Discussion ...... 85 4.5.1 Animal Model ...... 85 4.5.2 OSe and MIX Forms of Se Supplementation Resulted in Greater Whole Blood Se than ISe...... 87 4.5.3 Concentrations of Serum Prolactin Were Greater in MIX and OSe Steers ...... 88 4.5.4 Hepatic GS Activity, mRNA, and Protein Expression Are Greater in MIX than ISe Steers...... 90 4.5.5 Caudal Artery Area, Animal Performance, and Carcass Characteristics Were Not Affected by Se Treatment ...... 92 4.6 Summary ...... 94 CHAPTER 5. Forms of selenium in vitamin-mineral mixes differentially affect serum alkaline phosphatase activity, and serum albumin and blood urea nitrogen concentrations, of steers grazing endophyte-infected tall fescue ...... 105 5.1 Abstract ...... 105 5.2 Introduction ...... 107 5.3 Materials and Methods ...... 109 5.3.1 Animals, Slaughter and Tissue Collection ...... 109
vi 5.3.2 Blood Collection and Analyses ...... 111 5.3.3 Western Blot Analysis ...... 112 5.3.4 Hepatic RNA Extraction and Analysis ...... 114 5.3.5 Real-time RT-PCR Analysis ...... 115 5.3.6 Statistical Analysis ...... 116 5.4 Results ...... 117 5.4.1 Serum Clinical Parameters ...... 117 5.4.2 Hepatic Bovine Serum Albumin Protein Content, Alkaline Phosphatase mRNA and Protein Content ...... 121 5.4.3 Partial Correlation of Whole Blood Se Concentration with Serum Clinical Parameters ...... 122 5.5 Discussion ...... 122 5.5.1 Animal Model ...... 123 5.5.2 MIX and OSe Forms of Se Supplementation Resulted in Greater Serum Alkaline Phosphatase Activity Vs. ISe ...... 124 5.5.3 MIX Form of Se Supplementation Resulted in Greater Serum Albumin than OSe and ISe ...... 127 5.5.4 Blood Urea Nitrogen, and Serum Sodium, Phosphorus, and Magnesium Concentration Were Affected by Form of Se ...... 128 5.5.5 Whole Blood Se Concentration Is Correlated with Alkaline Phosphatase Activity, Serum Albumin, Blood Urea Nitrogen, and Magnesium Concentration ...... 131 5.6 Summary ...... 132 CHAPTER 6. Gene expression profiling indicates a shift in ammonia assimilation capacity along hepatic acinus induced by different forms of selenium in vitamin- mineral mixes fed to steers grazing endophyte-infected tall fescue ...... 146 6.1 Abstract ...... 146 6.2 Introduction ...... 149 6.3 Materials and Methods ...... 151 6.3.1 Animals, Slaughter and Tissue Collection ...... 151 6.3.2 Immunoblot Analysis ...... 153 6.3.3 Hepatic RNA Extraction and Analysis ...... 155 6.3.4 Microarray Analysis ...... 156 6.3.5 Real-time RT-PCR Analysis ...... 159 6.3.6 Statistical Analysis ...... 161 6.4 Results ...... 161 6.4.1 Differentially Expressed Genes ...... 161 6.4.2 Pathways and Gene Network Analysis ...... 162 6.4.3 Real-time RT-PCR Analysis of Genes Selected mRNA ...... 162 6.4.4 Hepatic Content of OAT and System Transporters and Regulatory Proteins ...... 164 6.5 Discussion ...... 𝑿𝑿𝑿𝑿𝑿𝑿...... − ..... 164 6.5.1 Animal Model ...... 164 6.5.2 Hepatic Capacities of Sinusoidal Ammonia Assimilation Are Shifted in
vii MIX and OSe vs. ISe Steers...... 167 6.5.3 Hepatic Proline Metabolism is Differentially Affected by Forms of Se ...... 177 6.6 Summary ...... 178 CHAPTER 7. Summary and Conclusions ...... 229 APPENDICES ...... 233 APPENDIX 1. The Form of Selenium in Free-choice Vitamin-mineral Mixes Affects the Percentage of Circulating Neutrophils and Lymphocytes in Beef Calves Subjected to Combined Weaning and Shipping Events...... 233 Introduction ...... 233 Objective ...... 236 Materials and Methods ...... 236 Animal model...... 236 Blood Collection ...... 237 Whole Blood RNA Collection and Isolation ...... 238 Real-time RT-PCR Analysis ...... 238 Statistical Analysis ...... 240 Results ...... 240 Conclusion ...... 242 APPENDIX 2. Microarray signal intensity of selected key enzymes and transporters involved hepatic glutamate/glutamine, ammonia, and proline metabolism...... 255 Conclusion ...... 258 REFERENCE ...... 259 VITA ...... 312
viii LIST OF TABLES Table 2. 1 Summary of cattle serum ALP activity reference range in literature...... 61 Table 2. 2 Serum alkaline phosphatase (ALP) concentrations in animals consuming endophyte-infected tall fescue...... 62 Table 2. 3 List of genes differently altered by supplementing forms of Se and grazing endophyte-infected tall fescue...... 64 Table 4. 1 Primer information used for real-time RT-PCR analyses...... 96 Table 4. 2 Proximate, mineral, and alkaloid analysis of composited pasture samples (DM basis)1 ...... 97 Table 4. 3 Comparison of glutamine synthetase mRNA and protein content in liver homogenates of growing beef steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as either sodium selenite (ISe), SEL-PLEX (OSe), or a 1:1 blend of ISe and OSe (MIX)1...... 98 Table 4. 4 Animal performance and carcass characteristics of growing beef steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as either sodium selenite (ISe), SEL-PLEX (OSe), or a 1:1 blend of ISe and OSe (MIX)1...... 99 Table 5. 1 Primer information and results of real-time RT-PCR product sequence (Figure 5.3) validation...... 133 Table 5. 2 Serum clinical parameters in growing beef steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as sodium selenite (ISe), SEL-PLEX (OSe), or an 1:1 blend of ISe and OSe (MIX)...... 134 Table 5. 3 Hepatic bovine serum albumin protein content, alkaline phosphatase (tissue non-specific, liver/bone/kidney, TNALP) mRNA and protein content in liver homogenates after slaughter of beef steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as sodium selenite (ISe, n = 6), SEL-PLEX (OSe, n = 8), or an 1:1 blend of ISe and OSe (MIX, n = 8)1...... 136 Table 5. 4 Partial correlation of serum clinical parameters with whole blood selenium concentration in growing beef steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as sodium selenite (ISe), SEL-PLEX (OSe), or an 1:1 blend of ISe and OSe (MIX). (n = 6 for ISe, n = 8 for OSe and MIX)...... 137 Table 6. 1 List of differentially expressed and annotated liver genes (P < 0.01, 573 genes) from steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as sodium selenite (ISe, n = 6), SEL-PLEX (OSe, n = 8), or an 1:1 blend of ISe and OSe (MIX, n = 7)1...... 180 Table 6. 2 Primer information and results of real-time RT-PCR product sequence validation...... 207 Table 6. 3 Top IPA-identified canonical pathways of genes differentially expressed from liver of steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as sodium selenite (ISe, n = 6), SEL-PLEX (OSe, n = 8), or an 1:1 blend of ISe and OSe (MIX, n = 7)...... 211 ix Table 6. 4 IPA-identified canonical pathways of genes involved in glutamate/glutamine and nitrogen metabolism differentially-expressed from liver of steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin- mineral mixes as sodium selenite (ISe, n = 6), SEL-PLEX (OSe, n = 8), or an 1:1 blend of ISe and OSe (MIX, n = 7)...... 212 Table 6. 5 Microarray and real-time RT-PCR identification of selected genes from livers of steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as sodium selenite (ISe, n = 6), SEL-PLEX (OSe, n = 8), or an 1:1 blend of ISe and OSe (MIX, n = 7 for microarray, n = 8 for RT- PCR)...... 213 Table 6. 6 Hepatic content of proteins associated with glutamate metabolism and transport in steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as sodium selenite (ISe, n = 6), SEL- PLEX (OSe, n = 8), or an 1:1 blend of ISe and OSe (MIX, n = 8)1...... 215 Table A1. 1 Summary table of the literature on the effect weaning and transportation stress on cattle...... 243 Table A2. 1 List of the microarray signal intensity of selected key enzymes and transporters involved hepatic glutamate/glutamine, ammonia, and proline metabolism...... 255
x LIST OF FIGURES Figure 2. 1 Ergoline ring system...... 53 Figure 2. 2 Structures of three classes of ergot alkaloids. Examples of clavine alkaloids (a and b), lysergic acid and its simple amides (c and d), ergopeptine alkaloids (e, f, and g)...... 54 Figure 2. 3 Overview of main glutamine/glutamate and ammonia metabolic pathways in periportal and perivenous hepatocytes1...... 55 Figure 2. 4 Structures of inorganic selenium compounds, the related oxyanions, and organic selenium compounds1...... 57 Figure 2. 5 Schematic illustration of translation mechanism for the synthesis of selenoproteins1...... 58 Figure 2. 6 Schematic illustration of the initial metabolism of the principal dietary forms of selenium1...... 59 Figure 2. 7 Scheme of regulated selenium metabolism in hepatocytes1...... 60 Figure 4. 1 The sequences of the real-time RT-PCR products (5’ to 3’ orientation). Within a sequence, underlined nucleotides indicate the forward and reserve primer positions...... 100 Figure 4. 2 Whole blood selenium (Se) (A.) and serum prolactin (B.) concentrations in growing beef steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as either sodium selenite (ISe), SEL- PLEX (OSe), or a 1:1 blend of ISe and OSe (MIX)1...... 101 Figure 4. 3 Glutamine synthetase (GS) activity in liver and Longissimus dorsi (Muscle) homogenates of growing beef steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as either sodium selenite (ISe), SEL-PLEX (OSe), or a 1:1 blend of ISe and OSe (MIX)1. .... 102 Figure 4. 4 Western blot analysis of glutamine synthetase protein (42.5 kDa) content in liver homogenates (20 ug/lane) of growing beef steers grazing endophyte- infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as either sodium selenite (ISe), SEL-PLEX (OSe), or a 1:1 blend of ISe and OSe (MIX)...... 103 Figure 4. 5 Caudal artery area in growing beef steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as either sodium selenite (ISe), SEL-PLEX (OSe), or a 1:1 blend of ISe and OSe (MIX)1...... 104 Figure 5. 1 Immunoblot validation of rabbit IgG anti-bovine serum albumin (BSA) polyclonal antibody conjugated to horse radish peroxidase detection (69.3 kDa) of bovine BSA1...... 138 Figure 5. 2 Immunoblot validation of rabbit IgG anti-bovine alkaline phosphatase (tissue non-specific, liver/bone/kidney; TNALP)/donkey anti-rabbit IgG-horse radish peroxidase polyclonal antibody pair detection (21, 37, and 48 kDa) of bovine TNALP1...... 139 Figure 5. 3 The sequences of the real-time RT-PCR products (5’ to 3’ orientation). Within a sequence, underlined nucleotides indicate the position of forward and reverse primers...... 140 xi Figure 5. 4 Serum alkaline phosphatase (A), albumin (B), and blood urea nitrogen (C) concentrations in growing beef steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as sodium selenite (ISe), SEL-PLEX (OSe), or an 1:1 blend of ISe and OSe (MIX)1...... 141 Figure 5. 5 Serum sodium (D), phosphorus (E), and magnesium (F), concentrations in growing beef steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as sodium selenite (ISe), SEL-PLEX (OSe), or an 1:1 blend of ISe and OSe (MIX)1...... 143 Figure 5. 6 Western blot analysis of alkaline phosphatase (tissue non-specific, liver/bone/kidney, TNALP), bovine serum albumin (BSA) content in liver homogenates (45 μg per lane for BSA, 30 μg per lane for TNALP) after slaughter of growing beef steers grazing endophyte-infected tall fescue and supplemental with 3 mg Se/d in vitamin-mineral mixes as sodium selenite (ISe), SEL-PLEX (OSe), or an 1:1 blend of ISe and OSe (MIX)1...... 145 Figure 6. 1 Immunoblot validation of rabbit IgG anti-bovine ornithine aminotransferase (OAT)/donkey anti-rabbit IgG-horse radish peroxidase polyclonal antibody pair detection of bovine OAT1...... 216 Figure 6. 2 Microarray array-array intensity correlation plot...... 217 Figure 6. 3 Score-plot of principle component analysis of microarray transcriptome analysis of 21 liver samples from steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as sodium selenite (ISe, n=6, red sphere), SEL-PLEX (OSe, n=8, blue sphere), or an 1:1 blend of ISe and OSe (MIX, n=7, green sphere)1...... 218 Figure 6. 4 Flowchart of filtering algorithm and procedures identifying differentially expressed genes...... 219 Figure 6. 5 Hierarchical cluster analysis of the 738 genes selected as differentially expressed (ANOVA P-values of < 0.01 and false discovery rates of 33%) by the liver of steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as sodium selenite (ISe, n = 6), ≤SEL-PLEX (OSe, n = 8), or an 1:1 blend of ISe and OSe (MIX, n = 7)1...... 220 Figure 6. 6 The sequences of the real-time RT-PCR products (5’ to 3’ orientation). Within a sequence, underlined nucleotides indicate the forward and reverse primer positions...... 221 Figure 6. 7 Western blot analysis of EAAC1, GLT-1, GTRAP3-18 content in liver homogenates (35 μg per lane for EAAC1, GLT-1, GTRAP3-18, and ARL6IP1; 45 μg per lane for OAT) of growing beef steers grazing endophyte-infected tall fescue and supplemental with 3 mg Se/d in vitamin-mineral mixes as sodium selenite (ISe), SEL-PLEX (OSe), or an 1:1 blend of ISe and OSe (MIX)1. .. 225 Figure 6. 8 Overview of main glutamine/glutamate cycle and ammonia metabolic pathways in periportal and perivenous hepatocytes1...... 226 Figure 6. 9 Schemactic of pathways for proline metababolism1...... 228 Figure A1. 1 Whole blood selenium (Se) concentrations at weaning (Day 0) in heifer calves raised on free-choice vitamin-mineral mixes as sodium selenite (ISe) or an 1:1 blend of ISe and SEL-PLEX(organic Se) (MIX). Data are least squares
xii means (n=9 for ISe, 12 for MIX) ± SE. Means with different letters differ (P < 0.05)...... 246 Figure A1. 2 Serum cortisol concentrations after weaning and transportation events in heifer calves raised on free-choice vitamin-mineral mixes as sodium selenite (ISe) or an 1:1 blend of ISe and SEL-PLEX(organic Se) (MIX)1...... 247 Figure A1. 3 Serum albumin concentrations after weaning and transportation events in heifer calves raised on free-choice vitamin-mineral mixes as sodium selenite (ISe) or an 1:1 blend of ISe and SEL-PLEX(organic Se) (MIX)1...... 248 Figure A1. 4 Blood urea nitrogen concentrations after weaning and transportation events in heifer calves raised on free-choice vitamin-mineral mixes as sodium selenite (ISe) or an 1:1 blend of ISe and SEL-PLEX(organic Se) (MIX)1. ... 249 Figure A1. 5 Percentage of circulating neutrophils after weaning and transportation events in heifer calves raised on free-choice vitamin-mineral mixes as sodium selenite (ISe) or an 1:1 blend of ISe and SEL-PLEX(organic Se) (MIX)1. ... 250 Figure A1. 6 Percentage of circulating lymphocytes after weaning and transportation events in heifer calves raised on free-choice vitamin-mineral mixes as sodium selenite (ISe) or an 1:1 blend of ISe and SEL-PLEX(organic Se) (MIX)1. ... 251 Figure A1. 7 Relative mRNA expression of whole blood interleukin 8 after weaning and transportation events in heifer calves raised on free-choice vitamin-mineral mixes as sodium selenite (ISe) or an 1:1 blend of ISe and SEL-PLEX(organic Se) (MIX)1...... 252 Figure A1. 8 Relative mRNA expression of whole blood tumor necrosis factor alpha after weaning and transportation events in heifer calves raised on free-choice vitamin-mineral mixes as sodium selenite (ISe) or an 1:1 blend of ISe and SEL- PLEX(organic Se) (MIX)1...... 253 Figure A1. 9 Relative mRNA expression of whole blood interferon gamma after weaning and transportation events in heifer calves raised on free-choice vitamin-mineral mixes as sodium selenite (ISe) or an 1:1 blend of ISe and SEL- PLEX(organic Se) (MIX)1...... 254
xiii CHAPTER 1. Introduction
Tall fescue (Lolium arundinaceum) is the predominant temperate pasture grass grown within the transition zone of the eastern and central part of the United
States (Strickland et al., 2009b), covering approximately 15 million hectare
(Buckner et al., 1979). As a symbiotic endophyte of tall fescue, Epichloë coenophiala produces a variety of ergot alkaloids, which have been identified as causative agents of several disorders of different physiological systems of animals consuming endophyte-infected tall fescue. Collectively, the symptoms of these disorders are termed fescue toxicosis (Strickland et al., 2011). In the United States, the annual economic losses from decreased conception rates and weaning weights of beef cattle, equine and small ruminants grazing endophyte-infected tall fescue were estimated to exceed 2 billion dollars (Kallenbach, 2015).
In addition to the classic reduction of serum prolactin concentration, recent studies have reported that growing steers grazing high vs. low endophyte-infected tall fescue displayed classic endophyte toxicity symptoms for growth (decreased
ADG) and serological variables (e.g., decreased serum prolactin, alkaline phosphatase, and albumin) concomitant with an altered hepatic expression of several enzymes critical to amino acid and glucose metabolism (Brown et al., 2009).
Subsequent genomic profiling (microarray) and targeted gene (RT-PCR) analyses of the liver and pituitary from these steers indicated that the expression of genes for prolactin signaling; redox capacity; regulation of lactotroph, gonadotroph, and thyrotroph proliferation; gonadotrophin-releasing hormone-mediated signaling;
1 and selenium-based metabolism was impaired in cattle grazing high endophyte fescue (Matthews and Bridges, 2014; Liao et al., 2015; Li et al., 2017).
Compounding the negative effects of fescue toxicosis is that forages and grains grown in Southeastern USA, have low selenium (Se) contents due to Se- poor soil (Ammerman and Miller, 1975). Importantly, beef cattle operations in the
Southeastern USA have the highest percentage of Se-deficient animals compared with other surveyed regions of the USA (Dargatz and Ross, 1996). Beef cattle require 0.10 mg Se/kg of diet to meet the daily requirements (NRC, 1996). Thus, the diets of cattle in these and other regions with Se-deficient soils require Se supplementation. Inorganic form (ISe, sodium selenite) of Se is commonly supplemented in cattle diets. However, sources of organic forms of Se (OSe) in specially cultivated strains of yeast (Saccharomyces cerevisiae) are available and approved for use in beef cattle diets. Our lab’s previous work has shown that more
Se was found in whole blood, red blood cells, serum, and liver of heifers supplemented with an equimolar blend of ISe:OSe (MIX) or OSe than with ISe
(Brennan et al., 2011). Moreover, microarray analysis indicated that MIX stimulates gene expression involved in selenoprotein synthesis and glutamate/glutamine metabolism in the liver relative to ISe or OSe (Matthews et al., 2014). Serendipitously, some of the genes upregulated by MIX were found downregulated in the liver (Liao et al., 2015) and pituitary (Li et al., 2017) of steers grazing high vs. low endophyte-infected forages.
Therefore, the first goal of this dissertation was to investigate whether the
2 form of supplemental Se (ISe, OSe, and MIX) in vitamin-mineral mixes consumed by growing beef steers grazing endophyte-infected tall fescue pasture would ameliorate some of the negative physiological parameters associated with fescue toxicosis. The second goal was to elaborate and extend such findings by conducting transcriptome and targeted gene and protein expression analyses of the liver tissue of the same animals.
3 CHAPTER 2. Literature Review
2.1 Fescue Toxicosis
2.1.1 Tall Fescue
Tall fescue (Lolium arundinaceum (Schreb.) Darbysh) is one of the most widely distributed cool season, perennial grasses in the world. Although mainly originated from Western Europe (Hoveland, 2009), tall fescue has been distributed and cultivated in North and South America, South Africa, Australia, New Zealand, and Eastern Asia
(Hannaway et al., 2009). Within the transition zone of the eastern and central part of the United States, tall fescue is the predominant temperate pasture grass, covering approximately 14 million hectare (Thompson et al., 2001). The date that tall fescue was introduced into the United States is unknown, but it is believed that tall fescue was brought in as a contaminant in other grass seed imported from England before 1880
(Vinall, 1909). The extensive planting of tall fescue did not happen until the release of two cultivars in the early 1940s, Alta and Kentucky 31 (Hoveland, 2009). The ecotype of Kentucky 31 was initially found in 1931 and grown in a steep hill pasture in Menifee
County, eastern Kentucky (Fergus, 1972). After testing and selection, Kentucky 31 was released in 1942 as a cultivar (Fergus, 1952), and then soon became popular as forage pasture, roadside cover and turf in the eastern USA where no other cool-season perennial grass was adapted and persisted in pastures (Hoveland, 2009). The popularity of tall fescue can be explained by its ease of broad establishment, adaptability to a wide range of soils, extended grazing season, tolerance to poor management, pest resistance, and good seed production (Stuedemann and Hoveland, 1988). The symbiotic
4 interactions between tall fescue and endophytic fungi benefit the host in terms of greater resistance to insects, herbivores, pathogens, as well as enhanced environmental tolerance and overall competitiveness. In addition, it has been proven that certain endophytic genus such as Epichloë, and Balansia, can produce ergot alkaloids on endophyte-infected plants (Bacon, 1988; Flieger et al., 1997). The ergot alkaloids produced by these endophytes, especially Epichloë coenophialum-infected tall fescue, were believed the culprit the fescue toxicosis (Strickland et al., 2011). The first conclusive evidence was unclear until Bacon et al. (1977) and coworkers first reported that the presence of endophytic fungi, Epichloë typhina, in tall fescue was involved in the syndrome of fescue toxicosis. Later this endophyte was renamed as Acremonium coenophialum, and then Neotyphodium coenophialum (Morgan-Jones and Gams,
1982). Recent nomenclatural realignment of Neotyphodium species with genus
Epichloë officially termed this endophytic fungus as Epichloë coenophialum
(Leuchtmann et al., 2014).
2.1.2 Definition, Clinical Symptoms, and Economic Impacts
With the wider application of tall fescue in pastures, incidences of health problems and poor performance have long been reported in dairy heifers and milking cows consuming endophyte-infected tall fescue (Pratt and Haynes, 1950; Pratt and Davis,
1954). Later several grazing studies spanning multiple years reported that the gains of
beef steers on tall fescue were found significantly lower than on orchardgrass (Dactylis
5 glomerata L.) (Blaser et al., 1956; Harris, 1972). In addition, a beef cow/calf study
reported that the calf weight gain and cow conception rate was substantially decreased
on tall fescue than on tall fescue-clover (Petritz et al., 1980). Other than the negative
impacts on grazing cattle’s performances, three major disorders have been observed and characterized (Stuedemann and Hoveland, 1988).
One of the most acute and dramatic visible symptoms of cattle grazing endophyte- infected tall fescue is fescue foot, which was first reported by Cunningham (1949) in
New Zealand. The lameness symptom develops as early as 10 to 14 days (Cunningham,
1949) after cattle first graze the fescue, whereas signs of gangrene were reported as early as 25 days after the start of tall fescue grazing (Jacobson et al., 1970). The incidence was usually higher in cold weather with the signs: stiffness and soreness of tissue (dry gangrene) appearing near the end of hood or tail, lameness in hind quarters, loss of tail switch (Cunningham, 1949), as well as loss of gangrenous hooves in extreme cases (reviewed by in (Strickland et al., 2009a; Klotz, 2015). These signs in grazing cattle resemble the symptoms of gangrenous form of ergotism in human, which is caused by the vasoconstrictive effect of ergot alkaloids on extremities.
Fat necrosis, or abdominal lipomatosis, is another disorder associated with animal grazing endophyte-infected tall fescue. Unlike the visible signs of fescue foot, fat necrosis is only diagnosed in post-mortem examinations. Fat necrosis is a disorder defined by the accumulation of hard masses of mesenteric adipose tissue around the intestinal tract. The necrotic fat occupies critical spaces in the abdominal cavity, therefore potentially hinders the processes of digesta passage, reproductive capacities,
6 and parturition (Bush and Buckner, 1973; Waller, 2009; Klotz, 2015). However, it is unclear if the concurrent poor growth and reproductive performance were directly associated with fat necrosis. Limited literature is available in regard to the mechanism of fat necrosis formation and its physiological impacts on cattle.
The third disorder, summer slump, is often associated with unthrifty animal appearance and poor performance during the summer (Schmidt and Osborn, 1993).
Summer slump has been intensively reviewed (Bush and Buckner, 1973; Strickland et al., 2009a; Waller, 2009) and is characterized by reduced bodyweight gain, rough hair coat, elevated body temperature and respiration rate, reduced milk production, lesser tolerance to heat. In general, these three typical disorders belong to a more comprehensive toxicity syndrome, termed fescue toxicosis (Strickland et al., 2009b).
Considering tall fescue’s prevalence as a pasture grass in the southeastern United
States, it is self-evident that the economic loss of fescue toxicosis on livestock production is profound. Using the survey questionnaire data from forage and animal science extension specialists in 21 states, the annual economic losses in the United
States from decreased conception rates and weaning weights of beef cattle grazing endophyte-infected tall fescue were conservatively estimated at 609 million dollars
(Hoveland, 1993). When taking into account the influences on the equine and small ruminant industries, as well as the currency inflation, the overall annual losses are estimated to exceed 2 billion dollars (Kallenbach, 2015).
7 2.1.3 Ergot Alkaloids
2.1.3.1 History
The history of human using ergot alkaloids as natural pharmaceuticals is very long,
with the earliest report dating back to 1100 B.C., when ergot alkaloids were used in obstetrics (Schiff, 2006). As toxins, the earliest incident associated with ergot alkaloids was documented as a long-term ergot poisoning, also termed ergotism during the
Middle Ages (Caporael, 1976). The epidemic outbreaks of ergotism in medieval
European countries are now understood and have been attributed to the indirect consumption of ergot alkaloids from ergot-contaminated grains (Strickland et al., 2011).
Based on the different toxic symptoms, two forms of ergotism were characterized from these outbreaks. The first type of ergotism symptom was referred as gangrenous form
(Ergotismus gangraenosus) (Schiff, 2006), with typical symptoms of severe burning
(“fire”) sensation in the extremities (Wasson et al., 1978), therefore, it is also known as
“holy fire”, or “St. Anthony’s fire” (Flieger et al., 1997). The swelling and extreme burning pain of limbs are clearly due to the prominent peripheral vasoconstriction induced by ergot alkaloids (Flieger et al., 1997). The second form of symptom was described as the convulsive form (Ergotismus convulsivus) (Schiff, 2006). Besides the severe pain in limbs, patients suffered from this type typically developed delirium and hallucinations, accompanied with convulsions, and severe diarrhea. However, with the improvements on seed and grain sanitation techniques, and on farm management practices, most of the sclerotia is removed from the grain, resulting in a scarce incidence of ergotism in modern times.
8 Attempts to isolate pure ergot alkaloids from natural sources were made in the
1900s for therapeutic purposes. Ergotoxine was first isolated in 1906 (Barger and Dale,
1907) and thought to be a pure compound, but was later realized to be a mixture of four
alkaloids (De Costa, 2002). Ergotamine, as the first pure alkaloid, was isolated by
Arthur Stoll in 1918, and its pharmaceutical product was soon produced and proved to
relieve headaches induced by migraine (Tfelt-Hansen and Koehler, 2008). The isolation
of pure ergot alkaloids allowed scientists to specifically investigate their
chemical/structural and physiological/pharmacological properties, which dramatically
broadened pharmaceutical uses.
2.1.3.2 Chemistry of Ergot Alkaloids
Although more than 80 natural ergot alkaloids have been identified (Schiff, 2006),
the common structural feature of all ergot alkaloids is a tetracyclic ergoline ring system
with the nitrogen at 6 position methylated and carbon at 8 position variously substituted
(Figure 2.1), which has been reviewed in a number of papers (Berde, 1980; Garner et
al., 1993; Hafner et al., 2008). From a biosynthetic perspective, the indole part of the
ergoline ring is derived from tryptophan (Bu'Lock and Barr, 1968), and the methyl
group on nitrogen-6 is originated from methionine (Garner et al., 1993). In many ergot
alkaloids, a double bound usually exists between C-8 and C-9 or C-9 and C-10. The position of the double bond permits the compound to have epimers, which is reported tohave not only different sensitivities to temperature and solvents (Hafner et al., 2008), but also differently biological potency in animal systems (Berde and Stürmer, 1978;
9 Berde, 1980).
Based on the different type of substitutes on C-8 position of ergoline ring, ergot alkaloids are classified into three groups: 1) clavine alkaloids; 2) lysergic acid and its simple amides (derivatives); 3) ergopeptine alkaloids (Figure 2.2) (Schardl et al., 2006;
Wallwey and Li, 2011). As shown in Figure 2.2, clavine alkaloids generally are 6, 8- dimethylergolines with a few exceptions, such as chanoclavine, which has a 6, 7- Seco ring. The common feature of lysergic acid is characterized as having C-8 of ergoline ring substituted with a carboxyl group. Amidation of the carboxyl group on C-8 derives the lysergic acid amide (Schiff, 2006). Due to their high pharmacological activity, lysergic acid amides, such as ergometrine and methylergometrine, have been used to prevent than treat postpartum hemorrhage (De Costa, 2002; Rajan and Wing, 2010).
The third group, ergopeptine alkaloids, are structurally characterized as lysergic acid derivatives with a tripeptide moiety attached to its carboxy group by peptide-like amide bonds (Figure 2.2) (Hafner et al., 2008). Various substitutions at R1 and R2 accounts for the diversity of ergopeptine alkaloids. Among ergopeptines, ergovaline and ergotamine commonly draw more attention of researchers. Tandem MS revealed that ergovaline was the predominant alkaloid, and account for 84 to 97% of all the five detected ergopeptine alkaloids from tall fescue pasture (Lyons et al., 1986). Both ergovaline and ergotamine are vasoconstrictive and therefore have some therapeutically significant properties, especially ergotamine and its derivatives have been used as a therapy for vascular headaches, such as migraines (Schiff, 2006). The structural similarities of ergoline ring to the biogenic amines (dopamine, epinephrine,
10 norepinephrine, serotonin) explains many of the biological effects of ergot alkaloids at the cellular or molecular level (Weber, 1980).
2.1.4 Physiological Impacts of Consuming Ergot Alkaloids
Consumption of ergot alkaloids produced from symbiotic endophyte in tall fescue induces a comprehensive syndrome, termed fescue toxicosis, involved in different physiological systems of grazing animals. The impacts of consumption of ergot alkaloids from endophyte-infected tall fescue on animals have been intensively reviewed in regard to the animal microbial ecology, gastrointestinal system, neural and neuroendocrine systems, reproductive system, immune system, and cardiovascular system (Strickland et al., 2009b; Strickland et al., 2011). In this section, the major focus is on the impact of ergot alkaloids on several classical serological parameters and hepatic metabolic functions.
2.1.4.1 On Serological Parameters 2.1.4.1.1 Prolactin
Introduction
Prolactin is a peptide hormone mainly synthesized in and secreted from lactotrophs of the anterior pituitary (Freeman et al., 2000). The name of prolactin was originally termed based on the ability of an extract of bovine pituitary gland to promote lactation in rabbits (Stricker, 1928; Riddle et al., 1933). However, this name no longer represents its biological functions in mammals with the expansion of the knowledge
11 about prolactin. More than 300 different biological actions of prolactin have been
identified across reproduction, water and electrolyte balance, brain and behavior, and
immunoregulation (Saleem et al., 2018).
Prolactin structure, isoform, expression, and biology
Prolactin is conservatively encoded by a single gene, PRL, among all vertebrates.
In human, it is located on chromosome 6 (Owerbach et al., 1981) and composed of 5
exons and 4 introns (Truong et al., 1984). The human PRL cDNA contains 914
nucleotides with a 681-nucleotide open reading frame encoding the prolactin
prohormone of 227 amino acids. The cleavage of the 28 amino acid signal peptide
results in the mature prolactin protein with 199 amino acids and molecular weight of
23k Da (Cooke et al., 1981). A number of variants of prolactin have been characterized in many mammals as a result of alternative splicing of the transcript, proteolytic cleavage and other post-translational modifications of the peptide chain (Freeman et al.,
2000). Although a 137 amino acid prolactin alternative splicing variant has been described in the rat anterior pituitary (Emanuele et al., 1992), the most prolactin variants
are produced from post-translational modifications of mature protein in the anterior
pituitary or the plasma, including proteolytic cleavage, dimerization and
polymerization, phosphorylation, glycosylation, sulfation, and deamidation (Bernard et
al., 2015). Proteolytic cleavage of the 23 kDa mature protein results in the 14 kDa, 16
kDa, and 22 kDa prolactin variants, as reviewed in (Freeman et al., 2000).
In circulation, the majority (65-85%) of the prolactin exists in the form of monomeric 23 kDa prolactin. However, prolactin is also present in two other forms,
12 termed “big prolactin” and “big-big prolactin” (macroprolactin), accounting for 10-20% and less than 10% of the total circulating prolactin, respectively (Fahie-Wilson and
Smith, 2013). The “big prolactin” is the dimmer of monomeric form with a molecular mass of 40-60 kDa, whereas “big-big prolactin” refers to a monomeric prolactin-IgG complex (autoantibodies) with a molecular weight of approximately 150 kDa (Lippi and Plebani, 2016). Regardless, the bioactivity of these two non-monomeric prolactin form is minimal in vivo, because they are likely to be restricted to the intravascular compartment by virtue of size (Fahie-Wilson and Smith, 2013). What’s more, the prolactin-IgG auto-antibody complex may not bind with the prolactin receptor due to steric hindrance (Hattori et al., 2007).
Although predominantly synthesized and secreted by lactotrophic cells of the anterior pituitary gland, prolactin is also expressed and secreted in various cells and tissues, collectively called extrapituitary prolactin (Ben-Jonathan et al., 1996). The identified sites of extrapituitary prolactin expression and secretion include decidua, mammary gland, ovary, prostate, testis, lymphocyte, endothelial cells and brain (Ben-
Jonathan et al., 1996). More recently findings have shown that extrapituitary prolactin is also present in skin and hair follicles (Langan et al., 2010), adipose tissue
(Brandebourg et al., 2007) and cochlea (Marano et al., 2013). The regulation of the extrapituitary prolactin expression and secretion, as well as its function within these tissues has been reviewed recently (Marano and Ben-Jonathan, 2014). Transcription of extrapituitary prolactin gene is regulated by a super distal promoter regions at -3500 to
-5000 (Berwaer et al., 1991), whereas the pituitary prolactin gene is regulated by a
13 different proximal promoter region contains Pit-1 binding site (Ben-Jonathan et al.,
1996). In addition to the classic endocrine pathway of pituitary prolactin, the extra-
pituitary prolactin can also act on the prolactin-secreting cell itself and on adjacent cells
by autocrine and paracrine mechanisms, respectively (Bole-Feysot et al., 1998).
The actions of prolactin on the cellular level are mediated by binding to its trans-
membrane receptor, which is constitutively expressed by various cells and tissues
(Bole-Feysot et al., 1998). Prolactin receptor is a member of the class 1 cytokine
receptor superfamily, and composed of an extracellular domain, a single
transmembrane domain and an intracellular signal-transducing domain (See review,
(Freeman et al., 2000)). Multiple prolactin receptor isoforms resulting from alternative splicing of the primary transcript have been identified in the mouse (Davis and Linzer,
1989), rat (Ali et al., 1991), and human (Boutin et al., 1989). In cattle, two distinct
prolactin receptor isoforms have been identified as a result of alternative splicing events
(Bignon et al., 1997): long isoform with 557 amino acid (Scott et al., 1992) and short
isoform with 272 amino acids (Schuler et al., 1997). The human prolactin receptor long
isoform forms a homodimer when the ligand (prolactin) binds the two extracellular
interaction sites, which triggers the downstream intracellular signal transduction,
including JAK-2, Src family of tyrosine kinases and phosphatidylinositol 3-kinase
(PI3K)/AKT, mitogen-activated protein kinase (MAPK) 3 and serine/threonine kinase
Nek3-Vav2-Rac1 pathways, as reviewed in (Saleem et al., 2018). However, little is
known about the intracellular signal transduction mediated by short isoform of prolactin
receptor (Bernard et al., 2015). Furthermore, the short isoform can form a heterodimer
14 with long isoform of prolactin receptor and, therefore, inhibit the activation of long
isoform (Bole-Feysot et al., 1998).
Regulation of prolactin expression and secretion
Prolactin expression and secretion in the pituitary is under deliberate regulation,
and is a net effect of various stimulatory and inhibitory factors, as extensively reviewed
in (Freeman et al., 2000). Of these factors, dopamine plays a tonic and crucial inhibitory
role in the regulation of pituitary prolactin secretion, whose secretory activity is
spontaneously high in lactotrophs (Grattan and Kokay, 2008). Although not regulated
by the classical pituitary hormone-mediated negative feedback loop, pituitary prolactin
is still regulated in a negative short-loop feedback manner, with prolactin itself
providing the afferent signal to stimulate the dopaminergic neurons in the hypothalamus.
Dopamine is mainly secreted by dopaminergic neurons located at the periventricular
and arcuate nuclei of the medial-basal hypothalamus (Goudreau et al., 1992; Goudreau
et al., 1995). Dopamine receptors expressed on lactotroph membranes belong to the D2-
like family (Caron et al., 1978). Several transduction mechanisms of D2 dopamine
receptor have been characterized that mediate the dopaminergic control of prolactin
secretion (see review (Freeman et al., 2000)). The activation of D2 dopamine receptor
by coupling with Gi-3α can excite voltage-sensitive potassium channels and inhibit adenylyl cyclase activity thereby suppressing prolactin gene expression (Ishida et al.,
2007). Concomitantly, while coupled with Goα, D2 dopamine receptor inhibits voltage-
sensitive calcium channels, therefore block the Ca2+ influx through voltage-sensitive calcium channels which is responsible for the basal prolactin secretion (Saleem et al.,
15 2018).
The release pattern of prolactin changes under different physiological conditions, especially in the different reproductive states, including in lactation, estrous and menstrual cycles, and mating and pregnancy, as intensively reviewed in (Freeman et al.,
2000). Circadian rhythm of prolactin secretion was observed in humans with concentrations of plasma prolactin the highest during sleep and the lowest during the waking hours (Parker et al., 1974). In lactating dairy cows, peripheral prolactin concentrations follow a circadian rhythm, but not tightly related to sleep patterns
(Lefcourt et al., 1994). Importantly, prolactin secretion is also affected by the daylight length in seasonal mammals. Specifically, the shortened daylight/photoperiod results in the diminution of prolactin secretion in hamsters (Badura and Goldman, 1997), ewes
(Kennaway et al., 1983), rams (Lincoln et al., 1978), and cattle (Peters and Tucker,
1978; Tucker et al., 1984). Furthermore, Schams (1972) and Schams and Reinhardt
(1974) reported that the basal prolactin levels were affected by seasonal changes in cattle regardless of sex, age, and lactation.
Biological functions of prolactin
Reproduction. As the name indicates, the most recognized and predominant function of prolactin is promoting the growth of and development of mammary gland
(mammogenesis), stimulating the milk secretion (lactogenesis), and maintaining the lactation (galactopoiesis) (Freeman et al., 2000). Prolactin directly regulates the lobuloalveolar growth in the late stage of mammary gland development, as evidenced by prolactin (Horseman et al., 1997) or prolactin receptor (Ormandy et al., 1997)
16 knockout studies, which abnormal development of mammary gland with complete lack
of lobuloalveolar units was observed. The requirement of pituitary prolactin for
lactogenesis is proved by the fact that hypophysectomy during pregnancy prevents
subsequent lactation (Nelson and Gaunt, 1936). The maintenance of milk secretion
(galactopoiesis) requires different sets of hormones in different mammals, but the
common absolute requirement is prolactin (Freeman et al., 2000). However, it should
be noted that these processes of mammogenesis, lactogenesis, and galactopoiesis are
not solely controlled by prolactin, instead a great deal of research indicates that these
processes are orchestrated by the effects of many hormones including estrogen, progesterone, insulin, glucocorticoid, growth hormone, and prolactin (Saleem et al.,
2018).
The functions of prolactin on other aspects of reproduction have been intensively
reviewed in (Bole-Feysot et al., 1998; Freeman et al., 2000). In rodents, it has been
recognized that prolactin can act as either a luteotropic hormone after mating or a
luteolytic hormone in the absence of a mating stimulus (Armstrong et al., 1970;
Behrman et al., 1970; Ota et al., 1982). There are data indicates that various
reproductive behaviors are also affected by prolactin (Dutt et al., 1994). Of these,
parental behaviors are probably the best-characterized prolactin-driven behavior
(Bridges, 1994). But literature has suggested that maternal behaviors are not initiated by prolactin itself, and the latency to the onset of maternal behavior is decreased by prolactin (Bridges et al., 1990).
Water and electrolyte balance. The role of prolactin on osmoregulation is
17 critically important for lower vertebrates, especially for teleost fishes that migrate between fresh and seawater (Bern, 1975). The roles of prolactin on the gill and kidney in regulating water and electrolyte hemostasis of fish have been thoroughly reviewed in (Bole-Feysot et al., 1998). In mammals, the roles of prolactin on osmoregulation are one of the least understood functions (Shennan, 1994). It is suggested that prolactin promotes the retention of Na+ and K+ in the kidney (Richardson, 1973). The expression of prolactin receptors has been identified in duodenum, jejunum, and ileum epithelium of rabbits (Lobie et al., 1993), rats (Ouhtit et al., 1994), and human (Freemark et al.,
1997), which indicates a functional role for prolactin in intestine. Various studies showed that prolactin promotes the absorption of Na+, K+ and Ca2+ in the intestine
(duodenum, jejunum, and ileum) epithelium (Mainoya et al., 1974; Mainoya, 1975b;
Mainoya, 1975c; Mainoya, 1975a). A number of studies also showed that prolactin is
able to stimulate the calcium transport across the intestinal epithelial membrane of rats
both in vitro and in vivo, and these actions are inhibitable by bromocriptine
(Charoenphandhu and Krishnamra, 2007). What’s more, the transcellular active and
solvent-drag induced transport mechanisms of calcium were stimulated by prolactin
(Charoenphandhu et al., 2001; Tanrattana et al., 2004). Taken together, these data of
prolactin promoting solute transport and sodium/potassium/calcium retention seems to
be a mechanism whereby prolactin contributes to the preparation by the pregnant
mother for subsequent lactation (Freeman et al., 2000).
Immune response. As a neuroendocrine hormone, prolactin plays essential roles
in the communication of immune-neuroendocrine network. Although mainly secreted
18 in the pituitary, prolactin can be produced by macrophages, B cells, NK cells, T cells, thymocytes, and peripheral blood mononuclear cells (O'Neal et al., 1992; Pellegrini et al., 1992; Matera et al., 1997; Gingras and Margolin, 2000). Not surprisingly, the prolactin receptor is widely present through the immune system, including monocytes, lymphocytes, macrophages, NK cells, granulocytes, and thymic epithelial cells (Orbach et al., 2007). Therefore, the binding of prolactin to its receptor activates intracellular signaling pathways that regulates the humoral and cellular immune responses in physiological as well as pathological states (as reviewed in (Bole-Feysot et al., 1998;
Freeman et al., 2000)), such as autoimmune diseases (Tang et al., 2017; Borba et al.,
2018).
Suppression of prolactin, a hallmark of fescue toxicosis
Depression of circulating prolactin is consistently observed in animals suffering from fescue toxicosis, as a result of grazing endophyte-infected tall fescue (Hurley et al., 1980; Hemken et al., 1984; Boling, 1985; Boling et al., 1989; Davenport et al.,
1993). Therefore depressed circulating prolactin is regarded as an indicator of fescue toxicosis (Strickland et al., 1993; Klotz, 2015). Early efforts to investigate the mechanisms of the ergot alkaloids-induced the suppression of circulating prolactin were focused on the pituitary because, as mentioned in the section of prolactin release and regulation, most of the prolactin is synthesized in and secreted from the anterior pituitary, and under the tonic inhibitory regulation of dopamine. In concurrence with the reduction of serum prolactin, Schillo et al. (1988) reported that the concentration of prolactin in the anterior pituitary and the concentration of dopamine in the stalk median
19 eminence were decreased in steers grazing endophyte-infected tall fescue. It was
believed that the ergot alkaloids might inhibit the pituitary prolactin synthetic capacity
by acting on the dopaminergic neurons (Schillo et al., 1988). Soon, the association of ergot alkaloids with D2 dopamine receptor was indirectly proven by a rat study. Larson et al. (1994) reported that the D2 dopamine receptor mRNA and density (Bmax) in the
whole brain were decreased in rats fed with endophyte-infected tall fescue seed,
whereas the reduction can be restored by injection of dopamine antagonist. Later, two
in vitro cell culture studies demonstrated that ergovaline extracted from endophyte-
infected tall fescue binds and activates the D2 dopamine receptor as a dopaminergic agonist (Larson et al., 1995), and elicits similar EC50 as commercially available ergot
alkaloids (ergotamine tartrate and ergonovine) (Larson et al., 1999). The structural
similarity between the ergoline ring portion of ergot alkaloids with dopamine allows them to interact with D2 dopamine receptors (Berde and Stürmer, 1978). As mentioned in the prolactin secretion regulation section, the activated D2 dopamine receptors in lactotrophs inhibit prolactin gene expression by blocking adenylyl cyclase and prolactin exocytosis through modulating potassium and calcium channels (Fitzgerald and Dinan,
2008). It is not surprising that reductions of milk yield have been observed in cattle consuming endophyte-infected tall fescue (Strahan et al., 1987; Lean, 2001), given the critical roles of prolactin in lactation. A number of studies have demonstrated that prolactin stimulates hair growth, molting, and shedding in sheep and mink (Foitzik et al., 2009). As discussed in Klotz (2015), the serum prolactin concentration in cattle exposed to endophyte-infected tall fescue may be too low to initiate the shedding of the
20 winter hair coat, therefore causing the symptoms of rough hair coat, which is one of the most visible symptoms of fescue toxicosis. Nevertheless, other than a hallmark of fescue toxicosis, more studies need to focus on understanding the physiological and functional consequences of the decreased serum prolactin induced by consuming endophyte-infected tall fescue.
2.1.4.1.2 Alkaline Phosphatase
Introduction
Alkaline phosphatase (ALP; EC 3.1.3.1) contains a number of heterogeneous enzymes that are catalytically involved in the hydrolysis of monophosphate esters
(Fernandez and Kidney, 2007), and the dephosphorylation of a variety of substrates
(Millan, 2006). The binding of two Zn2+ ions and one Mg2+ ion on the catalytic site of
ALP is necessary for enzymatic function (Van Hoof and De Broe, 1994; Hoylaerts et
al., 1997). The conserved serine residue on catalytic site functions over a pH range of
6.5 - 10.5, and prefers an optimal alkaline pH of 9 - 10.5 (Vestn OftalmolMader et al.,
1994; Poelstra et al., 1997; Picher et al., 2003).
Isoenzymes and isoforms
In mammals, ALP has 2 isoenzymes encoded by 2 distinct gene loci (as reviewed
in (Goldstein et al., 1980; Hank et al., 1993)): (1) the tissue-nonspecific isoenzymes which are expressed in most tissues, including developing nervous system, skeletal tissues, liver, bone, kidney, and placenta; (2) the intestinal isoenzymes which are expressed in intestinal epithelium. However, in humans and other higher primates, two 21 more gene loci were discovered and responsible for coding a placental isoenzyme and
a germ cell/placental-like isoenzyme, respectively (Millan, 2006).
Besides the various isoenzymes produced transcriptionally, different isoforms of
ALP can be produced by tissue-specific post-translational modifications from one isoenzyme (gene product) (Fernandez and Kidney, 2007). ALP from liver, bone and kidney is transcribed from the same tissue-nonspecific gene locus, and is then modified post-translationally, which result in tissue-specific ALP isoforms.
Function and distribution
In mammals, although its exact physiological function on different tissue has not been fully delineated, ALP has been found widely expressed on the cellular membrane of various tissues throughout the body (Harris, 1990). Alkaline phosphatase was found
on the canalicular membranes of hepatocytes (Inoue et al., 1983), luminal surface of
biliary epithelial cells (Milne, 1985), brush borders of intestinal epithelium (Moog and
Glazier, 1972; Hirano et al., 1985), and cell membranes of osteoblasts (Doty and
Schofield, 1976). Crystallographic structure studies of mammalian ALP (Le Du et al.
(2001); human placental ALP) found that ALPs are ecto-enzymes bound to the plasma membrane via a glycosylphosphatidylinositol (GPI) anchor. However, membrane-
anchored ALP may be released from the membrane, becoming a plasma-soluble form
in the circulation. This process can occur via the cleavage action of
phosphatidylinositol-specific phospholipase C (Van Hoof and De Broe, 1994) or D
(Low and Huang, 1991) on GPI-linkage.
22 Serum alkaline phosphatase
Total serum ALP activity is contributed from various soluble ALPs released from membranes of different tissues. Therefore, the dynamic profile of various isoenzymes and isoforms of ALP in serum, during pathological changes, provides the theoretical foundations of measuring serum ALP activities for diagnostic purposes. In cattle, serum
ALP is mostly originated from the liver and bone (Doornenbal et al., 1988), thus it has been used as a serum biomarker of liver or bone-related diseases. A clear and consistent agreement on the reference range of cattle serum ALP activity has not been established so far. A wide variety of reference ranges has been suggested in papers, books, and veterinary diagnostic laboratories (Table 2.1). Despite variations from different quantification methods, the broad reference ranges (0 to about 500 U/L) reflect that the serum ALP activity dynamically fluctuates with various physiological processes of healthy cattle. A neonatal calf study observed that the serum ALP activity was about
800 U/L in newborn calves, and steadily decreased to 400 U/L at 83 days of age
(Knowles et al., 2000). A similar negative correlation between serum ALP activity and age also was demonstrated, where newborn and growing calves had greater serum ALP activity than that of adult animals (Roussel et al., 1982; Doornenbal et al., 1988).
Although ALP isoforms were not determined, much of the serum ALP activity in calves was believed from the bone origin, as indicative of rapid skeletal growth (Doornenbal et al., 1988). However, kidney ALP isoform was found present in the serum of newborn calves (Miyazawa and Tomoda, 1991). Another physiological stage that could elevate serum ALP activity is lactation. In lactating dairy cows, serum ALP activity increased
23 by 80% due to increases in liver and bone ALP isoforms (Sato et al., 2005).
However, fluctuations of the ALP activity in serum may also be contributed by
ALP originating from other tissues, therefore reflect the physiological or pathological changes beyond those of hepatic and/or skeletal (osseous) origin. Cattle suffering from intractable diarrhea showed an elevated serum ALP activity, which was contributed from an increase in serum intestinal ALP as demonstrated by enzyme inhibition studies
(Healy, 1971). An increase of total serum ALP activity was reported in cows of mid and late pregnancy (Yokus and Cakir, 2006). Although ALP isoform was not measured, this increase was likely due to an increased placental ALP.
Serum indicator of fescue toxicosis
Decreased serum total ALP activity has been widely reported in animals consuming ergot alkaloids from endophyte-infected tall fescue, as summarized in Table
2.2. The consistently suppressed serum alkaline phosphatase activity has been regarded as a repeatable clinical measure of fescue toxicosis (Oliver et al., 2000). Various cattle studies, using grazing or fescue seed model, have induced fescue toxicosis via different combinations of ergot alkaloids dose, exposure time, and ambient temperature (Table
2.2). But it remains unclear if the reduction of serum ALP activity follows a dose- and/or time-dependent manner. On the other hand, heat stress seems to impact the reduction of serum ALP activity, as observed in a study where the magnitude of the reduction became more dramatic as the ambient temperature increased from 21 °C to
34 °C (Boling et al., 1989). Nevertheless, given the wide reference range of serum ALP
24 activity (Table 2.1), it is difficult to estimate the clinical significance of the suppressed
serum ALP activity in cattle suffering fescue toxicosis.
The exact mechanism of this decrease of serum total ALP activity induced by fescue toxicosis has not been fully delineated. Due to structural similarities with dopamine and other biogenic amines, ergot alkaloids bind and stimulate dopamine type two receptors (Larson et al., 1994; Larson et al., 1999), consequently inhibiting
adenylyl cyclase and then cyclic AMP (Fitzgerald and Dinan, 2008). Meanwhile, in
vitro studies have shown that cyclic AMP induces de novo synthesis of ALP mRNA
and resulting in an increased ALP protein production in mouse L-cells (Firestone and
Heath, 1981). Also, cyclic AMP has been reported to induce the tissue non-specific
ALP mRNA expression (liver/bone/kidney, tissue non-specific isoenzyme) in L929
fibroblastic cells (Gianni et al., 1993). Therefore, researchers (Boling et al., 1989; Rice
et al., 1998) have speculated that ergot alkaloids could negatively impact the ALP induction by inhibiting cyclic AMP, thus resulting in a decrease of total ALP or certain
ALP isoform activity in the serum. Due to the majority of ALP activity in serum is the
liver isoform (McComb et al., 1979), the decrease of serum ALP activity was suspected
to be due to a decrease of liver isoform (Boling et al., 1989; Rice et al., 1998). However,
an ALP isoform study suggested the decreased serum ALP activity in cattle suffering
fescue toxicosis was attributed to decreases in the activities of intestinal and bone
isoforms (Schultze et al., 1999). It was speculated that the metabolic inhibition of
synthetic pathways or actual loss of mucosal cells might be responsible for the
decreased activity of intestinal ALP. Schultze et al. (1999) suggested that the reduced
25 activities of bone ALP could be explained by a decreased osteoblastic activity as
evidenced by reduced intake and growth of cattle grazing endophyte-infected tall fescue.
Suppression of intake and growth performance observed in cattle under fescue toxicosis might be another reason for the decreased serum ALP activity. Because according to an
epidemiological survey, malnutrition and magnesium deficiency are associated with
low serum ALP activity in the adult male population (Lum, 1995).
2.1.4.1.3 Albumin
Introduction
The mature protein of bovine serum albumin is a 66.5 kDa negatively charged
protein with 583 amino acids, which shares 75.6% sequence homology with human
serum albumin. According to X-ray crystallographic studies, bovine serum albumin is composed of three homologous helical domains arranged in a heart-shaped molecule
(Majorek et al., 2012). The primary structure of bovine serum albumin possess 35
cysteine resides, so after forming 14 internal disulfide bonds, a free cysteine residue
(thiol group) is left, which is critical to certain functions of the protein.
As the most abundant protein in serum of healthy adults, albumin accounts for 50%
of the total serum protein (Rothschild et al., 1972). It is synthesized and secreted from
hepatocytes as a nonglycosylated protein into blood circulation, which makes up about
13% of the total protein produced by the liver (Peters, 1977). Within hepatocytes, the
synthesis and secretion process of albumin involves the transfer from bound ribosome
to rough membrane to cisterna, subsequently via the smooth endoplasmic reticulum to
the Golgi complex, eventually through the cell membrane to the sinusoid (Peters Jr, 26 1995). However, only 20-30% of hepatocytes produce albumin under normal physiological conditions, therefore the synthetic capacity can be upregulated on demand by a factor of 200-300% (Evans, 2002). The rate of albumin production is controlled at both transcriptional and posttranscriptional levels (Prinsen and de Sain- van der Velden, 2004), and more specifically influenced by colloid osmotic pressure, supply of amino acids, hormones (such as insulin, growth hormones, thyroxine, and cortisol), and inhibitory cytokines (particularly interleukin-6) (Dufour et al., 2000;
Kaneko et al., 2008). After secretion into the blood circulation, 6-8% of albumin molecules are readily turned into glycoalbumin, where the lysine resides in albumin are non-enzymatically glycated after conjugation with glucose or galactose. As revealed by isotope injection studies, the catabolism of serum albumin in rabbit occurs at all tissues, but 40-60% of the albumin dose are degraded by the muscle, liver, and kidney (Yedgar et al., 1983; Bent-Hansen, 1991). The half-life of albumin shows considerable species variations, ranging from 1.9 days in the mouse to 16.5 days in the cow (Kaneko et al.,
2008).
Function
One of the major functions of albumin is mediating colloid osmotic pressure and the blood volume. Although accounting 50% of the total serum protein, albumin is responsible for 80% of the colloid osmotic pressure, due to albumin having a lower molecular mass than serum globulins mass (170 kDa) and a low iso-electric point
(Prinsen and de Sain-van der Velden, 2004). Albumin also serves as a circulating depot,
27 and a transport vehicle for a number of molecules, including fatty acid, thyroxine,
cholesterol, nitric oxide, bilirubin, and metal ions (Kaneko et al., 2008). Through
covalent glycations, albumin also binds with D-glucose and D-galactose, which affects its charge and therefore may impact capillary permeability characteristics (Evans, 2002).
Because of the single exposed cysteine residue, albumin may be the predominating antioxidant in the circulation (Anraku et al., 2001), and involves in the scavenging of reactive oxygen and nitrogen species.
Serum albumin concentration is commonly measured for clinically diagnostic purposes. Typically, increases of serum albumin may indicate dehydration, prolonged tourniquet use during collection, or specimen evaporation (Doumas and Peters, 1997).
The decreases of serum albumin concentration may be reflective of the liver, kidney, gastrointestinal disease, malnutrition (decreased protein intake), acute phase response, and blood/plasma loss (Kaneko et al., 2008). In contrast to the acute phase protein, serum albumin concentrations decrease gradually during infectious and inflammatory disease.
Fescue toxicosis and serum albumin
Two studies spanning from April to August of 1996 to 1998 have reported that serum albumin concentration of Angus steers was not affected by grazing endophyte- infected tall fescue (Schultze et al., 1999; Oliver et al., 2000). However, in these two studies, it is worth noting that the ergot alkaloids concentrations were not measured, instead endophyte frequency in tillers was reported as greater than 80% infected and 0%
28 infected in endophyte-infected and endophyte-free tall fescue respectively. In contrast, a summer-long grazing study showed that the serum albumin concentrations was lower
(P = 0.05) in steers grazing high endophyte-infected (0.52 ppm of ergovaline and ergovalinine) tall fescue than those grazing low endophyte-infected (0.01 ppm of ergovaline and ergovalinine) tall fescue for 85 days (Brown et al., 2009). Interestingly, this decreased concentration of serum albumin was also observed on day 37 (P = 0.03)
and day 59 (P = 0.01) of steers grazing high endophyte-infected tall fescue (Jackson et
al., 2015). It is possible that the hepatic albumin synthetic capacity was reduced in steers
grazing endophyte-infected tall fescue (Brown et al., 2009), and possibly as a
consequence of reduced intake and malnutrition.
2.1.4.2 On Liver Metabolic Physiology and Function
The metabolism of ergot alkaloids has yet to be fully characterized, but it is suggested that absorbed ergot alkaloids are transported via the lymphatic system or the mesenteric veins through the portal system and liver to the systemic circulation (Eckert et al., 1978). Moreover, the enzymatic metabolism of ergot alkaloids has been linked to the CYP3A of cytochrome P450 (CYP) enzyme family in microsomes of bovine liver, resulting in hydroxylated metabolites (Moubarak and Rosenkrans, 2000). These data clearly indicate that the liver is exposed to ergot alkaloids and is tightly involved in their metabolism. In addition, a great number of studies have observed the decrease of serum albumin, alkaline phosphatase, alanine transaminase, aspartate transaminase, lactic acid dehydrogenase concentrations in cattle consuming endophyte-infected tall
29 fescue (Dougherty et al., 1991; Oliver et al., 2000; Nihsen et al., 2004; Jackson et al.,
2015), indicating potentially altered liver metabolic capacities. Therefore, the biological impact of consuming ergot alkaloids or fescue toxicosis, directly or indirectly, on liver function needs to be further investigated. Several studies have characterized the effect of fescue toxicosis induced by consuming endophyte-infected tall fescue seeds on hepatic transcriptome profiles using mice (Bhusari et al., 2006), rats (Settivari et al., 2006), and steers (Tanaree et al., 2013). These studies collectively demonstrated that fescue toxicosis is associated with changes in expression of hepatic genes involved in carbohydrate (Bhusari et al., 2006; Settivari et al., 2006), cholesterol (Bhusari et al.,
2006) and lipid (Settivari et al., 2006) metabolism, immune response (Settivari et al.,
2006), and cytochrome P450 (CYP) family and antioxidant activities (Settivari et al.,
2006; Tanaree et al., 2013). More specifically, the expression of critical genes responsible for carbohydrate metabolism (phosphorylase kinase gamma 2 and glucagon receptor) was decreased in mice fed endophyte-infected tall fescue seeds (Bhusari et al.,
2006). In addition, an elevated gluconeogenic capacity was observed in rats suffering fescue toxicosis, as evidenced by the increased expression of cytosolic phosphoenolpyruvate carboxykinase and fructose-1,6-bisphosphatase mRNA (Settivari et al., 2006). However, it should be noted that the dose and exposure length of ergot alkaloids were different in these rodent and steer models. Particularly in the steer study
(Tanaree et al., 2013), a considerable amount of variability in microarray results was observed and potentially resulted from low sample size (n = 4). Moreover, although a tall fescue straw diet (576 ng/g ergovaline) was fed for 29 days, the concentration of
30 serum prolactin of the steers was not affected by consumption of tall fescue straw
(Tanaree et al., 2013).
