Global warming has negatively influenced animal production as well as poultry industry (Nardone et al. 2010). The high ambient temperature may slow growth performance, decrease immunity and reproduction ability of chickens (Rimoldi et al. 2015). Furthermore, heat stress affects meat quality in broilers (Hashizawa et al. 2013). Immediate physiological reactions of animals are crucial to ameliorate the effects of sudden changes in ambient temperature (Slawinska et al. 2016). Generally, chickens have no sweat glands or long and moist tongues to regulate body temperature. Thus, exposure to high environmental temperatures causes severe signs of heat stress (Li et al. 2015). However, different breeds may show various behaviors against heat stress (Felver-Gant et al. 2012). Commercial breeds are more sensitive to stress because high selective programs deteriorate the immune function (Cahaner et al. 1995; Fouad et al. 2016). Indeed, continuous selection for fast growth has decreased resistance to heat stress in rapidly growing strains (Soleimani et al. 2011). High ambient temperature is also involved in oxidative stress as it causes a redox imbalance between pro- and antioxidants (Mujahid et al. 2007) and increases superoxide radicals (Rimoldi et al. 2015). One of the consequences of an increase of these harmful components is misfolding and degrading of intracellular proteins (Slawinska et al. 2016). At molecular level, heat stress induces the production of a group of proteins with different weight called as heat shock proteins that their most important role is to protect cells from toxic effect of the heat, and also several of them function as intracellular chaperones for other proteins (Ganter et al. 2006; Staib et al. 2007; Rimoldi et al. 2015). These chaperones involved in binding and refolding the misfolded proteins and protein translocation (Whitley et al. 1999; Rimoldi et al. 2015). Cell defense mechanism modulates gene transcription in the manner of down or upregulation to keep homeostasis against environmental changes (Lopez-Maury et al. 2008). Recently, high throughput technologies have been developed and assist to identify the expression level of many genes simultaneously (Wang et al. 2015; Lan et al. 2016; Jastrebski et al. 2017). However, qRT-PCR is still necessary to confirm the results of microarray or RNA sequencing (RNA-Seq) techniques. So far, Transcriptomic analysis has been performed to study gene expression changes in different organs of chickens under heat stress. The liver is an organ that plays a variety of vital roles such as energy metabolism, digestion, immune function, glycogenolysis, glycogen synthesis and detoxification. The results of studies revealed that different kinds of genes are regulated in the liver to protect the chickens against heat stress (Li et al. 2011; Coble et al. 2014; Luo et al. 2014; Xie et al. 2014; Lan et al. 2016). Among the genes, those that encode the heat shock proteins (HSPs) are commonly expressed in the chickens exposed to high ambient temperature. These conserved chaperone proteins help to maintain cell homeostasis through refolding the misfolded proteins, preventing aggregation of denatured proteins, participating in protein translocation and protein folding (Kregel, 2002). Previous studies indicated that the expression of HSPs increased in poultry exposed to heat manipulation (Figueiredo et al. 2007; Hwang et al. 2016; Cedraz et al. 2017). To our knowledge, the effect of heat stress on the expression of stress-related genes in the native chickens of Khorasan has not been studied so far. Therefore, the present study was performed to investigate the expression of HSPB1 (HSP20), HSPB9 (HSP25), SERPINH1 (HSP47), HSPA2 (HSP70) and HSP110 (HSPH1) in the liver of Khorasan native chickens under acute heat stress.
