Author’s Accepted Manuscript Thermotolerance, health profile and cellular expression of HSP90AB1 in Nguni and Boran cows raised on natural pastures under tropical conditions C.L.F. Katiyatiya, G. Bradley, V. Muchenje www.elsevier.com/locate/jtherbio
PII: DOI: Reference:
S0306-4565(17)30084-0 http://dx.doi.org/10.1016/j.jtherbio.2017.06.009 TB1949
To appear in: Journal of Thermal Biology Received date: 3 March 2017 Revised date: 8 June 2017 Accepted date: 25 June 2017 Cite this article as: C.L.F. Katiyatiya, G. Bradley and V. Muchenje, Thermotolerance, health profile and cellular expression of HSP90AB1 in Nguni and Boran cows raised on natural pastures under tropical conditions, Journal of Thermal Biology, http://dx.doi.org/10.1016/j.jtherbio.2017.06.009 This is a PDF file of an unedited manuscript that has been accepted for publication. As a service to our customers we are providing this early version of the manuscript. The manuscript will undergo copyediting, typesetting, and review of the resulting galley proof before it is published in its final citable form. Please note that during the production process errors may be discovered which could affect the content, and all legal disclaimers that apply to the journal pertain.
Thermotolerance, health profile and cellular expression of HSP90AB1 in Nguni and Boran cows raised on natural pastures under tropical conditions C.L.F Katiyatiyaa, G. Bradleyb, V. Muchenjea,* a
Department of Livestock and Pasture Science, University of Fort Hare, Private Bag X1314, Alice 5700,
Republic of South Africa b
Department of Biochemistry and Microbiology, University of Fort Hare, Private Bag X1314, Alice 5700,
Republic of South Africa
[email protected] [email protected] *
Corresponding author: Tel: +27 40 602 2059; Fax: +27 86 628 2967
Abstract
Boran (n = 15) and Nguni (n = 15) cows were used in a study to determine the effect of breed, age and coat colour on the concentration of heat shock protein 90 (HSP90AB1), physiological rectal and skin temperature, and markers of health. The cows were exposed to summer heat stress and Boran cows had higher significant (P<0.05) skin temperature (35.1±0.42 ˚C) as compared to the Nguni cows (36.0±0.38 ˚C). Nguni cows had higher body thermal gradients than the Boran cows. Boran cows had thicker skin (P<0.05) and longer hairs (24.3±2.26 mm) than their Nguni counterparts (20.2±2.00 mm). The HSP90AB1 concentration was increased in Boran cows, although breed had no significant (P>0.05) influence. Significantly (P<0.05) high urea and total cholesterol was recorded in Boran cows. Coat colour had a significant (P<0.05) effect on the weight and rectal temperature of the study animals. Coat colour and age had no significant effect (P>0.05) on the concentration of HSP90AB1, although older cows ( 9 years) had higher concentrations (5.4±1.29 ng/ml). Age had a significant (P<0.05) effect on packed cell volume, neutrophil/lymphocyte, urea, total protein and gamma-glutamyl transferase whereas cows with 9 years had more concentrations than young ones. Age significantly (P<0.05) influenced hair length, skin 1
temperature and the thermal gradients. Breed was positively correlated (P<0.001) to coat colour, age, body condition score, weight and temperature humidity index while negatively correlated to urea and total cholesterol. It was concluded that Nguni cows were more adaptable to hot environments than the Boran cows as the latter were unable to balance thermal load between their bodies and the environment. Keywords: hair length, thermal gradient, coat colour, breed, skin temperature, rectal temperature, protein concentration.
1. Introduction Tropical and arid areas are characterized by environmental conditions typified by intense radiation and high temperatures and humidity that negatively impact on thermoregulation (Mishra and Palai, 2014; Shibata et al., 2014). Heat stress may induce hyperthermia and negatively affect feed intake, fertility, conception rate, milk production, health and growth of animals (Roth et al., 2002; Deb et al., 2015; Strong et al., 2015). Under heat stressful conditions, animals seek shade, drink more water, change postures and/or reduce feed intake in order to maintain core body temperature (Shilja et al., 2016; Akbarian et al., 2016). Heat stress is a major concern around the world for farmers as they incur costs trying to modify their farms to relieve cattle from heat stress (Srikanth et al., 2017). Climate change and global warming contribute to heat stress which then affects animals resulting in economic losses to the livestock industry (Roth et al., 2002; Srikanth et al., 2017). According to Baumgard and Rhoads (2013), the global livestock sector loses more than $1.2 billion due to heat stress. It is therefore important to use tropically adapted breeds which can survive under hot conditions hence reducing economic losses (Scholtz et al., 2013; Deb et al., 2015). Tropical breeds such as the Nguni and Boran are known to have adapted to local
