Organismal performance assays for detecting adverse health impacts of nutritional and toxic exposures: consequences of dietary fructose

Determining the health impacts of a nutritional regimen, suspected toxicant or other treatment is often a difficult task in both the realms of safety assessment and basic research. There are far too many examples of agents, once considered safe, found later through epidemiology (or other means) to cause adverse health effects. To prevent such experimentation on ourselves there is a great societal need for broad, sensitive assays able to detect toxicity at human-relevant exposure levels. Similarly, basic researchers often lack the experimental tools necessary to determine if a treatment adversely impacts the health of their model organism. We argue that these problems can be partially solved by using house mice in the crucible of their natural setting where they are challenged daily by the very tasks that have shaped them for millennia. Quantifying the lifelong fitness of experimentally treated animals directly competing with control individuals offers a sensitive and broad approach for detecting adverse health effects. We refer to this approach as an Organismal Performance Assay (OPA). To illustrate the effectiveness of OPAs, herein we apply them for detecting adverse health consequences of nutritional and toxic exposures. First, using OPAs we capture adverse health impacts (decreased survival, competitive ability and reproduction) from consuming 12.5% kcal of fructose; this finding now represent the lowest observed adverse effect level for dietary fructose. Next, we apply OPAs to determine if differential health impacts occur due to the consumption of one, or the other, of the two common types of added sugar, high fructose corn syrup (fructose and glucose monosaccharides) or table sugar (sucrose, which is a disaccharide of fructose and glucose), and show that the high fructose corn syrup diet increases mortality and decreases reproduction of female mice compared to sucrose, providing the first experimental evidence that the two most common forms of caloric sweeteners have differential health impacts. Next, we use OPAs to determine if an acute exposure to 3mg/kg of amine-terminated generation seven poly amido-amine dendrimers, the current maximum tolerated dose, is actually toxic and find that it is not. Finally, to address the criticism that OPAs do not lead to the underlying mechanisms of observed organismal outcomes, we illustrate the discovery of the molecular basis of the first phenomenon revealed using OPAs, major histocompatibility complex (MHC)-based mating preferences, which is done in the context of a review paper on the role of MHC during social communication.

ORGANISMAL PERFORMANCE ASSAYS FOR DETECTING ADVERSE HEALTH IMPACTS OF NUTRITIONAL AND TOXIC EXPOSURES: CONSEQUENCES OF DIETARY FRUCTOSE by James S. Ruff A dissertation submitted to the faculty of The University of Utah in partial fulfillment of the requirements for the degree of Doctor of Philosophy Department of Biology The University of Utah August 2012 Copyright © James S. Ruff 2012 All Rights Reserved The U n i v e r s i t y of Utah Gradu a t e School STATEMENT OF DISSERTATION APPROVAL The dissertation of James S. Ruff has been approved by the following supervisory committee members: Wayne Potts Chair 05/11/2012 Date Approved Katherine Beals Member 05/11/2012 Date Approved David Carrier Member 05/11/2012 M. Denise Dearing Member 05/11/2012 Date Approved J. Gregory Lamb Member 05/11/2012 Date Approved and by Neil Vickers the Department of Biology Chair of and by Charles A. Wight, Dean of The Graduate School. ABSTRACT Determining the health impacts of a nutritional regimen, suspected toxicant or other treatment is often a difficult task in both the realms of safety assessment and basic research. There are far too many examples of agents, once considered safe, found later through epidemiology (or other means) to cause adverse health effects. To prevent such experimentation on ourselves there is a great societal need for broad, sensitive assays able to detect toxicity at human-relevant exposure levels. Similarly, basic researchers often lack the experimental tools necessary to determine if a treatment adversely impacts the health of their model organism. We argue that these problems can be partially solved by using house mice in the crucible of their natural setting where they are challenged daily by the very tasks that have shaped them for millennia. Quantifying the lifelong fitness of experimentally treated animals directly competing with control individuals offers a sensitive and broad approach for detecting adverse health effects. We refer to this approach as an Organismal Performance Assay (OPA). To illustrate the effectiveness of OPAs, herein we apply them for detecting adverse health consequences of nutritional and toxic exposures. First, using OPAs we capture adverse health impacts (decreased survival, competitive ability and reproduction) from consuming 12.5% kcal of fructose; this finding now represent the lowest observed adverse effect level for dietary fructose. Next, we apply OPAs to determine if differential health impacts occur due to the consumption of one, or the other, of the two common types of added sugar, high fructose corn syrup (fructose and glucose monosaccharides) or table sugar (sucrose, which is a disaccharide of fructose and glucose), and show that the high fructose corn syrup diet increases mortality and decreases reproduction of female mice compared to sucrose, providing the first experimental evidence that the two most common forms of caloric sweeteners have differential health impacts. Next, we use OPAs to determine if an acute exposure to 3mg/kg of amine-terminated generation seven poly amido-amine dendrimers, the current maximum tolerated dose, is actually toxic and find that it is not. Finally, to address the criticism that OPAs do not lead to the underlying mechanisms of observed organismal outcomes, we illustrate the discovery of the molecular basis of the first phenomenon revealed using OPAs, major histocompatibility complex (MHC)-based mating preferences, which is done in the context of a review paper on the role of MHC during social communication. iv To the faculty, staff and students of the University of Utah Department of Biology, for fostering a collaborative and engaging environment. ABSTRACT........................................................................................................................... Ill LIST OF TABLES............................................................................................................... viii LIST OF FIGURES............................................................................................................... ix ACKNOWLEDGEMENTS...................................................................................................xi Chapter 1 USING ORGANISMAL PERFORMANCE DURING NATURAL CHALLENGES TO DETECT ADVERSE HEALTH EFFECTS FROM ENVIORNMENTAL EXPOSURES...................................................................................................................1 Abstract.......................................................................................................................1 Environmental impacts on disease.............................................................................2 Organismal performance assays................................................................................4 Applying OPAs to environmental exposures............................................................6 From phenotype to mechanism..................................................................................8 References....................................................................................................................9 2 HUMAN-RELEVANT LEVELS OF DIETARY FRUCTOSE DECREASE MOUSE COMPETITIVE ABILITY, SURVIVAL AND FITNESS........................................13 Summary paragraph..................................................................................................13 Main body..................................................................................................................14 Methods summary.....................................................................................................21 References..................................................................................................................22 Acknowledgements and contributions.................................................................... 23 Supplementary methods........................................................................................... 28 Supplementary references........................................................................................ 37 3 MODERATE LEVELS OF FRUCTOSE AND GLUCOSE MONOSACCHARIDES INCREASE DEATH RATES AND REDUCE FITNESS OF FEMALE MICE COMPARED TO THOSE FED SUCROSE...............................................................45 TABLE OF CONTENTS Abstract......................................................................................................................45 Introduction............................................................................................................... 46 Methods......................................................................................................................49 Results........................................................................................................................56 Discussion..................................................................................................................59 Acknowledgements...................................................................................................62 References..................................................................................................................63 4 ORGANISMAL PERFORMANCE ASSES SMENT OF AMINE-TERMINATED G7 PAMAM DENDRIMERS SUPPORTS THRESHOLD MODEL OF TOXICITY.....................................................................................................................75 Abstract......................................................................................................................75 Introduction............................................................................................................... 76 Methods......................................................................................................................78 Results........................................................................................................................84 Discussion..................................................................................................................85 Acknowledgements...................................................................................................87 References..................................................................................................................87 5 MHC SIGNALING DURING SOCIAL COMMUNICATION.................................96 Abstract......................................................................................................................97 Introduction............................................................................................................... 98 Signaling of MHC genotype: molecular mechanisms...........................................98 MHC as a signal in individual recognition...........................................................102 MHC as a signal in kin recognition...................................................................... 105 MHC as a signal of genetic compatibility in mate choice...................................109 MHC and signals of quality in mate choice..........................................................112 MHC evolution: what are the primordial functions?........................................... 113 Conclusion.............................................................................................................. 114 Acknowledgements.................................................................................................115 References............................................................................................................... 115 vii LIST OF TABLES Table 52.1. Mixed model results for competitive ability, reproduction and mass................41 52.2. Summary statistics of plasma measures...............................................................42 52.3. Formulation of fructose diet..................................................................................43 52.4. Formulation of control diet.................................................................................... 44 3.1. Formulation of fructose/glucose diet................................................................... 72 3.2. Formulation of sucrose diet..................................................................................73 3.3. Mixed model results for competitive ability, reproduction and mass................74 4.1 Summary of mixed model results for competitive ability..................................95 5.1. Summary of studies investigating MHC-genotype signaling in social communication................................................................................................99-100 5.2. MHC correlations with secondary sexual traits and mating preferences........................................................................................................... 112 LIST OF FIGURES Figure 2.1 Survival of fructose-fed and control animals within OPA enclosures by sex...... 25 2.2 Reproduction of fructose-fed and control animals within OPA enclosures by sex 26 2.3 Glucose tolerance of female a,c, and male b,d, fructose-fed and control animals before and after OPA entrance as depicted by the glucose challenge time course plots a,b, and integrated area under the curve values c,d,......................................27 52.1 Body mass of OPA founders over time by sex.........................................................38 52.2 Relative fitness costs of published OPA studies.......................................................39 52.3 Photograph of OPA enclosure................................................................................... 