A more industry-relevant model (Brown et al., 2009) was used to investigate the effect of grazing endophyte-infected tall fescue on growing steers and the hepatic expression of enzymes and transporters critical for amino acid, carbohydrate, and nitrogen metabolism. After summer-long (86 days) grazing of low (LE) vs. high (HE) endophyte-infected tall fescue, HE steers showed lower absolute and relative liver weight than LE steers (Brennan et al., 2011), which similar reduced liver weight has been observed in rats consuming endophyte-infected tall fescue seed (Chestnut et al.,
1992; Settivari et al., 2006). Importantly, HE steers displayed an elevated hepatic content (Western blotting) of aspartate transaminase and cytosolic phosphoenolpyruvate carboxykinase, collectively indicating an elevated capacity for gluconeogenesis partially by an increased carbon influx from metabolizing aspartate for phosphoenolpyruvate production (Brown et al., 2009). Hepatic transcriptome profile of these steers was later evaluated and revealed 374 differentially expressed genes (P < 0.01) functionally involved carbohydrate (gluconeogenesis) and amino acid
(proline and serine) metabolism, cell-mediated immune response, and glucocorticoid receptor signaling network (Liao et al., 2015). With regard to the amino acid metabolism, the combination of proline dehydrogenase 1 (proline catabolizing) downregulation and pyroline-5-carboxylate reductase 1 (proline synthesizing) upregulation strongly indicated an increased synthetic capacity of proline in the liver of
HE steers. Similarly, an increased hepatic capacity for serine synthesis was also
31 evidenced by the upregulation of phosphoserine phosphatase, which regulates the serine biosynthesis from 3-phophoglycerate (Liao et al., 2015). Together with the
previous findings of increased protein content of aspartate transaminase and cytosolic
phosphoenolpyruvate carboxykinase (Brown et al., 2009), the upregulation of alanine
transaminase mRNA content from the same liver of the HE steers indicated another
potential source of amino acid carbon (pyruvate) for elevated gluconeogenic capacity
(Liao et al., 2015), besides oxaloacetate carbons (Brown et al., 2009). The increased
protein content of COX4 in the liver of HE steers suggested that an increased hepatic
mitochondrial mass and ATP synthesizing capacity, an understanding that is consistent
with the findings that liver from HE steers had a greater capacity for the ATP-
demanding syntheses of glucose, proline, and serine.
To further expand the understandings from microarray results, a custom-designed, cattle-specific, miRGE Nanostring (NanoString Technologies, Seattle, WA, USA) was
used to evaluate the effect of grazing high vs. low endophyte-infected tall fescue on selected hepatic RNA targets from canonical pathways associated with amino acid, Se, and oxidative stress metabolism (Matthews and Bridges, 2014). Consistent with the microarray results, the Nanostring data indicate that hepatic glutamate/glutamine cycle metabolism was impaired, and glutamate, alanine, and aspartate carbons were available for gluconeogenesis. Also as initially identified by microarray analysis, the capacity for proline synthesis from glutamate and ornithine was increased. An unexpected and novel finding from Nanostring analysis was that expression of 10 selenoprotein genes was decreased by grazing high endophyte-infected tall fescue, including the decreased
32 expression of two genes responsible for selenocysteine synthesis and incorporation into selenoproteins (SEPHS1, SEPSECS).
In summary, the literature from both rodent and cattle models provide an initial insight for the potential impact of fescue toxicosis on hepatic metabolism, whereas the mechanistic underlying of these alterations, as well as their whole body physiological consequences, remain to be determined.
2.1.4.2.1 Liver Metabolic Zonation and Glutamate/Glutamine Cycle In mammals, liver functions as the predominant metabolic organ responsible for whole-body energy and nitrogen metabolism, detoxification of toxins, xenobiotics and endogenous metabolic byproducts, as well as the synthesis of bile, serum proteins and membrane lipids (Schleicher et al., 2015). These diverse functions are achieved by the unique spatial organization of hepatocyte along the sinusoid of the liver. From a histological perspective, there are three zones arbitrarily distinguished, periportal, intermediate, and pericentral/perivenous zone (Jungermann and Kietzmann, 1996). The periportal zone includes the hepatocytes adjacent to the branches of the portal triad, consisting of portal vein, hepatic artery, and bile duct. The pericentral zone consist the hepatocytes surrounding the central vein, and an intermediary zone locates between pericentral and periportal zone. As comprehensively reviewed in several papers (Boon et al., 1999; Braeuning et al., 2006; Schleicher et al., 2015), the activities of critical enzymes in a plethora of metabolic pathways were preferentially identified in one or the other zone, therefore indicating heterogeneous function capacities in different zones, known as metabolic zonation (Jungermann and Sasse, 1978; Gebhardt, 1992). The 33 zonation of liver is a necessary and beneficial for most of its functions, especially in
homeostasis. One benefit is that the anabolic and catabolic opposing pathways can be
spatially separated to prevent futile cycling (Kietzmann, 2017), for example, glycolysis
and gluconeogenesis occur mainly in pericentral and periportal hepatocytes,
respectively. Another advantage is that metabolic zonation results in more efficient
metabolic/detoxification processes (Schleicher et al., 2015), such as ammonia uptake
by ureagenesis and glutamine synthesis in periportal and pericentral hepatocytes,
respectively. Factors involved in the establishment and regulation of the zonation have
been studied over the years to better understand this phenomenon. In a recent review,
the authors suggested that the dynamic interplay among gradients of morphogens
(Wnt/β-catenin), hormones or growth factors (HGF), and oxygen can restrict gene
expression to differentiated hepatocytes located in specific zones of the liver, thus
contribute to metabolic zonation (Kietzmann, 2017).
One characteristic example of metabolic zonation is hepatic metabolism of
glutamate and glutamine, which is critical for ureagenesis, glutathione production, de novo protein synthesis, and gluconeogenesis by providing key substrates (Meijer et al.,
1990; Watford, 2000; Matthews, 2005). The heterogeneous metabolism of glutamate
and glutamine across the liver sinusoid is governed by a variety of enzymes and
membrane transporters differentially expressed in periportal and pericentral
hepatocytes (Watford, 2000; Watford et al., 2002). From a nutrient flux perspective, an
important aspect of glutamate and glutamine metabolism is its role in the “hepatic
intercellular glutamine cycle”, as described by Häussinger and coworkers (Häussinger
34 et al., 1985; Häussinger, 1990a). Generally, glutamine and ammonia from portal blood are absorbed and metabolized for urea synthesis in periportal hepatocyte, where glutamate and excess ammonia are taken up in pericentral hepatocytes and used as
substrates (catalyzed by glutamine synthetase) for glutamine synthesis. Therefore, the
cycle of glutamine degradation and re-synthesis is accomplished by the heterogeneous functional capacity along the hepatic acinus due to preferentially expression of enzymes and transporters in the periportal and pericentral zone (Boon et al., 1999; Braeuning et al., 2006).
In periportal hepatocytes (Figure 2.3), the glutamine is imported by SNAT3
(SLC38A3) and/or SNAT5 (SLC38A5) (Schioth et al., 2013) activity, and subsequently deaminated in mitochondria by glutaminase II (Curthoys and Watford, 1995), which expressed predominantly in population of periportal hepatocytes of rats (Häussinger,
1990b; Moorman et al., 1994). Concomitantly, alanine transaminase has been identified primarily expressed in periportal hepatocytes (Boon et al., 1999), which releases ammonia by converting alanine to pyruvate (Welsh, 1972). In addition, hepatic glutamate dehydrogenase activity is potentially another source of ammonia, because enzymatically it is able to catalyze the conversion between glutamate and alpha- ketoglutarate in both directions (amination and deamination). Studies of perfused rat liver with 15N-labeled ammonia (Brosnan et al., 1996) or 15N-labeled glutamine (Nissim et al., 1999) indicated that hepatic glutamate dehydrogenase acts in a bi-directional
manner. Sinusoidal microdissection of rat liver followed by enzymatic assays showed
that glutamate dehydrogenase activity increased from periportal to perivenous cells
35 (Maly and Sasse, 1991). This is further supported by quantitative in situ hybridization
studies, in which the expression of glutamate dehydrogenase mRNA shows a gradient
of increasing concentration from periportal to perivenous hepatocytes (Geerts et al.,
1996; Boon et al., 1999). It has been suggested that the net direction of glutamate dehydrogenase is deamination in periportal hepatocytes where many deamination processes take place to support ureagenesis, whereas in the glutamine synthetase-
containing pericentral hepatocytes glutamate dehydrogenase functions in amination
direction to produce glutamate. The pericentral glutamate dehydrogenase mRNA can
be upregulated after a high protein diet, indicating an increased glutamate synthesizing
capacity in pericentral hepatocytes to allow ammonia detoxification by glutamine
synthetase (Boon et al., 1999).
Thus, the pool of ammonia potentially contributed from portal blood, periportal
glutaminase, alanine transaminase, and glutamate dehydrogenase activity is
incorporated into the urea cycle via carbamoyl phosphate (Figure 2.3). This is the first,
committed step in the urea cycle, and is catalyzed by carbamoyl phosphate synthetase.
Carbamoyl phosphate synthetase has an absolute requirement for its allosteric activator
(Meijer et al., 1990), N-acetyl-glutamate, which is synthesized within mitochondria by
N-acetyl-glutamate synthetase (Morris, 2002). Both the activity and mRNA of
carbamoyl phosphate synthetase are expressed primarily in the periportal zone, as well
as the expression of arginase 1 (Häussinger et al., 1992), which catalyzes the final step
of the urea cycle and produces urea. Arginase has two distinct isoenzymes, as encoded
by two different genes (Jenkinson et al., 1996). Arginase 1 (liver type) is highly
36 expressed in liver as a critical part of the urea cycle. However, a perfused rat liver study suggested that arginase 2 (kidney type) is co-expressed with ornithine aminotransferase in pericentral hepatocytes to provide glutamate molecules for glutamine synthetase
(O'Sullivan et al., 1998). Because the carbamoyl phosphate synthetase and ornithine carbamoyltransferase are located within the mitochondrial matrix, whereas other urea
enzymes are cytosolic, the shuttle of ornithine and citrulline across mitochondrial
membrane is essential for the continuation of the urea cycle. This is achieved,
predominantly, by the anti-porter of ornithine and citrulline, mitochondrial ornithine
transporter 1 (SLC25A15, ORNT1) (Palmieri, 2013) (Figure 2.3). However, it is
unclear if ORNT1 represents the sole transporter of ornithine and citrulline across the
mitochondrial membrane (Morris, 2002). Nevertheless, the abundance of ORNT1
mRNA (Northern blotting) is increased in livers of mice fed a high-protein diet
(Camacho et al., 1999). Various studies have demonstrated that the activities of urea
cycle enzymes are elevated in response to starvation and high-protein diets and reduced
in response to low-protein or protein-free diets (Freedland, 1964; Christowitz et al.,
1981). Similar to the response of ORNT1 mRNA, upregulation of urea enzymes
(carbamoyl phosphatase synthetase, ornithine carbamoyltransferase, and arginase)
mRNA were also observed in the liver of rat after a high-protein diet (Morris et al.,
1987). Moreover, ORNT1 mRNA is significantly induced by cyclic AMP and dexamethasone in cultured rat hepatocytes, a response pattern very similar to that of urea cycle enzyme mRNAs (Nebes and Morris, 1988). These data seem to suggest that
changes in ORNT1 activity are coordinated with changes in activity of the urea cycle
37 enzymes. However, more study is needed to test if this is true under other conditions.
As proposed by Häussinger (1990b) and summarized earlier in this section, glutamine and ammonia are taken up and metabolized in the periportal zone to urea by a high capacity/low affinity system (Watford, 2000). However, in the pericentral zone, a low capacity/high affinity glutamine synthesizing system functions to efficiently scavenge the ammonia escaped the periportal zone. Glutamine synthetase activity is strictly expressed in periportal hepatocytes, where glutamate and “escaped” sinusoidal ammonia is incorporated into glutamine by glutamine synthetase. As mentioned above,
System N (SNAT3 and/or SNAT5) activity is responsible for exporting the glutamine out into blood flow to finish the glutamine cycle (Figure 2.3). The uncaptured ammonia from the periportal zone is taken up by ammonia transporter family, RhBG (SLC42A2)
(Figure 2.3), which is strictly expressed on the basolateral membrane of mouse
pericentral hepatocytes (Weiner et al., 2003; Braeuning et al., 2006). Another member
of ammonia transporter family, RhCG, is also expressed in mouse liver but at
substantially lower levels (about 0.4% of RhBG mRNA expression), and RhCG immunoreactivity is present in bile duct epithelial cells, where it may mediate ammonia secretion into bile (Weiner et al., 2003). Besides being used as a substrate for cytosolic glutamine synthetase, ammonia can also be used to make glutamate in mitochondria catalyzed by pericentral glutamate dehydrogenase, as described above (Figure 2.3).
With regard to the glutamate source, high affinity system X activity expressed on − 𝐴𝐴𝐴𝐴 basolateral membrane of pericentral hepatocyte (Cadoret et al., 2002; Matthews, 2005;
Braeuning et al., 2006) are responsible for importing sinusoidal glutamate to make
38 glutamine. In addition, ornithine aminotransferase is expressed in pericentral
hepatocytes in the adult mouse (Kuo et al., 1991) and rat (Colombatto et al., 1994; Boon et al., 1999). Its co-localization with glutamine synthetase suggests that ornithine
aminotransferase may contribute to glutamate production: with the rapid reduction of
glutamate-5-semialdehyde to glutamate by P5C dehydrogenase in mitochondria
(Ginguay et al., 2017). The supporting role of ornithine aminotransferase in glutamine
synthetase mediated ammonia uptake is evidenced by a number of observations of
increased ornithine aminotransferase activity in liver of rat after a high-protein diet
(Pitot and Peraino, 1963; Peraino, 1967; Boon et al., 1999), when an elevated level of
substrate for glutamine synthetase is needed to detoxify ammonia in pericentral
hepatocytes.
In summary, from a glutamate/glutamine and ammonia metabolism perspective,
glutamine and ammonia from portal blood are absorbed and metabolized for urea
synthesis in periportal hepatocyte, where glutamate and excess ammonia are taken up
in pericentral hepatocytes, and used as substrates (catalyzed by GS) for glutamine
synthesis. It should be noted that it remains unclear if ruminant liver displays this
heterogeneity. Nevertheless, it has been reported that sheep liver exhibits a
simultaneous release and removal of glutamine, as evidenced by the observation of net
liver removal of glutamine was 2.6 times lower than unidirectional removal (Bergman
and Heitmann, 1978). This was interpreted by Reynolds (1992) as potentially an
indication of liver heterogeneity in sheep.
39 2.2 Selenium Supplementation in Cattle
2.2.1 Selenium Overview
Selenium (Se) is an element first discovered in 1817 by chemist Jöns Jacob
Berzelius, who later named it after the Greek word for Moon, selènè (Boyd, 2011). In the periodic table, Se is located at the same column of sulfur and oxygen, and resembles both elements in some aspects. In biological systems, Se most likely exists as the form of selenol, R-SeH, or, as the Se ether analogous to sulfur in the amino acid methionine (Reddy and Massaro, 1983). After discovery, Se has long been recognized for its toxic effects to humans and livestock (Franke, 1934). Until 1957, its biological essentiality was recognized in the research work from Schwarz and Foltz (1957) who showed that dietary Se prevents liver necrosis in the rat. Later, unequivocal evidence of Se as an essential trace element, independent of its function as a substitute for vitamin E, were obtained (McCoy and Weswig, 1969; Thompson and Scott, 1969).
Although it was speculated that Se served as the active site of an antioxidant enzyme, the mechanisms for the biological functions of Se remained to be determined. In 1973, a physiological role of Se emerged from the knowledge of several milestone studies where it was discovered that Se is an integral structural component of the glutathione peroxidase (GPX) (Flohe et al., 1973), and GPX is a Se-dependent glutathione peroxidase, responded to dietary Se (Hafeman et al., 1974). After this, a considerable amount of progress has been made in discovering new selenoproteins and identifying their corresponding biological role in various physiological and pathological processes.
So far, the established selenoproteome includes 25 selenoprotein genes in human 40 (Labunskyy et al., 2014), and pig (Chen et al., 2018), and 24 in rodents (Kryukov et
al., 2003), and poultry (Li et al., 2018). Compared to mammals, fish generally possess
a greater number of selenoproteins, with zebrafish has a maximum of 38
selenoproteins found in zebrafish (Mariotti et al., 2012). Although the exact biological
functions of these selenoproteins remained to be determined, many of the
selenoproteins presumably have antioxidant activities due to the redox potential of Se
in the form of selenocysteine residue present in selenoproteins.
2.2.2 Nutritional Sources of Se
In nature and organisms, Se is present in various forms including selenite, selenate, selenocysteine (SeCys), and selenomethionine (SeMet) (Suzuki, 2005) (Figure 2.4).
Selenite and selenate are inorganic forms of Se commonly found in most soils and used as typical supplemental forms of Se to humans and livestock. The average Se level in the soil can vary from 0.1 to 4.5 ppm in different soil types, with volcanic soils and granite being generally poor in Se (Mehdi et al., 2013). The Se in soil can be incorporated by selenium-accumulating plants, and the Se content in plants is directly related to surrounding soil Se level. The normal range of Se concentration in forages is from 0.1 to 0.5 ppm, with extreme values from 0.006 to 20000 ppm, dependent upon plant and soil Se levels (Suttle, 2010; Mehdi et al., 2013). Forages and grains grown in
Southeastern USA have low (< 0.05 mg Se/kg) to variable (< 0.1 mg Se/kg) content of
Se contents due to Se-poor soil (Ammerman and Miller, 1975). Importantly, beef cattle
41 operations in the Southeastern USA have the highest percentage of Se-deficient animals compared with other surveyed regions of the USA (Dargatz and Ross, 1996). However, the dietary requirement of Se for beef cattle is suggested at 0.1 ppm (NRC, 1996). Thus, the diets of cattle in these and other regions with Se-deficient soils require Se supplementation. Sodium selenite, as an inorganic form of Se, is the most commonly supplemented form in cattle diets.
Organic forms of Se, mainly SeCys and SeMet, can come from the decomposition of plants that accumulate Se (Martens and Suarez, 1996; Finley, 2005). SeMet and
SeCys residues are the most common organic Se sources in foods (Suzuki and Ogra,
2002). Commercially, sources of organic Se in specially cultivated strains of yeast
(Saccharomyces cerevisiae) are available from several manufacturers (e.g., SEL-
PLEXTM, Alltech, KY, USA) and approved for use in beef cattle diets. SeMet is the
major single component from these Se-yeast products, and varying from 60-84% of
extracted Se (Rayman, 2004). Although as illustrated in Figure 2.4, both SeMet and
SeCys are present in amino acid residues of methionine and cysteine, respectively, with
the sulfur group being replaced with Se. However, there is a fundamental difference
between SeMet and SeCys in regarding to their biosynthesis, incorporation peptide chain, and whole body metabolism, as described later (2.2.3 Selenoprotein Synthesis).
Briefly, SeCys is incorporated into the peptide sequence of selenoproteins by the
specific codon (SeCystRNA) to SeCys residue (Suzuki, 2005), as analogous to other 20
amino acids. On the other hand, the SeMet is present in the form of SeMet residue in
general selenol-containing proteins, as tRNAmet does not discriminate between
42 methionine and SeMet (McConnell and Hoffman, 1972).
2.2.3 Selenoprotein Synthesis
Unlike unregulated incorporation of exogenous and/or endogenous SeMet into the peptide chain by methionine codon, SeCys residues incorporated into the selenoproteins are endogenously synthesized from mounting activated Se to eventually
SeCys SeCystRNA via the intermediates of selenophosphate and serine SeCystRNA (Veres
et al., 1992; Glass et al., 1993), as shown in Figure 2.5. There are five known molecular
components required for the following selenoprotein synthesis (Burk and Hill, 2015).
Two of them are uniquely present at selenoprotein mRNA structure, a UGA in the open
reading frame, and the other is a SeCys insertion sequence (SECIS) element (Berry et
al., 1993) (Figure 2.5). SECIS is a specialized stem-loop structure in the 3’ untranslated
region, and mandatory for the recognition of the in-frame UGA, otherwise a stop codon,
as the codon for SeCys insertion (Burk and Hill, 2015). As demonstrated in Figure 2.5,
three trans-acting factors: SeCys SeCystRNA, a SeCys-specific translation elongation
factor (eEFsec), and a SECIS-binding protein (SBP2) are also identified playing
essential roles in selenoprotein synthesis (Labunskyy et al., 2014). The SeCystRNA
contains the anticodon for UGA. The initial step is the charging of serine on the specific
SeCystRNA by seryl-tRNA synthetase, followed by Ser-SeCystRNA to SeCys-SeCystRNA
conversion, which is catalyzed by SeCys synthase, an enzyme that utilizes
monoselenophosphate as Se donor to generate SeCys (Xu et al., 2006). The trans-acting
43 factor, eEFsec is responsible for recruiting SeCys SeCystRNA and the other trans-acting factor SBP2, and inserting the SeCys into nascent protein chains in response to UGA codons (Fagegaltier et al., 2000).
2.2.4 Selenium Absorption
The exact mechanisms of the uptake and transport of Se have not been fully
characterized. In monogastric animals, the absorption of all forms of Se (selenite, SeCys,
and SeMet) is relatively high (70-95%) (Finley, 2006). There is evidence that SeMet
absorption occurs rapidly at all segments of the small intestine (Vendeland et al., 1992), and selenate and selenite were most efficiently absorbed from the most distal regions of the small intestine (Ardüser et al., 1985; Wolffram et al., 1985). Using rat intestinal brush border membrane vesicles (BBMV) as an experimental model, the isolated
BBMV uptake capacity of selenite, selenate, and SeMet are several orders of magnitude above physiological needs and normal intraluminal concentrations, and the uptake characteristics of BBMV for selenite, selenate, and SeMet are not altered by Se status
(Vendeland et al., 1994). In contrast to the absorption of zinc, the intestinal uptake of
selenite, selenate, and SeMet do not appear to be homeostatically regulated (Vendeland et al., 1992), and are not affected by Se status of rats (Brown et al., 1972) and chicks
(Humaloja and Mykkanen, 1986). In ruminants, Se75 disappearance studies using sheep
has shown that absorption of Se (sodium selenite) mainly occurs in the duodenum with
little evidence of uptake by the rumen, abomasum, jejunum, or ileum (Wright and Bell,
44 1966). In the same study, the absorption of orally dosed Se75 in the form of sodium
selenite was only 34% in sheep compared with 85% in swine (Wright and Bell, 1966).
The low Se absorption in ruminants was believed due to the reduction of dietary Se to insoluble forms such as elemental Se or selenides in the rumen microbial environment
(Spears, 2003).
The uptake of Se from selenite has generally been believed to occur by diffusion
(McConnell and Cho, 1965; Wolffram et al., 1985). However, several transporter systems have been proposed to be involved in Se uptake (Cousins and Liuzzi, 2018).
In lung cancer cells, it was reported that Se uptake depends on extracellular reduction, which is dependent on cysteine uptake through the X cysteine/glutamate antiporter − c (Olm et al., 2009). On the other hand, it has been speculated that amino acid transporter
1 (SLC3A1) and neutral amino acid transporter (SLC1A4) in enterocytes might be
involved in the transcellular movement of selenoamino acids, similar to that of amino
acids (Cousins and Liuzzi, 2018). As might be expected, these transporters do not
respond to selenium status, and homeostatic control of selenium metabolism is not at
the level of absorption.
2.2.5 Selenium Metabolism
After absorption, the metabolic fate is different among various dietary forms of Se,
although there are overlapping components (Suzuki, 2005) (Figure 2.6).
Selenomethionine is able to enter the methionine metabolic pool in the body by random
45 incorporation into proteins at methionine positions. This random insertion is proportional to the relative concentration of SeMet and methionine (Burk and Hill,
2015). The SeMet in proteins is known to serve as an unregulated reserve pool of Se
(Waschulewski and Sunde, 1988), and released during the turnover of methionine pool to enter Se metabolic pathways (Figure 2.6). However, little is known about the impact of SeMet in the metabolic pathways and the physiological processes involved methionine. Alternatively, SeMet can feed into the methionine cycle and transsulfuration pathway, and resulting SeCys (Esaki et al., 1981). SeCys from the dietary origin and transsulfuration pathway are then transformed to selenide by β-lyase activity, and enters the regulated Se metabolic pathway (Suzuki, 2005), as shown in
Figure 2.6.
The liver is the first organ that Se reaches after absorption across the intestinal membrane (Kato et al., 1992). Moreover, the transsulfuration pathway in liver is more active than in other tissues. As reviewed in Burk and Hill (2015), liver plays a critical role in whole-body Se regulation (Figure 2.7). Hepatic selenide is either used to supply selenoprotein synthesis, or metabolized to smaller excretory metabolite for excretion.
The allocation of selenide to these fates determines the amount of Se retained in the body and the amount excreted from it (Burk and Hill, 2015). The mechanism of the allocation of hepatic selenide to retention an excretion remained to be characterized.
Nevertheless, the retained Se in liver is transported to other tissues via secreting selenoprotein P (SELP) into the systemic circulation (Hill et al., 2012). Selenium is excreted predominately via urine and feces in the physiological range of Se intake (Burk
46 et al., 1972; Pedrosa et al., 2012). Trimethylselenonium ion and selenosugar are the excretory forms of Se identified in urine (Kobayashi et al., 2002), and only selenosugar was identified in feces (Suzuki et al., 2010). In ruminants, the urinary excretion of Se is generally low. Selenium is primarily excreted through feces result from low intestinal absorption (Mehdi et al., 2013).
2.2.6 Effects of Forms Supplemental Selenium on Cattle
The many biological functions of Se are carried out by selenoproteins, which are
important constituents of various enzymes, such as glutathione peroxidase, thioredoxin
reductase, and thyroid hormone deiodinase (Labunskyy et al., 2014). The biological roles of these redox enzymes in different tissues of human and rodent have been extensively reviewed (Rayman, 2012; Avery and Hoffmann, 2018), including antioxidant and thyroid hormone metabolism, spermatogenesis, brain development, and the immune system, etc. In cattle, the role of Se and the effects of Se supplementation has been recently reviewed (Mehdi and Dufrasne, 2016). The intent of this section is to review the effect of Se supplementation at various levels and forms on cattle from the perspective of blood/tissue assimilation and liver metabolic function.
2.2.6.1 On Blood and Tissue Selenium Assimilation
Se status has been commonly assessed by measuring the blood/tissue Se concentration, or blood glutathione peroxidase activity. Whole blood Se is comprised from serum (or plasma) Se (active pool) and Se in glutathione peroxidase in the red 47 blood cells (steady pool). Therefore, whole blood Se has been shown to be quickly responsive, and also well correlated with Se intake (Longnecker et al., 1996; Patterson et al., 2013). There is no clear agreement in the literature as to what whole blood Se concentrations in cattle are considered to be deficient or adequate. Regardless, studies have reported that it is considered adequate when whole blood Se is greater than 100
ng/mL (Gerloff, 1992), or between 81 to 160 ng/mL (Dargatz and Ross, 1996).
The Se concentrations in whole blood, plasma, and the glutathione peroxidase
activity in erythrocytes were not different between dairy cows supplemented (3 mg
Se/day) with sodium selenite and sodium selenate, indicating a similar assimilation rate
of these inorganic forms of Se (Ortman and Pehrson, 1999). However, a common
observation is that supplementation of dietary Se in organic forms vs. equal amounts of
Se in inorganic forms results in greater whole blood Se concentrations in weaning
calves (Hall et al., 2013), growing heifers (Brennan et al., 2011), lactating cows (Fisher
et al., 1995), and growing bulls (Mehdi et al., 2015). After 8 weeks of Se
supplementation (0.2 ppm) to Se-deficient dairy cows, organic Se (Se yeast) resulted in
an increase of whole blood Se concentration from 5.6 to 167 ng/mL vs 91 ng/mL for
cows supplemented with inorganic Se (selenite) (Malbe et al., 1995). The supplement
of Se (0.75 mg/day) from the Se-enriched yeast maintained the Se concentrations of
whole blood and milk of dairy cows at the same level as sodium selenite supplemented
at 3 mg Se/day (Ortman and Pehrson, 1997). The difference in effect between these two
forms of Se is estimated at 20% for the whole blood Se content and 16% in the GPx
activity (Weiss and Hogan, 2005; Mehdi and Dufrasne, 2016). Similarly, a 20 to 30%
48 increase in whole blood Se levels was associated with organic Se supplementation compared to inorganic Se (Eliott et al., 2005).
Using a model with maturing heifers fed an industry-relevant basal diet, our lab has demonstrated that Se supplementation (3 mg Se/day) in vitamin-mineral mixes as organic form (OSe, Se-enriched yeast, SEL-PLEX) for 75 days resulted in greater Se content in whole blood, red blood cells, and biopsied liver tissue than inorganic Se form
(ISe, sodium selenite) (Liao et al., 2011). However, the time-dependent assimilation and stabilization of Se concentrations in tissues have not been well described, especially in beef cattle. A long-term (224 days) Se dietary supplementation trial (ISe, OSe, and an equal blend of ISe:OSe (MIX)) was later conducted, using the same animal model
(Liao et al., 2011) to characterize the time-dependent assimilation of Se in blood and liver tissue of maturing beef heifers (Brennan et al., 2011). It was suggested that Se content either increased until day 56, then was stable (liver and plasma), or was stable until day 56 (whole blood) or day 112 (red blood cells) and then increased steadily through day 224, for all supplemental Se treatments (Brennan et al., 2011). In addition, more Se was found in the whole blood , red blood cells, serum, and liver of MIX and
OSe heifers than ISe heifers (Brennan et al., 2011). These data indicate that a 1:1 mix
(1.5 mg Se:1.5 mg Se) of supplemental ISe and OSe is equal to 3 mg/day OSe supplementation and greater than 3 mg/day ISe supplementation.
2.2.6.2 On Hepatic Gene Expression Profiles
Although the liver plays an essential role in metabolizing Se/selenoproteins and
49 regulates whole body Se metabolism in rodents (Burk and Hill, 2015), little has been characterized regarding the effect of dietary Se supplementations on hepatic gene expression. A mouse hepatic gene expression profiling (microarray gene chips) study indicated that different forms of supplemental Se resulted in different gene expression patterns (Barger et al., 2012). More specifically, a similar expression pattern of individual genes and gene functional categories was observed between mouse supplemented (1 mg Se/kg diet) with sodium selenite and yeast-derived Se (SEL-PLEX,
Alltech, KY), which were distinct form SeMet (Barger et al., 2012). However, this interesting hepatic gene expression similarity between sodium selenite and yeast- derived Se was not understood by the authors. In maturing heifers models previously developed in our lab, compared to no exogenous Se supplementation, supplementing dietary ISe or OSe at a same level (3 mg/day) resulted in different hepatic gene expression profiles, although with a common change in a core set of genes commonly affected by both forms of supplemental Se (Liao et al., 2011). Bioinformatic analysis
(IPA) of Se-affected genes indicated that they are associated with a broad range of physiological functions including nutrient metabolism, cellular growth, proliferation, and immune response, cell communication or signaling, and tissue/organ development and function (Liao et al., 2011).
To further investigate the effect of forms of supplemental Se (Control (no supplementation), ISe, OSe, and MIX) on hepatic gene expression, a microarray
(custom WT Btau 4.0 Array, Affymetrix) analysis was conducted (Matthews et al., 2014) using the biopsied liver on day 168 of Se supplementation, after when Se assimilation
50 had been stable on day 56 of Se supplementation (Brennan et al., 2011). The expression
of 139 gene transcripts was affected by Se treatment, and, specifically, OSe treatment
responses were more closely aligned with Control than were MIX, and the ISe profile
was similar to MIX and most dissimilar to Control. Interestingly, these Se treatment-
induced hepatic gene expression profiles did not match differences in hepatic Se content
(OSe = MIX > ISE > Control; (Brennan et al., 2011)). Therefore, the global gene
expression profiles seem not to be reflective of absolute hepatic Se assimilation (Se
concentration). These findings suggested that the different hepatic gene expression
profile of ISe, MIX, OSe, and Control heifers, was not caused by an inter-form gradient
(0%, 50%, 100% ISe or OSe) effect, but by their biochemical form and form-specific
metabolic pathways. Moreover, hepatic transcriptome profiles of MIX heifers suggested an increased potential for selenoprotein synthesis and selenoprotein- mediated metabolism. In addition, several genes involved with increased redox capacity were upregulated in MIX versus ISe heifers (Matthews et al., 2014). Based on these understandings, future studies should characterize the relationship among total Se assimilation, the form of Se assimilated and patterns of gene expression. More research is also needed to further understand the physiological consequences of altered hepatic gene expression profiles induced by different forms of supplemental Se.
2.3 Summary
As reviewed above, research has demonstrated that grazing endophyte-infected tall fescue resulted in the classic reductions of serum prolactin, alkaline phosphatase,
51 and albumin concentration in cattle. In addition, hepatic transcriptome profile
(microarray, targeted RT-PCR and immunoblot analysis) was affected by grazing high
vs. low endophyte-infected tall fescue. The increase in relative mRNA abundance
putatively indicated a shift in functional capacities for proline and serine synthesis,
shunting of amino acid carbons into pyruvate and ATP synthesis, and mitochondria
mass. Consistent with the microarray results, Nanostring data (Table 2.3) indicated that
hepatic nitrogen recycling and redox capacity was impaired by the consumption of
endophyte-infected tall fescue. In addition, the expression of several selenoprotein
genes was decreased in liver of steers grazing high endophyte-infected tall fescue
(Table 2.3).
On the other hand, supplementation of Se (3 mg/day) in forms of OSe or MIX
resulted in greater whole blood, serum, red blood cell Se concentrations than ISe did in
maturing heifers. Hepatic transcriptome profile was also affected by forms of supplemental Se, and MIX stimulated the expression of genes involved in selenoprotein and glutamine/glutamate metabolism (Table 2.3). Serendipitously, some of the genes
upregulated by MIX were found downregulated in the liver and pituitary of steers
grazing high vs. low endophyte-infected forages. Therefore, future studies are
necessary to investigate whether form of supplemental Se (ISe, OSe, and MIX) in
vitamin-mineral mixes consumed by growing beef steers grazing endophyte-infected tall fescue pasture would ameliorate some of the negative physiological parameters associated with fescue toxicosis.
52
Figure 2. 1 Ergoline ring system.
8
9 7
12 10 D 6 11 13
5 CH3
53 A C 14 4
15 3 B
1 2
Ergoline ring
Figure 2. 2 Structures of three classes of ergot alkaloids. Examples of clavine alkaloids (a and b), lysergic acid and its simple amides (c and d),
ergopeptine alkaloids (e, f, and g).
54
a. Chanoclavin b. Emyloclavine c. Lysergic Acid d. Lysergic Acid Amide
e. Ergonovine f. Ergovaline g. Ergotamine
Figure 2. 3 Overview of main glutamine/glutamate and ammonia metabolic pathways in periportal and perivenous hepatocytes1.
55
1Assignment of a process and its related enzyme and transporter expressions is based on data from rodents model andprevious reviews. More detailed decription of these metabolic pathways, as well as exprimental results supporting this zonation patterns are presented in the text. Abbreviations: SNAT3: glutamine transporter, SLC38A3; SNAT5: glutamine transporter, SLC38A5; EAAC1: high affinity Na+-dependent, glutamate/aspartate transporters, SLC1A1; GLT1: high affinity Na+-dependent, glutamate/aspartate transporters, SLC1A2; RHBG: ammonia transporter, SLC42A2; GLS2: glutaminase 2, liver mitochondria; ALT: alanine transaminase; AST: aspartate transaminase; GDH: glutamate dehydrogenase; CPS1: carbamoyl phosphate synthetase; NAGS: N-acetylglutamate synthase; OCT: ornithine carbamoyltransferase; ASS: argininosuccinate synthase; ASL: argininosuccinase; ARG1: arginase 1; ORNT1: ornithine/arginine exchanger, SLC25A15; ARG2: arginase 2; OAT: ornithine aminotransferase; GS: glutamine synthetase.
56
Figure 2. 4 Structures of inorganic selenium compounds, the related oxyanions, and organic selenium compounds1.
57
1Selenocysteine, SeCys; Se-methylselenocysteine, MeSeCys; Selenomethionine, SeMet. Adapted from Suzuki et al., 2005.
Figure 2. 5 Schematic illustration of translation mechanism for the synthesis of selenoproteins1.
58
1Two cis-sequences, a SECIS element in the 3’-untranlated region and a SeCys codon (UGA) in the coding region, and three trans-acting factors, a SeCys-specific translation elongation factor (EFSeCys), the SeCys SeCystRNA, and a SECIS-binding protein (SBP2) are proposed for the translation of the UGA codon to the SeCys sequence. Adapted from Suzuki et al., 2005.
Figure 2. 6 Schematic illustration of the initial metabolism of the principal dietary forms of selenium1.
59
1Abbreviations: Met, methionine; SeMet, selenomethionine; SeCys, selenocysteine;
Figure 2. 7 Scheme of regulated selenium metabolism in hepatocytes1.
60
1The broken line indicates that selenosugar, an excretory metabolite, also has modest bioavailability. Abbreviations: Gpx1, glutathione peroxidase- 1; Sec, selenocysteine; Sepp1, selenoprotein P. Adapted from Burk and Hill, et al., 2015.
Table 2. 1 Summary of cattle serum ALP activity reference range in literature.
Serum ALP Range Animal Name of book, paper, and organization Citation (U/L) Cattle 90-170 Paper (Knowles et al., 2000) Veterinary Medicine: A textbook of the diseases of Cattle 0-500 (Radostits et al., 2007) cattle, horses, sheep, pigs and goats (Kaneko et al., 2008) Cattle 0-488 Clinical Biochemistry of Domestic Animals (6th Ed.)
61 Cattle 27-260 UK Veterinary Diagnostic Lab http://vetmed.ucdavis.edu/vmth/local_r Cow 24-74 UC Davis VMTH Clinical Diagnostic Lab esources/pdfs/lab_pdfs/UC_Davis_VM TH_Chem_Reference_Intervals.pdf
Table 2. 2 Serum alkaline phosphatase (ALP) concentrations in animals consuming endophyte-infected tall fescue.
Serum ALP Animal concentration Endophyte-infected tall fescue model (U/L) Comments Reference BW/Ag Breed E- E+ Delivery Routes Dose Exposure Length e ADG: 1.04 vs. 0.22 80.3a 59.6b 30 days Angus 271±5.1 0 vs. 0.28 ppm kg/d (Rice et al., Grazing tall fescue steer kg ergovaline ADG: 0.75 vs. 0.77 1997) 79.6a 53.8b 65 days kg/d Angus 62 275-300 Apr to Aug of (Oliver et
-cross 84.4 76.6 Grazing tall fescue 0% vs. >80% infected kg 1996 to 1998 al., 2000) steer Angus 0.02 vs. 0.52 ppm 85 days (Jun to ADG: 0.58a vs. 0.4b (Brown et -cross 266 kg 159.8a 109.1b Grazing tall fescue ergovaline + Sep) kg/d al., 2009) steer ergovalinine ADG: 0.4 vs. -0.05 93.0 71.6 Day 0-36 Angus 0.02 vs. 0.52 ppm kg/d (Jackson et -cross 266 kg Grazing tall fescue ergovaline + ADG: 0.26 vs. 0.27 81.2 66.5 Day 37-58 al., 2015) steer ergovalinine kg/d 159.8a 109.1b Day 59-85 ADG: 1.3 vs. 1.4 kg/d
Table 2. 2 (continued) <0.05 vs. 1.63 ppm 234 ± May to Oct of ADG: 0.6a vs. 0.34b (Nihsen et Steers 135a 64b Grazing tall fescue ergovaline + 3.2 kg 1999 and 2000 kg/d al., 2004) ergovalinine Angus 275-300 Apr to Sep of Intestinal and bone (Schultze et -cross 87.9a 75.9b Grazing tall fescue 0% vs. >80% infected kg 1997 to 1998 isoforms decreased al., 1999) steer 12 d at heat Angus 95.3 78.0 (Boling et 312 kg Grazing tall fescue <1% vs. >90% infected neutral heifer al., 1989) 89.7a 59.0b 7 d at heat stress E+ seed and alfalfa 0.52 ppm ergovaline in 7 d at 33 °C and Feed intake 1.35a vs. (Gadberry et Lambs NA 111.5a 78.9b meal based diet E+ diet 50% humidity 0.97b kg al., 2003)
63 Matur E+ seed and e 0.5 ppm ergovaline + 0.3 (Schultz et NA 207.4 210.4 timothy hay based 21 days geldin lysergic acid in E+ diet al., 2006) diet g BALB 2 ± 0.34 E+ seed and basal 1.5 ppm ergovaline in E+ Mean weight gain: (Rice et al., /c male 115a 105b 13 days g diet diet 1.04 vs. -0.08 g 1998) mice
Table 2. 3 List of genes differently altered by supplementing forms of Se and grazing endophyte-infected tall fescue.
Form of selenium supplementation1 Grazing endophyte-infected tall fescue (E+)4 Gene Category Metabolic Day 36 Day 85 Day 85 Metabolic ISe OSe MIX consequence Liver Liver Pituitary consequence Decreased Se Up SEPHS1 Down Down selenocysteine metabolism 34%2 synthesis (Liver) Glutamate Up ARL6iP1 Down Same Same metabolism 27%2 64
Glutamine Up Reduced glutamine GLUL Down Down metabolism 44%2 synthesis (Liver)
Oxidative Up Up Up Increased oxidative Sel W Down Down metabolism 41%2 36%2 60%2 stress (Liver) Increased Oxidative Up Up Up Sel W antioxidant metabolism 22%3 26%3 22%3 capacity Increased Decreased thyroid- Oxidative Up thyroid- DIO2 Down mediated metabolism metabolism 43%2 mediated (Pituitary) metabolism
Table 2. 3 (continued) Decreased thyroid- Oxidative DIO1 Same Down mediated metabolism metabolism (Liver)
Decreased Se SEPSECS Down Down selenocysteine metabolism synthesis (Liver)
1Data are expressed relative (%) to Control heifer mRNA transcript abundance. 2Data from Nanostring analysis (J.C. Matthews, unpublished data). 3Data from (Matthews et al., 2014). 4Data from (Matthews and Bridges, 2014). 65
CHAPTER 3. Dissertation Objectives
Besides fescue toxicosis, another challenge to endophyte-infected tall fescue-
based beef cattle operations is that the forage is typically selenium (Se)-inadequate
(below 0.1 ppm), due to Se-poor soils (Ammerman and Miller, 1975). Beef cattle
require 0.10 mg Se/kg of diet to meet the daily requirements (NRC, 1996). To remedy
this, Se is supplemented using free-choice vitamin-mineral mixes. Inorganic form (ISe,
sodium selenite) of selenium (Se) is commonly supplemented. However, the use of organic forms of Se (OSe) in vitamin-mineral mix results in greater blood and tissue Se concentrations (bioavailability) (Nicholson et al., 1991; Gunter et al., 2003; Liao et al.,
2011). Interestingly, feeding a 1:1 blend of ISe:OSe (MIX) results in equal amounts of
Se in whole blood, red blood cells, serum, and liver of heifers as when supplemented with only OSe, both of which are greater than ISe supplemented heifers (Brennan et al.,
2011). Hepatic transcriptome profiles have indicated that, compared to ISe or OSe, MIX uniquely stimulates expression of genes involved in selenoprotein synthesis and glutamate/glutamine metabolism (Matthews et al., 2014). Serendipitously, some of the genes upregulated by MIX were found downregulated in the liver (Liao et al., 2015) and pituitary (Li et al., 2017) of steers grazing high vs. low endophyte-infected forages.
Therefore, the overall goal this dissertation was to investigate whether the form of supplemental Se (ISe, OSe, and MIX) in vitamin-mineral mixes consumed by growing beef steers grazing endophyte-infected tall fescue pasture would ameliorate some of the negative physiological parameters associated with fescue toxicosis. More specifically,
1) To test the general hypotheses that the form (ISe, OSe, and MIX) of
66
supplemental Se in vitamin-mineral mixes consumed by growing beef steers grazing endophyte-infected tall fescue forage would ameliorate negative physiological parameters associated with fescue toxicosis, including depressed serum prolactin and hepatic glutamine synthetase. (Experiment 1, Chapter 4)
2) Using the serum sample of the steers from Experiment 1 (Chapter 4), to test the hypotheses that the form (ISe, OSe, and MIX) of supplemental Se in vitamin-mineral mixes consumed by growing beef steers grazing endophyte-infected tall fescue forage would ameliorate the negative serological parameters associated with fescue toxicosis, including depressed serum alkaline phosphatase activity and albumin. The second goal was to evaluate the potential relationships between whole blood Se concentration and serum clinical parameters. (Experiment 2, Chapter 5)
3) To conduct a transcriptome analysis of the same hepatic tissue sample from experiment 1 (Chapter 4) to gain greater perspectives of potentially altered hepatic metabolic pathways and identify potential regulatory connections with other serological and physiological changes, the second goal was to conduct targeted RT-PCR and western-blotting analyses to investigate the expression of key enzymes and transporters involved in hepatic glutamine/glutamate metabolism, ammonia assimilation, and proline metabolism (Experiment 3, Chapter 6).
67
CHAPTER 4. Forms of selenium in vitamin-mineral mixes differentially affect serum prolactin concentration and hepatic glutamine synthetase activity of steers grazing endophyte-infected tall fescue
Note: a subset of the material in this chapter has been publised: Yang Jia, Qing
Li, Walter R Burris, Glenn E Aiken, Phillip J Bridges, James C Matthews;
Forms of selenium in vitamin-mineral mixes differentially affect serum prolactin concentration and hepatic glutamine synthetase activity of steers grazing endophyte-infected tall fescue, Journal of Animal Science, Volume 96, Issue 2, 6
March 2018, Pages 715–727, doi:10.1093/jas/skx068.
4.1 Abstract
The goal of this study was to test the hypothesis that sodium selenite (ISe), SEL-
PLEX (OSe), vs a 1:1 blend (MIX) of ISe and OSe in a basal vitamin-mineral mix
would differentially affect metabolic parameters and performance of growing steers
grazing toxic endophyte-infected tall fescue mixed forage pasture. Predominately-
Angus steers (BW = 183 ± 34 kg) were randomly selected from herds of fall-calving
cows grazing endophyte-infected tall fescue pasture and consuming vitamin-mineral
mixes that contained 35 ppm Se as ISe, OSe, and MIX forms. Steers were weaned,
depleted of Se for 98 d, and subjected to summer-long common grazing of an
endophyte-infected tall fescue pasture (0.51 ppm total ergovaline/ergovalinine; 10.1
ha). Steers were assigned (n = 8/treatment) to the same Se-form treatments upon
which they were raised. Selenium treatments were administered by daily top-dressing
68
85 g of vitamin-mineral mix onto 0.23 kg soyhulls, using in-pasture Calan gates. The
PROC MIXED procedure of SAS was used to assess effect of Se form treatments on
whole blood Se (ng/mL) and serum prolactin (ng/mL) at d 0, 22, 43, 64, and 86, and
caudal arterial area (mm2) at d -7, 43, and 86. The effect of Se treatment on ADG (d
86), and liver glutamine synthetase (GS) mRNA, protein, and activity (nmol∙mg-1 wet
tissue∙min-1) were assessed using the PROC GLM procedure of SAS. Fisher’s
protected LSD procedure was used to separate treatment means. Whole blood Se
increased (P < 0.01) for all treatments from d 0 to 22 and then did not change (P ≥
0.17), and was greater (P ≤ 0.04) for MIX and OSe steers. Serum prolactin decreased
(P < 0.01) over time and was greater (P < 0.05) for MIX and OSe steers. Liver GS
mRNA content was 66% and 59% greater (P < 0.05) in MIX and OSe steers, respectively, than ISe steers. Liver GS protein content in MIX steers was 94% more
(P < 0.01) than ISe steers. Moreover, MIX and OSe steers had 99% and 55% more (P
≤ 0.01) liver GS activity, respectively, than ISe steers. ADG was not affected (P =
0.36) by Se treatments. We conclude that consumption of 3 mg Se/d as OSe or MIX forms of Se in vitamin-mineral mixes increased (a) whole blood Se content, an indicator of greater whole-body Se assimilation; (b) serum prolactin, the reduction of which is a hallmark of fescue toxicosis; and (c) hepatic GS activity, indicating greater hepatic assimilation of acinar ammonia. However, (d) these positive effects on metabolic parameters were not accompanied by growth performance.
KEYWORDS: steer, fescue toxicosis, selenium supplementation, prolactin, glutamine synthetase
69
4.2 Introduction
It is well-established that cattle consuming tall fescue (Lolium arundinaceum)
infected with a symbiont endophyte (Epichloë coenophiala) develop a syndrome of
negatively-affected altered physiological systems, collectively known as fescue
toxicosis (Strickland et al., 2011). In addition to the classical decrease in prolactin,
recent studies have identified that the hepatic metabolism of specific amino acid is
altered in fescue toxicosis cattle (Brown et al., 2009; Liao et al., 2015), including a
putative decrease in glutamine synthetase (GS) expression (Matthews and Bridges,
2014).
Another challenge to endophyte-infected tall fescue-based beef cattle operations
is that the soil is often Se-poor, necessitating the need to provide supplemental Se
(Dargatz and Ross, 1996). Inorganic Se (ISe, sodium selenite) is the most common Se
supplemented in cattle diets, whereas organic forms of Se (OSe), derived from
specially cultivated Saccharomyces cerevisiae, also are available and approved for
use in beef cattle diets. Supplementation (3 mg/d) with an 1:1 blend of ISe:OSe
(MIX) or OSe vs. ISe results in greater amounts of Se in blood and liver of cattle
(Brennan et al., 2011). Moreover, MIX stimulates expression of genes involved in hepatic selenoprotein synthesis and glutamate/glutamine metabolism relative to ISe or
OSe (Matthews et al., 2014). Serendipitously, some of the genes up-regulated by MIX were found down-regulated in the liver (Liao et al., 2015) and pituitary (Li et al.,
2017) of steers grazing high vs. low endophyte-infected forages.
70
The goal of this study was to test the general hypotheses that the form (ISe, OSe,
MIX) of supplemental Se in vitamin-mineral mixes consumed by growing beef steers grazing endophyte-infected tall fescue forage would ameliorate negative physiological parameters associated with fescue toxicosis, including depressed serum prolactin and hepatic GS.
4.3 Materials and Methods
All experimental procedures were approved by the University of Kentucky
Institutional Animal Care and Use Committee.
4.3.1 Animals
Twenty-four suckling, predominantly Angus, beef steers (BW: 182.6 ± 33.9 kg, age: 165.5 ± 14.2 day) were randomly selected (n = 8) from herds of fall-calving cows grazing toxic endophyte-infected tall fescue mixed forage pastures and consuming vitamin-mineral mixes that contained 35 ppm Se as either inorganic Se (ISe, sodium selenite, Prince Se Concentrate; Prince Agri Products, Inc., Quincy, IL, USA), organic
Se (OSe, SEL-PLEX, Alltech Inc., Nicholasville, KY), or an 1:1 blend of ISe:OSe
(MIX) forms.
Steers were removed from their dams; housed in feedlot pens of 4; fed (ad libitum access) a hay, soyhull, and DDGS-based “adaptation” diet; and had ad libitum access
71
to a basal free-choice vitamin-mineral mix that lacked Se; for 40 d. Then, over a 39-d
period (in consecutive groups of six, 2 steers from each treatment group, 2 wk/group),
steers were moved to an in-pasture Calan gate facility and trained to eat the adaptation
diet from individual in-pasture Calan gates. During this 39-d period, steers continued
to have ad libitum access to the Se-free basal vitamin-mineral mix. Next, over a 19-d
period, steers were transitioned from the adaptation diet to a common mixed-forage
pasture that lacked endophyte-infected tall fescue and trained to consume the Se-free
basal vitamin-mineral mix from individual Calan gates by top-dressing 85 g of the
basal vitamin-mineral mix onto 227 g soyhulls. In summary, over a 98-d period
(March 11 to June 17, 2015) steers were weaned, commonly depleted of Se, and
trained to consume vitamin-mineral mix from in-pasture Calan gates. During this pre-
trial Se-depletion period, the ADG of steers was 0.82 ± 0.18 kg/d.
Steers then began (d 0) an 86-d (June 17 to September 9, 2015) period in which
they commonly grazed a predominately endophyte-infected tall fescue-mixed pasture
(10.1 ha) and individually consumed their respective Se form-specific vitamin-
mineral mix treatments, through the use of in-pasture Calan gates. During this 86-d period, 2 ISe steers were removed from the trial due to a bad hoof and failure to consume their mineral treatment, respectively. Thus, the final number of experimental observations were: ISe = 6, and OSe and MIX = 8.
The composition (analyzed by Dairy One Cooperative, Inc., Ithaca, NY) of the
basal vitamin-mineral mix was 11.62% Ca; 4.88% P; 1.05% S; 1.95% Mg; 0.88% K;
9.95% Na; 1,321 ppm Fe; 3,388 ppm Zn; 1,761 ppm Cu; 5,262 ppm Mn; 0.98 ppm
72
Mo; 19.07 ppm Co; 550,000 IU/kg vitamin A; and 550 IU/kg vitamin E. The Se-
specific mixes contained the basal mix plus 35 ppm Se as either ISe, OSe, or MIX. As
noted above, to ensure individual consumption of 3 mg Se·d-1·steer-1, 85 g of the
specific vitamin-mineral mix (35 ppm Se) was top-dressed onto 227 g of soyhulls in
each individual Calan gate feeder. The consumption of the mixture of
soyhulls/vitamin-mineral mix was monitored daily, and all steers consumed all of the
mixture every day. Thus, every steer consumed 3 mg of supplemental Se/d.
On d 0 and 86, shrunk BW were determined (steers were denied access to water
and forage for 12 h) to calculate ADG. Steers were then returned to pasture, randomly
assigned to 1 of 8 slaughter d (from d 93 to 119), and maintained on their Se
treatments until slaughter.
4.3.2 Pasture Sampling and Analysis
Pasture samples were collected on d 0, 22, 43, 64, 86, and 115 for determination of ergot alkaloid (ergovaline and ergovalinine) concentrations as previously described
(Brown et al., 2009). Samples were stored on ice during transportation to the laboratory, and then frozen and stored at -20°C. Analysis of ergot alkaloids was
performed by a high-performance liquid chromatography fluorescence procedure
(Carter et al., 2010). Proximate analysis and mineral content were determined
(http://dairyone.com/wp-content/uploads/2014/02/Forage-Lab-Analytical-Procedures-
73
Listing-Alphabetical-July-2015.pdf) by Dairy One Cooperative, Inc.
4.3.3 Blood Collection
Jugular vein blood samples were collected by venipuncture on d 0, 22, 43, 64, and 86. For the preparation of whole blood, 8 mL of blood was collected in sodium heparin-containing blood collection tubes (Becton Dickinson, Franklin Lakes, NJ).
For serum, 16 mL of blood was collected in serum blood collection tubes (Becton
Dickinson, Franklin Lakes, NJ) without an anticoagulant. Serum was recovered by centrifugation at 3,000 × g for 10 min at 4°C and stored at -80°C. Whole blood Se concentrations were analyzed by Michigan State University Diagnostic Center for
Population and Animal Health (DCPAH) using an Agilent 7900 Inductively Coupled
Plasma-Mass Spectrometer as described previously (Wahlen et al., 2005). Serum prolactin concentrations were quantified by the laboratory of Dennis Hallford (New
Mexico State University), using a double antibody RIA as described previously
(Spoon and Hallford, 1989). The inter-assay CV was 9.5% and the intra-assay CV was
6.6%.
4.3.4 Slaughter, Tissue Collection, and Carcass Evaluation
Steers were slaughtered over a 26-d period, from d 93 to 119 (September 17 to 74
October 13, 2015) of the study. Specifically, 1 OSe and 1 MIX steer were killed on
the first 2 slaughter d. On the remaining 6 slaughter d, 1 steer each from ISe, OSe, and
MIX treatment groups were killed. On any given slaughter day, steers were
transported from the University of Kentucky Research and Education Center at
Princeton, KY to the University of Kentucky Meat Laboratory at Lexington, KY, and
allowed to rest 1 to 2 h before slaughter and had ad libitum access to water. Body
weight was determined and steers were stunned by captive-bolt gun followed by
exsanguination. Liver samples were collected from the mid-lower right lobe and used fresh for determination of GS activity. For real-time RT-PCR analysis, liver samples were placed in foil packs, snap-frozen in liquid nitrogen, and stored at -80°C.
Longissimus dorsi (LM) tissue was collected from between the 12th and 13th rib from
the left side of the carcass, and used fresh for determination of GS activity. After 24 h
postmortem, carcass evaluations (ribeye area and fat depth at 12th rib) were conducted
on the right side of the carcass according to USDA standards (USDA, 2017).
4.3.5 Analysis of GS Activity in Hepatic and LM Tissue Homogenates
After collection, fresh liver and LM muscle tissue were put on ice and
immediately transferred to the laboratory. About 0.4 g of tissue was homogenized
(30,000 rpm for two 15-second cycles) in 5 volumes of ice-cold extraction buffer (pH
7.9), containing 50 mM Tris and 2 mM EDTA, using a PowerGen 124 homogenizer
75
(Thermo Fisher Scientific, Waltham, MA). The homogenate was centrifuged at 2,000
× g and 4°C for 10 min. The derived supernatant was assayed for GS (EC 6.3.1.2)
activity using a radiochemical method modified from James et al. (1998). A 50 µL
aliquot of the supernatant was mixed with 200 µL of reaction medium which
consisted of 0.25 µCi L-[1-14C]glutamate (ARC, Saint Louis, MO; specific activity:
50-60 mCi/mmol), 25 mM unlabeled glutamate, 25 mM MgCl2, 25 mM NH4Cl, 18.75
mM ATP, 12.5 mM phosphocreatine, 4 units creatine kinase, and 62.5 mM imidazole-
HCl buffer, at pH 7.6. The mixture was incubated at 37°C for 20 min, and the reaction
was then terminated by adding 1mL of ice-cold 20 mM imidazole-HCl buffer, at pH
7.5. A sample of the incubate (1 mL) was loaded into a 4 mL prefilled (formate resin)
ion-exchange column (Bio-Rad, Hercules, CA) previously rinsed by distilled water.
The column was washed with 4 mL of distilled water, and the effluent was collected.
A sample of effluent (1 mL) was mixed with 4 mL of a ScintiSafe Plus 50% cocktail
(Thermo Fisher Scientific, Waltham, MA), and the radioactivity was measured in a
liquid scintillation analyzer TRI-CARB 2900TR (PerkinElmer, Downers Grove, IL).
Assays were conducted in triplicate. Positive control contained 2.5 units of GS from
Escherichia coli (Sigma, Saint Louis, MO) instead of supernatant from liver or LM muscle tissue. Negative control contained neither supernatant nor GS. Glutamine
synthetase activity is expressed as nmol/min/mg wet mass. The intra- and inter-assay
CV were 8.5% and 8.8%, respectively.
76
4.3.6 Caudal Artery Area Measurement
Ultrasound measures of caudal artery area were performed on d -7, 43, 86 of the experiment as previously described (Aiken et al., 2007). Briefly, caudal artery at the
fourth coccygeal vertebra was scanned by an Aloka 3500 Ultrasound Unit (Aloka Inc.,
Wallingford, CT) with a UST-5542 (13 MHz) linear array transducer set to a 2-cm depth. Three cross-sectional color Doppler flow scans were taken to determine the mean artery lumen area (mm2).
4.3.7 RNA Extraction and Analysis
For each animal, total RNA was extracted from 300 mg of frozen liver tissue using TRIzol Reagent (Invitrogen Corporation, Carlsbad, CA) following the manufacturer’s instructions. The purity and concentration of total RNA samples was analyzed using a NanoDrop ND-100 Spectrophotometer (NanaDrop Technologies,
Wilmington, DE, USA). All samples had an average concentration of 1.05 μg/μL and a high purity with 260/280 absorbance ratios of 1.98-2.03 and 260/230 absorbance ratios ranging from 1.89 to 2.18. The integrity of total RNA was examined by gel electrophoresis using an Agilent 2100 Bioanalyzer System (Agilent Technologies,
Santa Clara, CA) at the University of Kentucky Microarray Core Facility.
Visualization of gel images and electropherograms showed that all RNA samples were
77
of high quality with RNA integrity numbers (RIN) being greater than 8.7 and 28s/18s
rRNA absorbance ratios greater than 2.
4.3.8 Real-time RT-PCR Analysis
The quantification of relative mRNA for genes of interest was performed using
standard procedures in our laboratory, as previously described (Cerny et al., 2016).
Briefly, 1 µg of each steer’s liver RNA was reversely transcribed to cDNA using the
SuperScript III 1st Strand Synthesis System (Invitrogen). Real-time RT-PCR were performed using an Eppendorf Mastercycler ep realplex2 system (Eppendorf,
Hamburg, Germany) with iQ SYBR Green Supermix (Bio-RAD, Hercules, CA). A
total volume of 25 µL was used in each real-time RT-PCR reaction containing 5 µL of
cDNA, 1 µL of a 10 µM stock of each primer (forward and reverse), 12.5 µL of 2 ×
SYBR Green PCR Master Mix, and 5.5 µL of nuclease-free water. The relative
amount of each transcript was calculated using the 2-ΔΔCT method (Livak and
Schmittgen, 2001). Primer sets (Table 4.1) for genes of interest were designed and obtained from NCBI Primer-BLAST tool (https://www.ncbi.nlm.nih.gov/tools/primer- blast/) against RefSeq sequence (accessed February to April 2016).
All real-time RT-PCR cDNA products were validated by DNA sequencing verification. Briefly, the PCR-amplified cDNA products were electrophoresed in a
1.2% agarose (UltraPureTM Agarose, Invitrogen, Carlsbad, CA) slab gel. A single
78
cDNA band at the desired size was identified under a UV light, excised from the gel, purified using the PureLink Quick Gel Extraction Kit (Invitrogen, Carlsbad, CA), then sequenced by Eurofins Genomics (Eurofins MWG Operon LLC, Louisville, KY). The resulting sequences (Figure 4.1) were compared to the NCBI RefSeq mRNA sequences used as templates for primer pair set design. Three constitutively expressed genes (GAPDH, PLOD1, and PCK2) were used and their CT values were not affected
(P > 0.43) by the Se form treatment. Thus, the relative mRNA expression was normalized to the geometric means of three constitutively expressed genes. For the
RT-PCR analysis, n = 6, 8, and 8 samples were used for ISe, OSe, and MIX treatments, respectively. RT-PCR reactions were performed in triplicate.