MATERIALS AND METHODS
For this experiment, 80 one-day-old chicks were collected from the Khorasan native chicken breeding center. The chicks were kept in a controlled room. The temperature at first was 29 ˚C with a humidity of 50% and gradually decreased until the test day, which was maintained at 25 ˚C and 50% humidity. At the age of 30 days, 30 chicks were transferred to separate rooms with the ability to control temperature and humidity and were accustomed to the new environment for five days (Lan et al. 2016). From day 36 to day 42, the ambient temperature for the thermal stress group gradually increased every day with an increase of 2 ˚C per day and finally was adjusted to 40 ˚C and 50% moisture. During the day before sampling, the temperature was maintained at 40 ˚C for the first 12 hours and 42 ˚C for the second 12 hours. The temperature was constant for the control group at 25 ˚C and 50% humidity. During the maintenance period, two hours of blackout was applied to each group during the day, and access to water and food was ad libitum. The energy and protein content of the diet were constant for both control and treatment groups. The starter diet contained 22.5% crude protein and 3000 kcal of metabolizable energy and the growth diet contained 21% crude protein and 2960 kcal of metabolizable energy. Then, eight chickens from each group were killed through cervical dislocation and their liver was sampled. The liver samples were frozen immediately in the liquid nitrogen and kept at -80°C until the extraction of RNA.
RNA extraction and the control of its quality and quantity
Trizol (SIGMA) was used to extract the total RNA based on the manufacturer protocols. Then, the concentration and quality of RNA were measured using a spectrophotometer (Microplate reader, Epoch, USA) by measuring optical absorption at 230, 260 and 280 nm. In addition, RNA integrity was examined by observing 28s and 18s ribosomal RNA bands on 1.5% agarose gel and staining with GelRedÒ (Figure 1).
RNA reverse transcription
A commercial kit (Thermo Fisher, USA) was used to produce cDNA library from the extracted RNA. Five micrograms of the total RNA were mixed with one microliter of Oligo (dT) primer and kept at 70 ˚C for five minutes. Then, 4 μL of 5X buffer, 3.2 μL of MgCl2, 1 μL of dNTP, and 1 μL of reverse transcriptase were added to the mixture and the volume of the reaction reached to 20 μL with pure water. At first, the annealing was carried out at 25 ˚C for five minutes, then the extension was performed at 42 ˚C for 1 hour and eventually, the enzyme was deactivated at 70 ˚C for 15 minutes. The produced cDNA was stored for the next step at -20 ˚C.
SYBRÒ Green qPCR Master Mix (Thermo Fisher, USA) was used for the reaction of RT-qPCR through ABI 7300 Real Time PCR system.
Figure 1 Quality and quantity of extracted total RNA bands on 1.5% agarose gel
The specific primers which were used are shown in Table 1. Each reaction was carried out in two replications. To determine the reaction efficiency, the standard curve was plotted according to the reaction at different concentrations. The amplification efficiency of each target gene was calculated according to the following formula: E= 10(-1/slope) (Pfaffl, 2001). The negative control for the reactions was also considered. The reaction conditions were as follows: initial denaturation at 95 ˚C for 10 minutes and then 40 cycles with a temperature of 95 ˚C for 30 seconds, annealing at 62 ˚C for 30 seconds and extension at 72 ˚C for 30 seconds. Also, the drawing of the melting curve was performed in accordance with the protocol of the software used in ABI 7300 device. The reaction cycle threshold (Ct) value was corrected for statistical analysis using the following equation (Ciraci et al. 2010; Coble et al. 2014):
40- [(sample mean Ct) + (median GAPDH Ct–mean GAPDH Ct) × (sample gene slope/GAPDH slope)]
The results of RT-qPCR were analyzed using SASÒ software version 9.1 (SAS, 2003). Mean adjusted Ct values of each duplicate of RT-qPCR were used in the analysis. Regarding that there was a treatment group and a control group, the Ct output was converted to 2-CT (Livak and Schmittgen, 2001), and then the means of the control and heat-treated groups were compared by t-test. Also, the expression level of the target genes was compared with 2-DDCT through one-way ANOVA.
The STRING database (www.string-db.org) was used to examine protein-protein interactions in silico. After entering the genes into the database, the data of protein interactions and the ontology of genes were processed. This database basically examines the functional and metabolic pathways of genes by connecting to other databases such as GO and KEGG. The paths with a value of P < 0.05 which were corrected by FDR multi-test method were considered as significant tests.
