Investigating the Effects of Incremental Conditioning

EXPLORING THE EFFECTS OF REPETITIVE ENDURANCE EXERCISE AND TRYPTOPHAN SUPPLEMENTATION OR DIETARY SOLUBLE FIBER ON THE BEHAVIOUR OF SLED DOGS

Eve Robinson

A Thesis presented to The University of Guelph

In partial fulfilment of requirements for the degree of Master of Science in Animal Biosciences

Guelph, Ontario, Canada

ABSTRACT

EXPLORING THE EFFECTS OF REPETITIVE ENDURANCE EXERCISE AND

TRYPTOPHAN SUPPLEMENTATION OR DIETARY SOLUBLE FIBER ON THE

BEHAVIOUR OF SLED DOGS

Eve Robinson Advisor: University of Guelph, 2020 Dr. Anna-Kate Shoveller

The impacts of repetitive endurance exercise and dietary interventions on the behaviour and voluntary physical activity of dogs has not been previously studied. This thesis investigated the effects of incremental conditioning, supplemental tryptophan and increased dietary soluble fiber on the behaviour and voluntary physical activity of sled dogs. Repetitive endurance exercise generally resulted in a progressive decrease in voluntary physical activity and locomotive behaviours prior to an exercise bout. Additionally, voluntary physical activity increased after two consecutive rest days, indicating a potential recovery from the physiological impacts of endurance exercise. Increasing the tryptophan: large neutral amino acid ratio of the diet reduced agonistic behaviors prior to exercise, however, increasing the soluble fiber content had no effect on any behaviour prior to or following an exercise bout. This research could be used to improve the exercise training regimens and diets of sled dogs and promote their overall performance, health and well-being.

ACKNOWLEDGEMENTS

Firstly, I would like to thank my advisor Dr. Anna-Kate Shoveller for providing me with this opportunity. I would not be where I am today without your support, encouragement, and confidence in me. I would also like thank my committee members, Drs Candace Croney and Lee Niel. Your knowledge and expertise have been invaluable throughout this process. I am extremely grateful to have had this team of women supporting me on this journey.

A big thank you to James Templeman and Emma Thornton, for being part of the core team that made this possible. James, thank you for being a mentor. And thanks for freezing every morning driving the ATV, and for eventually teaching Emma and I to do the same. And Emma, thank you for being by my side every step of the way. This research did not come without challenges, but I am glad we were able to get through them together. Additionally, thank you to all the volunteers and students that put in time and effort to help us.

Thank you to everyone else in the Shoveller lab: Sydney Banton, Fiona Tansil, Julia Guazzelli Pezzali, Cara Cargo-Froom and Renan Donadelli. From help with statistics, to de-stressing with drinks, you have all supported me in so many ways. My experience in graduate school would not have been the same without you.

I would also like to thank all my friends and family for your constant love and encouragement. To my parents, thank you for supporting me (financially and otherwise!) and for allowing me to follow my passion. I will forever be grateful.

To Ralph and Jen from RaJenn Siberian Huskies, thanks for welcoming us into your home and trusting us with your amazing dogs. And to all the dogs, thank you for making it so easy to come to the farm every day.

And finally, thank you to Champion PetFoods and MITACS Accelerate for funding this research and making it possible.

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TABLE OF CONTENTS Abstract ...... ii Acknowledgements ...... iii Table of Contents ...... iv List of Tables ...... vi List of Figures ...... vii List of Abbreviations...... viii Chapter 1: Literature Review...... 1 1.1 Introduction ...... 1 1.2 The effects of endurance exercise on dog behaviour ...... 1 1.2.1 Physiological and behavioural effects of endurance exercise and recovery ...... 2 1.2.2 Fatigue and overtraining...... 5 1.2.3 Future research ...... 6 1.3 The effects of tryptophan on dog behaviour...... 7 1.3.1 Serotonin influence on behaviour and mood ...... 7 1.3.2 Synthesis of serotonin ...... 8 1.3.3 Tryptophan supplementation in dogs ...... 10 1.3.4 Combined influence of tryptophan and exercise on behaviour ...... 12 1.3.5 Future research ...... 13 1.4 The effects of soluble fiber on dog behaviour ...... 14 1.4.1 Gut-brain axis ...... 15 1.4.2 The canine gut microbiome ...... 16 1.4.3 Fiber impacts on canine gut microbiome ...... 18 1.4.4 Combined influence of fiber and exercise on behaviour ...... 20 1.5 Overall conclusions ...... 22 1.6 Thesis Objectives and Hypotheses...... 22 1.7 References ...... 24 Chapter 2: Investigating the effects of incremental conditioning and supplemental dietary tryptophan on the voluntary activity and behaviour of mid-distance training sled dogs1 ...... 35 2.1 Abstract ...... 35 2.2 Introduction ...... 36 2.3 Materials and methods ...... 39 2.3.1 Animals, training regimen and diet ...... 39 2.3.2 Behavioral evaluation ...... 41 2.3.3 Activity monitoring ...... 42 2.3.4 Statistical analysis ...... 42 2.4 Results ...... 44 2.4.1 Behaviour ...... 44 2.4.2 Voluntary activity ...... 50 2.5 Discussion...... 52 2.5.1 Tryptophan effect on aggression-related behaviours ...... 52

2.5.2 Effect of single bout and repetitive exercise on behaviour and activity ...... 54 2.6 Conclusion ...... 56 2.7 References ...... 58 Chapter 3: Investigating the effects of dietary soluble fiber and incremental exercise on the voluntary activity and behaviour of sled dogs ...... 62 3.1 Abstract ...... 62 3.2 Introduction ...... 63 3.3 Materials and methods ...... 65 3.3.1 Animals, training regimen and diet ...... 65 3.3.2 Behavioural evaluation...... 69 3.3.3 Activity monitoring ...... 69 3.3.4 Statistical analysis ...... 69 3.4 Results ...... 70 3.4.1 Pre-run exercise behaviour ...... 70 3.4.2 Post-run exercise behaviour ...... 73 3.4.3 Voluntary physical activity ...... 75 3.5 Discussion...... 77 3.6 References ...... 82 Chapter 4: General Discussion ...... 86 4.1 References ...... 93

LIST OF TABLES Table 2.1. Distance (km) run and ambient daily temperature (˚C) when behavioural evaluations were carried out during 12 weeks of incremental conditioning for dogs fed either a treatment diet containing supplemental Trp compared to dogs fed control diet...... 40 Table 2.2. Description of behavioural parameters analyzed during 5 minutes of video taken immediately pre- and post-exercise for dogs fed either a treatment diet containing supplemental Trp compared to dogs fed control diet...... 41 Table 2.3. Linear regression estimates for the relationship between week of training and the time spent performing a behaviour for sled dogs undergoing 12 weeks of incremental conditioning. . 46 Table 2.4. Average percent of time (%) spent performing observed behaviours during 5-min pre exercise throughout 12 weeks of incremental conditioning...... 47 Table 2.5. Average percent of time (%) spent performing observed behaviours during 5-min post exercise throughout 12 weeks of incremental conditioning...... 49 Table 2.6. Mean voluntary activity counts for control dogs or tryptophan-supplemented (treatment) dogs on active days and rest days during weeks 0, 6 and 11 of a 12-week incremental conditioning period...... 50 Table 3.1 Cumulative distance the dogs ran during each week, and distance run and daily temperatures when behavioural observations took place ...... 67 Table 3.2 Nutrient content and ingredient composition of the control and treatment diet on a dry matter basis...... 68 Table 3.3. Percent of time (%) spent performing observed behaviours during the 5 min pre- exercise period for all dogs1 undergoing 10 weeks of incremental conditioning...... 72 Table 3.4 Percent of time (%) spent performing observed behaviours during the 5-min post- exercise period for all dogs1 undergoing 10 weeks of incremental conditioning ...... 74

LIST OF FIGURES Figure 2.1. Agonistic behaviour performed by sled dogs undergoing 12 weeks of incremental conditioning...... 45 Figure 2.2. Average activity counts of sled dogs undergoing 12 weeks of incremental conditioning...... 51 Figure 3.1. Mean voluntary activity counts during rest days for all dogs (n=12) throughout 10 weeks of incremental conditioning ...... 75 Figure 3.2 Mean voluntary physical activity counts on first rest day and second rest day of all dogs undergoing 10 weeks of incremental conditioning ...... 76 Figure 3.3 Mean voluntary physical activity counts on run days for all dogs undergoing 10 weeks of incremental conditioning ...... 77

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LIST OF ABBREVIATIONS 5-HT: Serotonin AA: Amino acid AAFCO: Association of American Feed Control Officials BBB: Blood brain barrier BDNF: Brain-derived neurotrophic factor BW: Body weight CSF 5-HIAA: Cerebrospinal fluid 5-hydroxyindoleacetic acid CK: Creatine kinase CNS: Central nervous system d: Day (s) ENS: Enteric nervous system FOS: Fructo-oligosaccharide GABA: γ-Aminobutyric acid GF: Germ free GI: Gastrointestinal GIT: Gastrointestinal tract H: Hour (s) km: Kilometer (s) LNAA: Large neutral amino acid (s) MOS: Mannan-oligosaccharide mRNA: Messenger ribonucleic acid NRC: National research council rRNA: Ribosomal ribonucleic acid SCFA: Short chain fatty acid (s) TPH: Tryptophan hydroxylase Trp: Tryptophan wk: Week (s)

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1. Chapter 1: Literature Review 1.1 Introduction Dogs have been used as working and sporting animals, such as in the sled dog industry, for many years (Zink, 2013a). Sled dogs are high endurance athletes that typically run in teams, ranging from 2-18 dogs in size, for long distances spanning multiple days, such as during the

Iditarod (1600km). An appropriate conditioning period is required to ensure sled dogs have the ability to perform at these intense exercise capacities. However, current training techniques are generally based on the anecdotal accounts of mushers with little qualitative data used

(Templeman et al., 2018a). There is a dearth of information on the effects of exercise and conditioning regimens on the behaviour and welfare of high-performance dogs. In addition to appropriate conditioning regimens, nutrition is vital for dog health, well-being and performance.

Alterations in dietary contents such as dietary tryptophan and total dietary fiber have the potential to influence canine behaviour and improve welfare. This review will examine the current literature on the effects of repetitive endurance exercise on sled dog behaviour and well- being. Furthermore, research regarding the ability of tryptophan and soluble fiber to modulate behaviour displayed during training, as well as how these dietary interventions may specifically influence actively-training sled dogs, will be discussed.

1.2 The effects of endurance exercise on dog behaviour The amount of exercise and the conditioning regimen of working dogs is solely the responsibility of the owner and/or trainer, highlighting the importance of understanding the effects of endurance exercise on their physiology and well-being. Twenty-five minutes of moderate exercise a day reduces salivary cortisol, suggesting reduced stress, in individually kennel-housed shelter dogs (Menor-Campus et al., 2011), but the effects of repetitive, endurance

exercise has not been similarly studied. Without appropriate conditioning, it is thought that sled dogs might perform endurance exercise that is greater than their physical and mental capacity, potentially having detrimental effects on their health, such as increasing the risk of injury and fatigue (Zink et al., 2013b). While the physiological effects of repetitive endurance exercise have been investigated for sled dogs (Hinchliff et al., 1993; Hinchliff et al., 1998; McKenzie et al.,

2007; Davis et al., 2008; McKenzie et al., 2008), there is a dearth of research on its effect on behaviour. Behavioural markers that indicate motivation to exercise or recovery from exercise could serve as a practical tool for working dog owners and trainers, to aid in the identification of fatigue or exercise-induced health issues. Being able to differentiate between normal and abnormal behavioural responses to endurance exercise could additionally improve the training regimens of sled dogs and have an overall benefit on their health and welfare.

1.2.1 Physiological and behavioural effects of endurance exercise and recovery The behaviour of actively-training sled dogs likely correlates with the physiological changes that occur during endurance exercise. The physiological impact and recovery from a bout of endurance exercise is dependent on multiple factors, such as genetics (Gulda et al.,

2018), exercise intensity and duration (Paul and Issekuts, 1967, Pasquini et al., 2010), environmental conditions (Kozlowski et al., 1985), nutrition (Reynolds et al., 1997; Wakshlag et al., 2002) and the fitness level of the dog (Reynolds et al., 1995, Davis et al., 2008). During an endurance exercise bout, there is a large increase in the requirement for oxygen and energy substrates in skeletal muscle (Paul and Issekuts, 1967; Hinchcliff et al., 2000). Dogs rely both on carbohydrate and lipid metabolism for energy provision during exercise (Paul and Issekutz,

1967). In order to meet these high demands for energy, both the cardiovascular and respiratory systems increase their function to maximize the delivery of oxygen to the muscles. This requires

an increase in heart rate and respiratory rate and leads to a consequential increase in body temperature (Rovira et al., 2008). Immediately following an exercise bout, dogs experience a return of cardiac, respiratory and body temperature to homeostatic equilibrium, but at different rates. This initial recovery period has been observed to last for up to 30 minutes but will vary depending on exercise intensity and individual differences (Roviera et al., 2008). During this period, dogs may increase lying time to allow for more rapid return to resting respiratory and heart rate; however, the behavioural correlates of this immediate recovery period have not been investigated in dogs.

Additionally, continued recovery of endogenous energy stores may last for hours to days.

While there are no current behavioural markers of long-term recovery from endurance exercise in dogs, voluntary wheel running has been investigated as a behavioural measure in laboratory rodents (Carmichael et al., 2005; Davis et al., 2007; Takahashi et al., 2013). After 150 minutes of forced endurance exercise, the distance of voluntary wheel running decreased, and then gradually increased to pre-exercise levels in either 3 or 4 days (Carmichael et al., 2005; Davis et al., 2007).

It is possible that voluntary physical activity could also be used as a measure of recovery from exercise in dogs. However, researchers have not examined the relationship between various durations or intensities of endurance exercise and the relationship to voluntary physical activity in mice or dogs. Additionally, voluntary wheel running in mice has only been used as an indicator of recovery after a single bout of exercise, not repetitive bouts.

One physiological factor that will determine the time to total recovery from endurance exercise is the extent of glycogen depletion. Glycogen depletion occurs during aerobic exercise and has been demonstrated following single bouts of endurance exercise in sled dogs (Reynolds et al., 1995; Reynolds et al., 1997; Wakshlag et al., 2002). This is a critical factor that may 3

influence voluntary physical activity post-exercise as it is associated with muscle fatigue in humans and mice (reviewed in humans: Ortenblad et al., 2013). Additionally, exercise-induced liver glycogen depletion is correlated with reduced post-exercise voluntary wheel running in mice (Gomes et al., 2009). The rate of glycogen resynthesis following endurance exercise depends on multiple factors, such as diet (Wakshlag et al., 2002) and duration of exercise

(McKenzie et al., 2008). However, sled dogs are exceptional at attenuating the use of glycogen during exercise, suggesting that repeated bouts of exercise prompt the use of other substrates, such as lipids, for energy provision (Costill et al., 1971; McKenzie et al., 2005; McKenzie et al.,

2008). Even though relative glycogen depletion over multiple days of exercise may be minimal for sled dogs, glycogen depletion might still influence recovery behaviour by contributing to muscle fatigue and reducing voluntary activity after an exercise bout.

When appropriate exercise conditioning is performed, various physiological adaptations occur that aid in sustaining the high intensity and duration of exercise and subsequently help to improve performance and recovery (Zink et al., 2013b). The physiological adaptations that occur during this period in dogs include increased cardiorespiratory function (Sneddon et al., 1989;

Stepien et al., 1998), VO2 max, lactate threshold (Proscurshim et al., 1989) and mitochondrial density (Gerth et al., 2015; Miller et al., 2017). Appropriate endurance training involves incremental increases in exercise intensity, duration and frequency, and results in improvements in the exercise capacity of dogs (Zink et al., 2013b). However, if exercise is performed beyond a dog’s capacity and without adequate recovery between exercise bouts, it could lead to fatigue, a decrease in performance and have negative effects on the behaviour and welfare of dogs (Zink et al., 2013b).

1.2.2 Fatigue and overtraining Exercise-induced fatigue can be classified as either central fatigue, which refers to the cognitive aspects of fatigue, or peripheral fatigue, which refers to the performance of the motor systems (Wan et al., 2017). Fatigue is defined as the failure to produce necessary muscle force production and leads to cessation of physical activity (Sale, 1987). There are multiple factors that could potentially impact the onset of fatigue.

One factor that potentially contributes to fatigue during endurance exercise is oxidative stress. Endurance exercise leads to a proportional production of free radicals, a by-product of oxygen consumption, which, when overwhelming the antioxidant defense capacities, causes oxidative stress and contributes to muscle damage (Reid et al., 1992; Ji and Leichtweis, 1997).

Oxidative stress in dogs has been linked to muscle fatigue (Barclay and Hansel, 1991) and reduced performance (Piercy et al., 2001). Sled dogs undergoing 58km runs on 3 consecutive days had a progressive increase in isoprostanes and serum creatine kinase (CK), which are markers of oxidative stress and muscle damage, respectively (Hinchliff et al., 2000). The recovery from oxidative stress is related to the duration of endurance exercise, as dogs who ran for 20 minutes recovered faster than dogs who ran for 4 hours (Pasquini et al., 2010).

