Determinazione di biomarcatori in matrici biologiche non invasive per la valutazione dello stato di benessere del cane.

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Corso di Dottorato di Ricerca in Scienze e Biotecnologie Agrarie

in convenzione con Università degli Studi di Udine

Dipartimento di Scienze AgroAlimentari, Ambientali e Animali

Ciclo XXX

Coordinatore: prof Giuseppe Firrao

TESI di DOTTORATO di RICERCA

Development of biomarkers in non-invasive

biological matrices

in order to assess dog well-being

.

Anno Accademico 2017/2018

Dottoranda

Supervisore

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Development of biomarkers in non-invasive biological matrices in order to assess dog well-being

INDEX OF CONTENT

Development of biomarkers in non-invasive

biological matrices in order to assess dog well-being

INDEX OF CONTENT

SUMMARY

Chapter 1 OVERALL INTRODUCTION ………..

3

1.1_AIMS OF THIS RESEARCH ... 5

1.2_LITERATURE REVIEW ... 6

1.2.1_SALIVA: A NON-INVASIVE, READILY AVAILABLE MATRIX FOR MANY BIOMARKERS ... 6

1.2.1.1_Salivary Cortisol: a hormone used to evaluate HPA axis activity ... 7

1.2.2_MICROBIOME: AN IMPORTANT MARKER FOR ANIMAL WELFARE ... 11

1.2.2.1_Metagenomics as an evaluation tool of microbiome composition ... 14

1.2.3_HAIR, A NON-INVASIVE MATRIX USEFUL FOR MEASURING SOME BIOMARKERS ... 16

1.2.3.1_Hair Cortisol: a useful matrix for long term monitoring ... 16

1.2.3.2_Heavy metals in hair as biomarkers of health state... 18

1.3_OUTLINE OF THE THESIS ... 19

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INDEX OF CONTENT

Part 1 SALIVARY CORTISOL: AN EFFICIENT BIOINDICATOR OF

HYPOTHALAMIC–PITUITARY–ADRENAL AXIS ACTIVATION

Chapter 2 SALIVARY CORTISOL: A MARKER OF THE ADAPTIVE RESPONSE OF

THE ORGANISM TO ENVIRONMENTAL STIMULI ...

36

2.1_ABSTRACT ... 37

2.2_THE PLEIOTROPIC ROLE OF CORTISOL ... 37

2.3_ASSAYING CORTISOL IN BIOLOGICAL MATRICES ... 40

2.3.1_Sampling ... 40

2.3.2_Factors that influence salivary cortisol levels in the dog ... 42

2.3.3_Potential applications of salivary cortisol assays ... 46

2.3.3.1_Animal-assisted activities ... 47

2.3.3.2_Genetics and breeding ... 48

2.3.3.3_Diseases ... 49

2.4_CONCLUSIONS ... 50

2.5_REFERENCES ………. 51

Chapter 3 SALIVARY CORTISOL CONCENTRATION IN HEALTHY DOGS IS

AFFECTED BY SIZE, SEX, AND HOUSING CONTEXT ...

57

3.1_ABSTRACT ... 58

3.2_INTRODUCTION ... 59

3.3_MATERIALS AND METHODS ... 60

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INDEX OF CONTENT 3.3.2_Salivary sampling ... 60 3.3.3_Statistical analysis ... 61 3.4_RESULTS ... 61 3.5_DISCUSSION ... 66 3.6_CONCLUSIONS ... 68 3.7_REFERENCES ………. 69

Chapter 4 VARIATIONS OF SALIVARY CORTISOL IN DOGS EXPOSED TO

DIFFERENT COGNITIVE AND PHYSICAL ACTIVITIES ……… 73

4.1_ABSTRACT ……… 74

4.2_INTRODUCTION ……….. 75

4.3_MATERIALS AND METHODS ……….. 76

4.3.1_Recruitment of dogs ……….. 76

4.3.1.1_Study 1: Baseline value of salivary cortisol ……….. 76

4.3.1.2_Study 2: Variation of salivary cortisol during activity ………… 76

4.4_RESULTS ……… 81

4.4.1_Study 1: Baseline value of salivary cortisol ……… 81

4.4.2_Study 2: Variation of salivary cortisol during activity ………. 81

4.5_DISCUSSION ... 84

4.5.1_Study 1: Baseline value of salivary cortisol ……… 84

4.5.2_Study 2: Variation of salivary cortisol during activity ………. 84

4.6_CONCLUSIONS ………. 86

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INDEX OF CONTENT

Part 2 NUTRIONAL EFFORTS, FAECAL MICROBIOME, HPA AXIS

Chapter 5 PRELIMINARY STUDY: FAECAL MICROBIOME AS BIOINDICATOR OF

DOG WELL-BEING AND POSSIBLE RELATION WITH

HYPOTHALAMIC-PITUITARY-ADRENAL (HPA) AXIS ...