40 3.1 Survival of fructose/glucose and sucrose animals within OPA enclosures by sex 67 3.2 Male competitive ability over time...........................................................................68 3.3 Cumulative reproductive success of OPA founders by sex....................................69 3.4 Body mass of fructose/glucose and sucrose animals within OPA enclosures by sex............................................................................................................................. 70 3.5 Glucose tolerance curves of fructose/glucose-fed and sucrose-fed females prior to release in OPA enclosures....................................................................................... 71 4.1 Survival of treatment and control males.................................................................. 91 4.2 Male competitive ability over time...........................................................................92 4.3 Reproduction of treatment and control animals by sex..........................................93 4.4 Mass of OPA founders at entrance and eight weeks later by sex.......................... 94 5.1 Possible phenotype matching systems using MHC-based odors and their effectiveness for the recognition of kin.........................................................107 x ACKNOWLEDGEMENTS I greatly thank my advisor Wayne Potts for supporting me throughout graduate school and providing me with mentorship in all aspects of the scientific enterprise, as well as far beyond. I am indebted to my advisory committee, Katherine Beals, David Carrier, Denise Dearing, Gregory Lamb, and Wayne Potts for challenging me and providing me with opportunity to grow as a scientist and teacher. I am thankful for the many meaningful collaborative projects in which I engaged, specifically with David Carrier, Lesley Chesson, Chris Cunningham, Jim Ehleringer, Sean Laverty, Jason Kubinak and Mark Shigenaga. Likewise, I am grateful to Katherine Beals, Laurie Dizney, Rick Graham, Jael Malenke, and Neil Vickers for allowing me to be an educator at this university. The Potts lab family has been a continuous source of aid: lab manager Linda Morrison has been an adoptive mother to me over the past ten years; Jason Kubinak and Adam Nelson are the best colleagues, friends, and intellectual nemeses that one could hope to find; Shannon Gaukler and Jeremy Gendelman are promising scientists and it has been a privilege to work with them. Numerous undergraduates and high school students contributed to my dissertation research. I am especially appreciative for the contributions of Sara Hugentobler, Brad Schwartz, Mirtha Sosa, Amanda Suchy and Ruth Tanner. I was also honored to be a member of and supported by both the TGLL (DGE 08-41233) and WEST programs and I would like to particularly thank David Chapman, Don Feener and Holly Godsey, for making these programs a success. Additionally, I was supported by the Department of Biology and my work was supported by an NIH grant (RO1- GM039578) to Wayne Potts. I owe a great deal to my fellow graduate students in my cohort including Lesley Chesson, Chris Cunningham, Jennifer Koop, and Jessica Waite; they are an amazing group of scientist who will do many great things. Finally, I am ever grateful to my spouse Brit, my mother Janie and other family members (both furred and feathered), who are the source of my confidence and inspiration. xii CHAPTER 1 USING ORGANISMAL PERFORMANCE DURING NATURAL CHALLENGES TO DETECT ADVERSE HEALTH EFFECTS FROM ENVIORNMENTAL EXPOSURES Abstract Determining the health impacts of a nutritional regimen, suspected toxicant or other treatment is often a difficult task in both the realms of safety assessment and basic research. There are far too many examples of agents, once considered safe, that are found later through epidemiology to cause adverse health effects. To prevent such widespread experimentation on ourselves and other animals there is a great societal need for broad, sensitive assays able to detect toxicity at relevant exposure levels. Similarly, basic researchers often lack the experimental tools necessary to determine if a treatment adversely impacts the health of their model organism. Examples include geneticists who knock-out genes and see no phenotype, or physiologists whose treatment causes numerous changes in gene expression; although it is seldom clear if these changes are adverse. We argue that these problems can be partially solved by using classic animal models (e.g., house mice) in the crucible of their natural setting where they are challenged daily by the very tasks that have shaped them for millennia. Quantifying the lifelong fitness (and key components thereof) of experimentally treated animals directly competing with control individuals appears to offer a sensitive and broad approach for detecting adverse health effects. Environmental impacts on disease The importance of the role of the social and physical environment on the induction and elucidation of human disease is well established. Examples are numerous and include, but are not limited to, the role of stress in cardiovascular disease, mortality due to heart malformations manifesting themselves during student athletics, and asthmatic conditions brought on by exercise (1-3). The question begs itself, if we know that the social and physical environment is key in both exacerbating and revealing human diseases then why do we ignore the potential influences of environment when conducting animal safety research? Typically, animal subjects are maintained under artificial conditions that do not reflect the natural environments that forged them into existence through natural selection. In essence, to study animals in these conditions is akin to studying people in an asocial environment in which they do not exert themselves, do not encounter hardships and have ad libitum access to well formulated food. When a substance is declared safe, ideally it is safe while practicing a typical vigorous, stressful lifestyle, not simply safe in a setting devoid of challenge. Could the failure to provide natural or seminatural environments for our laboratory animals increase the likelihood that they provide us with misinformation concerning the adversity of experimental treatments? When comparing concordance rates between human and animal studies a certain degree of discrepancy is to be expected, but what is the cause of this disparity? Typically 2 this question is answered by species-based differences in genetics and physiology, and though these differences are real it seems unlikely that they account for the entire explanation. Currently, concordance rates for pharmaceutical safety assessment between rodents and humans are 43% and when rodent plus a nonrodent models are combined concordance increases to 71% (4). Pharmaceutical concordance rates are equally split between false-negatives and false-positive and they are artificially low compared to other environmental exposures as most overtly toxic substances are not considered as potential therapeutic agents. Pharmaceutical concordance rates are arguably the best tracked, but discrepancies in concordance exist in toxicology and nutrition as well. In toxicology they are generally assumed to be approximately 80% for humans and rodents (5). When we compare animal data to that generated from human studies we have changed two major variables, one of course being the species, but the other is the environment in which that organism dwells. Therefore, if we would like to increase the power and translatability of animal research a key first step is recognizing and incorporating the role of a representative natural environment. For decades research groups studying animal behavior, ecology and evolution have used seminatural environments in many animal model systems of biomedical importance including macaques, mice, and pigs, but few researchers have used such systems in the applied fields of biomedicine, nutrition, pharmaceutics and toxicology (6­10). There are notable examples, however, in the areas of feeding psychology and addiction (11, 12). Though there is general applicability in creating more naturalistic settings for many species, the specific alterations and considerations for any given species will be unique. Therefore, though we advocate for numerous animal models to 3 4 incorporate more realistic environments we will specifically address the house mouse (Mus musculus) system, which is the best developed. Organismal performance assays We refer to our methodology as an Organismal Performance Assay (OPA). OPAs use wild house mice in seminatural enclosures where mice treated with a potential toxicant or other experimental manipulation compete directly with control animals. OPAs achieve their sensitivity and breadth because high performance from most physiological systems is required for individual success as determined by survival, social dominance, reproduction and a variety of other components of fitness. Consequently, any health declines that reduce performance of any physiological system (e.g., cardiovascular, neurological, or metabolic) are likely to be detected by OPAs and no a priori assumption about the target organ or mechanism of toxicity has to be made. OPAs are defined as sensitive phenotyping approaches that use seminatural conditions to challenge the physiological performance of control and experimental animals in direct competition with each other. The relative success of control and experimental animals can be compared for any measurable components of fitness, allowing detection and quantification of any reduced performance due to treatment. The design of OPA enclosures is based on the preference of house mice to maintain territories that include isolated, dark, nest sites that offer protection from predators and infanticidal conspecifics (13-15). OPA enclosures measure about 5m by 7m (35m2), but dimensions could vary. Each pen is subdivided into six subsections by hardware cloth, which provides spatial complexity. Each subsection has food and water that is associated with a set of nest boxes in either one of four "optimal" territories, which contain nest boxes in enclosed structures or two "suboptimal" territories with nest boxes in the open. Together, the hardware fences and the two types of nest boxes create environmental complexity in which mice establish nesting sites, territorial boundaries and social hierarchies. OPA enclosures mimic habitat and social environments experienced by mice in nature, and the population density is representative of measurements from wild populations (16). OPAs have been previously used to quantify adverse consequences associated with cousin and sibling-level inbreeding as well as bearing the selfish genetic element known as the t complex (17-19). The primary cause of inbreeding depression is deleterious recessive alleles that are expressed at a higher rate in inbred individuals, and though these negative consequences have been known for centuries actual fitness effects were less clear (20). Two major studies were conducted on mice indicating that the consequences of full-sibling mating are a 10% decline in litter size (21, 22). Further studies were conducted on the surviving inbred offspring, but these mice performed similar to outbred controls. We conducted OPAs on these seemingly normal inbred progeny by competing them against outbred controls and discovered an additional 500% decline in male reproduction (18). We have repeated these experiments at the level of cousin unions and OPAs revealed that this level of inbreeding reduced male fitness by 34%, challenging clinical claims that health effects from cousin-level inbreeding are tolerable (17, 23). Since its discovery half a century ago, the mouse t complex has become a textbook example of a selfish gene. Despite much success characterizing its underlying genetics and transmission distortion effects, the population dynamics of this persistent 5 6 genetic polymorphism has remained paradoxical because population frequencies are far lower than theoretical predictions would suggest (24). Thus, it is likely that some form of selection is operating against the invasion and spread of t haplotypes among wild mouse populations. We used OPAs to discover the missing phenotypes, which were reproductive declines in both t bearing males and females. These reproductive defects reduced t allele frequencies to 49% below transmission distortion expectations (19). In all cases above, OPAs discovered large health declines associated with treatments that had been missed for decades by researchers using conventional laboratory methods. Applying OPAs to environmental exposures The following chapters of this disseration represent the first application of OPAs to detect and quantify health consequences of environmental expsoures. These exposures include both nutrional and toxicological exposures. While previous OPA studies have focused on genetic treatments such as the aformintioned inbreeding and t complex, the application of this technigue is arugabley most needed in the fields of nutrition and toxicology, where substances once considered safe, such as asbestos, DDT, diethylstilbestrol, polycyclic aromatic hydrocarbons (from grilled meat), second-hand smoke and trans fatty acids are often found to be detrimental to health after years of human exposure (25-30). OPAs help us answer the simple but crucial question, does an exposure at a given level make a mouse sick; if OPAs had been utilized to evaluate the safety of the substances mentioned above, decades of human exposure and sickness could have been avoided. In the second chapter, OPAs are applied to dietary fructose to determine if a human relevant exposure level decreases mouse health and performance. Though association between human disease and fructose consumption are well established and many mechanistic aspects of fructose toxicity have been elucidated at high dose levels, no experimental characterization of adversity has been made at exposure levels that are relevant to human consumption (31-37). Using OPAs, however, we determine that fructose exposure at 12.5% kcal results in increased mortality, decreased competitive ability and decreased reproductive