Additionally, it is likely that oxidative stress is related to decreased voluntary wheel running in mice (Davis et al., 2007). Following 150 minutes of endurance exercise, CK levels recovered in

48 hours; however, voluntary wheel running took longer to return to baseline measurements, suggesting that there is more than just one factor that impacts the recovery of voluntary activity post-exercise (Davis et al., 2007). It is likely that oxidative stress would impact the recovery and post-exercise activity in sled dogs; however, more research is warranted to determine the relationship between oxidative stress and behaviour in dogs.

Overtraining is a general term used when athletes are not appropriately conditioned to endurance exercise or do not recover fully between exercise bouts, resulting in decreased performance and chronic fatigue in humans (reviewed in humans: Purvis et al., 2010). For working dogs, it is the responsibility of the owner to ensure that overtraining does not occur.

This highlights the importance of reliable behavioural indicators of recovery that can be used by working dog owners. Overtraining in humans can lead to increased risk of injury, chronic soreness, lethargy, decreased motivation to exercise and illness (Purvis et al., 2010). These symptoms of overtraining also likely occur in canine athletes (Zink et al., 2013b). In humans, the most reliable sign of overtraining is measured as decreased mood (Hooper et al., 1997; Meeusen et al., 2006). Morgan et al. (1987) summarized data from 400 individuals, and reported that mood disturbances, defined by the Profile of Mood State questionnaire, increased in a dose- respondent manner to the training stimulus, with these mood changes returning to baseline following a reduction in the training load. In dogs, changes in mood or affective state are difficult to measure subjectively (Burman et al., 2011) and may not be a realistic or reliable method for owners to identify overtraining. Since there are no current reliable markers of overtraining, the diagnosis is difficult. In dogs the symptoms of overtraining, such as decreased motivation or chronic pain, may present themselves as behavioural changes such as an increase in lethargy (a decrease in locomotion). Being aware of the various behavioural changes that occur during the recovery period may enable owners to identify abnormal behaviours that might indicate overtraining.

1.2.3 Future research Many of the training techniques used by sled dog owners are based on traditions that have been passed down through generations rather than from science-based evidence

(Templeman et al., 2018a). More research is needed to demonstrate how repetitive endurance exercise affects the behaviour of dogs. Behavioural indicators may serve as a practical tool for working dog owners to assess the effectiveness of the training regimen, ensure the health and well-being of their dogs and minimize potential long-term health issues. Future research should identify the behavioural changes that occur over a standard incremental training program in sled dogs. This will be the first step that paves the way for future studies to correlate behavioural indicators to various physiological markers of fatigue or overtraining.

1.3 The effects of tryptophan on dog behaviour Endurance exercise has the potential to impact the behaviour and well-being of sled dogs, and diet is also likely to be a contributing factor. Tryptophan (Trp) is an indispensable amino acid (AA) for dogs. After being used for protein synthesis, Trp participates in two major pathways in the body - the kynurenine and serotonergic pathways (Wolf 1974). The primary pathway for Trp is the kynurenine pathway, which accounts for over 90% of ingested Trp, and is involved in many different fundamental biological functions (reviewed in humans: Badawy et al., 2017). However, 5% of Trp is used as the precursor for the neurotransmitter serotonin (5-

HT), via the serotonergic pathway (Tyce, 1990). While this pathway only accounts for a minor proportion of Trp intake, 5-HT is an influential neurotransmitter that is used for a wide variety of physiological functions.

1.3.1 Serotonin influence on behaviour and mood

In humans, 5-HT is known to influence cardiovascular function, cardiac rhythm. respiration, thermoregulation and appetite, as well as behaviour (Lucki, 1998). While the range of physiological and psychological effects of 5-HT have been well documented in humans, there has been less focus on how it influences dog behaviour. Studies in dogs use peripheral measures 7

of 5-HT, such as plasma and platelet 5-HT concentrations, to indicate central 5-HT functioning, as there is a strong positive relationship between these measurements (Yan et al., 1993). One behaviour documented to be influenced by serotonin in dogs is aggression. Reiser et al. (1996) first reported that concentrations of cerebral spinal fluid 5-hydroxyindolacetic acid (CSF 5-

HIAA), a metabolite of serotonin, are lower in aggressive dogs compared to non-aggressive dogs. Additionally, serum concentrations of 5-HT are lower in aggressive dogs compared to non- aggressive dogs (Cakiroğlu et al., 2007; Rosado et al., 2010; León et al., 2012). Combined, these results indicate that a decreased level of 5-HT is associated with increased aggressive behaviours in dogs. Serotonin has also been reported to be associated with fearfulness and anxiety in dogs.

In shelter dogs, there is a negative relationship between serum 5-HT and fearfulness (Alberghina et al., 2017). However, anxious dogs have higher serum 5-HT levels than control dogs (Riva et al., 2008). While more research is warranted to confirm the specific effects of 5-HT in dogs, it is evident that this neurotransmitter is involved in the regulation of various behaviours. In working dogs, behaviours like aggression or negative affective states like fearfulness and anxiety should be minimized to ensure that dogs are able to be handled/trained effectively and safely. Central 5-

HT concentrations can be manipulated through alterations in dietary Trp concentrations, potentially minimizing behavioural problems that may arise when dogs experience these states.

1.3.2 Synthesis of serotonin

The synthesis of serotonin from Trp occurs via a short pathway. While 5-HT is also synthesized in the periphery where it acts as a hormone, the neurotransmitter serotonin is synthesized in the brain. In order for this to occur, Trp first crosses the blood brain barrier (BBB) via a common transport protein (Padridge, 1983). Tryptophan is present in the blood both as free

Trp and bound to albumin. It was originally suggested that only free Trp can cross the BBB, but

the amount of free Trp does not determine the rate of uptake into the brain (Pardridge and Fierer,

1990). Once tryptophan has crossed the BBB, it is converted to 5-hydroxytryptophan by tryptophan hydroxylase (TPH). Almost instantaneously, 5-hydroxytryptohan is decarboxylated to form 5-HT (Leathwood, 1987). Serotonin is stored in the synaptic cleft, and when released can bind to various receptor subtypes. Due to the large number of different receptors, 5-HT has a wide variety of functions (Darmon et al., 2015). The rate limiting step for this reaction is the hydroxylation of Trp by TPH (Leathwood, 1987). Since TPH is not fully saturated under normal conditions, an increase in Trp concentration in the brain will increase the conversion of Trp to 5-

HT.

The amount of Trp that is transported across the BBB is largely dependent on the composition of the ingested diet. Primarily, Trp competes with large neutral amino acids

(LNAA; valine, leucine, isoleucine, tyrosine, phenylalanine, methionine) for binding to the BBB transporter (Pardridge, 1998). Therefore, the amount of Trp entering the brain depends on the ratio of Trp to LNAA, where a low Trp: LNAA leads to less Trp transport to the brain and vice- versa. However, Trp is typically present in small amounts compared to the LNAA in most protein sources (Fernstrom, 1990). It has been reported that increasing the dietary Trp: LNAA ratio causes an increase in brain Trp in rats (Fernstrom et al., 1973; Wurtman and Fernstrom,

1974; Sarwar and Botting, 1999). Additionally, dietary carbohydrate content impacts the transport of Trp to the brain. The rise in glucose following a carbohydrate-rich meal triggers insulin secretion, which in turn facilitates the uptake of LNAA, but not Trp, into skeletal muscle

(Lotspeich and Shelton, 1949; Fernstrom and Wurtman, 1971). This causes an increase in the

Trp: LNAA ratio in the blood, favouring the transport of Trp across the BBB (Fernstrom and

Wurtman, 1971; Markus et al., 2008). Dietary changes in tryptophan content and the Trp:LNAA 9

ratio have been used as a method to alter serotonin synthesis in various monogastrics, including dogs.

1.3.3 Tryptophan supplementation in dogs

In dogs, Trp supplementation has been studied as a way to influence behaviour.

Behavioural issues have been identified as a primary reason that working dogs are unsuccessful at their roles (Evans et al., 2007; Arnott et al., 2014). Research with various working dogs have identified anxiety, fear (guide dogs: Caron-Lormier et al., 2016) and aggression (military dogs:

Haverbeke et al., 2009) as undesirable in working dogs. Additionally, fear and anxiety are aversive states (Grandin and Deesing, 2002) that may interfere with the ability of dogs to engage in and learn their tasks (Blackwell et al., 2010). Inter-dog and human-directed agonistic behaviours that occur as a result of experiencing these states may interfere with training, human handling and performance of sled dogs. Agonistic interactions include behaviours related to aggression, submission, threat or retreat, which are generally considered a normal part of social interactions in dogs (Miklósi et al., 2015). However, some of these agonistic behaviours in working dogs may pose safety concerns for both the handler and other dogs, and lead to pain or injury. Changes in the diet, such as increased Trp content, may be a means to minimize these behaviours and states in dogs.

Various researchers have looked at Trp effects on behaviour in dogs. DeNapoli et al.

(2000) examined the effects of Trp supplementation in both high protein and low protein diets, using dogs previously diagnosed with behavioural problems. Dogs fed a high protein diet with supplemental tryptophan, to achieve a Trp: LNAA ratio of 0.06:1, exhibited less dominance aggression, compared to dogs fed a control diet (Trp: LNAA ratio of 0.04:1) (DeNapoli et al.,

2000). Additionally, Trp supplementation in a low protein diet, to achieve a Trp: LNAA ratio of

0.07:1, reduced territoriality scores compared to a control diet (DeNapoli et al., 2000). Seven weeks of consuming a diet containing a Trp: LNAA ratio of 0.048:1 decreased stranger-directed aggression, fear and touch sensitivity, but not owner-directed aggression, in dogs previously diagnosed with anxiety (Kato et al., 2010). However, this diet also contained casozeprine, a bioactive peptide that has potential anxiolytic effects, which could have been a contributing factor in the behavioural changes observed (Kato et al., 2010).

However, opposing results have been reported. In client-owned dogs with no behavioural diagnoses, Trp supplementation had no effect on anxiety-like behaviours (Bosch et al., 2009).

Additionally, there was no effect of various dietary concentrations of tryptophan on multiple behavioural parameters, such as confidence and posture, in kennel dogs with no behavioural diagnoses (Templeman et al., 2018b). It is possible that dietary Trp supplementation only affects dogs with previously diagnosed behavioural problems. Potentially, dogs with behavioural issues have insufficient serotonin production, and supplementation with Trp increases serotonin and normalizes behaviour. Bosch et al. (2009) and Templeman et al. (2018b), both studied dogs that did not have previous behavioural diagnoses, like anxiety or aggression. However, when dogs with predetermined diagnoses were used as subjects, Trp had a beneficial effect on their behaviour (DeNapoli et al, 2000; Kato et al., 2012).

The inclusion level of Trp compared to LNAA in diets also impacts behavioural responses. While the NRC recommendations for AA intake for dogs translates into a Trp: LNAA ratio of 0.061:1, diets are formulated to meet individual AA requirements, suggesting they may not meet this Trp: LNAA ratio (NRC, 2006). Only a few of the diets discussed surpasses this

Trp: LNAA ratio. The two Trp supplemented diets used by DeNapoli et al. (2000), both 11

contained a Trp: LNAA ratio of equal to or above 0.061:1, which reduced dominance aggression and territoriality scores compared to the control diet. Additionally, the diet used by Bosch et al.

(2009) contained a Trp: LNAA ratio of 0.085:1. However, this treatment diet did not reduce the anxiety-like behaviours of the dogs used in the study. Again, this could be attributed to the fact that that not all dogs used by Bosch et al., (2009) exhibited anxiety-related behavioural diagnoses. The behavioural impacts of dietary Trp supplementation likely depends on both the level of supplementation and the cohort of dogs that are being studied. These factors should be considered when developing future studies investigating Trp supplementation and the effects on dog behaviour.

1.3.4 Combined influence of tryptophan and exercise on behaviour

Both endurance exercise and tryptophan individually have been shown to influence dog behaviour. Additionally, 5-HT has been implicated to contribute specifically to the onset of central fatigue during exercise. Endurance exercise results in an increase in serum free fatty acids, which compete with Trp for binding to albumin and therefore increases the free serum Trp pool. This suggests that endurance exercise should increase Trp transport into the brain and the subsequent 5-HT production (Bloomstrand, 2011). However, there are conflicting results as to whether the bound: free ratio of Trp actually impacts the amount of Trp that is transported into the brain, so this mechanism is often disputed (Pardridge, 1998). Furthermore, endurance exercise leads to increased LNAA being taken up into the skeletal muscle for energy production, which increases the Trp: LNAA ratio, allowing for an increase in Trp transport across the BBB

(Davis et al., 2000). The central fatigue theory states the increase in serotonin production via these two mechanisms during endurance exercise generates feelings of lethargy, drowsiness and a lack of motivation to continue performing physical activity (Newsholme and Blomstrand,

1995). In rats, administration of Trp through intraperitoneal injection reduces the time to fatigue when undergoing moderate intensity treadmill exercise (Soares et al., 2003; Soares et al., 2007;

Cordeiro et al., 2014). Furthermore, an increase in 5-HT during prolonged exercise results in a decrease in performance capacity in human athletes (Blomstrand, 2011; Newsholme &

Blomstrand, 2006). It is possible that an increase in 5-HT production in dogs may also lead to fatigue and reduced motivation to exercise.

However, opposing results, which suggest Trp does not contribute to fatigue during exercise, have also been reported. Ingestion of 150 mg of L-Trp improved performance during endurance treadmill exercise (Segura and Ventura, 1988) and 60 minutes of cycling (Javierre et al., 2010) in human athletes. Fernstrom and Fernstrom (2006), additionally stated that the central fatigue hypothesis is unsupported as there is a lack of evidence that shows the mechanism behind an increase in brain uptake of tryptophan during exercise. While there are conflicting results surrounding the effects of Trp and increased serotonin on central fatigue in humans, there has been no research in dogs. Although Trp may elicit beneficially effects on behaviour, such as a reduction in anxiety and aggression, there is a possibility that the increase in 5-HT could contribute to central fatigue and lead to reduced performance, premature fatigue and decreased motivation to exercise. Research is warranted to examine the impact of Trp on central fatigue in sled dogs, to determine if Trp can be used to improve behaviour without affecting performance or physical activity.

1.3.5 Future research Overall, the effects of tryptophan on behaviour in dogs is a relatively new and limited topic of research. Evidence suggests that increases in central 5-HT are related to improvements in behaviour, such as decreased anxiety and aggression. However, more research is needed to 13

determine the behavioural effects in working dogs, with a focus on increasing the Trp: LNAA ratio. Addressing certain behavioural problems in sled dogs using this particular dietary intervention could potentially improve training and workability. Additionally, future research should focus on the interaction between tryptophan and exercise in dogs, to determine if an increase in 5-HT production leads to the onset of fatigue or a decrease in motivation to exercise.

1.4 The effects of soluble fiber on dog behaviour

Another dietary component that may influence the behaviour of sled dogs is dietary fiber.

However, a survey showed that only 39% of sled dog owners consider fiber an important nutrient

(Templeman et al., 2018a). Dietary fiber can be divided into two categories based on its solubility in water. Soluble fibers are typically highly fermentable, and include beta glucans, pectins, natural gums, and oligosaccharides. Prebiotics, which include various soluble fibers, are defined as “a selectively fermented ingredient that allows specific changes, both in the composition and/or activity in the gastrointestinal (GI) microflora, that confer benefits” (Gibson et al., 2004). Common prebiotics include disaccharides, oligo- or polysaccharides (fructooligosaccharides (FOS), mannanoligosaccharides (MOS)) or inulin. Short chain fatty acids

(SCFAs), primarily acetate, propionate and butyrate, are the end products of bacterial fermentation of saccharides and are involved in various biological processes (Swanson et al.,

2002a). In contrast, insoluble fibers have partial or low fermentability, and include cellulose, hemicellulose, lignans and waxes. Insoluble fibers convey various health benefits to dogs, such as decreasing gastric time and diluting caloric density, and are often used in weight loss diets (de

Godoy et al., 2013). However, soluble fibers have beneficial effects on the gut microbiome and the inclusion of increased soluble fibers in the diet of dogs has been suggested to influence behaviour via the gut-brain axis. 14

1.4.1 Gut-brain axis There is rapidly emerging evidence surrounding the connection between the gut microbiome and the central nervous system (CNS). In humans, the gut microbiome has been implicated to play a role in various disorders such as autism spectrum disorders (Mayer et al.,

2014), depression and anxiety (Park et al., 2013; Foster and McVey, 2013) and chronic pain

(Amaral et al., 2008; Bercik et al., 2012). The complex interactions between the microbes and their metabolites in the mammalian GI tract and the brain are still being explored. The gut microbiota may interact with the brain both through the enteric nervous system (ENS) and directly with the CNS through various neuroendocrine and metabolic pathways (Bercik et al.,

2011; Carabotti et al., 2015).