4.3.9 Immunoblot Analysis
All immunoblot and densitometric analyses for the relative expression of targeted proteins were performed using a standard protocol of our lab as previously described
(Miles et al., 2015). Approximately 0.2 g of liver was homogenized on ice for 30 s
(setting 11, Polytron Model PT10/35, Kinematic Inc., Lucerne, Switzerland) in 7.5 mL of 4°C sample extraction buffer solution [0.25 mM sucrose, 10 mM HEPES-KOH pH 7.5, 1 mM EDTA, and 50 µL of protease inhibitor (Sigma, St. Louis, MO)].
Protein was quantified by a modified Lowry assay, using bovine serum albumin as a standard (Kilberg, 1989). Proteins were separated using 12% SDS-PAGE and
79
electrotransferred onto a 0.45 μm nitrocellulose membrane (BioRad, Hercules, CA) and then stained with Fast-Green (Fisher, Pittsburgh, PA). The relative amount of
stained protein/lane/sample was determined by densitometric analysis and recorded as arbitrary units (Brown et al., 2009).
The relative content of GS in liver homogenate was evaluated using an antibody as previously described (Miles et al., 2015). Briefly, blots were hybridized with 1.25
µg of IgG anti-sheep polyclonal antibody (BD Biosciences, San Jose, CA) per milliliter of blocking solution [5% nonfat dry milk (wt/vol), 10 mM Tris-Cl (pH 7.5),
100 mM NaCl, 0.1% Tween 20 (vol/vol)] for 1 h at 37 °C with gentle rocking.
Protein-primary antibody binding reactions were visualized with a
chemiluminescence kit (Pierce, Rockford, IL) after hybridization of primary antibody
with horseradish peroxidase-conjugated goat anti-mouse IgG (BD Biosciences, San
Jose, CA; GS, 1:5000).
Densitometric analysis of immunoreactive products was performed as described
previously (Miles et al., 2015). After exposure of auto-radiographic film (Amersham,
Arlington Heights, IL), digital images of all observed immunoreactive species were
recorded and quantified as described (Dehnes et al., 1998) using the BioRad Versadoc
imaging system and the Quantity One Program (Version 4.2.3, BioRad). A single
immunoreaction product (GS, 42.5 kDa) was assessed for treatment effect by
densitometric analysis. The linearity of antibody-ligand immunoreactions and densitometry were validated using immunoblots containing protein gradients (data not shown). Data were collected as arbitrary densitometric units and then were corrected
80
for unequal loading and/or transfer of proteins by normalization to densitometric
values of Fast-Green-stained proteins common to all immunoblot lanes/samples. The
range of Fast-Green normalization for GS was 6.9% to 8.2%. For all results,
densitometric values were normalized to ISe steers by obtaining an average ISe steer
densitometric value and dividing all results by this value.
4.3.10 Statistical Analysis
Data are presented as least square means (± SEM). Steers were the experimental
units. The effect of Se supplementation on whole blood Se, serum prolactin, and
caudal artery area were evaluated by ANOVA, using the PROC MIXED procedure of
SAS (v 9.4, SAS Inst. Inc., Cary, NC). The statistical model included Se
supplementation, time, and their interaction as fixed effects. Class variables were Se
supplementation and steer, with steer included in the random statement. The
Kenward-Roger adjustment was used to calculate the denominator of df (Kenward
and Roger, 1997). Within Se supplement treatment, non-orthogonal polynomial contrasts (linear, quadratic, cubic, quartic) were used to characterize the effect of Se treatments over time on whole blood Se and serum prolactin concentration, using the
PROC IML procedure of SAS to generate coefficients for unequally spaced contrasts.
After slaughter, the effect of Se supplementation on growth and carcass parameters, hepatic GS activity, and the relative abundance of hepatic GS mRNA and protein was
81
assessed by ANOVA, using the PROC GLM procedure of SAS. Fisher’s protected
LSD procedure was used to separate treatment means of the time-course data.
4.4 Results
4.4.1 Nutrient and Ergot Alkaloid Profiles of Forages
The composited means of proximate, mineral, and alkaloid analysis of pasture
samples are presented in Table 4.2. The pasture samples from throughout the grazing
periods had a CP of 16.3%, Se of 0.07 μg/g DM, and total ergot alkaloids of 0.51
μg/g.
4.4.2 Whole Blood Se Concentration
The concentration of Se in whole blood was affected by Se supplementation treatment (P = 0.01), time (P < 0.01), and their interaction (P < 0.01) (Figure 4.2A).
Specifically, OSe steers and MIX steers had 11% (P < 0.01) and 7.5% (P = 0.04) more whole blood Se than ISe steers, respectively, and did not differ from each other
(P = 0.30). Across Se supplementation treatments, the whole blood Se concentration increased (P < 0.01) 49% from d 0 to 22 and then did not change (P ≥ 0.17) throughout d 86 (Figure 4.2A). Within Se treatments, non-orthogonal polynomial
82
contrast analysis showed that the concentrations of whole blood Se essentially
increased in a quadratic manner (P < 0.01) over time for all 3 Se treatments.
4.4.3 Serum Prolactin Concentration
The concentration of prolactin in serum was affected (P < 0.05) by Se treatment
(Figure 4.2B). Across periods, OSe and MIX steers had 59% (P < 0.03) and 52% (P <
0.05) more serum prolactin than ISe steers, respectively. A time effect was found (P <
0.01) in serum prolactin concentration, but there was no (P = 0.12) Se treatment by time interaction. Across Se treatments, serum prolactin concentration decreased (P <
0.01) from d 0 to 22, and plateaued (P > 0.25) from d 22 to 64, then decreased (P <
0.01) again from d 64 to 84. Within Se treatments, non-orthogonal polynomial contrasts analysis revealed that serum prolactin essentially decreased in a linear (P <
0.01) manner for OSe and ISe steers. In contrast, serum prolactin essentially decreased in a cubic manner (P < 0.01) for MIX steers, apparently reflecting a decrease from d 0 to 22, and then from d 64 to 86.
4.4.4 GS Activity and Expression
At slaughter, Se treatment affected (P < 0.01) hepatic GS activity of steers
(Figure 4.3), where MIX steers had 99% (P < 0.01) and 29% (P = 0.03) more activity 83
than ISe and OSe steers, respectively, and OSe steers had 55% more (P = 0.01) than
ISe steers. In contrast, Se treatment did not affect (P = 0.21) GS activity in LM tissue
(Figure 4.3).
The relative expression of hepatic GS mRNA differed (P = 0.02) among Se treatment steers (Table 4.3). MIX steers had 66% more (P < 0.01) hepatic GS mRNA expression than did ISe steers, and there was 59% more (P < 0.05) hepatic GS mRNA in OSe than ISe steers. However, hepatic GS mRNA content did not differ (P = 0.75) between
OSe and MIX steers. Similarly, the relative hepatic GS protein content was affected
(P = 0.02) by Se treatments (Table 4.3 and Figure 4.4). Specifically, MIX steers had
94% more (P < 0.01) hepatic GS protein than ISe steers. However, the hepatic GS protein content of OSe steers did not differ (P > 0.05) with that of both ISe and MIX steers.
4.4.5 Caudal Artery Area
Selenium form did not affect (P = 0.65) caudal artery area, nor (P = 0.89) was there a Se form × time interaction (Figure 4.5). However, there was a time effect (P
= 0.03). Specifically, across Se treatments, the caudal artery area at d 43 (6.19 ± 1.3
mm2) was 41% greater (P = 0.03) than d -7 (4.4 ± 0.69 mm2), and 40% greater (P =
0.02) than d 86 (4.41 ± 0.77 mm2), whereas the caudal area did not differ (P = 0.98) between d -7 and 86.
84
4.4.6 Animal Performance
Final BW were 293.6, 293.5, and 272.0 kg, respectively, for ISe, OSe, and MIX
steers, and did not differ (P = 0.34). Average daily gain (Table 4.4) was 0.43, 0.53,
and 0.47 kg/day for ISe, OSe, and MIX steers, respectively, and was not affected by
Se treatment (P = 0.36). Selenium treatments did not (P ≥ 0.37) affect (ISe, OSe, and
MIX, respectively) ribeye area (56.24, 50.89, 51.61 cm2), 12th-rib fat thickness (0.26,
0.29, 0.25 cm), or marbling score (300, 270, 271). (Table 4.4)
4.5 Discussion
4.5.1 Animal Model
The goal of this study was to test the general hypothesis that the form of Se (ISe,
OSe, MIX) in vitamin-mineral mixes would affect the expression of important physiological parameters in growing beef steers commonly grazing an endophyte- infected tall fescue pasture. Steers had ad libitum access to their respective supplemental Se treatments as suckling calves before selection into the trial. During a pre-trial Se-depletion period (98 d), steers received the basal vitamin-mineral mix that lacked any form of Se. From initiation of the trial to slaughter, steers individually consumed 85 g/d of a basal vitamin-mineral mix that contained 35 ppm Se supplied as
85
ISe, OSe, or MIX forms. Thus, steers consumed 3 mg Se/d of their respective Se from initiation of the grazing period until their slaughter (up to 113 d) by use of Calan gates. The 3 mg Se/animal daily supplementation is the legal maximal limit for free- choice vitamin-mineral mixes allowed by the Food and Drug Administration, and is considered adequate to achieve the NRC (NRC, 1996) recommendation of 0.1 mg/kg of diet. We chose to use a Se-adequate model to avoid confounding effects of Se deficiency and to legitimately compare the effect of Se form on experimental parameters.
Steers commonly grazed a single 10.1-ha predominately tall fescue-mixed pasture, which contained 0.51 ppm total ergot alkaloids (Table 4.2). In a previous study by our group (Brown et al., 2009), a similar level of ergot alkaloid challenge
(0.52 ppm) induced fescue toxicosis in beef steers grazing endophyte-infected tall fescue and consuming ad-libitum amounts of a similar vitamin-mineral mix that contained the ISe form of Se. Importantly, these steers had similar concentrations of serum prolactin and levels of ADG, as did the ISe steers of the current study. The rapid increase then stabilization of Se assimilation in the whole blood of all 3 Se treatment groups is consistent with our previous Se depletion/repletion regimens with growing cattle (Brennan et al., 2011; Liao et al., 2011). Thus, the animal model of the current study was successfully established to properly evaluate the potential effect of different Se-form treatments on physiological parameters of growing beef steers subjected to summer-long grazing of toxic endophyte-infected tall fescue pasture.
86
4.5.2 OSe and MIX Forms of Se Supplementation Resulted in Greater Whole
Blood Se than ISe
Selenium status is commonly determined by measuring the concentration of Se in
blood or tissues, or the activity of glutathione peroxidase in blood. Whole blood Se
concentrations are well correlated with Se intake (Patterson et al., 2013). Although
there is no clear agreement in the literature as to what concentrations of whole blood
Se are considered to be deficient or adequate, studies have reported that cattle have
adequate levels of Se when whole blood Se is greater than 100 ng/mL (Gerloff, 1992),
or between 81 to 160 ng/mL (Dargatz and Ross, 1996). In the current study, across-
periods, mean whole blood Se concentration ranged from 154 to 231 ± 5.4, 181 to 252
± 4.7, and 153 to 257 ± 4.7 ng/mL in ISe, OSe, and MIX steers, respectively,
indicating that all steers were Se adequate. Importantly, MIX and OSe steers had
greater whole blood Se concentrations than did ISe steers. This finding is in
agreement with previous studies, where greater whole blood Se was found in grazing
cows supplemented with organic Se at 3.3 mg·day-1·animal-1 (Pehrson et al., 1999) or had ad libitum access to Se-containing mineral mixes (Gunter et al., 2013; Patterson et al., 2013). Of note, supplementation (3 mg/day) of slow maturing beef heifers with the MIX form of Se for 224 days resulted in similar Se concentrations in whole blood, red blood cells, serum, and liver compared to that supplemented with OSe (Brennan et al., 2011). Consistently, in the current study with growing grazing steers, the whole
blood Se concentration of MIX steers also was essentially the same as for OSe steers.
87
This finding suggests that the MIX form of Se (1:1 equal blend of ISe and OSe) was assimilated as efficiently as was the 100% organic form of Se (OSe).
4.5.3 Concentrations of Serum Prolactin Were Greater in MIX and OSe Steers
Reduced serum prolactin concentrations are a hallmark of fescue toxicosis
(Goetsch et al., 1987; Davenport et al., 1993). One mechanism by which ergot alkaloids exert their inhibitory effect on serum prolactin is to bind dopamine receptor
D2 (Larson et al., 1994), resulting in suppression of prolactin synthesis and release by lactotrophs within the anterior pituitary (Schillo et al., 1988; Li et al., 2017). In the current study, OSe and MIX steers had greater serum prolactin concentrations than
ISe steers throughout the grazing period. A priori, this novel finding suggests that supplemental organic Se interacts in some manner with the prolactin synthetic cascade, or enzymes involved in the degradation of circulating prolactin.
With regard to the first possibility, it may be reasonable to speculate that potential links exist between Se and prolactin given the critical roles of Se and selenoproteins in neurotransmission and brain function (Solovyev, 2015). More specifically, consumption (1 to 9 μg/g DM) of inorganic (selenite), but not organic Se resulted in increased dopamine concentrations in murine striatum (Tsunoda et al., 2000). As noted above, one of the key roles of dopamine is to negatively regulate prolactin secretion by binding and stimulating the dopamine receptor D2-mediated inhibition of
88
prolactin synthesis (Fitzgerald and Dinan, 2008). The greater serum prolactin
concentrations of MIX and OSe vs. ISe steers in the present study appears consistent
with the understanding that selenite supplementation increases dopamine content,
accompanied by decreased prolactin synthesis in mouse brain models. Thus, it may be
reasonable to speculate that the serum prolactin difference in current study may be
due to the different dopamine concentrations induced by different form of Se.
However, more research is needed about the expression and function of key
enzyme/signaling proteins involved in lactotroph dopamine-prolactin interactions
(such as dopamine receptor D2 (Beaulieu and Gainetdinov, 2011), prolactin receptor
(Bernard et al., 2015), and Jak-Stat cascades (Rawlings et al., 2004) to support this speculation.
As discussed earlier, consumption of endophyte-infected tall fescue suppresses serum prolactin. Unsurprisingly, in the current study, the serum prolactin concentration decreased (86%) from d 0 to its nadir on d 86, regardless of the Se form treatments of the steers. More specifically, from d 0 to 22, the serum prolactin concentration of all steers quickly dropped 43%, accounting for approximately half of the total reduction. The rapid decrease of serum prolactin concentrations after consumption of forages containing endophyte-infected tall fescue has been reported in steers (Aldrich et al., 1993; Jackson et al., 2015). The serum prolactin depression from d 0 to 84 observed in this study was approximately 86% (from 73.4 to 10.1 ng/mL).
This magnitude of the reduction is in agreement with reported reductions of serum prolactin concentrations of 80% (Aldrich et al., 1993), 81% (Schillo et al., 1988), and
89
90% (Brown et al., 2009) in cattle consuming endophyte-infected vs. endophyte-free tall fescue.
The current summer-long grazing study was conducted during June to September of 2015. Because reduction of photoperiod decreases concentrations of circulating prolactin in many species, including cattle (Dahl et al., 2000), it should be noted that the decrease in daylight also may have contributed to the depression of serum prolactin in steers from all 3 Se treatments.
4.5.4 Hepatic GS Activity, mRNA, and Protein Expression Are Greater in MIX than ISe Steers
Part of the general hypotheses of this trial was that the form of supplemental Se would affect GS expression. This hypothesis was derived from a preliminary understanding (Matthews and Bridges, 2014) that the MIX form of Se increases the content of GS mRNA in steer liver whereas the consumption of endophyte-infected tall fescue mixed forage decreases hepatic GS mRNA content. Thus, an important finding from the current study was that hepatic GS activity was strongly affected
(MIX > OSe > ISe) by the form of Se in the vitamin-mineral mix (Figure 4.3). In contrast, LM GS activity was not affected by Se form treatment. Hepatic GS expression is restricted to pericentral hepatocytes (Häussinger, 1990b). As such, GS is involved in scavenging ammonia that escapes periportal hepatocyte detoxification
(urea cycle) by synthesizing glutamine from sinusoidal ammonia and glutamate 90
(Wagenaar et al., 1994). Given the marked increase in hepatic GS activity by MIX and
OSe steers, it is reasonable to expect that they possessed an increased N recycling
capacity.
Although the regulatory mechanisms of GS have not been clearly defined, several studies indicate that GS activity is at least partially under transcriptional regulation
(Gaunitz et al., 2001). More specifically, regulatory elements have been reported in the first intron (Fahrner et al., 1993) and in 5’ upstream regions (Gaunitz et al., 2001) of the GS gene. These regions contain binding sites for various transcription factors,
and have a functional role in the organ-specific expression patterns of GS, and in the restricted pericentral expression of GS within the liver (Lie-Venema et al., 1995).
Moreover, it has been reported that post-transcriptional regulations such as alternative splicing also may contribute to the tissue specific expression of GS (Shin et al., 2003).
Although GS isolated from brain and other tissues of the same species have identical
sequences, tissue-specific differences in substrate feedback regulation exist (Tate et
al., 1972). Therefore, post-translational modifications may exist (Eisenberg et al.,
2000).
To gain insight into potential transcription, translational, or both, processes
accounting for Se form differences in hepatic GS activity, the relative mRNA and
protein abundance of GS was determined (Table 4.3). In agreement with the 99%
greater hepatic GS activity, MIX steers had a 66% and 94% more hepatic GS mRNA
and protein, respectively, than ISe steers. Although statistically not different from ISe
steers, the 50% quantitatively greater GS protein content of OSe vs. ISe steers is
91
consistent with the 59% greater mRNA content and 55% greater GS activity.
Collectively, these data suggest that the MIX and OSe forms of Se affected at least the
transcriptional regulation of hepatic GS.
Little is known aout the potential for Se or selenoproteins to interact with GLUL
(gene for GS) or GS. However, it has been reported that long-term supranutritional supplementation of sodium selenite to diabetic mice (vs. no supplementation) results in increased GS mRNA and protein (Wang et al., 2014). Although the specific mechanism(s) is unclear, our current finding in steer liver, coupled with this limited report in mouse liver, suggests that hepatic GS expression and activity may be sensitive to the form of Se and, possibly, the amount of supplemental Se.
4.5.5 Caudal Artery Area, Animal Performance, and Carcass Characteristics
Were Not Affected by Se Treatment
Caudal Artery Area
Consumption of ergot alkaloids by cattle is known to constrict the caudal artery
(Aiken et al., 2007), right ruminal artery and vein (Foote et al., 2011), and mesenteric artery and vein (Jia et al., 2015). Ergot alkaloid-induced vasoconstriction is thought to
be a contributor to several symptoms of fescue toxicosis (Klotz and Nicol, 2016).
Therefore, the caudal artery luminal area was determined in the current study as a
parameter to assess potential Se-form treatment differences. However, the caudal
artery area was not affected by Se treatment. The range of the caudal artery areas was 92
4.40 to 6.19 mm2, which was higher (thus, less restricted) than the 2.0 to 3.8 mm2
(Aiken et al., 2007) and 1.2 to 5.0 mm2 (Aiken et al., 2009) reported for heifers (345-
375 kg) consuming endophyte-infected tall fescue seed plus chopped alfalfa hay/concentrate diets. The difference in caudal artery areas in the present study employing grazing steers and the earlier studies using confined heifers may be due to
the difference of ergot alkaloid load. That is, in the current study, the pasture
contained 0.51 ppm ergovaline and ergovalinine, whereas endophyte-infected seed
containing 1.17 (Aiken et al., 2009) to 1.21 ppm (Aiken et al., 2007) of ergovaline
and ergovalinine were consumed by confined heifers. Another possible explanation
for the relatively higher caudal artery area in current study may be an inherent
difference between heifers and steers in artery size and luminal diameter. For
example, intravascular ultrasound analysis has revealed that left main and proximal
left anterior descending coronary arterial areas were smaller in women than in men
(Sheifer et al., 2000).
Growth Performance and Carcass Characteristics
As noted above, the amount of ADG achieved by the ISe steers (0.43 kg/d) is
almost identical to that achieved (0.40) by beef steers consuming endophyte-infected
tall fescue pastures (0.52 ppm ergovaline/ergovalinine) and that had ad libitum access
to ISe-containing (35 ppm) vitamin-mineral mix over a 85-d summer-long grazing period (Brown et al., 2009). In mammals, prolactin affects various physiologic parameters besides lactation, including osmoregulation, immunoregulation, and
93
growth and development (Bole-Feysot et al., 1998). Moreover, prolactin has a somatogenic effect on postnatal body growth and BW of male rats (Perez-Villamil et al., 1992). However, the ADG by ISe steers did not differ from that by MIX or OSe steers over the 86-d grazing period. The form of Se (ISe, OSe, MIX) also does not affect the ADG of slow-growing beef heifers supplemented with 3 mg Se/day
(Brennan et al., 2011). Similarly, no significant improvement on animal growth performances (ADG, ADI, or gain: feed ratio) has been reported by studies comparing the effects of OSe and ISe supplementation (Lawler et al., 2004; Brennan et al., 2011).
Previously, we observed a reduction in liver weight (g/100 kg BW), final BW,
HCW, dressing percentage, and ribeye area of predominately Angus steers that had
been subjected to summer-long grazing of high- vs. low-endophyte infected forages
(Brown et al., 2009). Accordingly, we evaluated these parameters for Se-form effects.
However, none of these, or other, carcass parameters were affected by Se form
treatments (Table 4.4). In a different model (slow-maturing beef heifers fed concentrate diet and ISe, OSe, or MIX forms of supplemental Se, (Brennan et al.,
2011)), we also did not find Se-form effects on carcass parameters. Similarly, supplemented with supranutritional levels of organic Se (33 mg Se/day) to finishing steers resulted in no Se form effects on carcass characteristics (Lawler et al., 2004).
4.6 Summary
In summary, predominately-Angus steers subjected to summer-long grazing of
endophyte-infected pasture and supplemented (3 mg/d) with MIX or OSe forms of Se
94
had greater whole blood Se, serum prolactin concentrations, and greater hepatic GS activity than ISe-supplemented steers. Despite these effects, no difference in growth performance was found.
95
Table 4. 1 Primer information used for real-time RT-PCR analyses.
Oligonucleotide Primer Design (5’ to Amplicon Product Gene Gene Name Accession number 3’ direction) length (bp) identity (%)
F: GAAGAGTTGCCCGAGTGGAA GLUL Glutamine synthetase NM_001040474.2 370 100% R: CCTCCACAATATCCCTGCCG
Glyceraldehyde 3- F: ACATCAAGTGGGGTGATGCT
96 GAPDH NM_001034034.2 201 97% phosphate dehydrogenase R: GGCATTGCTGACAATCTTGA
F:TCCACTACCCCCAAAAACGG PLOD1 Lysyl hydroxlase 1 NM_174148.1 218 99% R:GGCATCCACGCTGAAGTAGT
Phosphoenolpyruvate F:GCAAGCTGTGGATGAGAGGT PCK2 carboxykinase 2, NM_001205594.1 203 99% R:TGACAAAGTCGCCATCTCCC mitochondrial
Table 4. 2 Proximate, mineral, and alkaloid analysis of composited pasture samples
(DM basis)1
Item Value Proximate analysis, % DM 28.05 TDN 59.42 CP 16.26 Adjusted CP 15.84 ADF 37.58 aNDF 60.08 Crude fat 2.62 Lignin 6.46 Starch 0.89 Mineral analysis Ash, % 10.32 Calcium, % 0.6 Phosphorus, % 0.25 Magnesium, % 0.23 Potassium, % 2.08 Sodium, % 0.01 Sulfur, % 0.28 Iron, ppm 438.67 Zinc, ppm 28.5 Copper, ppm 6.17 Manganese, ppm 63.5 Molybdenum, ppm 1.68 Selenium, ppm 0.07 Ergot alkaloids analysis, µg/g Ergovaline 0.34 Ergovalinine 0.17 Total ergot alkaloids 0.51
1Values are the average of samples collected and analyzed on d 0, 22, 43, 64, 86, and 115, presented on a DM basis. Samples were obtained systematically from approximately 30 sites from a common pasture, using a knife to cut the forage at approximately 2 cm above soil level.
97
Table 4. 3 Comparison of glutamine synthetase mRNA and protein content in liver
homogenates of growing beef steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as either sodium selenite
(ISe), SEL-PLEX (OSe), or a 1:1 blend of ISe and OSe (MIX)1.
Treatment2 Glutamine synthetase ISe OSe MIX SEM3 P-value mRNA4 1.03a 1.64b 1.71b 0.15 0.02 Protein5 2,098a 3,041ab 3,632b 331 0.02
1Values are least squares means (n = 6 for ISe, n = 8 for OSe and MIX) and pooled SEM. 2Means within a row that lack a common letter differ (P < 0.05). 3Most conservative error of the mean. 4Values are relative level of mRNA expression. 5Values (arbitrary densitometric units) were determined by densitometric evaluation of Western blot data (Figure 4.4).
98
Table 4. 4 Animal performance and carcass characteristics of growing beef steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin- mineral mixes as either sodium selenite (ISe), SEL-PLEX (OSe), or a 1:1 blend of ISe and OSe (MIX)1.
Treatment Item ISe OSe MIX SEM P-value Initial BW, kg 256.4 247.6 231.7 12.81 0.41 Final BW, kg 293.6 293.5 272.0 11.86 0.34 Liver weight, kg 3.76 3.65 4.00 0.16 0.28 Liver weight as percentage BW, % 0.55 0.58 0.59 0.01 0.17 ADG2, kg/day 0.43 0.53 0.47 0.05 0.36 HCW, kg 164.8 158.2 146.6 8.73 0.37 Dressing percentage, % 53.0 50.7 52.5 1.62 0.59 Ribeye area, cm3 56.24 50.89 51.61 3.38 0.51 12th-Rib fat thickness, cm 0.26 0.29 0.25 0.05 0.87 KPH2, % 2.0 2.0 2.0 0 1.0 USDA Yield Grade 1.75 1.98 1.81 0.15 0.53 Marbling Score4 300 270 271 17.61 0.44
1Data are least squares means (± SEM) of ISe (n = 6), OSe (n = 8), and MIX (n = 8) steers grazing endophyte-infected tall fescue for 93 to 119 d. 2Calaculated as the difference between shrunk BW at d 86 – at d 0. 3Percentage of kidney, pelvic, heart fat in total fat. 4Marbling score: 200=traces00; 300=slight00.
99
Figure 4. 1 The sequences of the real-time RT-PCR products (5’ to 3’ orientation).
Within a sequence, underlined nucleotides indicate the forward and reserve primer positions.
GLUL: GAAGAGTTGCCCGAGTGGAATTTTGATGGCTCTAGTACTTTTCAGTCTGAAGGCTCCA ACAGTGACATGTATCTTGTCCCCGCTGCCATGTTTCGGGACCCTTTCCGCAAGGACCCC AACAAGCTGGTGTTCTGTGAAGTCTTCAAGTACAACCGAAAGCCTGCAGAGACCAAT TTAAGGCACACCTGTAAACGGATAATGGACATGGTGAGCAACCAGCGCCCCTGGTTTG GAATGGAGCAGGAATATACCCTCATGGGCACTGATGGGCACCCCTTTGGTTGGCCTTCC AATGGCTTTCCTGGGCCCCAAGGTCCCTACTACTGTGGTGTGGGAGCGGACAAGGCCT ACGGCAGGGATATTGTGGAGG GAPDH: ACATCAAGTGGGGTGATGCTGGTGCTGAGTATGTGGTGGAGTCCACTGGGGTCTTCAC TACCATGGAGAAGGCTGGGGCTCACTTGAAGGGTGGCGCCAAGAGGGTCATCATCTCT GCACCTTCTGCCGATGCCCCCATGTTTGTGATGGGCGTGAACCCACGAGAAGTATAAC AACACCCTCAAGATTGTCAGCAATGCC PLOD1: TCCACTACCCCCAAAAACGGTTGAGGCTTTTCATTCACAACCACGAGCAGCACCACAA GGCTCAGGTGGAGCAGTTCCTGGCAGAGCACGGCGATGAGTACCAGTCTGTGAAACT GGTGGGCCCCGAGGTGCGGGTGGCCAACGCAGACGCCAGGAACATGGGCGCGGACT GGCCGGCAGGACCGTGGCTGCACTTACTACTTCAGCGTGGATGCC PCK2: GCAAGCTGTGGATGAGAGGTTTCCAGGCTGCATGCTGKGCCSAACATGTACGTGATTC CGTTCAGCATGGGTCCCGTGGGCTCCCCGCTGTCCCGCATCGGAGTGCAGCTCACGGA CTCTGCCTACGTGGTGGCAAGCATGCGGATTATGACTCGGTTGGGGACACCTGTGCTT CAGGCCCTGGGAGATGGCGACTTTGTCA
100
Figure 4. 2 Whole blood selenium (Se) (A.) and serum prolactin (B.) concentrations in growing beef steers grazing endophyte-infected tall fescue and supplemented with
3 mg Se/d in vitamin-mineral mixes as either sodium selenite (ISe), SEL-PLEX
(OSe), or a 1:1 blend of ISe and OSe (MIX)1.
1Data are least squares means (n = 6 for ISe, n = 8 for OSe and MIX) ± SE. A. Selenium form (P = 0.01), time (P < 0.01), and Se form by time interaction (P < 0.01) effects. Non-orthogonal polynomial contrasts: ISe, linear (P < 0.01), quadratic (P < 0.01), cubic (P < 0.01), and quartic (P = 0.03) effects; OSe, linear (P < 0.01), quadratic (P < 0.01), and cubic (P = 0.03) effects; MIX steers, linear (P < 0.01), quadratic (P < 0.01), and quartic (P = 0.04) effects. B. Selenium form (P < 0.05), and time (P < 0.01) effects. Non-orthogonal polynomial contrasts: ISe, linear (P < 0.01) effect; OSe, linear (P < 0.01) effects; MIX, linear (P < 0.01) and cubic (P < 0.01) effects.
101
Figure 4. 3 Glutamine synthetase (GS) activity in liver and Longissimus dorsi
(Muscle) homogenates of growing beef steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as either sodium selenite
(ISe), SEL-PLEX (OSe), or a 1:1 blend of ISe and OSe (MIX)1.
1Data are least squares means (n = 6 for ISe, n = 8 for OSe and MIX) ± SE. Selenium form effect on liver GS activity (P < 0.01). Means with different letters differ (P < 0.05).
102
Figure 4. 4 Western blot analysis of glutamine synthetase protein (42.5 kDa) content in liver homogenates (20 ug/lane) of growing beef steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as either sodium selenite (ISe), SEL-PLEX (OSe), or a 1:1 blend of ISe and OSe (MIX).
103
Figure 4. 5 Caudal artery area in growing beef steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as either sodium selenite (ISe), SEL-PLEX (OSe), or a 1:1 blend of ISe and OSe (MIX)1.
1Data are least squares means (n = 6 for ISe, n = 8 for OSe and MIX) ± SE. Time (P =
0.03) effect.
104
CHAPTER 5. Forms of selenium in vitamin-mineral mixes
differentially affect serum alkaline phosphatase activity, and serum
albumin and blood urea nitrogen concentrations, of steers grazing
endophyte-infected tall fescue
Note: a subset of the material in this chapter has been submmitted to Journal of
Animal Science with manuscript ID JAS-2019-3310. A revision has been
summitted on March 11, 2019.
5.1 Abstract
The goal of this study was to test the hypothesis that sodium selenite (ISe), SEL-
PLEX (OSe), vs a 1:1 blend (MIX) of ISe and OSe in a basal vitamin-mineral mix
would differentially affect serological parameters of growing steers grazing toxic
endophyte-infected tall fescue mixed forage pasture. Predominately-Angus steers
(BW = 183 ± 34 kg) were randomly selected from herds of fall-calving cows grazing
endophyte-infected tall fescue mixed pasture and consuming vitamin-mineral mixes
that contained 35 ppm Se as ISe, OSe, and MIX forms. Steers were weaned, depleted
of Se for 98 d, and subjected to summer-long common grazing of an endophyte-
infected tall fescue mixed pasture (0.51 ppm total ergovaline/ergovalinine; 10.1 ha).
Steers were assigned (n = 8/treatment) to the same Se-form treatments upon which
they were raised. Se treatments were administered by daily top-dressing 85 g of
vitamin-mineral mix onto 0.23 kg soyhulls, using in-pasture Calan gates. The PROC
105
MIXED procedure of SAS was used to assess effect of Se form treatments on serum parameters at d 0, 22, 43, 64, and 86. After slaughter, the effect of Se treatment on hepatic alkaline phosphatase (tissue non-specific isoform, TNALP) mRNA, protein and albumin protein content were assessed using the PROC GLM procedure of SAS.
Fisher’s protected LSD procedure was used to separate treatment means. Partial correlation analysis was used to evaluate the relationship among whole blood Se concentration and serum parameters, accounting for the effect of time. Across periods,
MIX steers had more (P ≤ 0.04) serum albumin than OSe and ISe steers, respectively.
However, the relative hepatic bovine serum albumin protein content was not affected
(P = 0.28) by Se treatments. Serum alkaline phosphatase activity was greater (P ≤
0.01) in MIX and OSe steers. Similarly, hepatic TNALP protein content in MIX steers was greater (P = 0.01) than ISe steers. Partial correlation analysis revealed that serum albumin, blood urea nitrogen, and alkaline phosphatase activity were correlated (r ≥
0.23, P ≤ 0.02) with whole blood Se concentration. In summary, consumption of 3 mg
Se/d as OSe or MIX forms of Se in vitamin-mineral mixes increased serum albumin concentration and alkaline phosphatase activity, the reduction of which is associated with fescue toxicosis. We conclude that the organic forms of Se ameliorated the depression of two of known serological biomarkers of fescue toxicosis.
KEYWORDS: steer, fescue toxicosis, selenium supplementation, albumin, alkaline phosphatase
106
5.2 Introduction
Ergot alkaloids produced by symbiont endophytes in tall fescue (Lolium
arundinaceum) have been identified as the causative agents for a variety of negative
physiological capacities, collectively known as fescue toxicosis (Strickland et al.,
2011). In addition to the classical suppression of serum prolactin, decreased serum alkaline phosphatase activity is another common clinical marker associated with cattle
grazing endophyte-infected tall fescue (Boling et al., 1989; Schultze et al., 1999;
Brown et al., 2009; Jackson et al., 2015). Other serological markers of fescue
toxicosis have been reported, including decreased aspartate aminotransferase activity
(Brown et al., 2009), alanine aminotransferase activity (Oliver et al., 2000; Brown et
al., 2009), albumin concentration (Jackson et al., 2015), and creatinine kinase activity
(Dougherty et al., 1991), but increased creatinine concentration (Schultze et al.,
1999). However, the exact mechanisms, as well as the physiological consequence of
these serological changes have not been fully delineated.
Besides fescue toxicosis, another challenge to endophyte-infected tall fescue-
based beef cattle operations is that the forage is typically Se-inadequate (below 0.1
ppm), due to Se-poor soils (Ammerman and Miller, 1975). Beef cattle require 0.10 mg
Se/kg of diet to meet the daily requirements (NRC, 1996). To remedy this, Se is
supplemented using free-choice vitamin-mineral mixes. Inorganic form (ISe, sodium
selenite) of selenium (Se) is commonly supplemented. However, the use of organic
forms of Se (OSe) in vitamin-mineral mix results in greater blood and tissue Se
107
concentrations (bioavailability) (Nicholson et al., 1991; Gunter et al., 2003; Liao et
al., 2011). Interestingly, feeding a 1:1 blend of ISe:OSe (MIX) results in equal
amount of Se in whole blood, red blood cells, serum, and liver of heifers as when
supplemented with only OSe, both of which are greater than ISe supplemented heifers
(Brennan et al., 2011). Hepatic transcriptome profiles have indicated that, compared
to ISe or OSe, MIX uniquely stimulates expression of genes involved in selenoprotein
synthesis and glutamate/glutamine metabolism (Matthews et al., 2014).
Serendipitously, some of the genes upregulated by MIX were found downregulated in
the liver (Liao et al., 2015) and pituitary (Li et al., 2017) of steers grazing high vs. low
endophyte-infected forages. Subsequently, a study (Jia et al., 2018) was conducted to
evaluate the effect of forms (ISe, OSe, and MIX) of supplemental Se on physiological
parameters of growing steers subjected to summer-long grazing of endophyte-infected tall fescue pasture. As a hallmark of fescue toxicosis, the concentration of serum prolactin in this study was decreased over time in all steers. However, across summer-
long grazing periods, steers supplemented with MIX or OSe forms of Se had 59% (P
< 0.03) and 52% (P < 0.05) more serum prolactin than ISe steers, respectively (Jia et
al., 2018).
To elaborate and explore these findings from the initial study (Jia et al., 2018),
the first goal of this study was to test the hypotheses that the form (ISe, OSe, and
MIX) of supplemental Se in vitamin-mineral mixes consumed by growing beef steers
grazing endophyte-infected tall fescue forage would ameliorate the negative
serological parameters associated with fescue toxicosis, including depressed serum
108
alkaline phosphatase activity and albumin content. The second goal was to evaluate the potential relationships between whole blood Se concentration and serum clinical parameters.
5.3 Materials and Methods
All experimental procedures were approved by the University of Kentucky
Institutional Animal Care and Use Committee.
5.3.1 Animals, Slaughter and Tissue Collection
Specific descriptions of the animal model, Se treatment administration, and liver sample collection procedures used in the initial study have been described (Jia et al.,
2018). However, briefly, twenty-four suckling predominantly Angus beef steers (BW:
183 ± 33.9 kg, age: 166 ± 14.2 day) were randomly selected (n = 8) from herds of fall-calving cows grazing toxic endophyte-infected tall fescue mixed forage pastures and that had ad libitum access to a common, basal, vitamin-mineral mix that contained either 35 mg/kg Se as ISe (sodium selenite, Prince Se concentrate; Prince
Agri Products, Inc., Quincy, IL), OSe (SEL-PLEX, Alltech Inc., Nicholasville, KY), or an 1:1 blend of ISe : OSe (MIX) forms. Over a pre-study, 98-day Se-depletion period (March 11 to June 17, 2015), steers were weaned, commonly depleted of Se, and trained to consume vitamin-mineral mix (lacing Se) from in-pasture Calan gates. 109
During this 98-day pretrial Se-depletion period, the ADG of steers was 0.82 ± 0.18 kg/day.
Steers then began (day 0) an 86-day (June 17 to September 9, 2015) common grazing period in which steer collectively grazed a predominately endophyte-infected tall fescue-mixed pasture (10.1 ha) and individually consumed their respective Se- form-specific vitamin-mineral mix treatments (ISe, OSe, MIX) through the use of in- pasture Calan gates. Steers were assigned to the same Se-form-specific vitamin- mineral mix treatment on which they were raised and which their dams received. The
Se-specific mixes contained the basal mix plus 35 mg/kg Se as ISe, OSe, or MIX. The composition of the basal vitamin-mineral mix was analyzed by Dairy One (Dairy One
Cooperative, Inc., Ithaca, NY) and previously described (Jia et al., 2018). To ensure individual consumption of 3 mg Se/day/steer, 85 g of the specific vitamin-mineral mix
(35 mg/kg Se) was top-dressed onto 227 g of soyhulls in each individual Calan gate feeder. The consumption of the mixture of soyhulls/vitamin-mineral mix was monitored daily, and all steers consumed all of the mixture every day. Thus, every steer consumed 3 mg of supplemental Se/day. During this 86-day period, two ISe steers were removed from the trial due to a bad hoof and failure to consume their mineral treatment. Thus, the final number of experimental observations was as follows: ISe = 6, OSe =8, and MIX = 8.
Steers were slaughtered over a 26-day period, from day 93 to 119 (September 17 to October 13, 2015) of the study. Specifically, one OSe and one MIX steer were killed on the first two slaughter days. On the remaining six slaughter days, one steer
110
each from ISe, OSe, and MIX treatment groups were killed. The slaughter process for these steers has been described in detail (Jia et al., 2018). Liver samples were collected from the mid-lower right lobe and placed in foil packs, snap-frozen in liquid nitrogen, and stored at −80 °C for microarray and real-time RT-PCR analyses.
Pasture samples (30 sites per sample day) were collected throughout the common grazing (days 0, 22, 43, 64, 86) and slaughter (day 115) periods and analyzed separately. The mean total concentration of ergovaline and ergovalinine was 0.51 ppm
(Jia et al., 2018).
5.3.2 Blood Collection and Analyses
Jugular vein blood samples were collected by venipuncture on day 0, 22, 43, 64, and 86. For serum, 16 mL of blood was collected in serum blood collection tubes
(Becton Dickinson) without an anticoagulant. Serum was recovered after centrifugation at 3,000 × g for 10 min at 4 °C, and stored at −80 °C. All serum enzymes and analytes were analyzed by the American Association for Veterinary
Laboratory Diagnosticians approved-University of Kentucky Veterinary Diagnostic
Laboratory (Lexington, KY). For serum analytes, activities of alkaline phosphatase
(ALP), E.C. 3.1.3.1; aspartate transaminase (AST/SGOT), E. C. 2.6.1.1; γ- glutamyltransferase (GGT), E. C. 2.3.22; creatine kinase, E. C. 2.7.3.2 were determined as per the manufacturer of the reagent kits (Alfa Wassermann, Diagnostic
111
Technologies, West Caldwell, NJ) using a VET AXCEL Chemical Analyzer (Alfa
Wassermann, Diagnostic Technologies, West Caldwell, NJ).
5.3.3 Western Blot Analysis
All Western blot and densitometric analyses for the relative expression of targeted proteins were performed using a standard protocol of our lab as previously described (Miles et al., 2015). Approximately 0.2 g of liver was homogenized on ice for 30 s (setting 11, Polytron Model PT10/35, Kinematic Inc., Lucerne, Switzerland) in 7.5 mL of 4 °C sample extraction buffer solution (0.25 mM sucrose, 10 mM
HEPES-KOH pH 7.5, 1 mM EDTA, and 50 μL of protease inhibitor [Sigma, St.
Louis, MO]). Protein was quantified by a modified Lowry assay, using bovine serum albumin as a standard (Kilberg, 1989). Proteins were separated using 12% SDS-PAGE and electrotransferred onto a 0.45 μm nitrocellulose membrane (Bio-Rad) and then stained with Fast-Green (Fisher, Pittsburgh, PA). The relative amount of stained protein per lane per sample was determined by densitometric analysis and recorded as arbitrary units (Brown et al., 2009)
The use of rabbit IgG anti-bovine serum albumin (BSA) polyclonal antibody and rabbit IgG anti-bovine alkaline phosphatase (tissue non-specific, liver/bone/kidney;
TNALP) were validated by pre-adsorption of primary antibodies with their respective antigen polypeptides, using the general procedures of Xue et al. (2011).
112
Immunoreaction products for BSA (Figure 5.1) and TNALP (Figure 5.2) in liver
homogenates (5 μg for BSA, 40μg for TNALP) were all abolished if pre-adsorbed
(μg: μg) with increasing amounts of their antigens, thus validating their use. The abolishing antibody:antigen ratios were 1:2 and 1:5 for BSA and TNALP, respectively. The relative protein content of BSA and TNALP in liver homogenates was detected using procedures as previously described (Miles et al., 2015). Briefly, blots were hybridized with 1 μg of IgG anti-bovine serum albumin polyclonal antibody (Abcam Inc., Cambridge, MA) per milliliter of blocking solution (3% nonfat dry milk [wt/vol], 10 mM Tris-Cl [pH 7.5], 100 mM NaCl, 0.1% Tween 20 [vol/vol]) for 1.5 h at room temperature with gentle rocking. For TNALP detection, blots were hybridized with 0.6 μg IgG anti-recombinant bovine TNALP polyclonal antibody
(MyBioSource, San Diego, CA) per milliliter of blocking solution (5% nonfat dry milk [wt/vol], 10 mM Tris-Cl [pH 7.5], 100 mM NaCl, 0.1% Tween 20 [vol/vol]) for
1.5 h at room temperature with gentle rocking. Protein-primary antibody binding reactions were visualized with a chemiluminescence kit (Pierce, Rockford, IL) after hybridization of primary antibody with horseradish peroxidase-conjugated donkey anti-rabbit IgG (Amersham, Arlington Heights, IL; TNALP, 1:5000).
Densitometric analysis of immunoreactive products was performed as described previously (Miles et al., 2015). After exposure of auto-radiographic film (Amersham,
Arlington Heights, IL), digital images of all observed immunoreactive species were recorded and quantified as described (Dehnes et al., 1998). Apparent migration weights (Mr) were calculated by regression of the distance migrated against the Mr of
113
a 16 to 185 kDa standard (Gibco BRL, Grand Island, NY) using the Versadoc imaging
system (Bio-Rad) and Quantity One software (Version 4.2.3, Bio-Rad). Band
intensities of the single immunoreactant (69.3 kDa) for BSA, and the predominant immunoreactant (39 kDa) for TNALP, were quantified by densitometry (as described above for Fast-Green stained proteins) and reported as arbitrary units. Densitometric data were corrected for unequal (10%, TNALP; 17%, BSA) loading, transfer, or both,
and amount of detected protein normalized to relative amounts of Fast-Green-stained
proteins common to all immunoblot lanes/samples (Miles et al., 2015). Digital images
were prepared using PowerPoint software (Microsoft, PowerPoint 2013, Bellevue,
MA).
5.3.4 Hepatic RNA Extraction and Analysis
For each animal, total RNA was extracted from 300 mg of frozen liver tissue
using TRIzol Reagent (Invitrogen Corporation, Carlsbad, CA) following the
manufacturer’s instructions. The purity and concentration of total RNA samples was analyzed using a NanoDrop ND-100 Spectrophotometer (NanaDrop Technologies,
Wilmington, DE, USA). All samples had an average concentration of 1.05 μg/μL and a high purity with 260/280 absorbance ratios of 1.98-2.03 and 260/230 absorbance ratios ranging from 1.89 to 2.18. The integrity of total RNA was examined by gel electrophoresis using an Agilent 2100 Bioanalyzer System (Agilent Technologies,
114
Santa Clara, CA) at the University of Kentucky Microarray Core Facility.
Visualization of gel images and electropherograms showed that all RNA samples were
of high quality with RNA integrity numbers (RIN) being greater than 8.7 and 28S/18S
rRNA absorbance ratios greater than 2.
5.3.5 Real-time RT-PCR Analysis
The quantification of relative mRNA for genes of interest was performed using
standard procedures in our laboratory, as previously described (Cerny et al., 2016).
Briefly, 1 µg of each steer’s liver RNA was reversely transcribed to cDNA using the
SuperScript III 1st Strand Synthesis System (Invitrogen). Real-time RT-PCR were performed using an Eppendorf Mastercycler ep realplex2 system (Eppendorf,
Hamburg, Germany) with iQ SYBR Green Supermix (Bio-RAD, Hercules, CA). A total volume of 25 µL was used in each real-time RT-PCR reaction containing 5 µL of cDNA, 1 µL of a 10 µM stock of each primer (forward and reverse), 12.5 µL of 2 ×
SYBR Green PCR Master Mix, and 5.5 µL of nuclease-free water. The relative amount of each transcript was calculated using the 2-ΔΔCT method (Livak and
Schmittgen, 2001). Primer sets (Table 5.3) for genes of interest were designed and obtained from NCBI Primer-BLAST tool (https://www.ncbi.nlm.nih.gov/tools/primer- blast/) against RefSeq sequence (accessed February to April, 2018)
All real-time RT-PCR cDNA products were validated by DNA sequencing
115
verification and were 97% to 100% identical with their RefSeq sequences (Table 5.3).
Briefly, the PCR-amplified cDNA products were electrophoresed in a 1.2% agarose
(UltraPureTM Agarose, Invitrogen, Carlsbad, CA) slab gel. A single cDNA band at the
desired size was identified under a UV light, excised from the gel, purified using the
PureLink Quick Gel Extraction Kit (Invitrogen, Carlsbad, CA), then sequenced by
Eurofins Genomics (Eurofins MWG Operon LLC, Louisville, KY). The resulting
sequences (Figure 5.3) were compared to the NCBI RefSeq mRNA sequences used as
templates for primer pair set design. From 9 constitutively expressed gene candidates
(ACTB, GAPDH, SDHA, PCK2, UBC, YWHAZ, HPRT1, PPIA,TBP) three constitutively expressed genes (YWHAZ, HPRT1, PPIA) were selected with the lowest average stability value of M = 0.19, calculated using the geNorm software v3.5
(Vandesompele et al., 2002). The relative mRNA expression was normalized to the
geometric means of three constitutively expressed genes. For the RT-PCR analysis, n
= 6, 8, and 8 samples were used for ISe, OSe, and MIX treatments, respectively. RT-
PCR reactions were performed in triplicate.
5.3.6 Statistical Analysis
Data are presented as least square means (±SEM). Steers were the experimental units. The effect of Se supplementation on serum analytes was evaluated by ANOVA, using the PROC MIXED procedure of SAS (v 9.4, SAS Inst. Inc., Cary, NC). The
116
statistical model included Se supplementation, time, and their interaction as fixed
effects. Class variables were Se supplementation and steer, with steer included in the
random statement. The Kenward-Roger adjustment was used to calculate the denominator of df (Kenward and Roger, 1997). Within Se supplement treatments, nonorthogonal polynomial contrasts (linear, quadratic, and cubic) were used to characterize the effect of Se treatments over time on serum clinical parameters, using the PROC IML procedure of SAS to generate coefficients for unequally spaced contrasts. Partial correlations between whole blood selenium concentrations and serum clinical analytes, and controlling the effects of day, were conducted by using the MANOVA/PRINTE statement of PROC GLM procedure of SAS. After slaughter, the effect of Se supplementation on the relative abundance of hepatic mRNA (RT-
PCR) and protein (Western blotting) was assessed by ANOVA, using the PROC GLM procedure of SAS. For all data, Fisher’s protected LSD procedure was used to separate treatment means.
5.4 Results
5.4.1 Serum Clinical Parameters
Serum alkaline phosphatase activity was affected (P = 0.01) by Se treatment
(Figure 5.4A). Across periods, MIX and OSe steers had 42% (P < 0.01) and 40% (P =
0.01) more serum alkaline phosphatase activity than ISe steers, respectively, and did
not differ from each other (P = 0.87). A day effect was observed (P < 0.01) in serum 117
alkaline phosphatase activity, but there was no (P = 0.70) Se treatment by day
interaction. Across Se treatments, serum alkaline phosphatase activity on day 0, day 22,
and day 64 were not different (P ≥ 0.15) within each other, and all greater than that on
day 43 (P ≤ 0.07) and day 86 (P ≤ 0.01). Within Se treatments, nonorthogonal
polynomial contrast analysis revealed a linear (P = 0.05) decrease response pattern of
serum alkaline phosphatase activity to time in ISe steers. Similarly, serum alkaline
phosphatase activity of MIX steers tended (P = 0.07) to linearly decrease to time. In contrast, serum alkaline phosphatase activity of OSe steers did not (P ≥ 0.11) show a significant response to time.
The concentration of serum albumin was affected by Se treatment (P = 0.03), day
(P < 0.01), and their interaction (P < 0.01) (Figure 5.4B). Specifically, across periods,
MIX steers had 4.3% (P = 0.01) and 3.7% (P = 0.04) greater serum albumin
concentrations than OSe and ISe steers, respectively, whereas the serum albumin concentration of OSe steers was not significantly different (P = 0.74) from that of ISe steers. Across Se treatments, the concentration of serum albumin was least on day 86
(P < 0.01), whereas, day 22 had significantly greater (P < 0.02) serum albumin than day 0 and day 64. The Se treatment by day interaction seems to mostly reflect the differential change of albumin concentration from day 0 to day 22, and day 64 to day
86. Therefore, nonorthogonal polynomial contrast analysis was conducted to characterize the response pattern of serum albumin over time within Se treatments. The concentration of serum albumin essentially decreased in a quadratic manner for both
ISe and OSe steers, reflecting a marked drop of 7 (P = 0.10) and 6% (P < 0.01),
118
respectively, from day 64 to day 86. In contrast, the serum albumin concentration of
MIX steers did not (P ≥ 0.07) change over time. The differential response in serum albumin concentrations over time between ISe and OSe vs. MIX is reflected by the significant Se treatment by day interaction.
The concentration of blood urea nitrogen was affected (P < 0.01) by Se treatment
(Figure 5.4C). Specifically, MIX and OSe steers had 21% (P < 0.01) and 17% (P < 0.01) greater blood urea nitrogen than ISe steers, respectively, and did not differ from each other (P = 0.50). A day effect was found (P < 0.01) for blood urea nitrogen, but there was no (P = 0.93) Se treatment by day interaction. Across Se treatments, the concentration of blood urea nitrogen was least on day 0 (P < 0.01), greatest on day 64
(P ≤ 0.05), and not different among day 22, day 43, and day 86 (P ≥ 0.34). Within Se treatments, nonorthogonal polynomial contrast analysis indicated that blood urea nitrogen increased in a quadratic manner for ISe (P = 0.02), OSe (P = 0.02), and MIX
(P = 0.01) steers, apparently reflecting a marked increase from day 0 to day 22 before plateauing.
A main effect of Se supplementation treatment (P = 0.03), day (P < 0.01), and their
interactions (P < 0.01) were observed for serum sodium concentrations (Figure 5.5D).
Across periods, MIX steers had 1.4 % greater (P < 0.01) serum sodium concentration than ISe steers, but did not differ (P = 0.21) from OSe steers. The concentration of serum sodium between ISe and OSe steers was not different (P = 0.11). Across Se treatments, the concentration of serum sodium among day 0, day 43, and day 86 were not different (P ≥ 0.07), and greater (P ≤ 0.01) than those on day 22 and day 64. Within
119
Se treatments, nonorthogonal polynomial contrast showed that the concentration of serum sodium responded in a quartic manner over time for ISe (P = 0.02), OSe (P <
0.01) and MIX (P = 0.01) steers.
The concentration of serum phosphorus was affected (P < 0.01) by Se treatment
(Figure 5.5E). Specifically, OSe steers had 11% (P < 0.01) and 6.8% (P = 0.04) greater serum phosphorus concentration than MIX and ISe steers, respectively, but ISe and
MIX steers did not differ (P = 0.23) from each other. A day effect (P < 0.01) was observed on serum phosphorus concentration, but there was no (P = 0.48) Se treatment by day interaction. Within Se treatments, according to nonorthogonal polynomial contrast analysis, serum phosphorus concentration tended (P = 0.08) to quadratically decrease over time in ISe steers. However, the concentration of serum phosphorus in
OSe steers decreased in a cubic manner (P < 0.01) over time, whereas it tended (P =
0.07) to cubically decrease in MIX steers.
The concentration of serum magnesium was affected by Se treatment (P = 0.02), day (P < 0.01) and Se treatment by day interaction (P < 0.01) (Figure 5.5F). Across periods, OSe steers had 7.2% more (P < 0.01) serum magnesium concentration than
ISe steers, but did not differ (P = 0.06) from MIX steers. The concentration of serum magnesium between ISe and MIX steers did not differ (P = 0.29). Within Se treatments, nonorthogonal polynomial contrast analysis showed an essentially linear
(P < 0.01) increase of serum magnesium concentration in ISe and OSe steers. In contrast, serum magnesium concentration tended (P = 0.07) to cubically increase in
MIX steers.
120
The blood urea nitrogen:creatinine ratio was affected by Se treatment (P < 0.01)
and day (P < 0.01) (Table 5.2). However, no Se treatment by day interaction was observed (P = 0.21). More specifically, within the main effect of Se treatments, OSe and MIX steers had 20% (P < 0.01) and 17% (P < 0.01) greater blood urea nitrogen:creatinine ratio than ISe steers. This Se treatment effect might be driven by the combination of elevated blood urea nitrogen concentration (P < 0.01), and unchanged creatinine concentration (P = 0.51) in OSe and MIX steers versus ISe steers.
Significant day effects (P ≤ 0.02) were observed for serum potassium, chloride, calcium, creatinine, glucose, creatinine kinase, aspartate aminotransferase, γ- glutamyltransferase, total protein, and globulin analytes, and the albumin:globulin ratio. However, no Se treatment effect (P ≥ 0.13) was observed in these serum parameters. A Se treatment × day interaction was found (P < 0.01) for serum chloride, total protein, and globulin concentrations, and the albumin:globulin ratio.
5.4.2 Hepatic Bovine Serum Albumin Protein Content, Alkaline Phosphatase
mRNA and Protein Content
The relative amount of hepatic bovine serum albumin protein was not affected (P
= 0.28) by Se treatment (Table 5.3, Figure 5.6). In contrast, selenium treatment did
affect (P = 0.04) the amount of hepatic alkaline phosphatase (tissue non-specific,
liver/bone/kidney, TNALP), with MIX steers having 147% more (P = 0.01) TNALP
than ISe steers, and not differing (P = 0.17) from OSe steers (Table 5.3, Figure 5.6). 121
No difference (P = 0.15) was found in TNALP protein content between OSe and ISe
steers, despite OSe steers having numerically more (78%) TNALP than ISe steers. In
contrast, the relative expression of hepatic TNALP mRNA did not differ (P = 0.37)
among Se treatments (Table 5.3).
5.4.3 Partial Correlation of Whole Blood Se Concentration with Serum Clinical
Parameters
For both across and within Se treatments, partial correlation analysis was
conducted to determine the relationships between whole blood Se concentrations and
serum clinical parameters, while controlling the effect of day (Table 5.4). Across Se
treatments, weak positive correlations (0.244 > r > 0.209) were observed between
whole blood Se and serum albumin (P = 0.02), magnesium (P = 0.01), potassium (P =
0.03), glucose (P = 0.03), and total protein (P = 0.01). In contrast, the whole blood Se was weakly and negatively correlated with serum potassium (r = -0.213, P = 0.01).
Across Se treatments, moderate correlations were found between the whole
blood Se and serum alkaline phosphatase (r = 0.321, P < 0.01), blood urea nitrogen (r
= 0.38, P < 0.01), creatinine (r = -0.443, P < 0.01), and blood urea nitrogen:creatinine
ratios (r = 0.527, P < 0.01).
5.5 Discussion
122
5.5.1 Animal Model
As described previously for the initial study (Jia et al., 2018), the steers of this
study had ad libitum access to their respective supplemental Se treatments as suckling
calves before their selection into the trial. After being weaned, depleted and then
repleated with the form of supplemental Se on which they were raised, and adapted to
eat from Calan gates, steers then were subjected to summer-long common grazing of tall fescue-mixed pasture, while individually consuming 3 mg/d of their respective Se from initiation of the grazing period until their slaughter (up to 113 d) by use of Calan gates. Also as previously reported (Jia et al., 2018), the concentration of ergot
alkaloids in the endophyte-infected tall fescue pasture was 0.51 ppm (ergovaline plus
ergovalinine), which a previous grazing study from our lab showed summer-long
grazing of endophyte-infected tall fescue that contained 0.52 ppm ergovaline plus
ergovalinine was sufficient to induce fescue toxicosis (Brown et al., 2009). The
classic reduction of serum prolactin concentration in steers of the current study
confirms the onset of fescue toxicosis. The observed rapid increase and then
stabilization in whole blood concentrations of Se in all three Se treatment group steers
is consistent with our previous Se depletion/repletion regimens with growing beef
heifers (Brennan et al., 2011; Liao et al., 2011). Moreover, compared to ISe steers,
OSe and MIX steers had greater serum prolactin concentrations across summer-long
(86-d) grazing periods than ISe steers (Jia et al., 2018). Taken together, the animal
model was successfully established to evaluate the ability of different forms of
supplemental Se to ameliorate the negative serological parameters of growing beef
123
steers grazing toxic endophyte-infected tall fescue pasture.
5.5.2 MIX and OSe Forms of Se Supplementation Resulted in Greater Serum
Alkaline Phosphatase Activity Vs. ISe
Decreased serum total alkaline phosphatase activity has been widely reported in cattle consuming ergot alkaloids from endophyte-infected tall fescue (Boling et al.,
1989; Rice et al., 1997; Schultze et al., 1999; Brown et al., 2009). The consistently suppressed serum alkaline phosphatase activity has been regarded as a repeatable clinical measure of fescue toxicosis (Oliver et al., 2000). The exact mechanism of this decrease of serum total alkaline phosphatase activity induced by fescue toxicosis is not understood. However, in vitro studies have shown that cyclic AMP induces de novo synthesis of alkaline phosphatase mRNA and results in an increased alkaline phosphatase protein production in mouse L-cells (Firestone and Heath, 1981). Also, cyclic AMP has been reported to induce the tissue non-specific alkaline phosphatase mRNA expression (liver/bone/kidney, tissue non-specific isoenzyme) in L929 fibroblastic cells (Gianni et al., 1993). Due to structural similarities with dopamine and other biogenic amines, ergot alkaloids bind and stimulate dopamine type two receptors (Larson et al., 1994; Larson et al., 1999), consequently inhibiting adenylyl cyclase and then cyclic AMP (Fitzgerald and Dinan, 2008). Other researchers (Boling et al., 1989; Rice et al., 1998) have speculated that ergot alkaloids could negatively affect the alkaline phosphatase induction by inhibiting cyclic AMP, thus resulting in a decrease of total alkaline phosphatase or certain alkaline phosphatase isoform activity 124
in the serum.