success. The data within this chapter now represent the lowest observed adverse effect level for dietary fructose, a level experienced by 13% of Americans (37). The third chapter focuses on using OPAs to determine if differential health impacts are associated with eating high fructose corn syrup (HFCS) (fructose and glucose monosaccharides) or table sugar (sucrose). To date, only two published rodent studies have indicated that these sugars have different impacts; however, the studies used exposure levels far beyond human relevance, and the differences described cannot readily be concluded as adverse (38, 39). Using OPAs we capture clear evidence that an exposure modeling HFCS is more detrimental than table sugar, as females fed a diet modeling HFCS experience increased mortality and decreased reproduction. Within the fourth chapter OPAs are applied to determine if the established maximum tolerated dose of an engineered nanomaterial is actually toxic. Amine-terminated generation seven poly amido-amine (PAMAM) dendrimers are known to be toxic to mice at 10mg/kg body mass as they cause blood coagulation and death (40). Based on this observation the maximum tolerated dose was established at 3/mg/kg. Using OPAs we demonstrate that no adverse effects due to exposure are experienced from a one-time injection at this dose. 7 8 From phenotype to mechanism The fifth and final chapter is a published review illustrating how the initial phenotype characterized using OPAs, mating preferences associated with the Major histocompatibility complex (MHC), has helped lead to the discovery of the underlying molecular mechanism of this phenomenon (41). MHC-based mating preferences were first identified in mice using laboratory tests (42), but the illustration that these preferences existed in naturalistic settings was first made in OPAs (43). This initial discovery spurred further research and now MHC-based mating preferences have been shown in over 20 species of vertebrates including amphibians, birds, fish, and reptiles (44-47). Likewise, the initial OPA discovery illustrates a fascinating discovery that led others to pursue its mechanistic underpinnings and it has now been shown that the peptides known to bind to MHC molecules also bind neuronal receptors in the vomeronasal organ (VNO) and the main olfactory epithelium (48, 49). Remarkably, the VNO sensory receptors bind 10-mer peptides with the same rules used by MHC molecules, where two of the peptides act as anchor positions for binding, while the other eight amino acids are free to vary without affecting binding. This amazing case of convergent evolution creates a seamless link between MHC-mediated immune recognition and MHC-mediated olfactory behaviors. Similarly, detecting disease phenotypes with OPAs offers a model system for discovery of mechanism that is impossible when the disease state remains cryptic. References 1. Dimsdale JE. Psychological stress and cardiovascular disease. J Am Coll Cardiol. 2008 Apr 1;51(13):1237-46. 9 2. 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Female sticklebacks count alleles in a strategy of sexual selection explaining MHC polymorphism. Nature. 2001 Nov 15;414(6861):300-2. 47. Olsson M, Madsen T, Nordby J, Wapstra E, Ujvari B, Wittsell H. Major histocompatibility complex and mate choice in sand lizards. Proceedings of the Royal Society of London Series B-Biological Sciences. 2003 Nov 7;270:S254-S6. 48. Leinders-Zufall T, Brennan P, Widmayer P, S PC, Maul-Pavicic A, Jager M, et al. MHC class I peptides as chemosensory signals in the vomeronasal organ. Science. 2004 Nov 5;306(5698):1033-7. 49. Spehr M, Kelliher KR, Li XH, Boehm T, Leinders-Zufall T, Zufall F. Essential role of the main olfactory system in social recognition of major histocompatibility complex peptide ligands. J Neurosci. 2006 Feb 15;26(7):1961-70. CHAPTER 2 HUMAN-RELEVANT INTAKE OF DIETARY FRUCTOSE DECREASES MOUSE COMPETITIVE ABILITY, SURVIVAL AND REPRODUCTION James S. Ruff1, Amanda K. Suchy1, 2, Sara A. Hugentobler1, Mirtha M. Sosa1, Bradley L. Schwartz1, Linda C. Morrison1, Sin H. Gieng3, Mark K. Shigenaga3 & Wayne K. Potts1 1 Department of Biology, University of Utah, Salt Lake City, UT. 2 School of Life Sciences, Arizona State University, Tempe, AZ. 3 Nutrition and Metabolism Center, Children's Hospital Oakland Research Institute, Oakland, CA Summary paragraph Health impacts of fructose intake at human-relevant concentrations have been difficult to study in rodent models, as unnaturally high doses have been required to demonstrate disease phenotypes. Fructose has increased in the American diet by 50% since the 1970s and over this same period the proportion of individuals suffering from metabolic diseases has dramatically increased1. Fructose consumption has been indicated as a factor in the development of cardiovascular disease, fatty liver, metabolic syndrome, obesity, and type-2 diabetes2-6. However, rodent studies concerning health impacts of fructose have exclusively focused on doses above 20% Kcal for liquid calories and 50% for dry, and therefore largely characterize effects that are outside of the range of typical human exposure7-10. Here we report data produced by a novel methodology referred to as Organismal Performance Assays (OPAs), in which fructose-treated (12.5% Kcal) and control mice compete in seminatural enclosures for territories, resources, and mates. Within enclosures fructose-fed females experienced a two-fold increase in mortality while males fed fructose controlled 26% fewer territories and produced 25% less offspring. These findings represent the lowest observed adverse effect level (LOAEL) reported to date for fructose and highlight that fructose-induced physiological impairment can be substantial even when clinical endpoint measures are negative or inconclusive. These and other data suggest that OPAs are an innovative technique for detecting mammalian health decline and could have important utility in toxicity assessment of dietary components, environmental exposures, pharmaceuticals and other treatments. Main body Mechanisms for how fructose contributes to obesity, de novo lipogenesis, lipid deregulation and insulin resistance have been recently reviewed11. Support for these mechanisms is seen in rodent models where high-levels of fructose consumption has been shown to increase adiposity, levels of fasting cholesterol and triglycerides, impair glucose tolerance and promote inflammation7-10. However, rodent studies evaluating health impacts of fructose have exclusively focused on doses outside of the range of human exposure. To sensitively assess whether the consumption of fructose decreases mouse health, as measured by survival, competitive ability and reproduction (common measures of evolutionary fitness), at human-relevant concentrations we utilized a novel technique, which we refer to as Organismal Performance Assays (OPAs). OPAs are sensitive 14 phenotyping approaches that use seminatural conditions to challenge the physiological performance of control and experimental animals in direct competition with each other. It is this competition that reveals performance differences between treatment and control individuals. The relative success of control and experimental animals can be compared for any measurable component of fitness. Though the OPA moniker has been recently derived, the technique has been used to detect mating preferences due to major histocompatibility genes and to quantify adverse consequences associated with cousin and sibling-level inbreeding as well as costs of bearing a selfish genetic element12-15. In all cases OPAs quantified substantial health impacts that had been missed by studies using standard laboratory methodologies. Here we use OPAs to test if fructose exposure at a concentration of 12.5% Kcal, a level currently consumed by 13-25% of Americans, decreases mouse health1,16. Additionally, we monitor common metabolic endpoints between experimental and control animals to determine if established mechanisms correlate with whole organism phenotypes observed in OPAs. Survival of female animals within OPA enclosures was impacted by diet, with fructose-fed females experiencing death rates 1.97 times higher than controls (Proportional Hazards (PH), P = 0.048); Fig. 2.1a). There was no difference in survival among replicate populations (PH, P = 0.351) nor did the impact of diet differ among replicate populations (PH, P = 0.554). In regards to male survival, no relationship between diet and survival was detected (PH, P = 0.777); Fig. 2.1b). Survival did not differ among replicate populations 15 16 (PH, P = 0.438) nor did the impact of diet differ among replicate populations (PH, P = 0.311). Male competitive ability was adversely affected by fructose feeding, with fructose-fed animals defending 25.9% fewer territories than control males throughout the study. At week three (model intercept) control males occupied 47.9% of territories and fructose-fed males only 35.5%. This difference was found to be significant (Generalized Linear Mixed Model (GLMM), P = 0.036). No effects of time or diet by time were detected on territorial acquisition indicating that the competitive advantage of control males was consistently maintained throughout the study. For a complete readout of all mixed model results see Table S2.1. Female reproductive success was impacted by diet in two distinct and opposing ways (Fig. 2.2a). First, reproduction of control females at week eight (model intercept) was 23.81 ± 2.71 (M ± S.E.M.) offspring per population and for fructose-fed females it was 36.24 ± 3.11 offspring per population, this difference was significant (GLMM, P < 0.0001). Second, while the reproductive output of control females increased significantly over time at a rate of 1.02 ± 0.01 offspring per week (GLMM, P = 0.042), fructose-fed animals exhibited significantly reduced reproduction rate of -0.99 ± 0.00 offspring per week, the rates between fructose-fed and control females significantly differed (GLMM, P < 0.0001). Male reproductive success was negatively impacted by diet, with fructose-fed males siring 25.3% fewer offspring per population than controls (Fig. 2.2b). Diet did not significantly affect the level of reproduction at week eight (model intercept) with control males producing 14.21 ± 1.88 (M ± S.E.M.) male offspring per population and fructose- fed males producing 14.94 ± 1.99. However, there was a significant diet by time interaction causing fructose-fed males to sire 0.98 ± 0.05 fewer male offspring per week per population than controls (GLMM, P = 0.035). A marginally significant effect of time alone on male reproduction was also found (GLMM, P = 0.088). Diet did not impact the mass of population founders at week zero (Fig. S2.1). Nor did the diets have differential impacts on mass over time or between the sexes. Female glucose tolerance, as assessed by intraperitoneal glucose tolerance tests (IPGTT), was impacted by both diet and environment (Fig. 2.3a,c); fructose-fed females had decreased rates of glucose clearance overall (ANOVA, N = 39, P = 0.037) as did females in cages before OPA release compared to those inhabiting OPA enclosures (ANOVA, P = 0.024). No interaction between diet and environment was detected (ANOVA, P = 0.182). With posthoc tests, only the difference between dietary groups in cages prior to OPA entrance was found to be significant. In cages fructose-fed females had Area Under the Curve (AUC) values 1.42 times higher than controls (Fructose-fed 29,384 ± 2,597: Control 20,719 ± 1,692 mg/dL/120 minutes). Male glucose clearance rates were not affected by diet (ANOVA, N = 25, P = 0.519), though, like females, there was a large effect of environment, with males in cages prior to OPA release having higher levels then postrelease (ANOVA, P < 0.0001; Fig. 2.3b,d). No interaction between diet and environment was detected (ANOVA, P = 0.190). Fasting measures of plasma cholesterol, glucose, insulin, and triglycerides of both female and male animals prior to OPA entrance were not impacted by diet. All plasma measure data were also analyzed with the sexes combined revealing that total cholesterol 17 was 1.69 times higher in fructose-fed animals (t-test, t =2.271, df = 30, P = 0.031; Table S2.2). Though nearly twice as many fructose-fed females died there was no clear pattern detected in regards to female reproductive success. Female reproduction was difficult to interpret as fructose-fed females had significantly higher reproduction early in the study as well as significantly lower reproduction as the study progressed. The decreased reproduction over time experienced by fructose-fed females was likely due to their significantly increased mortality. It is not surprising to see milder treatment-induced reproductive effects in females than males, as this has been seen in previous OPA studies13-15. Overall, fructose-fed males were outcompeted by control animals as measured by competitive ability and reproduction. Since death rates did not differ, it is likely that the lower reproduction of fructose males was due to their decreased ability to defend territories. The relationship between competitive ability and reproductive success is well established and has been seen before in OPAs13-15. Cholesterol was the only fasting plasma measure that may be predictive of the organismal impairment exhibited by fructose-fed animals in OPAs as no difference was seen in plasma glucose, insulin, or triglyceride concentrations. These data provide partial support that the fructose-fed animals may be suffering from increased levels of lipid deregulation prior to OPA entrance. Impaired glucose clearance rates of fructose-fed females compared to controls prior to OPA entrance may reflect an as of yet to be identified physiological alteration that may underlie and be predictive of increased risk of death within OPA enclosures. 