Various molecules have been implicated as key communicators between the GI tract and the brain, primarily using laboratory rodent models. SCFAs act as G-protein coupled receptors and can interact with the CNS and ENS (Cherbut et al., 1998; Soret et al., 2010; Kimura et al.,

2011). Injection of butyrate into the cerebrum of rats decreases depressive-like behaviours

(Schroeder et al., 2007); however, research is needed to confirm whether SCFA produced in the gut can cross the BBB and influence behaviour. Brain-derived neurotrophic factor (BDNF) has also been suggested to be involved in the gut-brain axis. Germ free (GF) mice exhibit a significantly lower hippocampal BDNF expression, accompanied by an elevated stress response

(Sudo et al., 2004) and decreased anxiety-like behaviours (Heijtz et al., 2011) in contrast to normal mice. Furthermore, γ-Aminobutyric acid (GABA), the primary inhibitory neurotransmitter in the CNS, is located throughout the GI tract (Hyland and Cryan, 2010). GF mice exhibit decreased levels of GABA within the colon, suggesting that specific gut microbiota can synthesize GABA (Matsumoto et al., 2013). GABA deficiencies are linked to anxiety and

depression in humans (reviewed in: Cryan and Kaupmann, 2005). Finally, bacterial metabolites, including SCFA’s, signal the GI production of serotonin in enterochromaffin cells (Yano et al.,

2015). The behavioural impacts of serotonin have been discussed previously; however, more research is warranted in dogs to determine if peripheral serotonin has behavioural effects similar to that of central serotonin.

Studies have also reported connections between specific bacteria in the gut and behaviour. Specifically, Lactobacillus spp. and Bifidobacterium spp., members of the Firmicute and Actinobacteria phyla, respectively, have been implicated in the regulation of mood and behaviour. Lactobacillus has been reported to influence GABA mRNA in specific brain regions

(Bravo et al., 2011). Mice treated with Lactobacillus rhamnosus displayed less anxiety-like and depressive-like behaviours than control fed mice (Bravo et al., 2011). Bifidobacterium longum normalized anxiety-like behaviours and BDNF expression in mice that exhibited chronic inflammation in the gut (Bercik et al., 2011). The microbial communication with the brain likely involves the vagus nerve, which transmits information from the luminal environment to the CNS, as behavioural effects are not present in vagotomised mice (Bravo et al., 2011; Bercik et al.,

2011). While there is a growing base of evidence surrounding the connection between the gut microbiome and the CNS in humans and mice, there is a dearth of research that focuses on dogs.

1.4.2 The canine gut microbiome

The classification of the gut microbiome in healthy dogs is an area of ongoing research.

However, varying microbial abundances have been reported, due to different dog characteristics such as breed, age, diet and environment, as well as laboratory methodologies (Middelbos et al.,

2010; Omatsu et al., 2018). Additionally, bacteria are present in different proportions along the

GI tract, with bacterial diversity increasing from the duodenum to the colon, where the majority 16

of fiber fermentation occurs (Suchodolski et al., 2008). Firmicutes (23-40%), Bacteroidetes (31-

38%), Proteobacteria (5-15%), Fusobacteria (7-40%) and Actinobacteria (0.8%- 1.4%) are the most predominant phyla in the colon of healthy dogs (Suchodolski et al., 2008; Middelbos et al.,

2010; Omatsu et al., 2018).

Two studies have attempted to characterize the gut microbiome in dogs who exhibit behavioural disorders. In 2019, Kirchoff et al. analyzed fecal samples from 31 pit-bull type shelter dogs, which included dogs who either displayed conspecific aggression or not. 16S rRNA gene sequencing was used to detect differences in fecal microbiome concentrations between the dogs. Proteobacteria and Fusobacteria were in higher abundance in non-aggressive dogs, while

Firmicutes were higher in aggressive dogs. Specifically, the genus Lactobacillus was more abundant in aggressive dogs, while Fusobacteria was more abundant in non-aggressive dogs

(Kirchoff et al., 2019). In 2020, Mondo et al. similarly characterized the dog fecal microbiome using aggressive, phobic and normal mixed breed dogs. Aggressive dogs exhibited higher biodiversity compared to the normal and phobic dogs, with specific increases in Catenibatrium and Megamonas, which belong to the Erysipelotrichaceae and Veillonellacease families, respectively. Additionally, phobic dogs had an increased abundance of Lactobacillus than normal dogs (Mondo et al., 2020). The results of these studies are somewhat contradictory to previous studies in mice and humans, where Lactobacillus was associated with decreased anxiety-like and depressive-like behaviours (Bravo et al., 2011; Messaoudi et al., 2011). More research is warranted to do widespread analysis of the canine microbiome in dogs with behavioural disorders; however, evidence suggests that increases in certain microbiota produce beneficial effects on behaviour in dogs.

1.4.3 Fiber impacts on canine gut microbiome

It is evident that connections exist between the microbial abundance in the gut and behaviour. While more research still needs to be done to clarify relationships between specific bacteria and behaviour in dogs, it is possible that overall improvements in gut health could influence behaviours such as aggression and anxiety. One way to positively shift the gut microbial abundance is through dietary interventions, such as higher inclusion of fermentable soluble fibers.

Many studies have examined the benefits of FOS and MOS which are commercially available fermentable soluble fibers. In dogs, FOS supplementation has been reported to reduce

C. perfringens (Swanson et al., 2002b), increase bifidobacterium fecal concentrations (Swanson et al., 2002b; Pinna et al., 2018) and lactobacillus fecal concentrations (Swanson et al., 2002b).

FOS supplementation also increased fecal butyrate and lactate concentrations (Swanson et al.,

2002b). MOS supplementation increases the fecal concentration of Lactobacillus spp. compared to un-supplemented dogs (Swanson et al., 2002a) and decreased C. perfringes compared to dogs fed FOS (Strickling et al., 2000). Yeast cell wall, which is high in MOS, increased

Bifidobacterium compared to control dogs when fed a raw meat diet (Beloshapka et al., 2013).

Additionally, dogs that were fed diets with inulin had a in greater abundance of lactobacillus compared to dogs fed yeast cell wall (Beloshapka et al., 2013).

The effects of specific ingredients on the gut microbial abundance have also been reported. A diet containing beet pulp, which increased the total dietary fiber content, increased

Firmicutes and Eubactrium halli, a butyrate producer, compared to a control diet, suggesting the diet increased hind-gut fermentation (Middelbos et al., 2010). Potato fiber, which contains 32% insoluble fiber and 23% soluble fiber (as a percent of total dietary fiber), increased Firmicutes 18

and decreased Fusobacteria, and increased fecal SCFA concentrations (Panasevich et al., 2014).

It is likely that at least a 0.5-1% increase in soluble fibers in the diet is required to cause significant increases in the fecal microbiome of species such as Lactobacillus (Swanson et al.,

2002b).

However, varying results have been reported. One study found that MOS and FOS did not alter the fecal concentrations of bifidobacteria in dogs (Swanson et al., 2002a). Furthermore,

Kerr et al. (2013) found no significant differences in the microbial abundance between dogs fed a control diet or a diet containing 25% navy beans, which are a source of protein and fiber. A prebiotic and increased soluble fiber blend also caused no significant differences in microbial abundance compared to dogs fed a control diet; however, the diet did increase total fecal SCFA concentration, suggesting an increase in fermentation (Nogueira et al., 2019).

The large variation in outcomes suggests that further investigation is needed to examine how specific ingredients influence specific gut microbial abundances. The majority of research in this area uses fecal samples to estimate GI microbiota content. It is possible that this fecal sampling method does not accurately represent the true microbial abundances, as fiber is rapidly fermented by colonic bacteria, which may influence the microbial abundances in the proximal colon without affecting the fecal concentrations (Swanson et al., 2002a; Noguiera et al., 2019).

More research in this area will allow for the inclusion of specific ingredients in the diet that have targeted beneficial effects on the gut microbiome and behaviour; however, it is commonly accepted that increases in soluble fiber produces beneficial shifts in the gut microbiota populations.

While there is a growing body of research examining how soluble fiber influences the gut microbiota, and how specific bacterial species and their metabolites impact behaviour, there is limited research that bridges the gap between these two areas in dogs. Bosch et al. (2009a) compared a diet containing highly fermentable fibers with a low fermentable diet and found no differences between any behavioural measures in dogs, including measures of anxiety (such as oral behaviours and paw lifting), restlessness and vocalizations, in an open field test. However, dogs fed the highly fermentable diet rested more during the night and before feeding (Bosch et al., 2009a). In humans with irritable bowel syndrome, supplementation with 5 g/day of FOS for 4 weeks, increased fecal bifidobacterial, which has been linked to a decrease in visceral pain, and decreased anxiety scores compared to a placebo group (Azpiroz et al., 2016). Future research should aim to further investigate how soluble fermentable fibers influence behaviours in dogs and should aim to correlate changes in the gut microbiome with changes in behaviour.

1.4.4 Combined influence of fiber and exercise on behaviour

Endurance exercise can produce shifts in the gut microbiota abundance in sled dogs

(Gagne et al., 2013; Tysnes et al., 2020). Additionally, sled dogs are at a high risk of developing

GI issues, such as inflammatory gastric lesions (Davis et al., 2003a; Davis et al., 2003b; Ritchey et al., 2011), GI barrier dysfunction (Davis et al., 2005; Royer et al., 2005), and diarrhea

(McKenzie et al., 2010). Exercise-induced oxidative stress may be one mechanism explaining the high prevalence of GI diseases in exercising sled dogs, since it can lead to inflammatory damage and cell apoptosis (Darmon et al., 1993); however, the exact mechanism behind exercise-induced GI disorder is unknown. Additionally, GI dysfunctions are often related to increased pro-inflammatory cytokines, which have been noted to induce ‘sickness behaviour’ in humans, characterized by depressive-like symptoms such as decreased motor activity, reduced

exercise tolerance, and lack of interest in the environment (Dunn 2006; Dantzer et al., 2008).

Furthermore, the level of gut dysbiosis in sled dogs prior to a race is related to exercise performance; specifically, teams with a lower overall degree of gut dysbiosis place higher in competitive races (Tysnes et al., 2020). Soluble fiber inclusion in the diets may reduce these exercise-induced GI issues and influence sled dog behaviour.

Certain gut microbes and their metabolites play a key role in controlling the inflammatory response and oxidative stress in athletes. SCFAs produced by soluble fiber fermentation can reduce colonic pH, which improves intestinal mobility, gut permeability, epithelial cell proliferation, and prevents mucosal degradation (Canani et al., 2011; Wang et al.,

20120). Specifically, butyrate exhibits anti-inflammatory effects (reviewed in humans: Morrison et al., 2016). Futhermore, administration of the probiotic Bifidobacterium infantis reduced markers of acute inflammation in rats (Desbonnet et al., 2008), and Bifidobacterium and

Lactobacillus spp., improved gut barrier function and reduced acute inflammation in actively training men (Lamprecht et al., 2012). Furthermore, Lactobacillus spp. increased antioxidant activity following 4 weeks of endurance exercise training in humans, thus improving physiological defenses against exercise-induced oxidative stress (Martarelli et al., 2011). In actively-training sled dogs, a symbiotic, which included probiotic bacteria and prebiotics such as

FOS and MOS, reduced the prevalence of diarrhea and increased the abundance of Lactobacillus and Bifidobacteria after 2 weeks of treatment; however, these alterations in the gut microbiome were not sustained after 6 weeks of continued treatment (Gagne et al., 2013). Overall, these results suggest that increases in specific bacteria in the gut, which can be supported by the dietary inclusion of soluble fermentable fibers, could reduce GI issues that are commonly seen in

sled dogs. The reduction of these GI disorders could reduce sickness behaviours, which could be represented as an increase in physical activity and continued motivation to exercise in sled dogs.

1.5 Overall conclusions The purpose of this literature review was to outline previous knowledge on the effects of both exercise and dietary interventions on the behaviour of dogs. While the physiological impacts of repetitive endurance exercise have been examined for actively training sled dogs, there is no current knowledge on how these training regimens affect behaviour. Characterizing the behavioural changes that occur due to exercise could serve as useful tool for dog owners and trainers and assist in developing appropriate training regimens that ensure the health and well- being of their dogs. Voluntary wheel running has been examined as a potential marker of recovery from exercise in mice; however, a similar technique has not been investigated in dogs.

Additionally, both tryptophan and dietary soluble fibers have the potential to modulate the behaviour of dogs, such as reducing aggression and anxiety-like behaviours. While tryptophan has been suggested to be involved in central fatigue during exercise in humans, the effect of tryptophan on performance has not been investigated in dogs. Additionally, dietary soluble fiber may be particularly beneficially for actively training sled dogs by reducing GI issues and increasing physical activity and motivation to exercise. However, the impacts of repetitive endurance exercise, tryptophan, and soluble fiber supplementation on the behaviour and physical activity of actively-training sled dogs has not been previously investigated.

1.6 Thesis Objectives and Hypotheses The research objectives of this thesis are to examine the effects of (1) repetitive endurance exercise training, (2) dietary tryptophan supplementation, and (3) optimized dietary soluble fiber inclusion, on the pre- and post- exercise behaviours and voluntary physical activity 22

of sled dogs. It was hypothesized that (1) voluntary physical activity and pre- and post-exercise locomotive behaviours would decrease throughout a training regimen, (2) tryptophan supplementation would decrease agonistic behaviours and locomotive behaviours, (3) soluble fiber supplementation would decrease agonistic behaviours and (4) soluble fiber supplementation would increase voluntary physical activity and pre-exercise locomotive behaviors due to alleviation of GI issues.

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2. Chapter 2: Investigating the effects of incremental conditioning and supplemental dietary tryptophan on the voluntary activity and behaviour of mid-distance training sled dogs1 1Submitted and formatted for publication in PLOS One 2.1 Abstract Serotonin is a neurotransmitter synthesized by the amino acid tryptophan, that has the potential to impact the behaviour and activity of dogs. The objective of this study was to assess the effects of supplemental tryptophan and a 12-week incremental training regimen on the voluntary activity and behaviour of client-owned Siberian Huskies. Sixteen dogs were blocked for age, BW and sex and then randomly allocated to either the control or treatment group. Both groups were fed the same dry extruded diet; however, the treatment group were supplemented with tryptophan to achieve a tryptophan: large neutral amino acid ratio of 0.075:1. Once a week, a 5- minute video recording was taken immediately pre- and post- exercise to evaluate dogs’ behaviours. Activity monitors were used to record voluntary activity on both training and rest days.

Linear regression analysis was used to assess the relationship between training week and time spent performing each behaviour. Additionally, a repeated measure mixed model was used to test differences between diet groups and training week for both behavioural and activity count data.

The time spent performing agonistic behaviours prior to exercise was negatively associated with week for treatment dogs (β = -0.32, 95% CI [-0.55, -0.10], P < 0.05) and no change was observed for control dogs (β = -0.13, 95% CI [-0.41, 0.15], P > 0.10). Treatment did not have any effect on activity levels (P > 0.10). For all dogs, locomotive behaviours decreased prior to exercise as weeks progressed (P < 0.05), while run day voluntary activity depended on the distance run that day (P <

0.05). These data suggest that sled dogs experience an exercise-induced reduction in voluntary locomotion in response to both single bouts and repetitive bouts of exercise. Additionally,

tryptophan supplementation may decrease agonistic behaviours, without having any effect on voluntary activity.

2.2 Introduction Sled dogs are endurance athletes that perform high levels of repetitive aerobic and resistance exercise. The success of sled dogs depends on multiple factors, including aerobic capacity and physical fitness as well as workability and trainability. While physical fitness is of primary importance, in order to achieve and maintain the level of fitness required to compete at a high level, it is critical to ensure that sled dogs continue to be motivated to exercise throughout their training and racing seasons. However, repetitive training programs can induce oxidative stress and muscle damage in working dogs (Hincliff et al., 2000; Pasquini et al., 2010), which can result in muscle fatigue and soreness (Ji and Leichtweis, 1997). While researchers have examined the physiological effects of exercise and anticipation of exercise in sled dogs (Angle et al., 2009), more focus is needed on understanding how exercise can impact behaviour in both the short and long term. Exercise-induced muscle fatigue, as well as overtraining, can lead to decreased mood and lack of motivation to exercise in humans (Stone et al., 1991). In canines, these symptoms may manifest as behavioural changes, such as a reduction in locomotive behaviours prior to a bout of exercise, or a generalized decrease in voluntary daily activity. For working dogs, voluntary activity consists of physical activity performed outside of scheduled training or racing bouts. However, there is a dearth of literature that defines how commonly implemented training regimens and repetitive bouts of exercise may impact the behaviour of performance dogs.

Exercise capacity and motivation are not the only important factors to consider when investigating the performance of sled dogs. Sled dogs work in teams of 2 to 18 and typically interact with one or more handlers throughout their lives. Therefore, another key component to a 36

successful sled dog is the ability to work in close proximity with other dogs and humans.

Undesirable behavioural states commonly reported in working dogs include fear and anxiety

(Haverbeke et al., 2009; Rooney et al., 2016). As well, both inter-dog and human-directed aggression can result in a poor team environment and may lead to pain and injury (Rooney et al.,

2016). For sled dogs, inter-dog aggression can present itself as contact or non-contact social conflict, which are forms of agonistic behaviours. Previous research has found that dogs who display aggressive behaviours have lower serum and central serotonin concentrations than non- aggressive dogs (Çakiroǧlu et al., 2007, León et al., 2012).