91

5.3_MATERIALS AND METHODS ……….. 95

5.3.1_Animal selection ... 95 5.3.2_Diet ... 96 5.3.3_Experimental design ... 97 5.3.4_Sample collection ... 98 5.3.4.1_Faeces collection ... 98 5.3.4.2 Salivary sampling ... 98 5.3.5_Faeces analysis ... 99

5.3.5.1_Faecal DNA extraction and sequencing ... 99

5.3.5.2_Faecal score, pH, nitrogen and fatty acids analysis ... 99

5.3.6_Saliva analysis ... 101

5.3.7_Statistical Analysis ... 101

5.4_RESULTS AND DISCUSSIONS ... 103

5.4.1_Microbiome analysis ... 103

5.4.2_Microbiome, SCFAs, lactate and nitrogen in faeces ... 112

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INDEX OF CONTENT

5.5_CONCLUSIONS ... 117

5.6_REFERENCES ... 119

Part 3 BIOMARKERS OF DOG WELL-BEING DETECTED IN HAIR

Chapter 6 PRELIMINARY STUDY: HEAVY METALS AND CORTISOL IN HAIR,

EVALUATED AS POSSIBLE BIOMARKERS OF DOG WELL-BEING ... 126

6.3_MATERIALS AND METHODS ……….. 131

6.3.1_Animal selection ... 131 6.3.2_Diet ... 131 6.3.3_Experimental design ... 131 6.3.4_Sample collection ... 132 6.3.4.1_Hair sampling ... 132 6.3.5_Samples analysis ... 132 6.3.5.1_Cortisol analysis ... 132

6.3.5.2_Heavy metal analysis ... 133

6.3.6_Statistical analysis ... 134

6.4_RESULTS AND DISCUSSION ………. 135

6.4.1_Heavy metals in dog hair ... 135

6.4.2_Cortisol in dog hair... 138

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INDEX OF CONTENT 6.5_CONCLUSIONS ………. 141 6.6_REFERENCES ………. 142

Chapter 7 CONCLUSION ...

146

7.1_FUTURE RESEARCH ………. 147 7.1.1_Measurement of cortisol ... 148

7.1.2_Evaluation of faecal microbiome ... 151

7.1.3_Measurement of heavy metals ... 151

7.2_FINAL NOTES ………. 152

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SUMMARY

1

Development of biomarkers in non-invasive

biological matrices in order to assess dog well-being

SUMMARY

The domestic dog (Canis lupus familiaris) is the most phenotypically diverse mammal species known and has wide ranges in size between breeds (over two orders of magnitude from diminutive 1-kg Chihuahua to the 100-kg Mastiff). Furthermore breed conformation and also behavioural and physiological attributes are far more extreme in dogs (Wayne, 1986a,b; Coppinger and Coppinger, 2001; Wayne and vonHoldt, 2012).

These are some of the reasons that make the research on physiological aspects of dogs more difficult. However it should be also considered the fact that the dog is the only large carnivore ever domesticated so far (Wayne and vonHoldt, 2012). As a consequence in the last decade the close relationship with human has caused an increased attention and an increased number of studies in dog well-being.

The aim of numerous researches is to discover the largest number of not invasive biomarkers that could indicate the state of health of the animals. In these studies is important also to consider breed, gender, age of subjects and also environmental factor.

The work of thesis is composed of three parts:

The first part includes two already published articles and one in submission that identify cortisol as one of the biomarkers useful in evaluating adaptive response at different stimuli.

In the second part, is reported a preliminary study about the evaluation of fecal microbiome in 8 healthy pet dogs after the probiotic addition in an extrused complete diet. For each faecal samples were also analysed short chain fatty acids (SCFA) and lactate, and nitrogen. For each subject were collected saliva and evaluated cortisol variations in correlation with faecal microbiome.

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SUMMARY

2

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Chapter 1 OVERALL INTRODUCTION

3

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The domestic dog (Canis lupus familiaris) is the only large carnivore that have ever been domesticated by man (Wayne and vonHoldt, 2012). The current close relationship between humans and dogs is probably the result of a coevolution developed for cooperative work and that has been ongoing from 150.000 years (vonHoldt et al., 2010; Overall, 2011). Size, shape and behaviour variability, which characterise the current domestic dog breeds, are the result of human artificial selections performed in hundreds of years (Sutter et al., 2007; Overall, 2011). The majority of the physical variations are the consequence of an overt selection for specific behaviourals suites (e.g., coats adapted for hunting vs. retrieving behaviours, and the behavioural patterns that differ with tasks like herding vs. retrieving) (Overall, 2011). These selections are the reflection of both traditional classifications from various kennel clubs, but also from clustering analyses, which used genetic information from representative breeds (Parker et al., 2004; Parker and Ostrander, 2005).

One of the consequence of the human-dog coevolution is that the domestic dog has become the most phenotypically diverse mammal species known. Ranges in size (over two orders of magnitude from diminutive 1-kg Chihuahua to the 100-kg Mastiff), breed conformation and also behavioural and physiological attributes are far more extreme in dogs (Wayne, 1986a,b; Coppinger and Coppinger, 2001; Wayne and vonHoldt, 2012).