Throughout the grazing period of the current study the serum alkaline
phosphatase activity was greater in OSe and MIX than ISe steers. A priori, this finding suggests that consumption of organic forms of Se somehow mitigated the negative effects of ergot alkaloid binding of the dopamine type two receptor, thus resulting in less repression of cyclic AMP production. However, an alternative or parallel explanation may involve the reported differential effect of Se forms on dopamine-
stimulated neuronal signaling (Solovyev, 2015). More specifically, consumption (3
and 9 ppm in drinking water) of ISe (selenite), but not OSe, resulted in increased
concentrations of dopamine and its metabolites in murine striatum (Tsunoda et al.,
2000). Therefore, compared to ISe, it is reasonable to speculate that OSe-
supplemented steers may have had lower dopamine concentration, and consequently,
less activation of dopamine signaling cascades and less inhibition of cyclic AMP. The inductive effect of cyclic AMP to alkaline phosphatase mRNA and protein, and the greater serum alkaline phosphatase activity found in OSe and MIX than ISe steers in this study appears consistent with the findings in brain tissue (Tsunoda et al., 2000) and cell culture models (Firestone and Heath, 1981; Gianni et al., 1993) discussed above. That is, the consumption of ISe may exacerbate the negative effect of consuming ergot alkaloids has on cyclic AMP-mediated repression of alkaline phosphatase. However, to support this speculation, research is needed to determine the effect of Se form on the expression and function of key enzyme/proteins involved in the dopamine signaling cascade, and its possible downstream regulatory effects on
125
prolactin and alkaline phosphatase.
Total serum alkaline phosphatase activity is comprised from various soluble
alkaline phosphatase released from membranes of different tissues. In cattle, serum
alkaline phosphatase mostly originates from liver and bone (Doornenbal et al., 1988),
and has been used as a serum biomarker of liver or bone-related diseases. In mammals, including cattle, tissue non-specific isoenzyme of alkaline phosphatase
(TNALP) is expressed in most tissues, including liver, bone, kidney, and placenta
(Hank et al., 1993). Therefore, to determine if Se treatments on liver may have contributed to the greater serum alkaline phosphatase activity of OSe and MIX steers, the TNALP mRNA and protein content was measured in homogenates of liver collected at slaughter. In agreement with their trial-long increased serum alkaline phosphatase activity, MIX steers had 147% more hepatic TNALP protein content than
ISe steers (Table 5.3). In contrast to the significantly higher serum alkaline phosphatase activity of OSe steers, the hepatic TNALP protein content of OSe steers did not differ, despite being numerically greater (78%). These data indicate that the elevated serum alkaline phosphatase in MIX steers was at least partially the result of increased liver isoform of alkaline phosphatase. That hepatic mRNA content also did not differ, is consistent with the understanding that hepatic TNALP is commonly regulated by post-translational modifications (Fernandez and Kidney, 2007).
126
5.5.3 MIX Form of Se Supplementation Resulted in Greater Serum Albumin than
OSe and ISe
Serum albumin is another parameter previously found affected by grazing endophyte-infected tall fescue. A summer-long grazing study showed that the serum albumin concentrations was lower (P = 0.05) in steers grazing high endophyte- infected (0.52 ppm of ergovaline and ergovalinine) tall fescue than those grazing low endophyte-infected (0.01 ppm of ergovaline and ergovalinine) tall fescue for 85 days
(Brown et al., 2009). Interestingly, this decreased concentration of serum albumin was also observed on days 37 (P = 0.03) and 59 (P = 0.01) of the same steers undergoing summer-long grazing high endophyte-infected tall fescue (Jackson et al., 2015). It is important to note that all steers had ad libitum access (free-choice) to a vitamin- mineral mix that was identical in composition to the ISe treatment in the current study. Although the exact reason behind the serum albumin reduction is not clear, the authors suggested that the hepatic albumin synthetic capacity was reduced in steers grazing endophyte-infected tall fescue (Brown et al., 2009), and possibly as a consequence of reduced intake and malnutrition. In the current study, this reduced serum albumin associated with grazing endophyte-infected tall fescue was alleviated in steers supplemented with MIX form of Se. However, in contrast to the serum concentrations, the hepatic albumin protein content in MIX steers did not differ from that of OSe and ISe steers (Table 5.3). Because it is well accepted that serum albumin is synthesized and secreted from hepatocytes into blood circulation (which accounts for about 13% of the total protein produced by liver, Peters (1977)), these data suggest
127
that the increased serum albumin concentration in MIX steers either was not due to an
elevated synthetic capacity of hepatic albumin, or that MIX steers had an elevated
albumin synthesis capacity that was matched by an increased albumin secretion
capacity. To better understand the physiological significance of the greater
concentration of serum albumin in MIX steers, research is needed to study the
metabolic fate of circulating albumin.
5.5.4 Blood Urea Nitrogen, and Serum Sodium, Phosphorus, and Magnesium
Concentration Were Affected by Form of Se
The concentration of blood urea nitrogen is a function of synthesis from hepatic
ornithine cycle and renal removal by renal glomerular filtration. In addition,
ruminants recycle a considerable amount of blood urea to the rumen by excretion
across forestomach epithelia and salivary gland secretion (Archibeque et al., 2001). In the current study, serum creatinine concentrations were not affected by the form of Se supplementation (Table 5.2). Thus, it is reasonable to suggest that the renal capacity
of glomerular filtration did not differ among ISe, OSe, and MIX steers, given that
serum creatinine is the most efficient indirect marker of glomerular filtration rate in
mammals (Kaneko et al., 2008). Therefore, altered hepatic urea synthesis or
gastrointestinal tract urea recycle seems more likely to be responsible for the elevated
serum blood urea nitrogen concentration in OSe and MIX steers than that of ISe
steers. Interestingly, as reported previously (Jia et al., 2018), the upregulation of glutamine synthetase (critical enzyme in hepatic ammonia fixating) in mRNA, protein 128
content, and enzyme activity in MIX and OSe steers strongly indicates an altered
hepatic nitrogen metabolism in MIX- and OSe-treated steers. Taken together, it appears to be reasonable to relate the different blood urea nitrogen profile to the altered hepatic nitrogen metabolism induced by MIX and OSe form of Se.
It is important to note that the difference in serum alkaline phosphatase activity
(Figure 5.4A) and blood urea nitrogen concentration (Figure 5.4C) among ISe, OSe, and MIX existed at the beginning of the experiment (Day 0). This preexisting difference might be explained by the inherent different Se physiology of these three groups of steers raised on different forms of selenium in their vitamin-mineral mixes.
As described in the Materials and Methods, ISe, OSe, and MIX steers were randomly selected from three cow-calf herds with free access to ISe, OSe and MIX form of Se in vitamin-mineral mixes, respectively. Because Se was depleted for 98 days after selection, it is reasonable to suggest that the preexisting differences in serum alkaline phosphatase activity and blood urea nitrogen concentration possibly were caused by
Se status-induced epigenetic effects. Importantly, Se status has been shown to affect
hepatic DNA methylation in the liver of mice (Speckmann et al., 2017). Moreover, our lab has shown that calf whole blood Se concentrations were correlated to, and affected by, the dam’s sources of Se (Patterson et al., 2013), wherein the whole blood
Se concentrations in OSe and MIX calves were higher than for ISe calves. Therefore, it is reasonable to speculate in the current study that a different Se status existed in Se form-specific steers from after birth to weaning (selection), which may have resulted in epigenetic changes that fundamentally affected the metabolism of alkaline
129
phosphatase and blood urea nitrogen.
The literature is limited with regard to the potential interaction of Se
supplementation with sodium, phosphorus, and magnesium metabolism. When
supplemented with the ISe form of Se, steers grazing high endophyte-infected tall
fescue (0.52 ppm total ergot alkaloids: ergovaline plus ergovalinine) had decreased
serum sodium concentration on day 36 than that grazing low endophyte-infected tall fescue (Jackson et al., 2015). It was speculated that the reduction of serum prolactin might be responsible for this, because prolactin promotes the retention of Na+ and K+
in kidney (Richardson, 1973) and the absorption of Na+, K+, and Ca2+ in intestine epithelial (Mainoya, 1975b). In the current study, across periods, MIX steers had higher serum sodium concentration than ISe steers (Figure 5.5D). Interestingly, the serum prolactin concentration in current study was higher in MIX steers than ISe steers (Jia et al., 2018). Given the various biological effects of prolactin on water and electrolyte balance (Bole-Feysot et al., 1998), the higher serum sodium concentration in MIX steers in the current study could be due to the high serum prolactin concentrations, However, concentrations of serum potassium and calcium was not affected (Table 5.2) by Se form treatment in this study. Nevertheless, and regardless their physiological consequences, across periods, the average concentration of serum sodium, phosphorus, and magnesium in ISe, OSe and MIX steers (Figure 5.5D) were all within reference range, as serum sodium 132-152 mmol/L, serum phosphorus 3.5-
8 mg/dL, and magnesium 1.7-2.9 mg/dL (University of Kentucky Veterinary
Diagnostic Lab (http://vdl.uky.edu/).
130
5.5.5 Whole Blood Se Concentration Is Correlated with Alkaline Phosphatase
Activity, Serum Albumin, Blood Urea Nitrogen, and Magnesium Concentration
Whole blood Se concentration is one of the parameters commonly determined to
indicate Se status, and is well correlated with Se intake in cattle (Patterson et al.,
2013). Again as reported (Jia et al., 2018), whole blood Se concentrations were
affected by the form of Se supplementation, with OSe and MIX steer concentrations
being higher than that of ISe steers. Therefore, the second goal of this study was to evaluate the potential relationships between whole blood Se and serum analytes
(Table 5.4). Due to the significant time effect observed in all serum parameters, the partial correlation was used to account for the time effect. The significant positive
correlation between whole blood Se and the serum blood urea nitrogen:creatinine
ratio can be mathematically explained by the finding that whole blood Se was
positively and negatively correlated with blood urea nitrogen and serum creatinine,
respectively. Although the concentrations of serum creatinine and potassium did not
differ among Se treatments, significant negative correlations were observed between
whole blood Se and serum creatinine and potassium concentrations. The reason and
physiological consequences of these negative correlations need to be determined.
Nevertheless, significant positive correlations between whole blood Se and serum
albumin, alkaline phosphatase activity, magnesium, and blood urea nitrogen, were
found, which seems to suggest that the changes of these parameters were associated
with the alterations of whole blood Se. In contrast, serum prolactin, sodium, and
phosphorus concentrations were affected by the form of supplemental Se, but not
131
correlated with whole blood Se concentration. This inconsistency may be reasonable given the various biological roles of Se and given that selenoproteins perform many of these roles (Labunskyy et al., 2014).
5.6 Summary
In summary, predominantly Angus steers subjected to summer-long grazing of endophyte-infected pasture and supplemented (3 mg/day) with MIX or OSe forms of
Se had higher whole blood Se, serum albumin, and blood urea nitrogen concentrations, and greater serum alkaline phosphatase activity than ISe-supplemented steers.
Moreover, these analytes were positively correlated with whole blood Se concentration, which is one of the indicators of whole body Se status. These findings indicate the inclusion of organic forms of Se in vitamin-mineral mixes of steers grazing endophyte- infected tall fescue forages increase the concentration of two of known serological biomarkers of fescue toxicosis, that are depressed in cattle suffering from fescue toxicosis. When combined with the understanding that organic forms of Se also elevate depressed serum prolactin concentrations in the same steers (Jia et al., 2018), results of this study indicate that inclusion of 3 mg Se/day in MIX or OSe forms of Se in vitamin- mineral mixes ameliorates the depression of three known biomarkers of fescue toxicosis
.
132
Table 5. 1 Primer information and results of real-time RT-PCR product sequence (Figure 5.3) validation.
RefSeq accession Oligonucleotide primer design (5’ to Amplicon Product identity RT-PCR product Gene name number 3’ direction) length (bp) (%) accession number
F:GCCAGCCGGCTACGTTAT HPRT1 NM_001034035.2 256 100% MK396253 R:ATCCAACAGGTCGGCAAAGA
F:TTGATCCCCAACGCTTCACA YWHAZ NM_174814.2 208 99% MK396254 R:AGTTAAGGGCCAGACCCAGT
133 F:GGCAAGTCCATCTATGGCGA PPIA NM_178320.2 240 99% MK309342
R:TTGCTGGTCTTGCCATTCCT
F:ACATCGAGGTGATCATGGGC ALPL NM_176858.2 369 100% MK310189 R:CAATCCTGCCCCCTTCCAC
Table 5. 2 Serum clinical parameters in growing beef steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in
vitamin-mineral mixes as sodium selenite (ISe), SEL-PLEX (OSe), or an 1:1 blend of ISe and OSe (MIX).
P value Item Trt D 0 D 22 D 43 D 64 D 86 SEM Se form by Se form Day Day ISe 4.53 3.98 4.23 4.09 4.37 0.060 Potassium, OSe 4.60 4.09 4.34 4.08 4.38 0.056 0.78 < 0.01 0.22 mmol/L MIX 4.68 4.20 4.50 3. 95 4.13 0.056 ISe 108.4 104.3 105.7 100.4 104.7 0.53 Chloride,
134 OSe 103.3 107.0 103.1 103.6 101.9 0.49 0.40 < 0.01 < 0.01 mmol/L
MIX 108.5 104.5 101.4 101.1 106.4 0.49 ISe 10.21 10.00 9.41 9.96 9.57 0.088 Calcium, OSe 9.70 10.25 9.34 9.79 9.51 0.081 0.43 < 0.01 0.23 mg/dL MIX 9.65 10.39 9.49 9.71 10.06 0.081 ISe 1.43 1.12 1.11 1.00 1.24 0.037 Creatinine, OSe 1.35 1.13 1.09 1.03 1.18 0.035 0.51 < 0.01 0.05 mg/dL MIX 1.46 1.15 1.16 1.10 1.18 0.035 Blood urea ISe 8.43 13.67 14.14 16.86 12.71 0.470 nitrogen1:creatinine OSe 10.88 16.25 16.50 19.50 15.38 0.437 < 0.01 < 0.01 0.21 ratio MIX 10.38 15.88 16.13 17.63 16.38 0.437 ISe 82.9 84.3 84.7 81.6 77.7 1.48 Glucose, OSe 81.4 85.1 85.6 84.8 77.8 1.38 0.79 < 0.01 0.35 mg/dL MIX 82.9 83.5 81.8 81.6 78.1 1.38
Table 5. 2 (continued) ISe 218.4 218.7 187.9 199.7 180.4 9.2 Creatinine kinase, OSe 225.4 213.4 205.3 200.6 205.5 8.6 0.71 < 0.01 0.44 U/L MIX 229.0 208.3 197.3 214.8 183.3 8.6 Aspartate ISe 63.7 55.3 56.4 58.3 54.0 2.88 aminotransferase, OSe 62.4 60.0 60.9 61.5 58.5 2.69 0.24 < 0.01 0.10 U/L MIX 70.8 60.4 60.8 63.0 65.9 2.69 γ- ISe 13.14 13.00 15.14 14.86 14.14 0.749 Glutamyltransferase, OSe 13.00 14.88 15.75 15.50 15.38 0.699 0.73 0.02 0.50 U/L MIX 13.38 13.75 14.25 14.88 15.75 0.701 ISe 6.67 6.83 7.19 6.84 7.14 0.082 Total protein, OSe 6.88 7.05 7.24 7.03 6.95 0.076 0.13 < 0.01 < 0.01
135 g/dL MIX 7.11 7.28 7.19 7.25 7.01 0.076
ISe 3.57 3.73 4.09 3.77 4.24 0.094 Globulin, OSe 3.81 3.90 4.15 3.96 4.11 0.088 0.61 < 0.01 < 0.01 g/dL MIX 4.00 4.04 3.99 4.10 3.86 0.088 ISe 0.86 0.85 0.76 0.83 0.70 0.024 Albumin2:globulin OSe 0.81 0.81 0.76 0.78 0.71 0.023 0.70 < 0.01 < 0.01 ratio MIX 0.79 0.80 0.80 0.79 0.81 0.023
1Data are least squares means (n = 6 for ISe, n = 8 for OSe and MIX). 2Value of blood urea nitrogen and albumin are presented in Figure 5.4
Table 5. 3 Hepatic bovine serum albumin protein content, alkaline phosphatase (tissue non-specific, liver/bone/kidney, TNALP) mRNA and
protein content in liver homogenates after slaughter of beef steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d
in vitamin-mineral mixes as sodium selenite (ISe, n = 6), SEL-PLEX (OSe, n = 8), or an 1:1 blend of ISe and OSe (MIX, n = 8)1.
Treatment2 Item ISe MIX OSe SEM P value Bovine serum albumin, protein3 2329 2579 1825 344.3 0.28 TNALP, protein3 828a 2046b 1470ab 298.0 0.04 TNALP, mRNA4 1.05 0.85 0.98 0.1 0.37
136 1
Values are least squares means and pooled SEM. 2Means within a row that lack a common letter differ (P < 0.05). 3Values (arbitrary densitometric units) were determined by densitometric evaluation of Western blot data (Figure 5.6). 4Values are relative level of mRNA expression normalized to the geometric mean of three constitutively-expressed reference gens: Tyrosine 3- Monooxygenase/Tryptophan 5-Monooxygenase (YWHAZ), Hypoxanthine Phosphoribosyltransferase 1 (HPRT1), Peptidylprolyl Isomerase A (PPIA).
Table 5. 4 Partial correlation of serum clinical parameters with whole blood selenium concentration in growing beef steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as sodium selenite (ISe),
SEL-PLEX (OSe), or an 1:1 blend of ISe and OSe (MIX). (n = 6 for ISe, n = 8 for
OSe and MIX).
Partial Correlationa Item Coefficient P-value Prolactin -0.046 0.64 Blood urea nitrogen 0.38 < 0.01 Creatinine -0.443 < 0.01 Blood urea nitrogen/creatinine ratio 0.527 < 0.01 Glucose 0.209 0.03 Alkaline phosphatase 0.321 < 0.01 Creatine kinase -0.13 0.18 Aspartate aminotransferase -0.136 0.16 γ-Glutamyltransferase 0.026 0.79 Total protein 0.244 0.01 Albumin 0.226 0.02 Globulin 0.144 0.14 Albumin/globulin ratio -0.015 0.88 Sodium -0.121 0.22 Potassium -0.213 0.03 Chloride -0.17 0.08 Calcium 0.109 0.27 Phosphorus -0.006 0.95 Magnesium 0.246 0.01 aWhole blood Se vs. serum analytes, with accounting for the effect of time.
137
Figure 5. 1 Immunoblot validation of rabbit IgG anti-bovine serum albumin (BSA) polyclonal antibody conjugated to horse radish peroxidase detection (69.3 kDa) of bovine BSA1.
1Bovine steer liver homogenates (5 μg/lane) were hybridized with either rabbit IgG anti-BSA antibody (lanes 1, 2) or rabbit IgG anti-BSA antibody that had been pre- adsorbed (μg: μg) with its antigen polypeptide (at 1:0.002, 1:0.02, and 1:2; lanes 4, 5, 6, respectively) before hybridization and then detected, as described in Materials and Methods. Lane 3 is blank. The apparent migration weight (Mr) markers (kDa) and Mr of a single (69 kDa) immunoreactant are indicated to the left of the immunoblots.
138
Figure 5. 2 Immunoblot validation of rabbit IgG anti-bovine alkaline phosphatase
(tissue non-specific, liver/bone/kidney; TNALP)/donkey anti-rabbit IgG-horse radish peroxidase polyclonal antibody pair detection (21, 37, and 48 kDa) of bovine
TNALP1.
1Bovine steer liver homogenates (30 μg/lane) were hybridized with only secondary antibody (donkey anti-rabbit IgG-horse radish peroxidase polyclonal antibody) (lane 3) or either rabbit IgG anti-TNALP antibody (lane 1, 2) or rabbit IgG anti-TNALP antibody that had been pre-adsorbed (μg: μg) with its antigen polypeptide (at 1:5, 1:0.05, and 1:0.0005; lane 4, 5, 6, respectively) before hybridization and then detected with donkey anti-rabbit IgG-horse radish peroxidase, as described in Materials and Methods. The apparent migration weight (Mr) markers (kDa) and Mr of 3 TNALP-specific immunoreactants (21, 37, 48 kDa) are indicated to the left of the immunoblots.
139
Figure 5. 3 The sequences of the real-time RT-PCR products (5’ to 3’ orientation).
Within a sequence, underlined nucleotides indicate the position of forward and reverse primers.
HPRT1: GCCAGCCGGCTACGTTATGGCGGCCCGCAGCCCCAGCGTGGTGATTAGCGATGATGA ACCAGGTTATGACCTAAATTTATTTTGTATACCCAATCATTATGCTGAGGATTTGGAGAA GGTGTTTATTCCTCATGGACTAATTATGGACAGGACCGAACGGCTGGCTCGAGATGTGA TGAAGGAGATGGGTGGCCATCACATTGTGGCCCTCTGTGTGCTCAAGGGGGGCTATAA GTTCTTTGCCGACCTGTTGGAT
YWHAZ: TTGATCCCCAACGCTTCACAAGCAGAGAGCAAAGTCTTCTATTTGAAAATGAAGGAGACT ACTACCGCTACTTGGCTGAGGTTGCAGCTGGTGATGACAAGAAAGGGATTGTGGACCAGTC ACAGCAAGCATACCAAGAAGCTTTGAAATCAGCAAAAAGGAAATGCAACCAACACATCCT AT CAGACTGGGTCTGGCCCTTAACT
PPIA: GGCAAGTCCAATTATGGCGAGAAATTTGATGATGAGAATTTCATTTTGAAGCATACAGGTC CTGGCATCTTGTCCATGGCAAATGCTGGCCCCAACACAAATGGTTCCCAGTTTTTCATTTGC ACTGCCAAGACTGAGTGGTTGGATGGCAAGCACGTGGTCTTTGGCAAGGTGAAAGAGGGC AT GAATAT TGTGGAAGCCATGGAGCGCTTTGGGTCCAGGAATGGCAAGACCAGCAA
ALPL: ACATCGAGGTGATCATGGGCGGCGGCCGGAAGTACATGTTCCCCAAGAACAGAACCGAT GTGGAGTATGAGCTGGATGAGAAGGCCAGAGGCACGAGGCTGGACGGCCTGAACCTCATC GACATCTGGAAGAGCTTCAAACCGAAACACAAGCACTCTCACTATGTCTGGAACCGCACT GATCTCCTGGCCCTTGACCCCCACAGCGTGGACTACCTCTTGGGTCTCTTTGAGCCGGGGG ACATGCAGTACGAACTCAACAGGAACAATGCGACTGACCCTTCACTCTCTGAGATGGTAGA GATGGCCATCAGGATCCTGAACAAGAACCCCAAAGGCTTCTTCCTGCTGGTGGAAGGGGG CAGGATTG
140
Figure 5. 4 Serum alkaline phosphatase (A), albumin (B), and blood urea nitrogen (C)
concentrations in growing beef steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as sodium selenite (ISe),
SEL-PLEX (OSe), or an 1:1 blend of ISe and OSe (MIX)1.
141
1Data are the least squares means (n = 6 for ISe, n = 8 for OSe and MIX) ± SE. (A) Se form (P = 0.01), time (P < 0.01), and Se from by time interaction (P = 0.70). Nonorthogonal polynomial contrasts: ISe, linear (P = 0.05), quadratic (P = 0.20), cubic (P = 0.37), and quartic (P = 0.11) effects; OSe, linear (P = 0.95), quadratic (P = 0.23), cubic (P = 0.48), and quartic (P = 0.11) effects; MIX, linear (P = 0.07), quadratic (P = 0.56), cubic (P = 0.35), and quartic (P = 0.10) effects. (B) Se form (P = 0.03), time (P < 0.01), and Se form by time interaction (P < 0.01). Nonorthogonal polynomial contrasts: ISe, linear (P = 0.03), quadratic (P = 0.10), cubic (P = 0.47), and quartic (P = 0.88) effects; OSe, linear (P < 0.01), quadratic (P < 0.01), cubic (P = 0.75), and quartic (P = 0.27) effects; MIX, linear (P = 0.93), quadratic (P = 0.07), cubic (P = 0.08), and quartic (P = 0.80) effects. (C) Se form (P < 0.01), time (P < 0.01), and Se from by time interaction (P = 0.92). Nonorthogonal polynomial contrasts: ISe, linear (P < 0.01), quadratic (P = 0.02), cubic (P = 0.73), and quartic (P = 0.27) effects; OSe, linear (P < 0.01), quadratic (P = 0.02), cubic (P = 0.79), and quartic (P = 0.09) effects; MIX, linear (P < 0.01), quadratic (P = 0.01), cubic (P = 0.33), and quartic (P = 0.29) effects. Note that the y-axis for Panel B does not begin at 0.
142
Figure 5. 5 Serum sodium (D), phosphorus (E), and magnesium (F), concentrations in
growing beef steers grazing endophyte-infected tall fescue and supplemented with 3
mg Se/d in vitamin-mineral mixes as sodium selenite (ISe), SEL-PLEX (OSe), or an
1:1 blend of ISe and OSe (MIX)1.
143
1Data are the least squares means (n = 6 for ISe, n = 8 for OSe and MIX) ± SE. (D) Se form (P = 0.03), time (P < 0.01), and Se from by time interaction (P < 0.01). Nonorthogonal polynomial contrasts: ISe, linear (P = 0.04), quadratic (P = 0.12), cubic (P = 0.06), and quartic (P = 0.02) effects; OSe, linear (P = 0.65), quadratic (P ≤ 0.01), cubic (P = 0.97), and quartic (P < 0.01) effects; MIX, linear (P = 0.24), quadratic (P = 0.03), cubic (P = 0.64), and quartic (P < 0.01) effects. (E) Se form (P < 0.01), time (P < 0.01), and Se from by time interaction (P = 0.48). Nonorthogonal polynomial contrasts: ISe, linear (P = 0.15), quadratic (P = 0.08), cubic (P = 0.11), and quartic (P = 0.68) effects; OSe, linear (P < 0.01), quadratic (P = 0.36), cubic (P < 0.01), and quartic (P = 0.64) effects; MIX, linear (P = 0.31), quadratic (P = 0.74), cubic (P = 0.07), and quartic (P = 0.33) effects. (F) Se form (P = 0.02), time (P < 0.01), and Se from by time interaction (P < 0.01). Nonorthogonal polynomial contrasts: ISe, linear (P < 0.01), quadratic (P = 0.13), cubic (P = 0.11), and quartic (P < 0.01) effects; OSe, linear (P < 0.01), quadratic (P = 0.69), cubic (P = 0.08) effects; MIX, linear (P = 0.40), quadratic (P = 0.14), cubic (P = 0.07), and quartic (P = 0.17) effects. Note that the y-axis for Panels D and E does not begin at 0.
144
Figure 5. 6 Western blot analysis of alkaline phosphatase (tissue non-specific, liver/bone/kidney, TNALP), bovine serum albumin (BSA) content in liver homogenates (45 μg per lane for BSA, 30 μg per lane for TNALP) after slaughter of growing beef steers grazing endophyte-infected tall fescue and supplemental with 3 mg Se/d in vitamin-mineral mixes as sodium selenite (ISe), SEL-PLEX (OSe), or an
1:1 blend of ISe and OSe (MIX)1.
OSe MIX ISe OSe MIX ISe
TNALP
BSA
1Western blot data (n = 2) are representative of six ISe, eight OSe, and eight MIX steers (as described in Table 5.3). The apparent migration weights (kDa) of the lower, middle, and upper immunoreactants for TNALP were 21, 37, and 48, respectively. The apparent migration weights (kDa) for the immunoreactants for BSA was 69.
145
CHAPTER 6. Gene expression profiling indicates a shift in ammonia assimilation capacity along hepatic acinus induced by different forms of selenium in vitamin- mineral mixes fed to steers grazing endophyte-infected tall fescue
6.1 Abstract
Endophyte-infected tall fescue-based beef cattle operations are often challenged by both fescue toxicosis and selenium deficiency due to insufficient Se from forage. A summer-long grazing with in-pasture Calan gate model was established to test the effect of sodium selenite (ISe), SEL-PLEX(OSe), vs. an 1:1 blend (MIX) of ISe and OSe in a basal vitamin-mineral on metabolic parameters and performance of growing steers grazing endophyte-infected tall fescue mixed forage pasture. Predominately-Angus steers (BW = 183 ± 34 kg) were randomly selected from herds of fall-calving cows grazing endophyte-infected tall fescue pasture and consuming vitamin-mineral mixes that contained 35 ppm Se as ISe, OSe, and MIX forms. Steers were weaned, depleted of Se for 98 d, and subjected to summer-long common grazing of an endophyte-infected tall fescue pasture (0.51 ppm total ergovaline/ergovalinine; 10.1 ha). Steers were assigned (n = 8/treatment) to the same Se-form treatments upon which they were raised.
Se treatments were administered by daily top-dressing 85 g of vitamin-mineral mix onto 0.23 kg soyhulls, using in-pasture Calan gates. Several serum analytes that are classically decreased with fescue toxicosis were found higher in MIX and/or OSe steers than ISe steers. After slaughter, MIX and OSe steers had greater the hepatic glutamine synthetase mRNA and activity than ISe steers. To gain a greater perspective of forms
146
of Se induced changes in hepatic metabolism and identify potential regulatory
connections with observed serological changes, the first goal of the current research was to conduct a transcriptome analysis of the same hepatic tissue sample. The second goal was to investigate the expression changes of key enzymes and transporters
involved in hepatic glutamine/glutamate, ammonia, and proline metabolism using
targeted RT-PCR and immunoblot analyses. Microarray analysis indicated that a total
of 738 gene transcripts were differentially expressed, of which 573 were annotated (P
< 0.01, false discovery rate of < 34%). Bioinformatic analysis revealed that canonical
pathways central to glutamine biosynthesis/degradation, glutamate
biosynthesis/degradation, and proline biosynthesis. Targeted RT-PCR and immunoblot
analyses corroborated these findings and collectively indicated that, compared to ISe,
MIX and OSe steers displayed a decreased periportal ammonia assimilation and urea-
synthesizing capacity, as evident by the decreased expression of glutaminase 2 and key
enzymes (N-acetylglutamate synthase, ornithine carbamoyltransferase, and arginase 1)
and transporter (ornithine mitochondria transporter). Interestingly, MIX and OSe steers
showed an elevated pericentral ammonia assimilation capacity, as supported by the up
regulations of GS activity and ammonia transporter. Moreover, the increased
(microarray data) glutamine dehydrogenase and decreased (microarray and RT-PCR)
arginase 2 and ornithine aminotransferase expression indicates that MIX and OSe steers
had a greater capacity to make glutamate in pericentral hepatocytes from α-
ketoglutarate, and not from arginine and/or ornithine, to meet the glutamate demand
from increased GS activity. The enzymes involved in proline metabolism also were
147
differentially affected by forms of Se supplementation and, more specifically, indicated
an increased proline-synthesizing capacity in the liver of OSe steers, and an elevated pyrolline-5-carboxylate-synthesizing capacity in MIX steers. In summary, these data suggest that supplementing MIX and OSe vs. ISe form of Se in vitamin-mineral mixes induces a capacity shift from periportal hepatocyte incorporation of ammonia into urea to pericentral incorporation into glutamine in steers grazing endophyte-infected tall fescue pasture.
KEYWORDS: steer, selenium supplementation, ammonia, urea cycle, proline
148
6.2 Introduction
Grazing-based beef cattle operations in the transition zone of the eastern and central part of the United States are economically challenged by the negative impacts of fescue toxicosis, which is a comprehensive syndrome caused by animal consumption of ergot alkaloids produced in endophyte-infected tall fescue (Strickland et al., 2009b; Strickland et al., 2011). Multiple studies have been conducted to characterize the effect of fescue toxicosis induced by consuming endophyte-infected tall fescue seeds on hepatic transcriptome profiles using mice (Bhusari et al., 2006), rats (Settivari et al., 2006), and steers (Tanaree et al., 2013). A more commercially relevant model was used to investigate the effect of fescue toxicosis on liver metabolism and function on steers subjected to a summer-long grazing of low (LE) vs. high (HE) endophyte-infected tall fescue (Brown et al., 2009). Hepatic transcriptome profile of these steers was later evaluated and revealed 374 differentially expressed genes (P < 0.01) functionally involved carbohydrate
(gluconeogenesis) and amino acid (proline and serine) metabolism, cell-mediated immune response, and glucocorticoid receptor signaling network (Liao et al., 2015).
Selenium (Se) supplementation typically is necessary for the endophyte-infected tall fescue-based beef cattle operations due to the inadequate level of Se in the forages resulting from Se-poor soils (Ammerman and Miller, 1975). Comparing to inorganic form of Se (ISe, sodium selenite), organic form of Se (OSe, selenium-enriched yeast,
SEL-PLEX) shows greater bioavailability in cattle, as evident by the greater blood
149
and tissue Se concentrations (Nicholson et al., 1991; Gunter et al., 2003; Liao et al.,
2011). Our lab has previously shown that supplementing Se at 3 mg/day as a 1:1 blend of ISe:OSe (MIX) results in equal amount of Se in whole blood, RBC, serum, and liver of heifers as when supplemented with OSe, both of which are greater than
ISe supplemented heifers (Brennan et al., 2011). Moreover, microarray analysis indicated that MIX stimulates gene expressions involved in selenoprotein synthesis and glutamate/glutamine metabolism (Matthews et al., 2014). Serendipitously, some of the genes upregulated by MIX were found downregulated in the liver (Liao et al.,
2015) and pituitary (Li et al., 2017) of steers grazing high vs. low endophyte-infected forages.
Subsequently, a grazing with in-pasture calan gate model was established (Jia et al., 2018) to evaluate the effects of forms (ISe, OSe, and MIX) of supplemental Se on physiological parameters of growing steers subjected to summer-long (86 days) grazing of endophyte-infected tall fescue pasture. At slaughter, hepatic glutamine synthetase activity and expression were affected by forms of Se (Jia et al., 2018).
Specifically, MIX and OSe steers had more hepatic glutamine synthetase (GS) activity and mRNA expression than ISe steers. Similarly, more hepatic GS protein content was found in MIX steers than ISe and OSe steers. Given the critical roles of hepatic GS in pericentral ammonia assimilation and glutamate/glutamine metabolism, it is reasonable to expect an altered hepatic ammonia and glutamate/glutamine metabolism
(Jia et al., 2018).
To elaborate and extend these findings, the first goal of present experiment was
150
to conduct a transcriptome analysis of the same hepatic tissue (Jia et al., 2018) to gain
a greater perspective into other potentially altered hepatic metabolic pathways. The
second goal was to conduct targeted RT-PCR and western-blotting analyses to
investigate the expression of key enzymes and transporters involved in hepatic
glutamine/glutamate metabolism, ammonia assimilation, and proline metabolism.
6.3 Materials and Methods
All experimental procedures were approved by the University of Kentucky
Institutional Animal Care and Use Committee.
6.3.1 Animals, Slaughter and Tissue Collection
Specific descriptions of the animal model, treatment administration, liver sample
collection procedures used have been described (Jia et al., 2018). However, briefly,
twenty-four suckling predominantly Angus beef steers (BW: 182.6 ± 33.9 kg, age:
165.5 ± 14.2 day) were randomly selected (n=8) from herds of fall-calving cows grazing toxic endophyte-infected tall fescue mixed forage pastures and consuming
vitamin-mineral mixes that contained 35 mg/kg Se as ISe (sodium selenite, Prince Se
concentrate; Prince Agri Products, Inc., Quincy, IL), OSe (SEL-PLEX, Alltech Inc.,
Nicholasville, KY), or an 1:1 blend of ISe : OSe (MIX) forms. Over a 98-d period
(March 11 to June 17, 2015), steers were weaned, commonly depleted of Se, and 151
trained to consume vitamin-mineral mix from in-pasture Calan gates. During this pretrial Se-depletion period, the ADG of steers was 0.82 ± 0.18 kg/d.
Steers then began (day 0) an 86-d (June 17 to September 9, 2015) period in which they commonly grazed a predominately endophyte-infected tall fescue-mixed
pasture (10.1 ha) and individually consumed their respective Se-form-specific
vitamin-mineral mix treatments, through the use of in-pasture Calan gates. The Se- specific mixes contained the basal mix plus 35 mg/kg Se as ISe, OSe, or MIX. The composition of the basal vitamin-mineral mix was analyzed by Dairy One (Dairy One
Cooperative, Inc., Ithaca, NY) and previously described (Jia et al., 2018). To ensure individual consumption of 3 mg Se/d·steer, 85 g of the specific vitamin-mineral mix
(35 mg/kg Se) was top-dressed onto 227 g of soyhulls in each individual Calan gate feeder. The consumption of the mixture of soyhulls/vitamin-mineral mix was monitored daily, and all steers consumed all of the mixture every day. Thus, every steer consumed 3 mg of supplemental Se/d. During this 86-d period, two ISe steers were removed from the trial due to a bad hoof and failure to consume their mineral treatment. Thus, the final number of experimental observations was as follows: ISe =
6, and OSe and MIX = 8.
Steers were slaughtered over a 26-d period, from day 93 to 119 (September 17 to
October 13, 2015) of the study. Specifically, one OSe and one MIX steer were killed on the first two slaughter d. On the remaining six slaughter d, one steer each from ISe,
OSe, and MIX treatment groups were killed. The slaughter process again has been
described in detail in previous model paper (Jia et al., 2018). Liver samples were
152
collected from the mid-lower right lobe and placed in foil packs, snap-frozen in liquid
nitrogen, and stored at −80 °C for microarray and real-time RT-PCR analyses.
6.3.2 Immunoblot Analysis
All immunoblot and densitometric analyses for the relative expression of
targeted proteins were performed using a standard protocol of our lab as previously
described (Miles et al., 2015). Approximately 0.2 g of liver was homogenized on ice for 30 s (setting 11, Polytron Model PT10/35, Kinematic Inc., Lucerne, Switzerland) in 7.5 mL of 4 °C sample extraction buffer solution (0.25 mM sucrose, 10 mM
HEPES-KOH pH 7.5, 1 mM EDTA, and 50 μL of protease inhibitor [Sigma]). Protein was quantified by a modified Lowry assay, using bovine serum albumin as a standard
(Kilberg, 1989). Proteins were separated using 12% SDS-PAGE and
electrotransferred onto a 0.45 μm nitrocellulose membrane (Bio-Rad) and then stained
with Fast-Green (Fisher, Pittsburgh, PA). The relative amount of stained protein per
lane per sample was determined by densitometric analysis and recorded as arbitrary
units (Brown et al., 2009)
The use of rabbit IgG anti-bovine ornithine aminotransferase (OAT) polyclonal
antibody was validated by pre-adsorption of primary antibodies with their antigen
polypeptides, using the general procedures of Xue et al. (2011). Immunoreaction
product for OAT (Mr = 62 kDa, Figure 6.1) in liver homogenates (45μg) was
abolished if pre-adsorbed (μg : μg) with increasing amounts of their antigens, thus
153
validating their use. The relative content of excitatory AA carrier/SLC1A1 (EAAC1),
SLC1A2 (GLT-1), glutamate transporter-associated protein 3-18 (GTRAP3-18), ADP- ribosylation factor-like 6 interacting protein 1 (ARL6IP1) in liver homogenate was evaluated using an antibody as previously described (Miles et al., 2015; Huang et al.,
2018). Briefly, blots were hybridized with 0.7 μg of IgG anti-rabbit OAT polyclonal antibody (Novus Biologicals, Littleton, CO), 1 μg of IgG anti-human EAAC1 polyclonal antibody (Santa Cruze Biotechnology, Inc., Santa Cruze, CA), 1 μg of IgG anti-rabbit GLT-1 polyclonal antibody (Abcam Inc., Cambridge, MA), 4 μg of IgG anti-human GTRAP3-18 (Abcam Inc., Cambridge, MA), and 5 μg of IgG anti-human
ARL6IP1 (Novus Biologicals, Littleton, CO), respectively, per mL of blocking solution (3% nonfat dry milk [wt/vol], 10 mM Tris-Cl [pH 7.5], 100 mM NaCl, 0.1%
Tween 20 [vol/vol]) for 1 h at room temperature with gentle rocking. Protein-primary antibody binding reactions were visualized with a chemiluminescence kit (Pierce,
Rockford, IL) after hybridization of primary antibody with horseradish peroxidase- conjugated donkey anti-rabbit IgG (Amersham, Arlington Heights, IL; EAAC1, OAT, and ARL6IP1 1:5,000; GLT-1, 1:2,500;); horseradish peroxidase-conjugated donkey anti-goat IgG (Santa Cruz Biotechnology, Inc., Santa Cruz, CA; GTRAP3-18,
1:5,000).
Densitometric analysis of immunoreactive products was performed as described previously (Miles et al., 2015). After exposure of auto-radiographic film (Amersham,
Arlington Heights, IL), digital images of all observed immunoreactive species were recorded and quantified as described (Dehnes et al., 1998). Apparent migration
154
weights (Mr) were calculated by regression of the distance migrated against the Mr of
a 16 to 185 kDa standard (Gibco BRL, Grand Island, NY) using the Versadoc imaging
system (Bio-Rad) and Quantity One software (Version 4.2.3, Bio-Rad). Band
intensities of all observed immunoreactive species within a sample were quantified by
densitometry (as described above for Fast-Green stained proteins) and reported as arbitrary units. Densitometric data were corrected for unequal (15%, ARL6IP1; 12%,
EAAC1; 11%, GTRAP3-18; 17%, GLT-1; 22%, OAT) loading, transfer, or both, and amount of detected protein normalized to relative amounts of Fast-Green-stained proteins common to all immunoblot lanes/samples (Miles et al., 2015). Digital images were prepared using PowerPoint software (Microsoft, PowerPoint 2013, Bellevue,
MA).
6.3.3 Hepatic RNA Extraction and Analysis
For each animal, total RNA was extracted from 300 mg of frozen liver tissue using TRIzol Reagent (Invitrogen Corporation, Carlsbad, CA) following the manufacturer’s instructions. The purity and concentration of total RNA samples was analyzed using a NanoDrop ND-100 Spectrophotometer (NanaDrop Technologies,
Wilmington, DE, USA). All samples had an average concentration of 1.05 μg/μL and a high purity with 260/280 absorbance ratios of 1.98-2.03 and 260/230 absorbance ratios ranging from 1.89 to 2.18. The integrity of total RNA was examined by gel
155
electrophoresis using an Agilent 2100 Bioanalyzer System (Agilent Technologies,
Santa Clara, CA) at the University of Kentucky Microarray Core Facility.
Visualization of gel images and electropherograms showed that all RNA samples were
of high quality with RNA integrity numbers (RIN) being greater than 8.7 and 28S/18S
rRNA absorbance ratios greater than 2.
6.3.4 Microarray Analysis
The effect of Se form on steer hepatic transcriptome profile was evaluated using
Bovine Gene 1.0 ST Arrays (GeneChip; Affymetrix, Inc., Santa Clara, CA), and
conducted according to the manufacturer’s standard protocol at the University of
Kentucky Microarray Core Facility. Briefly, 3 μg of RNA for each sample was first
reverse-transcribed to cDNA and then from cDNA (double-stranded) to complementary RNA (cRNA; single-stranded), which was then labeled with biotin.
The biotinylated cRNAs were further fragmented and used as probes to hybridize the gene chips in the GeneChip Hybridization Oven 640 (Affymetrix), using 1 chip per
RNA sample. After hybridization, the chips were washed and stained on a GeneChip
Fluidics Station 450 (Affymetrix). The reaction image and signals were read with a
GeneChip Scanner (GCS 3000, 7G; Affymetrix), and data were collected using the
GeneChip Operating Software (GCOS, version 1.2; Affymetrix). Due to the degradation of a RNA sample, the experimental observations for each treatment were:
156
n = 6, 7, and 8 for ISe, MIX, and OSe treatments, respectively.
The raw expression intensity values from the GCOS (i.e., 21 *.cel files from the
raw methylation measurements) were imported into Partek Genomics Suite software
(PGS, version 6.6; Partek Inc., St. Louis, MO). For GeneChip background correction, the algorithm of Robust Multichip Averaging adjusted with probe length and GC oligo contents was implemented (Irizarry et al., 2003; Wu et al., 2004). The background- corrected data were further converted into expression values using quantile normalization across all the chips and median polish summarization of multiple probes for each probe set.
All the GeneChip transcripts were annotated using the NetAffx annotation database for Gene Expression on Bovine GeneChip Array ST 1.0, provided by the manufacturer (http://www.affymetrix.com/analysis/index.affx, last accessed in April
2018, annotation file last updated in March 2016). Quality control of the microarray hybridization and data presentation was performed by MA plot on all the gene expression values and by box plot on the control probe sets on the Affymetrix chips.
Pearson (linear) Correlation generated the similarity matrix (last accessed in April
2018, Partek Genomics Suite 6.6 6.15.0422). The average correlation between any pair of the 21 GeneChips was 0.96 (Figure 6.2), and all GeneChips were further analyzed. Principal component analysis (Figure 6.3) was performed to elucidate the quality of the microarray hybridization and visualize the general data variation among the chips (Partek, 2015).
To exclude the meaningless and unnecessary gene probes in the analysis and
157
reduce the multiple comparison errors (expected false positives), total gene probe sets
(26,773 gene transcripts) were reduced using a multistep filtering algorithm with some modifications (Blalock et al., 2003) (Figure 6.4a). Briefly, first, to remove gene transcript that was not expressed from subsequent analyses, gene transcripts that had a signal intensity less than 3.6 in every gene chip were removed. This signal intensity cutoff was determined based on the signal intensity histogram, which showed a clear plateau before 3.6 (Figure 6.4b). Consequently, 25,767 gene transcripts were deemed as expressed. Second, the multiple gene probe sets designed for one gene transcript were sorted by signal intensity, then the gene probe set with highest signal intensity was considered more representative and then kept (24,947 gene transcripts) for further analysis. To assess treatment effects on the relative expression of the hepatic gene transcripts, qualified microarray data were subjected to one-way ANOVA using the same PGS software. All the gene chip transcripts were annotated using the NetAffx annotation database for Gene Expression on Bovine GeneChip Array ST 1.0, provided by the manufacturer (http://www.affymetrix.com/analysis/index.affx, last accessed in
April 2018, annotation file last updated in March 2016). A total of 738 transcripts showing treatment effects at the significance level of P < 0.01 with false discovery rate (FDR) of < 33%. These differentially expressed genes/gene transcripts (DEGs) were subjected to hierarchical clustering analysis (Figure 6.5) using PGS software.
After annotation, at P < 0.01, a total of 573 out of 738 DEGs were found to be annotated (Table 6.1) and submitted (Figure 6.4) to canonical, functional, and network pathway analyses using the Core Analysis program of Ingenuity Pathway Analysis
158
online software (IPA, Build version 481437M, Content version 44691306;
http://www.ingenuity.com [accessed in September, 2018]; Ingenuity Systems, Inc.,
Redwood City, CA).
All the microarray*.cel files collected by GCOS plus the GC Robust Multichip
Averaging corrected data processed by PGS software of this manuscript have been deposited in the National Center for Biotechnology Information's Gene Expression
Omnibus (GEO; http://www.ncbi.nlm.nih.gov/geo/) [released July 13, 2018]), are
minimum information about a microarray experiment (MIAME) compliant, and are
accessible through GEO series accession number GSE115802.
6.3.5 Real-time RT-PCR Analysis
The quantification of relative mRNA for genes of interest was performed using
standard procedures in our laboratory, as previously described (Cerny et al., 2016).
Briefly, 1 µg of each steer’s liver RNA was reverse-transcribed to cDNA using the
SuperScript III 1st Strand Synthesis System (Invitrogen). Real-time RT-PCR was performed using an Eppendorf Mastercycler ep realplex2 system (Eppendorf,
Hamburg, Germany) with iQ SYBR Green Supermix (Bio-RAD, Hercules, CA). A
total volume of 25 µL was used in each real-time RT-PCR reaction containing 5 µL of
cDNA, 1 µL of a 10 µM stock of each primer (forward and reverse), 12.5 µL of 2 ×
SYBR Green PCR Master Mix, and 5.5 µL of nuclease-free water. The relative
159
amount of each transcript was calculated using the 2-ΔΔCT method (Livak and
Schmittgen, 2001). Primer sets (Table 6.2) for genes of interest were designed and obtained from NCBI Primer-BLAST tool (https://www.ncbi.nlm.nih.gov/tools/primer- blast/) against RefSeq sequence (accessed February to April, 2018).
All real-time RT-PCR cDNA products were validated by DNA sequencing verification and were 97% to 100% identical with their RefSeq sequences (Table 6.2).
Briefly, the PCR-amplified cDNA products were electrophoresed in a 1.2% agarose
(UltraPureTM Agarose, Invitrogen, Carlsbad, CA) slab gel. A single cDNA band at the desired size was identified under a UV light, excised from the gel, purified using the
PureLink Quick Gel Extraction Kit (Invitrogen, Carlsbad, CA), then sequenced by
Eurofins Genomics (Eurofins MWG Operon LLC, Louisville, KY). The resulting
sequences (Figure 6.6) were compared to the NCBI RefSeq mRNA sequences used as
templates for primer pair set design. From 9 constitutively expressed gene candidates
(ACTB, GAPDH, SDHA, PCK2, UBC, YWHAZ, HPRT1, PPIA,TBP) three constitutively expressed genes (YWHAZ, HPRT1, PPIA) were selected with the lowest average stability value of M = 0.19, calculated using the geNorm software v3.5
(Vandesompele et al., 2002). The relative mRNA expression was normalized to the geometric means of three constitutively expressed genes. For the RT-PCR analysis, n
= 6, 8, and 8 samples were used for ISe, OSe, and MIX treatments, respectively. All
RT-PCR reactions were performed in triplicate.
160
6.3.6 Statistical Analysis
Data are presented as least square means (±SEM). Steers were the experimental
units. Microarray hybridization data (relative expression of hepatic gene transcripts) data
were subjected on ono-way ANOVA using the PGS software as described in the “Microarray
Analysis” section above. After slaughter, the effect of Se supplementation on the
relative abundance of hepatic mRNA (RT-PCR) and protein (Western blotting) was
assessed by ANOVA, using the PROC GLM procedure of SAS. Fisher’s protected
LSD procedure was used to separate treatment means.
6.4 Results
6.4.1 Differentially Expressed Genes
Principal component analysis of all microarray data was performed to evaluate
the correlation and variation among the gene chips. The score plot (Figure 6.3)
showed the first principal component (PC #1, x-axis) explained 7.9% of the total variance, whereas PC #2 (y-axis) and PC #3 (z-axis) explained 7.35% and 6.77% of the variance, respectively. Overall, the score plot indicated that the chips within each treatment group were clustered closely together.
Individual ANOVA were conducted to identify altered expression of RNA transcripts in the livers of ISe, OSe, and MIX steers. At the P < 0.01 and a false discovery rate of < 34%, a total of 738 gene transcripts were identified, of which 573
161
were annotated (P < 0.01, FDR < 33%; Table 6.1). Hierarchical clustering analysis of the 738 DEGs indicated a clear separation among Se treatment groups (Figure 6.5) with OSe and MIX generally displaying similar, but different, patterns of from ISe.
6.4.2 Pathways and Gene Network Analysis
To determine the physiological significance of Se treatment-induced DEG (Table
6.1), bioinformatics analysis of canonical, functional, and network pathway analyses were performed. Canonical pathway analysis (Table 6.3) indicated that the top 6 pathways were HER-2 signaling in breast cancer (10 genes), tyrosine degradation I (3 genes), PEDF signaling (9 genes), sumoylation pathway (9 genes), LPS-stimulated
MAPK signaling (9 genes), and induction of apoptosis by HIV I (7 genes).
Additionally, several affected pathways closely involved in glutamate/glutamine and nitrogen metabolism were identified (Table 6.4), including glutamine biosynthesis I, glutamine degradation I, glutamate biosynthesis II, glutamate degradation X, arginine biosynthesis IV, and proline biosynthesis II (from arginine).
6.4.3 Real-time RT-PCR Analysis of Genes Selected mRNA
To corroborate the altered expression of the critical proteins involved in glutamate/glutamine, proline, and asparagine metabolism, and urea cycle indicated by
Jia et al. (2018) or current microarray analysis, hepatic expression of these genes by
ISe, OSe, vs. MIX steers was compared by real-time RT-PCR analysis (Table 6.5).
162
With the exception of glutamate dehydrogenase 1 (GLUD1), glutaminase 1 (GLS1),
proline dehydrogenase 1 (PRODH), pyrroline-5-carboxylate synthetase
(ALDH18A1), Carbamoyl phosphate synthetase 1 (CPS1), SLC38A2 (SNAT2),
SLC42A2 (RHBG) and glucocorticoid receptor (NR3C1), the ANOVA P-values for
Se treatment effect were consistent between the microarray and RT-PCR analyses.
However, in GLUD1, PRODH, RHBG, and ALDH18A1, the trend of numeric values
of the two analyses was consistent. In genes directly responsible for
glutamate/glutamine metabolism, both analyses revealed that the expression of
glutamine synthetase (GLUL) mRNA was increased (P < 0.05) in MIX and OSe than
ISe steers. In contrast, the expression of glutaminase 2 (GLS2) mRNA was decreased
(P < 0.05) in MIX and OSe steers.
Within genes involved in proline metabolism, both analyses showed that the
expression of pyrroline-5-carboxylate reductase 2 (PYCR2) and pyrroline-5-
carboxylate dehydrogenase (ALDH4A1) was not affected by Se treatments. However,
compared to ISe steers, the expression of pyrroline-5-carboxylate reductase 1
(PYCR1) mRNA was upregulated (P < 0.05) in OSe steers, but not (P > 0.1) in MIX steers. From the RT-PCR results, hepatic NR3C1 expression was affected (P = 0.04) by forms of Se, and decreased in MIX and OSe steers than ISe steers.
A high congruency between microarray and RT-PCR analyses was observed in genes involved in the urea cycle (Table 6.5). Specifically, the expression of arginase 1
(ARG1), arginase 2 (ARG2), OAT, N-acetylglutamate synthase (NAGS), ornithine carbamoyltransferase (OCT), and ornithine/arginine exchanger (ORNT1) were
163
decreased (P < 0.05) in MIX and OSe steers.
6.4.4 Hepatic Content of OAT and System Transporters and Regulatory − Proteins 𝑿𝑿𝑨𝑨𝑨𝑨
To further explore the glutamate metabolism by evaluating the capacity of
glutamate transport, the relative hepatic content of high-affinity glutamate transporters
(EAAC1, GLT-1) and their regulatory proteins (GTRAP3-18, ARL6IP1) was assessed by Western blot (Figure 6.7) and densitometric analysis (Table 6.6). Similar to the mRNA expression (Table 6.5), OAT protein content was decreased (P < 0.05) in OSe steers vs. MIX and ISe steers. Forms of Se did not (P ≥ 0.24) affect the EAAC1 and
GLT-1 protein content, which are responsible for pericentral uptake of glutamate. The protein content of GTRAP3-18 and ARL6IP1, regulators of EAAC1 and GLT-1 abundance and activity, were not affected (P ≥ 0.88) by Se form treatments.
6.5 Discussion
6.5.1 Animal Model
To evaluate the effect of forms of supplemental Se (ISe, OSe, vs. MIX) on physiological parameters of steers grazing endophyte-infected tall fescue, an animal model has been successfully established and described previously (Jia et al., 2018).
Briefly, steers were subjected to summer-long common grazing of tall fescue-mixed pasture, while individually consuming 3 mg/d of their respective Se from initiation of 164
the grazing period until their slaughter (up to 113d). The ergot alkaloid (ergovaline
plus ergovalinine) content averaged 0.51 ppm throughout the summer, and the ISe
treatment steers displayed depressed serum prolactin (Jia et al., 2018), alkaline
phosphatase (Chapter 5), and albumin (Chapter 5) at levels characteristic of fescue
toxicosis (Jia et al., 2018). The rapid increase then differentially stabilized
concentration of whole blood Se in all three Se treatment groups was consistent with our previous Se depletion/repletion regimens with growing cattle (Brennan et al.,
2011; Liao et al., 2011), thereby indicating successful administration of ISe, OSe, and
MIX forms of supplemental Se. In addition, it is reported (Jia et al., 2018) that hepatic glutamine synthetase (GS) mRNA content and activity were increased (P < 0.05) in
MIX and OSe steers vs. ISe steers. This increased GS activity was of especial interest from a glutamate/glutamine carbon and nitrogen metabolism perspective. In ruminants, a substantial amount of dietary nitrogen is absorbed as ammonia, accounting up to 73% of nitrogen intake (Huntington and Archibeque, 2000). Like non-ruminants, liver is the organ in ruminants that detoxifies the ammonia from portal blood by primarily converting it into urea. In addition, The hepatic nitrogen metabolism is critically important for ruminants, because there is a constant demand for amino acid-derived carbon moieties to support hepatic gluconeogenesis
(Reynolds, 1992). Thus, the overall goal of the present study was to evaluate the effect of forms of supplemental Se (ISe, OSe, vs. MIX) on targeted mRNA expressions of critical enzymes involved in glutamate/glutamine and nitrogen metabolism, and on hepatic transcriptome profiles of steers grazing endophyte-
165
infected tall fescue-mixed pasture.
To investigate the potential reason for increased GS activity (Jia et al., 2018) and to assess potential shifts in the capacity of the associated glutamate/glutamine and urea nitrogen metabolism, a group of critical enzymes and transporters to these processes was identified (Figure 6.8) and expression of their genes evaluated (Table
6.5). In mouse and rat liver, the activities of critical enzymes and transporters responsible for a plethora of metabolic pathways have been found to be heterogeneously expressed along the hepatic acinus. Collectively, this metabolic zonation between periportal and pericentral hepatocytes gives rise to the separation of urea (periportal) and glutamine (pericentral) metabolism (Jungermann and Sasse,
1978; Gebhardt, 1992) (Figure 6.8). Briefly, from a glutamate/glutamine and ammonia metabolism perspective, glutamine and ammonia from portal blood are absorbed and metabolized for urea synthesis in periportal hepatocytes, whereas glutamate and excess ammonia are taken up by pericentral hepatocytes, and used as substrates (catalyzed by GS) for glutamine synthesis. It should be noted that it remains unclear if ruminant liver displays this metabolic zonation. Nevertheless, it has been reported that sheep liver exhibits a simultaneous release and removal of glutamine, as evidenced by the observation of net liver removal of glutamine was 2.6 times lower than unidirectional removal (Bergman and Heitmann, 1978). This was interpreted by Reynolds (1992) as potentially indicative of liver heterogeneity in sheep. Therefore, the differential hepatic acinar localization of these enzymes and transporters in steer liver are assumed similar with their counterparts in mouse/rat
166
liver.
6.5.2 Hepatic Capacities of Sinusoidal Ammonia Assimilation Are Shifted in MIX
and OSe vs. ISe Steers.
As shown in Figure 6.8, GLS2 (mitochondrial glutaminase) is predominantly
expressed in the population of periportal hepatocytes of rats (Häussinger, 1990b;
Moorman et al., 1994). Periportal-specific GLS2 deaminates the portal origin
glutamine (Curthoys and Watford, 1995) imported by the hepatic SNAT2 (SLC38A2)
(Kondou et al., 2013; Broer, 2014), SNAT3 (SLC38A3) and/or SNAT5 (SLC38A5)
(Schioth et al., 2013) activity. The GLS2-derived ammonia is then used for urea synthesis catalyzed by urea cycle enzymes co-localized in periportal hepatocytes
(Meijer et al., 1990; Häussinger et al., 1992). In the current study, the microarray
results indicated that hepatic SNAT2 mRNA expression tended (P = 0.08) to be higher
in MIX and OSe vs ISe steers. However, this was not confirmed by RT-PCR results, where no difference (P = 0.364) was found in hepatic SNAT2 mRNA expression among Se treatments. In addition, the microarray results indicate that both SNAT3 and
SNAT5 mRNA expression are not significantly affected by forms of Se (P ≥ 0.1), but
a 44-fold greater signal intensity of SNAT3 than SNAT5 may suggest a more
significant functional role of SNAT3 in cattle hepatic glutamine uptake. Therefore,
from a transporter perspective, the uptake capacity of periportal glutamine may not be
different among Se treatments. However, a downregulation of GLS2 mRNA
expression (both microarray and RT-PCR results) in livers of MIX and OSe steers 167
may indicate a decreased glutamine deamination capacity in periportal hepatocytes of
MIX and OSe vs. ISe steers. Rat liver metabolic studies using radio isotopes have
reported that up to 13% of ammonia used in urea synthesis are from portal glutamine
(by GLS2 activity) (Cooper et al., 1988; Meijer et al., 1990). A priori, the ammonia
available in periportal hepatocytes for urea synthesis may be decreased.
Concomitantly, the mRNA expression (both microarray and RT-PCR) of key urea
cycle enzymes were decreased in liver of MIX and OSe vs. ISe steers, including OCT,
NAGS, ARG1, and ARG2 (Table 6.5). Catalyzing the initial, committed step of the
urea cycle, carbamoyl phosphate synthetase (CPS1) mRNA expression (RT-PCR
results) were decreased in liver of MIX and OSe vs ISe steers, despite no significant
difference was observed from Microarray results. Although being the rate-limiting
enzyme of the urea cycle, CPS1 has an absolute requirement for its allosteric activator
(Meijer et al., 1990), N-acetyl-glutamate, which is synthesized within mitochondria
by NAGS (Morris, 2002). Therefore, a downregulated NAGS mRNA in livers of MIX
and OSe steers may indicate a less activation of CPS1, which could be interpreted as
less ammonia being committed to periportal urea cycle in livers of MIX and OSe vs.
ISe steer. Moreover, the availability of mitochondrial ornithine is considered another
controlling factor of urea synthesis (Meijer et al., 1990). A shuttle of ornithine and
citrulline across mitochondrial wall is essential for the continuation of the urea cycle.