Serotonin, a neurotransmitter associated with regulation of mood, is synthesized in the brain from the amino acid tryptophan (Trp; Leathwood et al., 1987). Increased serotonin can enhance stress resistance (Koopmans et al., 2005) and reduce the prevalence of undesirable emotional states and behaviours, such as anxiety (Orosco et al., 2004), fear (Rouvinen et al., 1999) and agonistic behaviours (DeNapoli et al., 2000) in numerous monogastric species, including dogs

(DeNapoli et al., 2000). Serotonergic activity is also linked to alterations in general voluntary activity and locomotion (Lasley and Thurmond, 1985; Gainetdinov et al., 1999). Tryptophan has sedative effects in humans (Leathwood and Pollet, 1982) and increasing central serotonin during exercise has been proposed to be associated with feelings of lethargy and a lack of motivation

(Newsholme and Blomstrand, 2006). However, other research has presented conflicting results, with some reports indicating that increased levels of dietary Trp decreases fatigue perception in humans (Segura et al., 1988; Javierre et al., 2010), and has no effect on hyperactivity in client- owned dogs (DeNapoli et al., 2000). Increasing central serotonin concentrations may reduce various locomotory behaviours and activity; however, no previous research has looked at the

effects of Trp-supplementation on the locomotive behaviours or voluntary activity levels in actively-training sled dogs.

Supplementing Trp in canine diets has been previously investigated as a means of increasing the production of serotonin (Bosch et al., 2009; DeNapoli et al., 2000). However, Trp competes with the large neutral amino acids (LNAA) for transport across the blood-brain barrier.

Most protein-containing ingredients have lower concentrations of Trp relative to other amino acids, thus resulting in a reduced Trp:LNAA ratio (Leathwood et al., 1987). Therefore, diet formulation, while still meeting the requirements for Trp, may lead to an imbalance of Trp and

LNAA. Thus, the ratio of Trp:LNAA should be considered when formulating diets to ensure adequate transport of Trp to the brain for serotonin synthesis. The suggested Trp:LNAA ratio is

0.061:1 (NRC, 2006), although the optimal ratio may be greater (Templeman et al., 2018) suggesting that current sporting dog diets may not adequately supply Trp to support serotonin synthesis. Therefore, increasing dietary Trp and the ratio of Trp:LNAA may result in an increase in central serotonin production and a reduction in agonistic or other undesirable behaviours in actively training sled dogs.

The objective of this study was to investigate the effects of 12 weeks of incremental conditioning and supplemental dietary Trp on the voluntary activity and pre and post- exercise gangline behaviours of mid-distance training sled dogs. We hypothesized that dietary supplementation of Trp would decrease the time spent performing various locomotive and agonistic behaviours, pre-and post-exercise, as well as decrease daily voluntary activity, due to an increase in serotonergic activity. We also hypothesized that as exercise intensity and duration increase, the voluntary activity and locomotive behaviours performed would decrease due to exercise-induced physical fatigue. 38

2.3 Materials and methods 2.3.1 Animals, training regimen and diet All procedures and facilities were approved by the Animal Care Committee at the University of

Guelph (AUP #4008). Sixteen client-owned domestic Siberian Huskies (9 female: 4 intact, 5 spayed; 7 males: 2 intact, 5 neutered), with an average age of 4.8 ± 2.5 years and body weight

(BW) of 24.3 ± 4.3kg, were housed, fed and trained at an off-site facility (RaJenn Siberian Huskies,

Ayr, Ontario, Canada). A training regimen was proposed where dogs ran in a standard 16-dog gangline formation four times a week (Mon-Thurs) and distance increased incrementally over a

12-week period. Dogs ran in the same position on the gangline throughout the study. Dogs were anticipated to run 8km during week 0 and reach 86km during week 11; however, due to inclement weather, the training regimen was adjusted (Table 2.1; refer to Templeman et al. (2020) for full proposed and adjusted training regimen). Daily temperature was recorded (Table 1). Total distance travelled over the training period was reduced from ~1900km to ~1230km. When training, dogs pulled an all-terrain vehicle carrying one passenger while maintaining an average speed of approximately 15km per hour throughout the study period. Training began consistently at 08:30 h. When not running, dogs were group housed in free-run outdoor kennels ranging from 3.5 to 80 square meters, containing anywhere from 2 – 10 dogs each. Two dogs were removed from the trial

(one CON dog on week 7 and one TRT dog on week 9) due to exercise-related injuries. All data collected up until their respective points of removal are included in this report.

Table 2.1. Distance (km) run and ambient daily temperature (˚C) when behavioural evaluations were carried out during 12 weeks of incremental conditioning for dogs fed either a treatment diet containing supplemental Trp compared to dogs fed control diet. Ambient temperature Week Distance (km) (°C) 0 8.9 5 1 12.9 7 2 19.7 3 3 26.7 7 4 30.8 3 5 38.4 -2 6 30.2 3 7 30.0 3 8 30.0 1 9 53.2 -5 10 30.2 0 11 38.2 -4

Dogs were blocked for age, gender and BW and then randomly assigned into one of two groups (n = 8 per group): the control group (CON), fed a dry extruded diet (Champion Petfoods

LT., Morinville, AB; refer to Templeman et al. (2020) for full diet formulation) formulated to meet or exceed all AAFCO (2016) nutrient recommendations, or the treatment group (TRT), fed the control diet top-dressed with dietary Trp so as to reach a Trp:LNAA ratio of 0.075:1. Tryptophan solution was prepared by dissolving 10g of crystalline Trp (ADM Animal Nutrition, Woodstock,

ON) per L of deionized water heated to 30˚C. The solution was brought to room temperature (22

˚C) and stored at 4˚C until use. Each diet was stirred for 10 minutes after the addition of Trp solution to equally coat all kibble and ensure homogenous incorporation. Dogs were individually fed once a day at approximately 16:00 h to maintain BW, with individual BW recorded weekly.

Dogs were provided ad libitum access to clean water.

2.3.2 Behavioral evaluation Using a digital camera (Sony HDR-CX110 HD Handycam, Sony Corp., Tokyo, Japan), video recordings were taken on one day (either Day 1 or Day 2) of each week to evaluate changes in the dogs pre- and post-exercise behaviours, where the distances they ran depended on week (Table

2.1). Once all dogs were put into their harnesses and individually placed in their respective positions on the 16-dog gangline, they were recorded for 5 continuous minutes immediately prior to exercise. Upon return from the training bout, 5 minutes of continuous video was again recorded while the dogs remained on the gangline. Dogs had been previously acclimatized to remain on the gangline post-exercise. Immediately upon cessation of the video, dogs were removed from the harness, and returned to their respective pens. Ten out of the 16 dogs (5 CON dogs and 5 TRT dogs) were chosen to be recorded, based on gangline position and visibility, to identify the occurrence of the following behaviours: jumping, lunging, changing posture, chewing on the gangline, sitting, lying, standing, digging, and changing posture (Table 2.2). All behavioural analysis was completed by a single individual who was blind to treatment groups. The overall time spent performing each behaviour (seconds) was determined from the video.

Table 2.2. Description of behavioural parameters analyzed during 5 minutes of video taken immediately pre- and post-exercise for dogs fed either a treatment diet containing supplemental Trp compared to dogs fed control diet. Behaviour Description Sitting Positioned with rear end and two front paws in contact with the ground Lying Positioned with ventral or side body in contact with the ground Standing Upright position with three or four paws in contact with the ground Digging* Using two front paws to dig at the ground Posture Frequent changes in state of motion, repeatedly lifting paws, pacing (>3 s) changes* Jumping* Upward motion where all four paws leave the ground Lunging* Upward and forward motion where front two paws leave the ground Agonistic Behaviours associated with social conflict, including noncontact (baring Behaviour teeth, snapping) and contact (biting, nosing, wrestling) *Behaviours classified as locomotive behaviours 41

2.3.3 Activity monitoring Three-dimensional accelerometers (Fitbarks, Fitbark Inc., Kansas City, MO) were attached to the collars of each dog to record activity on weeks 0, 6, and 11. For each of those weeks, activity was evaluated continuously for 24 hours during a rest day (no training) and again on an active day

(training). Data is expressed as an activity count, which represents physical activity and is generated by company algorithm. Similar to a step count generated by a human activity monitor, the voluntary activity counts described herein represent physical activity and a larger voluntary activity count indicates the dog is more active. While activity was being recorded, any periods of human interference, such as feeding, owner interaction, or training, were noted and subsequently removed from the activity count data. This ultimately left 3 hours of uninterrupted data that represented the voluntary activity performed by the dogs in their kennels, which was used for further analysis. For rest days, 3 consecutive hours of data were used from 11:00 h to 14:00h, while for active days, total activity counts were combined from 1-h pre-run (7:00 h to 8:00 h), 1-h post- run (dependent on run finishing time) and 1-h post-feeding (18:15h to 19:15h). Activity data from

4 CON dogs was removed from the week 1 rest day due to unanticipated owner interaction.

2.3.4 Statistical analysis The time spent performing a behaviour was converted into percentage of time [(duration of behaviour/duration of recording) x 100]. The average length of a bout of agonistic behaviour was also calculated [sum of duration of bouts/number of bouts]. The relationship between training week and the percentage of time performing a behaviour was analyzed using PROC REG of SAS

(v.9.4; SAS Institute Inc., Cary, NC). If both TRT and CON groups had similar significant regression slopes for a particular behaviour, data were pooled and reanalyzed using PROC REG of SAS (v.9.4; SAS Institute Inc., Cary, NC). Behavioural data were also analyzed using PROC 42

GLIMMIX of SAS (v.9.4; SAS Institute Inc., Cary, NC), with dog as a random effect and week and treatment as fixed effects. Week*treatment interaction effects were analyzed but removed if insignificant. Week was additionally treated as a repeated measure. Means were separated using

Fisher’s LSD. Results are reported as least square means (LSM) ± standard error (SE). For all models, residuals were tested for homogeneity and normality by using the Shapiro-Wilk test and plots. PROC CORR of SAS (v.9.4; SAS Institute Inc., Cary, NC) was used to assess the relationship between daily temperature (°C), behaviour and week. Significance was declared at P

≤ 0.05, and trends at 0.05 < P ≤ 0.10.

Activity counts during rest days and training days were analyzed separately but using the same statistical method. Data were analyzed using the PROC GLIMMIX of SAS (v.9.4; SAS

Institute Inc., Cary, NC) with dog as a random effect and week and treatment as fixed effects.

Week was treated as a repeated measure. Week*treatment interaction effects were also analyzed.

Means were separated using the Tukey adjustment. Results are reported as LSM ± SE.

Additionally, PROC REG of SAS (v.9.4; SAS Institute Inc., Cary, NC) was used to evaluate the relationship between distance of exercise bout and run day activity counts. PROC CORR of SAS

(v.9.4; SAS Institute Inc., Cary, NC) was used to assess the relationship between daily temperature

(°C) and activity. For all models, residuals were tested for homogeneity and normality by using the Shapiro-Wilk test and plots. Significance was declared at P ≤ 0.05, and trends at 0.05 < P ≤

0.10.

2.4 Results 2.4.1 Behaviour 2.4.1.1 Pre-exercise gangline behaviour There was a negative association between the duration of a bout of agonistic behaviours and week of training for dogs receiving Trp-supplementation (β = -0.32, 95% CI [-0.55, -0.09], R2 = 0.10, P

= 0.007; Fig 2.1B); however, no association was observed for dogs receiving the control diet (β =

-0.13, 95% CI [-0.41, 0.15], R2 = 0.01, P > 0.10; Fig 2.1A). For all other behaviours, similar regression slopes were found between CON and TRT dogs; therefore, data were pooled to assess the effects of exercise. When the data were pooled, there was a negative association between week of training and time spent lunging and changing posture, and a positive association between week of training and time spent lying down (P < 0.05; Table 2.3). No associations were found between training week and time spent chewing on the line, digging, sitting or standing (P > 0.10; Table

2.3).

A 25

20 y = -0.1315x + 2.1634, p > 0.05

Time (s) Time 10

0 0 1 2 3 4 5 6 7 8 9 10 11

B 25

y = -0.3233x + 3.1326, p < 0.05 15

Time (s) Time 10

0 0 1 2 3 4 5 6 7 8 9 10 11 Week

Figure 2.1. Agonistic behaviour performed by sled dogs undergoing 12 weeks of incremental conditioning. Average bout (sec) of agonistic behaviour performed by control dogs (A) and tryptophan- supplemented dogs (B) during 5-minutes immediately prior to exercise.

Table 2.3. Linear regression estimates for the relationship between week of training and the time spent performing a behaviour for sled dogs undergoing 12 weeks of incremental conditioning. Week Behaviour Β [95% CI] 1 p-value Pre-run2 Chewing -0.01 [-0.03, 0.01] 0.472 Digging -0.02 [-0.14, 0.10] 0.746 Jumping -0.12 [-0.26, 0.01] 0.077 Lunging -0.60 [-1.00, -0.19] 0.005 Posture Changes -2.96 [-4.1, -1.76] <0.001 Lying 2.33 [1.23, 3.43] <0.001 Sitting 0.33 [-0.71, 1.38] 0.529 Standing 1.13 [-0.46, 2.72] 0.162 Post-run3 Lying 2.96 [1.39, 4.53] <0.01 Sitting 0.22 [-0.97, 1.42] 0.71 Standing -3.14 [-4.90, -1.38] <0.01 1Β = Regression coefficient, 95% confidence interval; n = 10 for wks 0 to 2, 4 to 6 and 8 to 11; n = 9 for wk 7; n = 8 for wk 3 2Behaviours observed for 5 minutes immediately pre-exercise 3Behaviours observed for 5 minutes immediately post-exercise

There was no effect of dietary treatment on the overall time spent performing any pre-run behaviour evaluated (P > 0.10; data not shown), therefore data from all dogs were pooled to examine week by week differences in behaviour. The time spent lunging was greater during week

1 than weeks 0, 6, 7, 9, 10 and 11, greater during week 2 than weeks 7, 9 and 11, and greater during weeks 3 and 4 than weeks 7 and 9 (P = 0.025; Table 2.4). Time spent changing posture was greater during weeks 0, 3, 4, 5 and 6 than weeks 9 to 11, and greater during weeks 1 and 2 than weeks 5 to 11 (P < 0.001; Table 2.4). Time spent lying down was greater during week 9 than any other week, and greater during weeks 7 and 11 than weeks 0 to 2 and 4 to 6 (P < 0.001; Table 2.4).

Week tended to have an effect on time spent sitting (P = 0.065; Table 2.4) but had no effect on time spent performing agonistic behaviours, chewing on the gangline, digging, jumping or standing (P > 0.10; Table 2.4). 46

Table 2.4. Average percent of time (%) spent performing observed behaviours during 5-min pre exercise throughout 12 weeks of incremental conditioning. Week (Distance ran) 0 1 2 3 4 5 6 7 8 9 10 11 (8.9 (12.9 (19.7 (26.7 (30.8 (38.4 (30.2 (30 (30 (53.2 (30.2 (38.2 SEM1 p- Behaviour km) km) km) km) km) km) km) km) km) km) km) km) value

Agonistic 0.8 1.6 1.8 2.4 1.0 0.2 0.9 0.5 2.2 0 0 0 1.0 0.542

Chewing 0 0.1 0.1 0 0 0.4 0 0 0 0 0 0 0.1 0.318

Digging 0.1 0.6 0.4 0.7 1.3 0.1 2.3 0 0.2 0 0.8 0 0.8 0.551

Jumping 1 1.7 1.9 1.5 1.7 1.1 1 0 1.8 0 0.5 0.3 0.9 0.194

Lunging 2.5bcd 9a 7.6ab 7.0abc 6.0abc 3.3abcd 2.8bcd 0d 4.5abcd 0d 2.0bcd 1.0cd 2.8 0.025

Postural 32.0ab 44.2a 41.7a 32.7ab 34.7ab 32.5ab 25.2bc 22.4bcd 25.7bc 2.8e 13.7cde 12.3de 7.6 <0.001 Changes

Sitting 22.5 1.7 10.8 6.3 1.7 1.6 5.5 2.5 5.1 20.7 17.2 11.8 6.8 0.065

Standing 39.3 39.6 36.1 44.4 51.1 59.9 63.3 55.0 56.6 29.5 53.1 55.5 10.4 0.134

Lying 1.9c 1.8c 0c 4.2bc 2.4c 0.8c 0c 19.3b 3.8bc 47a 12.7bc 19.0b 6.6 <0.001

1Standard error of the mean; n = 10 for wks 0 to 2, 4 to 6 and 8 to 11; n = 9 for wk 7; n = 8 for wk 3 abcValues in a row with a different superscript are different (P < 0.05)

Environmental temperature was positively correlated with the time spent performing agonistic behaviours (r = 0.22, P = 0.0178), lunging (r = 0.27, P = 0.003) and changing posture (r

= 0.38, P <0.001), and was negatively correlated with the time spent lying down (r = -0.41, P

<0.001). Environmental temperature tended toward a positively correlation with time spent jumping (r = 0.17, P = 0.066), and was not correlated with time spent chewing, digging, sitting or standing (P > 0.10). Environmental temperature was negatively correlated with week (r = -0.75, P

<0.001).

2.4.1.2 Post-exercise gangline behaviour The only behaviours observed post-exercise were sitting, standing or lying. Similar regression slopes were found between CON and TRT dogs for the time spent performing any behaviour and week; therefore, data from all dogs were pooled. There was a positive association between week of training and time spent lying down and a negative association was found between week of training and time spent standing (P < 0.05; Table 2.3). No association was found between week and time spent sitting (P > 0.10; Table 2.3).