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1.1_ AIMS OF THIS RESEARCH

Researchers have been striving to develop objective ways to determine how stressor can influence the being of animals (Mason and Mendl, 1993; Protopopova, 2016). Definition of poor well-being of animals range from decrease of fitness, such as reduced life expectancy, impaired growth and reproduction (Barnett and Hemsworth, 1990; Broom, 1991; Protopopova, 2016), to a focus on the inability of the animal to cope with environmental changes (Broom, 1991). It is clear that the attention in understanding which can be the more suitable parameters to evaluate the state of health and well-being of the dog is an area of scientific interestconcerning both companion and working dogs (Dreschel, 2010; Cobb et al., 2015). As a consequence of this increasing awareness, there are many scientists employed in investigations of several and reliable physiological and genetic markers of dog welfare. Until now, the measures used for well-being evaluation, include reproductive fitness, hypothalamic-pituitary-adrenal (HPA) axis activity, immunosuppression and abnormalities in behaviour (Protopopova, 2016).

In canine research, salivary cortisol is one of the HPA axis biomarkers widely used as indicator of stress or well-being, but much remains unclear about the basic features of salivary cortisol in domestic dogs (Cobb et al., 2016).

For these reasons, in this thesis was decided to deepen/investigate different factors that may affect the well-being of the animals. In the preliminary studies of this doctoral thesis, were used the least invasive and the most responsive matrices in relation to external and internal stimuli that can cause changes in animal welfare conditions. In order to evaluate the reliability of some biomarkers, it was developeded a spectrum of dog well-being state as complete as possible.

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1.2_LITERATURE REVIEW

Although the interest for dog well-being is fairly recent, the continue increase in research on this topic had led to considerable progresses in the analysis of possible animal well-being biomarkers. The following overview of literature aims at showing the role of some matrices and biomarkers that have been taken into account for this study. In this thesis, these biomarkers were considered as possible indicators of dogs well-being.

1.2.1_SALIVA: A NON-INVASIVE, READILY AVAILABLE MATRIX FOR MANY

BIOMARKERS

Saliva is a readily available matrix, which can be collected by non-invasive procedures. Normally, in carnivores the whole saliva is composed by water, electrolytes, proteins, hormones, antibodies and cellular components such as desquamated mucosal epithelium and microorganisms.

It is known that a wide range of biomarkers can be measured in saliva, including heavy metals (e.g., lead), hormones (cortisol and dehydroxyepiandrosterone, DHEA), toxins and their metabolites (cotinine), enzymes (lysozyme, α-amylase), immunoglobulins (IgA), proteins (eosinophil cationic proteins) and DNA. Researchers are also studying the proteomic components of saliva in the perspective of identifying novel biomarkers of diseases (Koh and Koh, 2007). Saliva is also used in screening and diagnosis of acute mental stress, oral and systemic diseases as oral cancer, breast cancer (Devaraj, 2013; Naumova et al., 2014). For example, in humans the complex patterns of salivary responsiveness during mental stress are reflected in an increase of total salivary protein concentration (Bosch et al., 1996; Bosch et al., 2003; Naumova et al., 2014) and in cortisol levels fluctuations (Tornhage, 2009; Naumova et al., 2014).

Saliva represents a good resource for the evaluation of some interesting biomarkers variations. Furthermore, it has to be considered that steroid hormones enter unbound (as ‘free’ molecules) in the saliva through passive diffusion.

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important to recognise the exact moment when doing the sampling, as most of the salivary biomarkers are not secreted constantly but episodically. However saliva allows collecting the samples frequently, being, as mentioned above, a non-invasive matrix. In addition, its collection is also less likely to cause stress if compared to other procedures, such as phlebotomy. This is an important consideration when searching biomarkers of stress. Lastly, saliva samples can reflect real-time levels of biomarkers, unlike other biological fluids, such as urine, whose collection is possible only after a few hours of storage in the bladder (Koh and Koh, 2007).

In humans, and in animals, analysis of salivary inflammatory biomarkers might offer an attractive opportunity for the diagnosis of different systemic disorders. In fact, saliva-based clinical tests can supply a potential diagnostic tool for the detection of certain diseases and syndromes by using biomarkers associated with enhanced systemic inflammation molecules (Rathnayake et al., 2013). For example, Rathanayake et al. (2013) observed that salivary Interleukin-8 (IL-8) concentration was twice as high in patients with experience of tumour diseases compared to subjects who had not suffered and that matrix metalloproteinase-8 (MMP-8) levels were elevated in patients after cardiac surgery or suffering from diabetes, and muscle and joint diseases.

Additionally, it is important to pay attention to the methods of collecting saliva. In humans, when cotton-based saliva sampling methods are used, the salivary levels of steroid hormones (testosterone, progesterone, oestradiol and DHEA) may be artificially high, whereas salivary secretory IgA concentration may be artificially low. In contrast, salivary cortisol, DHEA sulphate and cotinine may not be affected by the cotton-based method. The reason for these differences is still uncertain. Awareness of such sampling issues is important in ensuring the measurement validity in any salivary biomarker assay. However, further researches on the individual salivary normal levels of the molecules mentioned above, is necessary before salivary biomarkers can be used in daily practice (Koh and Koh, 2007).

1.2.1.1_Salivary Cortisol: a hormone used to evaluate HPA axis activity

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Figure 1.1_Response of the HPA axis to a stressor (Protopopova, 2016).