18 However, this impairment in glucose clearance disappears within two weeks of residing in OPAs, well before the majority of deaths have occurred. No similar observations were made in regards to male glucose clearance. The sex-specific nature of these findings is interesting and may be due to the intense metabolic demands experienced by females undergoing gestation and lactation. The finding that both dietary groups, as well as both sexes, markedly increased their rates of glucose clearance after entering OPAs is likely due to increased activity demanded by their new environment17. The above findings provide direct evidence of adverse health impacts due to fructose intake at 12.5% Kcal. The increased rates of mortality and decreased reproduction observed in this study now represent the LOAEL for dietary fructose. These adverse organismal-level findings are detectable while standard clinical measures are either unaltered, (mass, glucose, insulin, and triglycerides) or inconclusive (cholesterol and glucose tolerance), indicating that either our current mechanistic understanding of fructose induced toxicity is incomplete and/or that available clinical measures are not of sufficient sensitivity to reflect the physiological impairments leading to early death in females and drop in reproductive capacity in males. We detected substantial adverse outcomes due to an added sugar exposure consisting of a 1:1 ratio of fructose and glucose amounting to 25% Kcal. Our results provide evidence that added sugar consumed at concentrations currently considered safe exerts dramatic adverse impacts on mammalian health18,19. Many researchers have already made calls for reevaluation of these safe levels of consumption11; whereas, others have advocated for more drastic regulatory measures to curtail sugar consumption20. 19 Though OPAs detected profound differences in reproductive output and survival between fructose-fed and control animals the results from our studies are likely conservative. First, OPAs were terminated at 34 weeks because of the common, diet independent, high-rates of male attrition; it is likely that if the study continued for the entirety of the mouse lifespan that reproductive outputs between the treatments would continue to diverge. Second, at the start of OPA assessment all animals were put on the same fructose enriched diet, meaning that all of the adverse effects of the "fructose diet" are a consequence of exposure prior to OPA entrance. Third, our fructose diet was based on a modified chow and not a refined diet; meaning that our fructose-fed animals showed impairment despite having the remainder of their diet being highly nutritive with optimum mineral and vitamin composition. Quantifying the ultimate negative impact on a mammal due to a treatment is a difficult undertaking and requires long-term studies that follow subjects, as they inhabit a relevant environment with associated stresses. Because of this, such studies have largely fallen under the purview of human epidemiology or clinical trials. By directly assessing the impacts of a treatment on the performance of house mice in OPAs we are capable of bridging the environmental relevance and longitudinal nature of human studies with the controllability and feasibility of animal models. These fructose data along with other similar successes using OPAs suggest that this and similar approaches will be an important tool in the detection and quantification of adversity caused by a wide array of treatments13-15. Since output measures (survival, competitive ability and reproduction) are similar across experiments, OPAs allow for the direct comparison of disparate treatments. For example our data indicate that this fructose diet is as detrimental to male reproduction 20 21 as cousin-level inbreeding (Fig. S2.2). Currently, there is a great need for sensitive toxicity assessment methods that work across a broad range of experimental manipulations. This need is particularly strong for both pharmaceutical science where 73% of drugs that pass preclinical trials fail due to safety concerns and for toxicology, where shockingly few compounds receive long-term testing21,22. Methods summary Wild derived house mice were exposed under caged conditions to either a diet containing a 1:1 ratio of fructose and glucose monosaccharides amounting to 25% Kcal from added sugar (fructose diet), or to a control diet (free of added-sugar) from weaning through adulthood. Experimental and control animals (n=156) were then used to cofound six independent OPA populations (Fig. S2.3). Once in OPAs, all mice were fed the fructose diet. Populations were maintained for 32 weeks and differential performance between control and experimental founders was monitored for survival, competitive ability, and reproduction. Survival was ascertained by periodic checking for corpses, competitive ability through the use of passive integrated transponder (PIT) tags and PIT tag readers, and reproduction by genetically analyzing offspring produced within enclosures. Founder mass was assessed over the course of the study. In an additional population not used to assess any of the above endpoints, glucose tolerance was assessed in individuals before OPA entrance and again two weeks after release. Fasting cholesterol, glucose, insulin, and triglycerides, were also measured in a subset of animals at the end of the dietary exposure. 1 2 3 4 5 6 7 8 9 10 11 12 13 22 References Vos, M. B., Kimmons, J. E., Gillespie, C., Welsh, J. & Blanck, H. M. Dietary fructose consumption among US children and adults: the Third National Health and Nutrition Examination Survey. Medscape J Med 10, 160, (2008). Fung, T. T. et al. Sweetened beverage consumption and risk of coronary heart disease in women. Am J Clin Nutr 89, 1037-1042, (2009). Ouyang, X. et al. Fructose consumption as a risk factor for non-alcoholic fatty liver disease. J Hepatol 48, 993-999, (2008). Dhingra, R. et al. Soft drink consumption and risk of developing cardiometabolic risk factors and the metabolic syndrome in middle-aged adults in the community. Circulation 116, 480-488, (2007). Bray, G. A., Nielsen, S. J. & Popkin, B. M. Consumption of high-fructose corn syrup in beverages may play a role in the epidemic of obesity. Am J Clin Nutr 79, 537-543, (2004). Gross, L. S., Li, L., Ford, E. S. & Liu, S. Increased consumption of refined carbohydrates and the epidemic of type 2 diabetes in the United States: an ecologic assessment. Am J Clin Nutr 79, 774-779, (2004). Jurgens, H. et al. Consuming fructose-sweetened beverages increases body adiposity in mice. Obes Res 13, 1146-1156, (2005). Kelley, G. L., Allan, G. & Azhar, S. High dietary fructose induces a hepatic stress response resulting in cholesterol and lipid dysregulation. Endocrinology 145, 548­555, (2004). Thresher, J. S., Podolin, D. A., Wei, Y., Mazzeo, R. S. & Pagliassotti, M. J. Comparison of the effects of sucrose and fructose on insulin action and glucose tolerance. Am J Physiol Regul Integr Comp Physiol 279, R1334-1340, (2000). Bergheim, I. et al. Antibiotics protect against fructose-induced hepatic lipid accumulation in mice: role of endotoxin. J Hepatol 48, 983-992, (2008). Stanhope, K. L. Role of fructose-containing sugars in the epidemics of obesity and metabolic syndrome. Annu Rev Med 63, 329-343, (2012). Potts, W. K., Manning, C. J. & Wakeland, E. K. Mating patterns in seminatural populations of mice influenced by MHC genotype. Nature 352, 619-621, (1991). Ilmonen, P. et al. Experimental infection magnifies inbreeding depression in house mice. Journal o f Evolutionary Biology 21, 834-841, (2008). 23 14 Meagher, S., Penn, D. J. & Potts, W. K. Male-male competition magnifies inbreeding depression in wild house mice. Proc. Natl. Acad. Sci. U.S.A. 97, 3324­3329., (2000). 15 Carroll, L. S., Meagher, S., Morrison, L., Penn, D. J. & Potts, W. K. Fitness effects of a selfish gene are revealed in an ecological context. Evolution 58, 1318­1328, (2004). 16 Marriott, B. P., Olsho, L., Hadden, L. & Connor, P. Intake of added sugars and selected nutrients in the United States, National Health and Nutrition Examination Survey (NHANES) 2003-2006. Crit Rev Food Sci Nutr 50, 228-258, (2010). 17 Suzuki, M., Shindo, D., Kimura, M. & Waki, H. Effects of exercise, diet, and their combination on metabolic-syndrome-related parameters in OLETF rats. Int J Sport Nutr Exerc Metab 21, 222-232, (2011). 18 Naitonal Research Council. Dietary Reference Intakes for Energy, Carbohydrate, Fiber, Fat, Fatty Acids, Cholesterol, Protein, and Amino Acids (Macronutrients). (The National Academies Press, 2005). 19 Dietary Guidelines Advisory Committee. Report of the Dietary Guidelines Advisory Committee (DGAC) on the Dietary Guidelines for Americans, (2010). 21 Lipsky, M. S. & Sharp, L. K. From idea to market: the drug approval process. J Am BoardFam Pract 14, 362-367, (2001). 22 Nel, A., Xia, T., Madler, L. & Li, N. Toxic potential of materials at the nanolevel. Science 311, 622-627, (2006). Acknowledgements and contributions Acknowledgements We thank D. Dearing and A. Torregrossa for aid in experimental design; S. Laverty for statistical modeling assistance; and P. Ault, S. Ault, D. Pearson and R. Tanner for help in data collection. This work was supported by NIH grant RO1- GM039578 and was partially conducted while W.K.P was supported by NSF grant DEB 09-18969. J.S.R. was supported by an NSF GK-12 Educational Outreach Fellowship (DGE 08-41233). M.M.S. was supported by the NSF funded Western Alliance to Expand Student Opportunities (WAESO). Author Contributions J.S.R, M.K.S., and W.K.P designed the experiment. J.S.R., A.K.S, S.A.H, M.M.S., B.L.S, and L.C.M. maintained OPA enclosures and collected the associated data. J.S.R. and A.K.S collected plasma. S.H.G. obtained plasma measures. J.S.R analyzed data and wrote the manuscript. All authors discussed results and commented on the manuscript. 24 Percent survival 25 A B Time (weeks) Time (weeks) Figure 2.1. Survival of fructose-fed and control animals within OPA enclosures by sex. a, Fructose-fed females experienced a death rate twice that of control females (P = 0.048). b, This pattern was not not seen in males (P = 0.778). 26 A B Figure 2.2. Reproduction of fructose-fed and control animals within OPA enclosures by sex. a, Fructose-fed females produced significantly more offspring early in the study (P < 0.0001), though this effect was negated due to a significant decrease in fructose-fed female reproduction over time (P < 0.0001). b, Male reproductive success was negatively impacted by diet, as fructose-fed males had a 25% reduction in reproductive output relative to controls (P = 0.036). Lines connect means and error bars represent standard error. A B 27 500n ^ 400- "5> E 300H o inoo 200H _2 O 100- Fructose Cage Control Cage Fructose OPA Control OPA 500-I ^ 400 O) E 300 o in oo _2 O 100- 200- 0 15 30 45 60 75 90 105120 Time (minutes) 0 15 30 45 60 75 90 105120 Time (minutes) 50000-1 <>u L. 3Oai_> T3 c TO a> 40000- 30000- 20000- 10000- Fructose Control ? 50000-1 Cage OPA Cage OPA Figure 2.3. Glucose tolerance of female a,c, and male b,d, fructose-fed and control animals before and after OPA entrance as depicted by the glucose challenge time course plots a,b, and integrated area under the curve values c,d. Fructose-fed females had reduced glucose tolerance relative to controls (P = 0.037). Animals of both sexes and treatments had reduced glucose clearance prior to OPA release F:M (P = 0.024P < 0.0001). Lines and bars represent means and error bars represent standard error. * Denotes significant (P < 0.05) posttest result. Supplementary methods Animals Outbred, wild-derived house mice (Mus musculus) were used in this study, since many laboratory strains do not possess the functional behaviors required for OPA assessment1. Individuals in this study were from the 10th and 11th generation of the colony originally described by Meagher et al.2. Before animals were released into OPA enclosures they were housed according to standard protocols under a 12:12h light:dark cycle with food and water available ad libitum. All protocols were approved by and conducted under the animal care guidelines of the IACUC at the University of Utah. Dietary exposure Exposure to specified diets began at weaning and continued until animals were released into OPA enclosures approximately 26 weeks later. At the time of weaning a litter was split in half and assigned to either the treatment or control group. The Fructose diet (TD.05668) (Harlan Teklad, Madison, WI) contained 25% Kcal from a 1:1 mixture of fructose and glucose monosaccharides, and therefore has the same ratio of these monosaccharides as sucrose and approximately that of the 55:41 ratio found in the high fructose corn syrup (HFCS) used in soft drinks (or 42:53 ratio found in HFCS used in many food preparations). The control diet (TD.05669) (Harlan Teklad, Madison, WI) is identical except for the component coming from the fructose and glucose monosaccharides is replaced by cornstarch and a small amount of raw fiber used to offset mass differences (See Tables S2.3 and S2.4). Upon entrance into OPA enclosures all individuals consume the fructose diet. 28 OPA enclosures OPA enclosures are indoors, measure about 5m by 7m (35m2), and each pen is subdivided into six subsections by hardware cloth, which provides spatial complexity (Fig. S2.3). Each subsection has food and water that is associated with a set of nest boxes in either one of four "optimal" territories, which contain nest boxes in enclosed structures or two "suboptimal" territories with nest boxes in the open. Optimal nest boxes were made of covered plastic storage bins (75 liter) with 5cm diameter entryways and contained four standard mouse cages (also with 5cm entryways), bedding, and food. The suboptimal nest boxes made of plastic planter boxes (61cm long by 15cm wide by 19cm high) fitted with chicken-wire lids and 5cm circular entryways; food containers and one gallon poultry waterers were adjacent to these nest boxes and both provided ad libitum resource access. Together, the hardware fences and the two types of nest boxes created environmental complexity in which mice established nesting sites, territorial boundaries, and social hierarchies. OPA enclosures mimic habitat and social environment experienced by mice in nature and the population density is representative of measurements from wild populations3. To assess impacts of fructose consumption on survival, competitive ability and reproduction six OPA populations were founded by 22-28 individuals, 8-10 males and 14-18 females for a total of 156 individuals (58 male: 98 female). Equal numbers of fructose-fed and control animals were represented for