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environments having the capability of maintaining homeostasis under high environmental temperature as compared to temperate breeds (Deb et al., 2015; Srikanth et al., 2017). The Nguni breed is a multi-coloured indigenous Sanga type which performs well under harsh hot and tropical environmental conditions; a characteristic acquired through natural selection over the years (Collins-Luswet, 2000; Strydom et al., 2008; Mwai et al., 2015). It possesses low maintenance requirements, excellent walking and foraging ability, tick and tick borne disease resilience, heat resistance and excellent reproductive performance (Muchenje et al., 2008; Marufu et al., 2010, 2011a; Katiyatiya et al., 2014, 2015). According to Rewe et al. (2011) the Boran is another indigenous genetic resource said to be of robust nature. The characteristics of the Boran cattle include an ability to withstand periodic shortage of water and feed, walk long distances, digestion of low quality feeds, drought resistance, and excellent mothering ability and herd instinct, docility, disease resistance and heat tolerance (Haile-Mariam et al., 1993; Sprinkle et al., 1998; Boran Cattle Breeders Society (BCBS), 2016). Environmental stressors have been reported to affect the fertility and growth of the Boran (Wasike et al., 2006). However, the Boran and Nguni cattle have small body sizes which allow them to be more adaptable under tropically stressful environmental conditions (Haile-Mariam and Kassa-Mersha, 1994; Collins-Luswet, 2000). There is need therefore, to increase the efficient production of these breeds regardless of stressful conditions (BCBS, 2016). Thermotolerance tends to vary with animal species, among and within breeds (Renaudeau et al., 2012). However, coat characteristics such as skin thickness and coat colour influence the individual animal’s thermotolerance capabilities (Mattioli et al., 2000). Interestingly, coat colour is perceived to have played a significant role in animal selection before farmers could use objective measurements (Andersson and Georges, 2004). It holds cultural connotations, and hides with colours have different economic values (Scholtz, 2010; Makina et al., 2015;
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Chikwanda, 2016). However, it plays a significant role in animals when heat stress response is activated by extreme environmental temperatures leading to the modulation of differential gene expression and protein activation (Kregel, 2002; Min et al., 2015). Under hot environmental conditions, the expression of heat shock proteins (HSPs) increases, and heat shock transcription factors (HSF) are activated as heat stress response mechanisms (Pirkkala et al., 2001; Page et al., 2006; Collier et al., 2008; Basirico et al., 2011). Heat shock proteins are highly conserved, ubiquitous chaperone proteins whose release in eukaryotes and prokaryotes is induced by cellular stress and elevated temperature (Basu et al., 2002, Ross et al., 2003). In eukaryotes, HSP are grouped according to molecular mass and weight into families such as HSP60, HSP70 and HSP90 (Basu et al., 2002; Luan et al., 2009). The elevation of the expression of heat shock genes and chaperones under heat stress facilitates cell survival which prevents aggregation and misfolding of proteins (Srikanth et al., 2017). This further triggers the activation of the immune system and leads to the expression of tumor suppressors, cycle arrestors and genes involved in apoptotic processes to prevent tumorigenesis. Previous studies have shown that among the HSPs, HSP90 plays a crucial role in cellular thermotolerance (Marcos-Carcavilla et al., 2010; Pu et al., 2016). Heat shock proteins are possible biomarkers of animal adaptation to severe environmental stress and are associated with resistance to stress (Feder and Hofmann, 1999; Hansen, 2004). The severity of heat stress in animals globally is currently being established through HSP expression profiling of blood among other ways (Gade et al., 2010; Gaughan et al., 2013). However, there is paucity of information on the expression of HSP90AB1 in the Nguni and Boran cows during heat stress. Therefore, the aim of this study was to determine the effects of breed, age and coat colour on the concentration of HSP90AB1, physiological parameters and some blood markers of health.
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2. Materials and methods 2.1. Ethical consideration The study was conducted in accordance to the guidelines of the Research Ethics Committee of the University of Fort Hare, South Africa (MUC171SKAT01). 2.2. Location and animal management Fifteen Nguni and 15 Boran cows from Honeydale and Edendale farms respectively, were used in the study. These farms fall in the False Thornveld veld and their vegetation comprises of Vachellia karoo, Themeda triandra, Panicum maximum, Cynodon dactylon, Digitaria eriantha, Eragrostis spp. and Pennisetum clandestinum. They are geographically located on 32˚ 47’ S, 26˚ 38’ 00” E and 32˚ 46’ S, 26˚ 52’ E (Edendale and Honeydale, respectively), receive 480-490 mm annual rainfall and have a mean temperature of 18.3-18.7 ˚C. The study animals were separated into three age groups: 3-5 years, 6-8 years and 9 years with each group having 11, 13 and 6 cows, respectively. The cows were also divided into 7 different colour patterns: black (n = 4), red (n = 5), white-brown (n = 5), white-red (n = 4), fawn (n = 4), white (n = 4), and white-black (n = 4). The study was conducted during the summer season and ear tagging was done for easy identification of each cow. Rotational grazing of the cows on the natural grasslands was practised. Both breeds used in the study are stud animals which were kept on separate farms under similar management practises.