There was no effect of dietary treatment on the overall time spent performing any behaviour evaluated (P > 0.10; data not shown), therefore data from all dogs were pooled to examine week by week differences in behaviour. The time spent standing was greater during weeks 0, 1, 2, 4 and

7 than weeks 8 and 11, greater during week 3 than weeks 8 to 11, greater during week 5 than week

8 and 11 and greater during week 6 than weeks 5 and 8 to 11 (P < 0.05; Table 2.5). Time spent lying down was greater during weeks 8 and 11 than weeks 0 - 7 and 9 (P < 0.05; Table 2.5). Week had no effect on time spent sitting (P > 0.10; Table 2.5).

Table 2.5. Average percent of time (%) spent performing observed behaviours during 5-min post exercise throughout 12 weeks of incremental conditioning. Week (distance ran) 0 1 2 3 4 5 6 7 8 9 10 11 (8.9 (12.9 (19.7 (26.7 (30.8 (38.4 (30.2 (30 (30 (53.2 (30.2 (38.2 SEM1 p- Behaviour km) km) km) km) km) km) km) km) km) km) km) km) value

Sitting 11.8 10.8 14.5 10.2 4.1 13.9 6.7 4.1 13.0 20.1 12.8 12.1 8.2 0.83

Standing 75.3abc 74.5abc 70.8abc 88.1ab 70.0abc 64.0bc 91.0a 75.9abc 35.3d 57.8cd 55.4cd 35.9d 11.2 <0.01

Lying 12.9bcd 15.2bcd 14.6bcd 2.4cd 24.9bcd 25.6bc 2.3d 19.8bcd 51.7a 24.5bcd 31.8ab 52.0a 10.0 <0.01

1Standard error of the mean; n = 10 for wks 0 to 2, 4 to 6 and 8 to 11; n = 9 for wk 7; n = 8 for wk 3 abcValues in a row with a different superscript are different (P < 0.05)

Environmental temperature was negatively correlated with time spent lying (r = -0.30, P <

0.05), and positively associated with time spent standing (r = 0.31, P <0.05). Environmental temperature was not correlated with time spent sitting (r = -0.09, P > 0.10).

2.4.2 Voluntary activity Voluntary activity is expressed as a count and the value is generated by company algorithm

(Fitbark Inc., Kansas City, MO). Treatment had no effect on activity counts during rest days or active days throughout the 12-week conditioning period (P > 0.10; Table 2.6). When data from all dogs were pooled, total activity count on rest days (no regimented exercise) decreased from week

0 to week 6 and from week 6 to week 11 (P < 0.05; Fig 2.2A). Total activity counts on run days

(regimented exercise) decreased between week 0 and 6 (P < 0.05); however, run day activity counts on week 11 did not differ from either week 0 or 6 (P > 0.05; Fig 2.2B). Additionally, total activity counts on active days was negatively associated with the distance run that day (β = -14.59, 95%

CI [-22.03, -7.15]; P < 0.05). Daily environmental temperature was positively correlated with off day activity (r = 0.62, P <0.05) and run day activity (r = 0.31, P <0.05).

Table 2.6. Mean voluntary activity counts for control dogs or tryptophan-supplemented (treatment) dogs on active days and rest days during weeks 0, 6 and 11 of a 12-week incremental conditioning period. Week (Distance ran) p-value 0 6 11 (8.9 km) (46.2 km) (38.2 km) SEM1 Week Treatment Week*Treatment Active Day Control 1054.36a 409.08ab 538.34b 165.52 0.03 0.73 0.51 Treatment 849.75a 336.69b 659.58ab 148.11 0.03 Rest Day Control 1358.02a 1076.18a 374.40b 197.63 <0.01 0.78 0.28 Treatment 1539.00a 716.93b 345.43b 230.80 <0.01 1Standard error of the mean; For active days, n = 8 for control and treatment week 0 and 6, n = 7 for control and treatment week 11; for rest days, n = 4 for control week 0, n = 8 for treatment week 0, n = 8 for control and treatment week 6, n= 7 for control and treatment week 11 abcValues in a row with a different superscript are different (P < 0.05)

1800 a 1600 1400 1200 b 1000 800 600 c

Total Activity Counts Activity Total 400 200 0 Week 0 Week 6 Week 11

1200 a 1000

800 ab

600 b

400 Total Activity Counts Activity Total 200

0 Week 0 Week 6 Week 11

Figure 2.2. Average activity counts of sled dogs undergoing 12 weeks of incremental conditioning. (A) Average activity counts of sled during rest day (no regimented exercise). (B) Average activity counts during active days (regimented exercise) where dogs ran 8.9km, 46.2km and 38.2km during weeks 0, 6 and 11, respectively. Columns with different letters are different from each other (P < 0.05). Error bars represent the standard error of the mean.

2.5 Discussion To the authors’ knowledge, this is the first study to evaluate the effects of dietary Trp and an incremental training regimen on the pre- and post-exercise behaviour and voluntary activity of dogs. Dietary Trp may influence behaviours related to anxiety (Orosco et al., 2004), stress

(Koopmans et al., 2005) and fear (Rouvinen et al., 1999) and in the present study, dogs receiving

Trp supplementation experienced a reduction in agonistic behaviours prior to exercise throughout a 12-week period. However, Trp-supplementation did not affect any other observed behaviour, nor did it affect the voluntary activity of dogs during training or rest days. Although previous research has suggested that dietary Trp can have a sedative effect resulting in a decrease in locomotion in humans (Leathwood and Pollet, 1982) and mice (Lasley and Thurmond, 1985), we found no effect in actively training dogs. In agreement with the present work, research by DeNapoli et al. (2000) found that dietary Trp supplementation did not reduce hyperactivity in dogs; which the authors characterized by criteria including excessive pacing, chewing of objects and the inability to remain in a sit position. These behaviours are comparable to the pre-exercise behaviours observed in the current study, which were also unaffected by dietary Trp supplementation. Additionally, Bosch et al. (2009) found no differences in the percentage of time spent changing posture, walking or lying down in an open-field test following 8 weeks of Trp supplementation in client-owned dogs.

Combined, these results suggest that Trp supplementation does not influence activity levels and associated locomotive behaviours in domestic dogs.

2.5.1 Tryptophan effect on aggression-related behaviours Although Trp did not appear to affect overall locomotion in sled dogs, there was a significant effect of the dietary treatment on agonistic behaviours performed throughout the study period. A decrease in aggression following dietary Trp supplementation has been previously

reported in pigs (Li et al., 2006) chickens (Shea et al., 1991), vervet monkeys (Chamberlain et al.,

1987) and rats (Gibbons et al., 1981). As well, dogs previously diagnosed with aggression that were being fed a high protein diet supplemented with additional Trp to reach a Trp:LNAA of

0.07:1 showed reduced aggressive behaviour (DeNapoli et al., 2000). In the present study, no preliminary evaluations were performed to identify any potential behavioural pre-dispositions; however, Trp-supplementation still decreased the time spent performing agonistic behaviours prior to exercise over the 12-week period. The Trp:LNAA ratio of 0.075:1 in the treatment diet resulted in increased serum Trp concentration in the treatment dogs compared to the control dogs

(Templeman et al., 2020), which favors the conditions for higher transport of Trp across the blood- brain barrier. Theoretically, this suggests that more Trp will be converted to serotonin in the brain which is thought to be involved in the regulation of aggressive behaviour, likely through the enhancement of impulse control (Coccaro et al., 1989). Male rhesus macaques with low levels of cerebrospinal fluid 5-hydroxyindoleacetic acid (CSF 5-HIAA), which is the primary metabolite of serotonin, were found to be more likely to show aggressive behaviours as well as experience a loss of impulse control characterized by greater risk-taking behaviours (Mehlman et al., 1994). Dogs who demonstrated impulse aggression, identified by biting without warning, also had lower concentrations of CSF 5-HIAA than non-aggressive dogs (Reisner et al., 1996). Through the action of central serotonin, treatment dogs in our study may have experienced improved impulse control causing the slight reduction in agonistic behaviours prior to exercise. While the recommended

Trp:LNAA ratio derived from minimal AA requirements by the NRC is 0.061:1 (NRC, 2006), the ratio needed to influence a behavioural response may be higher. Various inclusion levels of Trp in canine diets leading to Trp:LNAA ratios of 0.0274:1, 0.0403:1, 0.0448:1, and 0.0581:1, all had no impact on aggressive behaviours in response to a familiar or unfamiliar human in mixed-breed

hounds (Templeman et al., 2018b). However, a Trp:LNAA ratio of 0.075:1 used in the present study, and 0.07:1 used by DeNapoli et al., (2000) both caused reductions in agonistic behaviours.

This suggests that diets aimed to reduce agonistic behaviours should be formulated to include a

Trp:LNAA ratio of over 0.07:1 in order to elicit the desired behavioural change. The results of this study further contribute to the existing literature that dietary Trp can influence behaviours related to aggression, with no apparent sedative effects on locomotive activity or behaviour. In the present study, the average level of agonistic behaviour was minimal during any given week (< 5%). Future research should consider incorporating a baseline evaluation of behaviour to ensure adequate inclusion of dogs that are known to exhibit agonistic behaviours.

2.5.2 Effect of single bout and repetitive exercise on behaviour and activity In addition to the effects of dietary treatment on agonistic behaviours, additional findings from this study revealed that a 12-week conditioning period influenced the locomotive behaviours and voluntary activity of sled dogs, regardless of dietary treatment. Endurance exercise causes physiological changes, and recovery from exercise involves restoration of endogenous energy stores and a return to a normal heart rate, respiratory rate, and internal temperature (Gillette et al.,

2011). In addition to the inevitable physiological impact, intense aerobic exercise in human athletes can lead to an increased risk of oxidative stress and the subsequent skeletal muscle damage is associated with soreness, reduced range of motion, and muscle fatigue (Ji and Leichtweis, 1997;

Peternelj and Coombes, 2011). These physiological effects and the extent of recovery depend on the duration and frequency of exercise (Noakes, 1987; Nieman, 2005). In the present study, the amount of voluntary activity performed by the dogs in their free-run kennels during days of active training depended upon the distance run that day, which likely represents a decrease in available metabolic energy due to exercise. During the post-exercise period, dogs are likely resting, in part,

to restore endogenous energy and return to homeostasis. Furthermore, as indicators of oxidative stress and muscle damage are linked to the intensity of aerobic exercise (Skenderi et al., 2006;

Ramos et al., 2013), it is expected that voluntary activity performed by sled dogs would be dependent on the duration of an exercise bout. This suggests that voluntary activity surrounding exercise may be useful as an additional indicator of intensity of a bout of exercise in sled dogs.

While voluntary activity was found to be related to the duration of a single bout of exercise, it is also evident that behaviour and locomotion may be additionally affected by repetitive exercise.

For all dogs, there was an overall decrease in voluntary activity during rest days and a reduction in locomotive behaviours pre-exercise over the 12-week study period. Although no markers of metabolic stress were measured in the present study, previous research has shown that repetitive exercise in sled dogs is associated with increased creatine kinase (CK) concentrations, which is an indirect marker of skeletal muscle damage (Mckenzie et al., 2005). Sled dogs who ran 58-km on each of three consecutive days had a significant increase in serum CK following the first exercise bout, with a further significant increase after the third exercise bout (Hinchcliff et al., 2000).

Although the distances run in the present study did not exceed 53km a day, it is possible that similar muscle fatigue was experienced, which caused the documented reduction in voluntary activity and locomotive behaviours. Taken together, this suggests that while short-term voluntary activity is related to the distance of an exercise bout on a specific day, activity and locomotion can also be affected in the long term by the repetitiveness of a training regimen. Sled dogs are simultaneously experiencing both an acute and chronic response to exercise, which should be considered when designing training regimens to optimize exercise programs. It is important to note that ambient temperature may also affect behaviour. Interestingly, in the present study, sled dogs were less active and exhibited fewer locomotive behaviours as temperatures decreased. Since the 55

average daily temperature decreased as the study progressed, it is possible that these behavioural changes represent the effects of the repetitive training regimen rather than the decrease in temperature.

Along with the physiological impacts of endurance exercise, dogs may have also experienced additional psychological symptoms throughout the conditioning period. Although acute exercise is associated with a positive effect on mood (Menor-Campos et al., 2011), the extreme exertion experienced by sled dogs may have variable effects. In humans, over-training is most often characterized by a decrease in mood, lack of motivation to exercise and chronic fatigue

(Stone et al., 1991; McKenzie, 1999]. Although these symptoms are difficult to evaluate in working canines, it is likely that sled dogs have the potential to experience similar effects of overtraining. Unfortunately, no previous research has defined behavioural signs of motivation to exercise in dogs. It is possible that the prevalence of postural changes or lunging forward on the gangline could be an indicator of anticipation or motivation to exercise when exhibited prior to running. The decrease in these behaviours seen throughout the conditioning period could potentially indicate a decrease in motivation; however, more research is needed to determine how these behaviours might be associated with other indicators of fatigue and well-being. It is also possible that a decrease in these behaviours could suggest that dogs were becoming habituated to the training regimen, and therefore were less responsive as it progressed. Tracking observable behaviours prior to exercise may be useful for mushers or other sporting dog owners as an indication of motivation to exercise.

2.6 Conclusion The findings of the current study suggest that Trp supplementation decreases agonistic behaviours in actively training sled dogs, while having no effect on activity or locomotion. Future research 56

should continue to examine the use of Trp to decrease pre-run agonistic behaviours in working dogs, with a focus on dogs who have been pre-diagnosed with behavioural issues. Additionally, the reduction in activity and locomotive behaviours, such as lunging and changes in posture, following exercise was related to both to the intensity of a bout of exercise as well as to the repetitiveness of the training regimen. Short-term voluntary activity was related to the distance of the bout of exercise performed that day, while repetitive exercise caused a progressive decrease in locomotive behaviours during a pre- and post- exercise period. Future research should focus on assessing correlations between behavioural responses to repetitive exercise and physiological markers of over-training or fatigue. Overall, this research is the first to show the positive impact of an increased Trp:LNAA ratio on agonistic behaviour, which ultimately improves the workability of sled dogs and potentially decreases their risk of pain and injury. These results can be used to inform the development of diets and training programs designed to maximize the performance and success of sled dogs.

2.7 References

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Anaerobic Bouts in Young Healthy Men. International Journal of Neuroscience. 2010 Apr 1;120(5):319–27. Ji LL, Leichtweis S. Exercise and oxidative stress: Sources of free radicals and their impact on antioxidant systems. Age (Omaha). 1997 Apr;20(2):91–106. Koopmans SJ, Ruis M, Dekker R, van Diepen H, Korte M, Mroz Z. Surplus dietary tryptophan reduces plasma cortisol and noradrenaline concentrations and enhances recovery after social stress in pigs. Physiology & Behavior. 2005 Jul 21;85(4):469–78. Lasley SM, Thurmond JB. Interaction of dietary tryptophan and social isolation on territorial aggression, motor activity, and neurochemistry in mice. Psychopharmacology. 1985 Nov;87(3):313–21. Leathwood PD, Pollet P. Diet-induced mood changes in normal populations. J Psychiatr Res. 1982 1983;17(2):147–54. Leathwood PD. Tryptophan Availability and Serotonin Synthesis. Proceedings of the Nutrition Society. 1987 Feb;46(01):143–56. León M, Rosado B, García-Belenguer S, Chacón G, Villegas A, Palacio J. Assessment of serotonin in serum, plasma, and platelets of aggressive dogs. Journal of Veterinary Behavior. 2012 Nov;7(6):348–52. Li YZ, Kerr BJ, Kidd MT, Gonyou HW. Use of supplementary tryptophan to modify the behavior of pigs. Journal of animal science. 2006;84(1):212–20. McKenzie DC. Markers of excessive exercise. Canadian Journal of Applied Physiology. 1999 Feb;24(1):66-. Mckenzie E, Holbrook T, Williamson K, Royer C, Valberg S, Hinchcliff K, et al. Recovery of Muscle Glycogen Concentrations in Sled Dogs during Prolonged Exercise: Medicine & Science in Sports & Exercise. 2005 Aug;37(8):1307–12. Mehlman PT, Higley JD, Faucher I, Lilly AA, Taub DM, Vickers J, et al. Low CSF 5-HIAA concentrations and severe aggression and impaired impulse control in nonhuman primates. The American Journal of Psychiatry. 1994;151(10):1485–91. Menor-Campos DJ, Molleda-Carbonell JM, López-Rodríguez R. Effects of exercise and human contact on animal welfare in a dog shelter. Veterinary Record. 2011 Oct 8;169(15):388– 388. National Research Council. Nutrient Requirements for dogs and cat. 2nd rev. ed. Washington, DC: The National Academies Press; 2006. Newsholme EA, Blomstrand E. Branched-Chain Amino Acids and Central Fatigue. J Nutr. 2006 Jan 1;136(1):274S-276S. Nieman DC, Dumke CL, Henson DA, McAnulty SR, Gross SJ, Lind RH. Muscle damage is linked to cytokine changes following a 160-km race. Brain Behav Immun. 2005 Sep;19(5):398–403.