Another important part of this mechanism, still to be explored in order to understand the different GCs mechanisms of action, is the structure/function of the glucocorticoid’s receptors (GR). A GR is built as a modular protein and the existence of different GR isoforms and combinations hereof with alternatively spliced variants is bound to contribute to the vast pleiotropicity of GR’s functionality in different tissues (Ratman et al., 2013). It is clear that different mechanisms of GR and consequently of GC, engrave on a large part of tissues.

Furthermore, some studies in humans have led to the identification of FK506 binding protein 5, also known as FKBP5, key role in increasing HPA axis activity and GR sensitivity. FKBP5 is a co-chaperone component of the GR heterocomplex (Schiene-Fischer and Yu, 2001; Binder et al., 2008; Gillespie et al., 2009). An overexpression of FKBP5 reduces the hormone binding affinity and nuclear traslocation of GR (Denny et al., 2000; Scammell et al., 2001; Gillespie et al., 2009) (Figure 1.2). New world monkeys with naturally-occurring overexpression of FKBP5 experienced an increased GR resistance and hypercortisolemia (Denny et al., 2000; Scammell et al., 2001; Gillespie

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Figure 1.2_Schematic of FKBP5 cellular (modified from Gillespie et al., 2009).

Schematic diagram depicting the function of FKBP5 as a co-chaperone which regulates glucocorticoid receptor (GR) binding and translocation within the nucleus. When sufficient cortisol is present leading to GR dimerization and FKBP4 binding, FKBP5 is displaced allowing GR translocation and transcriptional activation. However, one of the gene targets of GR is the FKBP5 gene, which when increased in expression is thought to act as a negative intracellular feedback on the GR system within the cell (Gillespie et al., 2009).

As mentioned earlier, also immune system is involved in the response to a possible stressor stimulation. Prolonged exposures to stress may lead to immuno-suppression and dysregulation of HPA-axis. This dysregulation may manifest in an initial hypercorticolism, followed by hypocorticolism, where cortisol levels remain low even under stress situations (Dreschel, 2007; Protopopova, 2016). The neuro-endocrine and the immune networks work together in complex ways that affect each branches of all systems (Dreschel, 2007; Protopopova, 2016). In fact, there are many conflicting effects of glucocorticoids on immune system function and competence (Sapolsky et al., 2000).

In the specific case of cortisol, its purpose is primarily to divert cellular processes from metabolic functions to functions that are necessary for immediate survival (“fight or flight” respose) (Protopopova, 2016).

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In dogs, salivary cortisol has been revealed to be highly correlated with plasma cortisol with an approximately 20 minute temporal lag period during which hormone increments in plasma are reflected in saliva (Vincent and Michell, 1992). When compared to faecal or urinary cortisol, salivary one is temporally more closely related to the circulatory levels.

1.2.2_ MICROBIOME: AN IMPORTANT MARKER FOR ANIMAL WELFARE

In recent years, the research in the area of microbiome science has received a large amount of interest (O’Callaghan et al., 2016). The gastrointestinal tract of humans and animals is occupied by a dense and diverse population of microorganisms which can influence the health of the host (Panasevich et al., 2015). Gut microbiota is important in modulating human health, as it is in animals, such as cats, dogs and monkeys (McKenna et al., 2008; Suchodolski, 2011; Suchodolski et

al., 2012; An et al., 2017). Thus, microbiome is thought to be a useful marker to determine the

health state of both humans and animals, and the well-being of companion animals, just as their owners, depends also on the gut microbes functions (Daniels et al., 2014; Grześkowiak et al., 2015; An et al., 2017). Intestinal microbes play a crucial role in the preservation of host health by acting as a defending barrier against transient pathogens, supporting the host during the digestion and harvesting energy from diet; they can also stimulate the immune system and provide nutritional support for the enterocytes (Suchodolski, 2011; Suchodolski et al., 2012).

Constant communication between gut and brain occurs mainly at a subconscious level and plays a critical role in the maintenance of an optimal health status. In humans the gastrointestinal tract, in addition of being the largest endocrine organ, is a nexus of communication among the immune cells (here present at the highest concentration in the body), 200-600 million neurons and the gut microbiome (trillions of bacteria, fungi and viruses) (Forsythe et al., 2016). Alterations of this complex ecosystem has been associate with numerous diseases in humans, dogs and cats (Suchodolski et al., 2010; Handl et al., 2011). Microbiome can be viewed as a metabolic ‘‘organ’’ tuned exquisitely to mammals physiology and that performs fuctions mammals have not had to evolve on their own. The definition of the host signalling pathways regulated by microbiome provides an opportunity to identify new therapeutic targets deputed in promoting health (Bäckhed et al., 2004).

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Figure 1.3_Mechanisms of the microbiota-gut-brain axis (modified from Forsythe et al., 2016).

The intestinal microbiota has direct and indirect effects of on the intestinal epithelium, local mucosal immune system, enteric nervous system and spinal and vagal nerves. _{Signals from the Central Nervous} System and neuroendocrine system, including cortisol, catecholamines and acetylcholine, can alter gut microbiota composition (Forsythe et al., 2016).

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development, control of allergic disorders and, as recently reported by Grześkowiak et al. (2015), probiotic can contrast obesity.