each sex within all populations. No male individual was related at the cousin level or above to any other individual (male or female) within a given population. Relatedness between female founders was also avoided, though in several populations a single pair of sisters was included (a typical 29 condition in natural populations); when this was the case sister-pairs were balanced across diets. Mean age of individuals at the time of population founding was 29.83 ± 3.60 (M ± S.D.) weeks for males and 30.64 ± 3.60 weeks for females. To prevent incidental breeding before the establishment of male social territories, we released placeholder (nonexperimental) females with the experimental males at the onset of each population. After one week, the placeholder females were removed and the experimental females were released into the enclosures marking the start (week one) of the OPA portion of the study. Five of the six populations ran for 34 weeks, while the other replicate had to be terminated early at 26 weeks due to attrition. A seventh population was established under the same criteria above to collect blood samples from individuals under seminatural conditions and ran for only six weeks. This seventh population was not used to assess competitive ability, survival, or reproduction. Male competitive ability One week prior to entrance each founder was implanted with a unique passive integrated transponder (PIT) tag (TX1400ST, BioMark, Boise ID). A set of PIT antennae and readers (FS2001F-ISO, BioMark, Boise ID) were rotated through the six populations at regular intervals throughout the study and placed at each of the optimal and suboptimal feeders, and data were streamed to a computer equipped with data-logging software (Minimon, Culver City, CA). Male social dominance was assigned when a male had >75% of the PIT-tag reads at a single location over the course of a multi-day reader session, and territories were designated as controlled by a fructose or control-fed male based on the dietary exposure of the male controlling them. Female data were collected 30 but results are not reported here as not enough is known about female dominance behavior to use it as a measure of performance. Survivorship Survivorship of population founders was determined by periodic checks in each enclosure. Dead founders were identified by their PIT-tag ID or personalized ear punches and removed from enclosures. Date of death was estimated based on three factors: date of last check, the last date an animal was recorded at a feeding station, and the condition of the corpse. Reproductive success Samples to determine the reproductive success of founders were gathered during "pup sweeps" in which pups born during the previous cycle were removed from the population, sacrificed and tissue samples taken for genetic analysis. The first sweep occurred during week eight of the study and additional sweeps followed every six weeks. This schedule prevented offspring born in the enclosures from breeding. In five of the six populations five pup sweeps occurred while in the remaining replicate only four sweeps were conducted. A total of 1,894 individual samples were collected with an average of 315.67 ± 65.54 (M ± S.D.) per population. Population level reproductive success was determined for fructose and control groups as described previously2. Briefly, in each competition enclosure male and female founders of each treatment were categorized by a common allelic variant on the Y-chromosome and mitochondrial genome, respectively. Allelic assignments were reversed across populations to avoid possible confounding effects of allele types. We obtained 31 1836 (97% of total) mitochondrial and 870 Y- chromosome (92% of total assuming a 1:1sex ratio) genotypes. Metabolic measures In addition to OPA endpoints, traditional metabolic measures associated with fructose-induced disease were taken including body mass, glucose tolerance, plasma fasting cholesterol, glucose, insulin, and triglyceride concentrations. Body mass was assessed in the 156 animals that founded the six OPA enclosures described above at the time they were released into enclosures and at each of the pup sweeps, for a total of six time points. Glucose tolerance was assessed in a different set of individuals composed of 24 females (16 fructose-fed and 8 controls) and 16 males (8 fructose-fed and 8 controls) at two time points, prior to entrance into an OPA enclosure and again two weeks after release. Finally, fasting concentrations of plasma cholesterol, glucose, insulin, and triglycerides were assessed on a third set of 17 female (8 fructose-fed, 9 control) and 15 male (8 fructose-fed, 7 control) animals at the end of the dietary exposure period (i.e., the time point that the OPA founders were released into enclosures). Intraperitoneal Glucose Tolerance Tests (IPGTTs) were conducted by giving an intraperitoneal injection of 1.5mg D-glucose/g body mass after an eight-hour fast. Blood was collected from the retro-orbital sinus prior to glucose injection and 5, 10, 30, 60 and 120 minutes postinjection. This fast duration and bleeding technique were selected because our wild-derived mice do not tolerate fasting or handling stress as well as laboratory strains. Blood samples were immediately centrifuged at 10,000g for 10 minutes after which 8-10^l of plasma was decanted and flash frozen. Samples were 32 shipped on dry ice to the CHORI and glucose concentrations were assessed by the hexokinase method4 . Plasma samples for fasting cholesterol, glucose, insulin, and triglycerides were collected and shipped in the same manner as those for IPGTT. Plasma glucose was measured as described above. To determine plasma total cholesterol and triglyceride concentrations, the Infinity Triglycerides or Cholesterol liquid stable reagent (Thermo Scientific), respectively, were employed. Briefly, plasma or standards were added in duplicate to a 96-well plate and the reagent was added and incubated at 37°C. Through a series of reactions, a colored dye was formed in proportion to the concentration of cholesterol or triglycerides and their levels were measured by the increase of absorbance at 500 nm. Plasma insulin was determined using a direct sandwich ELISA (Mercodia, Uppsala, Sweden). Briefly, plasma or standards were added to a detection antibody-coated 96-well plate. After incubation together with a peroxidase conjugated detection antibody, the substrate TMB was added and allowed to react and subsequently stopped with H2SO4. A colored product was formed in proportion to the concentration of insulin and its level was measured by the increase in absorbance at 450 nm. The homeostatic model assessment of insulin resistance (HOMA-IR) was calculated by first multiplying fasting insulin (mM) and glucose (mM) together, and then dividing by 22.55. Statistical analysis Survival. Survivorship of the 156 founders was analyzed by Cox proportional hazard models with male and female animals assessed separately due to vastly different mortality rates. Day one was defined as when animals entered OPA enclosures. A multivariate model was used to assess the impacts of diet, population, and diet by 33 population. Individuals that survived the duration of the trial or that were removed from the study were censored. In the male data set there were 34 events and 24 censorings while in the female data set there were 24 events and 74 censorings. Male competitive ability. To assess the main effects of diet and time (and a time by diet interaction) on male competitive ability, we used a generalized linear mixed model (GLMM) to predict the probability of ownership. As a territory can only be defended or not, we used a binomial distribution with a logit link to assess the probability of ownership. The numbers of territories controlled within populations by each dietary treatment was assessed at multiple time points throughout the study for a total of 140 observations. The number of possible territories in each population is constant at six and territories were occupied (by a mouse of either diet) or unoccupied. Time, diet and their interaction were treated as fixed effects and population was modeled as a random effect with a random intercept calculated for each. Reproduction. As reproduction data are discrete counts, for each sex we modeled offspring counts over time in a GLMM with a Poisson distribution and a logarithmic link. The model assessed the main effects of diet and time and the interaction on population-level reproduction across the six populations. Reproductive output of each dietary treatment was measured five times (except for one population that was only measured four times) at six-week intervals for a total of 58 observations. Time, diet and their interaction were modeled as fixed effects and population was modeled as a random effect with a random slope and intercept for females and only an intercept for males. The intercept was set at week eight as this was the first time point for which data were available and reproduction at week zero was biologically impossible. Male and female 34 reproduction data were analyzed separately as they were based on separate measurements, with male reproduction being in terms of number of male offspring and female reproduction in terms of total offspring. Mass. A linear mixed-effects model (LMM) was used to assess the main effects of diet, sex and time, as well as their respective interactions on the mass of the 156 population founders. As mass data are continuous, a normal distribution was assumed. Diet, sex, time and their interaction were modeled as main fixed effects and individual and population were modeled as random effects with a random intercept. The intercept was set at week zero as this was the first time point for which data were available and made biological sense. Founders were weighed at week zero and surviving individuals were weighed across the five aforementioned pup sweeps for a total of 713 observations. Due to nested random effects within the model degrees of freedom are not readily calculable and therefore P values are not provided. The authors of the statistical package suggest that estimates with |t| > 2 are deemed significantly different from zero. IPGTT. The area under the curve (AUC) was calculated for plasma glucose concentrations over time using the trapezoid rule. AUC values were calculated for all individuals prior to OPA entrance and two weeks postrelease. Male and female data were analyzed separately as sex has been shown to impact glucose tolerance6. AUC values were compared across time points and dietary treatments using two-way analysis of variance (ANOVA) with Bonferroni's posttests. Sample prior to OPA entrance was 23 females (15 fructose-fed and 8 controls) and 16 males (8 fructose-fed and 8 controls). While the sample two weeks postentrance had 16 females (8 fructose-fed and 8 controls) and 9 males (5 fructose-fed and 4 controls). 35 Fasting plasma cholesterol, glucose, insulin, triglycerides and HOMA-IR. Plasma measures in 17 (8 fructose-fed, 9 control) female mice and 15 male mice (8 fructose-fed, 7 control) were compared between dietary treatments. Sexes were analyzed both separately and combined. Normality of each measurement was assessed with a Shapiro-Wilk normality test. Blood measurements that did not significantly differ from a normal distribution were assessed with t-tests, while those that differed significantly were analyzed with a Mann-Whitney U test. An F-test was used to tests for unequal variance of all blood measurements between dietary groups. All tests were two-tailed and all a values were 0.5. Summaries of normality, and F-test results may be found in Table S2.2. All mixed-effects models were fit in R using the glmer or lmer functions of the lme4 library7 8. For all mixed-effects models several candidate models for the random effects terms were fit to the data including models estimating both intercept and/or slope for random effects. In all cases the model that explained at least some of the variance with random effects and had the lowest AIC score was selected. Neither the significance of any reported fixed effect nor the magnitude of the effect differed between models. Estimates (and significance) were consistent with those obtained when we ignored either the nested structure and repeated measurements of individuals within populations or repeated measurements of individuals or populations. Proportional hazard models were performed in JMP 9.0.3 (SAS institute Inc., Cary NC) and two-way ANOVAs, Mann- Whitney U tests, and t-test were performed in Prism 5.03 (Graphpad Software Inc, La Jolla CA). All a values are 0.05 and all tests were two-tailed. 36 37 Supplementary references 1 Manning, C. J., Potts, W. K., Wakeland, E. K. & Dewsbury, D. A. in Chemical Signals in Vertebrates Vol. VI (eds R.L. Doty & D. Muller-Schwarze) 229-235 (Plenum, 1992). 2 Meagher, S., Penn, D. J. & Potts, W. K. Male-male competition magnifies inbreeding depression in wild house mice. Proc. Natl. Acad. Sci. U.S.A. 97, 3324­3329., (2000). 3 Sage, R. D. in The Mouse in Biomedical Research Vol. I (eds H.L. Foster, J.D. Smalll, & J.G. Fox) 40-90 (Academic Press, 1981). 4 Slein, M. W. Methods o f Enzymatic Analysis. 117-123 (Academic Press, 1963). 5 Matthews, D. R. et al. Homeostasis model assessment: insulin resistance and beta-cell function from fasting plasma glucose and insulin concentrations in man. Diabetologia 28, 412-419, (1985). 6 Ayala, J. E. et al. Standard operating procedures for describing and performing metabolic tests of glucose homeostasis in mice. Dis ModelMech 3, 525-534, (2010). 7 R Development Core Team R: A language and environment for statistical computing (R Foundation for Statistical Computing, Vienna, Austria, 2012). 8 Bates, D., Maechler, M., & Bolker, B. lme4: Linear mixed-effects models using S4 classes v. R package version 0.999375-42 (2011). 9 Ilmonen, P. et al. Experimental infection magnifies inbreeding depression in house mice. Journal o f Evolutionary Biology 21, 834-841, (2008). 10 Carroll, L. S., Meagher, S., Morrison, L., Penn, D. J. & Potts, W. K. Fitness effects of a selfish gene are revealed in an ecological context. Evolution 58, 1318­1328, (2004). 