2.3. Meteorological parameters, rectal and skin temperature and thermal gradient A portable data logger (Model: MT669, Major Tech, South Africa) was used to record ambient temperature and relative humidity of the study sites. The data for wet (Tw) and dry (Td) temperatures was collected using wet and dry bulb thermometer between 0900 h and 1200 h. The wet and dry temperatures were used to calculate THI using the formula below: THI = 0.72 (Tw + Td) + 40.6 (World Meteorological Organisation, 1989). 5
Rectal and skin temperatures were recorded before blood sampling between 0900 h and 1200 h. Skin temperatures on the neck, belly and thurl regions were measured using an infrared thermometer (Nubee NUB8380 Temperature Gun, California, USA). The thermometer was held at a 15 cm distance away from the animal without contacting it (Scharf et al., 2012). The average skin temperature of each cow in the current study was calculated by averaging the temperature on the neck, belly and thurl region. A digital thermometer (Kruuse Digi-Vet SC 12, Denmark) was used to measure rectal temperature in the rectum of each cow for 60 seconds. Body thermal gradients were calculated according to Richards (1973) using the formulas below: Internal gradient = Rectal temperature - skin temperature; External gradient = Rectal temperature- ambient temperature; Total thermal gradient = Skin temperature - ambient temperature.
2.4. Blood sampling, storage and analysis Blood samples were collected from the jugular vein of each cow into EDTA-coated and heparinized vacutainer tubes with BD hemogardTM to ease plasma separation (Chulayo et al., 2016). The EDTA-coated vacutainer tubes were used to collect blood for biochemical tests. Blood samples in heparinized tubes were centrifuged for 10 minutes at 3500 rpm using a Model 5403 centrifuge (Geratebay Eppendorf GmbH, Engelsdorp, Germany). Thereafter, the centrifuged samples were stored at -20˚C until analysis was conducted. The obtained plasma samples were analysed using a Checks machine (Next/Vetex Alfa Wasseman Analyser) and commercially purchased kits (Siemens). Total protein, creatinine, alkaline phosphate and gamma-glutamyl transferase were spectrophotometrically analysed using colorimetric procedures. Glucose, total cholesterol and urea were analysed using enzymatic methods while aspartate transaminase and alanine transaminase were determined using ultraviolet
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techniques. A Model DXC 600 machine (Beckman Coulter, Ireland) was used to analyse blood samples in EDTA-coated tubes for concentrations of packed cell volume and neutrophil/lymphocyte.
2.5. Expression of heat shock protein (HSP90AB1) A sandwich commercial enzyme-linked immunosorbent assay (ELISA) kit was used to assess the concentrations of HSP90AB1 in blood plasma according to the manufacturer’s instructions. Upon receipt of the ELISA kit, the reagents (× 2), standard and the 96-well plate reader inside it were kept under -20 ˚C while the TMB substrate, wash buffer and stop solution were stored at 4 ˚C. Afterwards, the reagents (× 2), standard, plate reader and thawed samples in heparinized tubes (Section 2.3) were brought to room temperature (18-25 ˚C) without additional heating on the day of the experiment. Analysis of all the samples and standards was conducted in duplicate. The performance ranges of HSP90AB1 for intra- and inter assay coefficient of precision were <10% and <12%, respectively while the detection range was 0.156 ng/ml to 10 ng/ml. The HRP-avidin (Horseradish peroxidase) and the standard biotin antibody were prepared as per instructions provided by the assay manufacturers. The samples and the standards were pipetted into the immobilised antibodycoated wells of the strip plate and incubated for 2 hours to allow any present HSP90AB1 to be bound by the antibody. Incubation was conducted at 37 ˚C throughout the experiment. The liquid of each well was then aspirated and a biotin-conjugated specific for HSP90AB1 added into the wells. An incubation period of 1 hour was allowed. Thereafter, the liquid of each well was aspirated and the wells washed 3 times using a Wash Buffer. Each wash was allowed to sit for 1-2 minutes before complete aspiration. After the last wash and aspiration, the plate was inverted and taped against a clean absorbent paper. Avidin-conjugated HRP was then added to each well and incubated for 1 hour. This was followed by the aspiration of
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liquid in each well and washing (5 times) to remove any unbound avidin-enzyme reagent. A TMB substrate was then added to each well and incubation was conducted for 20 minutes until optimum development of a blue colour which corresponded with the concentration of HSP90AB1 in each well. This was followed by the addition of a stop solution to each well to halt colour development and the blue colour changed to yellow. The optical density of each well was then determined using a microplate reader (SynergyMx BioTek, model SN 236255, Winooski, VT, USA) set to 450nm. The concentrations of HSP90AB1 in the wells (samples) were calculated from the standard curve that was obtained from each ELISA plate.
2.6. Statistical analysis The Generalized Linear Model procedures of SAS (2003) were used to analyse data on breed,
age,
coat
colour,
hair
length,
skin
temperature,
rectal
temperature,
neutrophil/lymphocyte, packed cell volume, skin thickness, body condition score, body weight, HSP90AB1 and thermal gradients measured in the study. The following model was used: Yijklm = µ + Ai + Bj + Ck + ɛ
ijkl,
where Yijkl = response variables (skin temperature, rectal temperature, HSP90AB1, body weight, body condition score, thermal gradients) µ = overall mean; Ai = effect of age (i = 3-5, 6-8 and 9 years); Bj = effect of breed (i = Nguni, Boran); Ck = effect of coat colour (i = black, red, white and brown, white and red, fawn, white, white and black); and, ɛ
ijkl
= random error.