This is achieved principally by the anti-porter of ornithine and citrulline,
mitochondrial ORNT1 (Palmieri, 2013) (Figure 6.8). But, it is unclear if ORNT1 represents the sole transporter of ornithine and citrulline across the mitochondrial
168
membrane (Morris, 2002). The decreased mRNA expression of ORNT1 (both
microarray and RT-PCR) in MIX and OSe vs. ISe steers seems to reflect a decreased
capacity of exchanging citrulline and ornithine across the mitochondrial membrane,
which may limit the substrate availability for the urea (really ornithine) cycle in livers
of MIX and OSe steers. The urea-producing step of the urea cycle in the periportal
hepatocytes is catalyzed by arginase activity. Arginase has two distinct isoenzymes,
ARG1 (liver type) and ARG2 (kidney type), which are encoded by two different
genes (Jenkinson et al., 1996). ARG1 (liver type) is highly expressed in liver as a
critical part of the urea cycle. Again, in the current study, the ARG1 mRNA expression (both microarray and RT-PCR) in livers of MIX and OSe steers was decreased vs. ISe steers. Thus, this finding indicates a decreased urea production capacity from the periportal zone of livers from MIX and OSe steers. From a transcriptional regulation perspective, the simultaneous downregulation of key enzymes (NAGS, OCT, and ARG1) and transporters (ORNT1) in urea cycle seems to agree with the literature that genes for the urea cycle enzymes are usually regulated in a co-ordinated manner (Takiguchi and Mori, 1995). The abundance of ORNT1 mRNA
(Northern blot analysis) increased in livers of mice fed a high-protein diet (Camacho
et al., 1999). Various studies have demonstrated that the activities of the urea cycle
enzymes are elevated in response to starvation and high-protein diets and reduced in
response to low-protein or protein-free diets (Freedland, 1964; Christowitz et al.,
1981). Similar to the response of ORNT1 mRNA, upregulation of urea enzymes
(carbamoyl phosphatase synthetase, ornithine carbamoyltransferase, and arginase)
169
mRNA were also observed in liver of rat after a high-protein diet (Morris et al., 1987).
Moreover, ORNT1 mRNA is significantly induced by cyclic AMP and dexamethasone in cultured rat hepatocytes, a response pattern very similar to that of urea cycle enzyme mRNAs (Nebes and Morris, 1988). Taken together, in the current study, the consistent reductions of urea enzymes and transporters suggest a dampened urea-synthesizing capacity in periportal hepatocytes of MIX and OSe steers. In contrast, the blood urea nitrogen concentrations of MIX and OSe steers were higher than that of ISe steers across the 86-day grazing period. This discrepancy potentially could be due to decreased renal urea removal and/or decreased GI tract/saliva recycling of urea. In ruminants, a considerable amount of urea is recycled to the gastrointestinal tract by direct diffusion across the gut epithelium or saliva secretion
(Archibeque et al., 2001).
It is reasonable to speculate that the decreased expression of urea cycle enzymes and transporters in the livers of MIX and OSe steers vs. ISe steers may be mediated by a shared factor or pathway. This supposition is supported by reports in the literature that the activity of hepatic mitochondrial glutaminase (GLS2) changes in parallel with the activity of urea cycle enzymes (McGivan et al., 1984; Häussinger,
1990a; Curthoys and Watford, 1995). An overlap of their regulatory pathways might explain several common factors or physiological challenges known to affect both hepatic glutaminase activity and urea cycle flux, including portal ammonia concentration, glucagon, α-adrenergic agonists, vasopressin, acidosis/alkalosis, and high-protein diet (Freedland and Sodikoff, 1962; McLean and Novello, 1965; Lin et
170
al., 1982; Häussinger, 1990a).
As discussed above, the ammonia uptake and metabolism in periportal
hepatocytes of mouse/rat is achieved by increasing deaminating glutamine (periportal
GLS2 activity) and urea synthesizing enzyme activities. In the current study, mRNA expression of GLS2 and key urea cycle enzymes and transporters were all
downregulated in MIX and OSe vs. ISe steers, which together indicate a decreased
capacity of ammonia-metabolizing in the periportal zone. Interestingly, as previously
reported (Jia et al., 2018), the GS mRNA (GLUL), protein and activity in livers of
MIX and OSe steers were upregulated than that of ISe steers. The microarray results
of GLUL expression (Table 6.5) in the current study is in agreement with these
previous findings (Jia et al., 2018). Given the crucial roles of GS activity in
scavenging of ammonia by pericentral hepatocytes (Figure 6.8), an elevated pericentral ammonia assimilation capacity is expected in MIX and OSe steers. From a substrate availability and functional capacity perspective, the elevated ammonia
assimilation capacity derived from increased GS activity in pericentral of MIX and
OSe vs. ISe steers could be due to either (a) an increased demand of glutamine
resulted from elevated periportal glutamine exporting capacities, or (b) an increased
supply of substrates as intra-cellular glutamate or ammonia. The possibility of an elevated pericentral glutamine exporting capacity is in pericentral hepatocytes is less likely due to, as discussed previously, the unchanged expression of glutamine transporter SNAT3, which are responsible for transporting glutamine out of the pericentral hepatocyte (Schioth et al., 2013; Broer, 2014; Rubio-Aliaga and Wagner,
171
2016).
With regard to the second possibility of increased ammonia supply, it is reasonable to expect an increased amount of ammonia reaching pericentral hepatocytes of MIX and OSe vs. ISe steers due to less periportal ammonia assimilating capacity, as indicated by the decreased expression of GLS2 and urea synthesizing enzyme mRNA and an increased expression of ammonia transporter
(SLC42A2, RHBG) mRNA (Microarray results) in livers of MIX and OSe steers vs.
ISe steers. Although similar numerical increase was observed in RHBG mRNA expression from RT-PCR results, no significant difference was found. Because RhBG immunoreactivity has been identified strickly on the basolateral membrane of mouse pericentral hepatocytes (Weiner et al., 2003; Braeuning et al., 2006), these findings indicate that a greater ammonia importing capacity existed across the basolateral membrane of pericentral hepatocytes in MIX and OSe steers. However, it has been argued that even with an excess of ammonia inputs, glutamate availability can still limit GS activity (Bera et al., 2016). Thus, the question becomes “where is the glutamate coming from to meet the upregulated GS activity in pericentral hepatocytes?”
Regarding a possible increased extracellular glutamate source, the high-affinity system X glutamate uptake activity expressed on the basolateral membrane of − 𝐴𝐴𝐴𝐴 pericentral hepatocyte (Figure 6.8) (Cadoret et al., 2002; Matthews, 2005; Braeuning et al., 2006) are responsible for importing sinusoidal glutamate to support glutamine synthesis. High affinity X glutamate transporters are members of the solute carrier − 𝐴𝐴𝐴𝐴 172
family 1A (SLC1A) and function to mediated the Na+-dependent, concentrative
uptake of glutamate, aspartate, and cysteine across cell membranes (Krehbiel and
Matthews, 2003). In bovine liver, EAAC1 (SLC1A1) and GLT-1 (SLCA2) are the only know system X transporters (Howell et al., 2001; Miles et al., 2015). In − 𝐴𝐴𝐴𝐴 rodents, it has been demonstrated that endoplasmic reticulum-localized GTRAP3-18
(a.k.a. addicsin, ADP-ribosylation factor-like interacting protein 5/ARL6IP5, PRAF3)
binds and inhibits the function of EAAC1 and GLT-1 (Ruggiero et al., 2008; Watabe et al., 2008) and that the effect of GTRAP3-18 on EAAC1 activity is proportional to
GTRAP3-18 content (Lin et al., 2001). However, ADP-ribosylation factor-like 6 interacting protein 1 (ARL6IP1) binds and inhibits GTRAP3-18, and indirectly promotes EAAC1 activity (Akiduki and Ikemoto, 2008; Aoyama and Nakaki, 2012;
Aoyama and Nakaki, 2013). The EAAC1/GTRAP3-18/ARL6IP1 triad is expressed in rat (Akiduki and Ikemoto, 2008) and cattle (Huang et al., 2018) liver. However, in the
current study, the hepatic protein content of EAAC1 and GLT1 did not differ among
Se treatments (Table 6.6), neither did the GTRAP3-18 and ARL6IP1. Together, these data suggest that the glutamate uptake capacity in the pericentral zone was not affected by Se treatments.
With regard to an increased intracellular supply of glutamate to support GS- mediated glutamine production in pericentral hepatocytes, glutamate could have been derived from arginine and/or ornithine carbons, mediated by the activity of ARG2 and/or OAT (Figure 6.8). Ornithine aminotransferase is expressed by pericentral hepatocytes in the adult mouse (Kuo et al., 1991) and rat (Colombatto et al., 1994;
173
Boon et al., 1999). The co-localization of OAT with GS suggests that OAT may
contribute to glutamate production, through the rapid reduction of glutamate-5-
semialdehyde to glutamate by P5C dehydrogenase in mitochondria (Ginguay et al.,
2017). The supporting role of OAT in GS mediated ammonia assimilation is
evidenced by a number of observations of increased OAT activity in liver of rat after a
high-protein diet (Pitot and Peraino, 1963; Peraino, 1967; Boon et al., 1999), when an
elevated level of substrate for GS is needed to detoxify ammonia in pericentral
hepatocytes. In addition, a perfused rat liver study suggested that ARG2 is co-
expressed with OAT in pericentral hepatocytes to provide glutamate molecules for GS
(O'Sullivan et al., 1998). In the current study, ARG2 and OAT mRNA expression were
downregulated (microarray and RT-PCR analyses) in livers of both MIX and OSe vs.
ISe steers. The hepatic protein content of OAT in OSe steers was significantly lower
than that in ISe steers. These data indicate glutamate likely is not being derived from
arginine and ornithine in pericentral hepatocytes.
Another potential source of intracellular glutamate in pericentral hepatocytes is
the glutamate dehydrogenase (GDH) mediated amination of α-ketoglutarate.
Glutamate dehydrogenase can catalyze the conversion between glutamate and alpha-
ketoglutarate plus ammonium in both directions (amination and deamination). Studies
of perfused rat liver with 15N-labeled ammonia (Brosnan et al., 1996) or 15N-labeled glutamine (Nissim et al., 1999) indicated that hepatic GDH acts in a bi-directional manner. Liver sinusoidal microdissection of rat followed by enzymatic assays showed that GDH activity increased from periportal to perivenous cells (Maly and Sasse,
174
1991). This is further supported by quantitative in situ hybridization studies, in which the expression of GDH mRNA shows a gradient of increasing concentration from periportal to perivenous hepatocytes (Geerts et al., 1996; Boon et al., 1999). It has
been suggested that the net direction of GDH is deamination in periportal hepatocytes
to support ureagenesis, whereas in the GS-containing pericentral hepatocytes, GDH
mediates the amination of alpha-ketoglutarate to produce glutamate. In the current
study, the mRNA expression (microarray) of GDH is increased in the livers of MIX
and OSe vs. ISe steers. Given the primarily expression and the amination direction of
GDH in pericentral, this data may suggest a greater pericentral glutamate-producing
capacity mediated by GDH in the livers of MIX and OSe than ISe steers. This
increased expression of GDH mRNA, together with elevated GS activity, in the liver
of growing steers to agree with the role of GDH in regulating hepatic pericentral
amination demonstrated in rodents (Bera et al., 2016). In rats, the pericentral GDH
and OAT mRNA are upregulated after a high protein diet, indicating an increased
glutamate synthesizing capacity in pericentral hepatocytes to allow ammonia
detoxification by GS (Boon et al., 1999). However, in the current study, compared to
ISe steers, the OAT, and ARG2 mRNA were decreased in MIX and OSe steers. Thus,
the data from the current study indicate that to fulfill the glutamate demand of GS,
pericentral hepatocytes produce glutamate from α-ketoglutarate and ammonium
mediated by GDH activity, and not from arginine and/or ornithine.
When considering the downregulations of enzymes involved in periportal
glutamine deamination and urea cycle, and in company with the upregulations of
175
pericentral GS activity, these data suggest a location shift of ammonia metabolism
along the liver sinusoid of MIX and OSe vs. ISe steer. More specifically, compared to
ISe, MIX and OSe steers showed a decreased capacity of ammonia assimilation in periportal and a compensatory, enhanced, capacity of ammonia assimilation in pericentral hepatocytes, as evidenced by the downregulation of periportal GLS2 and key urea cycle enzymes and transporter, and by the upregulation of pericentral GS activity, respectively. The exact mechanisms of this form of Se induced changes in hepatic glutamate/glutamine and ammonia metabolism are not clear. However, as
demonstrated in rodents, hepatic urea cycle enzymes (Morris et al., 1987; Nebes and
Morris, 1988) and glutaminase (Häussinger, 1990a; Curthoys and Watford, 1995) are regulated by a variety of hormones, including glucocorticoids. Both rat and cow hepatic glutamate dehydrogenase activity were increased following glucocorticoid administration (Heitzman et al., 1972). In the current study, the glucocorticoids receptor NR3C1 mRNA expression was affected by forms of Se, and decreased in liver of MIX and OSe steers than in ISe steers (Table 6.5). The mechanism of this change in NR3C1 is not clear, but a potential Se and glucocorticoid receptor interaction was previously reported, in which an inhibitory effect of selenite on the hormone binding activity of the liver glucocorticoid receptor was observed (Tashima et al., 1989). Moreover, transcriptome profiles (microarray and RT-PCR) from the pituitaries of the same animals in the current study have reported that the mRNA expression of pituitary genes involved in POMC/ACTH synthesis was differentially expressed by form of supplemental Se (ISe, OSe, and MIX) in steers grazing
176
endophyte-infected tall fescue (Qing et al., 2018, accepted by Journal of animal
Science, November 2018). Therefore, it is reasonable to expect a different
glucocorticoid stimulating capacities in adrenal cortex among ISe, OSe, and MIX
steers, given the stimulating role of ACTH on glucocorticoid secretion. All these data
seem to support the speculation that the form of Se induced changes of mRNA in
hepatic glutamate/glutamine and ammonia metabolism could be mediated by
glucocorticoid and its receptor pathway. However, research is needed to test this
supposition.
6.5.3 Hepatic Proline Metabolism is Differentially Affected by Forms of Se
To investigate the potential effects of Se treatment on liver proline metabolism,
the mRNA expression (microarray and RT-PCR) of enzymes involved in proline
synthesis and degradation (Figure 6.9) were evaluated. In the liver of both MIX and
OSe vs. ISe steers, mRNA expression of ALDH18A1 was increased (RT-PCR results), whereas OAT was decreased (microarray and RT-PCR). These data indicate that MIX and OSe vs. ISe steers potentially had a greater capacity to make proline from glutamate than from ornithine, because hepatic OAT functions to produce glutamic semialdehyde from ornithine (Ginguay et al., 2017). However, compared to ISe, upregulation (microarray and RT-PCR) of PYCR1 was only observed in the liver of
OSe, not MIX steers. Whereas, the PRODH mRNA (microarray) was increased only in the liver of MIX, not OSe steers. These data suggested that the enzymes involved
177
in the proline cycle were differentially affected by forms of Se supplementation. More
specifically, an increased proline-synthesizing capacity was observed in the liver of
OSe steers, whereas an elevated pyrolline-5-carboxylate-synthesizing capacity was found in MIX steers. There is limited literature in regard to the potential interaction of forms of Se and proline metabolism. Although it remains unclear about the mechanisms behind the differential effect of MIX and OSe form of Se on proline metabolism, our lab has previously demonstrated that MIX (50:50 ISe and OSe) of Se induced an independent transcriptomal phenotype in liver of maturing beef heifers
(Matthews et al., 2014) and in testis of neonatal calf (Matthews and Bridges, 2014;
Cerny et al., 2016) that was not intermediate between the OSe and ISe treatment groups. Consistent with these prior analyses, the MIX steers in the current study also revealed a unique hepatic transcriptomal profile, as evident by the score plot of the
PCA analysis of all microarray chips (Figure 6.3) and the hierarchical cluster analysis of the DEGs (Figure 6.5). These results suggest that future research on how the form of supplemental Se differentially affects enzymes of proline metabolism and hepatic function is needed.
6.6 Summary
In summary, the form of supplemental Se (ISe, MIX, or OSe) affected the hepatic transcriptome profiles of steers subjected to summer-long grazing of endophyte-infected tall fescue pasture. Bioinformatic analysis of these profiles
178
indicated that Se treatment-induced differentially expressed hepatic genes were
involved in several canonical pathways, including glutamine
biosynthesis/degradation, glutamate biosynthesis/degradation, and proline
biosynthesis. To further elaborate the microarray data, targeted RT-PCR and Western- blotting analyses of key enzymes and transporters involved in hepatic glutamate/glutamine and ammonia metabolism were conducted. Hepatic mRNA expression of enzymes responsible for proline metabolism were differentially affected by forms of Se supplementation. The differential expression of hepatic enzymes and transporters characterized a unique change of ammonia-assimilation capacity along the hepatic sinusoid of steer grazing endophyte-infected tall fescue induced by the supplementation of MIX and OSe vs. ISe form of Se. Specifically, compared to ISe,
MIX and OSe steers indicated a decreased periportal ammonia assimilation and urea- synthesizing capacity, and a compensatory elevated pericentral ammonia assimilation capacity. However, the metabolic consequences of these alterations in enzymes and transporters in terms of whole-body nitrogen and glutamate/glutamine flux are unclear and need to be addressed in the future research.
179
Table 6. 1 List of differentially expressed and annotated liver genes (P < 0.01, 573 genes) from steers grazing endophyte-infected tall fescue
and supplemented with 3 mg Se/d in vitamin-mineral mixes as sodium selenite (ISe, n = 6), SEL-PLEX (OSe, n = 8), or an 1:1 blend of ISe
and OSe (MIX, n = 7)1.
Transcript Gene symbol Gene assignment ISe MIX OSe SEM P-value ID 12717255 LOC522845 similar to ANKRD protein 1.00a 0.64b 0.86c 0.054 0.00001 12745320 LRAT lecithin retinol acyltransferase 1.00a 0.70b 1.14a 0.077 0.00002 12721273 KIAA1462 hypothetical protein LOC784675 1.00a 0.74b 0.63c 0.077 0.00003 180 12901402 ZC3H12D zinc finger CCCH-type containing 12D 1.00a 1.31b 1.35b 0.052 0.00003 12853639 PDK4 pyruvate dehydrogenase kinase, isozyme 4 1.00a 0.36b 0.34b 0.198 0.00005 12837074 TXNIP thioredoxin interacting protein 1.00a 0.70b 0.63b 0.079 0.00005 12826569 DDIT4 DNA-damage-inducible transcript 4 1.00a 0.57b 0.52b 0.114 0.00005 12807029 KCNK5 potassium channel, subfamily K, member 5 1.00a 0.63b 0.59b 0.098 0.00007 12885754 LRRTM2 leucine rich repeat transmembrane neuronal 2 1.00a 1.26b 1.05a 0.043 0.00007 12723730 TP53INP1 tumor protein p53 inducible nuclear protein 1 1.00a 0.60b 0.50b 0.126 0.00008 12787702 IL7R interleukin 7 receptor 1.00a 0.75b 0.61c 0.086 0.00011 12896970 TNFAIP3 tumor necrosis factor, alpha-induced protein 3 1.00a 0.79b 0.69c 0.068 0.00011 12746988 PPTC7 PTC7 protein phosphatase homolog (S. cerevisiae) 1.00a 0.57b 0.50b 0.126 0.00012 12843099 C3H1orf146 chromosome 1 open reading frame 146 1.00a 1.22b 1.30b 0.045 0.00012 12765816 TOB1 transducer of ERBB2, 1 1.00a 0.80b 0.75b 0.055 0.00013
Table 6. 1 (continued) 12859818 TDG thymine-DNA glycosylase 1.00a 1.04a 0.90c 0.024 0.00014 12726077 OTUD6B OTU domain containing 6B 1.00a 0.82b 0.67c 0.068 0.00015 12895371 LOC616371 hypothetical LOC616371 1.00a 0.75b 0.52c 0.119 0.00016 12830162 LOC509323 similar to Olfactory receptor 8G2 1.00a 1.33b 1.44b 0.067 0.00017 12742487 TPCN1 two pore segment channel 1 1.00a 0.69b 0.70b 0.076 0.00018 12881048 LOC538782 hypothetical LOC538782 1.00a 1.53b 1.42b 0.078 0.00021 12785308 RANBP3L RAN binding protein 3-like 1.00a 1.53b 1.35b 0.069 0.00023 12746191 ZNF74 zinc finger protein 74 1.00a 1.61b 1.23c 0.087 0.00023 12764440 C19H17orf42 chromosome 17 open reading frame 42 1.00a 0.94a 0.79c 0.046 0.00024 12852248 ARL4A ADP-ribosylation factor-like 4A 1.00a 0.92a 0.73c 0.064 0.00025 181 12821078 BAG3 BCL2-associated athanogene 3 1.00a 0.91a 0.70c 0.074 0.00026
12769776 SLC43A2 solute carrier family 43, member 2 1.00a 0.74b 0.80b 0.058 0.00029 12849449 CUL1 cullin 1 1.00a 1.14b 1.09b 0.025 0.00030 12889453 PLAA phospholipase A2-activating protein 1.00a 1.25b 1.20b 0.044 0.00031 12729339 PIK3C2A phosphoinositide-3-kinase, class 2, alpha polypeptide 1.00a 1.11b 0.90c 0.043 0.00032 12759670 SERTAD3 SERTA domain containing 3 1.00a 0.85b 0.79b 0.047 0.00032 12847154 MAEL maelstrom homolog (Drosophila) 1.00a 0.56b 0.52b 0.133 0.00032 12865807 KRR1 KRR1, small subunit (SSU) processome component, homolog (yeast) 1.00a 1.20b 1.12b 0.034 0.00033 12843181 CEPT1 choline ethanolamine phosphotransferase 1 1.00a 1.15b 1.11b 0.024 0.00036 12692254 JPH4 junctophilin 4 1.00a 0.86b 1.05a 0.043 0.00036 12846488 MSTO1 misato homolog 1 (Drosophila) 1.00a 0.89b 0.84b 0.035 0.00037 12803483 C23H6orf145 PX domain-containing protein C6orf145 homolog 1.00a 1.30b 1.17c 0.049 0.00037
Table 6. 1 (continued) 12791153 FAM174B membrane protein FAM174B 1.00a 1.56b 1.11a 0.089 0.00038 12810552 ATP8B1 ATPase, aminophospholipid transporter, class I, type 8B 1.00a 1.44b 1.42b 0.080 0.00041 12707461 RAB1A RAB1A, member RAS oncogene family 1.00a 1.16b 1.10b 0.029 0.00044 12774482 CHRND cholinergic receptor, nicotinic, delta 1.00a 0.96a 0.76c 0.061 0.00044 12788100 DUSP1 dual specificity phosphatase 1 1.00a 0.57b 0.47b 0.160 0.00044 12700664 EIF2B4 eukaryotic translation initiation factor 2B, subunit 4 delta 1.00a 1.14b 0.99a 0.032 0.00045 12862500 C5H12orf45 chromosome 12 open reading frame 45 ortholog 1.00a 0.69b 0.57b 0.119 0.00047 12904519 PCDH19 protocadherin 19 1.00a 0.68b 0.50c 0.136 0.00047 12755070 LOC100126043 hypothetical LOC100126043 1.00a 0.64b 0.73b 0.089 0.00047 12855278 COPG2 coatomer protein complex, subunit gamma 2 1.00a 0.75b 0.77b 0.063 0.00049 182 12819467 LOC511390 similar to ribosomal protein S15a 1.00a 1.07a 1.20c 0.039 0.00050
12842451 MIR2416 microRNA mir-2416 1.00a 1.23b 1.06a 0.044 0.00050 12843638 POLR3C polymerase (RNA) III (DNA directed) polypeptide C (62kD) 1.00a 0.84b 0.80b 0.046 0.00050 12762445 ASPA aspartoacylase 1.00a 0.60b 0.59b 0.109 0.00052 12907709 PRAF2 PRA1 domain family, member 2 1.00a 0.82b 0.92c 0.038 0.00053 12683452 IFNAR2 interferon (alpha, beta and omega) receptor 2 1.00a 1.26b 1.51c 0.083 0.00053 12816753 TRIM56 tripartite motif-containing 56 1.00a 1.18b 1.14b 0.035 0.00055 12724524 LOC507013 similar to Protein FAM91A1 1.00a 1.15b 1.08c 0.029 0.00055 12791746 NFKBIA nuclear factor of kappa light chain gene enhancer in B-cell inhibitor, α 1.00a 0.69b 0.62b 0.104 0.00057 12885601 LOC518124 similar to Os01g0835900 1.00a 1.06a 1.18c 0.032 0.00058 12808932 LOC100295096 similar to histone cluster 1, H2bd 1.00a 0.88b 1.07a 0.044 0.00059 12904088 ALG13 asparagine-linked glycosylation 13 homolog (S. cerevisiae) 1.00a 0.75b 0.74b 0.068 0.00062
Table 6. 1 (continued) 12822395 PDZD8 PDZ domain containing 8 1.00a 1.18b 1.14b 0.033 0.00063 12831930 KCNK4 potassium channel, subfamily K, member 4 1.00a 1.16b 1.04a 0.032 0.00065 12878470 ZNF608 zinc finger protein 608 1.00a 1.20b 1.50c 0.085 0.00065 12815269 SULT1A1 sulfotransferase family, cytosolic, 1A, phenol-preferring, member 1 1.00a 0.94a 0.84c 0.036 0.00065 12735921 CFHR2 complement factor H-related 2 1.00a 1.47b 1.38b 0.080 0.00066 12836660 OLFML3 olfactomedin-like 3 1.00a 0.74b 0.83b 0.063 0.00067 12720675 ZFP64 zinc finger protein 64 homolog (mouse) 1.00a 1.02a 1.21c 0.047 0.00068 12799840 ALAS1 aminolevulinate, delta-, synthase 1 1.00a 0.64b 0.47b 0.154 0.00068 12775398 STRADB STE20-related kinase adaptor beta 1.00a 1.22b 1.05a 0.042 0.00068 12782069 NOSTRIN nitric oxide synthase trafficker 1.00a 0.74b 0.68b 0.078 0.00068 183 12681397 PLOD2 procollagen-lysine, 2-oxoglutarate 5-dioxygenase 2 1.00a 1.03a 0.82c 0.055 0.00068
12876053 LOC782370 similar to UDP glucuronosyltransferase 2 family 1.00a 0.80b 0.71b 0.071 0.00069 12731162 ZNF259 zinc finger protein 259 1.00a 0.70b 0.65b 0.094 0.00070 12905382 PRRG3 proline rich Gla (G-carboxyglutamic acid) 3 (transmembrane) 1.00a 0.58b 0.58b 0.125 0.00070 12764872 G6PC glucose-6-phosphatase, catalytic subunit 1.00a 0.63b 0.69b 0.102 0.00072 12748964 LOC100299267 similar to pyruvate dehydrogenase phosphatase 1.00a 0.68b 0.60b 0.113 0.00072 12838072 OLFML2B olfactomedin-like 2B 1.00a 0.78b 0.81b 0.055 0.00072 12862110 KRAS v-Ki-ras2 Kirsten rat sarcoma viral oncogene homolog 1.00a 1.26b 1.13c 0.047 0.00073 12819543 PLEKHA1 pleckstrin homology domain containing, family A 1.00a 1.21b 1.21b 0.045 0.00075 12908347 RAP2C RAP2C, member of RAS oncogene family 1.00a 1.30b 1.38b 0.072 0.00083 12898797 TBPL1 TBP-like 1 1.00a 1.20b 1.39c 0.067 0.00083 12853698 MGC140754 hypothetical LOC508613 1.00a 1.04a 0.92c 0.031 0.00083
Table 6. 1 (continued) 12791562 MIR211 microRNA mir-211 1.00a 0.93b 1.06a 0.031 0.00084 12891778 C9orf89 chromosome 9 open reading frame 89 1.00a 1.27b 1.32b 0.062 0.00085 12864948 TOB2 transducer of ERBB2, 2 1.00a 0.83b 0.71c 0.070 0.00087 12865639 POLDIP3 polymerase (DNA-directed), delta interacting protein 3 1.00a 0.96a 0.91c 0.018 0.00089 12901108 PRDM1 PR domain containing 1, with ZNF domain 1.00a 0.82b 0.74b 0.063 0.00091 12700051 TEX261 testis expressed 261 1.00a 1.28b 1.17b 0.053 0.00093 12738460 GLUL glutamate-ammonia ligase 1.00a 1.37b 1.32b 0.070 0.00096 12840984 TRPM8 transient receptor potential cation channel, subfamily M 1.00a 0.81b 0.88b 0.046 0.00096 12837582 SELENBP1 selenium binding protein 1 1.00a 0.64b 0.66b 0.106 0.00097 12714756 RIP5 RAB5-interacting protein 1.00a 1.32b 1.27b 0.061 0.00097 184 12739643 DDI2 DNA-damage inducible 1 homolog 2 (S. cerevisiae) 1.00a 0.74b 0.68b 0.088 0.00098
12821282 ASAH2 N-acylsphingosine amidohydrolase (non-lysosomal ceramidase) 1.00a 0.71b 0.80b 0.069 0.00099 12714592 ERGIC3 ERGIC and golgi 3 1.00a 0.81b 0.87b 0.044 0.00104 12707762 CCT4 chaperonin containing TCP1, subunit 4 (delta) 1.00a 1.41b 1.17a 0.075 0.00105 12891698 RNASEH1 ribonuclease H1 1.00a 1.15b 1.02a 0.030 0.00105 12856334 LOC100270756 hypothetical protein LOC100270756 1.00a 1.47b 1.48b 0.087 0.00106 12873681 RASGEF1B RasGEF domain family, member 1B 1.00a 0.75b 0.68b 0.083 0.00107 12836428 DENND2D DENN MADD domain containing 2D 1.00a 1.49b 1.36b 0.090 0.00107 12770593 PER1 period homolog 1 (Drosophila) 1.00a 0.72b 0.60b 0.107 0.00107 12843331 GADD45A growth arrest and DNA-damage-inducible, alpha 1.00a 0.55b 0.62b 0.136 0.00107 12687168 CLDN14 claudin 14 1.00a 0.69b 0.81b 0.080 0.00108 12879664 REEP6 receptor accessory protein 6 1.00a 0.71b 0.74b 0.073 0.00111
Table 6. 1 (continued) 12712647 WASF3 WAS protein family, member 3 1.00a 0.65b 0.66b 0.107 0.00115 12684186 NMD3 NMD3 homolog (S. cerevisiae) 1.00a 1.24b 1.08a 0.046 0.00115 12688156 ANXA2 annexin A2 1.00a 2.44b 2.21b 0.178 0.00116 12818826 A1CF APOBEC1 complementation factor 1.00a 1.13b 1.10b 0.027 0.00117 12763805 MED13 mediator complex subunit 13 1.00a 0.91a 0.82c 0.046 0.00117 12697953 CNNM3 cyclin M3 1.00a 0.84b 0.86b 0.039 0.00118 12698769 PNO1 partner of NOB1 homolog (S. cerevisiae) 1.00a 1.26b 1.10a 0.052 0.00118 12871562 TMEM165 transmembrane protein 165 1.00a 1.19b 1.15b 0.040 0.00119 12907329 CLDN2 claudin 2 1.00a 1.17a 1.51c 0.088 0.00120 12823344 ASH2L ash2 (absent, small, or homeotic)-like (Drosophila) 1.00a 0.94a 0.87c 0.029 0.00120 185 12878044 CIRBP cold inducible RNA binding protein 1.00a 0.78b 0.88c 0.052 0.00124
12788065 TMEM171 transmembrane protein 171 1.00a 0.67b 0.64b 0.110 0.00124 12805437 SRPK1 SRSF protein kinase 1 1.00a 1.26b 1.15b 0.050 0.00124 12711952 ATP7B ATPase, Cu++ transporting, beta polypeptide 1.00a 0.74b 0.76b 0.073 0.00126 12732418 USP2 ubiquitin specific peptidase 2 1.00a 0.49b 0.32b 0.267 0.00128 12728293 LOC519902 similar to rCG39757 1.00a 0.96a 1.30c 0.077 0.00129 12815806 TMEM219 transmembrane protein 219 1.00a 1.12b 1.17b 0.038 0.00129 12863757 TMEM117 transmembrane protein 117 1.00a 1.28b 1.13c 0.056 0.00130 12760883 PRKCA protein kinase C, alpha 1.00a 1.31b 1.23b 0.060 0.00131 12691839 HOMEZ homeobox and leucine zipper encoding 1.00a 0.87b 0.85b 0.039 0.00131 12907114 MAOA monoamine oxidase A 1.00a 0.89b 0.81b 0.044 0.00134 12728955 ZNF143 zinc finger protein 143 1.00a 1.17b 1.06a 0.035 0.00136
Table 6. 1 (continued) 12877898 TMEM221 transmembrane protein 221 1.00a 1.14b 1.04a 0.030 0.00136 12843108 PLK3 polo-like kinase 3 1.00a 0.94a 0.80c 0.057 0.00138 12871103 NOP14 NOP14 nucleolar protein homolog (yeast) 1.00a 1.24b 1.15b 0.047 0.00139 12734266 LOC100301430 hypothetical protein LOC100301430 1.00a 1.05a 1.14c 0.031 0.00140 12744515 DDT D-dopachrome tautomerase 1.00a 0.80b 0.87b 0.048 0.00140 12836069 S100A12 S100 calcium binding protein A12 1.00a 1.29b 0.96a 0.075 0.00141 12832069 ASRGL1 asparaginase like 1 1.00a 1.21b 1.21b 0.049 0.00143 12785824 IL6ST interleukin 6 signal transducer (gp130, oncostatin M receptor) 1.00a 1.13b 1.17b 0.036 0.00146 12768112 TMEM220 transmembrane protein 220 1.00a 0.90a 0.69c 0.088 0.00147 12728761 TSKU tsukushi small leucine rich proteoglycan homolog (Xenopus laevis) 1.00a 0.51b 0.35b 0.222 0.00148 186 12774837 NDUFB3 NADH dehydrogenase (ubiquinone) 1 beta subcomplex, 3, 12kDa 1.00a 0.94a 0.86c 0.036 0.00148
12794927 RPN1 ribophorin I 1.00a 1.16b 1.20b 0.043 0.00151 12748493 LOC100125939 hypothetical protein LOC100125939 1.00a 0.78b 0.61c 0.115 0.00153 12876921 LDLR low density lipoprotein receptor 1.00a 0.65b 0.61b 0.116 0.00156 12730020 PRRG4 proline rich Gla (G-carboxyglutamic acid) 4 (transmembrane) 1.00a 1.45b 1.43b 0.088 0.00160 12851530 PSMA2 proteasome (prosome, macropain) subunit, alpha type, 2 1.00a 1.24b 1.29b 0.059 0.00160 12704320 ID2 inhibitor of DNA binding 2, dominant negative helix-loop-helix protein 1.00a 0.60b 0.64b 0.126 0.00161 12711702 TSC22D1 TSC22 domain family, member 1 1.00a 1.15a 0.83c 0.079 0.00161 12749099 MGC157082 hypothetical protein LOC788038 1.00a 0.73b 0.72b 0.085 0.00162 12739675 SLC25A34 solute carrier family 25, member 34 1.00a 0.69b 0.71b 0.094 0.00164 12895494 CORO2A coronin, actin binding protein, 2A 1.00a 1.25b 1.27b 0.062 0.00167 12724748 MTDH metadherin 1.00a 1.15b 1.15b 0.036 0.00167
Table 6. 1 (continued) 12711664 INTS6 integrator complex subunit 6 1.00a 1.20b 1.05a 0.043 0.00170 12686938 LSS lanosterol synthase (2,3-oxidosqualene-lanosterol cyclase) 1.00a 0.91a 0.70c 0.080 0.00171 12722787 MTSS1 metastasis suppressor 1 1.00a 0.78b 0.80b 0.061 0.00173 12726492 MMP8 matrix metallopeptidase 8 (neutrophil collagenase) 1.00a 0.85b 0.92c 0.035 0.00174 12751960 TMEM86B transmembrane protein 86B 1.00a 0.67b 0.77b 0.093 0.00176 12807824 TGIF1 TGFB-induced factor homeobox 1 1.00a 1.22b 1.37b 0.075 0.00178 12841743 TGFBR3 transforming growth factor, beta receptor III 1.00a 0.76b 0.82b 0.061 0.00178 12745970 GATSL3 GATS protein-like 3 1.00a 0.71b 0.75b 0.081 0.00181 12776671 LIMS2 LIM and senescent cell antigen-like domains 2 1.00a 0.64b 0.69b 0.107 0.00181 12778611 RND3 Rho family GTPase 3 1.00a 1.21b 1.25b 0.055 0.00182 187 12868256 CCDC53 coiled-coil domain containing 53 1.00a 1.17b 1.20b 0.044 0.00184
12868313 SLC16A7 solute carrier family 16, member 7 (monocarboxylic acid transporter) 1.00a 1.34b 1.54b 0.105 0.00185 12902223 TSC22D3 TSC22 domain family, member 3 1.00a 0.73b 0.75b 0.079 0.00185 12795069 NME6 non-metastatic cells 6, protein expressed in (nucleoside-diphosphate kinase) 1.00a 1.08b 1.15b 0.032 0.00188 12682021 GTF2E1 general transcription factor IIE, polypeptide 1, alpha 56kDa 1.00a 1.20b 1.02a 0.044 0.00189 12752908 TAT tyrosine aminotransferase 1.00a 1.09a 0.75c 0.086 0.00192 12747887 CCRN4L CCR4 carbon catabolite repression 4-like (S. cerevisiae) 1.00a 0.54b 0.51b 0.163 0.00197 12906670 LOC100336599 arylsulfatase D-like 1.00a 0.69b 0.74b 0.086 0.00201 12798750 THUMPD3 THUMP domain containing 3 1.00a 1.18b 1.13b 0.037 0.00203 12705036 FOSL2 FOS-like antigen 2 1.00a 0.59b 0.68b 0.130 0.00205 12801311 NEDD9 neural precursor cell expressed, developmentally down-regulated 9 1.00a 0.66b 0.63b 0.098 0.00206 12909019 LOC528342 similar to histone cluster 1, H2bd 1.00a 1.02a 1.33c 0.074 0.00206
Table 6. 1 (continued) 12741974 YWHAH tyrosine 3-monooxygenase tryptophan 5-monooxygenase activation protein η 1.00a 1.26b 1.20b 0.054 0.00209 12721857 HNF4G hepatocyte nuclear factor 4, gamma 1.00a 0.77b 0.74b 0.077 0.00210 12843423 CTPS CTP synthase 1.00a 1.54b 1.41b 0.101 0.00210 12897181 C9H6ORF70 chromosome 6 open reading frame 70 1.00a 0.94a 0.85c 0.037 0.00211 12881182 AKAP8L A kinase (PRKA) anchor protein 8-like 1.00a 0.90b 0.85b 0.039 0.00212 12746785 SDSL serine dehydratase-like 1.00a 0.88b 1.00a 0.037 0.00214 12759006 ASPDH aspartate dehydrogenase domain containing 1.00a 0.84b 0.85b 0.045 0.00216 12842468 FRRS1 ferric-chelate reductase 1 1.00a 1.49b 1.29b 0.087 0.00217 12803172 ENPP4 ectonucleotide pyrophosphatase phosphodiesterase 4 (putative) 1.00a 0.76b 0.77b 0.068 0.00220 12901045 MAP3K5 mitogen-activated protein kinase kinase kinase 5 1.00a 1.25a 1.58c 0.113 0.00221 188 12725205 WWP1 WW domain containing E3 ubiquitin protein ligase 1 1.00a 1.15b 1.16b 0.035 0.00223
12678773 COL6A2 collagen, type VI, alpha 2 1.00a 0.86b 0.87b 0.040 0.00224 12821375 CHUK conserved helix-loop-helix ubiquitous kinase 1.00a 1.25b 1.09a 0.053 0.00225 12758956 CMTM4 CKLF-like MARVEL transmembrane domain containing 4 1.00a 1.27b 1.15b 0.055 0.00226 12749252 CRX cone-rod homeobox 1.00a 1.31b 1.21b 0.065 0.00226 12883164 CLTB clathrin, light chain B 1.00a 1.10b 1.09b 0.025 0.00228 12749032 MIR2328 microRNA mir-2328 1.00a 1.22b 1.03a 0.048 0.00232 12869106 MON2 MON2 homolog (S. cerevisiae) 1.00a 1.11b 0.94a 0.040 0.00235 12798533 PRKCD protein kinase C, delta 1.00a 1.27b 1.22b 0.059 0.00237 12821712 OAT ornithine aminotransferase 1.00a 0.74b 0.71b 0.090 0.00238 12784635 PPP1R1C protein phosphatase 1, regulatory (inhibitor) subunit 1C 1.00a 0.94a 1.10c 0.041 0.00241 12855578 CNOT4 CCR4-NOT transcription complex, subunit 4 1.00a 0.89b 0.92b 0.027 0.00242
Table 6. 1 (continued) 12754033 LENG1 leukocyte receptor cluster (LRC) member 1 1.00a 0.97a 0.85c 0.040 0.00243 12908375 GRIPAP1 GRIP1 associated protein 1 1.00a 1.25b 1.14b 0.053 0.00250 12840924 TMEM53 transmembrane protein 53 1.00a 0.83b 0.81b 0.057 0.00255 12790233 FAM108C1 abhydrolase domain-containing protein FAM108C1 1.00a 1.29b 1.42b 0.087 0.00256 12828476 TSNAX translin-associated factor X 1.00a 1.17b 1.20b 0.047 0.00257 12693124 LOC100298610 hypothetical protein LOC100298610 1.00a 0.92a 1.13c 0.054 0.00258 12867556 CREBL2 cAMP responsive element binding protein-like 2 1.00a 1.12b 1.13b 0.033 0.00259 12709437 ERCC5 ERCC excision repair 5, endonuclease 1.00a 0.86b 0.95a 0.037 0.00259 12894663 KANK1 KN motif and ankyrin repeat domains 1 1.00a 1.23b 1.15b 0.051 0.00260 12843671 RIMKLA ribosomal modification protein rimK-like family member 1.00a 0.82b 0.95a 0.049 0.00260 189 12775426 MFF mitochondrial fission factor 1.00a 1.21b 1.16b 0.044 0.00261
12726488 MIR2313 microRNA mir-2313 1.00a 0.84b 1.06a 0.054 0.00262 12845908 COL6A3 collagen, type VI, alpha 3 1.00a 0.80b 0.95a 0.058 0.00262 12720257 MAFB v-maf musculoaponeurotic fibrosarcoma oncogene homolog B 1.00a 0.66b 0.74b 0.104 0.00265 12819033 FAS Fas (TNF receptor superfamily, member 6) 1.00a 1.65b 1.26a 0.110 0.00266 12881604 DDX39 DEAD (Asp-Glu-Ala-Asp) box polypeptide 39 1.00a 1.22b 1.16b 0.048 0.00267 12850400 LOC518003 similar to KIAA0644 gene product 1.00a 1.03a 1.15c 0.037 0.00270 12746040 HIP1R huntingtin interacting protein 1 related 1.00a 1.36b 1.34b 0.077 0.00270 12905266 ARHGEF9 Cdc42 guanine nucleotide exchange factor (GEF) 9 1.00a 0.53b 0.56b 0.160 0.00271 12841430 PPAP2B phosphatidic acid phosphatase type 2B 1.00a 0.84b 0.73b 0.078 0.00272 12883618 HSD17B4 hydroxysteroid (17-beta) dehydrogenase 4 1.00a 0.86b 0.84b 0.045 0.00277 12841451 LSM10 LSM10, U7 small nuclear RNA associated 1.00a 1.22b 1.26b 0.058 0.00279
Table 6. 1 (continued) 12696623 C10H14ORF1 chromosome 14 open reading frame 1 ortholog 1.00a 0.92a 0.82c 0.049 0.00281 12688873 OR4N4 olfactory receptor, family 4, subfamily N, member 4 1.00a 1.24b 1.17b 0.050 0.00284 12776995 GALE UDP-galactose-4-epimerase 1.00a 1.28b 1.08a 0.053 0.00284 12805296 NRM nurim (nuclear envelope membrane protein) 1.00a 0.81b 0.96a 0.054 0.00285 12809702 LPIN2 lipin 2 1.00a 0.93a 0.77c 0.068 0.00287 12805821 LEMD2 LEM domain containing 2 1.00a 1.16b 1.17b 0.043 0.00287 12835976 OVGP1 oviductal glycoprotein 1, 120kDa 1.00a 0.76b 0.69b 0.095 0.00288 12851630 NPC1L1 NPC1 (Niemann-Pick disease, type C1, gene)-like 1 1.00a 0.95a 0.83c 0.049 0.00288 12798204 MITF microphthalmia-associated transcription factor 1.00a 1.03a 1.29c 0.072 0.00294 12702578 BOLA3 bolA homolog 3 (E. coli) 1.00a 0.77b 0.88a 0.058 0.00296 190 12723513 TMEM55A transmembrane protein 55A 1.00a 0.83a 0.67c 0.103 0.00297
12874708 LOC530285 similar to F-box protein 27 1.00a 0.85b 0.97a 0.045 0.00299 12808401 TWSG1 twisted gastrulation homolog 1 (Drosophila) 1.00a 1.17b 1.14b 0.038 0.00307 12882644 RAB3D RAB3D, member RAS oncogene family 1.00a 1.40b 1.40b 0.082 0.00309 12707716 THNSL2 threonine synthase-like 2 (S. cerevisiae) 1.00a 0.72b 0.75b 0.082 0.00309 12710024 FARP1 FERM, RhoGEF (ARHGEF) and pleckstrin domain protein 1 1.00a 0.85b 0.84b 0.047 0.00309 12734971 BLZF1 basic leucine zipper nuclear factor 1 1.00a 1.09a 0.93a 0.042 0.00310 12779616 MOBKL3 MOB1, Mps One Binder kinase activator-like 3 (yeast) 1.00a 1.05a 0.90c 0.041 0.00310 12691120 EIF3J eukaryotic translation initiation factor 3, subunit J 1.00a 1.20b 1.08a 0.043 0.00310 12898434 SESN1 sestrin 1 1.00a 0.82b 0.81b 0.054 0.00312 12803164 GNMT glycine N-methyltransferase 1.00a 1.55b 1.21a 0.106 0.00316 12887668 TECR trans-2,3-enoyl-CoA reductase 1.00a 0.76b 0.81b 0.067 0.00317
Table 6. 1 (continued) 12750604 ACSF3 acyl-CoA synthetase family member 3 1.00a 0.87b 0.90b 0.035 0.00318 12769431 DDX52 DEAD (Asp-Glu-Ala-Asp) box polypeptide 52 1.00a 1.11a 0.92a 0.045 0.00319 12763454 SPNS3 spinster homolog 3 (Drosophila) 1.00a 0.95a 1.21c 0.066 0.00319 12745541 ATP6V0A2 ATPase, H+ transporting, lysosomal V0 subunit a2 1.00a 1.15b 1.11b 0.036 0.00324 12889942 ZNF395 zinc finger protein 395 1.00a 1.03a 1.24c 0.056 0.00324 12867519 RASSF3 Ras association (RalGDS AF-6) domain family member 3 1.00a 1.30b 1.34b 0.078 0.00325 12834100 TRIM64 tripartite motif-containing 64 1.00a 1.24b 1.18b 0.056 0.00326 12868043 MDM2 Mdm2 p53 binding protein homolog (mouse) 1.00a 0.85b 0.79b 0.060 0.00326 12817258 Sep14 septin 14 1.00a 0.74b 0.74b 0.084 0.00328 12759640 RPL28 ribosomal protein L28 1.00a 0.87b 0.90b 0.034 0.00329 191 12787518 PDZD2 PDZ domain containing 2 1.00a 0.84b 0.93a 0.044 0.00331
12848949 CALD1 caldesmon 1 1.00a 1.03a 0.97a 0.017 0.00335 12682346 LOC614619 similar to histone H2B 1.00a 0.88b 1.06a 0.046 0.00338 12770824 AFMID arylformamidase 1.00a 0.66b 0.79b 0.103 0.00339 12687596 ABHD12B abhydrolase domain containing 12B 1.00a 0.78b 0.69b 0.095 0.00341 12811906 VKORC1L1 vitamin K epoxide reductase complex, subunit 1-like 1 1.00a 1.14b 1.15b 0.034 0.00343 12709149 LRCH1 leucine-rich repeats and calponin homology (CH) domain c 1.00a 1.19b 1.30b 0.068 0.00343 12736270 DVL1 dishevelled, dsh homolog 1 (Drosophila) 1.00a 1.08b 0.97a 0.029 0.00345 12833908 SLC25A45 solute carrier family 25, member 45 1.00a 0.68b 0.76b 0.100 0.00345 12888531 THEG Theg homolog (mouse) 1.00a 0.97a 1.14c 0.044 0.00346 12687002 FAIM Fas apoptotic inhibitory molecule 1.00a 0.95a 0.76c 0.076 0.00351 12902917 UBE2A ubiquitin-conjugating enzyme E2A (RAD6 homolog) 1.00a 1.12b 0.96a 0.039 0.00357
Table 6. 1 (continued) 12726638 SERPING1 serpin peptidase inhibitor, clade G (C1 inhibitor), member 1 1.00a 0.93b 0.99a 0.019 0.00360 12875732 UGT2B4 UDP glucuronosyltransferase 2 family, polypeptide B4 1.00a 1.61b 1.75b 0.150 0.00364 12785694 RAD1 RAD1 homolog (S. pombe) 1.00a 1.28b 1.15b 0.062 0.00365 12684060 WDR4 WD repeat domain 4 1.00a 1.10b 0.96a 0.038 0.00368 12747614 NAA15 N(alpha)-acetyltransferase 15, NatA auxiliary subunit 1.00a 1.19b 1.09b 0.043 0.00369 12787233 TARS threonyl-tRNA synthetase 1.00a 1.23b 1.24b 0.059 0.00370 12859963 ERC1 ELKS RAB6-interacting ELKS RAB6-interacting 1.00a 0.94b 0.90b 0.026 0.00372 12824695 LOC100295410 similar to retinoic acid receptor, beta 1.00a 0.83b 1.03a 0.058 0.00373 12841144 MOBKL2C MOB1, Mps One Binder kinase activator-like 2C (yeast) 1.00a 0.53b 0.55b 0.176 0.00375 12742212 LOC506093 glutathione S-transferase, theta 4 1.00a 0.53b 0.64b 0.164 0.00377 192 12868148 SP1 Sp1 transcription factor 1.00a 0.95b 0.92b 0.020 0.00379
12827732 GLUD1 glutamate dehydrogenase 1 1.00a 1.20b 1.16b 0.047 0.00380 12773184 MIS12 MIS12, MIND kinetochore complex component, homolog (S. pombe) 1.00a 0.93a 0.80c 0.056 0.00390 12724021 LOC100336014 protease-like 1.00a 0.73b 0.77b 0.083 0.00397 12745611 UPB1 ureidopropionase, beta 1.00a 0.72b 0.84b 0.080 0.00399 12739768 NUAK2 NUAK family, SNF1-like kinase, 2 1.00a 1.25b 1.14b 0.057 0.00400 12705743 TMEM17 transmembrane protein 17 1.00a 0.75b 1.04a 0.092 0.00400 12765376 CD300LG CD300 molecule-like family member g 1.00a 0.77b 0.75b 0.079 0.00401 12689317 TRPM7 transient receptor potential cation channel, subfamily M 1.00a 1.38b 1.30b 0.080 0.00402 12749424 ZFP36 zinc finger protein 36, C3H type, homolog (mouse) 1.00a 0.75b 0.76b 0.082 0.00408 12868391 HAL histidine ammonia-lyase 1.00a 0.43b 0.42b 0.241 0.00410 12824460 RBPMS RNA binding protein with multiple splicing 1.00a 0.83b 0.78b 0.067 0.00411
Table 6. 1 (continued) 12740640 RAB7L1 RAB7, member RAS oncogene family-like 1 1.00a 1.26b 1.32b 0.075 0.00411 12846683 ZMPSTE24 zinc metallopeptidase (STE24 homolog, S. cerevisiae) 1.00a 1.19b 1.23b 0.056 0.00411 12853232 PLXNA4 plexin A4 1.00a 0.74b 0.90a 0.074 0.00422 12909004 KLHL13 kelch-like 13 (Drosophila) 1.00a 0.74b 0.68b 0.103 0.00422 12871741 LIMCH1 LIM and calponin homology domains 1 1.00a 0.74b 0.78b 0.079 0.00425 12737200 LPGAT1 lysophosphatidylglycerol acyltransferase 1 1.00a 1.31b 1.29b 0.073 0.00426 12777646 MRPL44 mitochondrial ribosomal protein L44 1.00a 0.87b 0.97a 0.036 0.00428 12747298 SETD8 SET domain containing (lysine methyltransferase) 8 1.00a 1.22b 1.18b 0.053 0.00428 12841469 SFPQ splicing factor proline glutamine-rich 1.00a 1.14b 1.05a 0.034 0.00431 12740133 ZNF281 zinc finger protein 281 1.00a 1.04a 1.12c 0.031 0.00431 193 12898204 MDN1 MDN1, midasin homolog (yeast) 1.00a 1.15b 1.03a 0.035 0.00435
12839991 PABPC4 poly(A) binding protein, cytoplasmic 4 (inducible form) 1.00a 1.03a 0.89c 0.038 0.00436 12749058 LOC100336101 hypothetical protein LOC100336101 1.00a 0.99a 1.19c 0.049 0.00441 12726992 OR2D2 olfactory receptor, family 2, subfamily D, member 2 1.00a 0.98a 0.84c 0.048 0.00441 12808638 LOC615119 similar to Uncharacterized protein KIAA0427 1.00a 1.24b 1.21b 0.060 0.00441 12862531 ASB8 ankyrin repeat and SOCS box-containing 8 1.00a 1.09b 1.02a 0.024 0.00444 12808054 MGC160046 hypothetical LOC527341 1.00a 0.91a 1.08a 0.045 0.00447 12825125 OXSM 3-oxoacyl-ACP synthase, mitochondrial 1.00a 0.84b 0.92a 0.046 0.00448 12861747 GLS2 glutaminase 2 (liver, mitochondrial) 1.00a 0.43b 0.42b 0.246 0.00452 12905830 NSDHL NAD(P) dependent steroid dehydrogenase-like 1.00a 0.85b 0.77b 0.062 0.00452 12868232 KLRF1 killer cell lectin-like receptor subfamily F, member 1 1.00a 1.65b 1.47b 0.122 0.00453 12718070 NMT2 N-myristoyltransferase 2 1.00a 0.75b 0.79b 0.075 0.00454
Table 6. 1 (continued) 12690470 MNS1 meiosis-specific nuclear structural 1 1.00a 0.77b 0.74b 0.084 0.00454 12718315 BCAS1 breast carcinoma amplified sequence 1 1.00a 0.75b 0.74b 0.087 0.00455 12802696 LOC532291 similar to hCG1805526 1.00a 1.12ab 1.23b 0.051 0.00461 12720558 ZNF335 zinc finger protein 335 1.00a 1.17b 1.08a 0.042 0.00462 12745580 PEBP1 phosphatidylethanolamine binding protein 1.00a 0.48b 0.65b 0.175 0.00462 12747213 MGC165715 hypothetical LOC530484 1.00a 1.16b 1.26b 0.055 0.00466 12850767 VPS41 vacuolar protein sorting 41 homolog (S. cerevisiae) 1.00a 0.85b 0.86b 0.045 0.00467 12812117 FAHD1 fumarylacetoacetate hydrolase domain containing 1 1.00a 1.09b 1.12b 0.027 0.00467 12819469 SHOC2 soc-2 suppressor of clear homolog (C. elegans) 1.00a 1.09b 1.00a 0.028 0.00467 12701607 ANAPC1 anaphase promoting complex subunit 1 1.00a 1.16b 1.04a 0.038 0.00468 194 12860625 CSF2RB colony stimulating factor 2 receptor, beta 1.00a 0.94a 1.19c 0.061 0.00468
12872704 LOC782350 similar to histone cluster 1, H2bd 1.00a 0.77b 0.67b 0.108 0.00469 12729629 REXO2 REX2, RNA exonuclease 2 homolog (S. cerevisiae) 1.00a 1.37b 1.22b 0.078 0.00476 12747381 PTPN11 protein tyrosine phosphatase, non-receptor type 11 1.00a 1.18b 1.12b 0.043 0.00479 12796656 GOLGA4 golgin A4 1.00a 1.17b 1.14b 0.043 0.00481 12881383 SH3RF2 SH3 domain containing ring finger 2 1.00a 0.89ab 0.79b 0.061 0.00484 12733108 BCL9L B-cell CLL lymphoma 9-like 1.00a 0.84b 0.78b 0.061 0.00484 12872721 LOC784077 similar to MGC138009 protein 1.00a 0.41b 0.34b 0.281 0.00485 12712881 MZT1 mitotic spindle organizing protein 1 1.00a 0.98a 0.85c 0.048 0.00485 12808262 PTPRM protein tyrosine phosphatase, receptor type, M 1.00a 0.85b 0.93a 0.036 0.00488 12683809 CDV3 CDV3 homolog (mouse) 1.00a 1.18b 1.16b 0.046 0.00490 12738972 DEGS1 degenerative spermatocyte homolog 1, lipid desaturase 1.00a 1.21b 1.11b 0.048 0.00490
Table 6. 1 (continued) 12810901 PDAP1 PDGFA associated protein 1 1.00a 1.15b 1.13b 0.040 0.00493 12759124 NAE1 NEDD8 activating enzyme E1 subunit 1 1.00a 1.19b 1.14b 0.041 0.00494 12727049 C15H11orf49 chromosome 11 open reading frame 49 1.00a 0.84b 0.93a 0.045 0.00494 12829664 MS4A8B membrane-spanning 4-domains, subfamily A, member 8B 1.00a 1.32b 1.26b 0.077 0.00495 12780084 DPP4 dipeptidyl-peptidase 4 1.00a 0.90b 0.86b 0.041 0.00498 12878322 Mar2 membrane-associated ring finger (C3HC4) 2 1.00a 0.92b 0.88b 0.033 0.00498 12740864 RGS1 regulator of G-protein signaling 1 1.00a 0.79ab 0.64b 0.119 0.00501 12856635 LOC100336846 enterophilin-2L-like 1.00a 1.02a 0.81c 0.072 0.00502 12733478 LMO2 LIM domain only 2 (rhombotin-like 1) 1.00a 1.01a 1.14c 0.040 0.00502 12776233 CAB39 calcium binding protein 39 1.00a 1.13b 1.10b 0.031 0.00504 195 12814923 MGC140681 hypothetical protein LOC617444 1.00a 1.11b 1.15b 0.031 0.00505