Therefore, properties, effects and characteristics of each individual strain should be well defined and demonstrated in a case by case manner (Gueimonde and Collado, 2012).

1.2.2.1_Metagenomics as an evaluation tool of microbiome composition

The intestinal ecology has been mostly investigated using culture-dependent techniques. The discovery of molecular methods, such as comparative 16S rRNA analysis, has revealed a much more diverse intestinal ecosystem than that recognised previously (Handl et al., 2011). In fact, until the last decade our knowledge on microbiota composition and development was largely based on the use of traditional culture-based methods. The culturing had provided interesting data, but also a very biased view of the gut microbiota composition. Traditional culture-based methods allow to identify only 1-3% of phyla of the microorganisms directly present in their environment (Handl et al., 2011; Gordon, 2012). The techniques based on extensive DNA sequencing, have increased enormously the awareness on microbiome composition and activity. The study of the entire microbial communities using genomic approaches has revealed a much greater diversity compared to what it was previously thought to exist and it has helped to determine the community structure of several ecosystems, previously unknown. Next generation sequencing technologies have recently been used to characterise the identity and functional capacity of a variety of microbial communities, including the gastrointestinal tracts of mammalian species (Swanson et al., 2011). Furthermore, another interesting and important aspect concerning the development of these techniques is the enormous contribution in exploring several aspects of the probiotics research (Gueimonde and Collado, 2012).

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Additionally, rRNA-based analysis remains the central method in microbiology, exploited not only to investigate microbial diversity, but also as a day-to-day method for bacterial identification (Wang et al., 2007).

As it is well known, the ribosomal 16S rRNA is an essential component of the small ribosome unit containing a specific sequence for each bacterial species. For this reason, it is used in the analysis of the microbial community composition. The gene consists of 10 conserved regions and 9 hypervariable ones, it is subjected to a low evolutionary rate and conserved in all bacteria species. The choice of using the 16S rRNA as a phylogenetic marker to examine microbial diversity and to identify and classify microorganisms arises from the difficulty in cultivating most of the microorganisms present in natural environments. 16S rRNA gene is sequenced through NGS platforms and similar sequences are grouped into Operational Taxonomic Units (OTUs); these represent a system to distinguish species and classify nucleotide sequences at different taxonomic levels. The abundance of the different OTUs is then estimated from the number of corresponding sequences. The individual sequenced hypervariable regions are grouped into OTUs, computing the same conventional distance value as it is used for the full sequence of the 16S rRNA. In some recent studies, individual hypervariable regions have been compared to each other with the entire sequence of the gene in order to estimate relative abundances (Claesson et al., 2009). Hence, it is now proven that different hypervariable regions do not always yield the same results if applied to different biological samples. In each matrix, the most informative hypervariable regions must be identified according to the bacterial community. Specifically, faecal samples in dogs provide greater taxonomic information by studying the hypervariable V3-V4 region (Figure 1.4).

Figure 1.4_Variable and conserved regions.

0 100 200 300 400 500 600 700 800 900 1000 1100 1200 1300 1400 1500 bp

V1 V2 V3 V4 V5 V6 V7 V8 V9

CONSERVED REGIONS:unspecific applications.

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1.2.3_HAIR, A NON-INVASIVE MATRIX USEFUL FOR MEASURING SOME

BIOMARKERS

Hair has been successfully used to measure both internal and external exposure to a wide variety of organic and inorganic pollutants (Schramm, 1997; Covaci et al., 2002; Zhang et al., 2007; Smolder et al., 2009). As hair in humans grows about one centimetre per month, analysis of hair of different length may reflect cumulative exposure over several months. Taking advantage of this property, differences in exposure can be followed over several months or even years.

Potential constraints on the use of hair as matrix include the difficulty in differentiating internal and external sources of contaminant (ATSDR, 2001; Schramm, 2008). Probably, the best-known usage of hair as a non-invasive matrix for metals is the biomonitoring of organic and inorganic mercury, as hair is by far the best integrator of past exposures (Gosselin et al., 2006; Choi and Grandjean, 2008), although also other metals have repeatedly been monitored using hair (Krause

et al., 1996; ATSDR, 2007; McDowell et al., 2004).

Many contaminants have been proven to reach hair and finger/toenails via two major routes: endogenous (xenobiotics reach the hair matrix through blood) and exogenous (atmospheric deposition) (Schramm, 1997; Esteban and Castano, 2009). Hence, it may be difficult to distinguish between contaminants absorbed and those related to external contamination.

1.2.3.1_Hair Cortisol: a useful matrix for long term monitoring

Cortisol has long been considered as a reliable physiological measure of the stress response in both humans (Russell et al., 2012) and other mammals (Park et al., 2016).

Hair sampling is non-invasive, painless and particularly valuable in providing a marker, which is easy to store even for long periods. The hair matrix is a promising tool that allows to study prolonged changes in the HPA axis activity through the measurement of the cortisol incorporated in hair. It is a method that can be used as an instrument to evaluate the animal well-being (Koren

et al., 2002; Accorsi et al., 2008; Bennett and Hayssen, 2010; Roth et al., 2016). Furthermore, the

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Hair cortisol has been extensively studied during the last years and positively correlated with cortisol levels in both saliva and faeces of dogs (Accorsi et al., 2008; Bennett and Hayssen, 2010; Roth et al., 2016).