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The separation of means (P<0.05) was done using Fisher’s Least Significant Difference (LSD) method. Pearson’s correlations among the measured variables were determined. Relationships among measured variables were determined using XLSTAT 2016.
3. Results 3.1. Effect of breed, age and coat colour on the body weight and body condition score Table 1 shows the effect of breed, age and coat colour on the weight and body condition of the Nguni and Boran cows. Coat colour had a significant (P<0.05) effect on the body weight of the cows. Red coloured cows had the highest weight (479.05±17.120 kg) while black cows recorded the lowest (370.97±15.593 kg). Nguni cows had significantly (P<0.05) higher body condition scores than their Boran counter parts (3.01±0.113, 3.37±0.106, respectively).
3.2. Effect of breed on the rectal and skin temperatures and body thermal gradients Breed had a significant (P<0.05) effect on the skin temperature of the cows in the study (Fig. 1). Boran cows had higher skin temperature (35.1±0.42 ˚C) as compared to the Nguni cows (36.0±0.38˚C). Nguni cows had higher significant (P<0.05) body thermal gradients than the Boran cows as shown in Fig. 2.
3.3. Effect of breed on skin thickness and hair length Boran cows had significantly thicker skins (P<0.05) as compared to their Nguni counterparts (Fig. 3). Results on Fig. 4 show that Boran cows had longer hairs (24.3±2.26 mm) than Nguni cows (20.2±2.00 mm) at P<0.05.
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3.4. Effect of breed on HSP90AB1 concentration and markers of health Boran cows had higher, but non-significant (P>0.05) serum HSP90AB1 concentration (Fig. 5). Breed significantly affected serum urea and total cholesterol concentration with Boran cows having 4.6±0.25 mmol/L and 5.5±0.69 mmol/L, respectively than their Nguni counterparts (Table 2).
3.5. Effect of age on HSP90AB1 concentration and markers of health Results on Fig. 6 show that age had no significant (P>0.05) effect on the concentration of HSP90AB1, although older cows ( 9 years) had higher concentrations (5.4±1.29 ng/ml). Age had a significant (P<0.05) effect on packed cell volume, neutrophil/lymphocyte ratio, urea, total protein and gamma-glutamyl transferase and cows with 9 years had more concentrations than the young ones (Table 3).
3.6. Effect of age on hair length, skin thickness, skin and rectal temperature, and thermal gradients of Nguni and Boran cows Age of the cows had a significant (P<0.05) effect on the hair length, skin temperature and thermal gradients (Table 4). Cows in the age group of 6-8 years had longer hairs (25.42±2.087) while the ones with 3-5 years had the shortest hairs (18.55±2.182). Younger cows had higher skin temperatures than the older ones. The rectal and skin temperature gradient was higher in older cows (≥9 years) while the skin temperature and ambient thermal gradient was lowest in the older cows.
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3.7 Effect of coat colour on hair length, skin thickness, rectal and skin temperatures and thermal gradients Coat colour had a significant (P<0.05) effect on the rectal temperature of the study animals (Table 5). White-red cows had higher rectal temperature (39.02±0.330 ˚C) while fawn cows recorded the lowest (35.55±0.434 ˚C). White-brown cows had non-significant (P>0.05) longer hairs (26.92±2.956 mm) and thicker skins (14.78±2.450 mm). Coat colour had a significant effect of the thermal gradients as shown in Fig. 7. Fawn cows had lower internal and total thermal gradients (2.23±1.187 ˚C, 5.04±0.462 ˚C, respectively) as compared to the black, red, white-brown, white-red, white, and white-black coloured cows.
3.8. Effect of coat colour on HSP90AB1 concentration and markers of health Coat colour had no significant effect (P>0.05) on the concentration of HSP90AB1 in the Nguni and Boran cows (Fig. 8). However, fawn and black cows had elevated concentrations of HSP90AB1. Red and white-red cows showed significant (P<0.05) association with the markers of health (Table 6).
3.9. Relationship between breed, age, body weight, body condition score, coat colour, hair length, THI, HSP90AB1 concentration and markers of health The relationship between HSP90AB1 concentration and animal characteristics is shown in Fig 9. Principal component (PC) 1 had 40.0% and represented hair length, rectal temperature, body weight, thermal gradients, body condition score and neutrophil/lymphocyte ratio. These were negatively correlated with skin temperature, skin thickness, HSP90AB1 concentration and packed cell volume. However, HSP90AB1 concentration was positively correlated to skin thickness, packed cell volume and packed cell volume as represented by PC 1 (11.57%).