12758448 ANKRD11 ankyrin repeat domain 11 1.00a 0.87b 0.86b 0.044 0.00505 12703154 LHX2 LIM homeobox 2 1.00a 0.82b 0.94a 0.054 0.00511 12853718 SNX10 sorting nexin 10 1.00a 1.31b 1.28b 0.076 0.00512 12824325 KLKB1 kallikrein B, plasma (Fletcher factor) 1 1.00a 0.75b 0.75b 0.086 0.00516 12763347 SPAG7 sperm associated antigen 7 1.00a 1.11b 0.98a 0.036 0.00516 12747840 GAB1 GRB2-associated binding protein 1 1.00a 0.88b 0.93b 0.034 0.00517 12696363 MDGA2 MAM domain containing glycosylphosphatidylinositol anchor 2 1.00a 0.88b 1.06a 0.047 0.00520 12756387 RPS16 ribosomal protein S16 1.00a 0.87b 0.95a 0.035 0.00520 12853522 ZNF786 zinc finger protein 786 1.00a 0.82b 0.88b 0.053 0.00522 12909597 KIR3DL2 killer cell immunoglobulin-like receptor, three domain 1.00a 0.80b 0.79b 0.065 0.00523 12856366 LOC100296778 similar to NKG2-D 1.00a 1.69b 1.24a 0.129 0.00527
Table 6. 1 (continued) 12689102 AVEN apoptosis, caspase activation inhibitor 1.00a 1.25b 1.19b 0.060 0.00528 12718774 TOMM34 translocase of outer mitochondrial membrane 34 1.00a 1.22b 1.18b 0.056 0.00529 12805840 PRP9 prolactin-related protein IX 1.00a 1.36b 1.30b 0.086 0.00529 12867888 CDK17 cyclin-dependent kinase 17 1.00a 1.07a 0.94a 0.037 0.00530 12800263 FLNB filamin B, beta 1.00a 0.81b 0.82b 0.062 0.00531 12707032 HNRPLL heterogeneous nuclear ribonucleoprotein L-like 1.00a 1.15b 1.03a 0.034 0.00531 12689859 LOC522864 similar to KIAA1370 1.00a 0.93a 0.74c 0.088 0.00533 12789614 FAH fumarylacetoacetate hydrolase (fumarylacetoacetase) 1.00a 0.82b 0.86b 0.054 0.00534 12846714 CELSR2 cadherin, EGF LAG seven-pass G-type receptor 2 1.00a 0.91a 1.08a 0.042 0.00537 12847775 GPR89 G protein-coupled receptor 89 1.00a 0.96a 0.89c 0.031 0.00540 196 12841542 UGT1A1 UDP glucuronosyltransferase 1 family, polypeptide A1 1.00a 0.87b 0.88b 0.039 0.00540
12809133 BCL2 B-cell CLL lymphoma 2 1.00a 0.74b 0.77b 0.077 0.00541 12849811 ABP1 amiloride binding protein 1 (amine oxidase (copper-containing)) 1.00a 0.67b 0.80b 0.092 0.00542 12874951 PDS5A PDS5, regulator of cohesion maintenance, homolog A 1.00a 1.13b 1.11b 0.034 0.00544 12856332 MIR331 microRNA mir-331 1.00a 1.21b 1.34b 0.079 0.00545 12885849 ARRDC2 arrestin domain containing 2 1.00a 0.81b 0.85b 0.055 0.00546 12710632 N4BP2L1 NEDD4 binding protein 2-like 1 1.00a 0.64b 0.70b 0.123 0.00546 12690566 PAPD4 PAP associated domain containing 4 1.00a 1.12b 1.12b 0.028 0.00549 12791710 SNRPN small nuclear ribonucleoprotein polypeptide N 1.00a 1.15b 1.08ab 0.038 0.00554 12833317 PNPLA2 patatin-like phospholipase domain containing 2 1.00a 0.71b 0.72b 0.101 0.00555 12747873 RAN RAN, member RAS oncogene family 1.00a 1.12b 1.08b 0.030 0.00557 12764643 USP32 ubiquitin specific peptidase 32 1.00a 1.13b 1.05a 0.033 0.00559
Table 6. 1 (continued) 12779699 NCKAP5 NCK-associated protein 5 1.00a 0.58b 0.62b 0.138 0.00563 12829088 LOC100126230 JY-1 1.00a 1.12b 0.97a 0.042 0.00566 12804005 LOC787269 similar to histone cluster 1, H2bd 1.00a 1.42b 1.33b 0.100 0.00567 12727354 CRY2 cryptochrome 2 (photolyase-like) 1.00a 0.81b 0.80b 0.064 0.00571 12887765 CCNH cyclin H 1.00a 1.20b 1.07a 0.050 0.00573 12683496 ITGB5 integrin, beta 5 1.00a 0.82b 0.79b 0.062 0.00578 12855131 MPP6 membrane protein, palmitoylated 6 1.00a 1.15b 1.17b 0.043 0.00581 12761572 ABCA10 ATP-binding cassette, sub-family A (ABC1), member 10 1.00a 0.74b 0.98a 0.082 0.00582 12887980 RAB24 RAB24, member RAS oncogene family 1.00a 1.06a 0.93a 0.037 0.00584 12898602 COQ3 coenzyme Q3 homolog, methyltransferase (S. cerevisiae) 1.00a 0.91ab 0.85b 0.046 0.00584 197 12888287 MRPL34 mitochondrial ribosomal protein L34 1.00a 1.04a 1.10c 0.025 0.00585
12905589 GPR143 G protein-coupled receptor 143 1.00a 1.08a 1.25c 0.060 0.00588 12756638 RPL18 ribosomal protein L18 1.00a 0.87b 0.90b 0.035 0.00589 12823815 DLC1 deleted in liver cancer 1 1.00a 0.67b 0.71b 0.113 0.00595 12825006 FAT1 FAT tumor suppressor homolog 1 (Drosophila) 1.00a 1.46b 1.57b 0.125 0.00596 12833243 SIAE sialic acid acetylesterase 1.00a 0.77b 0.80b 0.077 0.00596 12844695 ERMAP erythroblast membrane-associated protein 1.00a 1.13ab 1.28b 0.064 0.00601 12827991 OIT3 oncoprotein induced transcript 3 1.00a 0.81b 0.85b 0.056 0.00602 12710699 CUL4A cullin 4A 1.00a 1.19b 1.13b 0.044 0.00611 12729909 PTPMT1 protein tyrosine phosphatase, mitochondrial 1 1.00a 1.18b 1.09ab 0.044 0.00611 12838532 STK40 serine threonine kinase 40 1.00a 1.19b 1.20b 0.049 0.00614 12726088 SLC26A7 solute carrier family 26, member 7 1.00a 0.77b 0.73b 0.092 0.00616
Table 6. 1 (continued) 12708387 ZFP36L2 zinc finger protein 36, C3H type-like 2 1.00a 0.79b 0.82b 0.067 0.00618 12797177 XCR1 chemokine (C motif) receptor 1 1.00a 0.74b 0.81b 0.080 0.00618 12862614 LOC618614 similar to BIK1 1.00a 1.16b 1.00a 0.045 0.00619 12717327 PTF1A pancreas specific transcription factor, 1a 1.00a 0.90a 1.14a 0.067 0.00619 12772043 LSM12 LSM12 homolog (S. cerevisiae) 1.00a 1.11b 1.04a 0.024 0.00621 12875625 C6H4orf34 chromosome 4 open reading frame 34 1.00a 1.26b 1.27b 0.070 0.00621 12727117 TEX12 testis expressed 12 1.00a 0.58b 0.67b 0.150 0.00624 12709207 WBP4 WW domain binding protein 4 (formin binding protein 21) 1.00a 1.22b 1.08a 0.048 0.00625 12823868 ODZ3 odz, odd Oz ten-m homolog 3 (Drosophila) 1.00a 0.92a 0.80c 0.062 0.00630 12750723 NIP7 nuclear import 7 homolog (S. cerevisiae) 1.00a 1.28b 1.18b 0.066 0.00631 198 12735710 ERRFI1 ERBB receptor feedback inhibitor 1 1.00a 0.76b 0.72b 0.084 0.00635
12866101 DUSP6 dual specificity phosphatase 6 1.00a 1.40ab 2.09b 0.200 0.00636 12816117 C25H16ORF42 chromosome 16 open reading frame 42 1.00a 1.14b 1.11b 0.036 0.00638 12766383 CD300LD CD300 molecule like family member D 1.00a 1.37b 1.24b 0.079 0.00640 12721208 LOC782922 similar to prostaglandin F synthetase II 1.00a 2.02b 2.07b 0.220 0.00643 12885197 CREB3L3 cAMP responsive element binding protein 3-like 3 1.00a 0.65b 0.67b 0.129 0.00646 12692887 LOC100140532 similar to novel ankyrin repeat domain containing protein 1.00a 1.11a 1.33c 0.074 0.00647 12865664 MAPK12 mitogen-activated protein kinase 12 1.00a 1.14b 0.93a 0.059 0.00653 12834051 MAP4K2 mitogen-activated protein kinase kinase kinase kinase 2 1.00a 1.13b 1.11b 0.033 0.00654 12749561 MMP2 matrix metallopeptidase 2 1.00a 0.86b 0.79b 0.064 0.00655 12727888 LOC514367 similar to olfactory receptor MOR239-1 1.00a 1.04a 0.86c 0.055 0.00658 12898166 MYO6 myosin VI 1.00a 0.74b 0.77b 0.088 0.00660
Table 6. 1 (continued) 12752345 PARD6A par-6 partitioning defective 6 homolog alpha (C. elegans) 1.00a 0.86b 0.97a 0.039 0.00661 12708732 ZNF828 zinc finger protein 828 1.00a 0.84b 0.86b 0.048 0.00664 12691905 TMEM55B transmembrane protein 55B 1.00a 0.94a 0.83c 0.055 0.00665 12744965 LOC789355 similar to glutathione S-transferase, theta 3 1.00a 0.74b 0.77b 0.089 0.00666 12743889 NOS1 nitric oxide synthase 1 (neuronal) 1.00a 1.02a 1.18c 0.047 0.00668 12787588 FBXL7 F-box and leucine-rich repeat protein 7 1.00a 0.77b 0.88ab 0.070 0.00669 12704542 VAMP8 vesicle-associated membrane protein 8 (endobrevin) 1.00a 1.08ab 1.16b 0.039 0.00676 12772333 SPATA22 spermatogenesis associated 22 1.00a 0.69ab 0.48b 0.206 0.00680 12854099 ASNS asparagine synthetase (glutamine-hydrolyzing) 1.00a 1.17a 1.75c 0.145 0.00681 12856701 CS citrate synthase 1.00a 1.33b 1.16ab 0.072 0.00684 199 12759033 UBE2M ubiquitin-conjugating enzyme E2M (UBC12 homolog, yeast) 1.00a 1.30b 1.16b 0.071 0.00688
12853594 LOC506984 similar to LCHN protein 1.00a 0.89b 1.02a 0.038 0.00690 12696405 SPTLC2 serine palmitoyltransferase, long chain base subunit 2 1.00a 1.15b 1.20b 0.048 0.00692 12861924 C5H12orf41 chromosome 12 open reading frame 41 1.00a 0.92b 0.88b 0.037 0.00694 12844716 LOC514233 similar to cellular retinol binding protein 1 1.00a 0.82b 0.84b 0.051 0.00696 12902805 BGN biglycan 1.00a 0.85b 0.92ab 0.043 0.00698 12791683 MFGE8 milk fat globule-EGF factor 8 protein 1.00a 0.83b 0.89b 0.050 0.00700 12681678 DZIP3 DAZ interacting protein 3, zinc finger 1.00a 0.70b 0.72b 0.106 0.00701 12835883 SLAMF1 signaling lymphocytic activation molecule family member 1 1.00a 0.74b 0.85ab 0.081 0.00701 12773457 BAHCC1 BAH domain and coiled-coil containing 1 1.00a 0.97a 1.14c 0.051 0.00703 12706080 SPRED2 sprouty-related, EVH1 domain containing 2 1.00a 1.15b 1.12b 0.040 0.00706 12737028 BTG2 BTG family, member 2 1.00a 0.73b 0.66b 0.121 0.00706
Table 6. 1 (continued) 12758789 ZNF565 zinc finger protein 565 1.00a 0.89b 0.90b 0.035 0.00708 12707445 LMAN2L lectin, mannose-binding 2-like 1.00a 0.80b 0.85b 0.061 0.00712 12778603 ATP5G3 ATP synthase, H+ transporting, mitochondrial Fo complex, subunit C3 1.00a 1.14b 1.10b 0.033 0.00712 12742795 HPD 4-hydroxyphenylpyruvate dioxygenase 1.00a 0.92b 0.92b 0.027 0.00713 12760260 LOC100138645 similar to serum amine oxidase 1.00a 0.82b 0.77b 0.075 0.00714 12867807 CSRP2 cysteine and glycine-rich protein 2 1.00a 1.72b 1.33ab 0.140 0.00717 12723845 NKAIN3 Na+ K+ transporting ATPase interacting 3 1.00a 0.75b 0.77b 0.086 0.00717 12801263 PPARD peroxisome proliferator-activated receptor delta 1.00a 0.86b 0.84b 0.051 0.00718 12781910 ZAK sterile alpha motif and leucine zipper containing kinase A 1.00a 1.22b 1.22b 0.062 0.00720 12783946 SATB2 SATB homeobox 2 1.00a 0.81b 0.99a 0.065 0.00720 200 12802333 LOC520603 similar to KIAA0319 1.00a 1.10b 1.09b 0.029 0.00721
12786918 TPPP tubulin polymerization promoting protein 1.00a 0.85b 0.97a 0.044 0.00723 12713839 YWHAB tyrosine 3-monooxygenase tryptophan 5-monooxygenase activation protein β 1.00a 1.13b 1.14b 0.036 0.00724 12765241 CTNS cystinosis, nephropathic 1.00a 0.80b 0.87b 0.058 0.00726 12711651 NUFIP1 nuclear fragile X mental retardation protein interacting protein 1 1.00a 1.09a 0.84c 0.078 0.00727 12684080 CLDN11 claudin 11 1.00a 0.81b 1.00a 0.071 0.00727 12815419 COG7 component of oligomeric golgi complex 7 1.00a 0.86b 0.95a 0.043 0.00728 12683064 LOC100336374 ST6 beta-galactosamide alpha-2,6-sialyltranferase 1-lik 1.00a 1.24b 1.32b 0.078 0.00729 12697339 LOC617365 similar to CG11638 CG11638-PA 1.00a 0.90a 0.78c 0.065 0.00729 12685166 S100B S100 calcium binding protein B 1.00a 0.78b 0.83b 0.068 0.00730 12852262 IMMP2L IMP2 inner mitochondrial membrane peptidase-like 1.00a 0.83b 0.85b 0.054 0.00731 12728148 POU2F3 POU class 2 homeobox 3 1.00a 0.70b 0.69b 0.116 0.00736
Table 6. 1 (continued) 12867705 RIMKLB ribosomal modification protein rimK-like family member B 1.00a 0.80b 0.84b 0.058 0.00737 12687793 LOC100300401 similar to odorant receptor MOR83 1.00a 0.96a 0.77c 0.080 0.00741 12773167 RAC3 ras-related C3 botulinum toxin substrate 3 1.00a 0.74b 1.12a 0.111 0.00742 12835713 LOC528929 olfactory receptor MOR103-4-like 1.00a 0.76b 0.85b 0.069 0.00743 12702617 BARHL1 BarH-like homeobox 1 1.00a 0.94a 0.83c 0.046 0.00743 12708125 KLF11 Kruppel-like factor 11 1.00a 0.75b 0.77b 0.085 0.00743 12742187 RILPL1 Rab interacting lysosomal protein-like 1 1.00a 1.30b 1.20b 0.065 0.00744 12723373 FAM84B family with sequence similarity 84, member B 1.00a 0.99a 1.25c 0.077 0.00745 12852834 HECW1 HECT, C2 and WW domain containing E3 ubiquitin protein l 1.00a 0.89b 1.03a 0.035 0.00747 12882685 LOC100295390 hypothetical protein LOC100295390 1.00a 1.01a 0.78c 0.082 0.00748 201 12759859 LOC785630 zinc finger protein 665-like 1.00a 0.76b 0.77b 0.084 0.00748
12852035 GCK glucokinase (hexokinase 4) 1.00a 0.86b 0.97a 0.039 0.00748 12751673 VASP vasodilator-stimulated phosphoprotein 1.00a 1.17b 1.11b 0.044 0.00750 12699728 C11H2ORF7 chromosome 2 open reading frame 7 ortholog 1.00a 1.21b 1.10ab 0.052 0.00751 12896756 QKI quaking homolog, KH domain RNA binding (mouse) 1.00a 1.19b 1.18b 0.051 0.00751 12882142 PPIP5K2 diphosphoinositol pentakisphosphate kinase 2 1.00a 1.32b 1.23b 0.075 0.00753 12704020 PPP3R1 protein phosphatase 3, regulatory subunit B, alpha 1.00a 1.10b 1.14b 0.035 0.00755 12888026 GADD45B growth arrest and DNA-damage-inducible, beta 1.00a 0.52b 0.46b 0.228 0.00755 12771716 ADAP2 ArfGAP with dual PH domains 2 1.00a 0.79b 0.71b 0.098 0.00759 12812241 C25H7orf42 chromosome 7 open reading frame 42 ortholog 1.00a 1.15b 1.06a 0.038 0.00761 12866902 NTF3 neurotrophin 3 1.00a 1.21b 1.23b 0.063 0.00764 12851653 LOC540061 hypothetical LOC540061 1.00a 0.85b 0.77b 0.074 0.00765
Table 6. 1 (continued) 12697689 THAP10 THAP domain containing 10 1.00a 1.07a 1.21c 0.054 0.00769 12738995 G0S2 G0 G1switch 2 1.00a 0.67b 0.73b 0.114 0.00770 12758260 PAF1 Paf1, RNA polymerase II associated factor, homolog 1.00a 0.94a 0.85c 0.041 0.00772 12895180 TRAF1 TNF receptor-associated factor 1 1.00a 0.86b 1.03a 0.057 0.00773 12899976 PTPRK protein tyrosine phosphatase, receptor type, K 1.00a 0.78b 0.79b 0.068 0.00776 12746075 RFC5 replication factor C (activator 1) 5, 36.5kDa 1.00a 0.87b 0.92b 0.038 0.00781 12767763 KRT14 keratin 14 1.00a 0.90a 1.10a 0.056 0.00781 12885741 NHP2 NHP2 ribonucleoprotein homolog (yeast) 1.00a 1.17b 1.10b 0.041 0.00785 12685136 DCBLD2 discoidin, CUB and LCCL domain containing 2 1.00a 0.91ab 0.84b 0.047 0.00785 12687183 LOC783458 keratin associated protein-like 1.00a 1.17b 1.16b 0.049 0.00792 202 12684143 ZBTB20 zinc finger and BTB domain containing 20 1.00a 0.80b 0.80b 0.068 0.00794
12723435 TMEM65 transmembrane protein 65 1.00a 1.19b 1.18b 0.051 0.00800 12903824 ZNF449 zinc finger protein 449 1.00a 1.10a 1.31c 0.080 0.00805 12901808 SH3YL1 SH3 domain containing, Ysc84-like 1 (S. cerevisiae) 1.00a 0.78b 0.86b 0.067 0.00806 12714079 PSMA7 proteasome (prosome, macropain) subunit, alpha type, 7 1.00a 1.17b 1.06a 0.043 0.00813 12769741 TM4SF5 transmembrane 4 L six family member 5 1.00a 0.88b 0.86b 0.046 0.00814 12733522 APLNR apelin receptor 1.00a 0.80b 0.78b 0.074 0.00818 12709906 TPP2 tripeptidyl peptidase II 1.00a 1.15b 1.13b 0.042 0.00820 12681589 KPNA4 karyopherin alpha 4 (importin alpha 3) 1.00a 1.20b 1.14b 0.051 0.00823 12849356 SLC4A2 solute carrier family 4, anion exchanger, member 2 (ery 1.00a 1.14b 1.11b 0.037 0.00827 12717971 CST3 cystatin C 1.00a 0.71b 0.83ab 0.095 0.00828 12879771 NANOS3 nanos homolog 3 (Drosophila) 1.00a 1.03a 1.13c 0.037 0.00829
Table 6. 1 (continued) 12697921 WDR5 WD repeat domain 5 1.00a 1.21b 1.08a 0.053 0.00829 12897782 MAN1A1 mannosidase, alpha, class 1A, member 1 1.00a 1.11b 1.15b 0.038 0.00832 12882777 LOC100299578 hypothetical protein LOC100299578 1.00a 1.26b 1.32b 0.078 0.00832 12864320 GABARAPL1 GABA(A) receptor-associated protein like 1 1.00a 0.89b 0.89b 0.037 0.00836 12758504 SULT2A1 sulfotransferase family, cytosolic, 2A, dehydroepiandrostero 1.00a 1.17b 1.04a 0.046 0.00837 12752730 ZNF19 zinc finger protein 19 1.00a 0.70b 0.71b 0.114 0.00837 12848053 LOC784007 similar to LOC496253 protein 1.00a 0.94a 0.84c 0.050 0.00839 12906051 ERCC6L excision repair cross-complementing rodent repair deficiency 1.00a 1.28b 1.15ab 0.070 0.00841 12865085 TMCC3 transmembrane and coiled-coil domain family 3 1.00a 0.92a 0.78c 0.077 0.00842 12846075 S100A9 S100 calcium binding protein A9 1.00a 1.23b 1.21b 0.060 0.00842 203 12858450 RAB21 RAB21, member RAS oncogene family 1.00a 1.08b 1.02a 0.023 0.00843
12910540 LOC784285 similar to TSR2, 20S rRNA accumulation, homolog 1.00a 1.31b 1.22b 0.071 0.00847 12848043 ROR1 receptor tyrosine kinase-like orphan receptor 1 1.00a 0.80b 0.93a 0.060 0.00852 12686304 HES1 hairy and enhancer of split 1, (Drosophila) 1.00a 1.13ab 1.29b 0.073 0.00853 12709739 PRHOXNB parahox cluster neighbor 1.00a 0.87b 0.98a 0.034 0.00854 12806885 LOC618143 similar to histone cluster 1, H2ad 1.00a 1.23b 1.08a 0.059 0.00858 12847648 MYEOV2 hypothetical protein LOC617407 1.00a 1.14b 1.11b 0.038 0.00860 12723962 POLR2K polymerase (RNA) II (DNA directed) polypeptide K, 7.0kDa 1.00a 0.99a 0.88c 0.041 0.00861 12866188 GPRC5A G protein-coupled receptor, family C, group 5, member A 1.00a 0.82ab 0.72b 0.093 0.00861 12722615 SLC45A4 solute carrier family 45, member 4 1.00a 1.24b 1.12ab 0.058 0.00869 12805720 C2 complement component 2 1.00a 0.82b 0.95a 0.051 0.00871 12884176 ZNF692 zinc finger protein 692 1.00a 0.88b 0.90b 0.036 0.00873
Table 6. 1 (continued) 12887351 SNCAIP synuclein, alpha interacting protein 1.00a 0.82b 0.81b 0.066 0.00874 12689424 TMEM62 transmembrane protein 62 1.00a 1.15b 1.17b 0.044 0.00874 12714168 KLF6 Kruppel-like factor 6 1.00a 1.00a 0.77c 0.085 0.00876 12892819 GATA4 GATA binding protein 4 1.00a 0.92a 1.11a 0.053 0.00876 12810829 THOC6 THO complex 6 homolog (Drosophila) 1.00a 1.03a 1.14c 0.042 0.00879 12839104 AMIGO1 adhesion molecule with Ig-like domain 1 1.00a 0.81b 0.87b 0.056 0.00882 12837438 PARS2 prolyl-tRNA synthetase 2, mitochondrial (putative) 1.00a 0.83b 0.88b 0.055 0.00887 12825587 MLF1IP MLF1 interacting protein 1.00a 0.63b 0.63b 0.150 0.00890 12700220 EML6 echinoderm microtubule associated protein like 6 1.00a 0.78ab 0.59b 0.142 0.00890 12801174 POU5F1 POU class 5 homeobox 1 1.00a 1.07a 0.87c 0.060 0.00896 204 12852821 LOC617841 notch1-induced protein-like 1.00a 0.79b 0.82b 0.062 0.00901
12759864 LOC785881 similar to gene model 1082, (NCBI) 1.00a 1.26b 1.15b 0.065 0.00901 12729213 COPB1 coatomer protein complex, subunit beta 1 1.00a 1.18b 1.05a 0.047 0.00902 12822968 ARL3 ADP-ribosylation factor-like 3 1.00a 0.80b 0.85b 0.065 0.00913 12692077 RAD51L1 RAD51-like 1 (S. cerevisiae) 1.00a 0.77b 0.89ab 0.069 0.00916 12755466 LOC100335305 ribosomal protein S29-like 1.00a 0.78b 0.84b 0.068 0.00920 12808814 ONECUT2 similar to one cut domain, family member 2 1.00a 1.20b 1.14b 0.050 0.00921 12754803 ZNF226 zinc finger protein 226 1.00a 0.74b 1.08a 0.114 0.00922 12862788 PPP1R1A protein phosphatase 1, regulatory (inhibitor) subunit 1A 1.00a 0.78b 0.90ab 0.069 0.00923 12775460 BZW1 basic leucine zipper and W2 domains 1 1.00a 1.17b 1.12b 0.041 0.00923 12733168 PIH1D2 PIH1 domain containing 2 1.00a 1.14b 0.99a 0.048 0.00925 12739202 LOC510385 hypothetical LOC510385 1.00a 0.89b 0.87b 0.041 0.00925
Table 6. 1 (continued) 12698206 EHBP1 hypothetical LOC533149 1.00a 0.87b 0.92b 0.039 0.00928 12715418 BASE breast cancer and salivary gland expression protein 1.00a 0.95a 1.14c 0.050 0.00929 12696439 MAP3K9 mitogen-activated protein kinase kinase kinase 9 1.00a 0.92a 1.11a 0.052 0.00937 12885957 NACC1 nucleus accumbens associated 1, BEN and BTB (POZ) domain conta 1.00a 1.13b 1.08b 0.032 0.00938 12753342 CHD9 chromodomain helicase DNA binding protein 9 1.00a 1.08a 0.92a 0.050 0.00939 12679945 ABCC5 ATP-binding cassette, sub-family C (CFTRMRP), member 5 1.00a 0.75b 0.82b 0.082 0.00941 12746112 PXMP2 peroxisomal membrane protein 2, 22kDa 1.00a 0.91ab 0.86b 0.044 0.00942 12839522 LOC530689 similar to MGC157062 protein 1.00a 1.10ab 1.17b 0.046 0.00943 12821472 PRDX3 peroxiredoxin 3 1.00a 1.33b 1.43b 0.095 0.00946 12794243 MIR2372 microRNA mir-2372 1.00a 0.85ab 0.69b 0.109 0.00947 205 12863639 MIR2424-1 microRNA mir-2424-1 1.00a 0.80b 0.90ab 0.062 0.00947
12797303 MGC137053 hypothetical protein MGC137053 1.00a 0.86b 0.90b 0.044 0.00952 12779379 TMEM169 transmembrane protein 169 1.00a 0.74b 0.70b 0.110 0.00960 12769297 UNK unkempt homolog (Drosophila) 1.00a 0.89b 0.91b 0.033 0.00963 12702773 GALM galactose mutarotase (aldose 1-epimerase) 1.00a 0.82b 1.01a 0.069 0.00965 12693610 COL4A3BP collagen, type IV, alpha 3 (Goodpasture antigen) binding protein 1.00a 1.12b 1.04a 0.034 0.00966 12840526 DAB1 disabled homolog 1 (Drosophila) 1.00a 0.61b 0.67b 0.139 0.00967 12734981 DYRK3 dual-specificity tyrosine-(Y)-phosphorylation regulated kinase 1.00a 0.71b 0.75b 0.099 0.00971 12793812 GZMH granzyme H (cathepsin G-like 2, protein h-CCPX) 1.00a 1.51b 1.29b 0.120 0.00972 12910330 LOC617695 similar to melanoma antigen family A, 10 1.00a 1.48b 1.58b 0.142 0.00975 12859994 NEDD1 neural precursor cell expressed, developmentally down-regulate 1.00a 1.25b 1.22b 0.062 0.00976 12733016 LOC538693 hypothetical LOC538693 1.00a 0.88b 1.00a 0.044 0.00977
Table 6. 1 (continued) 12779862 LOC100140504 ribonuclease P protein subunit p38-like 1.00a 1.19b 1.11b 0.049 0.00977 12790487 TTC23 tetratricopeptide repeat domain 23 1.00a 1.33b 1.20b 0.078 0.00987 12786403 CDH12 cadherin 12, type 2 (N-cadherin 2) 1.00a 1.22b 1.18b 0.061 0.00987 12681420 C1H3ORF21 chromosome 3 open reading frame 21 ortholog 1.00a 0.87b 0.95a 0.041 0.00990 12741428 WDR64 WD repeat domain 64 1.00a 0.87b 1.04a 0.056 0.00992 12772843 TRAPPC1 trafficking protein particle complex 1 1.00a 0.84b 0.90b 0.044 0.00994 12767860 JUP junction plakoglobin 1.00a 0.84b 0.95a 0.050 0.00994 12787048 FST follistatin 1.00a 1.33a 2.13c 0.189 0.00996
1The abundance of gene transcripts are reported relative to the mean expression of the Control group and are expressed as the fold change of 206 non-transformed data.
Table 6. 2 Primer information and results of real-time RT-PCR product sequence validation.
RT-PCR Product Accession Oligonucleotide Primer Design (5’ to Amplicon product Gene Gene Name identity number 3’ direction) length (bp) Accession (%) number
Hypoxanthine F:GCCAGCCGGCTACGTTAT HPRT1 NM_001034035.2 256 100% MK396253 phosphoribosyltransferase R:ATCCAACAGGTCGGCAAAGA
Tyrosine 3- 207 monooxygenase/tryptophan F:TTGATCCCCAACGCTTCACA
YWHAZ NM_174814.2 208 100% MK396254 5-monooxygenase R:AGTTAAGGGCCAGACCCAGT activation protein zeta
F:GGCAAGTCCATCTATGGCGA PPIA Peptidylprolyl isomerase A NM_178320.2 240 99% MK309342 R:TTGCTGGTCTTGCCATTCCT
F:TCCACTACCCCCAAAAACGG PLOD1 Lysyl hydroxlase 1 NM_174148.1 218 99% MK518348 R:GGCATCCACGCTGAAGTAGT
Table 6. 2 (continued)
Pyrroline-5-carboxylate F:GGGGGCAAGAACTTCCACTT ALDH4A1 NM_001105646.1 242 100% MK526976 dehydrogenase R:GACTTGGCATCAATCACGGC
Pyrroline-5-carboxylate F:AGCGATCTCCAGGGGGTAAA ALDH18A1 NM_001046181.1 226 100% MK526977 synthetase R:TGCCACCCATTCCAACTCTG
F:CGGGAACTTGCATGGACAAC ARG1 Arginase 1 NM_001046154.1 314 100% MK533691 R:GCGTGAAAGATGGGTCCAGT 208
F:AGGGGGACTGACCTATCGAG ARG2 Arginase 2 NM_001017942.1 218 100% MK533692 R:TGGGAGTTGGAAGTTGGTCG
Carbamoyl-phosphate F: CTGACCCTGCTTACAAGGGG CPS1 NM_001192258.1 212 100% MK533700 synthase 1 R: TTCCCGTAGCCACTGTCCTA
F: CTGGACATGCCCATCCTTGA RHBG Rh family B glycoprotein NM_174723.2 231 100% MK533701 R: TGTGACAAACAGCCCGAAGA
Table 6. 2 (continued)
F: TCCTTGGGCTTTCTTATGCCA Sodium-coupled neutral SNAT2 NM_001082424.1 R: 352 100% MK533702 amino acid transporter 2 ATGAGCACCAGTGATACCAGC
F:TCTGGACAAGATGGGCAACA GLS1 Glutaminase 1 NM_001077964.2 R:TCTCTCCCAGACTTTCCATTC 278 100% MK533693 TA
F:ACATGGGTTTCAGCAATGCC GLS2 Glutaminase 2 NM_001192274.1 175 100% MK542014 R:CTGCCCGATTCACAGGTCAC 209
F:TCCACTACCCCCAAAAACGG GLUD1 Glutamate dehydrogenase 1 NM_182652.2 274 100% MK533694 R:GGCATCCACGCTGAAGTAGT
F:AAAGAGCAGTGGAAGGACA NR3C1 Glucocorticoid receptor NM_001206634.1 GC 261 100% MK309339 R:CCAGCGTAGGTGTGAGTTGT
F:GCGGGACCTGAAGACACTTT NAGS N-acetylglutamate synthase XM_002696039.5 T 390 100% MK533695 R:TGCTTGTCCTCCCTTGGGTA
Table 6. 2 (continued)
F: ATGTTAGGGACCAGTGTGCG OAT Ornithine aminotransferase NM_001034240.1 R: 211 99% MK533696 ACACATGGGAAAAGAGCGGT
Ornithine mitochondrial F:CGACTGCAGACCATGTACGA ORNT1 NM_001046326.1 220 100% MK533697 transporter, SLC25A15 R:CGTCTTTCGATCTCCCCGAG
Ornithine F:TCACAGATACAGCCCGTGTG OTC NM_177487.2 279 100% MK533698 carbamoyltransferase R:CCTGAAGGTGCATCCCGAAT 210
F:CGCCAGGTGTACTTTGGACA PRODH Proline dehydrogenase 1 NM_001075185.1 319 100% MK533699 R:AAAGGAGATCGGTGTGAGGC
Pyrroline-5-carboxylate F:ACCAGGAGAAGGTCTCACCA PYCR1 NM_001014957.1 245 100% MK542012 reductase 1 R:CGTGAGGACACCCTGTGTAG
Pyrroline-5-carboxylate F: GGGAGGGTGCAACAGTGTAT PYCR2 NM_001075181.1 400 100% MK542013 reductase 2 R: CAGGAGGCCTCAACCG
Table 6. 3 Top IPA-identified canonical pathways of genes differentially expressed from liver of steers grazing endophyte-infected tall fescue
and supplemented with 3 mg Se/d in vitamin-mineral mixes as sodium selenite (ISe, n = 6), SEL-PLEX (OSe, n = 8), or an 1:1 blend of ISe
and OSe (MIX, n = 7).
Canonical pathway Gene symbol Ratio1 -log(P-value)
HER-2 Signaling in Breast GAB1,PTPN11,PRKCD,MDM2,MMP2,KRAS,MAP3K5,PARD6A,ITGB5,PRKCA 0.108 4.37 Cancer Tyrosine Degradation I HPD,TAT,FAH 0.6 3.97 211
PEDF Signaling NFKBIA,GAB1,PTPN11,KRAS,CHUK,MAPK12,PNPLA2,FAS,BCL2 0.1 3.74
Sumoylation Pathway TDG,NFKBIA,SP1,RAN,MDM2,MAP3K5,MAPK12,RFC5,FAS 0.1 3.74
LPS-stimulated MAPK NFKBIA,GAB1,PTPN11,PRKCD,KRAS,CHUK,MAP3K5,MAPK12,PRKCA 0.098 3.67 Signaling Induction of Apoptosis by NFKBIA,MAP3K5,CHUK,MAPK12,FAS,TRAF1,BCL2 0.125 3.62 HIV 1
1The ratio calculated as the number of differentially expressed genes (P < 0.01) in a given pathway divided by the total number of genes that make up that pathway.
Table 6. 4 IPA-identified canonical pathways of genes involved in glutamate/glutamine and nitrogen metabolism differentially-expressed
from liver of steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as sodium selenite
(ISe, n = 6), SEL-PLEX (OSe, n = 8), or an 1:1 blend of ISe and OSe (MIX, n = 7).
Canonical pathway Gene symbol Ratio1 -log(P-value)
Arginine Biosynthesis IV OAT, GLUD1 0.4 2.32
Citrulline Biosynthesis OAT, GLS2 0.25 1.89 212
Glutamine Biosynthesis I GLUL 1 1.65
Glutamine Degradation I GLS2 0.5 1.35
Glutamate Biosynthesis II GLUD1 1 1.65
Glutamate Degradation X GLUD1 1 1.65
Proline Biosynthesis II (from Arginine) OAT 0.17 0.893
1The ratio calculated as the number of differentially expressed genes (P < 0.01) in a given pathway divided by the total number of genes that make up that pathway.
Table 6. 5 Microarray and real-time RT-PCR identification of selected genes from livers of steers grazing endophyte-infected tall fescue and
supplemented with 3 mg Se/d in vitamin-mineral mixes as sodium selenite (ISe, n = 6), SEL-PLEX (OSe, n = 8), or an 1:1 blend of ISe and
OSe (MIX, n = 7 for microarray, n = 8 for RT-PCR).
RT-PCR1 Microarray1 Gene Gene name ISe MIX OSe SEM P-Value ISe MIX OSe SEM P-Value Glutamate/glutamine metabolism GLUL Glutamine synthetase 1.01a 1.37b 1.45b 0.084 0.006 1.00a 1.37b 1.32b 0.070 0.001 GLUD1 Glutamate dehydrogenase 1 1.03 1.29 1.30 0.127 0.289 1.00a 1.20b 1.16b 0.047 0.004 a b ab 213 GLS1 Glutaminase 1 1.02 0.80 0.88 0.060 0.058 1.00 1.01 0.98 0.085 0.937 a b b a b b
GLS2 Glutaminase 2, liver mitochondria 1.13 0.48 0.41 0.177 0.018 1.00 0.43 0.42 0.246 0.005 SNAT2 SLC38A2, glutamine transporter 1.01 1.13 1.02 0.064 0.364 1.00a 1.23b 1.21b 0.090 0.080 Proline metabolism PRODH Proline dehydrogenase 1 1.01 1.13 1.03 0.107 0.689 1.00a 1.17b 1.03a 0.060 0.055 PYCR1 Pyrroline-5-carboxylate reductase 1 1.01a 1.38a 2.41b 0.286 0.023 1.00a 1.25ab 1.53b 0.131 0.037 PYCR2 Pyrroline-5-carboxylate reductase 2 1.04 0.93 0.98 0.071 0.729 1.00 1.02 1.09 0.051 0.242 ALDH4A1 Pyrroline-5-carboxylate dehydrogenase 1.05 0.88 0.80 0.086 0.158 1.00 1.07 0.95 0.077 0.284 ALDH18A1 Pyrroline-5-carboxylate synthetase 1.01a 1.21b 1.29b 0.069 0.036 1.00 1.17 1.20 0.090 0.170 Urea cycle CPS1 Carbamoyl phosphate synthetase 1 1.01a 0.79b 0.79b 0.042 0.004 1.00 0.99 0.94 0.033 0.146 ARG1 Arginase 1 1.01a 0.63b 0.63b 0.064 0.001 1.00a 0.86ab 0.75b 0.103 0.061 ARG2 Arginase 2 1.02a 0.64b 0.62b 0.109 0.038 1.00a 0.83b 0.81b 0.076 0.035 OAT Ornithine aminotransferase 1.01a 0.59b 0.58b 0.053 <.0001 1.00a 0.74b 0.71b 0.090 0.002
Table 6. 5 (continued) NAGS N-acetylglutamate synthase 1.02a 0.64b 0.55b 0.081 0.002 1.00a 0.81b 0.71b 0.103 0.012 OCT Ornithine carbamoyltransferase 1.01a 0.73b 0.71b 0.068 0.011 1.00a 0.85b 0.86b 0.069 0.064 ORNT1 SLC25A15, Ornithine/arginine exchanger 1.01a 0.61b 0.64b 0.756 0.009 1.00a 0.79b 0.72b 0.128 0.062 RHBG SLC42A2, ammonia transporter 1.06 1.55 1.36 0.171 0.172 1.00a 1.32b 1.16ab 0.101 0.079 NR3C1 Glucocorticoid receptor 1.00a 0.85b 0.89b 0.040 0.039 1.00 0.99 0.94 0.146 0.629
1Data are expressed as ratio of MIX and OSe relative to ISe expression 2Means within a row that lack a common letter differ (P < 0.05).
214
Table 6. 6 Hepatic content of proteins associated with glutamate metabolism and transport in steers grazing endophyte-infected tall fescue
and supplemented with 3 mg Se/d in vitamin-mineral mixes as sodium selenite (ISe, n = 6), SEL-PLEX (OSe, n = 8), or an 1:1 blend of ISe
and OSe (MIX, n = 8)1.
Treatment2 Item3 ISe OSe MIX SEM P value
OAT 3620a 1886b 2809a 407.3 0.0303
215 EAAC1 3375 3603 4772 613.1 0.2407
GLT-1 4010 5230 4998 906.0 0.6345
GTRAP3-18 923 862 883 181.9 0.9737
ARL6IP1 8925 8359 8655 779.6 0.8817
1Values are least squares means and pooled SEM. 2Means within a row that lack a common letter differ (P < 0.05). 3Values (arbitrary densitometric units) were determined by densitometric evaluation of Western blot data (Figure 6.7)
Figure 6. 1 Immunoblot validation of rabbit IgG anti-bovine ornithine
aminotransferase (OAT)/donkey anti-rabbit IgG-horse radish peroxidase polyclonal antibody pair detection of bovine OAT1.
1Size marker is shown in lane 1. Bovine steer liver homogenates (45 μg/lane) were hybridized with either rabbit IgG anti-OAT antibody (lane 2) or rabbit IgG anti-OAT antibody that had been pre-adsorbed (μg: μg) with its antigen polypeptide (at 1:5, 1:0.005; lane 3, 4, respectively) before hybridization and then detected with donkey anti-rabbit IgG-horse radish peroxidase, as described in Materials and Methods. The apparent migration weight (Mr) markers (kDa) and Mr of a single (62 kDa) immunoreactants are indicated to the left of the immunoblots.
216
Figure 6. 2 Microarray array-array intensity correlation plot.
217
Figure 6. 3 Score-plot of principle component analysis of microarray transcriptome analysis of 21 liver samples from steers grazing endophyte-infected tall fescue and supplemented with 3 mg Se/d in vitamin-mineral mixes as sodium selenite (ISe, n=6, red sphere), SEL-PLEX (OSe, n=8, blue sphere), or an 1:1 blend of ISe and OSe
(MIX, n=7, green sphere)1.
1The red, blue, and green spheres represent linear combinations of the relative expression data, including expression values and variances, of the 26,675 gene transcripts in each Bovine GeneChip. The light red, blue, and green spheres represent the centroids of red (ISe), blue (OSe), and green (MIX) spheres, respectively.
218
Figure 6. 4 Flowchart of filtering algorithm and procedures identifying differentially expressed genes.
219
Figure 6. 5 Hierarchical cluster analysis of the 738 genes selected as differentially
expressed (ANOVA P-values of < 0.01 and false discovery rates of 33%) by the
liver of steers grazing endophyte-infected tall fescue and supplemented≤ with 3 mg
Se/d in vitamin-mineral mixes as sodium selenite (ISe, n = 6), SEL-PLEX (OSe, n =
8), or an 1:1 blend of ISe and OSe (MIX, n = 7)1.
1As indicated by the legend color box, black color in the middle represents the mean value, 0; red color represents gene expression levels above the mean expression; and green color denotes expression below the mean. The intensity of the color reflects the relative intensity of the fold change.
220
Figure 6. 6 The sequences of the real-time RT-PCR products (5’ to 3’ orientation).
Within a sequence, underlined nucleotides indicate the forward and reverse primer positions.
HPRT1: GCCAGCCGGCTACGTTATGGCGGCCCGCAGCCCCAGCGTGGTGATTAGCGATGATGA ACCAGGTTATGACCTAAATTTATTTTGTATACCCAATCATTATGCTGAGGATTTGGAGAA GGTGTTTATTCCTCATGGACTAATTATGGACAGGACCGAACGGCTGGCTCGAGATGTGA TGAAGGAGATGGGTGGCCATCACATTGTGGCCCTCTGTGTGCTCAAGGGGGGCTATAA GTTCTTTGCCGACCTGTTGGAT
YWHAZ: TTGATCCCCAACGCTTCACAAGCAGAGAGCAAAGTCTTCTATTTGAAAATGAAAGGA GACTACTACCGCTACTTGGCTGAGGTTGCAGCTGGTGATGACAAGAAAGGGATTGTGG ACCAGTCACAGCAAGCATACCAAGAAGCTTTTGAAATCAGCAAAAAGGAAATGCAAC CAACACATCCTATCAGACTGGGTCTGGCCCTTAACT
PPIA: GGCAAGTCCAATTATGGCGAGAAATTTGATGATGAGAATTTCATTTTGAAGCATACAGGTC CTGGCATCTTGTCCATGGCAAATGCTGGCCCCAACACAAATGGTTCCCAGTTTTTCATTTGC ACTGCCAAGACTGAGTGGTTGGATGGCAAGCACGTGGTCTTTGGCAAGGTGAAAGAGGGC ATGAATATTGTGGAAGCCATGGAGCGCTTTGGGTCCAGGAATGGCAAGACCAGCAA
ALDH4A1: GGGGGCAAGAACTTCCACTTTGTGCACCGCTCGGCCGACGTGGACAGCGTGGTGAGTGG GACCCTGCGCTCGGCCTTTGAGTACGGCGGCCAGAAGTGCTCAGCGTGCTCCCGCCTCTAC GCGCCCCGCTCGCTGTGGCCGCAGATCAAAGGGCGGCTGCTGGAGGAGCTCGGTGGGATC AAAGTGGGCAATCCTGCAGAGGATTTTGGGACCTTCTTCTCTGCCGTGATTGATGCCAAG TC
ALDH18A1: AGCGATCTCCAGGGGGTAAATGTTATTAGTGTTAAAGATAATGATAGCCTGGCTGCCCGTC TGGCTGTGGAAATGAAGACTGACCTCTTAATTGTTCTTTCAGATGTAGAAGGCCTCTTTGAC AGCCCCCCAGGGTCAGATGATGCAAAGCTCATTGATATATTTTATCCTGGTGATCAGCAGTC TGTGACATTCGGAACCAAGTCCAGAGTTGGAATGGGTGGCA
ARG1: CGGGAACTTGCATGGACAACCTGTGTCTTTCCTTCTGAAGGAACTAAAGGAAAAGATGC CTGAGGTCCCAGGATTCTACTGGGTGGCTCCCTGCATATCTGCCAAAGACATTGTGTATATT GGTCTGAGAGATGTGGACCCTGGGGAACACTATATTTTGAAAACTCTGGGAATTAAATACTT TTCAATGACTGAAGTGGATAAACTGGGAATTGGCAAGGTGATGGAAGAAACATTCAGCTAT
221
CTACTAGGAAGAAAGAAAAGGCCAATTCATTTGAGCTTTGATGTTGATGGACTGGACCCAT CTTTCACGC
ARG2: AGGGGGACTGACCTATCGAGAAGGCATATATATTACTGAGGAAATACACAGTACAGGGTT GCTCTCGGCCCTGGACCTCGTTGAAGTCAATCCTCGGTTGGCCGTGTCAGAGGAGGAGGCC AAGGCTACAGCCAGCCTGGCAGTGGACGTCATTGCTTCGAGTTTCGGGCAGACGAGGGAG GGAGGGCATATTGTCTACGACCAACTTCCAACTCCCA
CPS1: CTGACCCTGCTTACAAGGGGCAG AT T CTTACCAT GGCCAAT CCTATTGTTGGGAATGGTGG AGCCCCAGATACTGCTGCACTGGATGAACTGGGACTCAGCAAATATTTGGAATCTGATGGG ATTAAGGTTGCAGGTTTGCTGGTGCTGAATTATAGTGATGACTACCACCACTGGCTGGCTAC CAAGAGTCTAGGACAGTGGCTACGGGAA
RHBG: CTGGACATGCCCATCCTTGAGTCCAAACTCAAAGTCCAAGACACATGTGGTGTGCACAA CCTCCATGGGATGCCGGGGGTCCTGGGAGCCCTCCTGGGTGGCCTTGTGGCTGGGCTGGCC ACCCGTGAAGCTTATGGAGATGGCCTGGAGAGTGTGTTTCCACTCATAGCCGAGGGCCAGC GCAGTGCCACGTCTCAGGCCATGCACCAGCTCTTCGGGCTGTTTGTCACA
SNAT2： TCCTTGGGCTTTCTTATGCCATGGCTAATACTGGAATTGCTCTTTTTATAATTCTGTTGACA TTTGTGTCAATATTTTCCCTGTATTCTGTTCATCTCCTTCTGAAGACTGCCAATGAAGGAGGG TCTTTATTATATGAACAGCTGGGACATAAAGCATTTGGAATGGTTGGGAAGCTCACAGCATC TGGATCCATTACAATGCAGAACATTGGAGCTATGTCAAGCTACCTCTTCATAGTGAAATATG AGTTACCTTTGGTGATCCAGGCATTAATGAACATTGAAGATACAAATGGATTGTGGTATCTG AACGGTGACTATTTGGTTCTGCTGGTATCACTGGTGCTCAT
ASRGL1: GCCGTGTGTAGGATCTGGAGGTTACGCTGACAATGACATCGGAGCTGTCTCAACGACAG GGCACGGTGAGAGCATCCTGAAGGTGAATCTGGCCAGACTCGCGCTCTTCCACGTTGAAC AGGGAAAATCACTAGAAGAAGCTGCCAACGCATCACTGGGTCATATGAAGTCAAAGGTCA AGGGCGTAGGTGGTATCATCATGGTCAACAAAGCAGGAGAGTGGGCGGTGAAGTGGACCT CCACATCCATGCCCTGGGCAGCGGCAAAGGATGGCAAGCTGCACTCGGGAATTGACTTCG GCGACACGAGCATCATTGAC
GLS1: TCTGGACAAGATGGGCAACAGTGTTAAGGGAATTCACTTCTGTCATGATCTTGTTTCTCTG TGTAATTTCCATAACTATGATAATTTGAGACACTTTGCTAAAAAACTTGATCCTCGAAGAGA AGGTGGTGATCAGAGGCATTCCTTTGGACCATTGGACTATGAAAGTCTCCAACAAGAACTT GCTTTAAAAGAGACAGTATGGAAAAAAGTGTCACCTGAGTCAAATGAGGACATCTCTACAA CTGTAGTATATAGAATGGAAAGTCTGGGAGAGA
222
GLS2: ACATGGGTTTCAGCAATGCCACATTCCAGTCAGAGAAGGAAACGGGGGATCGGAATTAT GCCATCGGTTATTATCTAAAGGAAAAGAAGTGCTTTCCTAAAGGGGTGGACATGATGGCTG CCCTTGATCTCTACTTCCAGCTGTGCTCTGTGGAGGTGACCTGTGAATCGGGCAG
GLUD1: GTGCCAAAGCTGGTGTGAAGATCAATCCCAAGAACTACACTGATAATGAATTGGAAAAG ATCACAAGGAGGTTCACCATGGAGCTGGCCAAGAAGGGCTTTATTGGCCCTGGCGTCGATG TGCCCGCCCCCGACATGAGCACCGGCGAGCGGGAGATGTCCTGGATCGCCGACACCTACG CCAGCACCATAGGACACTATGATATTAATGCCCACGCCTGTGTTACTGGTAAGCCCATCAGT CAGGGTGGAATCCACGGACGGATCTCTGCTAC
NAGS: GCGGGACCTGAAGACACTTTTCTGGCGCTCCCGGGTCACCAACCCCATCAATCCCTGGTA CTTCAAACACAGTGATGGCAGCTTCTCCAACAAGCAGTGGATCTTCTTCTGGTTTGGTCTG GCCGATATCCGGGACTCTTATGAGCTGGTCAACCATGCCAAGGGGCTACCGGACTCCTTTTG CAAGCCAGCTTCTGACCCAGGCAGCTGACCCTCTCTACCAGCCCTTCAGGCCCTGGGACAG CCAGTGTGGACTAAAGGCCGTGCCTGCTGGAGGAGACCCAAGGCAGCCACAGGCCGGAC CAGACATGCTGGCTGAGTGAACTGCAGAGGAAGCAGCAGCTGTTACTCTACCCTGCCCAG AGAAGGGTACCCAAGGGAGGACAAGCA
NR3C1: AAAGAGCAGTGGAAGGACAGCACAATTATCTTTGTGCTGGAAGAAATGATTGTATCATTG ATAAAATTCGAAGAAAAAACTGCCCAGCATGCCGCTATAGAAAATGCCTTCAAGCTGGAAT GAACCTGGAAGCTCGAAAAACAAAGAAAAAGATAAAAGGAATTCAGCAGGCCACTACAG GAGTCTCGCAAGAAACATCTGAAAATCCTGCTAACAAAACAATAGTTCCTGCAACATTACC ACAACTCACACCTACGCTGG
OAT: ATGTTAGGGACCAGTGTGCGGTTACTGCAGTGTTATCAGTTAACCTCACATTTTAAGCTCT CTGAGAATGTTTTTATTTGCTTCGTTTCTTGTGTTCTCTAAGAACATTTCAGTTTGTTTGGTA ATCTCTAGAAAAAGACAAATTATAAAAAGAAAGTTTCTTTCAGTACTCCTTCTCTGCTTTCA AAATAACCGCTCTTTTCCCATGTGT
ORNT1: CGACTGCAGACCATGTACGAGATGGAGACGTCGGGAAAGATAGCCAAAAGCCAGAACAC AGTCTGGTCTGTCGTGAAGACTGTCTTTAGGAAGGACGGCCCCTTGGGCTTCTACCATGGA CTCTCAAGTACTTTACTTCGAGAAGTACCAGGCTACTTCTTCTTTTTTGGTGGCTATGAACTA AGCCGGTCATTTTTTGCCTCGGGGAGATCGAAAGACG
OTC: TCACAGATACAGCCCGTGTGTTGTCTAGCATGACAGATGCCGTGCTGGCGCGAGTGTACA AACAATCAGATCTGGACCTCCTGGCTAAAGAAGCTTCCATCCCAATTGTCAATGGGCTGTC GGATTTGTACCACCCTATCCAGATCCTGGCTGATTACCTCACGCTCCAGGAACACTACGGCT 223
CTCTGAAAGGCCTTACCCTCAGCTGGATTGGGGATGGGAATAACATCCTGCACTCCATCATG ATGAGTGCGGCTAAATTCGGGATGCACCTTCAGG
PRODH: CGCCAGGTGTACTTTGGACAGCTTCTGGGCATGTGCGACCACATCAGCTTCCCGCTGGGC CAGGCAGGCTTCCCGGTGTACAAGTATGTCCCTTACGGGCCTGTGATGGAGGTGCTGCCCT ACCTGTCCCGCCGTGCCCTAGAGAACAGCGGGGTCATGAAGGGGGCTCAGCGGGAGCGGC AGCTGCTGTGGCAGGAGCTCAAGCGGAGGCTCTGCACCCGCAGCCTCTTCCACCAGCCTG CCTAGGCCACCTGCACCCACACCTGGGCCGCGACCTCCCCAGGCTCCGGCCAACCCCAGC CTCACACCGATCTCCTTT
PYCR1: ACCAGGAGAAGGTCTCACCAGCTGCCATCAAGAAAACCATCCTGGACAAGGTGAAACTG GACTCCCCTCCCGGCACCTCGCTGGCCCCTTCTGGCCACTCCAAGCTGCTGCCCCGCAGCA TGGCCCCAGCAGGCAAACAGGACTGAGGGGTCGAGCCTGCCTGTGGGCCACTCTCCACCT TCTCCTGGGCTCACAGCTCTTGCGCTGGGAGTATCTAGCCCCAGGCTACACAGGGTGTCC TCACG
PYCR2: GGGAGGGTGCAACAGTGTATGCCACAGGCACCCACGCCTTGGTGGAGGACGGGCAGCTC CTGGAGCAGCTCATGAGCAGCGTGGGCTTCTGCACGGAGGTGGAGGAGGACCTGATCGAT GCCGTCACAGGGCTCAGCGGCAGCGGGCCTGCCTATGCGTTCATGGCCCTGGACGCATTGG CTGACGGTGGGGTGAAGATGGGCCTGCCACGGCGCCTGGCCGTCCGACTGGGGGCCCAGG CCTTGCTGGGAGCTGCCAAGATGCTGCTGGACTCAGAACAGCATCCCGGCCAGCTCAAGG ACAACGTGTGCTCCCCTGGGGGGGCCACCATCCACGCCCTGCACTTCCTAGAGAGCGGGG GCTTCCGCTCCCTGCTCATCAATGCGGTTGAGGCCTCCTG
224
Figure 6. 7 Western blot analysis of EAAC1, GLT-1, GTRAP3-18 content in liver homogenates (35 μg per lane for EAAC1, GLT-1, GTRAP3-18, and ARL6IP1; 45 μg per lane for OAT) of growing beef steers grazing endophyte-infected tall fescue and supplemental with 3 mg Se/d in vitamin-mineral mixes as sodium selenite (ISe), SEL-
PLEX (OSe), or an 1:1 blend of ISe and OSe (MIX)1.
1Western blot data (n = 2) are representative of six ISe, eight OSe, and eight MIX steers (as described in Table 6.6). The apparent migration weights (kDa) for proteins were 57 for the lower, and 75 for the higher, predominant immunoreactants for EAAC1;75 for GLT-1; 42 for GTRAP3-18; 31 for ARL6IP1; and 67 for OAT; respectively.
225
Figure 6. 8 Overview of main glutamine/glutamate cycle and ammonia metabolic pathways in periportal and perivenous hepatocytes1.
226
1Assignment of a process and its related enzyme and transporter expressions is based on data from rodents model andprevious reviews. More detailed decription of these metabolic pathways, as well as exprimental results supporting this zonation patterns are presented in the text. Not all steps are shown. Abbreviations: SNAT3: glutamine transporter, SLC38A3; SNAT5: glutamine transporter, SLC38A5; EAAC1: high affinity Na+-dependent, glutamate/aspartate transporters, SLC1A1; GLT1: high affinity Na+-dependent, glutamate/aspartate transporters, SLC1A2; RHBG: ammonia transporter, SLC42A2; GLS2: glutaminase 2, liver mitochondria; ALT: alanine transaminase; AST: aspartate transaminase; GDH: glutamate dehydrogenase; CPS1: carbamoyl phosphate synthetase; NAGS: N-acetylglutamate synthase; OCT: ornithine carbamoyltransferase; ASS: argininosuccinate synthase; ASL: argininosuccinase; ARG1: arginase 1; ORNT1: ornithine/arginine exchanger, SLC25A15; ARG2: arginase 2; OAT: ornithine aminotransferase; GS: glutamine synthetase.
22 7
Figure 6. 9 Schemactic of pathways for proline metababolism1.
228
1Not all steps are shown. (Adaptaed and modified from Phang et al., 2010). Abbreviations: PRODH, proline dehydrogenase 1 (a.k.a. proline oxidase); PYCR1, pyrroline-5-carboxylate reductase 1; PYCR2, pyrroline-5-carboxylate rductase 2; OAT, ornithine aminotransferase; P5C synthetase, pyrroline-5-carboxylate synthetase, encoded by gene ALDH18A1; P5C dehydrogenase, pyrroline-5-carboxylate dehydrogenase, encoded by gene ALDH4A1.
CHAPTER 7. Summary and Conclusions
Forage-based beef cattle operations in Southeastern part of USA are usually
challenged by both fescue toxicosis and Se-inadequate forage and grains due to Se-poor soils. To our knowledge, little information is available with regard to the potential
interaction of fescue toxicosis and Se supplementation, although the effect of grazing
endophyte-infected tall fescue and the effect of supplementing different forms of Se to
beef cattle have been evaluated individually in a lot of studies. Our lab has previously
established two animal models separately to characterize the effect of grazing high vs.
low endophyte-infected tall fescue (Brown et al., 2009; Liao et al., 2015) and
supplementing sodium selenite (ISe), organic Se (OSe), or 1:1 blend of ISe:OSe (MIX)
(Brennan et al., 2011; Matthews et al., 2014) on beef cattle physiological parameters
and hepatic gene/protein expression profiles. From these data, serendipitously, some of
the genes upregulated by MIX were found to be downregulated in the liver (Liao et al.,
2015) and pituitary (Li et al., 2017) of steers grazing high vs. low endophyte-infected
forages. Thus, the overall goal this dissertation was to investigate whether the form of
supplemental Se (ISe, OSe, and MIX) in vitamin-mineral mixes consumed by growing
beef steers grazing endophyte-infected tall fescue pasture would ameliorate some of the negative physiological parameters associated with fescue toxicosis. The second goal was to elaborate and extend such findings by conducting transcriptome and targeted gene and protein expression analyses of the liver tissue of the same animals.
In the first experiment (Chapter 4), predominately-Angus steers subjected to summer-long grazing of endophyte-infected pasture and supplemented (3 mg/d) with
229
MIX or OSe forms of Se had greater whole blood Se, serum prolactin concentrations,
and greater hepatic GS activity than ISe-supplemented steers. Despite these effects, no differences in growth performance or carcass characteristics were found. However, the
MIX- and OSe-induced increases in serum prolactin and hepatic GS activity may have special relevance to other production regimens, including cow-suckling calf pairs
managed on endophyte-infected tall fescue forage (Koprowski and Tucker, 1973).
Nevertheless, future investigations on hepatic enzymes and transporters involved in
nitrogen and glutamate/glutamine metabolism are needed to further confirm and
understand the role of Se form on hepatic nitrogen metabolism.
In the second experiment (Chapter 5) was conducted to further explore the effect
of ISe, OSe, and MIX supplementation on other serological parameters associated with
fescue toxicosis, using the serum from the first experiment (Chapter 4). The results
from the second experiment showed that consumption of 3 mg Se/d as OSe or MIX
forms of Se in vitamin-mineral mixes increased serum albumin and alkaline
phosphatase activity, the reduction of which is associated with fescue toxicosis.
Furthermore, both serum albumin and alkaline phosphatase activity were correlated
with whole blood Se content, which is an indicator of whole-body Se status.
Given the alterations of serological parameters (Chapters 4 and 5) and hepatic GS
activities (Experiment 1, Chapter 4), a third experiment (Chapter 6) was conducted to
first evaluate the transcriptome profiles (microarray) of the same liver tissue from the
first experiment (Chapter 4), and identify potential hepatic regulatory connections with
altered serological parameters. The second goal of Chapter 6 experimentation was to
230
conduct targeted RT-PCR and immunoblotting analyses to investigate the expression of
key enzymes and transporters involved in hepatic glutamine/glutamate metabolism,
ammonia assimilation, and proline metabolism. In Chapter 6, the form of supplemental
Se (ISe, MIX, or OSe) affected the hepatic transcriptome profiles of steers subjected to
summer-long grazing of endophyte-infected pasture. Bioinformatic analysis of these profiles indicated that Se treatment-induced differentially expressed hepatic genes were involved in several canonical pathways, including glutamine biosynthesis/degradation, glutamate biosynthesis/degradation, and proline biosynthesis. Hepatic mRNA expression of enzymes responsible for proline metabolism were differentially affected by forms of Se supplementation. The differential expression of hepatic enzymes and transporters characterized a unique change of ammonia-assimilation capacity along the hepatic sinusoid of steer grazing endophyte-infected tall fescue induced by the supplementation of MIX and OSe vs. ISe form of Se. Specifically, compared to ISe steers, MIX and OSe steers indicated a dampened periportal ammonia assimilation and urea-synthesizing capacity, and compensatorily an elevated pericentral ammonia assimilation capacity. However, the metabolic consequences of these alterations in enzymes and transporters are unclear and need to be addressed in future research.
In conclusion, the dissertational research describes novel effects of supplementing
(3 mg Se/day) different forms of dietary Se (ISe, OSe, and MIX) on serological and physiological parameters, and hepatic gene expression profiles of growing steers grazing endophyte-infected tall fescue pasture. MIX and/or OSe steers showed greater concentrations of serum prolactin, alkaline phosphatase activity, and albumin,
231
reductions of which were associated with the fescue toxicosis, than ISe steers. All these
data indicate that supplementing MIX and/or OSe forms of Se in vitamin-mineral mixes seems to provide a unique serological phenotype that is potentially beneficial for steers grazing endophyte-infected tall fescue. Moreover, a shift of potential ammonia-
assimilating capacity along the hepatic sinusoids was indicated in the liver of MIX and
OSe steers. Further research is necessary to understand the mechanisms of this capacity shift, and to elaborate these findings to the scale of whole-body ammonia/nitrogen metabolism.
232
APPENDICES
APPENDIX 1. The Form of Selenium in Free-choice Vitamin-mineral Mixes
Affects the Percentage of Circulating Neutrophils and Lymphocytes in Beef
Calves Subjected to Combined Weaning and Shipping Events.
Introduction
Modern management strategies impose various physical, psychological, and nutritional stresses on beef cattle (Grandin, 1997; Burke et al., 2009). Especially during the transition from cow-calf beef production to feedlot, beef calves are often exposed to multiple stressors in a short time period, such as weaning and subsequent transportation, which may negatively affect the health, welfare and future performance of the animal (Duff and Galyean, 2007). Weaning and transportation are considered to be two of the predisposing factors to bovine respiratory disease (BRD) (Callan and
Garry, 2002; Snowder, 2009; Lynch et al., 2010), which is the most significant health problems facing the US beef cattle industry (Duff and Galyean, 2007).
Many studies have indicated that abruptly weaned beef calves exhibit distress behaviors (Price et al., 2003; Haley et al., 2005), with altered circulating hormones profiles associated with stress and Hypothalamic-pituitary-adrenal axis (Lefcourt and
Elsasser, 1995; Blanco et al., 2009). In addition, as summarized in Table A1.1, it has been suggested that weaning stress results in a number of modifications to the immune system with evidence of increased neutrophil number, neutrophil:lymphocyte ratio, and expression of leukocyte genes for pro-inflammatory cytokines (O'Loughlin et al., 2011). 233
Importantly, weaning-induced alterations in gene expression may extend beyond the 7 days measured. It is unclear that what point in time after weaning these cytokines gene expression returns to baseline levels (O'Loughlin et al., 2011). On the other hand, transportation stress induced similar hormonal changes with the increase of plasma cortisol as a hallmark (Buckham Sporer et al., 2007; Buckham Sporer et al., 2008).