RESULTS AND DISCUSSION
Prior to analyzing the gene expression, the PCR reaction efficiency was evaluated. The optimum annealing temperature was determined for all primers at 62 ˚C. The slope of the standard curve was between -3.1 and -3.3 with a coefficient of determination (R2) of 98% and the amplification efficiency between 1.99 and 2. The lack of primer dimer and the formation of a specific product was confirmed by a dissociation curve. The expression of the genes in this study ranged from 16 to 30 cycles, according to Cedraz et al. (2017). The average expression of the genes versus the control group is shown in Table 2. HSPB9, HSPA2 and HSP110 upregulated between 5 to 7 fold in the heat treated group compared to the control group. However, the results of the analysis of variance revealed that the expression of HSPA2 and HSP110 increased significantly (Figure 2).
Table 1 The primers sequences for RT-qPCR reaction
Table 2 The average expression of the genes versus the control group (upper) and Network statistics of protein interactions (lower)
Figure 2The comparison of gene expression level under heat stress
The means within the same column with at least one common letter, do not have a significant difference (P>0.05)
Comparing gene expressions between the control and the under thermal stress groups showed that HSPA2 and HSP110 had a significant upregulation in the chickens under heat stress (Figures 3). Furthermore, the expression of HSPB1 and SERPINH1 was not significant between the control and the treatment groups. High temperatures can cause lots of damage to livestock, especially poultry. There are several physiological factors that can reduce the effect of heat on the animal. Increasing ambient temperature increases the expression of the genes associated with homeostases, such as heat shock factors and heat shock proteins, and reduces the expression of the genes which are less essential (De Nadal et al. 2011). Previously, the effect of heat stress on gene expression in laying chickens (Xie et al. 2014), broiler strains (Rimoldi et al. 2015), distinct chicken lines (Lan et al. 2016), and a different breed of broilers (Xu et al. 2018) was reported. However, it is the first time that in a native chicken of Iran the expression of five stress-related genes under hyperthermic stress is reported in this study. Heat shock proteins are produced in response to rising temperatures and other factors such as microbial infection, cancers and genetic damage (Ali and Banu, 1991). However, in this study, the expression of HSPB9, HSPA2 and HSP110 in the treatment group was 5 to 7 times more than the control group, but this increase was significant only for HSPA2 and HSP110 (P<0.05). The products of both genes are HSPs with high molecular weight. HSPA2 and HSP110 belong to the family of heat shock protein 70. The HSPA2 acts as a molecular chaperone in many cellular processes, including protecting proteins against stress, folding and transferring of newly synthesized polypeptides, activating the proteolysis of damaged proteins, and forming and decomposing protein compounds (Cedraz et al. 2017). The expression of HSP70 and HSP90 in native chickens compared to the Cobb breed has indicated an increase under heat stress. The Cobb breed reveals more sensitivity to heat than native breeds. The commercial breeds have been selected for production traits and are not compatible with warm weather (Soleimani et al. 2011). Conversely, native breeds are more adapted to the surrounding environment and have the ability to withstand more heat (Cedraz et al. 2017). Increasing the expression of HSPB9, HSPA2 and HSP110 in Khorasan native chickens under heat stress confirms that this breed has the ability to tolerate heat. Meanwhile, there were no casualties due to heat. The expression of the HSP70 increases under physiological stresses, diseases and environmental stresses (Eissa et al. 2017), and can be regulated by hormones (Wu et al. 2019). However, the regulation of the gene transcription is also related to the type of tissue. Leptin injection reduced the expression of HSP70 in the liver and the hypothalamus, but it did not affect the expression of the gene in the muscle of broiler chicks (Figueiredo et al. 2007). The expression of the heat shock factor family (HSF) genes is increased under ambient temperature which can increase the expression of HSP genes (Xie et al. 2014). However, the expression of HSF genes was not examined in the present study. One reason for the increased expression of HSP70 may be an increase in the level of reactive oxygen species (ROS) in the cell (Singh et al. 2014). Increased levels of ROS have been observed in chicken and cattle cells under heat stress (Singh et al. 2014; Cheng et al. 2018). In response to oxidative stress, HSF-1 is isolated from the