38 A B Figure S2.1. Body mass of OPA founders over time by sex. Diet did not impact the mass of either female a, or male b, animals (LMM; t = -0.87). Founders did significantly gain mass over time (LMM; t= 11.52) with males gaining at decreased rate compared to females (LMM; t= -6.01). The large change in female mass between weeks 0 and 8 is due to pregnancy. Lines connect means and error bars represent standard error. 39 0.0 0.2 0.4 0.6 0.8 1.0 Male fitness relative to controls Figure S2.2. Relative male reproduction costs due to treatment from published OPA studies. Fructose-fed males experienced similar fitness declines to animals inbred at the cousin level, but not as severe as those bearing the selfish genetic element known as the t complex or inbred at the sibling level2,9,10. 40 Figure S2.3. Photograph of OPA enclosure. Enclosures are approximately 35m2, and are subdivided into six subsections by hardware cloth. Each subsection has food (black chimneys) and water (poultry waterers) that is associated with a set of nest boxes in either one of four "optimal" territories, which contain nest boxes in enclosed structures (storage tubs) or two "suboptimal" territories with nest boxes in the open (planter boxes with wire lids). PIT tag readers on the ledge of the enclosure are connected to antennae (black "tennis rackets"), which are placed over each feeding station. Photograph courtesy Ben Sutter. 41 Table S2.1. Mixed model results for competitive ability, reproduction and mass. Male Competitive ability GLMM with binomial distribution and logit link (Intercept at week 3) Random effects Variance Std. Deviation Population (Intercept) 0.0023 0.0479 Fixed effects Estimate Std. Error Z value P r ^ ^ ) Intercept -0.0733 0.1666 -0.440 0.6600 Diet (Fructose) -0.5054 0.2405 -2.102 0.0356* Time -0.0084 0.0114 -0.737 0.4610 Diet (Fructose)*Time -0.0092 0.0169 -0.543 0.5869 Female Reproduction GLMM witl (Intercept at i Poisson distribution and logarithmic link week 8) Random effects Variance Std. Deviation Population (Intercept) 0.0458 0.2140 Population (Slope) 0.0003 0.0183 Fixed effects Estimate Std. Error Z value Intercept 3.1700 0.1078 29.398 <0.0001*** Diet (Fructose) 0.4204 0.0821 5.119 <0.0001*** Time 0.0174 0.0086 2.032 0.0422* Diet (Fructose)*Time -0.0236 0.0057 -4.157 <0.0001*** Male Reproduction GLMM with Poisson distribution and logarithmic link (Intercept at week 8) Random effects Variance Std. Deviation Population (Intercept) 0.0097 0.0984 Fixed effects Estimate Std. Error Z value P r ^ ^ ) Intercept 2.6540 0.1245 21.311 <0.0001*** Diet (Fructose) 0.0503 0.1751 0.287 0.7738 Time 0.0092 0.0054 1.704 0.0884 Diet (Fructose)*Time -0.0174 0.0082 -2.114 0.0345* Mass LMM (Intercept at week 0) Random effects Variance Std. Deviation Individual (Intercept) 5.58350 2.36294 Population (Intercept) 0.48515 0.69653 Fixed effects Estimate Std. Error t value Significance M>2) Intercept 21.6511 0.5929 36.52 Yes Diet (Fructose) -0.6141 0.7044 -0.87 No Sex (Male) 0.5194 0.8099 0.64 No Time 0.2394 0.0208 11.52 Yes Diet (Fructose)*Sex (Male) 0.9643 1.0136 0.95 No Diet (Fructose)*Time 0.0267 0.0268 1.00 No Sex (Male)* Time -0.1768 0.0294 -6.01 Yes * Indicates a p value < 0.05., **< 0.01, ***< 0.001. 42 Table S2.2. Summary statistics of plasma measures Plasma Measure Sex M ± S.D. (n) Fructose/Con. Normally Distributed Fructose/Con. Unequal Variance P Cholesterol mg/dL Female 141.6 ± 40.58 (8) 116.5 ± 34.41 (9) Yes/Yes No 0.186 Male 202.2 ± 23.95 (8) 146.9 ± 16.39 (7) Yes/Yes No 0.087 Both 171.9 ± 15.59 (16) 129.8 ± 10.08 (16) Yes/Yes No 0.031 * Glucose mg/dL Female 102.7 ± 21.78 (8) 98.29 ± 21.98 (9) Yes/No No 1.000 Male 136.4 ± 6.369 (8) 124.3 ± 4.269 (7) Yes/Yes No 0.148 Both 119.5 ± 26.02 (16) 109.7 ± 22.04 (16) Yes/No No 0.396 Insulin ng/mL Female 0.5747 ± 0.1271 (8) 0.3968 ± 0.05674 (9) Yes/Yes No 0.203 Male 2.076 ± 2.290 (8) 1.283 ± 0.4124 (7) No/Yes Yes Fy,6=30.85 p=0.001*** 0.694 Both 1.325 ± 1.763 (16) 0.7846 ± 0.5382 (16) No/Yes Yes F15,15=10.73 p<0.001*** 0.356 Triglycerides Female 44.18 ± 2.939 (8) 45.92 ± 2.172 (9) Yes/Yes No 0.634 Male 47.84 ± 3.261 (8) 48.79 ± 2.565 (7) Yes/Yes No 0.826 Both 46.01 ± 2.173 (16) 47.18 ± 1.643 (16) Yes/Yes No 0.671 HOMA-IR Female 3.346 ± 2.547 (8) 2.036 ± 0.8298 (9) No/Yes Yes Fy,8=9.421 p=0.005** 0.236 Male 16.46 ± 19.73 (8) 8.706 ± 3.221 (7) No/No Yes Fy,6=37.50 P<0.001*** 0.867 Both 9.904 ± 15.18 (16) 4.954 ± 4.024 (16) No/No Yes F15,15=14.23 p< 0.001*** 0.300 * Indicates a p value < 0.05., **< 0.01, ***< 0.001. Normality was assessed with a Shapiro-Wilk test and variance with an F-test. 43 Table S2.3. Formulation of fructose diet. Fructose diet (TD.05668) 25% E from glucose + fructose Ingredient g/kg % mass Protein g/kg CHO g/kg Fat g/kg Wheat, Hard Ground 335.00 33.5 46.57 178.89 6.03 Dextrose, Monohydrate (Cerelose) 111.00 11.1 0 101.18 0 Fructose 101.00 10.1 0 101 0 Corn, Ground 95.00 9.5 7.695 65.74 3.04 Corn Gluten Meal 60 50.00 5 30.35 12.74 1.1 Soybean Meal, 48% 200.00 20 96.6 51 1.8 Dicalcium Phosphate, FG 16.00 1.6 0 0 0 Calcium Carbonate, FG 13.00 1.3 0 0 0 Sodium Chloride NaCl 5.00 0.5 0 0 0 Mineral Mix, TD.80318 1.50 0.15 0.0813 0.6946 0.0321 2 Vitamin Mix, TD.81125 3.00 0.3 0.0918 0.7844 0.0362 7 TBHQ (Antioxidant) 0.008 0.0008 0 0 0 Corn Oil 40.00 4 0 0 40 Cellulose (Fiber) 29.49 2.949 0 0 0 Totals (g/kg) 1000 100 181.38 512.02 52.04 Summary data Total Protein CHO Fat Diet % 100 18.14 51.20 5.20 kcal/kg 3241.96 725.53 2048.08 468.35 kcal % 100 22.38 63.17 14.45 44 Table S2.4. Formulation of control diet. Control diet (TD.05669) Ingredient g/kg % mass Protein g/kg CHO g/kg Fat g/kg Wheat, Hard Ground 335.00 33.5 46.57 178.89 6.03 Corn Starch 225.00 22.5 0.72 202.5 0.45 Corn, Ground 95.00 9.5 7.70 65.74 3.04 Corn Gluten Meal 60 50.00 5 30.35 12.74 1.1 Soybean Meal, 48% 200.00 20 96.6 51 1.8 Dicalcium Phosphate, FG 16.00 1.6 0 0 0 Calcium Carbonate, FG 13.00 1.3 0 0 0 Sodium Chloride NaCl 5.00 0.5 0 0 0 Mineral Mix, TD.80318 1.50 0.15 0.0813 0.6946 0.0321 Vitamin Mix, TD.81125 3.00 0.3 0.0918 0.7844 0.0363 TBHQ (Antioxidant) 0.008 0.0008 0 0 0 Corn Oil 40.00 4 0 0 40 Cellulose (Fiber) 16.49 1.649 0 0 0 Totals (g/kg) 1000.00 100.00 182.10 512.34 52.49 Summary data Total Protein CHO Fat Diet % 18.21 51.23 5.25 kcal/kg 3250.18 728.41 2049.38 472.40 kcal % 22.41 63.05 14.53 CHAPTER 3 MODERATE LEVELS OF FRUCTOSE AND GLUCOSE MONOSACCHARIDES INCREASE DEATH RATES AND REDUCE FITNESS OF FEMALE MICE COMPARED TO THOSE FED SUCROSE Abstract Intake of added sugar has been shown to correlate with the prevalence of many human metabolic diseases and rodent models have characterized many aspects of the resulting disease phenotypes. However, very little work has been done to address if differential health impacts occur due to the consumption of one, or the other, of the two common types of added sugar, high fructose corn syrup (fructose and glucose monosaccharides) or table sugar (the disaccharide of sucrose, which is composed of fructose and glucose monosaccharides). To address this question directly, we fed mice either a diet containing an equal ratio of fructose and glucose monosaccharides or one with an isocaloric amount of sucrose. Exposure lasted from weaning through adulthood, and then animals of both treatments were released into seminatural enclosures where they competed for territories, resources and reproduction. Here, we report that female mice fed a diet containing an equal ratio of fructose and glucose monosaccharides experienced a mortality rate 1.87 times higher and produced 26.4% fewer offspring than females fed the sucrose diet. Interestingly, no differential performance was seen in male animals, 46 indicating a sex-specific outcome of exposure. This study provides the first experimental evidence that fructose and glucose monosaccharides can be more deleterious to mammalian health than the disaccharide sucrose. Introduction Added sugars are defined as sugars and syrups that are added to foods during processing or preparation (1). The two most common forms of added sugar in the American diet are table sugar (sucrose) and high fructose corn syrup (HFCS) (fructose and glucose monosaccharides), which make up 44% and 42% of consumption annually (2). HFCS comes in two main forms, one that is 42% and another that is 55% fructose, with the remainder being glucose. Due to both varieties of HFCS being widely used, the fructose to glucose ratio that is actually consumed is approximately 1:1 (3). Though consumption of HFCS is high in the American population, globally its total consumption is only 8% compared to sucrose (4). Consumption of added sugar has been linked to numerous human disease states and the rapid increase in the prevalence of these diseases is becoming one of the most pressing health concerns world-wide as noncommunicable diseases now kill more people globally than infectious disease (5). Specifically, through epidemiological studies, added sugar consumption has been linked with cardiovascular disease, fatty liver disease, metabolic syndrome, obesity and type-2 diabetes (3, 6-9). Diseases that impact 36%, 11%, 24%, 36% & 11% of American adults respectively (10-14). The fructose portion of added sugar is suspected to be the detrimental component and mechanisms for how it contributes to obesity; de novo lipogenesis, lipid deregulation and insulin resistance have been recently reviewed (15). Support for these mechanisms can be seen in rodent models where high-levels of fructose consumption has been shown to increase adiposity, increase levels of fasting cholesterol and triglycerides and impair glucose tolerance (16-18). Additionally, fructose consumption has been shown to increase portal vein concentrations of bacterial endotoxin and therefore inflammation (19). This indicates that fructose, as opposed to other carbohydrates, has a deleterious impact on health. However, rodent studies concerning health impacts of fructose, with the exception of the data presented in Chapter 2, have exclusively focused on doses above 20% of total calories and often above 50%. Therefore, these studies largely characterize effects that are above the range of typical human exposure. Few experimental studies have attempted to differentiate health consequences of consuming a mixture of fructose and glucose monosaccharides and the disaccharide sucrose. Numerous studies have compared diets containing high levels of fructose alone to those containing isocaloric sucrose and concluded that free fructose is more detrimental than sucrose and therefore that sources of free fructose such as HFCS are more deleterious to health (20). Unfortunately, these studies do not control for the total amount of fructose between treatments, and use a fructose diet that is likely to never be experienced in the real world, where fructose is always found with glucose (21). Of the studies that have directly compared fructose and glucose monosaccharides to sucrose, only two have found significant differences. Thresher et al. (2000) found that rats fed a mixture of fructose and glucose had decreased glucose infusion rates required to maintain euglycemia compared to those fed sucrose, and MyPhoung et al. (2011) found that people absorb more fructose when consuming beverages sweetened with a mixture of fructose and glucose than they do with sucrose sweetened beverages and therefore have elevated 47 48 biomarkers associated with increased fructose consumption (e.g., higher blood pressure) (3, 22). A third study concluded that a mixture of fructose and glucose caused increased mass gain in male rats compared to sucrose, though this claim may be overstepping the data as a direct statistical comparison between these dietary groups was not made (23). To sensitively assess whether the consumption of fructose and glucose monosaccharides decreases mouse health relative to the consumption of sucrose we utilized a novel technique, which we refer to as Organismal Performance Assays (OPAs). OPAs are defined as sensitive phenotyping approaches that use seminatural conditions to challenge the physiological performance of differentially treated animals (i.e., treatment and control) in direct competition with each other. The relative success of individuals in each group can be compared for any fitness measures allowing detection and quantification of any reduced performance due to treatment. Though the OPA moniker has only recently been derived, the technique has been previously used to detect mating preferences due to major histocompatibility genes and quantify adverse consequences associated with cousin and sibling-level inbreeding as well as bearing the selfish genetic element known as the t complex (24-27). In all cases OPAs detected and quantified substantial health impacts that had been missed by previous studies that assessed animals with standard laboratory methodologies. Here we use OPAs to specifically test if a 1:1 ratio of fructose and glucose monosaccharides (fructose/glucose) at a level of 25% kcal, a level currently consumed by 13% of Americans (28), decreases mouse health compared to consumption of an isocaloric sucrose diet. OPA endpoint measures include survival, reproductive success 49 and male competitive ability. Additionally, we monitor mass and glucose tolerance of animals to determine if these measures are predictive of OPA outcomes. Methods Animals Outbred, wild-derived house mice (Mus musculus) were used in this study, as many laboratory strains do not possess the natural and functional behaviors required for OPA assessment (29). Individuals in this study were from the 10th and 11th generations of the colony originally described by Meagher et al. (26). Consanguinity was assessed during the 11th generation and found to be comparable to wild populations (30). Before animals were released into OPA enclosures they were housed according to standard protocols under a 12:12h light:dark cycle with food and water available ad libitum. All protocols were approved by and conducted under the animal care guidelines of the IACUC at the University of Utah. Dietary exposure Exposure to specified diets began at weaning and continued until animals were released into OPA enclosures approximately 40 weeks later. At the time of weaning a litter was split in half and each portion ascribed to either the fructose/glucose or sucrose group. The fructose/glucose diet (TD.05668) (Harlan Teklad, Madison, WI) contained 25% kcal