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4. Discussion High environmental temperature, humidity and wind affect animal production and reproduction. As a result, there is a need for the implementation of sound management practices to reduce economic losses and protect animals from heat stress (Srikanth et al., 2017). Previously, increase in cattle weight has been attributed to compensatory growth under mild heat stress conditions (Alfredo et al., 2008). However, weight loss in animals is usually slower than the decrease in their body conditions (Fourie et al., 2013). In the current study, breed had no effect on the body weight of the Nguni and Boran cows, but coat colour influenced the latter. This is in contrast with the findings of Decampos et al. (2013) in sheep. Lighter coloured cows in the current study had more weight and this concurs with a study by Finch et al. (1984) where coat colour had significant effects on growth as light animals gained more weight than dark ones. The observation that Boran cows had higher skin temperature than their Nguni counterparts could be associated with individual animal responses to heat stress (Srikanth et al., 2017). This indicates that Boran cows were unable to balance thermal load as compared to Nguni cows. Furthermore, rectal temperature differences in the current study suggest that Boran cows had lower heat tolerance capability than Nguni cows (Pereira et al., 2008). Charoensook et al. (2012) also reported breed-specific thermophysiological responses to heat stress. Boran cows experienced THI above the threshold values which exposed them to moderate stress and probably gained more heat from the environment. This is in line with reports by Richards (1973) who highlighted that when body thermal gradients (internal and external) are under the thermo-neutral zone (TNZ) heat is dissipated to the environment. The author further reported that when animals are subjected to heat stress, heat flows from the external environment to the body of the animal. In the current study, the body thermal gradients of the
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Boran cows were lower than the ones for the Nguni cows. This indicated that Boran cows constricted the thermal gradients between their bodies and the environment (Babor et al., 2014; Soerensen and Pedersen, 2015). This was likely due to the increased skin temperature of the Boran as a result of high environmental thermal load and elevated vasodilation of the skin capillaries which channelled blood flow to their skin surface (McManus et al., 2009; Schultz et al., 2011; Babor et al., 2014; Soerensen and Pedersen, 2015). This is also in agreement with the findings of Samara et al. (2012) and Al-Haidary et al. (2013). Boran cows had higher skin thickness than the Nguni cows and this significant breed difference concurs with reports by Veríssimo et al. (2002), Cardoso et al. (2015) and Chikwanda (2016). However, findings by Brown et al. (2000) indicated that the subcutaneous fat amount and the respective measured site influence skin thickness. Contrasting reports by Spicket et al. (1989) and Marufu et al. (2011b) highlighted non-significant breed differences in skin thickness. Nguni cows in the current study had shorter hairs than the Boran cows. This indicates that the Nguni is more adaptable to thermal environments as supported by CollinsLusweti (2000); Bernabucci et al. (2010) and Das et al. (2016). In other studies by Bertiplagia et al. (2015) and Katiyatiya et al. (2015) short hairs were associated with protection of animals from solar radiation and these tend to vary seasonally. However, age, seasonal, genetic and nutritional factors can influence hair length differences in animals (LandaetaHernández et al., 2011). The current study showed that breed did not have an effect on the concentration of HSP90AB1. This could be because the Nguni and Boran both have Bos indicus characteristics. This is in agreement with Chen et al. (2009), Chan et al. (2010) and Makina et al. (2015) who highlighted that HSP express themselves differently between taurine and indicine cattle. Deb et al. (2014) reported differences in HSP90 expression between Bos indicus and Bos indicus × Bos taurus cattle breeds. However, Charoensook et al. (2012) and
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Rosse et al. (2017) highlighted that HSP90AB1 contains allele T which improves heat tolerance, and its frequency is high in indicine than in taurine cattle breeds. Nguni cows in the study had lower urea concentration than the Boran. These findings can be attributed to possible reduced quantity and quality of the pastures as reported by Mapfumo and Muchenje (2015). Supportingly, Mapiye et al. (2010a) indicated that lower urea concentration in the Nguni implied that the breed was highly adaptable to reduced protein diets and could utilise efficiently amino acids for growth and animal development. Considering that the current study was conducted in the summer season, the higher urea concentration in the Boran could have been due to dehydration (Scharf et al., 2010) or protein catabolism for body metabolism maintenance (Chaudhary et al., 2015). This usually occurs under energy restriction periods resulting in elevated concentrations of urea in blood (Damptey et al., 2014). Total cholesterol was higher in the Boran than the Nguni cows and this suggests that Boran cows had more reserves for energy than the Nguni (Ndlovu et al., 2009a). On the other hand, the lower cholesterol concentration in the Nguni indicated the breed’s low demand for energy (Ndlovu et al., 2009b; Mapiye et al., 2010b) and was possibly associated with the breed’s physiological adaptation when searching for feed (Otto et al., 2000; Nazi et al., 2003). This concurs with Gudev et al. (2007), Pandey et al. (2012) and Singh et al. (2016) who reported reduced cholesterol in summer under heat stress conditions and this was attributed to decreased thyroid activity and feed intake reduction hence decreased dietary cholesterol intake. Age had no effect on the concentration of HSP90AB1, however, the concentration of the HSP increased with age. This is in agreement with Dangi et al. (2012) who did not find statistical significance of HSP90 concentrations within age groups although seasonal variations were observed. Concentrations of packed cell volume, neutrophil/lymphocyte, urea, total protein and gamma-glutamyl transferase increased with age. These findings