It is known that hair growth is cyclic:

 anagen phase (new growth), it consists in the formation of all the hair structures as the papilla, the bulb, the sebaceous gland, the eruptive muscle and the follicle. In this phase there is also the melanin synthesis in the form of fusiform granules contained in the melanocytes present in the deep part of the bulb matrix, then deposited in the cortex cells;

 catagen phase (transition), period in which the formed hair moves toward the superficial layers of the epidermis and papilla, which decreases its size;

 telogen phase (quiescence) represents the sleeping phase of the hair. The papilla almost disappears and the hair prepares to fall;

 pellow phase characterised by hair loss, it is followed by a new anagen phase.

However, the mechanism on how cortisol enters the hair is still unclear. On the other hand, a typical model of steroids incorporation in the hair starts with their assimilation by passive diffusion from the blood capillaries, which surrounds and supplies the growing hair cells (anagen phase), and ends with keratinization and dehydration of the hair cells (Cone, 1996; Meyer and Novak, 2012). Other proposed models include stereoids incorporation from shallow compartments of the skin during the formation of the hair shaft, or through the sebaceous gland attached to each hair follicle, otherwise from the nearby sweat glands that bathe the growing hair shaft for several days before it emerges from the skin. The substances can also be deposited from the outside environment. In addition, it seems that the hair follicles themselves could locally produce cortisol (Ito et al., 2005; Park et al., 2016). Regardless from the above mentioned mechanisms, cortisol concentrations in hair have been shown to reflect endocrine patterns (Park et al., 2016).

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also be influenced by Agouti gene. It has been observed that black dogs exhibit a lower cortisol concentration than non-black dogs, as black hair contains a greater amount of pigment that reduces in receptors the 'available' space for glucocorticoids, whose concentrations, instead, are larger in the hairs of canine lighter coats (Bennett and Hayssen, 2010).

Regarding the influence of temperature and photoperiod, it is currently unknown whether cortisol levels in the hair vary during the different seasons (Sauvé et al., 2007).

1.2.3.2_Heavy metals in hair as biomarkers of health state

Some metals and their compounds are essential to human health (i.e. iron (Fe), zinc (Zn), chromium (Cr)), although they are potentially harmful if consumed in large amounts. Other metals potentially harmful for health, arsenic (As), lead (Pb), cadmium (Cd) and mercury (Hg) do not have known beneficial biological functions, but long-term exposure to them may be toxic even at low doses (González-Muñoz et al., 2008).

In recent years, human scalp hair has gained considerable attention for its use as a biomonitor of trace elements aimed at estimating environmental exposure levels and assessing the nutritional status, as well as for the utilisation as a mean of illness diagnosis. Scalp hair constitutes an optima matrix for its ability to accumulate greater trace elements than that of other biological matrices (Sanna et al., 2003; Dunicz-Sokolowska et al., 2006; Varrica et al., 2014). As reported by Beernaert

et al. (2007), mammalian hair is predominantly composed by keratin, a protein rich in cystine sulfhydryl (thiol) groups with a binding affinity for various metals. Each hair shaft is continuously in contact with the bloodstream at the root, and thus may incorporate metals circulating in the blood during growth processes (McLean et al., 2009). Consequently, hair may reflect metal concentrations in the body and is a candidate as a non-invasive proxy for body metal burden. Sufficient evidences exist to suggest that mammalian hair is an appropriate accumulative indicator of metal bioavailability, with significant correlation between metals and metalloids within hair and other tissues.

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in order to evaluate any potential correlation between the levels of metals in blood and hair (Zaccaroni et al., 2014).

The mineral status of individuals has conventionally been determined by analysis of biological samples, basically blood ones. Nevertheless, the clinical utility of hair analysis is well accepted for some elements, as it is recognised that hair provides a better estimation of the total body intake of certain elements in comparison to blood or urine (Wilhelm et al., 1989).

Anyway, this approach remains in the realm of clinical investigation predominantly (Druyan et

al., 1998). Indeed, hair has become a well established metabolically inactive tissue, especially for

investigating changes and levels of various trace elements accumulated in the body (Druyan etal.,

1998). Furthermore, levels of these elements in the hair are less influenced by their immediate intake and for some of them may also prove to be reliable biological indicators in terms of nutritional status (Zaccaroni et al., 2014).

1.3_OUTLINE OF THE THESIS

It is known that, in canines, stressful situations can cause a wide variety of physiological and psychological health issues, such as an increased activity of the sympathetic nervous system, of catecholamine release, blood pressure augment and incremented permeability of the intestinal epithelial lining to microorganisms (Venable et al., 2016). Therefore, in order to prevent healthy issues, it seems to be important to have the necessary instruments to identify those biomarkers, which could provide an estimate of well-being in dogs. For these reasons, in this thesis, some physiological biomarkers were investigated in order to have a general spectrum of well-being state in dogs, as complete as possible. Cortisol was evaluated as one of the principal biomarkers of well-being and it was analysed in two different non-invasive matrices. In association with cortisol, other aspects of dog healthy status were taken into account, having some potential connections with the hormone or effects on theglucocrticoid. Moreover, in the present study, the possible variation of microbiome in association with probiotic addition to the diet and their connection with HPA axis were also explored. Additionally, heavy metals in hair were taken in consideration, especially in reference to their correlation with cortisol fluctuations.