from a 1:1 mixture of fructose and glucose monosaccharides, and approximately models high fructose corn syrup (HFCS). The sucrose diet (TD.05667) (Harlan Teklad, Madison, WI) is identical except for the component coming from the fructose/glucose monosaccharides is replaced by sucrose and has slightly less raw fiber added to offset mass differences. For an exact makeup of each diet see Tables 3.1 and 3.2. Upon entrance into OPA enclosures all individuals consume the glucose/fructose diet. OPA enclosures Indoor OPA enclosures measure 5m by 7m (35m2), and each pen is subdivided into six subsections by hardware cloth, which provides spatial complexity. Each subsection has food and water that is associated with a set of nest boxes in either one of four "optimal" territories, which contain nest boxes in enclosed structures or two "suboptimal" territories with nest boxes in the open. Optimal nesting structures were made of covered, opaque plastic storage bins (75L) with 5cm diameter entryways and contained four standard mouse cages (also with 5cm entryways), bedding and food. The suboptimal nest box is made of plastic planter boxes (61cm long by 15cm wide by 19cm high) fitted with chicken-wire lids and 5cm circular entryways; food containers and one-gallon poultry waterers were adjacent to these nest boxes and both provided ad libitum resource access. Together, the hardware fences and the two types of nest boxes created environmental complexity in which mice established nesting sites, territorial boundaries, and social hierarchies. OPA enclosures mimic habitat and social environments experienced by mice in nature and the population density is representative of measurements from wild populations (31). To assess impacts of the consumption of differential forms of fructose on survival, competitive ability and reproduction, six OPA populations were founded by 24­30 individuals, 8-10 males and 14-20 females for a total of 160 individuals (56 male:104 female). Equal numbers of fructose/glucose and sucrose-fed animals were represented in 50 each sex within all populations. No male individual was related at the cousin level or above to any other individual (male or female) within a given population. Relatedness between female founders was also avoided, though in several populations a single pair of sisters was included; when this was the case, sister-pairs were balanced across diets. Mean age of founders was 44.43 ± 5.69 (M ± S.D.) weeks for males and 44.28 ± 5.90 weeks for females. To prevent incidental breeding before the establishment of male social territories, we released placeholder (nonexperimental) females with the experimental males at the onset of each population to allow male territory formation prior to release of experimental females. After one week, the placeholder females were removed and the experimental females were released into the enclosures marking the start (week one) of the study. The six populations ran for 32 weeks. Survivorship Survivorship of population founders was determined by periodic checks in each enclosure. Dead founders were identified by their PIT-tag ID or unique ear punches and removed from enclosures. Date of death was estimated based on three factors: date of last check, the last date an animal was recorded at a feeding station, and the condition of the corpse. Reproductive success Samples to determine the reproductive success of founders were gathered during "pup sweeps" in which pups born during the previous cycle were removed from the population, sacrificed and had tissue samples taken for genetic analysis. The first sweep occurred during week eight of the study and additional sweeps followed every six weeks. 51 This schedule prevented offspring born in the enclosures from breeding. In all six of the populations five pup sweeps occurred. A total of 1,397 individual samples were collected with 235.83 ± 96.20 (M ± S.D.) per population. Population level reproductive success was determined for fructose/glucose and sucrose groups as described previously (26). Briefly, in each competition enclosure male and female founders of each treatment were categorized by a common allelic variant on the Y-chromosome and mitochondrial genome, respectively. Allelic assignments were reversed across populations to avoid possible confounding effects of allele types. We obtained 1,336 mitochondrial (95.63% of total) and 667 Y- chromosome (99.85% of total assuming a 1:1sex ratio) genotypes. Male competitive ability One week prior to entrance, each founder was implanted with a unique passive integrated transponder (PIT) tag (TX1400ST, BioMark, Boise ID). Individuals were monitored until release and no redness, swelling, or noticeable infection around the injection site was detected. A set of PIT antennae and readers (FS2001F-ISO, BioMark, Boise ID) were rotated through the six populations throughout the study and placed at each of the optimal and suboptimal feeders, and data were streamed to a computer equipped with data-logging software (Minimon, Culver City, CA). Male social dominance was assigned when a male had >75% of the PIT-tag reads at a single location over the course of a multi-day reader session, and territories were designated as controlled by a fructose/glucose-fed or sucrose-fed male based on the dietary exposure of the male controlling them. Female data were collected, but results are not reported here as 52 not enough is known about female dominance behavior to use it as a measure of performance. Body mass Body mass was assessed in the 160 animals that founded the six OPA populations described above at the time they were released into populations and at each of the aforementioned pup sweeps, for a total of six time points. Glucose clearance Intraperitoneal Glucose Tolerance Tests (IPGTT) were conducted on eight female animals of each dietary treatment at the end of the exposure period by giving an intraperitoneal injection of 1.5mg D-glucose/g body mass after an eight hour fast. Only female animals were assessed as previous work on this population has shown that male clearance rates are not impacted by this level of added sugar consumption compared to a sugar-free control (Chapter 2). Blood was collected from the retro-orbital sinus prior to glucose injection and at 5, 10, 30, 60 and 120 minutes postinjection. Fast duration and bleeding technique were selected because our wild-derived mice do not tolerate fasting or handling stress as well as laboratory strains. Blood samples were immediately centrifuged at 10,000g for 10 minutes after which 8-10^l of plasma was decanted and flash frozen. Samples were shipped on dry ice to the Children's Hospital of Oakland Research Institute, and glucose levels were assessed by the hexokinase method (32). Briefly, plasma or glucose standard were added in duplicate to a 96-well plate and a glucose reagent (Thermo Scientific, Middletown, VA) was added and incubated at 37°C. Through 53 a series of reactions NADH was formed in proportion to the concentration of glucose and its level was measured by the increase of absorbance at 340 nm. Statistical methods Survival. Survivorship of the 160 founders was analyzed by Cox proportional hazard models with male and female animals assessed separately due to vastly different mortality rates. Day one was defined as when animals entered OPA enclosures and is different by a week for males and females (see above). A multivariate model was used to assess the impacts of diet, population and their interaction. Individuals that survived the duration of the trial or that were removed from the study were censored. In the male data set there were 32 events and 24 censorings, while in the female data set there were 40 events and 64 censorings. Male competitive ability. To assess the main effects of diet and time (and a time by diet interaction) on male competitive ability, we used a generalized linear mixed model (GLMM) to predict the probability of ownership. As a territory can only be defended or not, we used a binomial distribution with a logit link to estimate probability of ownership (defense). The numbers of territories controlled within populations by each dietary treatment was assessed at multiple time points throughout the study for a total of 112 observations. The number of territories in each population is constant at six, and territories were occupied (by a mouse of either diet) or unoccupied. The intercept of the model was set at week zero when males were released into the enclosures. Week, time, diet and their interaction were treated as fixed effects and population was modeled as a random effect with a random intercept calculated for each. 54 Reproduction. As reproduction data are discrete counts, for each sex we modeled offspring counts over time in a GLMM with a Poisson distribution and a logarithmic link. The model assessed the main effects of diet and time and the interaction on population-level fitness across the six populations. Reproductive output of each dietary treatment was measured five times at six-week intervals for a total of 60 observations. Time, diet and their interaction were modeled as fixed effects and population was modeled as a random effect with both a random slope and intercept calculated. The intercept was set at week eight as this was the first time point for which data were available and reproduction at week zero was biologically impossible. Male and female reproduction data were analyzed separately as they were based on separate measurements, with male fitness measured in terms of number of male offspring and female fitness in terms of total offspring. Mass. A linear mixed-effects model (LMM) was used to assess the main effects of diet, sex and time, as well as their respective interactions on the mass of the 160 population founders. As mass data are continuous, a normal distribution was assumed. Diet, sex, time and their interaction were modeled as main fixed effects and individual and population were modeled as random effects with a random intercept. The intercept was set at week zero as this was the first time point for which data were available and made biological sense. Founders were weighed at week zero and surviving individuals were weighed across the five aforementioned pup sweeps for a total of 706 observations. IPGTT. The area under the curve (AUC) was calculated for plasma glucose levels over time using the trapezoid rule. AUC values were calculated for eight individuals of each treatment and comparisons were made between groups using a Mann Whitney U- 55 test as the distribution of the sucrose data set was found to vary significantly from that of a normal distribution using a Shaprio-Wilk normality test. All mixed-effects models were fit in R (33) using the glmer or Imer functions of the lme4 library. For all mixed-effects models several candidate models for the random effects terms were fit to the data, including models estimating both intercept and/or slope for random effects. In all cases the model that explained at least some of the variance with random effects and had the lowest AIC score was selected. Estimates (and significance) were consistent with those obtained when we ignored either the nested structure and repeated measurements of individuals within populations or the repeated measurements of individuals or populations. Proportional hazard models were performed in JMP 9.0.3 (SAS institute Inc., Cary NC) and two-way ANOVAs, were performed in Prism 5.03 (Graphpad Software Inc, La Jolla CA). All a values are 0.05 and all tests were two-tailed. Results Survival of female animals within OPA enclosures was impacted by diet, with fructose/glucose-fed females experiencing death rates 1.8734 times higher than sucrose-fed females (Proportional Hazards; x2 = 6.3834, P = 0.0115) (Figure 3.1a). There was no difference in survival among replicate populations (Proportional Hazards; x2 = 3.8825, P = 0.5665) nor did the impact of diet differ between populations (Proportional Hazards; x2 = 8.1634, P = 0.1475). In regards to male survival, no relationship between diet and survival was detected (Proportional Hazards; x2 = 2.6602, P = 0.1029) (Figure 3.1b). Overall survival did not differ among replicate populations (Proportional Hazards; x2 = 4.1569, P = 56 57 0.5271); however, survival of the two treatments did significantly vary across populations (Proportional Hazards; %2 = 11.6310, P = 0.0402). Male competitive ability was not impacted by diet, with fructose/glucose animals controlling approximately the same number of territories as sucrose males at week zero (the intercept) (GLMM; Z = -1.078, P = 0.2809) (Figure 3.2). Fructose/glucose-fed males controlled 39.2% and sucrose-fed males 32.8% of territories throughout the study, leaving approximately 28% unoccupied at any time. No effect of time (GLMM; Z = - 1.328, P = 0.1840) or diet by time (GLMM; Z = 0.322, P = 0.7476) was detected on territorial acquisition. For a complete readout of all GLMM (competitive ability and reproduction) and LMM (mass) results see Table 3.3. Female reproductive success was impacted by diet with fructose/glucose-fed females producing 26.4% fewer offspring than sucrose-fed females (Figure 3.3a). At week eight (the model intercept) fructose/glucose females produced 17.07 ± 2.35 (M ± S.E.M.) offspring per population, while sucrose animals produced 23.97 ± 2.45 offspring per population, this difference was found to be significant (GLMM; Z = 3.479, P = 0.0005). As there was no significant effect of time (GLMM; Z = 0.218, P =0.8275) or a time by diet interaction (GLMM; Z = -0.401, P =0.6883), the deficiency in offspring production suffered by fructose/glucose females at the intercept persisted throughout the duration of the study. In total, fructose/glucose-fed females produced 96.50 ± 20.32 offspring per population and sucrose-fed females produced 131.17 ± 23.81 offspring per population. No clear pattern emerged in regards to male reproductive success and treatment. At week eight (the model intercept) fructose glucose-fed males sired 16.25 ± 3.46 male 58 offspring per population, while sucrose-fed males sired 22.66 ± 3.19 (M ± S.E.M) male offspring per population, this difference was significant (GLMM; Z = 2.569, P = 0.0102). Conversely, sucrose fed-males suffered a significantly decreased rate (-1.06 ± 