Neutrophil transcriptome analysis (microarray) of transportation-stressed bull calves
indicated expression changes in genes involved in immune response, apoptosis, and
wound healing, as well as a signature of changes in genes whose function are as yet
unknown (Sporer et al., 2008).
Transport and weaning stressors may negatively affect animal’s overall health and
vulnerability to certain disease by diminishing antioxidant defenses or excess oxidative
species (Burke et al., 2009). Reactive oxygen species concentration is elevated in
leukocytes isolated from calves after shipping, likely as a consequence of enhanced
respiratory burst (Wernicki et al., 2006). Decreased serum total antioxidant capacity
was observed in transported calves (Chirase et al., 2004). One of the well-characterized
functions of Se is its ability to modulate oxidative stress through antioxidant-
functioning selenoproteins. Increased selenoprotein abundance and activities in
response to Se supplementation were shown in several studies (Lei et al., 1995; Allan
et al., 1999). Therefore, it is plausible to expect an increased antioxidant capacity when
supplementing Se. Redox enzymes are involved in a range of functions in different
tissues, including antioxidant metabolism, and enhancement of innate and adaptive
immune responses (Burk and Hill, 2015). Therefore, it is not surprising that
234
selenoproteins are intimately involved in regulating redox reactions, scavenging
reactive oxygen species (ROS), and affect inflammatory responses by regulating the oxidative state of immune cells (Hoffmann and Berry, 2008; Bellinger et al., 2009).
Selenium is commonly supplemented in cattle diets in an inorganic form (ISe, sodium selenite). However, sources of organic nutritional forms (OSe) of Se in specially cultivated strains of yeast (Saccharomyces cerevisiae) are available and approved for use in beef cattle diets. Our lab’s previous work has shown that more Se was found in whole blood, red blood cells, serum, and liver of heifers supplemented with MIX (an equimolar blend of ISe:OSe) and OSe for 224 days than supplemented with ISe.
Moreover, microarray analysis indicated that MIX stimulates gene expressions involved in selenoprotein synthesis and GSH metabolism in the liver relative to ISe or
OSe (Matthews and Bridges, 2014; Matthews et al., 2014).
Current research mainly focus on the evaluation of weaning and transportation stress individually, although the weaning and transportation of beef calves are often occurred sequentially in non-integrated calf-to-beef production systems (Duff and
Galyean, 2007). However, in Kentucky (and most of the surrounding states), calves are moved from their dams and immediately loaded onto trucks for an 8-10 h transport to a feedlot or a stocker farm. In addition, to our knowledge, no studies have investigated the effect of weaning with subsequent transportation on beef calves with different Se phenotypes, especially in the immune response.
235
Objective
The objective of this study was to test the hypothesis that MIX heifers have a greater better ability to handle weaning and transportation stress than do ISe heifers.
More specifically, compared to ISe heifers, MIX heifers were expected to have a greater concentration of whole blood Se, lower concentrations of stress-induced hormones, and a lesser expression of whole blood/leukocyte genes associated with oxidative status and pro-inflammatory responses, after being abruptly weaned and then transported 900 miles (a commercially-relevant model for dual weaning-shipping stress).
Materials and Methods
All experimental procedures were approved by the University of Kentucky
Institutional Animal Care and Use Committee.
Animal model
Thirty-nine sucking, predominantly Angus, beef steer (n = 18, BW: 297.2 ± 16.5 kg, Age: 210-240 days) and heifer (n = 21, BW: 253 ± 33 kg, Age: 210-240 days) calves were randomly selected from herds of fall-calving cows grazing endophyte- infected tall fescue mixed forage pasture and consuming vitamin-mineral mixes that contained 35 mg/kg Se as either an inorganic form (ISe, sodium selenite) or a 1:1 blend (MIX) of ISe and organic (SEL-PLEX, Alltech Inc., Nicholasville, KY) forms.
Calves (9 ISe steers, 9 MIX steers, 9 ISe heifers, 12 MIX heifers) were weaned on
Day 0 (7:30 am) and commingled for 4 hours (9:30 am to 1:30 pm). Then
236
immediately transported for 18 hours (900 miles, round trip from Princeton, KY to
Kansas City, MO). Post-shipping, all calves were penned by Se treatment and fed a
corn and cottonseed hull-based diet, and had ad libitum access to vitamin-mineral mixes containing their respective Se treatments.
Blood Collection
Jugular vein blood samples were collected by venipuncture on 7:30 am of Day 0,
Day 1, Day 2, Day 4, and Day 11 of the current study. For the preparation of whole blood, 8 mL of blood was collected in EDTA-containing blood collection tubes (Becton
Dickinson, Franklin Lakes, NJ). After collection, whole blood was stored on ice and transported to the University of Kentucky Veterinary Diagnostic Lab for complete blood count analysis. Whole blood Se concentrations were analyzed by Michigan State
University Diagnostic Center for Population and Animal Health (DCPAH) using an
Agilent 7900 Inductively Coupled Plasma-Mass Spectrometer as described previously
(Wahlen et al., 2005). For serum, 16 mL of blood was collected in serum blood collection tubes (Becton Dickinson, Franklin Lakes, NJ) without an anticoagulant.
Serum was recovered by centrifugation at 3,000 × g for 10 min at 4°C and stored at -
80°C. Serum cortisol (ug/dL) was evaluated using a commercial RIA Kit
(ImmuChemTM, 07221102, MP Biomedicals). The intra- and inter-assay CV were 7.4% and 9.3%, respectively. All serum enzymes and analytes were analyzed by the
American Association for Veterinary Laboratory Diagnosticians approved-University of Kentucky Veterinary Diagnostic Laboratory (Lexington, KY). For serum analytes,
237
activities of alkaline phosphatase (ALP), E.C. 3.1.3.1; aspartate transaminase
(AST/SGOT), E. C. 2.6.1.1; γ-glutamyltransferase (GGT), E. C. 2.3.22; creatine kinase,
E. C. 2.7.3.2 were determined as per the manufacturer of the reagent kits (Alfa
Wassermann, Diagnostic Technologies, West Caldwell, NJ) using a VET AXCEL
Chemical Analyzer (Alfa Wassermann, Diagnostic Technologies, West Caldwell, NJ).
Whole Blood RNA Collection and Isolation
Whole blood was collected into TempusTM blood RNA tube (Applied Biosystems),
and RNA was extracted using TempusTM spin RNA isolation kit (Invitrogen) following the manufacturer’s instructions. All samples had an average concentration of 0.4 μg/μL and a high purity with 260/280 absorbance ratios of 1.98-2.03 and 260/230 absorbance ratios ranging from 1.89 to 2.18. The integrity of total RNA was examined by gel electrophoresis using an Agilent 2100 Bioanalyzer System (Agilent Technologies,
Santa Clara, CA) at the University of Kentucky Microarray Core Facility. Visualization of gel images and electropherograms showed that all RNA samples were of high quality with RNA integrity numbers (RIN) = 9.3 ± 0.2 and 28S/18S rRNA absorbance ratios =
1.6 ± 0.2.
Real-time RT-PCR Analysis
The quantification of relative mRNA for genes of interest was performed using standard procedures in our laboratory, as previously described (Cerny et al., 2016).
Briefly, 1 µg of each animal’s whole blood RNA was reversely transcribed to cDNA
using the SuperScript III 1st Strand Synthesis System (Invitrogen). Real-time RT-PCR 238
was performed using an Eppendorf Mastercycler ep realplex2 system (Eppendorf,
Hamburg, Germany) with iQ SYBR Green Supermix (Bio-RAD, Hercules, CA). A total volume of 25 µL was used in each real-time RT-PCR reaction containing 5 µL of cDNA, 1 µL of a 10 µM stock of each primer (forward and reverse), 12.5 µL of 2 ×
SYBR Green PCR Master Mix, and 5.5 µL of nuclease-free water. The relative amount of each transcript was calculated using the 2-ΔΔCT method (Livak and
Schmittgen, 2001). Primer sets for genes of interest were designed and obtained from
NCBI Primer-BLAST tool (https://www.ncbi.nlm.nih.gov/tools/primer-blast/) against
RefSeq sequence (accessed February to April 2016).
All real-time RT-PCR cDNA products were validated by DNA sequencing verification. Briefly, the PCR-amplified cDNA products were electrophoresed in a
1.2% agarose (UltraPureTM Agarose, Invitrogen, Carlsbad, CA) slab gel. A single cDNA band at the desired size was identified under a UV light, excised from the gel, purified using the PureLink Quick Gel Extraction Kit (Invitrogen, Carlsbad, CA), then sequenced by Eurofins Genomics (Eurofins MWG Operon LLC, Louisville, KY). The resulting sequences were compared to the NCBI RefSeq mRNA sequences used as templates for primer pair set design. Three constitutively expressed genes (ACTB, L-
Sel, SELW) were used and their CT values were not affected by Se form (P > 0.4),
Time (P > 0.15), and Se form x time interaction (P > 0.13). Thus, the relative mRNA expression was normalized to the geometric means of three constitutively expressed genes. For the RT-PCR analysis, n = 9 and 12 samples were used for ISe and MIX treatments, respectively. RT-PCR reactions were performed in triplicate.
239
Statistical Analysis
Data are presented as least square means (± SEM). Calves were the experimental units. The effect of Se supplementation on complete blood counts, serum cortisol and chemical parameters, and whole blood gene expression data were evaluated by
ANOVA, using the PROC MIXED procedure of SAS (v 9.4, SAS Inst. Inc., Cary,
NC). The statistical model included Se supplementation, time, and their interaction as fixed effects. Class variables were Se supplementation and calves, with calves included in the random statement. The Kenward-Roger adjustment was used to calculate the denominator of df (Kenward and Roger, 1997). On Day 0, the effect of
Se supplementation on whole blood Se concentrations was assessed by ANOVA, using the PROC GLM procedure of SAS. Fisher’s protected LSD procedure was used to separate treatment means of the time-course data.
Results
On Day 0, the concentration of Se in whole blood was affected by Se supplementation treatment (P = 0.057), with MIX heifers had 21% more whole blood
Se than ISe heifers (Figure A1.1). Heifer serum cortisol concentration was not affected by Se form (P = 0.104), time (P = 0.205), nor by their interaction (P = 0.857)
(Figure A1.2). Heifer serum albumin concentration was affected by Se form, and was higher (P = 0.004) in ISe than MIX heifers throughout the trial (Figure A1.3). For both treatment groups, serum albumin concentration was affected time (P < 0.001). 240
Specifically, serum albumin increased (P < 0.05) after weaning and shipping (day 1
and 2), and retuned to baseline on Day 4. No interactions between Se form and time
(P = 0.546) were found for serum albumin (Figure A1.3). The concentration blood
urea nitrogen in heifers was affected by Se form (P < 0.001), and was higher in ISe
than MIX heifers throughout the trial (Figure A1.4). For both ISe and MIX heifers,
blood urea nitrogen concentrations were affected by time (P < 0.001), decreased (P <
0.05) after weaning and shipping (Day 2), and returned to baseline on Day 11 (Figure
A1.4). There was an interaction (P < 0.001) between Se form and time in blood urea
nitrogen (Figure A1.4). The percentage of neutrophils increased (P < 0.01) for both Se treatments after weaning and shipping (day 1) and was less (P < 0.01) in MIX than
ISe heifers throughout the trial (Figure A1.5). In contrast, the percentage of lymphocytes decreased (P < 0.01) for both Se treatments on day 1 and was greater (P
< 0.01) in MIX than ISe heifers from d 0 to d 11 (Figure A1.6). The relative mRNA expression of whole blood interleukin 8 (IL8) was upregulated in MIX than ISe heifers (P = 0.007) throughout the trial (Figure A1.7). The relative expression of IL8 for both ISe and MIX heifers was upregulated (P < 0.01) after weaning and shipping
(Day1>Day2=Day4>Day0) (Figure A1.7). No interaction was observed in whole blood IL8 expression (P = 0.1). The relative mRNA expression of whole blood tumor necrosis factor alpha (TNFα) was affected (P = 0.05) by Se form, and lower in MIX than ISe heifers throughout the trial (Figure A1.8). For both treatments, the expression of TNFα was affected (P < 0.01) by time. However, no interaction between Se form and time was observed in TNFα expression (P = 0.44) (Figure A1.8). The relative
241
mRNA expression of whole blood interferon γ (IFNγ) was affected (P = 0.004) by Se form, and lower in MIX than ISe heifers across the trial (Figure A1.9). The expression of IFNγ in both ISe and MIX heifers was also affected by time (P = 0.003), but no interaction was observed (P = 0.12) (Figure A1.9).
Conclusion
In summary, these data indicated that calves raised on MIX vs. ISe forms of Se, and which were subjected to a simultaneous weaning and transportation event, had (1) greater whole blood Se (21%), an indicator of greater whole body Se assimilation; (2) lower % neutrophils (16%), in agreement with the upregulation of whole blood IL8 mRNA expression, which is the primary cytokine involved in the recruitment of neutrophils to the site of infection; and (3) decreased whole blood IFNγ and TNFα expresssion, ostensibly an indication of a suppressed pro-inflammatory response in circulating immune cells.
242
Table A1. 1 Summary table of the literature on the effect weaning and transportation stress on cattle.
Acute Experimental Circulating Blood Animal Stress phase Immune function Reference timeline Hormones Metabolites proteins 12 Aberdeen Cortisol↑ Albumin↓ Angus bulls Blood sampled on - DHEA ↓ (Buckham 9 h of Globulin↓ Haptoglobin↓ 12 Friesian bulls 24, 0, 4.5, 9.75, Cortisol:DHEA ratio↑ Total Leukocyte count↑ Sporer et al., Transportation Urea↓ Fibrinogen↓ 12 Belgian Blue x 14.25, 24, and 48 h. Testosterone↓ 2008) Total protein↓ Friesian bulls Progesterone↑ Cell count Total Leukocyte↑ 243 Neutrophils↑
Neutrophil genes changed from Microarray and RT-PCR: Cortisol↑ ICAM3↑(Adhesion) Blood sampled on - DHEA ↓ 6 Belgian Blue x 9 h of IL-8↑ (Sporer et al., 24, 0, 4.5, 9.75, Cortisol:DHEA ratio↑ Friesian bulls Transportation Erythropoietin↑ 2008) 14.25, 24, and 48 h. Testosterone↓ IFN-γ R↓ Progesterone↑ Eotaxin-2 like protein↑ SHPS-1↑ Semaphorin 4A↑ p21↑ Caspase-13↓
Table A1. 1 (continued) Cell count Neutrophils↑ Neutrophil genes changed from Blood sampled on - (Buckham 6 Belgian Blue x 9 h of Cortisol↑ RT-PCR: 24, 0, 4.5, 9.75, Sporer et al., Friesian bulls Transportation Fas (Apoptosis)↓ 14.25, 24, and 48 h. 2007) MMP-9 (Tissue remodeling)↑ L-Selectin (vascular migration)↑ BPI (Bacterial killing)↑ Cell count Total Neutrophil ↑ Neutrophil:Lymphocyte ratio ↑
244 While blood cell genes changes
Immunized on d -28; from RT-PCR: 28 ¾ bred Blood taken on d -3, IL-1beta ↑ (O'Loughlin Simmental beef Weaning 0, 1,2,3,7, and 11 IL-8 ↑ et al., 2011) calves relative to weaning (d IFN g↑ 0) TNF α ↑ GRα (glucocorticoid receptor)↑ Fas (pro-apoptoic gene)↑ TLR4↑(Gram- pattern recognition receptor) 20 Angus, 20 Vaccinated at 2 week Leukocytes count ↑ Brahman X before ship. Plasma cortisol not (Blecha et al., 10 h (700 km) Lymphocyte blastogenic responses Angus(20 ship,20 Blood taken on -14 h, changed 1984) ↓ control) 10 h, and day 7
Table A1. 1 (continued) 16 spring-born, Total leukocytes ↑ single sucked Neutrophils ↑ steers ( Limousin × Phagocytosis+ neutrophils↓ Holstein-Friesian Abruptly No effect on Blood collected on CD4+ lymphocytes% ↓ and Simmental × weaned, n=8; Plasma (Lynch et al., day -7, 0 (housing), CD8+ lymphocytes% ↓ Holstein- non-weaned, fibrinogen, 2010) 2, 7, and 14 CD4+:CD8+ ratio ↑ Friesian dams and n=8 haptoglobin WC1+(gδ T cells) lymphocyte% ↓ Simmental and MHC II+ lymphocyte% ↑ Limousin sires, CD62L+ neutrophils ↓ respectively) The leukocyte transcriptomic
245 environment is profoundly
altered by weaning stress, at Abruptly least up to 7 days post-weaning Vaccinated at 28 weaned and and that a number of 16 intact male days prior to Plasma housed, n=8; processes are transcriptionally (O'Loughlin Simmental beef weaning. Blood Plasma cortisol ↑ Haptoglobin non-weaned activated to increase immune et al., 2012) calves collected on -4, 0, 1, ↓ and housed, cell adhesion and migration, 2, 3, and 7. n=8 potentially serving to increase immune surveillance following exposure to weaning stress
Figure A1. 1 Whole blood selenium (Se) concentrations at weaning (Day 0) in heifer calves raised on free-choice vitamin-mineral mixes as
sodium selenite (ISe) or an 1:1 blend of ISe and SEL-PLEX(organic Se) (MIX). Data are least squares means (n=9 for ISe, 12 for MIX) ±
SE. Means with different letters differ (P < 0.05).
A
B 246
Figure A1. 2 Serum cortisol concentrations after weaning and transportation events in heifer calves raised on free-choice vitamin-mineral
mixes as sodium selenite (ISe) or an 1:1 blend of ISe and SEL-PLEX(organic Se) (MIX)1.
247
1Data are least squares means (n = 9 for ISe, 12 for MIX) ± SE. Selenium form (P = 0.104), time (P = 0.205), and Se form by time interaction (P = 0.857) effects.
Figure A1. 3 Serum albumin concentrations after weaning and transportation events in heifer calves raised on free-choice vitamin-mineral
mixes as sodium selenite (ISe) or an 1:1 blend of ISe and SEL-PLEX(organic Se) (MIX)1.
248
1Data are least squares means (n = 9 for ISe, 12 for MIX) ± SE. Selenium form (P = 0.004), time (P < 0.001), and Se form by time interaction (P = 0.546) effects.
Figure A1. 4 Blood urea nitrogen concentrations after weaning and transportation events in heifer calves raised on free-choice vitamin-
mineral mixes as sodium selenite (ISe) or an 1:1 blend of ISe and SEL-PLEX(organic Se) (MIX)1.
249
1Data are least squares means (n = 9 for ISe, 12 for MIX) ± SE. Selenium form (P < 0.001), time (P < 0.001), and Se form by time interaction (P < 0.001) effects.
Figure A1. 5 Percentage of circulating neutrophils after weaning and transportation events in heifer calves raised on free-choice vitamin-
mineral mixes as sodium selenite (ISe) or an 1:1 blend of ISe and SEL-PLEX(organic Se) (MIX)1.
250
1Data are least squares means (n = 9 for ISe, 12 for MIX) ± SE. Selenium form (P = 0.006), time (P < 0.001), and Se form by time interaction (P < 0.001) effects.
Figure A1. 6 Percentage of circulating lymphocytes after weaning and transportation events in heifer calves raised on free-choice vitamin-
mineral mixes as sodium selenite (ISe) or an 1:1 blend of ISe and SEL-PLEX(organic Se) (MIX)1.
251
1Data are least squares means (n = 9 for ISe, 12 for MIX) ± SE. Selenium form (P = 0.008), time (P < 0.001), and Se form by time interaction (P < 0.001) effects.
Figure A1. 7 Relative mRNA expression of whole blood interleukin 8 after weaning and transportation events in heifer calves raised on free-
choice vitamin-mineral mixes as sodium selenite (ISe) or an 1:1 blend of ISe and SEL-PLEX(organic Se) (MIX)1.
252
1Data are least squares means (n = 9 for ISe, 12 for MIX) ± SE. Selenium form (P = 0.007), time (P < 0.001), and Se form by time interaction (P = 0.09) effects.
Figure A1. 8 Relative mRNA expression of whole blood tumor necrosis factor alpha after weaning and transportation events in heifer calves
raised on free-choice vitamin-mineral mixes as sodium selenite (ISe) or an 1:1 blend of ISe and SEL-PLEX(organic Se) (MIX)1.
253
1Data are least squares means (n = 9 for ISe, 12 for MIX) ± SE. Selenium form (P = 0.05), time (P < 0.001), and Se form by time interaction (P = 0.44) effects.
Figure A1. 9 Relative mRNA expression of whole blood interferon gamma after weaning and transportation events in heifer calves raised on
free-choice vitamin-mineral mixes as sodium selenite (ISe) or an 1:1 blend of ISe and SEL-PLEX(organic Se) (MIX)1.
254
1Data are least squares means (n = 9 for ISe, 12 for MIX) ± SE. Selenium form (P = 0.004), time (P = 0.003), and Se form by time interaction (P = 0.12) effects.
APPENDIX 2. Microarray signal intensity of selected key enzymes and transporters involved hepatic glutamate/glutamine,
ammonia, and proline metabolism.
Table A2. 1 List of the microarray signal intensity of selected key enzymes and transporters involved hepatic glutamate/glutamine, ammonia,
and proline metabolism.
Microarray Signal Intensity Gene Gene name, selected substrates ISe MIX OSe SEM P-Value Glutamate/glutamine metabolism GLUL Glutamine synthetase 10.21 10.67 10.61 0.070 0.001 255 GLUD1 Glutamate dehydrogenase 1 12.10 12.37 12.32 0.047 0.004
GLS1 Glutaminase 1 7.85 7.87 7.83 0.085 0.937 GLS2 Glutaminase 2, liver mitochondria 10.27 9.04 9.02 0.246 0.005 High-affinity glutamate and neutral amino acid transporter family (SLC1) SLC1A1 EAAC1, EAAT3; System X ; L-Glu, D/L-Asp 9.16 9.52 9.41 0.116 0.200 SLC1A2 GLT-1, EAAT2; System X −; L-Glu, D/L-Asp 10.04 9.97 9.68 0.246 0.567 AG SLC1A3 GLAST, EAAT1; System X− ; L-Glu, D/L-Asp 5.34 5.46 5.36 0.059 0.325 AG SLC1A4 ASCT1, SATT; System ASC;− L-Ala, L-Ser, L-Cys, L-Thr 6.68 6.69 6.69 0.095 0.998 AG SLC1A5 ASCT2, AAAT; System ASC; L-Ala, L-Ser, L-Cys, L-Thr, LGln, L-Asn 6.06 6.05 6.00 0.070 0.770 SLC1A6 EAAT4; System X ; L-Glu, D/L-Asp 5.38 5.43 5.50 0.079 0.585 SLC1A7 EAAT5; System X− L-Glu, D/L-Asp 5.70 5.52 5.79 0.079 0.059 AG System A and system N sodium-coupled− neutral amino acid transporter family (SLC38) AG SLC38A1 SNAT1; Q,A,N,C,H,S 5.95 6.07 5.97 0.127 0.786 SLC38A2 SNAT2; A,N,C,Q,G,H,M,P,S 9.70 10.00 9.97 0.090 0.079
Table A2. 1 (continued) SLC38A3 SNAT3; Q,H,A,N 11.16 10.94 10.99 0.068 0.102 SLC38A4 SNAT4; A,N,C,G,S,T 12.38 12.25 12.30 0.048 0.250 SLC38A5 SNAT5; Q,N,H,S 5.55 5.55 5.59 0.070 0.880 SLC38A6 SNAT6; 6.76 6.79 6.80 0.046 0.901 SLC38A7 SNAT7; Q,H,S,A,N 8.10 7.88 8.05 0.072 0.132 SLC38A9 N/A 8.56 8.58 8.61 0.059 0.828 SLC38A10 N/A 7.89 8.01 7.96 0.036 0.109 SLC38A11 N/A 4.14 4.00 4.16 0.104 0.532 Rh ammonium transporter family (SLC42) SLC42A1 RhAG; NH4+, NH3 4.16 4.13 4.23 0.082 0.661 SLC42A2 RhBG; NH4+, NH3, methyl amine, methyl ammonium 7.46 7.86 7.66 0.101 0.041
256 SLC42A3 RhCG; NH4+, NH3 5.65 5.75 5.73 0.054 0.428
Proline metabolism PRODH Proline dehydrogenase 1 7.62 7.85 7.67 0.060 0.055 PYCR1 Pyrroline-5-carboxylate reductase 1 7.84 8.16 8.45 0.131 0.037 PYCR2 Pyrroline-5-carboxylate reductase 2 6.83 6.86 6.96 0.051 0.242 ALDH4A1 Pyrroline-5-carboxylate dehydrogenase 8.99 9.08 8.91 0.077 0.284 ALDH18A1 Pyrroline-5-carboxylate synthetase 7.25 7.47 7.52 0.090 0.170 Urea cycle ARG1 Arginase 1 11.33 11.11 10.91 0.103 0.061 ARG2 Arginase 2 5.08 4.81 4.77 0.076 0.035 OAT Ornithine aminotransferase 7.54 7.12 7.05 0.090 0.002 NAGS N-acetylglutamate synthase 8.87 8.57 8.37 0.103 0.012 OCT Ornithine carbamoyltransferase 11.42 11.18 11.21 0.069 0.064 ORNT1 SLC25A15, Ornithine/arginine exchanger 10.84 10.49 10.37 0.128 0.062
Table A2. 1 (continued) ASL Argininosuccinate lyase 10.37 10.21 10.10 0.104 0.226 ASS Argininosuccinate synthase 1 12.57 12.55 12.46 0.039 0.131 CPS1 Carbamoyl-phosphate synthase 1, mitochondrial 13.14 13.13 13.05 0.033 0.146 Glucocorticoid receptor NR3C1 Glucocorticoid receptor 9.49 9.48 9.40 0.033 0.146 257
Conclusion
The microarray signal intensity reflects light (fluorescence) intensities of hybridization events after laser scanning. A photo-voltaic sensor converts light to a voltage signal, then the analog voltage signal is amplified and digitized in integer numbers of a particular size (mostly 16bit). The signal intensity values are presented as logarithms. For example, if the real measured signal intensity is 1024, the log2 is calculated as log2 (1024) =10, which is the value reported in the table. Therefore, the expression difference of ARG1 and ARG2 in ISe steers is 2^(11.33-5.08) =
2^6.22=74.54. In other words, the ARG1 expression in liver of ISe steers was about
75 fold higher than ARG2 expression. However, it should be cautioned that this comparison is valid under the assumption of the hybridization efficiency of the probes of ARG1 and ARG2 are identical.
Nevertheless, this table offers some informative understandings of the expression abundance of isoforms of some enzymes and transporters in bovine liver. For example, both SNAT3 and SNAT5 are expressed in hepatocytes of mouse and responsible for the import of glutamine from portal blood, and the export of glutamine at pericentral zone (Schiöth et al., 2013). However, in the current study, the microarray results indicated that both SNAT 3 and SNAT5 mRNA expression were not significantly affected by forms of Se (P ≥ 0.1), but a 44-fold greater signal intensity of SNAT3 than SNAT5 may suggest a more significant functional role of
SNAT3 in cattle hepatic glutamine transport.
258
REFERENCE
Aiken, G. E., B. H. Kirch, J. R. Strickland, L. P. Bush, M. L. Looper, and F. N. Schrick.
2007. Hemodynamic responses of the caudal artery to toxic tall fescue in beef
heifers. J Anim Sci 85: 2337-2345. 10.2527/jas.2006-821
Aiken, G. E., J. R. Strickland, M. L. Looper, L. P. Bush, and F. N. Schrick. 2009.
Hemodynamics are altered in the caudal artery of beef heifers fed different ergot
alkaloid concentrations. J Anim Sci 87: 2142-2150. 10.2527/jas.2008-1562
Akiduki, S., and M. J. Ikemoto. 2008. Modulation of the neural glutamate transporter
EAAC1 by the addicsin-interacting protein ARL6IP1. J Biol Chem 283: 31323-
31332. 10.1074/jbc.M801570200
Aldrich, C. G., J. A. Paterson, J. L. Tate, and M. S. Kerley. 1993. The effects of
endophyte-infected tall fescue consumption on diet utilization and thermal
regulation in cattle. J Anim Sci 71: 164-170. doi: 10.2527/1993.711164x
Ali, S., I. Pellegrini, and P. A. Kelly. 1991. A prolactin-dependent immune cell line
(Nb2) expresses a mutant form of prolactin receptor. J Biol Chem 266: 20110-
20117.
Allan, C. B., G. M. Lacourciere, and T. C. Stadtman. 1999. Responsiveness of
selenoproteins to dietary selenium. Annu Rev Nutr 19: 1-16.
10.1146/annurev.nutr.19.1.1
Ammerman, C. B., and S. M. Miller. 1975. Selenium in ruminant nutrition: a review. J
Dairy Sci 58: 1561-1577. https://doi.org/10.3168/jds.S0022-0302(75)84752-7
Anraku, M., K. Yamasaki, T. Maruyama, U. Kragh-Hansen, and M. Otagiri. 2001.
259
Effect of oxidative stress on the structure and function of human serum albumin.
Pharm Res 18: 632-639.
Aoyama, K., and T. Nakaki. 2012. Inhibition of GTRAP3-18 may increase
neuroprotective glutathione (GSH) synthesis. Int J Mol Sci 13: 12017-12035.
Aoyama, K., and T. Nakaki. 2013. Neuroprotective properties of the excitatory amino
acid carrier 1 (EAAC1). Amino Acids 45: 133-142. 10.1007/s00726-013-1481-
5
Archibeque, S. L., J. C. Burns, and G. B. Huntington. 2001. Urea flux in beef steers:
effects of forage species and nitrogen fertilization. J Anim Sci 79: 1937-1943.
https://doi.org/10.2527/2001.7971937x
Ardüser, F., S. Wolffram, and E. Scharrer. 1985. Active absorption of selenate by rat
ileum. J Nutr 115: 1203-1208.
Armstrong, D. T., K. A. Knudsen, and L. S. Miller. 1970. Effects of prolactin upon
cholesterol metabolism and progesterone biosynthesis in corpora lutea of rats
hyophysectomized during pseudopregnancy. Endocrinology 86: 634-641.
10.1210/endo-86-3-634
Avery, J. C., and P. R. Hoffmann. 2018. Selenium, Selenoproteins, and Immunity.
Nutrients 10: 1203. 10.3390/nu10091203
Bacon, C. W. 1988. Procedure for isolating the endophyte from tall fescue and
screening isolates for ergot alkaloids. Appl Environ Microbiol 54: 2615-2618.
Bacon, C. W., J. K. Porter, J. D. Robbins, and E. S. Luttrell. 1977. Epichloe typhina
from toxic tall fescue grasses. Appl Environ Microbiol 34: 576-581.
260
Badura, L. L., and B. D. Goldman. 1997. Anterior pituitary release of prolactin is
inhibited by exposure to short photoperiod. J Neuroendocrinol 9: 341-345.
Barger, G., and H. H. Dale. 1907. Ergotoxine and some other constituents of ergot.
Biochem J 2: 240.
Barger, J. L., T. Kayo, T. D. Pugh, J. A. Vann, R. Power, K. Dawson, R. Weindruch, and
T. A. Prolla. 2012. Gene expression profiling reveals differential effects of
sodium selenite, selenomethionine, and yeast-derived selenium in the mouse.
Genes Nutr 7: 155-165. 10.1007/s12263-011-0243-9
Beaulieu, J. M., and R. R. Gainetdinov. 2011. The physiology, signaling, and
pharmacology of dopamine receptors. Pharmacol Rev 63: 182-217.
10.1124/pr.110.002642
Behrman, H. R., G. P. Orczyk, G. J. Macdonald, and R. O. Greep. 1970. Prolactin
induction of enzymes controlling luteal cholesterol ester turnover.
Endocrinology 87: 1251-1256. 10.1210/endo-87-6-1251
Bellinger, F. P., A. V. Raman, M. A. Reeves, and M. J. Berry. 2009. Regulation and
function of selenoproteins in human disease. Biochem J 422: 11-22.
10.1042/BJ20090219
Ben-Jonathan, N., J. L. Mershon, D. L. Allen, and R. W. Steinmetz. 1996. Extrapituitary
prolactin: distribution, regulation, functions, and clinical aspects. Endocr Rev
17: 639-669. 10.1210/edrv-17-6-639
Bent-Hansen, L. 1991. Initial plasma disappearance and tissue uptake of 131I-albumin
in normal rabbits. Microvasc Res 41: 345-356.
261
Bera, S., S. Lamba, M. Rashid, A. K. Sharma, A. B. Medvinsky, C. Acquisti, A.
Chakraborty, and B. L. Li. 2016. Robust regulation of hepatic pericentral
amination by glutamate dehydrogenase kinetics. Integr Biol (Camb) 8: 1126-
1132. 10.1039/c6ib00158k
Berde, B. 1980. Ergot compounds: a synopsis. Adv Biochem Psychopharmacol 23: 3-
23.
Berde, B., and E. Stürmer. 1978. Introduction to the pharmacology of ergot alkaloids
and related compounds as a basis of their therapeutic application Ergot alkaloids
and related compounds.1-28. p 1-28. Springer.
Bergman, E., and R. Heitmann. 1978. Metabolism of amino acids by the gut, liver,
kidneys, and peripheral tissues. In: Federation proceedings. p 1228.
Bern, H. A. 1975. Prolactin and osmoregulation. American Zoologist 15: 937-948.
Bernard, V., J. Young, P. Chanson, and N. Binart. 2015. New insights in prolactin:
pathological implications. Nat Rev Endocrinol 11: 265-275.
10.1038/nrendo.2015.36
Berry, M. J., L. Banu, J. W. Harney, and P. R. Larsen. 1993. Functional characterization
of the eukaryotic SECIS elements which direct selenocysteine insertion at UGA
codons. EMBO J 12: 3315-3322.
Berwaer, M., P. Monget, B. Peers, M. Mathy-Hartert, E. Bellefroid, J. R. Davis, A.
Belayew, and J. A. Martial. 1991. Multihormonal regulation of the human
prolactin gene expression from 5000 bp of its upstream sequence. Mol Cell
Endocrinol 80: 53-64.
262
Bhusari, S., L. B. Hearne, D. E. Spiers, W. R. Lamberson, and E. Antoniou. 2006. Effect
of fescue toxicosis on hepatic gene expression in mice. J Anim Sci 84: 1600-
1612.
Bignon, C., N. Binart, C. Ormandy, L. Schuler, P. Kelly, and J. Djiane. 1997. Long and
short forms of the ovine prolactin receptor: cDNA cloning and genomic analysis
reveal that the two forms arise by different alternative splicing mechanisms in
ruminants and in rodents. J Mol Endocrinol 19: 109-120.
Blalock, E. M., K. C. Chen, K. Sharrow, J. P. Herman, N. M. Porter, T. C. Foster, and
P. W. Landfield. 2003. Gene microarrays in hippocampal aging: statistical
profiling identifies novel processes correlated with cognitive impairment. J
Neurosci 23: 3807-3819.
Blanco, M., I. Casasús, and J. Palacio. 2009. Effect of age at weaning on the
physiological stress response and temperament of two beef cattle breeds.
Animal 3: 108-117.
Blaser, R., R. Hammes, H. Bryant, C. Kincaid, W. Skrdla, T. Taylor, and W. Griffeth.
1956. The value of forage species and mixtures for fattening steers. Agron J 48:
508-513.
Blecha, F., S. L. Boyles, and J. G. Riley. 1984. Shipping suppresses lymphocyte
blastogenic responses in Angus and Brahman X Angus feeder calves. J Anim
Sci 59: 576-583.
Bole-Feysot, C., V. Goffin, M. Edery, N. Binart, and P. A. Kelly. 1998. Prolactin (PRL)
and its receptor: actions, signal transduction pathways and phenotypes observed
263
in PRL receptor knockout mice. Endocr Rev 19: 225-268.
https://doi.org/10.1210/edrv.19.3.0334
Boling, J. A. 1985. Endophytic Fungus and Tall Fescue Utilization by Ruminants. The
Professional Animal Scientist 1: 19-22. 10.15232/S1080-7446(15)32445-1
Boling, J. A., L. D. Bunting, G. M. Davenport, J. L. Van der Veen, K. M. Meekins, N.
W. Bradley, and R. E. Kohls. 1989. Physiological responses of cattle consuming
tall fescue to environmental temperature and supplemental phenothiazine. J
Anim Sci 67: 2377-2385. https://doi.org/10.2527/jas1989.6792377x
Boon, L., W. J. Geerts, A. Jonker, W. H. Lamers, and C. J. Van Noorden. 1999. High
protein diet induces pericentral glutamate dehydrogenase and ornithine
aminotransferase to provide sufficient glutamate for pericentral detoxification
of ammonia in rat liver lobules. Histochem Cell Biol 111: 445-452.
Borba, V. V., G. Zandman-Goddard, and Y. Shoenfeld. 2018. Prolactin and
Autoimmunity. Front Immunol 9: 73. 10.3389/fimmu.2018.00073
Boutin, J. M., M. Edery, M. Shirota, C. Jolicoeur, L. Lesueur, S. Ali, D. Gould, J. Djiane,
and P. A. Kelly. 1989. Identification of a cDNA encoding a long form of
prolactin receptor in human hepatoma and breast cancer cells. Mol Endocrinol
3: 1455-1461. 10.1210/mend-3-9-1455
Boyd, R. 2011. Selenium stories. Nat Chem 3: 570. 10.1038/nchem.1076
Braeuning, A., C. Ittrich, C. Kohle, S. Hailfinger, M. Bonin, A. Buchmann, and M.
Schwarz. 2006. Differential gene expression in periportal and perivenous mouse
hepatocytes. FEBS J 273: 5051-5061. 10.1111/j.1742-4658.2006.05503.x
264
Brandebourg, T., E. Hugo, and N. Ben-Jonathan. 2007. Adipocyte prolactin: regulation
of release and putative functions. Diabetes Obes Metab 9: 464-476.
10.1111/j.1463-1326.2006.00671.x
Brennan, K. M., W. R. Burris, J. A. Boling, and J. C. Matthews. 2011. Selenium content
in blood fractions and liver of beef heifers is greater with a mix of
inorganic/organic or organic versus inorganic supplemental selenium but the
time required for maximal assimilation is tissue-specific. Biol Trace Elem Res
144: 504-516. https://doi.org/10.1007/s12011-011-9069-y
Bridges, R. S. 1994. The role of lactogenic hormones in maternal behavior in female
rats. Acta Paediatr Suppl 397: 33-39.
Bridges, R. S., M. Numan, P. M. Ronsheim, P. E. Mann, and C. E. Lupini. 1990. Central
prolactin infusions stimulate maternal behavior in steroid-treated, nulliparous
female rats. Proc Natl Acad Sci U S A 87: 8003-8007.
Broer, S. 2014. The SLC38 family of sodium-amino acid co-transporters. Pflugers Arch
466: 155-172. 10.1007/s00424-013-1393-y
Brosnan, J. T., M. E. Brosnan, R. Charron, and I. Nissim. 1996. A mass isotopomer
study of urea and glutamine synthesis from 15N-labeled ammonia in the
perfused rat liver. J Biol Chem 271: 16199-16207.
Brown, D. G., R. F. Burk, R. J. Seely, and K. W. Kiker. 1972. Effect of dietary selenium
on the gastrointestinal absorption of ( 75 SeO3)2- in the rat. Int J Vitam Nutr
Res 42: 588-591.
Brown, K. R., G. A. Anderson, K. Son, G. Rentfrow, L. P. Bush, J. L. Klotz, J. R.
265
Strickland, J. A. Boling, and J. C. Matthews. 2009. Growing steers grazing high
versus low endophyte (Neotyphodium coenophialum)-infected tall fescue have
reduced serum enzymes, increased hepatic glucogenic enzymes, and reduced
liver and carcass mass. J Anim Sci 87: 748-760.
https://doi.org/10.2527/jas.2008-1108
Bu'Lock, J., and J. Barr. 1968. Regulation mechanism linking tryoptophan uptake and
synthesis with ergot alkaloid synthesis in Claviceps. Lloydia.
Buckham Sporer, K. R., J. L. Burton, B. Earley, and M. A. Crowe. 2007. Transportation
stress in young bulls alters expression of neutrophil genes important for the
regulation of apoptosis, tissue remodeling, margination, and anti-bacterial
function. Vet Immunol Immunopathol 118: 19-29.
10.1016/j.vetimm.2007.04.002
Buckham Sporer, K. R., P. S. Weber, J. L. Burton, B. Earley, and M. A. Crowe. 2008.
Transportation of young beef bulls alters circulating physiological parameters
that may be effective biomarkers of stress. J Anim Sci 86: 1325-1334.
10.2527/jas.2007-0762
Buckner, R. C., J. B. Powell, and R. V. Frakes. 1979. Historical development. Tall
fescue: 1-8.
Burk, R. F., D. G. Brown, R. J. Seely, and C. C. Scaief III. 1972. Influence of dietary
and injected selenium on whole-body retention, route of excretion, and tissue
retention of 75SeO32-in the rat. J Nutr 102: 1049-1055.
Burk, R. F., and K. E. Hill. 2015. Regulation of selenium metabolism and transport.
266
Annu Rev Nutr 35: 109-134. 10.1146/annurev-nutr-071714-034250
Burke, N. C., G. Scaglia, H. T. Boland, and W. S. Swecker, Jr. 2009. Influence of two-
stage weaning with subsequent transport on body weight, plasma lipid
peroxidation, plasma selenium, and on leukocyte glutathione peroxidase and
glutathione reductase activity in beef calves. Vet Immunol Immunopathol 127:
365-370. 10.1016/j.vetimm.2008.11.017
Bush, L., and R. Buckner. 1973. Tall fescue toxicity. Anti-Quality Components of
Forages: 99-112.
Cadoret, A., C. Ovejero, B. Terris, E. Souil, L. Levy, W. H. Lamers, J. Kitajewski, A.
Kahn, and C. Perret. 2002. New targets of beta-catenin signaling in the liver are
involved in the glutamine metabolism. Oncogene 21: 8293-8301.
10.1038/sj.onc.1206118
Callan, R. J., and F. B. Garry. 2002. Biosecurity and bovine respiratory disease. Vet
Clin North Am Food Anim Pract 18: 57-77.
Camacho, J. A., C. Obie, B. Biery, B. K. Goodman, C.-A. Hu, S. Almashanu, G. Steel,
R. Casey, M. Lambert, G. A. Mitchell, and D. Valle. 1999. Hyperornithinaemia-
hyperammonaemia-homocitrullinuria syndrome is caused by mutations in a
gene encoding a mitochondrial ornithine transporter. Nat Genet 22: 151.
Caporael, L. R. 1976. Ergotism: the satan loosed in Salem? Science 192: 21-26.
Caron, M. G., M. Beaulieu, V. Raymond, B. Gagne, J. Drouin, R. J. Lefkowitz, and F.
Labrie. 1978. Dopaminergic receptors in the anterior pituitary gland.
Correlation of [3H]dihydroergocryptine binding with the dopaminergic control
267
of prolactin release. J Biol Chem 253: 2244-2253.
Carter, J. M., G. E. Aiken, C. T. Dougherty, and F. N. Schrick. 2010. Steer responses to
feeding soybean hulls and steroid hormone implantation on toxic tall fescue
pasture. J Anim Sci 88: 3759-3766. 10.2527/jas.2009-2536
Cerny, K. L., S. Garbacik, C. Skees, W. R. Burris, J. C. Matthews, and P. J. Bridges.
2016. Gestational form of selenium in free-choice mineral mixes affects
transcriptome profiles of the neonatal calf testis, including those of
steroidogenic and spermatogenic pathways. Biol Trace Elem Res 169: 56-68.
https://doi.org/10.1007/s12011-015-0386-4
Charoenphandhu, N., and N. Krishnamra. 2007. Prolactin is an important regulator of
intestinal calcium transport. Can J Physiol Pharmacol 85: 569-581.
10.1139/y07-041
Charoenphandhu, N., L. Limlomwongse, and N. Krishnamra. 2001. Prolactin directly
stimulates transcellular active calcium transport in the duodenum of female rats.
Can J Physiol Pharmacol 79: 430-438.
Chen, X. D., Z. P. Zhao, J. C. Zhou, and X. G. Lei. 2018. Evolution, regulation, and
function of porcine selenogenome. Free Radic Biol Med 127: 116-123.
10.1016/j.freeradbiomed.2018.04.560
Chestnut, A. B., P. D. Anderson, M. A. Cochran, H. A. Fribourg, and K. D. Gwinn.
1992. Effects of hydrated sodium calcium aluminosilicate on fescue toxicosis
and mineral absorption. J Anim Sci 70: 2838-2846.
Chirase, N. K., L. W. Greene, C. W. Purdy, R. W. Loan, B. W. Auvermann, D. B. Parker,
268
E. F. Walborg, Jr., D. E. Stevenson, Y. Xu, and J. E. Klaunig. 2004. Effect of
transport stress on respiratory disease, serum antioxidant status, and serum
concentrations of lipid peroxidation biomarkers in beef cattle. Am J Vet Res 65:
860-864.
Christowitz, D., F. J. Mattheyse, and J. B. Balinsky. 1981. Dietary and hormonal
regulation of urea cycle enzymes in rat liver. Enzyme 26: 113-121.
Colombatto, S., G. Giribaldi, C. Vargiu, and M. A. Grillo. 1994. Modulation of
ornithine aminotransferase activity by oxygen in rat hepatocyte cultures.
Biochim Biophys Acta 1224: 329-332. https://doi.org/10.1016/0167-
4889(94)90264-X
Cooke, N. E., D. Coit, J. Shine, J. D. Baxter, and J. A. Martial. 1981. Human prolactin.
cDNA structural analysis and evolutionary comparisons. J Biol Chem 256:
4007-4016.
Cooper, A. J., E. Nieves, K. C. Rosenspire, S. Filc-DeRicco, A. S. Gelbard, and S. W.
Brusilow. 1988. Short-term metabolic fate of 13N-labeled glutamate, alanine,
and glutamine(amide) in rat liver. J Biol Chem 263: 12268-12273.
Cousins, R. J., and J. P. Liuzzi. 2018. Trace Metal Absorption and Transport Physiology
of the Gastrointestinal Tract (Sixth Edition).1485-1498. p 1485-1498. Elsevier.
Cunningham, I. 1949. A note on the cause of tall fescue lameness in cattle. Aust Vet J
25: 27-28.
Curthoys, N. P., and M. Watford. 1995. Regulation of glutaminase activity and
glutamine metabolism. Annu Rev Nutr 15: 133-159.
269
10.1146/annurev.nu.15.070195.001025
Dahl, G. E., B. A. Buchanan, and H. A. Tucker. 2000. Photoperiodic effects on dairy
cattle: a review. J Dairy Sci 83: 885-893. 10.3168/jds.S0022-0302(00)74952-6
Dargatz, D. A., and P. F. Ross. 1996. Blood selenium concentrations in cows and heifers
on 253 cow-calf operations in 18 states. J Anim Sci 74: 2891-2895. doi:
10.2527/1996.74122891x
Davenport, G. M., J. A. Boling, and C. H. Rahe. 1993. Growth and endocrine responses
of cattle to implantation of estradiol-17 beta during continuous or discontinuous
grazing of high- and low-endophyte-infected tall fescue. J Anim Sci 71: 757-
764. doi: 10.2527/1993.713757x
Davis, J. A., and D. I. Linzer. 1989. Expression of multiple forms of the prolactin
receptor in mouse liver. Mol Endocrinol 3: 674-680. 10.1210/mend-3-4-674
De Costa, C. 2002. St Anthony's fire and living ligatures: a short history of ergometrine.
Lancet 359: 1768-1770. 10.1016/S0140-6736(02)08658-0
Dehnes, Y., F. A. Chaudhry, K. Ullensvang, K. P. Lehre, J. Storm-Mathisen, and N. C.
Danbolt. 1998. The glutamate transporter EAAT4 in rat cerebellar Purkinje cells:
a glutamate-gated chloride channel concentrated near the synapse in parts of the
dendritic membrane facing astroglia. J Neurosci 18: 3606-3619.
https://doi.org/10.1523/JNEUROSCI.18-10-03606.1998
Doornenbal, H., A. K. Tong, and N. L. Murray. 1988. Reference values of blood
parameters in beef cattle of different ages and stages of lactation. Can J Vet Res
52: 99-105.
270
Doty, S. B., and B. H. Schofield. 1976. Enzyme histochemistry of bone and cartilage
cells. Prog Histochem Cytochem 8: 1-38.
Dougherty, C. T., L. M. Lauriault, N. W. Bradley, N. Gay, and P. L. Cornelius. 1991.
Induction of tall fescue toxicosis in heat-stressed cattle and its alleviation with
thiamin. J Anim Sci 69: 1008-1018. https://doi.org/10.2527/1991.6931008x
Doumas, B. T., and T. Peters, Jr. 1997. Serum and urine albumin: a progress report on
their measurement and clinical significance. Clin Chim Acta 258: 3-20.
Duff, G. C., and M. L. Galyean. 2007. Board-invited review: recent advances in
management of highly stressed, newly received feedlot cattle. J Anim Sci 85:
823-840. 10.2527/jas.2006-501
Dufour, D. R., J. A. Lott, F. S. Nolte, D. R. Gretch, R. S. Koff, and L. B. Seeff. 2000.
Diagnosis and monitoring of hepatic injury. I. Performance characteristics of
laboratory tests. Clin Chem 46: 2027-2049.
Dutt, A., M. G. Kaplitt, L. M. Kow, and D. W. Pfaff. 1994. Prolactin, central nervous
system and behavior: a critical review. Neuroendocrinology 59: 413-419.
10.1159/000126686
Eckert, H., J. R. Kiechel, J. Rosenthaler, and a. E. S. R. Schmidt. 1978. Ergot Alkaloids
and Related Compounds. Pages 1-28 Springer, Berlin, Heidelberg, New York.
Eisenberg, D., H. S. Gill, G. M. Pfluegl, and S. H. Rotstein. 2000. Structure-function
relationships of glutamine synthetases. Biochim Biophys Acta 1477: 122-145.
doi: 10.1016/S0167-4838(99)00270-8
Eliott, S., G. Harrison, and K. Dawson. 2005. Selenium supplementation of dairy cattle:
271
responses to organic and inorganic forms of selenium. In: Proc. Midwestern
section ASAS and Midwest Branch ADSA Meeting, Des Moines. Abstr
Emanuele, N. V., J. K. Jurgens, M. M. Halloran, J. J. Tentler, A. M. Lawrence, and M.
R. Kelley. 1992. The rat prolactin gene is expressed in brain tissue: detection of
normal and alternatively spliced prolactin messenger RNA. Mol Endocrinol 6:
35-42. 10.1210/mend.6.1.1738369
Esaki, N., T. Nakamura, H. Tanaka, T. Suzuki, Y. Morino, and K. Soda. 1981. Enzymic
synthesis of selenocysteine in rat liver. Biochemistry 20: 4492-4496.
Evans, T. W. 2002. Review article: albumin as a drug--biological effects of albumin
unrelated to oncotic pressure. Aliment Pharmacol Ther 16 Suppl 5: 6-11.
Fagegaltier, D., N. Hubert, K. Yamada, T. Mizutani, P. Carbon, and A. Krol. 2000.
Characterization of mSelB, a novel mammalian elongation factor for
selenoprotein translation. EMBO J 19: 4796-4805. 10.1093/emboj/19.17.4796
Fahie-Wilson, M., and T. P. Smith. 2013. Determination of prolactin: the
macroprolactin problem. Best Pract Res Clin Endocrinol Metab 27: 725-742.
10.1016/j.beem.2013.07.002
Fahrner, J., W. T. Labruyere, C. Gaunitz, A. F. Moorman, R. Gebhardt, and W. H.
Lamers. 1993. Identification and functional characterization of regulatory
elements of the glutamine synthetase gene from rat liver. Eur J Biochem 213:
1067-1073. doi: 10.1111/j.1432-1033.1993.tb17854.x
Fergus, E. 1952. Kentucky 31 fescue: culture and use. University of Kentucky, College
of Agriculture and Home Economics, Extension Division.
272
Fergus, E. 1972. A short history of Kentucky 31 fescue. In: Proc. 29th South. Pasture
Crop Imp. Conf. p 16-18.
Fernandez, N. J., and B. A. Kidney. 2007. Alkaline phosphatase: beyond the liver. Vet
Clin Pathol 36: 223-233. https://doi.org/10.1111/j.1939-165X.2007.tb00216.x
Finley, J. W. 2005. Selenium accumulation in plant foods. Nutr Rev 63: 196-202.
Finley, J. W. 2006. Bioavailability of selenium from foods. Nutr Rev 64: 146-151.
Firestone, G. L., and E. C. Heath. 1981. The cyclic AMP-mediated induction of alkaline
phosphatase in mouse L-cells. J Biol Chem 256: 1396-1403.
Fisher, D., S. Saxton, R. Elliot, and J. Beatty. 1995. Effects of selenium sources on Se
status of lactating cows. Vet. Clin. Nutr 2: 68-74.
Fitzgerald, P., and T. G. Dinan. 2008. Prolactin and dopamine: what is the connection?
A review article. J Psychopharmacol 22: 12-19.
https://doi.org/10.1177/0269216307087148
Flieger, M., M. Wurst, and R. Shelby. 1997. Ergot alkaloids--sources, structures and
analytical methods. Folia Microbiol (Praha) 42: 3-29.
Flohe, L., W. A. Gunzler, and H. H. Schock. 1973. Glutathione peroxidase: a
selenoenzyme. FEBS Lett 32: 132-134.
Foitzik, K., E. A. Langan, and R. Paus. 2009. Prolactin and the skin: a dermatological
perspective on an ancient pleiotropic peptide hormone. J Invest Dermatol 129:
1071-1087. 10.1038/jid.2008.348
Foote, A. P., D. L. Harmon, J. R. Strickland, L. P. Bush, and J. L. Klotz. 2011. Effect of
ergot alkaloids on contractility of bovine right ruminal artery and vein. J Anim
273
Sci 89: 2944-2949. 10.2527/jas.2010-3626
Franke, K. W. 1934. A new toxicant occurring naturally in certain samples of plant
foodstuffs. J Nutr 8: 597-608. 10.1093/jn/8.5.597
Freedland, R. 1964. Urea uycle adaptations in intact and adrenalectomized rats. Proc
Soc Exp Biol Med 116: 692-696.
Freedland, R. A., and C. H. Sodikoff. 1962. Effect of diets and hormones on two urea
cycle enzymes. Proc Soc Exp Biol Med 109: 394-396.
Freeman, M. E., B. Kanyicska, A. Lerant, and G. Nagy. 2000. Prolactin: structure,
function, and regulation of secretion. Physiol Rev 80: 1523-1631.
10.1152/physrev.2000.80.4.1523
Freemark, M., P. Driscoll, R. Maaskant, A. Petryk, and P. A. Kelly. 1997. Ontogenesis
of prolactin receptors in the human fetus in early gestation. Implications for
tissue differentiation and development. J Clin Invest 99: 1107-1117.
10.1172/JCI119239
Gadberry, M. S., T. M. Denard, D. E. Spiers, and E. L. Piper. 2003. Effects of feeding
ergovaline on lamb performance in a heat stress environment. J Anim Sci 81:
1538-1545. 10.2527/2003.8161538x
Garner, G. B., G. E. Rottinghaus, C. N. Cornell, and H. Testereci. 1993. Chemistry of
compounds associated with endophyte grass interaction - ergovaline-related and
ergopeptine-related alkaloids. Agric Ecosyst Environ 44: 65-80. Doi
10.1016/0167-8809(93)90039-R
Gaunitz, F., S. Weber, L. Scheja, and R. Gebhardt. 2001. Identification of a cis-acting
274
element and a novel trans-acting factor of the glutamine synthetase gene in liver
cells. Biochem Biophys Res Commun 284: 377-383. 10.1006/bbrc.2001.4967
Gebhardt, R. 1992. Metabolic zonation of the liver: regulation and implications for liver
function. Pharmacol Ther 53: 275-354.
Geerts, W. J., M. Verburg, A. Jonker, A. T. Das, L. Boon, R. Charles, W. H. Lamers,
and C. J. Van Noorden. 1996. Gender-dependent regulation of glutamate
dehydrogenase expression in periportal and pericentral zones of rat liver lobules.
J Histochem Cytochem 44: 1153-1159.
Gerloff, B. J. 1992. Effect of selenium supplementation on dairy cattle. J Anim Sci 70:
3934-3940. doi: 10.2527/1992.70123934x
Gianni, M., M. Terao, S. Sozzani, and E. Garattini. 1993. Retinoic acid and cyclic AMP
synergistically induce the expression of liver/bone/kidney-type alkaline
phosphatase gene in L929 fibroblastic cells. Biochem J 296 ( Pt 1): 67-77.
https://doi.org/10.1042/bj2960067
Gingras, M. C., and J. F. Margolin. 2000. Differential expression of multiple
unexpected genes during U937 cell and macrophage differentiation detected by
suppressive subtractive hybridization. Exp Hematol 28: 65-76.
Ginguay, A., L. Cynober, E. Curis, and I. Nicolis. 2017. Ornithine aminotransferase, an
important glutamate-metabolizing enzyme at the crossroads of multiple
metabolic pathways. Biology 6: 18.
Glass, R. S., W. P. Singh, W. Jung, Z. Veres, T. D. Scholz, and T. C. Stadtman. 1993.
Monoselenophosphate: synthesis, characterization, and identity with the
275
prokaryotic biological selenium donor, compound SePX. Biochemistry 32:
12555-12559.
Goetsch, A. L., A. L. Jones, S. R. Stokes, K. W. Beers, and E. L. Piper. 1987. Intake,
digestion, passage rate and serum prolactin in growing dairy steers fed
endophyte-infected fescue with noninfected fescue, clover or wheat straw. J
Anim Sci 64: 1759-1768. doi: 10.2527/jas1987.6461759x
Goldstein, D. J., C. E. Rogers, and H. Harris. 1980. Expression of alkaline phosphatase
loci in mammalian tissues. Proc Natl Acad Sci U S A 77: 2857-2860.
Goudreau, J. L., W. M. Falls, K. J. Lookingland, and K. E. Moore. 1995.
Periventricular-hypophysial dopaminergic neurons innervate the intermediate
but not the neural lobe of the rat pituitary gland. Neuroendocrinology 62: 147-
154.
Goudreau, J. L., S. E. Lindley, K. J. Lookingland, and K. E. Moore. 1992. Evidence
that hypothalamic periventricular dopamine neurons innervate the intermediate
lobe of the rat pituitary. Neuroendocrinology 56: 100-105.
Grandin, T. 1997. Assessment of stress during handling and transport. J Anim Sci 75:
249-257.
Grattan, D. R., and I. C. Kokay. 2008. Prolactin: a pleiotropic neuroendocrine hormone.
J Neuroendocrinol 20: 752-763. 10.1111/j.1365-2826.2008.01736.x
Gunter, S. A., P. A. Beck, and D. M. Hallford. 2013. Effects of supplementary selenium
source on the blood parameters in beef cows and their nursing calves. Biol Trace
Elem Res 152: 204-211. 10.1007/s12011-013-9620-0
276
Gunter, S. A., P. A. Beck, and J. K. Phillips. 2003. Effects of supplementary selenium
source on the performance and blood measurements in beef cows and their
calves. J Anim Sci 81: 856-864. https://doi.org/10.2527/2003.814856x
Hafeman, D. G., R. A. Sunde, and W. G. Hoekstra. 1974. Effect of dietary selenium on
erythrocyte and liver glutathione peroxidase in the rat. J Nutr 104: 580-587.
10.1093/jn/104.5.580
Hafner, M., M. Sulyok, R. Schuhmacher, C. Crews, and R. Krska. 2008. Stability and
epimerisation behaviour of ergot alkaloids in various solvents. World
Mycotoxin J 1: 67-78. 10.3920/WMJ2008.x008
Haley, D., D. Bailey, and J. Stookey. 2005. The effects of weaning beef calves in two
stages on their behavior and growth rate. Journal of Animal Science 83: 2205-
2214.
Hall, J. A., G. Bobe, J. K. Hunter, W. R. Vorachek, W. C. Stewart, J. A. Vanegas, C. T.
Estill, W. D. Mosher, and G. J. Pirelli. 2013. Effect of feeding selenium-
fertilized alfalfa hay on performance of weaned beef calves. PLoS One 8:
e58188. 10.1371/journal.pone.0058188
Hank, A. M., W. E. Hoffmann, R. K. Sanecki, D. J. Schaeffer, and J. L. Dorner. 1993.
Quantitative determination of equine alkaline phosphatase isoenzymes in foal
and adult serum. J Vet Intern Med 7: 20-24. https://doi.org/10.1111/j.1939-
1676.1993.tb03164.x
Hannaway, D. B., C. Daly, M. D. Halbleib, D. James, C. P. West, J. J. Volenec, D.
Chapman, X. Li, W. Cao, and J. Shen. 2009. Development of suitability maps
277
with examples for the United States and China. Tall Fescue for the Twenty-first
Century: 33-47.
Harris, H. 1990. The human alkaline phosphatases: what we know and what we don't
know. Clin Chim Acta 186: 133-150.
Harris, R. R. E., E.M.; Bosek, J.K.; Webster, W.B. 1972. Fescue, orchardgrass, and
Coastal bermudagrass grazing for yearling beef steers. Alabama Agric. Exp. Sta.
Bull 432.
Hattori, N., Y. Nakayama, K. Kitagawa, T. Li, and C. Inagaki. 2007. Development of
anti-PRL (prolactin) autoantibodies by homologous PRL in rats: a model for
macroprolactinemia. Endocrinology 148: 2465-2470. 10.1210/en.2006-1208
Häussinger, D. 1990a. Liver glutamine metabolism. JPEN J Parenter Enteral Nutr 14:
56S-62S. 10.1177/014860719001400405
Häussinger, D. 1990b. Nitrogen metabolism in liver: structural and functional
organization and physiological relevance. Biochem J 267: 281-290. doi:
10.1042/bj2670281
Häussinger, D., W. H. Lames, and A. F. M. Moorman. 1992. Hepatocyte heterogeneity
in the metabolism of amino acids and ammonia. Enzyme 46: 72-93.