Noakes TD. Effect of Exercise on Serum Enzyme Activities in Humans. Sports Medicine. 1987 Jul 1;4(4):245–67. Orosco M, Rouch C, Beslot F, Feurte S, Regnault A, Dauge V. Alpha-lactalbumin-enriched diets enhance serotonin release and induce anxiolytic and rewarding effects in the rat. Behavioural Brain Research. 2004 Jan;148(1–2):1–10. Pasquini A, Luchetti E, Cardini G. Evaluation of oxidative stress in hunting dogs during exercise. Res Vet Sci. 2010 Aug 1;89(1):120–3. Peternelj T-T, Coombes JS. Antioxidant Supplementation during Exercise Training: Beneficial or Detrimental? Sports Medicine. 2011 Dec;41(12):1043–69. Ramos D, Martins EG, Viana-Gomes D, Casimiro-Lopes G, Salerno VP. Biomarkers of oxidative stress and tissue damage released by muscle and liver after a single bout of swimming exercise. Appl Physiol Nutr Metab. 2013 Apr 20;38(5):507–11. Reisner IR, Mann JJ, Stanley M, Huang Y, Houpt KA. Comparison of cerebrospinal fluid monoamine metabolite levels in dominant-aggressive and non-aggressive dogs. Brain Research. 1996 Apr;714(1–2):57–64. Rooney NJ, Clark CCA, Casey RA. Minimizing fear and anxiety in working dogs: A review. Journal of Veterinary Behavior. 2016 Nov 16:53–64. Rouvinen K, Archbold S, Laffin S, Harri M. Long-term effects of tryptophan on behavioural response and growing-furring performance in silver fox (Vulpes vulpes). Applied Animal Behaviour Science. 1999 Mar 1;63(1):65–77. Segura R, Ventura JL. Effect of L-tryptophan supplementation on exercise performance. Int J Sports Med. 1988 Oct;9(5):301–5. Shea MM, Douglass LW, Mench JA. The interaction of dominance status and supplemental tryptophan on aggression in Gallus domesticus males. Pharmacology Biochemistry and Behavior. 1991 Mar 1;38(3):587–91. Skenderi KP, Kavouras SA, Anastasiou CA, Yiannakouris N, Matalas A-L. Exertional Rhabdomyolysis during a 246-km Continuous Running Race: Medicine & Science in Sports & Exercise. 2006 Jun;38(6):1054–7. Stone MH, Keith RE, Kearney JT, Fleck SJ, Wilson GD, Triplett NT. Overtraining: A Review of the Signs, Symptoms and Possible Causes. The Journal of Strength & Conditioning Research. 1991 Feb;5(1):35. Templeman J, Mansilla W, Fortener L, Shoveller A. Tryptophan requirements in small, medium, and large breed adult dogs using the indicator amino acid oxidation technique. J Anim Sci. 2018 Dec 7;96(suppl_3):148–148. Templeman, J. R., Thornton, E., Cargo-Froom, C., Squires, E. J., Swanson, K. S., & Shoveller, A. K. Effects of incremental exercise and dietary tryptophan supplementation on the amino acid metabolism, serotonin status, stool quality, fecal metabolites, and body composition of mid-distance training sled dogs. Journal of Animal Science. 2020;98(5).

Templeman JR, Davenport GM, Cant JP, Osborne VR, Shoveller A-K. The effect of graded concentrations of dietary tryptophan on canine behavior in response to the approach of a familiar or unfamiliar individual. Can J Vet Res. 2018 Oct;82(4):294-305.

3. Chapter 3: Investigating the effects of dietary soluble fiber and incremental exercise on the voluntary activity and behaviour of sled dogs

3.1 Abstract In previous research, repetitive endurance training was found to decrease locomotive behaviours prior to exercise, as well as decrease voluntary physical activity during a single rest day; however, voluntary physical activity over multiple consecutive rest days was not examined.

Additionally, inclusion of fermentable soluble fibers in the diet may produce beneficial shifts in gut microbial populations, thus influencing behaviours through the gut-brain axis. The objectives of this study were to determine the effects of increased inclusion of dietary soluble fiber and an incremental conditioning period on the behaviour and voluntary physical activity of actively training Siberian huskies. Fourteen dogs were blocked by age, BW and sex and randomly allocated to two groups. One group was fed a dry extruded diet that contained an insoluble: soluble fiber ratio of 4:1 (CON), and the second group was fed a dry extruded diet that contained an insoluble: soluble fiber ratio of 3:1 (TRT). All dogs underwent 10 weeks of incremental aerobic conditioning where they trained 4 days a week (Mon, Tues, Thurs, Fri). Once a week, 5- minute video recordings were taken immediately pre- and post-exercise to measure time spent sitting, lying, standing, digging, posture changing, jumping, lunging and performing agonistic behaviours. Activity monitors were attached to the dogs’ collars and used to record voluntary activity on two consecutive rest days and one active day during baseline, and weeks 1, 4, 5, and

7. All behavioural and activity count data were analyzed using a repeated measures mixed model to test for differences between dietary treatments and weeks of training using SAS (v.9.4).

Dietary fiber did not affect any behaviour or voluntary activity level (P > 0.05); however, all

dogs experienced a reduction in locomotive behaviours prior to exercise throughout the 10-week conditioning period (P < 0.05). Additionally, dogs were more active during the second consecutive day of rest relative to the first (P < 0.05). These data suggest that increasing dietary soluble fiber did not have any effects on sled dog behaviour and voluntary physical activity level.

Furthermore, the exercise-related reduction in physical activity observed begins to recover within one rest day.

3.2 Introduction Sled dogs regularly perform repetitive bouts of endurance exercise when training for, and throughout, a racing season. Although regular physical activity is generally beneficial, repetitive bouts of strenuous aerobic exercise can have deleterious physiological impacts, such as depleting internal energy stores (Snow et al., 1981), increasing oxidative stress (Hinchliff et al., 2000;

Pasquini et al., 2010) and muscle damage (Ji and Leichtweis, 1997) and promoting gut dysbiosis

(Tysnes et al., 2020). In human athletes, these symptoms may also negatively impact mood and contribute to the onset of fatigue and reduce the motivation to exercise (Stone et al., 1991). It is likely that these physiological symptoms similarly impact sporting dogs and may manifest as behavioural changes. We have previously demonstrated that as sled dogs progress through a repetitive, incremental training period, the locomotive behaviours demonstrated prior to exercise and the voluntary physical activity during rest days decrease (Robinson et al., 2020). Behavioural indications, such as voluntary physical activity, could potentially be used as a practical measure of the recovery from the physiological stress of endurance exercise. In mice, voluntary wheel running following 150 minutes of forced exercise was used as a marker of exercise recovery and returned to pre-exercise measurements in three consecutive rest days (Davis et al., 2007).

However, the changes in voluntary physical activity over consecutive rest days has not been

examined in actively-training sled dogs. Additionally, dietary nutrients such as fiber may play a role in mitigating these adverse exercise-related effects through modulation of the gut microbiota

(Clark and Mach, 2016; Mach and Fuster-Botella, 2017).

Dietary fibers have many different physiological benefits depending on their chemical structure and physical properties and are often categorized based on their solubility in water.

Soluble fibers, unlike insoluble fibers, are usually fermented by colonic bacteria into short chain fatty acids (SCFA). Moreover, increased dietary inclusion of soluble fibers stimulates the growth of commensal bacteria, such as Bifidobacterium and Lactobacillus spp., in the gastrointestinal tract (GIT) (Swanson et al., 2002; Rios-Covian et al., 2017; Nogueira et al., 2019). These bacterial strains have been reported to improve gut barrier function (Lamprecht et al., 2012), reduce acute inflammation (Lamprecht et al., 2012) and protect against oxidative stress (Martelli et al., 2011) in human athletes. The alleviation of these exercise-induced symptoms may reduce fatigue and increase the motivation to exercise (Stone et al., 1991), which could be demonstrated through increased voluntary activity and locomotive behaviours in sled dogs.

Mannooligosaccharides (MOS), inulin-type fructans and beta glucans are examples of selectively fermentable components of soluble fiber that can increase the proliferation of such beneficial microbes (Gibson et al., 2004; Zhao et al., 2018; Velikonja et al., 2019).

Furthermore, there is a growing body of research surrounding the bidirectional communication between the gut microbiota and the central nervous system, referred to as the gut-brain axis (Heijtz et al., 2011; Bravo et al., 2011; Sylvia et al., 2017). The gut microbiota is involved in the regulation of many behaviours, including anxiety-like behaviours (Heijtz et al.,

2011; Bravo et al., 2011) and aggression (Sapkota et al. 2016; Kirchoff et al., 2019). For example, a broad-spectrum antibiotic resulted in gut dysbiosis in Siberian Hamsters which was 64

correlated with a decrease in aggressive behaviours (Sylvia et al., 2017). Additionally, consumption of diets that included either increased soluble or insoluble fibers were negatively correlated to aggression scores in adolescent female humans (Khayyatzadeh et al., 2019). The mechanism behind the effect of modulation of the gut microbiome on aggressive behaviour remains unknown; however, these outcomes are likely related to the connection of the brain and gut through the vagal nerve (Bonaz et al., 2018). Thus, it is possible that the modulation of the gut microbiome through the increased inclusion of soluble fibers may reduce the prevalence of agonistic behaviours in actively training sled dogs.

The objective of this study was to determine the effects of increased dietary soluble fiber and incremental training on the behaviour and voluntary activity of sled dogs. We hypothesized that the higher inclusion of soluble fibers would reduce agonistic behaviours and alleviate the adverse physiological symptoms of exercise, which would be demonstrated through behavioural changes, via action of the gut brain axis. Secondly, we hypothesized that repetitive training would decrease voluntary activity and the time spent performing locomotive behaviours prior to exercise due to an increase in fatigue, and that intermittent consecutive rest days would permit recovery.

3.3 Materials and methods 3.3.1 Animals, training regimen and diet All procedures were approved by the Animal Care Committee at the University of

Guelph (AUP #4008). Fourteen client-owned Siberian Huskies (5 neutered males, 1 intact male;

8 intact females) with an average age of 3.7 ± 2.7 years and body weight (BW) of 21.5 ± 2.8 kg were used. All dogs were housed, fed and trained at an offsite facility previously approved by the

University of Guelph’s Animal Care Committee (Rajenn Siberian Huskies, Ayr, Ontario, 65

Canada). Dogs were exercised in a standard gangline formation four times a week (Mon, Tues,

Thurs and Fri), with the distance run each week increasing incrementally, starting at 3km and reaching 42km over a 10-week period. Dogs ran in the same position on the gangline throughout the study. Distances run were recorded daily and adjustments were made when necessary according to the ambient weather conditions (Table 3.1). When training, dogs pulled an all- terrain vehicle carrying one passenger while maintaining an average speed of approximately 15 km per hour throughout the study period. Exercise bouts began consistently at 08:30h.

Table 3.1 Cumulative distance the dogs ran during each week, and distance run and daily temperatures when behavioural observations took place Cumulative Weekly Distance Temperature Week1 Distance (km) (C) (km) Baseline (-1) 12 3 -3.15

0 23.2 5.8 1

1 44.8 11.2 5.3

2 67.8 17.2 -3.8

3 95.2 23.8 5

4 120.4 30.1 -6

5 101.7 35.8 -2

6 81.5 16.2 4

7 108 36 -2

8 148.4 41.4 0 1During baseline (week -1), all dogs were consuming the same diet. Dogs were switched to their allocated diet, containing an insoluble: soluble ratio of 4:1 (control) or 3:1 (treatment), starting at week 0.

Dogs were blocked by age, gender and BW and randomly assigned into two groups (n =

7). One group (3 intact females; 1 intact male, 3 neutered males) was fed the CON diet and the other (5 intact females, 2 neutered males) was fed the TRT diet. Both dietary treatments were dry extruded foods formulated to meet or exceed all NRC (2006) and AAFCO (2016) nutrient recommendations for adult dogs at maintenance (Champion Petfoods L.T., Morinville, AB;

Table 3.2). The CON diet was formulated to have an insoluble: soluble fiber ratio of 4:1 and the

TRT diet a ratio of 3:1. BioMOS, a MOS derived from a strain of Sacchoromyces cervisiae

yeast, oat soluble fiber, flaxseed meal and chicory root are included as soluble fiber sources in the TRT diet. All dogs were acclimatized to the CON diet for two weeks prior to the beginning of the study and historical feeding data was used to determine initial food intake. Baseline data was collected during week -1, and dogs were fed their assigned diets starting at the beginning of week 0. Dogs were weighed weekly and food intake was adjusted for dogs to maintain baseline

BW. Dogs were fed once a day at approximately 15:00h and were provided ad libitum access to fresh water.

Table 3.2 Nutrient content and ingredient composition of the control and treatment diet on a dry matter basis. Nutrient contents TRT CON1 Metabolizable energy, kcal/kg (calculated)2 4324.9 4074.35

DM3, % 94.15 94.15 CP, % 44.68 45.12 EE, % 24.31 23.17 TDF, % 7.95 5.2 SDF, % 2.05 0.7 IDF, % 5.95 4.4 Ash, % 8.03 8.55 Treatment diet ingredient composition: Pork meal, pea starch, fresh chicken, low ash herring meal, chicken fat, chicken meal, chicken skin meal, fresh pork, fresh pork organ blend4, flaxseed meal, chicken and turkey giblets, oat soluble fiber, spray dried pork liver, pork pal (liquid), hydrolyzed poultry protein, herring oil, pork pal (dry), sodium chloride, dried kelp, choline chloride, chicory root, enticer, alpha tocopherol, bio-MOS, natural antioxidant (liquid), thiamine, pantothenic acid, pyridoxine, potassium chloride, taurine, yucca, sel-plex, zinc proteinate, natural antioxidant (dry), copper proteinate

1Adapted from Templeman et al., (2020); for control diet ingredient composition, refer to Templeman et al., (2020) 2Calculated metabolizable energy based on modified Atwater values. 3DM, dry matter; CP, crude protein; EE, ether extract; TDF, total dietary fiber; SDF, soluble dietary fiber; IDF, insoluble dietary fiber. 4Blend of 51-52% fresh pork meat and 48-49% fresh pork organs (liver, kidney, spleen).

3.3.2 Behavioural evaluation All dogs were recorded while on the gangline for 5 minutes pre- and post-exercise on d 1 of each week of study. The time spent performing agonistic behaviours, chewing on the gangline, digging, jumping, lunging, changing posture, sitting, standing and lying were recorded.

For details regarding the performance of the behavioural evaluations and ethogram used, refer to

Chapter 2.3.2.

3.3.3 Activity monitoring Three-dimensional accelerometers (Fitbarks, Fitbark Inc., Kansas City, MO) were attached to the collars of each dog to record activity during baseline and weeks 1, 4, 5 and 7. For each of those weeks, activity was evaluated continuously for 2 rest days (Saturday and Sunday, no training) and on the first active day of the week (Monday, active training). While activity was being recorded, any periods of human interaction, such as feeding or training, were noted and subsequently removed from the activity count data. For rest days, 10.5 hours of data were used from 06:30 h to 15:00 h and 16:30 h to 18:30 h, for a total of 21 h of rest-day data collected each week. For active days, total activity counts were combined from 2-h post-run (dependent on run finishing time) and 1-h post-feeding (16:30 to 17:3 0h), for a total of 3-h of active day data collected each week.

3.3.4 Statistical analysis Behavioural data and activity counts were analyzed with a repeated measures mixed model using PROC GLIMMIX of SAS (v.9.4; SAS Institute Inc., Cary, NC), with dog as a random effect and week, treatment, and week*treatment as fixed effects. Day (either Saturday or Sunday) was also included as a fixed effect when analyzing rest day activity. Week was additionally treated as a repeated measure. When the fixed effects were significant, means were separated using Fisher’s

LSD and significance was declared at P < 0.05, and trends at 0.05 ≤ P < 0.10. Results are reported as least square means (LSM) ± standard error (SE). For all models, residuals were tested for homogeneity and normality by using the Shapiro-Wilk test and plots. Additionally, a correlation was performed using PROC CORR of SAS to evaluate the relationship between ambient temperature, run distance, cumulative distance run, week, activity counts and pre- and post-run behaviours.

3.4 Results Two control (CON) dogs were removed from the study (at weeks 2 and 4), due to unrelated health issues. All data collected up until their respective points of removal are included in this report.

3.4.1 Pre-run exercise behaviour Baseline data from one TRT dog and one CON dog, as well as week 0 data from one

TRT dog, were removed due to repeated human interactions which disrupted the behaviour of the dogs. Dietary soluble fiber concentration had no effect on any behaviour observed prior to exercise (P > 0.10; data not shown); therefore, data were pooled to examine the effects of exercise on behaviour. Dogs spent more time performing agonistic behaviours at baseline than any other week (P < 0.05; Table 3.3). Dogs spent more time changing posture during week 2 than weeks 0 and 3 to 8 (P < 0.05; Table 3.3). Dogs spent more time standing on the gangline in weeks 3 to 8 than during baseline, and more time during week 6 than baseline to week 4 (P <

0.05, Table 3.3). Dogs tended to spend more time lying down during weeks 4 and 5 than at baseline and weeks 1, 3, 6, and 8 (P = 0.0536; Table 3.3). Week had no effect on the time spent chewing the gangline, jumping, lunging, or sitting prior to exercise (P > 0.10; Table 3.3). The cumulative distance the dogs ran during the week prior to behavioural evaluations was 70

negatively correlated with the time spent performing agonistic behaviours (r = -0.27, P < 0.05), time spent changing posture (r = -0.25, P < 0.05), and was positively correlated with the time spent standing (r = 0.28, P < 0.05) and tended to be positively correlated with time spent lying (r

= 0.16, P = 0.067). There was no correlation between the cumulative distance the dogs ran the week prior and the time spent sitting, lunging, jumping, digging, or chewing on the gangline pre- run (P > 0.10).