0.01 male offspring per week) of reproduction in regards to time, while fructose/glucose-fed males reproduced steadily (GLMM; Z =5.986, P < 0.0001). No overall impact of time on reproduction was observed (GLMM; Z = 1.503, P = 0.1329). In total, fructose/glucose-fed males produced 66.67 ± 30.90 male offspring per population and sucrose-fed males produced 47.50 ± 20.26 male offspring per population. Diet did not impact the mass of population founders at the intercept (week zero) with sucrose-fed animals weighing 1.05 ± 0.71g (M ± S.E.M) less than fructose/glucose-fed animals (LMM; t = -1.47) (Figure 3.4). In addition, diet had no impact over time (LMM; t = 0.67) nor did it differentially impact the sexes (LMM; t = 0.48). Female founders significantly gained mass (0.22 ± 0.02g per week) (LMM; t = 9.78) while males largely maintained their entrance masses, the rate differences between males and females were significant (LMM; t = -8.90). However, at the intercept male founders weighed 1.93 ± 0.84g more than females. Due to nested random effects (individuals within populations) contained in the model, degrees of freedom are not readily calculable and therefore P values are not provided. The authors of the statistical package suggest that estimates with |t| > 2 are deemed significantly different from zero. Female glucose tolerance, as assessed by intraperitoneal glucose tolerance tests (IPGTT), was not impacted by diet with fructose/glucose-fed females having an AUC score (mg/dL/120 minutes) of 28945 ± 2812 (M ± S.E.M) and sucrose-fed females 59 having an AUC of 31086 ± 7233 (Mann Whitney, N = 16, U = 25.00, P = 0.5054). For glucose tolerance curves of each treatment see Figure 3.5. Discussion Within OPA enclosures, female mice on the fructose/glucose diet were dramatically outperformed by sucrose-fed females, as demonstrated by a two-fold higher death rate and a 26% relative reduction in reproductive output. These are the first experimental data to show differential health impacts of consuming fructose/glucose versus sucrose. Interestingly, the reproductive disadvantage of fructose/glucose-fed females is present from the start of the study, indicating that even before the unequal mortality rates were manifest, reproduction differentials were present. The increased female death rate observed here (1.873) is remarkably similar to the one (1.966) we detected in a previous OPA competition between animals on the same fructose/glucose diet versus a starch-based control, indicating that perhaps the increased mortality in the previous study was due to free fructose and not total fructose as originally concluded. However, to assess this question, a direct OPA comparison between sucrose and starch control mice is needed. Unlike females, males on the fructose/glucose diet were not outcompeted by their sucrose treated brethren. Fructose/glucose-fed males gained equivalent numbers of territories and experienced similar levels of mortality. Likewise, no overall pattern emerged in regards to reproduction with sucrose-fed male producing more offspring early on, while fructose/glucose-fed males sired more towards the end of the study. This, in conjuncture with our pervious study (Chapter 2), indicates that though male competitive ability and reproduction in OPAs is devastated by the consumption of 25% kcal from added sugar, the form of that added sugar, as either fructose and glucose monosaccharides or the disaccharide sucrose, appears inconsequential; though this should be confirmed with direct competition experiments. The sex-specific nature of our OPA findings is surprising, but not unprecedented. Twice our system has previously revealed a similar mortality pattern, the first being when females harboring the selfish genetic element known as the t complex experienced an increased risk of mortality while males with the t complex did not (27), and the second being that females fed the fructose/glucose diet in a previous study had increased mortality compared to controls while male animals showed no difference (Chapter 2). It is fallacious to assume that experimental treatments will impact the sexes in exactly the same way, as major differences in life histories of female and male mice are well established. For example, a female mouse when pregnant consumes 18-25% more calories than when she is not and therefore is likely to respond differentially to a nutritional treatment than a male (34). Even without considering pregnancy status, sex-specific differences are well established in metabolic processes such as the insulin response for both mice and humans (35, 36). As its importance is being realized, sex-specific reporting of results is becoming increasingly common in human studies and we believe that the data herein also reflect its importance in animal models (37). We found no evidence of differential mass gain or glucose tolerance between animals fed the fructose/glucose and the sucrose diet. This finding is consistent with our previous work in which animals fed the same fructose/glucose diet did not differ in mass from those fed a starch-based control diet (Chapter 2), but it does stand in contrast to conclusions reached by Bocarsly et al. (2010) possibly due to rat/mouse differences (23). 60 Interestingly, our mass data supports that house mice are sexually dimorphic, as males were heavier than nonpregnant females. This observation is consistent with most data, but recent investigations have revealed that some populations and age ranges of wild house mice that are sexually monomorphic (38, 39). Glucose clearance rates did not differ between females raised on either diet, indicating that glucose tolerance was not predictive of the observed mortality and reproductive deficiency. Both the clearance rates of fructose/glucose and sucrose-fed females were similar to those of female mice fed the same fructose/glucose diet in Chapter 2. This observation is in line with data gathered by Thresher and coworkers (2000), that showed overall glucose clearance rates did not differ between these groups (3). The Thesher study did detect differences in the glucose infusion rate required to maintain euglycemia; however, we did not assess that aspect of glucose homeostasis. The mechanistic cause of female mortality and reproductive impairment due to the consumption of the fructose/glucose diet, as opposed to sucrose, is not known. We directly tested for differences in glucose homeostasis and mass gain, two outcomes that previously had been reported as being differentially impacted by similar diets, but no differences emerged. We did not directly assess the rate of fructose uptake after consumption, a third metric that has been shown to differ between similar diets in humans, leaving the possibility that our fructose/glucose fed animals absorbed a higher amount of fructose each time they fed over the feeding trial. If not due to an increase in total fructose intake, then it seems likely that whatever mechanism is at play is taking place at or prior to the absorption of these sugars by enterocytes, as the bond connecting the monosaccharide components of sucrose is hydrolyzed at this time (40). Regardless of 61 what mechanism is contributing to the increased mortality and decreased reproduction of females on the fructose/glucose diet, the organismal-level phenotype characterized herein should greatly aid in its elucidation. Though previous claims have been made that HFCS and sucrose are not equivalent, this study provides the first clear experimental evidence that the consumption of a 1:1 ratio of fructose and glucose monosaccharides can dramatically decrease mammalian health compared to the intake of an isocaloric amount of sucrose. Moreover, the fructose and glucose monosaccharide diet used in this study contains these added sugars at levels that are consumed by 13% of the American population, indicating that human health may also be at risk (28). Though many aspects of fructose toxicity have been well described, there is still much that we can learn from the mouse, especially when we take the crucial role of environment into account for elucidating and exacerbating disease phenotypes. Acknowledgements I thank Wayne Potts, my Ph.D. advisor; Denise Dearing, Mark Shigenaga and Ann-Marie Torregrossa for aid in experimental design; Sean Laverty for statistical modeling assistance; Patricia Ault, Steven Ault, Megumi Hite, Sara Hugentobler, John Lelis, Linda Morrison, Bradley Schwartz, Mirtha Sosa, Amanda Suchy, and Ruth Tanner for help in data collection; and Sin Hoa Gieng for measuring plasma glucose. 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The mouse in biomedical research. New York, N.Y.: Academic Press; 1981. p. 40-90. 32. Slein MW. Methods of enzymatic analysis. Bergmeyer HU, editor. New York, NY: Academic Press; 1963. 33. R Development Core Team. R: A language and environment for statistical computing. Vienna, Austria: R Foundation for Statistical Computing; 2012. 34. Gittleman JL, Thompson SD. Energy allocation in mammalian reproduction. American Zoologist. 1988 1988;28(3):863-76. 35. Ayala JE, Samuel VT, Morton GJ, Obici S, Croniger CM, Shulman GI, et al. Standard operating procedures for describing and performing metabolic tests of glucose homeostasis in mice. Dis Model Mech. 2010 Sep-0ct;3(9-10):525-34. 36. Mittendorfer B. Insulin resistance: sex matters. Curr Opin Clin Nutr Metab Care. 2005 Jul;8(4):367-72. 37. Institute of Medicine. Sex-specific reporting of scientific research: A workshop summary: The National Academies Press; 2012. 66 38. Dewsbury DA, Baumgerdner DJ, Evans RL, Webster DG. Sexual dimorphism for body mass in 13 taxa of muroid rodents under laboratory conditions. J Mammal. 1980 Feb;61(1):146-9. 39. Haisova-Slabova M, Munclinger P, Frynta D. Sexual size dimorphism in free-living populations of Mus musculus: Are male house mice bigger? Acta Zoologica Academiae Scientiarum Hungaricae. 2010;56(2):139-51. 40. Riby JE, Fujisawa T, Kretchmer N. Fructose absorption. Am J Clin Nutr. 1993 Nov;58(5 Suppl):748S-53S. 67 B 100 Z 60- C <DOi . <D a. 40- - Fructose/Glucose - Sucrose T--- I--- I--- I--- |--- I--- I--- I--- I--- |--- I--- I--- I--- I--- |--- I--- I--- I 100-1------- re > ■> i.3 CO +■» c <DOi . <D a. 40 - Fructose/Glucose - Sucrose t -------i-------i------ i-------|------ i------ i-------i------ i------ |-------i-------r t ------ 1- i- r 10 20 30 10 20 30 Time (weeks) Time (weeks) Figure 3.1. Survival of fructose/glucose and sucrose animals within OPA enclosures by sex. a, fructose/glucose-fed females experienced nearly twice the death rate over the course of the study compared to sucrose animals (Proportional Hazards; %2 = 6.3834, P = 0.0115). b, No significant pattern was seen in males (Proportional Hazards; X2 = 2.6602, P = 0.1029). 68 ■P "D Q . O Q. k_ QJ Q. to <U QJ Time (weeks) Figure 3.2. Male competitive ability over time. No difference in territorial acquisition between fructose/glucose and sucrose-fed males was detected (GLMM; Z = -1.078, P = 0.2809). Lines are smoothed representations of mean territoriality over time. Boxes/Circles represent the data points that inform the line. 69 B J 200n 13 0 3 150H Fructose/glucose Sucrose 14 20 26 Time (weeks) 100 75- 50 25 Fructose/glucose Sucrose 8 14 20 26 Time (weeks) 32 Figure 3.3. Cumulative reproductive success of OPA founders by sex. a, Fructose/glucose-fed females produced fewer offspring throughout the study than those fed sucrose (GLMM; Z = 3.479, P = 0.0005). b, Fructose/glucose-fed males produced significantly fewer offspring at the onset of the study (GLMM; Z = 2.569, P = 0.0102), but the advantage enjoyed by sucrose-fed males decayed over time (GLMM; Z =5.986, P < 0.0001). Lines connects population means and errror bars represent standard error. 70 A B Figure 3.4. Body mass of fructose/glucose and sucrose animals within OPA enclosures by sex (a female, b male). No differences between treatment groups were observed (LMM; t = -1.47). Lines connect means of individuals assessed at OPA enterance and at the five pup sweeps, errror bars represent standard error. 71 Time (minutes) Figure 3.5. Glucose tolerance curves of fructose/glucose-fed and sucrose-fed females prior to release in OPA enclosures. No difference between treatment groups was observed (Mann Whitney, N = 16, U = 25.00, P = 0.5054). Lines connect means of individuals assessed at 0, 5, 10 , 30 , 60, and 120 minutes postglucose injection, errror bars represent standard error. 72 Table 3.1. Formulation of fructose/glucose diet. Fructose/glucose diet (TD.05668) 25% kcal rom glucose + fructose Ingredient g/kg % mass Protein g/kg CHO g/kg Fat g/kg Wheat, Hard Ground 335.00 33.5 46.57 178.89 6.03 Dextrose, Monohydrate (Cerelose) 111.00 11.1 0 101.18 0 Fructose 101.00 10.1 0 101 0 Corn, Ground 95.00 9.5 7.695 65.74 3.04 Corn Gluten Meal 60 50.00 5 30.35 12.74 1.1 Soybean Meal, 48% 200.00 20 96.6 51 1.8 Dicalcium Phosphate, FG 16.00 1.6 0 0 0 Calcium Carbonate, FG 13.00 1.3 0 0 0 Sodium Chloride NaCl 5.00 0.5 0 0 0 Mineral Mix, TD.80318 1.50 0.15 0.0813 0.6946 0.0321 2 Vitamin Mix, TD.81125 3.00 0.3 0.0918 0.7844 0.0362 7 TBHQ (Antioxidant) 0.008 0.0008 0 0 0 Corn Oil 40.00 4 0 0 40 Cellulose (Fiber) 29.49 2.949 0 0 0 Totals (g/kg) 1000 100 181.38 512.02 52.04 Summary data Total Protein CHO Fat Diet % 100 18.14 51.20 5.20 kcal/kg 3241.96 725.53 2048.08 468.35 kcal % 100 22.38 63.17 14.45 73 Table 3.2. Formulation of sucrose diet. Sucrose diet (TD.05667) 25% kcal sucrose Ingredient g/kg % mass Protein g/kg CHO g/kg Fat g/kg Wheat, Hard Ground 335.00 33.5 46.57 178.89 6.03 Sucrose 205.00 20.5 0 205 0 Corn, Ground 95.00 9.5 7.70 65.74 3.04 Corn Gluten Meal 60 50.00 5 30.35 12.74 1.1 Soybean Meal, 48% 200.00 20 96.6 51 1.8 Dicalcium Phosphate, FG 16.00 1.6 0 0 0 Calcium Carbonate, FG 13.00 1.3 0 0 0 Sodium Chloride NaCl 5.00 0.5 0 0 0 Mineral Mix, TD.80318 1.50 0.15 0.0813 0.6946 0.032 Vitamin Mix, TD.81125 3.00 0.3 0.0918 0.7844 0.0363 TBHQ (Antioxidant) 0.008 0.0008 0 0 0 Corn Oil 40.00 4 0 0 40 Cellulose (Fiber) 36.49 3.649 0 0 0 Totals (g/kg) 1000.00 100 181.38 514.84 52.04 Summary data Total Protein CHO Fat Diet % 18.14 51.48 5.20 kcal/kg 3253.25 725.53 2059.38 468.35 kcal % 100 22.30 63.30 14.40 74 Table 3.3. Mixed model results for competitive ability, reproduction and mass. Male Competitive GLMM wi