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contrast with Satue et al. (2009) and Katiyatiya et al. (2015) who reported decreased concentrations of haematological variables with age due to reduced activity of the bone marrow. The increase of total protein with age has been previously reported in domestic animals (Kaneko, 1997; Kitagaki et al., 2005). Contrasting findings to the current study on the effect of age on urea concentration were reported by Mapiye et al. (2010a). A similar increase in neutrophil/lymphocyte ratio with age was observed by Satue et al. (2009) in Carthusian brood mares and it was associated with predisposition to subtle infection and this indicated reduced cell regeneration (Fermaglich and Horohov, 2002) in older animals. However, in the present study, hair length increased with age, although older animals had shorter hairs. This is in agreement with the findings of Udo (1978), Maia et al. (2005) and Landaeta-Hernández et al. (2011). The observation that coat colour had a significant influence on rectal temperature is in line with the findings of Magona et al. (2009) and Fadare et al. (2012). The authors found higher rectal temperature in black sheep and associated it with solar radiation absorption by the dark pigment while light pigmented animals reflected more and absorbed less solar radiation. Concurring reports by Da Silva et al. (2003) and Hansen (2004) highlighted that lightcoloured animals with sleek and shiny hair coats reflected more solar radiation than darkcoloured animals. Coat colour did not influence skin thickness and hair lengths of the Nguni and Boran cows in the current study, although light coloured cows had longer hairs which possibly enhanced their heat tolerance capability as indicated by Maia et al. (2005) and Katiyatiya et al. (2015). Fawn-coloured cows showed lower internal and total gradients, although thermal gradient was not significantly affected by coat colour. This could have been attributed to their rectal temperature and skin temperature as blood flow to the skin surfaces could have increased together with body heat dissipation (Samara et al., 2012). Coat colour had no significant influence on the concentration of HSP90AB1, however fawn and black
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coloured cows had a higher concentration. These findings could be associated with the observation that dark colours absorb more heat making the respective animals to be more susceptible to heat stress hence the increase in HSP concentration. The close association of THI and thermal gradients concurs with reports by Renaudeau et al. (2012) who indicated that thermal gradients between the animals’ surface area and its surrounding environment determine heat loss through radiation, conduction, evaporation and convection. The positive correlation of HSP90AB1 concentration and other measured parameters are in line with Charoensook et al. (2012) who highlighted this gene is a good heat tolerance biomarker so it can be used in animal selection for tropical environments.
5. Conclusion Breed, age and coat colour had no influence on the protein concentration of HSP90AB1. Fawn and lack coloured cows had a higher concentration of HSP90AB1. Coat colour influenced the weight of the Nguni and Boran cows as lighter coloured cows in the current study had more weight. Fawn-coloured cows had lower internal and total thermal gradients. Boran cows had higher skin temperature and skin thickness as well as lower body thermal gradients than their Nguni counterparts. Coat colour influenced rectal temperature and light coloured cows had the long hairs. Nguni cows had shorter hairs, lower urea and total cholesterol than the Boran cows. The study showed that Nguni cows are more adaptable to hot environments than the Boran cows as the latter were unable to balance thermal load between their bodies and the environment. However, there is need for further research to be done comparing monthly and seasonal variations of concentration of HSP90AB1 and thermotolerance in the Nguni and Boran cows.
Conflict of interest
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The authors declare that they have no conflict of interest.
Acknowledgements This study was funded by the National Research Foundation’s Project 700 and the National Research Foundation-Research and Technology Fund (150329116339 and 150522118247). The authors are grateful to the National Research Foundation for providing a doctoral scholarship to C.L.F. Katiyatiya. The authors also express gratitude to Edendale and Honeydale farms for the study animals and necessary facilities.
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Rectal Temperature
Temperature (˚C)
40
Skin Temperature
a
a a
35
b
30
25
20
15 Boran
Nguni Breed
Fig. 1. Effect of breed on skin and rectal temperature variations of Nguni and Boran cows. ab means with different superscripts are significant at P<0.05.
12
(A) a
Tr - Tsk (˚C)
10 8 b 6 4 2 0
30
Tsk - Ta (˚C)
8
(B) a
6 4 2 0 -2
b
14
a
Tr - Ta (˚C)
12 10 8 6 4
b
2 0 Boran
Nguni Breed
Fig. 2. Least square means (± standard errors) for body thermal gradients of Nguni and Boran cows during the summer season. ab means with different superscripts are significant at P<0.05. A – TrTsk (rectal temperature-skin temperature gradient), B – TskTa (skin temperature-ambient temperature gradient), TrTa (rectal temperature-ambient temperature).
31
16
a 14
Skin thickness (mm)
12
b 10 8 6 4 2 0 Boran
Nguni Breed
Fig. 3. Breed effects on skin thickness of Nguni and Boran cows. superscripts are significant at P<0.05.
32
ab
means with different
30 a 25 b Hair length (mm)
20 15 10 5
0 Boran
Nguni Breed
Fig. 4. Influence of breed on hair length of Nguni and Boran cows. ab means with different
superscripts are significant at P<0.05.
33
7 a HSPAB1 expression (ng/ml)
6 a
5 4 3 2 1 0 Boran
Nguni Breed
Fig. 5. Breed effect on the concentration of HSP90AB1 profile in Nguni and Boran cows. a means
with similar superscripts are not significant at P>0.05.