In the development of this thesis the following points are dealt:

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Salivary cortisol is considered as one of the most useful biomarkers in evaluating adaptive responses to different stimuli and in pronouncing hypothalamic-pituitary-adrenal axis (HPA) activation. In particular, in the research field, cortisol is used as a tool for the evaluation of canine well-being (Cobb et al., 2016). In this part of the thesis, three studies, where saliva was used as a matrix for cortisol measurement, are described. Salivary cortisol reflects the blood changes of the hormone with a delay of 20 to 30 minutes (Vincent and Michell, 1992; Beerda et al., 1998; Oyama

et al., 2013), moreover, saliva is one of the least invasive available matrices. The delay of the

cortisol variation in saliva allows to avoid artefacts of this hormone caused by sampling manuality.Additionally, salivary cortisol reflects both the activation of the sympathetic nervous system (acute stress) as well as the activation of Hipothalamic Pituitary Adrenal (HPA) axis (Beerda

et al., 1996; Beerda et al., 1998; Dreschel and Granger, 2009).

Second point: faecal microbiome as an indicator of the healthy state of the dogs and the effects of probiotic addition to the diet on dog well-being.

In this second part of the thesis, the variation of faecal microbiome in relation to probiotic addition in an extruded complete diet was evaluated. Intestinal microbiome analyses were taken in consideration as a result of the important role of gut microbiome in host health both in humans and in domestic animals. Gut microbiota has a helpful role in the digestion, in the nutrition for the enterocytes, it plays an important role in the development of the immune system, acts as a barrier against pathogen invasion and it is also implicated in the regulation of the HPA axis (Neish, 2009; Dinan and Cryan, 2012). Nervethless, the evaluation of microbiome and the possible effects of probiotic addition to the diet were explored also to deepen their connection with HPA axis. In fact, the microbiota may influence the central nervous system (CNS) functions. On the other hand, also the brain can alter the microbiome through signalling molecules released into the gut lumen from cells in the lamina propria, since they are under CNS control thus resulting in changes in the gastrointestinal motility and secretion activity as well as intestinal permeability, altering in this way the enteric environment in which the bacteria reside.

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certain role for the microbiota in anxiety like behaviours, and it seems also that probiotics are involved in the decrement of the behavioural and endocrine components of stress (Dinan and Cryan, 2012). Even if it is not clear the connection of probiotic with cortisol, it seems possible to speculate that a reduction in cortisol levels is caused by a decrease in the release of pro-inflammatory cytokines, which activate the HPA, or alternatively by an alteration of neurotransmitter inputs such as 5-HT (5-hydroxy-tryptamine). As reported by Ait-Belgnaoui et al. (2012) in a research on rats, it seems that prevention of gut leakiness by intestinal microbiota modulation can lead to attenuated HPA axis response to an acute psychological stress (Dinan and Cryan, 2012).

Third point: evaluation of heavy metals and cortisol in hair and their possible correlation with dogs well-being.

It is generally known that mammal tissues are good bioindicators of trace elements, including heavy metals. Metals circulate in the blood stream and they are stored in some body tissues, hair included (Blaurock-busch et al., 2012). In particular, animal hair appears to be a good bioindicator of heavy metal levels and is one of the matrices that gives a better estimate of certain elements than blood or urine does (Wilhelm et al., 1989; Filistowicz et al., 2012; Donnici et al., 2016; Han et

al., 2016). For these reasons and for its non-invasive nature, hair matrix was chosen for this

preliminary study. Heavy metals constitute a wide and special group of chemical agents that may exercise a definite influence on the control of biological functions (many of them are essential to the development of a variety of physiological functions), affecting hormone systems (some metals have been characterized as endocrine disruptors, and one of their targets is the hypothalamus-pituitary-gonadal and/or hypothalamus-pituitary-adrenal axis) and development of different body tissues (Park et al., 2005; Pérez-Cadahìa et al., 2008).

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Part 1

SALIVARY CORTISOL: AN EFFICIENT BIOINDICATOR OF HYPOTHALAMIC–PITUITARY–ADRENAL AXIS ACTIVATION

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SALIVARY CORTISOL: AN EFFICIENT BIOINDICATOR OF HYPOTHALAMIC–PITUITARY–ADRENAL AXIS ACTIVATION

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Chapter 2 SALIVARY CORTISOL: A MARKER OF THE ADAPTIVE RESPONSE OF THE ORGANISM TO

ENVIRONMENTAL STIMULI

A. Colussi, M. Sandri, B. Stefanon

Veterinaria, Vol 30, Issue 3, June 2016

Dipartimento di Scienze Agroalimentari, Ambientali e Animali.