10.1159/000468779
Häussinger, D., H. Sies, and W. Gerok. 1985. Functional hepatocyte heterogeneity in
ammonia metabolism. The intercellular glutamine cycle. J Hepatol 1: 3-14.
Healy, P. J. 1971. Serum alkaline phosphatase activity in cattle. Clin Chim Acta 33:
423-430.
278
Heitzman, R., I. Herriman, and C. Mallinson. 1972. Some effects of glucocorticoids on
the subcellular distribution of the activities of citrate synthase and
phosphoenolpyruvate carboxykinase in livers of rats and cows. FEBS letters 20:
19-21.
Hemken, R. W., J. A. Jackson, Jr., and J. A. Boling. 1984. Toxic factors in tall fescue. J
Anim Sci 58: 1011-1016.
Hill, K. E., S. Wu, A. K. Motley, T. D. Stevenson, V. P. Winfrey, M. R. Capecchi, J. F.
Atkins, and R. F. Burk. 2012. Production of selenoprotein P (Sepp1) by
hepatocytes is central to selenium homeostasis. J Biol Chem: jbc. M112. 421404.
Hirano, K., Y. Iiizumi, Y. Mori, K. Toyoshi, M. Sugiura, and S. Iino. 1985. Role of
alkaline phosphatase in phosphate uptake into brush border membrane vesicles
from human intestinal mucosa. J Biochem 97: 1461-1466.
Hoffmann, P. R., and M. J. Berry. 2008. The influence of selenium on immune
responses. Mol Nutr Food Res 52: 1273-1280. 10.1002/mnfr.200700330
Horseman, N. D., W. Zhao, E. Montecino-Rodriguez, M. Tanaka, K. Nakashima, S. J.
Engle, F. Smith, E. Markoff, and K. Dorshkind. 1997. Defective mammopoiesis,
but normal hematopoiesis, in mice with a targeted disruption of the prolactin
gene. EMBO J 16: 6926-6935. 10.1093/emboj/16.23.6926
Hoveland, C. S. 1993. Importance and economic-significance of the acremonium
endophytes to performance of animals and grass plant. Agric Ecosyst Environ
44: 3-12. 10.1016/0167-8809(93)90036-o
Hoveland, C. S. 2009. Origin and History. In: H. A. Fribourg, D. B. Hannaway and C.
279
P. West (eds.) Tall Fescue for the Twenty-first Century.3-10 Agronomy
Monographs. p 3-10. American Society of Agronomy, Crop Science Society of
America, Soil Science Society of America, Madison, WI.
Howell, J. A., A. D. Matthews, K. C. Swanson, D. L. Harmon, and J. C. Matthews.
2001. Molecular identification of high-affinity glutamate transporters in sheep
and cattle forestomach, intestine, liver, kidney, and pancreas. J Anim Sci 79:
1329-1336. doi: 10.2527/2001.7951329x
Hoylaerts, M. F., T. Manes, and J. L. Millan. 1997. Mammalian alkaline phosphatases
are allosteric enzymes. J Biol Chem 272: 22781-22787.
Huang, J., Y. Jia, Q. Li, W. R. Burris, P. J. Bridges, and J. C. Matthews. 2018. Hepatic
glutamate transport and glutamine synthesis capacities are decreased in finished
vs. growing beef steers, concomitant with increased GTRAP3-18 content.
Amino Acids 50: 513-525. 10.1007/s00726-018-2540-8
Humaloja, T., and H. M. Mykkanen. 1986. Intestinal absorption of 75Se-labeled sodium
selenite and selenomethionine in chicks: effects of time, segment, selenium
concentration and method of measurement. J Nutr 116: 142-148.
10.1093/jn/116.1.142
Huntington, G., and S. Archibeque. 2000. Practical aspects of urea and ammonia
metabolism in ruminants. J Anim Sci 77: 1-11.
Hurley, W. L., E. M. Convey, K. Leung, L. A. Edgerton, and R. W. Hemken. 1980.
Bovine prolactin, TSH, T and T concentrations as affected by tall fescue
summer toxicosis and temperature. J Anim Sci 51: 374-379.
280
Inoue, M., R. Kinne, T. Tran, L. Biempica, and I. M. Arias. 1983. Rat liver canalicular
membrane vesicles. Isolation and topological characterization. J Biol Chem 258:
5183-5188.
Irizarry, R. A., B. Hobbs, F. Collin, Y. D. Beazer-Barclay, K. J. Antonellis, U. Scherf,
and T. P. Speed. 2003. Exploration, normalization, and summaries of high
density oligonucleotide array probe level data. Biostatistics 4: 249-264.
10.1093/biostatistics/4.2.249
Ishida, M., T. Mitsui, K. Yamakawa, N. Sugiyama, W. Takahashi, H. Shimura, T. Endo,
T. Kobayashi, and J. Arita. 2007. Involvement of cAMP response element-
binding protein in the regulation of cell proliferation and the prolactin promoter
of lactotrophs in primary culture. Am J Physiol Endocrinol Metab 293: E1529-
1537. 10.1152/ajpendo.00028.2007
Jackson, J. J., M. D. Lindemann, J. A. Boling, and J. C. Matthews. 2015. Summer-long
grazing of high vs. low endophyte (Neotyphodium coenophialum)-infected tall
fescue by growing beef steers results in distinct temporal blood analyte response
patterns, with poor correlation to serum prolactin levels. Front Vet Sci 2: 77.
https://doi.org/10.3389/fvets.2015.00077
Jacobson, D. R., S. B. Carr, R. H. Hatton, R. C. Buckner, A. P. Graden, D. R. Dowden,
and W. M. Miller. 1970. Growth, physiological responses, and evidence of
toxicity in yearling dairy cattle grazing different grasses. J Dairy Sci 53: 575-
587. 10.3168/jds.S0022-0302(70)86256-7
James, L. A., P. G. Lunn, and M. Elia. 1998. Glutamine metabolism in the
281
gastrointestinal tract of the rat assess by the relative activities of glutaminase
(EC 3.5.1.2) and glutamine synthetase (EC 6.3.1.2). Br J Nutr 79: 365-372. doi:
10.1079/BJN19980061
Jenkinson, C. P., W. W. Grody, and S. D. Cederbaum. 1996. Comparative properties of
arginases. Comp Biochem Physiol B Biochem Mol Biol 114: 107-132.
https://doi.org/10.1016/0305-0491(95)02138-8
Jia, Y., D. L. Harmon, M. D. Flythe, and J. L. Klotz. 2015. Interaction of Isoflavones
and Endophyte-Infected Tall Fescue Seed Extract on Vasoactivity of Bovine
Mesenteric Vasculature. Front Nutr 2: 32. 10.3389/fnut.2015.00032
Jia, Y., Q. Li, W. R. Burris, G. E. Aiken, P. J. Bridges, and J. C. Matthews. 2018. Forms
of selenium in vitamin-mineral mixes differentially affect serum prolactin
concentration and hepatic glutamine synthetase activity of steers grazing
endophyte-infected tall fescue. J Anim Sci 96: 715-727.
https://doi.org/10.1093/jas/skx068
Jungermann, K., and T. Kietzmann. 1996. Zonation of parenchymal and
nonparenchymal metabolism in liver. Annu Rev Nutr 16: 179-203.
10.1146/annurev.nu.16.070196.001143
Jungermann, K., and D. Sasse. 1978. Heterogeneity of liver parenchymal cells. Trends
Biochem Sci 3: 198-202. 10.1016/s0968-0004(78)91764-4
Kallenbach, R. L. 2015. BILL E. KUNKLE INTERDISCIPLINARY BEEF
SYMPOSIUM: Coping with tall fescue toxicosis: Solutions and realities. J
Anim Sci 93: 5487-5495. 10.2527/jas.2015-9229
282
Kaneko, J. J., J. W. Harvey, and M. L. Bruss. 2008. Clinical biochemistry of domestic
animals. 6th ed. Academic press.
Kato, T., R. Read, J. Rozga, and R. F. Burk. 1992. Evidence for intestinal release of
absorbed selenium in a form with high hepatic extraction. Am J Physiol
Gastrointest Liver Physiol 262: G854-858. 10.1152/ajpgi.1992.262.5.G854
Kennaway, D. J., E. A. Dunstan, T. A. Gilmore, and R. F. Seamark. 1983. Effects of
shortened daylength and melatonin treatment on plasma prolactin and melatonin
levels in pinealectomised and sham-operated ewes. Anim Prod Sci 5: 287-294.
10.1016/0378-4320(83)90050-7
Kenward, M. G., and J. H. Roger. 1997. Small sample inference for fixed effects from
restricted maximum likelihood. Biometrics 53: 983-997.
https://doi.org/10.2307/2533558
Kietzmann, T. 2017. Metabolic zonation of the liver: The oxygen gradient revisited.
Redox Biol 11: 622-630. 10.1016/j.redox.2017.01.012
Kilberg, M. S. 1989. Measurement of amino acid transport by hepatocytes in
suspension or monolayer culture. Methods Enzymol 173: 564-575.
https://doi.org/10.1016/S0076-6879(89)73039-1
Klotz, J. L. 2015. Activities and Effects of Ergot Alkaloids on Livestock Physiology
and Production. Toxins (Basel) 7: 2801-2821. 10.3390/toxins7082801
Klotz, J. L., and A. M. Nicol. 2016. Ergovaline, an endophytic alkaloid. 1. Animal
physiology and metabolism. Anim Prod Sci 56: 1761-1774. doi:
10.1071/AN14962
283
Knowles, T. G., J. E. Edwards, K. J. Bazeley, S. N. Brown, A. Butterworth, and P. D.
Warriss. 2000. Changes in the blood biochemical and haematological profile of
neonatal calves with age. Vet Rec 147: 593-598.
Kobayashi, Y., Y. Ogra, K. Ishiwata, H. Takayama, N. Aimi, and K. T. Suzuki. 2002.
Selenosugars are key and urinary metabolites for selenium excretion within the
required to low-toxic range. Proc Natl Acad Sci 99: 15932-15936.
Kondou, H., M. Kawai, K. Tachikawa, A. Kimoto, M. Yamagata, T. Koinuma, M.
Yamazaki, M. Nakayama, S. Mushiake, K. Ozono, and T. Michigami. 2013.
Sodium-coupled neutral amino acid transporter 4 functions as a regulator of
protein synthesis during liver development. Hepatol Res 43: 1211-1223.
10.1111/hepr.12069
Koprowski, J., and H. A. Tucker. 1973. Serum prolactin during various physiological
states and its relationship to milk production in the bovine. Endocrinology 92:
1480-1487. doi: 10.1210/endo-92-5-1480
Krehbiel, C., and J. Matthews. 2003. Absorption of amino acids and peptides. Amino
acids in animal nutrition 2: 41-70.
Kryukov, G. V., S. Castellano, S. V. Novoselov, A. V. Lobanov, O. Zehtab, R. Guigo,
and V. N. Gladyshev. 2003. Characterization of mammalian selenoproteomes.
Science 300: 1439-1443. 10.1126/science.1083516
Kuo, F. C., W. L. Hwu, D. Valle, and J. E. Darnell, Jr. 1991. Colocalization in pericentral
hepatocytes in adult mice and similarity in developmental expression pattern of
ornithine aminotransferase and glutamine synthetase mRNA. Proc Natl Acad
284
Sci U S A 88: 9468-9472.
Labunskyy, V. M., D. L. Hatfield, and V. N. Gladyshev. 2014. Selenoproteins:
molecular pathways and physiological roles. Physiol Rev 94: 739-777.
https://doi.org/10.1152/physrev.00039.2013
Langan, E. A., K. Foitzik-Lau, V. Goffin, Y. Ramot, and R. Paus. 2010. Prolactin: an
emerging force along the cutaneous-endocrine axis. Trends Endocrinol Metab
21: 569-577. 10.1016/j.tem.2010.06.001
Larson, B. T., D. L. Harmon, E. L. Piper, L. M. Griffis, and L. P. Bush. 1999. Alkaloid
binding and activation of D2 dopamine receptors in cell culture. J Anim Sci 77:
942-947. https://doi.org/10.2527/1999.774942x
Larson, B. T., M. D. Samford, J. M. Camden, E. L. Piper, M. S. Kerley, J. A. Paterson,
and J. T. Turner. 1995. Ergovaline binding and activation of D2 dopamine
receptors in GH4ZR7 cells. J Anim Sci 73: 1396-1400. 10.2527/1995.7351396x
Larson, B. T., D. M. Sullivan, M. D. Samford, M. S. Kerley, J. A. Paterson, and J. T.
Turner. 1994. D2 dopamine receptor response to endophyte-infected tall fescue
and an antagonist in the rat. J Anim Sci 72: 2905-2910.
https://doi.org/10.2527/1994.72112905x
Lawler, T. L., J. B. Taylor, J. W. Finley, and J. S. Caton. 2004. Effect of supranutritional
and organically bound selenium on performance, carcass characteristics, and
selenium distribution in finishing beef steers. J Anim Sci 82: 1488-1493.
10.2527/2004.8251488x
Le Du, M. H., T. Stigbrand, M. J. Taussig, A. Menez, and E. A. Stura. 2001. Crystal
285
structure of alkaline phosphatase from human placenta at 1.8 A resolution.
Implication for a substrate specificity. J Biol Chem 276: 9158-9165.
10.1074/jbc.M009250200
Lean, I. J. 2001. Association between feeding perennial ryegrass (Lolium perenne
cultivar Grasslands Impact) containing high concentrations of ergovaline, and
health and productivity in a herd of lactating dairy cows. Aust Vet J 79: 262-
264. 10.1111/j.1751-0813.2001.tb11978.x
Lefcourt, A. M., R. M. Akers, D. L. Wood, and J. Bitman. 1994. Circadian and ultradian
rhythms of peripheral prolactin concentrations in lactating dairy cows. Am J
Physiol 267: R1461-1466. 10.1152/ajpregu.1994.267.6.R1461
Lefcourt, A. M., and T. H. Elsasser. 1995. Adrenal responses of Angus x Hereford cattle
to the stress of weaning. J Anim Sci 73: 2669-2676.
Lei, X. G., J. K. Evenson, K. M. Thompson, and R. A. Sunde. 1995. Glutathione
peroxidase and phospholipid hydroperoxide glutathione peroxidase are
differentially regulated in rats by dietary selenium. J Nutr 125: 1438-1446.
10.1093/jn/125.6.1438
Leuchtmann, A., C. W. Bacon, C. L. Schardl, J. F. White, Jr., and M. Tadych. 2014.
Nomenclatural realignment of Neotyphodium species with genus Epichole.
Mycologia 106: 202-215. 10.3852/13-251
Li, Q., R. Hegge, P. J. Bridges, and J. C. Matthews. 2017. Pituitary genomic expression
profiles of steers are altered by grazing of high vs. low endophyte-infected tall
fescue forages. PLoS One 12: e0184612.
286
https://doi.org/10.1371/journal.pone.0184612
Li, S., F. Gao, J. Huang, Y. Wu, S. Wu, and X. G. Lei. 2018. Regulation and function
of avian selenogenome. Biochim Biophys Acta Gen Subj.
10.1016/j.bbagen.2018.03.029
Liao, S. F., J. A. Boling, and J. C. Matthews. 2015. Gene expression profiling indicates
an increased capacity for proline, serine, and ATP synthesis and mitochondrial
mass by the liver of steers grazing high vs. low endophyte-infected tall fescue.
J Anim Sci 93: 5659-5671. https://doi.org/10.2527/jas.2015-9193
Liao, S. F., K. R. Brown, A. J. Stromberg, W. R. Burris, J. A. Boling, and J. C. Matthews.
2011. Dietary supplementation of selenium in inorganic and organic forms
differentially and commonly alters blood and liver selenium concentrations and
liver gene expression profiles of growing beef heifers. Biol Trace Elem Res 140:
151-169. https://doi.org/10.1007/s12011-010-8685-2
Lie-Venema, H., W. T. Labruyere, M. A. van Roon, P. A. de Boer, A. F. Moorman, A. J.
Berns, and W. H. Lamers. 1995. The spatio-temporal control of the expression
of glutamine synthetase in the liver is mediated by its 5'-enhancer. J Biol Chem
270: 28251-28256. doi: 10.1074/jbc.270.47.28251
Lin, C. I., I. Orlov, A. M. Ruggiero, M. Dykes-Hoberg, A. Lee, M. Jackson, and J. D.
Rothstein. 2001. Modulation of the neuronal glutamate transporter EAAC1 by
the interacting protein GTRAP3-18. Nature 410: 84-88. 10.1038/35065084
Lin, R. C., P. J. Snodgrass, and D. Rabier. 1982. Induction of urea cycle enzymes by
glucagon and dexamethasone in monolayer cultures of adult rat hepatocytes. J
287
Biol Chem 257: 5061-5067.
Lincoln, G. A., A. S. McNeilly, and C. L. Cameron. 1978. The effects of a sudden
decrease or increase in daylength on prolactin secretion in the ram. J Reprod
Fertil 52: 305-311.
Lippi, G., and M. Plebani. 2016. Macroprolactin: searching for a needle in a haystack?
Clin Chem Lab Med 54: 519-522. 10.1515/cclm-2015-1283
Livak, K. J., and T. D. Schmittgen. 2001. Analysis of relative gene expression data
using real-time quantitative PCR and the 2(-Delta Delta C(T)) Method. Methods
25: 402-408. https://doi.org/10.1006/meth.2001.1262
Lobie, P. E., J. Garcia-Aragon, and M. J. Waters. 1993. Prolactin receptor expression in
the gastrointestinal tract: characterization of the prolactin receptor of gastric
mucosa. J Endocrinol 139: 371-382.
Longnecker, M. P., D. O. Stram, P. R. Taylor, O. A. Levander, M. Howe, C. Veillon, P.
A. McAdam, K. Y. Patterson, J. M. Holden, J. S. Morris, C. A. Swanson, and
W. C. Willett. 1996. Use of selenium concentration in whole blood, serum,
toenails, or urine as a surrogate measure of selenium intake. Epidemiology 7:
384-390.
Low, M. G., and K. S. Huang. 1991. Factors affecting the ability of
glycosylphosphatidylinositol-specific phospholipase D to degrade the
membrane anchors of cell surface proteins. Biochem J 279 ( Pt 2): 483-493.
Lum, G. 1995. Significance of low serum alkaline phosphatase activity in a
predominantly adult male population. Clin Chem 41: 515-518.
288
Lynch, E. M., B. Earley, M. McGee, and S. Doyle. 2010. Effect of abrupt weaning at
housing on leukocyte distribution, functional activity of neutrophils, and acute
phase protein response of beef calves. BMC Veterinary Research 6: 39.
Lyons, P. C., R. D. Plattner, and C. W. Bacon. 1986. Occurrence of peptide and clavine
ergot alkaloids in tall fescue grass. Science 232: 487-489.
Mainoya, J. R. 1975a. Analysis of the role of endogenous prolactin on fluid and sodium
chloride absorption by the rat jejunum. J Endocrinol 67: 343-349.
Mainoya, J. R. 1975b. Effects of bovine growth hormone, human placental lactogen
and ovine prolactin on intestinal fluid and ion transport in the rat. Endocrinology
96: 1165-1170. https://doi.org/10.1210/endo-96-5-1165
Mainoya, J. R. 1975c. Further studies on the action of prolactin on fluid and ion
absorption by the rat jejunum. Endocrinology 96: 1158-1164.
Mainoya, J. R., H. A. Bern, and J. W. Regan. 1974. Influence of ovine prolactin on
transport of fluid and sodium chloride by the mammalian intestine and gall
bladder. J Endocrinol 63: 311-317.
Majorek, K. A., P. J. Porebski, A. Dayal, M. D. Zimmerman, K. Jablonska, A. J. Stewart,
M. Chruszcz, and W. Minor. 2012. Structural and immunologic characterization
of bovine, horse, and rabbit serum albumins. Mol Immunol 52: 174-182.
10.1016/j.molimm.2012.05.011
Malbe, M., M. Klaassen, W. Fang, V. Myllys, M. Vikerpuur, K. Nyholm, S. Sankari, K.
Suoranta, and M. Sandholm. 1995. Comparisons of selenite and selenium yeast
feed supplements on Se‐incorporation, mastitis and leucocyte function in Se‐
289
deficient dairy cows. J Vet Med A Physiol Pathol Clin Med 42: 111-121.
Maly, I. P., and D. Sasse. 1991. Microquantitative analysis of the intra-acinar profiles
of glutamate dehydrogenase in rat liver. J Histochem Cytochem 39: 1121-1124.
10.1177/39.8.1856459
Marano, R. J., and N. Ben-Jonathan. 2014. Minireview: Extrapituitary prolactin: an
update on the distribution, regulation, and functions. Mol Endocrinol 28: 622-
633. 10.1210/me.2013-1349
Marano, R. J., J. Tickner, and S. L. Redmond. 2013. Prolactin expression in the cochlea
of aged BALB/c mice is gender biased and correlates to loss of bone mineral
density and hearing loss. PLoS One 8: e63952. 10.1371/journal.pone.0063952
Mariotti, M., P. G. Ridge, Y. Zhang, A. V. Lobanov, T. H. Pringle, R. Guigo, D. L.
Hatfield, and V. N. Gladyshev. 2012. Composition and evolution of the
vertebrate and mammalian selenoproteomes. PLoS One 7: e33066.
10.1371/journal.pone.0033066
Martens, D. A., and D. L. Suarez. 1996. Selenium speciation of soil/sediment
determined with sequential extractions and hydride generation atomic
absorption spectrophotometry. Environ Sci Technol 31: 133-139.
Matera, L., M. Cutufia, M. Geuna, M. Contarini, S. Buttiglieri, S. Galin, A. Fazzari,
and C. Cavaliere. 1997. Prolactin is an autocrine growth factor for the Jurkat
human T-leukemic cell line. J Neuroimmunol 79: 12-21. 10.1016/s0165-
5728(97)00096-9
Matthews, J. C. 2005. Expression of non-organelle glutamate transporters to support
290
peripheral tissue function Glutamate Receptors in Peripheral Tissue: Excitatory
Transmission Outside the CNS.47-75. p 47-75. Springer.
Matthews, J. C., and P. J. Bridges. 2014. NutriPhysioGenomics applications to identify
adaptations of cattle to consumption of ergot alkaloids and inorganic versus
organic forms of selenium: altered nutritional, physiological and health states?
Anim Prod Sci 54: 1594-1604. 10.1071/an14274
Matthews, J. C., Z. Zhang, J. D. Patterson, P. J. Bridges, A. J. Stromberg, and J. A.
Boling. 2014. Hepatic transcriptome profiles differ among maturing beef heifers
supplemented with inorganic, organic, or mixed (50% inorganic:50% organic)
forms of dietary selenium. Biol Trace Elem Res 160: 321-339.
https://doi.org/10.1007/s12011-014-0050-4
McComb, R., G. Bowers, and S. Posen. 1979. Alkaline Phosphatase plenum. New York.
McConnell, K., and J. Hoffman. 1972. Methionine‐selenomethionine parallels in rat
liver polypeptide chain synthesis. FEBS letters 24: 60-62.
McConnell, K. P., and G. J. Cho. 1965. Transmucosal movement of selenium. Am J
Physiol 208: 1191-1195. 10.1152/ajplegacy.1965.208.6.1191
McCoy, K. E., and P. H. Weswig. 1969. Some selenium responses in the rat not related
to vitamin E. J Nutr 98: 383-389.
McGivan, J., N. Bradford, A. Verhoeven, and A. Meijer. 1984. Liver glutaminase
Glutamine metabolism in mammalian tissues.122-137. p 122-137. Springer.
McLean, P., and F. Novello. 1965. Influence of pancreatic hormones on enzymes
concerned with urea synthesis in rat liver. Biochem J 94: 410-422.
291
Mehdi, Y., A. Clinquart, J.-L. Hornick, J.-F. Cabaraux, L. Istasse, and I. Dufrasne. 2015.
Meat composition and quality of young growing Belgian Blue bulls offered a
fattening diet with selenium enriched cereals. Can J Anim Sci 95: 465-473.
Mehdi, Y., and I. Dufrasne. 2016. Selenium in cattle: a review. Molecules 21: 545.
10.3390/molecules21040545
Mehdi, Y., J. L. Hornick, L. Istasse, and I. Dufrasne. 2013. Selenium in the environment,
metabolism and involvement in body functions. Molecules 18: 3292-3311.
10.3390/molecules18033292
Meijer, A. J., W. H. Lamers, and R. A. Chamuleau. 1990. Nitrogen metabolism and
ornithine cycle function. Physiol Rev 70: 701-748.
10.1152/physrev.1990.70.3.701
Miles, E. D., B. W. McBride, Y. Jia, S. F. Liao, J. A. Boling, P. J. Bridges, and J. C.
Matthews. 2015. Glutamine synthetase and alanine transaminase expression are
decreased in livers of aged vs. young beef cows and GS can be upregulated by
17beta-estradiol implants. J Anim Sci 93: 4500-4509.
https://doi.org/10.2527/jas.2015-9294
Millan, J. L. 2006. Alkaline Phosphatases : Structure, substrate specificity and
functional relatedness to other members of a large superfamily of enzymes.
Purinergic Signal 2: 335-341. 10.1007/s11302-005-5435-6
Milne, E. M. 1985. The diagnostic value of alkaline phosphatase in canine medicine: a
review. J Small Anim Pract 26: 267-278.
Miyazawa, K., and I. Tomoda. 1991. Electrophoretical analysis of serum ALP
292
isoenzymes in neonatal calves. J Vet Med Sci 53: 807-810.
Moog, F., and H. S. Glazier. 1972. Phosphate absorption and alkaline phosphatase
activity in the small intestine of the adult mouse and of the chick embryo and
hatched chick. Comp Biochem Physiol A Comp Physiol 42: 321-336.
Moorman, A. F. M., P. A. J. de Boer, M. Watford, M. A. Dingemanse, and W. H. Lamers.
1994. Hepatic glutaminase mRNA is confined to part of the urea cycle domain
in the adult rodent liver lobule. FEBS Letters 356: 76-80. 10.1016/0014-
5793(94)01230-x
Morgan-Jones, G., and W. Gams. 1982. Notes on hyphomycetes. XLI. An endophyte
of Festuca arundinacea and the anamorph of Epichloe typhina, new taxa in one
of two new sections of Acremonium. Mycotaxon 15: 311-318.
Morris, S. M., Jr. 2002. Regulation of enzymes of the urea cycle and arginine
metabolism. Annu Rev Nutr 22: 87-105.
10.1146/annurev.nutr.22.110801.140547
Morris, S. M., Jr., C. L. Moncman, K. D. Rand, G. J. Dizikes, S. D. Cederbaum, and W.
E. O'Brien. 1987. Regulation of mRNA levels for five urea cycle enzymes in rat
liver by diet, cyclic AMP, and glucocorticoids. Arch Biochem Biophys 256:
343-353. https://doi.org/10.1016/0003-9861(87)90455-3
Moubarak, A. S., and C. F. Rosenkrans, Jr. 2000. Hepatic metabolism of ergot alkaloids
in beef cattle by cytochrome P450. Biochem Biophys Res Commun 274: 746-
749. 10.1006/bbrc.2000.3210
Nebes, V. L., and S. M. Morris, Jr. 1988. Regulation of messenger ribonucleic acid
293
levels for five urea cycle enzymes in cultured rat hepatocytes. Requirements for
cyclic adenosine monophosphate, glucocorticoids, and ongoing protein
synthesis. Mol Endocrinol 2: 444-451. 10.1210/mend-2-5-444
Nelson, W. O., and R. Gaunt. 1936. Initiation of lactation in the hypophysectomized
guinea pig. Proc Soc Exp Biol Med 34: 671-673.
Nicholson, J. W. G., R. E. McQueen, and R. S. Bush. 1991. Response of growing cattle
to supplementation with organically bound or inorganic sources of selenium or
yeast cultures. Can J Anim Sci 71: 803-811. https://doi.org/10.4141/cjas91-095
Nihsen, M. E., E. L. Piper, C. P. West, R. J. Crawford, Jr., T. M. Denard, Z. B. Johnson,
C. A. Roberts, D. A. Spiers, and C. F. Rosenkrans, Jr. 2004. Growth rate and
physiology of steers grazing tall fescue inoculated with novel endophytes. J
Anim Sci 82: 878-883. 10.2527/2004.823878x
Nissim, I., M. E. Brosnan, M. Yudkoff, I. Nissim, and J. T. Brosnan. 1999. Studies of
hepatic glutamine metabolism in the perfused rat liver with 15N-labeled
glutamine. J Biol Chem 274: 28958-28965.
NRC. 1996. Minerals. In: Nutrient requirments of beef cattle, 7th revised edition.
National Academy Press, Washington, DC, pp54-74.
O'Loughlin, A., D. J. Lynn, M. McGee, S. Doyle, M. McCabe, and B. Earley. 2012.
Transcriptomic analysis of the stress response to weaning at housing in bovine
leukocytes using RNA-seq technology. BMC Genomics 13: 250. 10.1186/1471-
2164-13-250
O'Loughlin, A., M. McGee, S. M. Waters, S. Doyle, and B. Earley. 2011. Examination
294
of the bovine leukocyte environment using immunogenetic biomarkers to assess
immunocompetence following exposure to weaning stress. BMC veterinary
research 7: 45.
O'Neal, K. D., D. W. Montgomery, T. M. Truong, and L. Y. Yu-Lee. 1992. Prolactin
gene expression in human thymocytes. Mol Cell Endocrinol 87: R19-23.
O'Sullivan, D., J. T. Brosnan, and M. E. Brosnan. 1998. Hepatic zonation of the
catabolism of arginine and ornithine in the perfused rat liver. Biochem J 330 ( Pt
2): 627-632.
Oliver, J. W., A. E. Schultze, B. W. Rohrbach, H. A. Fribourg, T. Ingle, and J. C. Waller.
2000. Alterations in hemograms and serum biochemical analytes of steers after
prolonged consumption of endophyte-infected tall fescue. J Anim Sci 78: 1029-
1035. https://doi.org/10.2527/2000.7841029x
Olm, E., A. P. Fernandes, C. Hebert, A.-K. Rundlöf, E. H. Larsen, O. Danielsson, and
M. Björnstedt. 2009. Extracellular thiol-assisted selenium uptake dependent on
the xc− cystine transporter explains the cancer-specific cytotoxicity of selenite.
Proc Natl Acad Sci 106: 11400-11405.
Orbach, H., G. Zandman-Goddard, H. Amital, V. Barak, Z. Szekanecz, G. Szucs, K.
Danko, E. Nagy, T. Csepany, J. F. Carvalho, A. Doria, and Y. Shoenfeld. 2007.
Novel biomarkers in autoimmune diseases: prolactin, ferritin, vitamin D, and
TPA levels in autoimmune diseases. Ann N Y Acad Sci 1109: 385-400.
10.1196/annals.1398.044
Ormandy, C. J., A. Camus, J. Barra, D. Damotte, B. Lucas, H. Buteau, M. Edery, N.
295
Brousse, C. Babinet, N. Binart, and P. A. Kelly. 1997. Null mutation of the
prolactin receptor gene produces multiple reproductive defects in the mouse.
Genes Dev 11: 167-178.
Ortman, K., and B. Pehrson. 1997. Selenite and selenium yeast as feed supplements for
dairy cows. J Vet Med A Physiol Pathol Clin Med 44: 373-380.
Ortman, K., and B. Pehrson. 1999. Effect of selenate as a feed supplement to dairy cows
in comparison to selenite and selenium yeast. J Anim Sci 77: 3365-3370.
Ota, H., A. Wakizaka, M. Fukushima, and M. Maki. 1982. Dual regulation of rat ovarian
LH-receptor by the administration of prolactin or sulpiride. IRCS MEDICAL
SCIENCE-BIOCHEMISTRY 10: 859-860.
Ouhtit, A., P. A. Kelly, and G. Morel. 1994. Visualization of gene expression of short
and long forms of prolactin receptor in rat digestive tissues. Am J Physiol 266:
G807-815. 10.1152/ajpgi.1994.266.5.G807
Owerbach, D., W. J. Rutter, N. E. Cooke, J. A. Martial, and T. B. Shows. 1981. The
prolactin gene is located on chromosome 6 in humans. Science 212: 815-816.
Palmieri, F. 2013. The mitochondrial transporter family SLC25: identification,
properties and physiopathology. Mol Aspects Med 34: 465-484.
10.1016/j.mam.2012.05.005
Parker, D. C., L. G. Rossman, and E. F. Vanderlaan. 1974. Relation of sleep-entrained
human prolactin release to REM-nonREM cycles. J Clin Endocrinol Metab 38:
646-651. 10.1210/jcem-38-4-646
Patterson, J. D., W. R. Burris, J. A. Boling, and J. C. Matthews. 2013. Individual intake
296
of free-choice mineral mix by grazing beef cows may be less than typical
formulation assumptions and form of selenium in mineral mix affects blood Se
concentrations of cows and their suckling calves. Biol Trace Elem Res 155: 38-
48. https://doi.org/10.1007/s12011-013-9768-7
Pedrosa, L. F., A. K. Motley, T. D. Stevenson, K. E. Hill, and R. F. Burk. 2012. Fecal
selenium excretion is regulated by dietary selenium intake. Biol Trace Elem Res
149: 377-381.
Pehrson, B., K. Ortman, N. Madjid, and U. Trafikowska. 1999. The influence of dietary
selenium as selenium yeast or sodium selenite on the concentration of selenium
in the milk of Suckler cows and on the selenium status of their calves. J Anim
Sci 77: 3371-3376. doi: 10.2527/1999.77123371x
Pellegrini, I., J. J. Lebrun, S. Ali, and P. A. Kelly. 1992. Expression of prolactin and its
receptor in human lymphoid cells. Mol Endocrinol 6: 1023-1031.
10.1210/mend.6.7.1508218
Peraino, C. 1967. Interactions of diet and cortisone in the regulation of adaptive
enzymes in rat liver. J Biol Chem 242: 3860-3867.
Perez-Villamil, B., E. Bordiu, and M. Puente-Cueva. 1992. Involvement of
physiological prolactin levels in growth and prolactin receptor content of
prostate glands and testes in developing male rats. J Endocrinol 132: 449-459.
doi: 10.1677/joe.0.1320449
Peters Jr, T. 1995. All about albumin: biochemistry, genetics, and medical applications.
Academic press.
297
Peters, R. R., and H. A. Tucker. 1978. Prolactin and growth hormone responses to
photoperiod in heifers. Endocrinology 103: 229-234. doi: 10.1210/endo-103-1-
229
Peters, T., Jr. 1977. Serum albumin: recent progress in the understanding of its structure
and biosynthesis. Clin Chem 23: 5-12.
Petritz, D. C., V. L. Lechtenberg, and W. H. Smith. 1980. Performance and economic
returns of beef-cows and calves grazing grass-legume herbage. Agron J 72: 581-
584.
Picher, M., L. H. Burch, A. J. Hirsh, J. Spychala, and R. C. Boucher. 2003. Ecto 5'-
nucleotidase and nonspecific alkaline phosphatase. Two AMP-hydrolyzing
ectoenzymes with distinct roles in human airways. J Biol Chem 278: 13468-
13479. 10.1074/jbc.M300569200
Pitot, H. C., and C. Peraino. 1963. Carbohydrate repression of enzyme induction in rat
liver. J Biol Chem 238: 1910-1912.
Poelstra, K., W. W. Bakker, P. A. Klok, J. A. Kamps, M. J. Hardonk, and D. K. Meijer.
1997. Dephosphorylation of endotoxin by alkaline phosphatase in vivo. Am J
Pathol 151: 1163-1169.
Pratt, A., and R. Davis. 1954. Kentucky-31 fescue. Ohio Farm Home Res 39: 93-94.
Pratt, A., and J. Haynes. 1950. Herd performance on Kentucky 31 fescue. Ohio Farm
and Home Res 35: 10-11.
Price, E., J. Harris, R. Borgwardt, M. Sween, and J. Connor. 2003. Fenceline contact of
beef calves with their dams at weaning reduces the negative effects of separation
298
on behavior and growth rate. Journal of Animal Science 81: 116-121.
Prinsen, B. H., and M. G. de Sain-van der Velden. 2004. Albumin turnover:
experimental approach and its application in health and renal diseases. Clin
Chim Acta 347: 1-14. 10.1016/j.cccn.2004.04.005
Radostits, O., M., C. C. Gay, K. W. Hinchliffe, and P. D. Constable. 2007. Veterinary
Medicine: A textbook of the diseases of cattle, horses, sheep, pigs and goats.
10th ed. pp 2048. Edinburgh, London: ELSEVER.
Rajan, P. V., and D. A. Wing. 2010. Postpartum hemorrhage: evidence-based medical
interventions for prevention and treatment. Clin Obstet Gynecol 53: 165-181.
10.1097/GRF.0b013e3181ce0965
Rawlings, J. S., K. M. Rosler, and D. A. Harrison. 2004. The JAK/STAT signaling
pathway. J Cell Sci 117: 1281-1283. 10.1242/jcs.00963
Rayman, M. P. 2004. The use of high-selenium yeast to raise selenium status: how does
it measure up? Br J Nutr 92: 557-573.
Rayman, M. P. 2012. Selenium and human health. Lancet 379: 1256-1268.
10.1016/S0140-6736(11)61452-9
Reddy, C. C., and E. J. Massaro. 1983. Biochemistry of selenium: a brief overview.
Fundam Appl Toxicol 3: 431-436.
Reynolds, C. K. 1992. Metabolism of nitrogenous compounds by ruminant liver. J Nutr
122: 850-854. 10.1093/jn/122.suppl_3.850
Rice, R. L., D. J. Blodgett, G. G. Schurig, W. S. Swecker, J. P. Fontenot, V. G. Allen,
and R. M. Akers. 1997. Evaluation of humoral immune responses in cattle
299
grazing endophyte-infected or endophyte-free fescue. Vet Immunol
Immunopathol 59: 285-291. https://doi.org/10.1016/S0165-2427(97)00079-2
Rice, R. L., G. G. Schurig, and D. J. Blodgett. 1998. Evaluation of physiologic indices
in mice vaccinated with protein-ergotamine conjugates and fed an endophyte-
infected fescue diet. Am J Vet Res 59: 1258-1262.
Richardson, B. 1973. Evidence for a physiological role of prolactin in osmoregulation
in the rat after its inhibition by 2-bromo--ergokryptine. Br J Pharmacol 47: 623P.
Riddle, O., R. W. Bates, and S. W. Dykshorn. 1933. The preparation, identification and
assay of prolactin—a hormone of the anterior pituitary. American Journal of
Physiology-Legacy Content 105: 191-216.
Rothschild, M. A., M. Oratz, and S. S. Schreiber. 1972. Albumin synthesis. 1. N Engl J
Med 286: 748-757. 10.1056/NEJM197204062861404
Roussel, J. D., S. H. Seybt, and G. Toups. 1982. Metabolic profile testing for Jersey
cows in Louisiana: reference values. Am J Vet Res 43: 1075-1077.
Rubio-Aliaga, I., and C. A. Wagner. 2016. Regulation and function of the
SLC38A3/SNAT3 glutamine transporter. Channels (Austin) 10: 440-452.
10.1080/19336950.2016.1207024
Ruggiero, A. M., Y. Liu, S. Vidensky, S. Maier, E. Jung, H. Farhan, M. B. Robinson, H.
H. Sitte, and J. D. Rothstein. 2008. The endoplasmic reticulum exit of glutamate
transporter is regulated by the inducible mammalian Yip6b/GTRAP3-18 protein.
J Biol Chem 283: 6175-6183.
Saleem, M., H. Martin, and P. Coates. 2018. Prolactin Biology and Laboratory
300
Measurement: An Update on Physiology and Current Analytical Issues. Clin
Biochem Rev 39: 3-16.
Sato, J., M. Kanata, J. Yasuda, R. Sato, K. Okada, Y. Seimiya, and Y. Naito. 2005.
Changes of serum alkaline phosphatase activity in dry and lactational cows. J
Vet Med Sci 67: 813-815.
Schams, D. 1972. Prolactin levels in bovine blood, influenced by milking manipulation,
genital stimulation and oxytocin administration with specific consideration of
the seasonal variations. Acta Endocrinol (Copenh) 71: 684-696.
Schams, D., and V. Reinhardt. 1974. Influence of the season on plasma prolactin level
in cattle from birth to maturity. Horm Res 5: 217-226. 10.1159/000178634
Schardl, C. L., D. G. Panaccione, and P. Tudzynski. 2006. Ergot alkaloids--biology and
molecular biology. Alkaloids Chem Biol 63: 45-86.
Schiff, P. L. 2006. Ergot and its alkaloids. Am J Pharm Educ 70: 98.
Schillo, K. K., L. S. Leshin, J. A. Boling, and N. Gay. 1988. Effects of endophyte-
infected fescue on concentrations of prolactin in blood sera and the anterior
pituitary and concentrations of dopamine and dopamine metabolites in brains of
steers. J Anim Sci 66: 713-718. doi: 10.2527/jas1988.663713x
Schioth, H. B., S. Roshanbin, M. G. Hagglund, and R. Fredriksson. 2013. Evolutionary
origin of amino acid transporter families SLC32, SLC36 and SLC38 and
physiological, pathological and therapeutic aspects. Mol Aspects Med 34: 571-
585. 10.1016/j.mam.2012.07.012
Schleicher, J., C. Tokarski, E. Marbach, M. Matz-Soja, S. Zellmer, R. Gebhardt, and S.
301
Schuster. 2015. Zonation of hepatic fatty acid metabolism - The diversity of its
regulation and the benefit of modeling. Biochim Biophys Acta 1851: 641-656.
10.1016/j.bbalip.2015.02.004
Schmidt, S., and T. Osborn. 1993. Effects of endophyte-infected tall fescue on animal
performance. Agric Ecosyst Environ 44: 233-262.
Schuler, L. A., R. J. Nagel, J. Gao, N. D. Horseman, and M. A. Kessler. 1997. Prolactin
receptor heterogeneity in bovine fetal and maternal tissues. Endocrinology 138:
3187-3194. 10.1210/endo.138.8.5292
Schultz, C. L., S. L. Lodge-Ivey, L. P. Bush, A. M. Craig, and J. R. Strickland. 2006.
Effects of initial and extended exposure to an endophyte-infected tall fescue
seed diet on faecal and urinary excretion of ergovaline and lysergic acid in
mature geldings. N Z Vet J 54: 178-184. 10.1080/00480169.2006.36692
Schultze, A. E., B. W. Rohrbach, H. A. Fribourg, J. C. Waller, and J. W. Oliver. 1999.
Alterations in bovine serum biochemistry profiles associated with prolonged
consumption of endophyte-infected tall fescue. Vet Hum Toxicol 41: 133-139.
Schwarz, K., and C. M. Foltz. 1957. Selenium as an integral part of factor 3 against
dietary necrotic liver degeneration. J Am Chem Soc 79: 3292-3293.
10.1021/ja01569a087
Scott, P., M. A. Kessler, and L. A. Schuler. 1992. Molecular cloning of the bovine
prolactin receptor and distribution of prolactin and growth hormone receptor
transcripts in fetal and utero-placental tissues. Mol Cell Endocrinol 89: 47-58.
Settivari, R. S., S. Bhusari, T. Evans, P. A. Eichen, L. B. Hearne, E. Antoniou, and D.
302
E. Spiers. 2006. Genomic analysis of the impact of fescue toxicosis on hepatic
function. J Anim Sci 84: 1279-1294.
Sheifer, S. E., M. R. Canos, K. P. Weinfurt, U. K. Arora, F. O. Mendelsohn, B. J. Gersh,
and N. J. Weissman. 2000. Sex differences in coronary artery size assessed by
intravascular ultrasound. Am Heart J 139: 649-653. doi: 10.1016/S0002-
8703(00)90043-7
Shennan, D. B. 1994. Regulation of water and solute transport across mammalian
plasma cell membranes by prolactin. J Dairy Res 61: 155-166.
Shin, D., S. Park, and C. Park. 2003. A splice variant acquiring an extra transcript leader
region decreases the translation of glutamine synthetase gene. Biochem J 374:
175-184. 10.1042/BJ20030132
Snowder, G. 2009. Genetics, environment and bovine respiratory disease. Anim Health
Res Rev 10: 117-119. 10.1017/S1466252309990144
Solovyev, N. D. 2015. Importance of selenium and selenoprotein for brain function:
From antioxidant protection to neuronal signalling. J Inorg Biochem 153: 1-12.
https://doi.org/10.1016/j.jinorgbio.2015.09.003
Spears, J. W. 2003. Trace mineral bioavailability in ruminants. J Nutr 133: 1506S-
1509S. 10.1093/jn/133.5.1506S
Speckmann, B., S. Schulz, F. Hiller, D. Hesse, F. Schumacher, B. Kleuser, J. Geisel, R.
Obeid, T. Grune, and A. P. Kipp. 2017. Selenium increases hepatic DNA
methylation and modulates one-carbon metabolism in the liver of mice. J Nutr
Biochem 48: 112-119. https://doi.org/10.1016/j.jnutbio.2017.07.002
303
Spoon, R. A., and D. M. Hallford. 1989. Growth response, endocrine profiles and
reproductive performance of fine-wool ewe lambs treated with ovine prolactin
before breeding. Theriogenology 32: 45-53. doi: 10.1016/0093-
691X(89)90520-7
Sporer, K. R., L. Xiao, R. J. Tempelman, J. L. Burton, B. Earley, and M. A. Crowe.
2008. Transportation stress alters the circulating steroid environment and
neutrophil gene expression in beef bulls. Vet Immunol Immunopathol 121: 300-
320. 10.1016/j.vetimm.2007.10.010
Strahan, S. R., R. W. Hemken, J. A. Jackson, Jr., R. C. Buckner, L. P. Bush, and M. R.
Siegel. 1987. Performance of lactating dairy cows fed tall fescue forage. J Dairy
Sci 70: 1228-1234. 10.3168/jds.S0022-0302(87)80135-2
Stricker, P. 1928. Action du lobe anterieur de l'hypophyse sur la montee laiteuse.
Compendes Rendus Society of Biology 99: 1978-1980.
Strickland, J. R., G. E. Aiken, and J. L. Klotz. 2009a. Ergot alkaloid induced blood
vessel dysfunction contributes to fescue toxicosis. Forage and Grazinglands.
Strickland, J. R., G. E. Aiken, D. E. Spiers, L. R. Fletcher, and J. W. Oliver. 2009b.
Physiological basis of fescue toxicosis. Tall fescue for the twenty-first century:
203-227. doi: 10.2134/agronmonogr53.c12
Strickland, J. R., M. L. Looper, J. C. Matthews, C. F. Rosenkrans, Jr., M. D. Flythe, and
K. R. Brown. 2011. Board-invited review: St. Anthony's Fire in livestock:
causes, mechanisms, and potential solutions. J Anim Sci 89: 1603-1626.
https://doi.org/10.2527/jas.2010-3478
304
Strickland, J. R., J. W. Oliver, and D. L. Cross. 1993. Fescue toxicosis and its impact
on animal agriculture. Vet Hum Toxicol 35: 454-464.
Stuedemann, J. A., and C. S. Hoveland. 1988. Fescue endophyte: History and impact
on animal agriculture. J Prod Agric 1: 39-44.
Suttle, N. F. 2010. Mineral nutrition of livestock. Fourth Edition. Cabi.
Suzuki, K. T. 2005. Metabolomics of selenium: Se metabolites based on speciation
studies. J Health Sci 51: 107-114.
Suzuki, K. T., and Y. Ogra. 2002. Metabolic pathway for selenium in the body:
speciation by HPLC-ICP MS with enriched Se. Food Addit Contam 19: 974-
983. 10.1080/02652030210153578
Suzuki, Y., Y. Hashiura, K. Matsumura, T. Matsukawa, A. Shinohara, and N. Furuta.
2010. Dynamic pathways of selenium metabolism and excretion in mice under
different selenium nutritional statuses. Metallomics 2: 126-132.
10.1039/b915816b
Takiguchi, M., and M. Mori. 1995. Transcriptional regulation of genes for ornithine
cycle enzymes. Biochem J 312 649-659.
Tanaree, D., J. Duringer, D. Bohnert, and A. Craig. 2013. Microarray evaluation of
bovine hepatic gene response to fescue toxicosis. World Mycotoxin J 6: 419-
426.
Tang, M. W., S. Garcia, D. M. Gerlag, P. P. Tak, and K. A. Reedquist. 2017. Insight into
the endocrine system and the immune system: a review of the inflammatory role
of prolactin in rheumatoid arthritis and psoriatic arthritis. Front Immunol 8: 720.
305
10.3389/fimmu.2017.00720
Tanrattana, C., N. Charoenphandhu, L. Limlomwongse, and N. Krishnamra. 2004.
Prolactin directly stimulated the solvent drag-induced calcium transport in the
duodenum of female rats. Biochim Biophys Acta 1665: 81-91.
10.1016/j.bbamem.2004.06.017
Tashima, Y., M. Terui, H. Itoh, H. Mizunuma, R. Kobayashi, and F. Marumo. 1989.
Effect of selenite on glucocorticoid receptor. J Biochem 105: 358-361.
Tate, S. S., F. Y. Leu, and A. Meister. 1972. Rat liver glutamine synthetase. Preparation,
properties, and mechanism of inhibition by carbamyl phosphate. J Biol Chem
247: 5312-5321.
Tfelt-Hansen, P., and P. Koehler. 2008. History of the use of ergotamine and
dihydroergotamine in migraine from 1906 and onward. Cephalalgia 28: 877-
886.
Thompson, F., J. Stuedemann, and N. Hill. 2001. Anti-quality factors associated with
alkaloids in eastern temperate pasture. Journal of Range Management: 474-489.
Thompson, J. N., and M. L. Scott. 1969. Role of selenium in the nutrition of the chick.
J Nutr 97: 335-342. 10.1093/jn/97.3.335
Truong, A. T., C. Duez, A. Belayew, A. Renard, R. Pictet, G. I. Bell, and J. A. Martial.
1984. Isolation and characterization of the human prolactin gene. EMBO J 3:
429-437.
Tsunoda, M., V. J. Johnson, and R. P. Sharma. 2000. Increase in dopamine metabolites
in murine striatum after oral exposure to inorganic but not organic form of
306
selenium. Arch Environ Contam Toxicol 39: 32-37.
https://doi.org/10.1007/s002440010076
Tucker, H. A., D. Petitclerc, and S. A. Zinn. 1984. The influence of photoperiod on
body weight gain, body composition, nutrient intake and hormone secretion. J
Anim Sci 59: 1610-1620. doi: 10.2527/jas1984.5961610x
USDA. 2017. United States Standards for Grades of Carcass Beef. Livestock, Poultry
and Seed Program. Agricultural Marketing Service., Des Moines, IA.
Van Hoof, V. O., and M. E. De Broe. 1994. Interpretation and clinical significance of
alkaline phosphatase isoenzyme patterns. Crit Rev Clin Lab Sci 31: 197-293.
10.3109/10408369409084677
Vandesompele, J., K. De Preter, F. Pattyn, B. Poppe, N. Van Roy, A. De Paepe, and F.
Speleman. 2002. Accurate normalization of real-time quantitative RT-PCR data
by geometric averaging of multiple internal control genes. Genome Biol 3:
RESEARCH0034. https://doi.org/10.1186/gb-2002-3-7-research0034
Vendeland, S. C., J. A. Butler, and P. D. Whanger. 1992. Intestinal absorption of selenite,
selenate, and selenomethionine in the rat. J Nutr Biochem 3: 359-365.
Vendeland, S. C., J. T. Deagen, J. A. Butler, and P. D. Whanger. 1994. Uptake of selenite,
selenomethionine and selenate by brush border membrane vesicles isolated
from rat small intestine. Biometals 7: 305-312.
Veres, Z., L. Tsai, T. D. Scholz, M. Politino, R. S. Balaban, and T. C. Stadtman. 1992.
Synthesis of 5-methylaminomethyl-2-selenouridine in tRNAs: 31P NMR
studies show the labile selenium donor synthesized by the selD gene product
307
contains selenium bonded to phosphorus. Proc Natl Acad Sci 89: 2975-2979.
Vestn OftalmolMader, M., N. Kolbus, D. Meihorst, A. Kohn, W. Beuche, and K.
Felgenhauer. 1994. Human intestinal alkaline phosphatase-binding IgG in
patients with severe bacterial infections. Clin Exp Immunol 95: 98-102.
Vinall, H. N. 1909. Meadow fescue: its culture and uses. US Dept. of Agriculture.
Wagenaar, G. T., W. J. Geerts, R. A. Chamuleau, N. E. Deutz, and W. H. Lamers. 1994.
Lobular patterns of expression and enzyme activities of glutamine synthase,
carbamoylphosphate synthase and glutamate dehydrogenase during postnatal
development of the porcine liver. Biochim Biophys Acta 1200: 265-270. doi:
10.1016/0304-4165(94)90166-X
Wahlen, R., L. Evans, J. Turner, and R. Hearn. 2005. The use of collision/reaction cell
ICP-MS for the determination of elements in blood and serum samples.
Spectroscopy, 20(12): 84-89.
Waller, J. C. 2009. Endophyte effects on cattle. Tall Fescue for the Twenty-first Century:
289-310.
Wallwey, C., and S. M. Li. 2011. Ergot alkaloids: structure diversity, biosynthetic gene
clusters and functional proof of biosynthetic genes. Nat Prod Rep 28: 496-510.
10.1039/c0np00060d
Wang, C., S. Yang, N. Zhang, Y. Mu, H. Ren, Y. Wang, and K. Li. 2014. Long-term
supranutritional supplementation with selenate decreases hyperglycemia and
promotes fatty liver degeneration by inducing hyperinsulinemia in diabetic
db/db mice. PLoS One 9: e101315. 10.1371/journal.pone.0101315
308
Waschulewski, I. H., and R. A. Sunde. 1988. Effect of dietary methionine on utilization
of tissue selenium from dietary selenomethionine for glutathione peroxidase in
the rat. J Nutr 118: 367-374. 10.1093/jn/118.3.367
Wasson, R. G., A. Hofmann, and C. A. Ruck. 1978. The road to Eleusis. Unveiling the
Secret of the Mysteries, New York.
Watabe, M., K. Aoyama, and T. Nakaki. 2008. A dominant role of GTRAP3-18 in
neuronal glutathione synthesis. J Neurosci 28: 9404-9413.
10.1523/JNEUROSCI.3351-08.2008
Watford, M. 2000. Glutamine and glutamate metabolism across the liver sinusoid. J
Nutr 130: 983S-987S. 10.1093/jn/130.4.983S
Watford, M., V. Chellaraj, A. Ismat, P. Brown, and P. Raman. 2002. Hepatic glutamine
metabolism. Nutrition 18: 301-303. doi: 10.1016/S0899-9007(02)00739-6
Weber, H. P. 1980. The molecular architecture of ergopeptines: a basis for biological
interaction. Adv Biochem Psychopharmacol 23: 25-34.
Weiner, I. D., R. T. Miller, and J. W. Verlander. 2003. Localization of the ammonium
transporters, Rh B glycoprotein and Rh C glycoprotein, in the mouse liver.
Gastroenterology 124: 1432-1440. https://doi.org/10.1016/S0016-
5085(03)00277-4
Weiss, W. P., and J. S. Hogan. 2005. Effect of selenium source on selenium status,
neutrophil function, and response to intramammary endotoxin challenge of
dairy cows. J Dairy Sci 88: 4366-4374. 10.3168/jds.S0022-0302(05)73123-4
Welsh, F. A. 1972. Changes in distribution of enzymes within the liver lobule during
309
adaptive increases. J Histochem Cytochem 20: 107-111. 10.1177/20.2.107
Wernicki, A., R. Urban-Chmiel, M. Kankofer, P. Mikucki, A. Puchalski, and S.
Tokarzewski. 2006. Evaluation of plasma cortisol and TBARS levels in calves
after short-term transportation. Revue de médecine vétérinaire 157: 30.
Wolffram, S., F. Arduser, and E. Scharrer. 1985. In vivo intestinal absorption of selenate
and selenite by rats. J Nutr 115: 454-459. 10.1093/jn/115.4.454
Wright, P. L., and M. C. Bell. 1966. Comparative metabolism of selenium and tellurium
in sheep and swine. Am J Physiol 211: 6-10. 10.1152/ajplegacy.1966.211.1.6
Wu, Z., R. A. Irizarry, R. Gentleman, F. Martinez-Murillo, and F. Spencer. 2004. A
model-based background adjustment for oligonucleotide expression arrays.
Journal of the American statistical Association 99: 909-917.
Xu, X.-M., B. A. Carlson, H. Mix, Y. Zhang, K. Saira, R. S. Glass, M. J. Berry, V. N.
Gladyshev, and D. L. Hatfield. 2006. Biosynthesis of selenocysteine on its
tRNA in eukaryotes. PLoS biology 5: e4.
Xue, Y., S. Liao, J. Strickland, J. Boling, and J. Matthews. 2011. Bovine neuronal
vesicular glutamate transporter activity is inhibited by ergovaline and other
ergopeptines. J Dairy Sci 94: 3331-3341. https://doi.org/10.3168/jds.2010-3612
Yedgar, S., T. E. Carew, R. C. Pittman, W. F. Beltz, and D. Steinberg. 1983. Tissue sites
of catabolism of albumin in rabbits. Am J Physiol 244: E101-107.
10.1152/ajpendo.1983.244.1.E101
Yokus, B., and U. D. Cakir. 2006. Seasonal and physiological variations in serum
chemistry and mineral concentrations in cattle. Biol Trace Elem Res 109: 255-
310
266. 10.1385/BTER:109:3:255
311
VITA
Yang Jia
Education
Ph.D. Candidate-University of Kentucky, College of Agriculture, Food and
Environment, Lexington, KY. 2014-current. Animal and Food Sciences (Ruminant
Nutritional Physiology).
M.S-University of Kentucky, College of Agriculture, Food and Environment,
Lexington, KY. 2012-2014. Animal and Food Sciences (Ruminant Nutritional
Physiology).
B.S-Nanjing Agricultural University, College of Animal Sciences, Nanjing, China.
2007-2011.
Publications
Refereed Manuscripts
Wang, H., Jia, Y., Huang, W., Zheng, Y., & Li, H. (2014). Individual identification of
Chinese Holstein Bull by 10 STR loci. Molecular Biology Reports, 41:1201-
1206
Jia, Y., Harmon, D. L., Flythe, M. D., & Klotz, J. L. (2015). Interaction of isoflavones
and endophyte-infected tall fescue seed extract on vasoactivity of bovine
312
mesenteric vasculature. Frontiers in Nutrition 2:32. Doi:
10.3389/fnut.2015.00032
Miles, E. D., B. W. McBride, Y. Jia, S. F. Liao, J. A. Boling, P. J. Bridges, and J. C.
Matthews. 2015. Glutamine synthetase (GS) and alanine transaminase
expression are decreased in livers of aged vs. young beef cows and GS can be
up-regulated by 17β-estradiol implants. Journal of Animal Science 93:4500-
4509. Doi 10.2527/jas2015-9294.
Huang, J., Y. Jia, Q. Li, W. R. Burris, P. J. Bridges, and J. C. Matthews. 2017. Hepatic
glutamate transport and glutamine synthesis capacities are decreased in finished
vs. growing beef steers, concomitant with increased GTRAP3-18 content.
Amino Acids, 1-13. Doi: 10.1007/s00726-018-2540-8.
Jia, Y., Q. Li, G. E. Aiken, P. J. Bridges, J. C. Matthews. Form of supplemental
selenium increases plasma prolactin and hepatic glutamine synthesis capacity
of steers grazing endophyte-infected tall fescue. Journal of Animal Science,
Volume 96, Issue 2, 6 March 2018, Pages 715-727. Doi: 10.1093/jas/skx068
Huang, J., Q. Li, Y. Jia, K. Son, C. Hamilton, P. J. Bridges, and J. C. Matthews.
Glutathione Content and Expression of Proteins Involved with Glutathione
Metabolism Differs in Longissimus dorsi, Subcutaneous Adipose, and Liver
Tissues of Finished vs. Growing Beef Steers. Journal of Animal Science. In
press.
Refereed Abstracts
313
Jia, Y., Q. Li, G. E. Aiken, P. J. Bridges, J. C. Matthews. 2016. 057 Effects of Selenium-
form Phenotypes on Steers Grazing Endophyte-Infected Tall Fescue. Journal of
Animal Science, Volume 95, Issue suppl_1, 1 December 2016, Pages 28. Doi:
10.2527/ssasas2017.057.
Huang, J., Y. Jia, Q. Li, W. R. Burris, P. J. Bridges, and J. C. Matthews. 2017. 327
GTRAP3-18 protein negatively modulates canalicular glutamate transport and
glutamine synthesis capacity in the liver of finishing vs. growing beef steers.
Journal of Animal Science, Volume 95, Issue suppl_4, 1 August 2018, Pages
162. Doi: 10.2527/asasann.2017.327.
Jia, Y., A. A. Adams, W. R. Burris, P. J. Bridges, J. C. Matthews. 2017. 044 The Form
of Selenium in Free-Choice Vitamin-Mineral Mixes Affects the Percentage of
Circulating Neutrophils and Lymphocytes in Beef Calves Subjected to
Combined Weaning and Shipping Events. Journal of Animal Science, Volume
96, Issue suppl_1, 1 March 2018, Pages 23-24. Doi: 10.1093/jas/sky027.044.
Li, Q., Y. Jia, P. J. Bridges, J. C. Matthews. 2017. 040 Forms of Selenium in Vitamin-
Mineral Mixes Differentially Affect the Expression of Genes Responsible for
Prolactin and ACTH Synthesis in Pituitaries of Steers Grazing Endophyte-
Infected Tall Fescue. Journal of Animal Science, Volume 96, Issue suppl_1, 1
March 2018, Pages 21. Doi: 10.1093/jas/sky027.040.
314