34
8
Expression of HSP90AB1 (ng/ml)
7
a 6
a
a 5 4 3 2 1 0 3.5
6-8
>9
Age group (years) Fig.6. Concentration of HSP90AB1 in Nguni and Boran cows of different age groups. a means with
similar superscripts are not significant at P>0.05.
Thermal gradient (˚C)
TrTsk 10 9 8 7 6 5 4 3 2 1 0
a
a
TrTa
a
a
a
a
a
a a
a
a a
TskTa
a b
a a
a
a
b b
Coat colour 35
a
Fig. 7. Relationship between coat colour and thermal gradients of Nguni and Boran cows. ab means with different superscripts within the same thermal gradient are significant at P<0.05. TrTsk (rectal to skin thermal gradient), TskTa (skin to ambient thermal gradient), TrTa (rectal to ambient gradient).
10
Expresion of HSP90AB1 (ng/ml)
9
a
8 7
a
6
a
5
a
a
a
a
4 3 2 1 0 Black
Red
White-brown White-red
Fawn
White
White-black
Coat colour Fig. 8. Concentration of HSP90AB1 in differently coloured Nguni and Boran cows. a means with
similar superscripts are not significant at P>0.05.
36
Biplot 5 PCV
4
Component 2 (11.57 %)
3
HSP90AB1
2
1 1 1
1 0
1 1
1 11 11 1 Tsk 1 1
-1
Age BCS 2 22 TrTsk 2 2 THI TrTa
ST
1
TskTa
CC
2 Weight 22 2 2 2 2
Tr
-2 1 -3
2
N/L 2 2
HairL
-4 -5
-4
-3
-2
-1 0 1 2 3 Component 1 (40.00 %)
4
5
6
7
Fig. 9. Biplot showing the relationship between HSP90AB1 expression, skin temperature, skin thickness, packed cell volume, neutrophil/lymphocyte ratio, body condition score, weight, age, coat colour, rectal temperature, hair length, THI and thermal gradients. 1 – Boran, 2 – Nguni, HSP90AB1 – heat shock protein 90 AB1, THI – temperature humidity index, Tsk – skin temperature, ST - skin thickness, PCV – packed cell volume, N/L – neutrophil/lymphocyte ratio, BCS – body condition score, CC – coat colour, TrTsk – rectal temperature-skin temperature gradient, TrTa – rectal temperatureambient temperature gradient, TskTa – skin temperature-ambient temperature gradient
Table 1 Effect of breed, age and coat colour on the weight and body condition of Nguni and Boran cows.
Parameter Breed
Body condition score
Weight (kg)
Boran
3.01b±0.113
424.40a±15.881
Nguni
3.37a±0.106
451.93a±13.684
37
Age group (years)
Coat colour
abcd
3-5
3.17a±0.10
420.37a±14.382
6-8
3.24a±0.10
446.90a±13.752
9
3.11a±0.16
447.21a±21.274
Black
3.17a±0.118
370.97d±15.593
Red
3.23a±0.134
479.05a±17.120
White-brown
3.20a±0.146
453.83b±19.479
White-red
2.91a±0.211
421.18cd±29.771
Fawn
3.24a±0.291
476.82a±39.098
White
3.22a±0.218
438.65c±28.713
White-black
3.20a±0.106
426.63c±13.488
Means in the same column and animal trait differ significantly (P<0.05).
Table 2 Least square means (± standard errors) of the effect of breed on the markers of health in Nguni and Boran cows.
Parameter
Boran
Nguni
Packed cell volume (L/L)
0.39a±0.053
0.17b±0.046
Neutrophil/Lymphocyte
1.30a±0.107
0.54a±0.123
Urea (mmol/L)
4.62a±0.272
1.73b±0.235
38
Creatinine (g/L)
103.75a±12.022
110.35a±10.359
Total protein (g/dL)
87.79a±5.964
73.89a±5.139
Aspartate transaminase (U/L)
71.95a±7.205
70.37a±6.209
Alanine transaminase (U/L)
42.20a±3.725
36.24a±3.210
Alkaline phosphate (U/L)
98.36a±16.827
109.12a±14.500
Gamma-glutamyl transferase (U/L)
20.79a±2.128
15.65a±1.834
Total cholesterol (mmol/L)
5.37a±0.743
2.74b±0.640
ab
Means in the same row with different superscripts are significantly different (P<0.05).
Table 3 Least square means (± standard errors) of the effect of age on blood profiles of Nguni and Boran cows.
Age group (years) Parameter
3-5
6-8
9
Packed cell volume (L/L)
0.21b±0.048
0.20b±0.046
0.43a0.071
Neutrophil/Lymphocyte
0.15b±0.049
0.42b±0.125
2.20a±0.013
Urea (mmol/L)
2.67b±0.246
3.05b±0.236
3.81a±0.365
Creatinine (g/L)
89.53a±10.888
114.05a±10.411
117.58a±16.105
Total protein (g/dL)
66.28b±5.401
84.48a±5.165
91.76a±7.990
Aspartate transaminase (U/L)
61.08a±6.525
74.24a±6.239
78.17a±9.652
39
Alanine transaminase (U/L)
37.81a±3.374
37.84a±3.226
42.01a±4.990
Alkaline phosphate (U/L)
112.69a±15.239
99.34a±14.572
99.18a±22.542
Gamma-glutamyl transferase (U/L)
15.95ab±1.928
15.68b±1.843
23.04a±2.851
Total cholesterol (mmol/L)
4.10a±0.673
3.83a±0.643
4.25a±0.995
ab
Means in the same row with different superscripts are significantly different (P<0.05).