Table 3.3. Percent of time (%) spent performing observed behaviours during the 5 min pre-exercise period for all dogs1 undergoing 10 weeks of incremental conditioning. Week Behaviour -1 0 1 2 3 4 5 6 7 8 SEM2 P-value

Agonistic 5.4a 1.58 2.7ab 0.4b 0.8b 0b 0b 0b 1.5b 0b 1.2 0.0139

Chewing 0.6 2.0 0.7 1.3 0.2 0.7 0.8 0 0 0.4 0.6 0.1910

Digging 1.8 0.3 2.3 0.2 0.7 0.5 0.8 0.5 0.4 0.4 1.1 0.3679

Jumping 0.6 0 0.8 0.3 0 0.1 0 0 0.1 0.3 0.3 0.1145

Lunging 4.2 0.9 3.8 2.6 2.3 1 1.6 0.3 1.6 3 1.4 0.2363

Postural 32.4bc 20.1def 49.8a 35.9b 25.9cd 15.5ef 16.4ef 12.1f 21.1cde 21cdef 5.5 <0.0001 Changes

Sitting 5.5 8.4 3 2.3 1.8 6.6 2.4 1.1 0.4 0 2.7 0.3442

Standing 51.5d 65.2bc 36.9e 54.8cd 67.5b 69.9b 72.8b 84.7a 72.9b 71.9b 6.8 <0.0001

Lying 0.8bc 1.6abc 0c 1.2bc 0.2c 4.53a 4.5ab 0.1c 1bc 0.1c 1.4 0.0536

1Data presented were pooled for all dogs, regardless of dietary treatment 2Standard error of the mean; n = 14 for wks 1 and 2; n=13 for wks 0, 3 and 4; n=12 for wks -1 and wks 5 to 8 abcValues in a row with a different superscript are different (P < 0.05)

Ambient temperature was negatively correlated with the time spent lying pre-run (r = -

0.22, P < 0.05), but was not correlated with any other behaviour pre-run (P > 0.10).

3.4.2 Post-run exercise behaviour There was no effect of treatment on any behaviour observed post exercise (P > 0.10; data not shown); therefore, data were pooled to examine the effects of exercise on behaviour. Dogs spent more time lying down in week 8 than any other week except week 1, and more time lying down during weeks 7 than weeks 0 and 3 (P < 0.05; Table 3.4). Dogs spent more time standing during weeks 0 and 3 than any other week (P <0.05; Table 3.4). Week had no effect on time spent sitting post exercise (P > 0.10; Table 3.4). The distance the dogs ran was negatively correlated with the time spent standing (r = -0.29, P < 0.05) and positively correlated with the time spent sitting (r = 0.23, P < 0.05) and lying down (r = 0.18, P < 0.05) post run.

Table 3.4 Percent of time (%) spent performing observed behaviours during the 5-min post-exercise period for all dogs1 undergoing 10 weeks of incremental conditioning Week (Distance ran) -1 0 1 2 3 4 5 6 7 8 (3 (5.8 (11.2 (17.2 (23.8 (30.1 (35.8 (16.2 (36 (41.1 SEM2 p-value Behaviour km) km) km) km) km) km) km) km) km) km)

Sitting 0 3 1.8 2.9 0.8 9.4 4.6 7.2 11.6 11.1 3.9 0.2585

Standing 74.3bc 93.5a 61.6bc 70bc 94.4a 70.3bc 67.5bc 76.1ab 54.9c 35.7d 8.6 <0.0001

Lying 25.9bc 3.4e 37.6ab 27bc 4.4de 20.1bcde 12.9bcd 13.9cde 32.1b 52a 8.3 <0.0001

1Data presented were pooled for all dogs, regardless of dietary treatment 2Standard error of the mean; n = 14 for wks -1 to 2; n=13 for wks 3 and 4; n=12 for wks 5 to 8 abcValues in a row with a different superscript are different (P < 0.05)

Ambient temperature was not correlated with any behaviour post-run (P > 0.10).

3.4.3 Voluntary physical activity Two dogs (one CON and one TRT) were removed from rest day baseline data, and all rest day data from week 1 was not analyzed due to a software malfunction. Treatment had no effect on activity counts during active days or rest days (P > 0.10; data not shown). During rest days, the average activity was less during weeks 4, 5 and 7 compared to baseline (P < 0.0001;

Fig 3.1). Rest day activity was negatively correlated to the cumulative distance the dogs ran the previous week (r = -0.52, P < 0.0001). For all weeks combined, dogs were more active on the second consecutive rest day than on the first rest day (P = 0.0313; Fig 3.2).

7000 a

6000

5000 b b 4000 b

3000

2000 Physical Activity Counts Activity Physical

1000

0 -1 4 5 7 Week1

Figure 3.1. Mean voluntary activity counts during rest days for all dogs (n=12) throughout 10 weeks of incremental conditioning abcColumns with different letters are different (P < 0.05); Error bars represent standard error of the mean 1Distances run were 3 km (week -1), 30.1 km (week 4), 35.8 km (week 5) and 36 km (week 7).

6000 * 5000

4000

3000

2000 Physical Activty Count Activty Physical 1000

0 Rest Day 1 Rest Day 2

Figure 3.2 Mean voluntary physical activity counts on first rest day and second rest day of all dogs undergoing 10 weeks of incremental conditioning * Significantly different (P = 0.03); Error bars represent standard error of the mean

On run days, activity decreased from baseline to week 5, however it increased from week

5 to 7 (P < 0.0001, Fig 3.3). Activity during run days was negatively correlated to distance the dogs ran that day (r = -0.43, P < 0.001) and the cumulative distance run the previous week (r = -

0.51, P < 0.0001). Ambient temperature was not correlated with off day activity (r = 0.07, P >

0.10) or run day activity (r = 0.13, P > 0.10).

800 a ab 700 ab 600 b 500

400

300 c

Physical Activity Count Activity Physical 200

100

0 -1 1 4 5 7 Week1

Figure 3.3 Mean voluntary physical activity counts on run days for all dogs undergoing 10 weeks of incremental conditioning abcColumns with different letters are different (P < 0.05); Error bars represent standard error of the mean 1Distances run were 3 km (week -1), 11.2 km (week 1), 30.1 km (week 4), 35.8 km (week 5) and 36 km (week 7).

3.5 Discussion To our knowledge, no previous study has assessed the effects of dietary fiber composition on behaviour and voluntary physical activity of sled dogs. Soluble fermentable fibers, specifically MOS, beta-glucans and inulin-type fructans, are well accepted to improve gut health through reductions in pathogenic bacteria and an increase in commensal bacteria such as

Lactobacilli and Bifidobacteria spp. (Strickling et al., 2000; Swanson et al., 2002; Grieshop et al., 2004; Gouveia et al., 2006). As a result, the adverse physiological effects of exercise, such as

gut dysbiosis (Tysnes et al., 2020; Lamprecht et al., 2012) and oxidative stress (Hinchliff et al.,

2000; Pasquini et al., 2010; Martelli et al., 2011), could be alleviated which would be demonstrated through behavioural changes in sled dogs. Although beneficial bacteria in the gut have been previously seen to influence behaviours in mice (Heijtz et al., 2011; Bravo et al.,

2011; Clarke et al., 2013; Sylvia et al., 2017), in the present study supplementation of soluble fiber so as to achieve a dietary insoluble: soluble ratio of 3: 1 had no effect on any behavioural or voluntary activity related outcomes of sled dogs.

Changes in dietary soluble fiber content have been previously reported to increase the growth of commensal bacteria in the gut microbiome in dogs (Sunvold et al., 1995; Swanson et al. 2001). However, it is possible that the TRT diet may not have altered the microbiota concentrations to a great enough degree to elicit significant differences when compared to the control diet in the current study, explaining why no behavioural changes were observed. In laboratory dogs, behavioural responses between meals and in an open-field test were evaluated after seven weeks of being either fed a highly fermentable fiber diet with an insoluble: soluble ratio of approximately 4:1 or a low fermentable fiber diet with an insoluble: soluble ratio of approximately 11:1 (Bosch et al., 2009). The degree of difference between those two diets was greater than in the current study, but like the current study, Bosch et al. (2009) reported no impact of diet on various behaviours, including anxiety-like behaviours, tail wagging or exploration. However, dogs consuming the highly fermentable fiber diet were less active (Bosch et al., 2009). In the current study, there was no difference in voluntary physical activity levels between the dogs fed CON or TRT. Future research is warranted to investigate the effects of the

various insoluble: soluble dietary fiber ratios on the voluntary physical activity of actively training dogs.

While the dietary intervention did not influence the behaviour and voluntary activity of sled dogs, the training regimen itself had a significant impact. We previously reported a decrease in locomotive behaviours prior to exercise, and an increase in lying time post-exercise, in sled dogs undergoing 12 weeks of repetitive incremental exercise (Robinson et al., 2020).

Behavioural changes throughout the first 10 weeks of training were similar between both studies, with Robinson et al. (2020) reporting an increase in lying time prior to exercise predominantly in the additional two weeks of the trial. Combined, this suggests that repetitive endurance exercise in sled dogs results in a decrease in locomotive behaviours prior to exercise.

The results of the present study indicate a short-term recovery from exercise during the two consecutive rest days that were provided each week. Sled dogs were more active on their second rest day, suggesting they may have already begun to recover from the physiological impacts of repetitive endurance exercise by this second day. Endurance exercise results in a significant glycogen depletion in sled dogs; however, they are capable of attenuating muscle glycogen usage throughout repetitive training bouts (Reynolds et al., 1995; McKenzie et al.,

2005; McKenzie et al., 2008). Glycogen depletion is a possible reason for the decreased voluntary activity following endurance exercise, as it contributes to fatigue (Jensen et al., 2011).

Complete glycogen repletion typically occurs within 24 hours post exercise, and consumption of a high carbohydrate diet may accelerate the repletion in humans and dogs (Bergstrom et al.,

1967; Costill et al., 1981; Reynolds et al., 1997). The recovery of glycogen during the first rest day could contribute to the increase in voluntary activity on the second rest day. In addition to 79

glycogen depletion, endurance exercise increases creatine kinase concentration in sled dogs

(Hinchcliff et al., 2000; Mckenzie et al., 2005), which is a marker of muscle cell damage and contributes to muscle soreness and fatigue. In untrained humans, creatine kinase levels increased after three consecutive bouts of exercise and returned to pre-exercise levels after two days of rest

(Totsuka et al., 2002). It is possible that the dogs in the current study had elevated creatine kinase concentrations, causing muscle soreness, fatigue, and a reduction in voluntary locomotion. After the first rest day, a decrease in creatine kinase concentrations may further contribute to the increased voluntary physical activity observed in sled dogs. Future research should attempt to correlate various physiological markers, such as glycogen repletion rates and creatine kinase concentrations, with voluntary physical activity, to assess the recovery of sled dogs over multiple rest days.

Further findings from the current study also indicate an adaptation to the high levels of repetitive exercise performed on a weekly basis. Activity during run days decreased based on both the distance the dogs ran and the week of the training regimen, up until week five. After this week, the weekly training regimen was reduced due to inclement weather. Even though similar distances were run during weeks five and seven, the reduction in exercise performance between these weeks could have caused the increase in voluntary activity during week seven. This suggests that the sled dogs might have been rapidly adapting to performing at increased durations of exercise bouts, potentially through improved cardiovascular and respiratory function

(Thornton et al., 2020) and skeletal muscle capacity (Laughlin and Roseguini, 2009). When the training regimen was reduced, sled dogs appeared to compensate for this by performing more voluntary physical activity. This indicates that conditioned sled dogs are motivated to perform at

an increased level of exercise and will self-exercise when not provided with sufficient controlled exercise. While we have previously suggested that repetitive endurance exercise could lead to a decrease in motivation to exercise in sled dogs (Robinson et al., 2020), results from the current study indicate these dogs may actually be motivated and capable of adapting to perform high duration repetitive bouts of endurance exercise. Future research should continue to assess the motivation to exercise in working canines.

Overall, dietary soluble fiber content did not affect behaviour or voluntary physical activity of sled dogs. However, changes in behaviour and voluntary activity were observed throughout the repetitive conditioning period. The increase in voluntary activity following one rest day provides evidence of a potential short-term recovery of sled dogs. Sled dog owners should therefore consider using multiple rest days between repetitive training bouts to maximize recovery, which may subsequently improve performance. Additionally, the increase in voluntary physical activity after a reduction in exercise training suggests dogs can become acclimated to perform high duration repetitive exercise. Future research should assess specific behavioural indicators of motivation, to determine if sled dogs are continually motivated to perform repetitive endurance exercise. Furthermore, the impacts of dietary soluble fiber on exercising dogs should continue to be evaluated, to determine if a larger inclusion of soluble fibers in the diets reduces voluntary physical activity. Overall, these results can be used to improve training regimens that will maximize the recovery, health and performance of sled dogs.

3.6 References Bergström, J., Hermansen, L., Hultman, E., & Saltin, B. (1967). Diet, Muscle Glycogen and Physical Performance. Acta Physiologica Scandinavica, 71(2–3), 140–150. Bonaz, B., Bazin, T., & Pellissier, S. (2018). The Vagus Nerve at the Interface of the Microbiota- Gut-Brain Axis. Frontiers in Neuroscience, 12. Bosch, G., Beerda, B., van de Hoek, E., Hesta, M., van der Poel, A. F. B., Janssens, G. P. J., & Hendriks, W. H. (2009). Effect of dietary fibre type on physical activity and behaviour in kennelled dogs. Applied Animal Behaviour Science, 121(1), 32–41. Bravo, J. A., Forsythe, P., Chew, M. V., Escaravage, E., Savignac, H. M., Dinan, T. G., Bienenstock, J., & Cryan, J. F. (2011). Ingestion of Lactobacillus strain regulates emotional behavior and central GABA receptor expression in a mouse via the vagus nerve. Proceedings of the National Academy of Sciences, 108(38), 16050–16055. Clark, A., & Mach, N. (2016). Exercise-induced stress behavior, gut-microbiota-brain axis and diet: A systematic review for athletes. Journal of the International Society of Sports Nutrition, 13(1), 43. Clarke, G., Grenham, S., Scully, P., Fitzgerald, P., Moloney, R. D., Shanahan, F., Dinan, T. G., & Cryan, J. F. (2013). The microbiome-gut-brain axis during early life regulates the hippocampal serotonergic system in a sex-dependent manner. Molecular Psychiatry, 18(6), 666–673 Costill, D. L., Sherman, W. M., Fink, W. J., Maresh, C., Witten, M., & Miller, J. M. (1981). The role of dietary carbohydrates in muscle glycogen resynthesis after strenuous running. The American Journal of Clinical Nutrition, 34(9), 1831–1836. Gagné, J. W., Wakshlag, J. J., Simpson, K. W., Dowd, S. E., Latchman, S., Brown, D. A., Brown, K., Swanson, K. S., & Fahey, G. C. (2013). Effects of a synbiotic on fecal quality, short-chain fatty acid concentrations, and the microbiome of healthy sled dogs. BMC Veterinary Research, 9(1), 246. Gouveia, E., Silva, I., Onselem, V., Corrêa, R., & Silva, C. (2006). Use of mannanoligosacharides as an adjuvant treatment for gastrointestinal diseases and this effects on E.coli inactivated in dogs. Acta Cirúrgica Brasileira / Sociedade Brasileira Para Desenvolvimento Pesquisa Em Cirurgia, 21 Suppl 4, 23–26. Grieshop, C. M., Flickinger, E. A., Bruce, K. J., Patil, A. R., Czarnecki-Maulden, G. L., & Fahey, G. C. (2004). Gastrointestinal and immunological responses of senior dogs to chicory and mannan-oligosaccharides. Archives of Animal Nutrition, 58(6), 483–493. Heijtz, R. D., Wang, S., Anuar, F., Qian, Y., Björkholm, B., Samuelsson, A., Hibberd, M. L., Forssberg, H., & Pettersson, S. (2011). Normal gut microbiota modulates brain 82

development and behavior. Proceedings of the National Academy of Sciences, 108(7), 3047–3052. Hinchcliff, K. W., Reinhart, G. A., DiSilvestro, R., Reynolds, A., Blostein-Fujii, A., & Swenson, R. A. (2000). Oxidant stress in sled dogs subjected to repetitive endurance exercise. American Journal of Veterinary Research, 61(5), 512–517. Jensen, J., Rustad, P. I., Kolnes, A. J., & Lai, Y.-C. (2011). The Role of Skeletal Muscle Glycogen Breakdown for Regulation of Insulin Sensitivity by Exercise. Frontiers in Physiology, 2. Ji, L. L., & Leichtweis, S. (1997). Exercise and oxidative stress: Sources of free radicals and their impact on antioxidant systems. Age, 20(2), 91–106. Khayyatzadeh, S. S., Firouzi, S., Askari, M., Mohammadi, F., Nikbakht-Jam, I., Ghazimoradi, M., Mohammadzadeh, M., Ferns, G. A., & Ghayour-Mobarhan, M. (2019). Dietary intake of carotenoids and fiber is inversely associated with aggression score in adolescent girls. Nutrition and Health, 25(3), 203–208. Kirchoff, N. S., Udell, M. A. R., & Sharpton, T. J. (2019). The gut microbiome correlates with conspecific aggression in a small population of rescued dogs (Canis familiaris). PeerJ, 6, e6103. Academic OneFile. Klein, D. J., McKeever, K. H., Mirek, E. T., & Anthony, T. G. (2020). Metabolomic Response of Equine Skeletal Muscle to Acute Fatiguing Exercise and Training. Frontiers in Physiology, 11. Lamprecht, M., Bogner, S., Schippinger, G., Steinbauer, K., Fankhauser, F., Hallstroem, S., Schuetz, B., & Greilberger, J. F. (2012). Probiotic supplementation affects markers of intestinal barrier, oxidation, and inflammation in trained men; a randomized, double- blinded, placebo-controlled trial. Journal of the International Society of Sports Nutrition, 9(1), 45. Laughlin, M., & Roseguini, B. (2009). Mechanisms for exercise training-induced increases in skeletal muscle blood flow capacity: Differences with interval sprint training versus aerobic endurance training. Journal of Physiology and Pharmacology: An Official Journal of the Polish Physiological Society, 59 Suppl 7, 71–88. Mach, N., & Fuster-Botella, D. (2017). Endurance exercise and gut microbiota: A review. Journal of Sport and Health Science, 6(2), 179–197 Martarelli, D., Verdenelli, M. C., Scuri, S., Cocchioni, M., Silvi, S., Cecchini, C., & Pompei, P. (2011). Effect of a Probiotic Intake on Oxidant and Antioxidant Parameters in Plasma of Athletes During Intense Exercise Training. Current Microbiology, 62(6), 1689–1696.