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2.1_ABSTRACT

The increasing attention to animal well-being has stimulated the study of biomarkers of an organism’s adaptive response to the environment, with cortisol emerging as one of the most interesting. Saliva is a biological fluid that is easy to collect and has the advantage that its cortisol content parallels that in blood with a 20-30 minutes delay, thus “photographing” the adaptive response to a past stimulus without interference due to handling while taking the sample. Recent studies have shown that salivary cortisol can be used as a biomarker for some diseases and behavioural modifications, as well as in support of canine activities and sports. The new point-of-care devices for assaying salivary cortisol concentration in dogs provide practitioners with a useful method for evaluating the degree of activation of the hypothalamic-pituitary-adrenal axis in response to central or peripheral stimuli.

Keywords: Cortisol, Saliva, Pleiotropic role, Adaptive response, Environmental stimuli

Cortisol is a glucocorticoid (GC) that is often used to evaluate the activity of the hypothalamic-pituitary-adrenal (HPA) axis and the adaptive response of the body at a central level, in reaction to environmental stimuli to the nervous system, and peripherally, in reaction to metabolic variations, trauma or immune system responses of various tissues and organs. Besides being secreted by the HPA axis, in some cases, the secretion of GC can also be stimulated by higher brain centres, both in normal conditions (sleep-wake cycle in humans) and in unfavourable circumstances (fear, anxiety, pain, cold, etc.), thus promoting the recovery of homeostasis (Swenson and Reece, 2002; Poli, 2006).

2.2_THE PLEIOTROPIC ROLE OF CORTISOL

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(ACTH) stimulates the release of cortisol which, once in the circulation, has a half-life that varies between 70 and 120 minutes in humans (Sjaastad et al., 2003; Wiebke and Stewart, 2005).

The main metabolic effects of cortisol are gluconeogenesis in the liver, deposition of fat, and regulation in the brain of the hypothalamic neuropeptides involved in appetite control. Furthermore, in these tissues, cortisol can be locally inactivated to cortisone through the action of isoforms 1 and 2 of 11β-hydroxysteroid dehydrogenase or regenerated starting from the same hormone, thereby bypassing secretion of the hormone by the adrenal glands (Harno and White, 2010).

In circumstances of acute stress (“fight or flight”) high concentrations of cortisol increase the release of glucose into the blood and the feeling of hunger, thus facilitating the response to the stress itself. In adipose tissue, on the other hand, cortisol has an anabolic effect that can potentially promote the deposition of new tissue in metabolically disadvantaged areas. This feature has made cortisol a focus of attention in the strive for better understanding of the endocrine mechanisms related to obesity (Harno and White, 2010).

The pleiotropic effects of cortisol are fundamental for the adaptive response of the body and strict regulation, through negative feedback on the HPA axis, avoids overexposure of target tissues, thus preventing the typical negative effects of cortisol, such as glucose intolerance, immunosuppression, increased blood pressure, osteoporosis, insulin resistance, altered growth and tissue repair and even Cushing’s syndrome (Harno and White, 2010).

At a cellular level, the effects of cortisol are mediated by activation of GC receptors (GR), of which there are five different isoforms with specific functions, not yet completely understood, but

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Figure 2.1_ Genomic and non-genomic mechanisms of GC signal transduction (modified from Ratman et al., 2013).

mGR: membrane glucocorticoid receptor; GR: glucocorticoid receptor; GC: glucocorticoid; GRE: glucocorticoid

response element; TF: transcription factor.

As far as concerns non-genomic control, GC have an activating/deactivating role in the cytosol by interacting with the cell membranes in a GR-independent manner, acting directly on protein kinases (MAPKs) or by binding to membrane GR, which can lead to rapid activation of anti-inflammatory signals (Song and Buttgereit, 2006; Lowenberg et al., 2007). Furthermore, at a central level, GR, together with receptors for mineralocorticoids, play a critical role in coordinating a rapid adaptive response to stress, with the involvement of pre-receptors that are still under investigation (Strehl et al., 2011; Groeneweg et al., 2012).

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2.3_ASSAYING CORTISOL IN BIOLOGICAL MATRICES

Cortisol is involved in various metabolic, immune and nervous system processes and variations in its levels therefore reflect the adaptive response to the environment in the broadest sense of the term, taking into account all the actions in which this hormone is involved. The cortisol assay is a method that, together with other diagnostic information, has the advantage of providing the most objective and complete evaluation of an organism’s biological response, thus enabling data collected in different contexts to be compared with reference values.

2.3.1_Sampling

Cortisol can be assayed in various biological matrices including blood, saliva, urine and hair. The potential applications of cortisol assays have stimulated research into non-invasive methods of sampling that do not affect the secretion of the hormone, but that accurately reflect the activation of the HPA axis (Beerda et al., 1999b).Blood was one of the first reference substrates in which cortisol concentrations were evaluated to make a diagnosis of behavioural problems or diseases and, subsequently, to determine the efficacy of treatments. A blood sample provides a snapshot of cortisol levels. The secretion of cortisol is very sensitive to both internal and external stimuli, with these latter including handling during sample collection. Indeed, manipulation for more than 2 minutes can cause significant changes in blood cortisol concentrationswith the risk of artefacts when evaluating activation of the HPA axis (Kobelt et al., 2003; Hiby et al., 2006; Accorsi et al., 2007; Bennet and Hayssen, 2010).