Table 4 Effect of age on coat characteristics and physiological parameters of Nguni and Boran cows.
Age group (years) Parameter
3-5
6-8
9
Hair length (mm)
18.55b±2.182
25.42a±2.087
22.50ab±3.228
Skin thickness (mm)
11.98a±1.657
9.96a±1.585
11.63a±2.452
Skin temperature (˚C)
33.29a±0.404
33.50a±0.386
31.78b±0.598
Rectal temperature (˚C)
38.36a±0.159
38.18a±0.152
38.30a±0.236
TrTsk thermal gradient
5.06ab±0.443
4.68b±0.423
6.70a±0.655
TrTa thermal gradient
8.01a±0.161
7.82a±0.154
7.94a±0.239
TskTa thermal gradient
2.93ab±0.401
3.13a±0.384
1.44b±0.593
ab
Means in the same row with different superscripts are significantly different (P<0.05), Tr -
rectal temperature, Tsk – skin temperature, Ta – ambient temperature.
40
Table 5 Coat colour influence on rectal and skin temperature, hair length and skin thickness Nguni and Boran cows.
Coat colour
Rectal temperature
Skin temperature
Hair length
Skin thickness
(˚C)
(˚C)
(mm)
(mm)
Black
38.71a±0.173
33.13a±0.438
20.65a±2.366
11.14a±1.797
Red
38.52a±0.190
33.12a±0.481
22.93a±2.598
11.65a±1.973
White-brown
38.67a±0.216
32.61a±0.547
26.92a±2.956
14.78a±2.45
White-red
39.02a±0.330
32.03a±0.837
19.28a±4.518
9.96a±3.431
Fawn
35.55b±0.434
33.45a±1.099
19.34a±5.933
11.10a±4.506
White
38.92a±0.318
31.85a±0.807
22.81a±4.357
7.96a±3.309
White-black
38.59a±0.150
32.79a±0.379
23.19a±2.047
11.74a±1.554
ab
Means in the same column with different superscripts are significantly different (P<0.05).
Table 6 Least square means (standard errors) of coat colour influence on the markers of health of Nguni and Boran cows.
Parameter
Black
Red
White-
White-
brown
red
Fawn
White
Whiteblack
Neutrophil/Ly
0.70a±0.
1.08a±0.
0.75a±0.
0.65a±1.
1.08a±1.
0.61a±1. 1.57a±0.
mphocyte
596
654
744
137
494
097
0.33a±0.
0.22a±0.
0.17a±0.
0.38a±0.
0.21a±0. 0.33a±0.
cell 0.31a±0.
Packed
515
volume (L/L)
052
057
065
099
130
096
Urea
3.07a±0.
3.72a±0.
3.00a±0.
3.29a±0.
3.64a±0.
2.49a±0. 3.03a±0.
(mmol/L)
267
293
334
510
670
492
231
Creatinine
96.43a±1
128.68a± 121.55a±
101.73a± 120.13a±
92.70a±
88.16a±
(g/L)
1.804
12.961
22.538
21.736
10.211
71.15a±
72.47a±
Total
protein 78.56a±5
14.746
78.10a±6 79.60a±7
41
29.599
93.21a±1 92.80a±1
045
(g/dL)
.856
.430
.316
1.181
Aspartate
73.30a±7
76.86a±7 67.76a±8
transaminase
.075
.768
10.783
5.066
85.93a±1 67.80a±1
68.30a±
58.17
3.507
13.027
a
Alanine
41.18a±3
38.56a±4 34.05a±4
44.04a±6 41.96a±9
42.34a±
32.39a±
transaminase
.658
.016
.983
6.735
3.164
Alkaline
112.29a±
76.73a±1 109.92a±
121.26a± 136.22a±
86.16a±
83.59a±
phosphate
16.522
8.141
31.545
41.428
30.423
14.292
Gamma-
19.06a±2
10.70b±2 19.00a±2
16.72ab±
24.13a±5
20.37a±
17.60a±
glutamyl
.090
.295
.611
3.990
.240
3.848
1.808
Total
4.37a±0.
4.75a±0.
3.97a±0.
3.95a±1.
3.91a±1.
3.73a±1. 3.70a±0.
cholesterol
729
801
911
392
828
343
.838
4.684
7.739
±6.120
(U/L)
.569
.171
(U/L)
20.640
(U/L)
transferase (U/L)
(mmol/L) ab
Means in the same row with different superscripts differ significantly (P<0.05).
42
631
Highlights Heat tolerance was assessed in Boran and Nguni cows. The expression of HSP90AB1, skin thickness, rectal temperature and skin temperature had higher values in Boran cows as compared to Nguni cows. Breed, age and coat colour did not influence HSP90AB1 concentration. Thermal gradients of the cows were influenced by breed, age and coat colour.
43