McKenzie, E. C., Hinchcliff, K. W., Valberg, S. J., Williamson, K. K., Payton, M. E., & Davis, M. S. (2008). Assessment of alterations in triglyceride and glycogen concentrations in muscle tissue of Alaskan sled dogs during repetitive prolonged exercise. American Journal of Veterinary Research, 69(8), 1097–1103. Mckenzie, E., Holbrook, T., Williamson, K., Royer, C., Valberg, S., Hinchcliff, K., Jose- Cunilleras, E., Nelson, S., Willard, M., & Davis, M. (2005). Recovery of Muscle Glycogen Concentrations in Sled Dogs during Prolonged Exercise: Medicine & Science in Sports & Exercise, 37(8), 1307–1312. Nogueira, J. P. D. S., He, F., Mangian, H. F., Oba, P. M., & De Godoy, M. R. C. (2019). Dietary supplementation of a fiber-prebiotic and saccharin-eugenol blend in extruded diets fed to dogs. Journal of Animal Science, 97(11), 4519–4531. Pasquini, A., Luchetti, E., & Cardini, G. (2010). Evaluation of oxidative stress in hunting dogs during exercise. Research in Veterinary Science, 89(1), 120–123. Reynolds, A. J., Fuhrer, L., Dunlap, H. L., Finke, M., & Kallfelz, F. A. (1995). Effect of diet and training on muscle glycogen storage and utilization in sled dogs. Journal of Applied Physiology, 79(5), 1601–1607. Rios-Covian, D., Salazar, N., Gueimonde, M., & de los Reyes-Gavilan, C. G. (2017). Shaping the Metabolism of Intestinal Bacteroides Population through Diet to Improve Human Health. Frontiers in Microbiology, 8. Robinson, E., Templeman, J. R., Thornton, E., Croney, C. C., Niel, L., & Shoveller, A. K. (2020). Investigating the effects of incremental conditioning and supplemental dietary tryptophan on the voluntary activity and behaviour of mid-distance training sled dogs. PLOS One, forthcoming. Sapkota, A., Marchant-Forde, J. N., Richert, B. T., & Lay, D. C. (2016). Including dietary fiber and resistant starch to increase satiety and reduce aggression in gestating sows1,2. Journal of Animal Science, 94(5), 2117–2127. Snow, D. H., Baxter, P., and Rose, R. J. (1981). Muscle fibre composition and glycogen depletion in horses competing in an endurance ride. Vet. Rec. 108, 374–378. Stone, M. H., Keith, R. E., Kearney, J. T., Fleck, S. J., Wilson, G. D., & Triplett, N. T. (1991). Overtraining: A Review of the Signs, Symptoms and Possible Causes. The Journal of Strength & Conditioning Research, 5(1), 35. Strickling, J., Harmon, D., Dawson, K., & Gross, K. (2000). Evaluation of oligosaccharide addition to dog diets: Influences on nutrient digestion and microbial populations. Animal Feed Science and Technology - ANIM FEED SCI TECH, 86, 205–219.

Sunvold, G. D., Fahey, G. C., Merchen, N. R., Titgemeyer, E. C., Bourquin, L. D., Bauer, L. L., & Reinhart, G. A. (1995). Dietary fiber for dogs: IV. In vitro fermentation of selected fiber sources by dog fecal inoculum and in vivo digestion and metabolism of fiber- supplemented diets. Journal of Animal Science, 73(4), 1099–1109. Swanson, K. S., Grieshop, C. M., Clapper, G. M., Shields, R. G., Belay, T., Merchen, N. R., & Fahey, G. C. (2001). Fruit and vegetable fiber fermentation by gut microflora from canines. Journal of Animal Science, 79(4), 919–926. Swanson, Kelly S., Grieshop, C. M., Flickinger, E. A., Bauer, L. L., Healy, H.-P., Dawson, K. A., Merchen, N. R., & Fahey, G. C. (2002). Supplemental fructooligosaccharides and mannanoligosaccharides influence immune function, ileal and total tract nutrient digestibilities, microbial populations and concentrations of protein catabolites in the large bowel of dogs. The Journal of Nutrition, 132(5), 980–989. Sylvia, K. E., Jewell, C. P., Rendon, N. M., St John, E. A., & Demas, G. E. (2017). Sex-specific modulation of the gut microbiome and behavior in Siberian hamsters. Brain, Behavior, and Immunity, 60, 51–62. Templeman, J. R., Thornton, E., Cargo-Froom, C., Squires, E. J., Swanson, K. S., & Shoveller, A. K. (2020) Effects of incremental exercise and dietary tryptophan supplementation on the amino acid metabolism, serotonin status, stool quality, fecal metabolites, and body composition of mid-distance training sled dogs. Journal of Animal Science, 98(5). Totsuka, M., Nakaji, S., Suzuki, K., Sugawara, K., & Sato, K. (2002). Break point of serum creatine kinase release after endurance exercise. Journal of Applied Physiology, 93(4), 1280–1286. Thornton, E., Templeman, J. R., Bower, M., Cant, J. P., Holloway, G. P., & Shoveller, A. K. (2020). Exercise but Not Supplemental Dietary Tryptophan Influences Heart Rate and Respiratory Rate in Sled Dogs. Veterinary Sciences, 7(97), 97. Tysnes, K. R., Angell, I. L., Fjellanger, I., Larsen, S. D., Søfteland, S. R., Robertson, L. J., Skancke, E., & Rudi, K. (2020). Pre- and Post-Race Intestinal Microbiota in Long- Distance Sled Dogs and Associations with Performance. Animals, 10(2), 204. Velikonja, A., Lipoglavšek, L., Zorec, M., Orel, R., & Avguštin, G. (2019). Alterations in gut microbiota composition and metabolic parameters after dietary intervention with barley beta glucans in patients with high risk for metabolic syndrome development. Anaerobe, 55, 67–77. Zhao, L., Zhang, F., Ding, X., Wu, G., Lam, Y. Y., Wang, X., Fu, H., Xue, X., Lu, C., Ma, J., Yu, L., Xu, C., Ren, Z., Xu, Y., Xu, S., Shen, H., Zhu, X., Shi, Y., Shen, Q., … Zhang, C. (2018). Gut bacteria selectively promoted by dietary fibers alleviate type 2 diabetes. Science, 359(6380), 1151–1156. 85

4. Chapter 4: General Discussion

Even though dogs have been used for sporting and working purposes for many years, there is a dearth of data regarding the effects of typical exercise conditioning and training regimens on their behaviour. For sled dogs, the numerous physiological disruptions and adaptations that occur throughout repetitive endurance exercise have been reported (Hinchliff et al., 2000; McKenzie et al., 2005; McKenzie et al., 2007). However, it is important to similarly investigate the behavioural changes, as these could be utilized by working dog owners and trainers as simple and reliable markers in the identification of fatigue or overtraining. The results presented in this thesis are the first to characterize the behavioural changes that occur throughout a conditioning period in sled dogs, and to determine how behaviour changes in the context of different dietary interventions.

In both Chapters 2 and 3, a similar incremental exercise regimen was implemented, which resulted in a progressive decrease in locomotive behaviours, including posture changing and lunging (Chapter 2), and an increase in standing (Chapter 3) and lying down (Chapter 2), prior to an exercise bout. The variation in the behaviours observed between the two studies is likely due to environmental conditions and dog characteristics such as genetics, age, and experience. The average age for the cohort of dogs in Chapters 2 and 3 were 4.8 and 3.7 years, respectively, indicating that the dogs in Chapter 3 were younger and consequently less experienced. Lunging behaviours prior to exercise were observed more in total in Chapter 2, while standing was observed more in total in Chapter 3, potentially reflecting the age difference.

This could suggest that focus by sled dog owners/trainers should be placed on being familiar with the specific normal behaviour patterns of their individual dogs, in order to be aware of when 86

abnormal behavioural changes are occurring. However, posture changing, consisting of restlessness and constant changes in state of motion, prior to a bout of exercise decreased in both cohorts of dogs as the training regimen progressed. This suggests that this behaviour is the most reliable marker to watch for throughout an endurance exercise regimen. As discussed in Chapters

2 and 3, there are various potential reasons for these behavioural changes, such as decreased endogenous energy stores (Wakshlag et al., 2002; Gomes et al., 2009) or muscle soreness and fatigue (Barclay and Hansel, 1991; Hinchliff et al., 2000). A high rate of posture changing could indicate motivation to be active prior to an exercise bout, and the progressive decrease in this behaviour could indicate that dogs are becoming less motivated to exercise or are experiencing an accumulation of the various physiological effects of exercise. However, a decrease in locomotive behaviours prior to exercise could simply indicate that dogs are becoming acclimatized to the training routine. Future research should correlate physiological markers of endogenous energy, such as glycogen depletion, or muscle fatigue, such as creatine kinase concentrations, with these behavioural changes, specifically with pre-run posture changing, to aid in the identification of the underlying cause. If a decrease in posture changing prior to exercise is related to a decreased amount of endogenous energy, then mushers and working dog owners could potentially use this measure to identify dogs that need more recovery time between exercise bouts. Recovery of muscle glycogen between exercise bouts is necessary to sustain exercise capacity and starting an exercise bout with ample muscle glycogen stores is essential for improved exercise performance.

Voluntary physical activity generally decreased post-exercise as the distance of the training bout increased; however, it began to increase when dogs were given consecutive rest

days. While voluntary activity has been used a marker of exercise recovery previously in laboratory mice (Carmichael et al. 2005; Davis et al., 2007; Takahashi et al., 2013), this is the first study using this technique in dogs. The decrease of voluntary activity following long distance endurance exercise is likely an inevitable and normal part of the exercise-recovery process. Future research should work to correlate the recovery of voluntary activity to physiological markers of exercise-recovery, such muscle glycogen repletion. The restoration of voluntary activity following exercise could indicate that dogs have fully recovered from the physiological effects of exercise. Future research should investigate the time it takes to return to baseline voluntary physical activity following endurance exercise in dogs, both after single bout and repetitive conditioning exercise. Dogs who have undergone appropriate exercise conditioning may demonstrate a faster recovery period (faster return to baseline voluntary physical activity), than unconditioned dogs who participate in a single bout of long-distance exercise. This enhanced recovery of voluntary activity post-exercise may represent the physiological adaptation that occur due to repetitive endurance exercise. Mushers may also be able to use restoration of voluntary physical activity on consecutive rest days as a practical indication of exercise-recovery to ensure that dogs are adequately recovered between exercise bouts. The optimal balance between training and recovery is vital to ensure that dogs adapt to the exercise intensity and continue to improve their performance capacity with incremental exercise.

Furthermore, this thesis investigated the effects of two dietary interventions: supplemental dietary tryptophan and dietary inclusion of soluble fiber. Diet is one way to improve health and performance and to modulate behaviour in mammals. As discussed in

Chapter 2, tryptophan supplementation, which increased the Trp: LNAA ratio, decreased the

percent of time the dogs spent performing agonistic behaviours prior to exercise; however, the diet had no effect on voluntary physical activity. This suggests that dietary tryptophan does not contribute to central fatigue in dogs, as it does not decrease the voluntary physical activity levels of the dogs. Future research should further investigate the use of supplemental tryptophan, to achieve a Trp: LNAA ratio of at least 0.075: 1, to reduce agonistic behaviours in working dogs that have been previously diagnosed with behavioural problems. The reduction of excessive agonistic behaviours prior to exercise could improve the ease of handling and trainability of sporting dogs. Further research in this area could lead to the development of commercially available diets that include the optimum amount of Trp to combat specific behaviours.

Alternatively, consumers could increase the Trp: LNAA ratio by adding a top-dressed Trp solution to the daily feed. While no previous studies have reported any negative effects of over- supplementation of Trp in dogs, care should still be taken if owners add Trp to their feed, as the upper safe intake level is unknown.

As discussed in Chapter 3, the increased inclusion of soluble fiber sources in the diet had no effect on any behaviour or on the voluntary physical activity of the dogs. Future research by this lab aims to characterize the fecal microbiome of the sled dogs used in the present study. This may allow us to identify which bacterial strains and/or fecal metabolites were affected by the increased inclusion of soluble fiber in the diet. It is possible that a shift in the gut microbial abundance was not significant enough to influence any behavioural outcomes. Exercise-induced inflammation and oxidative stress can be alleviated by the increase in certain bacterial strains in humans (Martelli et al., 2011; Lamprecht et al., 2012); however, this has not been investigated in dogs. Future research should aim to determine how increased dietary soluble fiber impacts the

gut microbiome and improves the physiological symptoms that occur during exercise, such as inflammation and muscle damage, in dogs. Even so, the result of our current study may indicate that inclusion of soluble fiber in the diet does not have any adverse effects on behaviour or voluntary activity, and could potentially be used to improve GI disorders that are commonly seen in sled dogs (Davis et al., 2003; Davis et al., 2005).

There are a few limitations to this research. First, although the dogs were all group- housed in free run kennels, the size and number of dogs in each kennel varied. For example, other dogs not participating in the study were housed in the same kennel are those who were, and dogs receiving different treatments were also housed together. This may have influenced the level of voluntary physical activity that dogs performed in their kennel and increased the variability of the results. Additionally, dogs were occasionally moved kennels throughout the trial due to heat cycles and per the owner’s request. Although controlling for clustering in kennels in the statistical model would have potentially increased statistical rigor, for the current research the kennel was not accounted for due to the aforementioned housing restraints.

Additionally, due to the limited number of healthy dogs that were available to participate in the exercise regimen, the sample sizes used per group were relatively small, potentially not giving enough statistical power to detect differences between diet groups. A sample size calculation was conducted based on previous canine studies using physiological measures, that indicated that eight dogs per treatment allows for adequate statistical power to achieve a beta equal or higher than 0.08. Furthermore, it was only possible to exercise 16 dogs at one time due to the length of the gangline used for runs, limiting the capacity to increase the sample size. However, behavioural outcomes are often more variable and may require a higher sample size to achieve

powerful statistical differences. Inherent limitations in animal-based research make it challenging to conduct studies using a large number of animals. Although a larger sample size may be required to achieve more statistically significant differences in the behaviours of the dogs between treatment groups, the current research still provides valuable preliminary data surrounding the effects of diet and exercise on sled dogs.

Another limitation to this research was the lack of an unexercised control group, which could help differentiate behavioural changes from acclimatization to the pre-run routine, as opposed to behavioural changes due to the participation in repetitive endurance exercise.

However, when using working dogs as subjects, it would be unlikely to find participants that would be willing to allow their healthy dogs to act as an unexercised control group during their typical training period. Working dogs who are not training during this period are likely doing so due to injury or other health issues, so would additionally not be suitable candidates for scientific research.

Overall, the results presented within this thesis may be used by mushers and trainers to improve the diets and conditioning period of sled dogs. To improve training, mushers should monitor the prevalence of postural changing prior to exercise, as well as the recovery of voluntary physical activity during rest days, to ensure that the dogs are not experiencing fatigue or adverse symptoms due to the exercise regimen. Adequate recovery between bouts of exercise will ensure that dogs have replenished energy and nutrient stores, which will promote continued improvements in their exercise capacity and reduce the possibility of fatigue or overtraining.

Additionally, dietary supplementation of Trp may be used to reduce the prevalence of pre-run agnostic behaviours. Dietary soluble fiber had no effects on the behaviours of sled dogs, so has 91

the potential to be used to prevent gastro-intestinal issues in sporting dogs without altering exercise performance. The results presented within this thesis are the first to characterize the behavioural changes that occur throughout a conditioning period, as well as further the knowledge of how diet can impact sporting dog behaviour, and are a step in improving the overall performance and health of working dogs.

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