HSP90 complex and transported to the nucleus for activation of transcription of HSP70, thereby preventing cell apoptosis (Rimoldi et al. 2015). Heat shock proteins act as a cellular heat-sensing and may only respond to increased temperature and protein degradation (Figueiredo et al. 2007). The family of small heat shock proteins, such as HSP25, is expressed in terms of heat and chemical stress. Even in the early stages of the embryo's blastoderm, the expression of HSP25 and HSP30CL has been reported (Hwang et al. 2016). Also, the reduction of HSP25 expression in blastoderm reduces the ability to differentiate cells and cell death increases (Hwang et al. 2016). However, the increase in expression of HSPB1 and SERPINH1 was not considered in the present study (Table 2). The expression of HSP47 and HSP60 increased from 2 to 4 hours of heat stress in broiler kidneys and then decreased to 24 hours (Tang et al. 2018). HSPB9 is the first cellular defense system against environmental stressors and is expressed before HSPB1 and HSPA2, although, its expression is low in early hours and then increases (Xu et al. 2019). The expression of HSPB9 in the present study was 5 times higher in the treatment group (Table 2). Network statistics of protein interactions are shown in Table 2. On average, the proteins in the protein interaction network are associated with 2.5 proteins. The P-value for the enrichment of protein-protein interaction (PPI) of the four proteins studied shows that they have a large intergroup interaction and are probably parts of a functional biological group (Franceschini et al. 2013). Totally, the proteins interacted in five biological pathways. HSPB9 was not included in the analysis, as STRING found no protein by this name for Gallus gallus. The interactions among proteins are shown in Figure 4. The analysis of biological pathways in STRING indicated that most of the pathways associated with cell and protein regulation are activated under thermal stress conditions (Table 3).
Figure 3 Comparison of candidate gene expression between control and under thermal stress groups: HSPB1 (A), HSPB9 (B), SERPINH1 (C), HSPA2 (D) and HSP110 (E)
The means within the same column with at least one common letter, do not have a significant difference (P>0.05)
Two paths were important in KEGG biological pathways. The Protein Processing in Endoplasmic Reticulum pathway is involved in the regulation of the producing right proteins and the elimination of inappropriate proteins. The accumulation of damaged proteins in the endoplasmic network (ER) causes cellular tensions and, with the activation of the heat shock response system (HSR), the stress load decreases (Liu and Chang, 2008). Heat shock protein 40, HSP70, and HSP90 play a role in the process of protein degradation. Low molecular weight HSPs, such as HSPB1, are not present in this biological pathway. The HSPB1 protein has an active role in MAPK signaling pathway, which controls many cellular activities, such as proliferation, differentiation and cellular transfer (Abhinand et al. 2016). The activation of MAPK signaling pathway and the presence of HSP27 are essential for the structural transformation of actin and cell migration (Golan et al. 2014). In the biological processes of gene ontology, three processes had FDR < 0.01 (Table 3). HSPA2 and HSPB1 involve in the processes that stimulate cells against increasing temperature, in terms of movement, secretion, enzyme production, gene expression, etc. as well as the reduction of enzymatic activity and down-regulation of cellular protein metabolic process (www.informatics.jax.org/vocab/gene_ontology/GO:0009408). Although few genes were analyzed in this study thus, the gene ontology may give only general aspects about the interaction between genes and their products. In a study by Lan et al. (2016), heat shock proteins with a molecular weight greater than 70 influenced the expression of liver genes in broiler chickens under heat stress. While the difference in the expression of HSP genes was not found in the study by Coble et al. (2014). The reason for the variation in the expression of genes is related to the different ways of heat treatment in the experiments as well as the different breeds that have been used (Sun et al. 2015). The molecular functions of the gene ontology observed in this study were similar to the report by Sun et al. (2015). HSPB1, HSPA2, and SERPINH1 play a role in intracellular functions (Table 3). The creation of a genetic network for high-expression genes in broilers exposed to severe heat stress showed the existence of the interaction between HSP genes and immune genes, while most HSP and immune genes showed upregulation (Lan et al. 2016). The elevated expression of HSP90 in the early hours of stress may be due to its protective role in cells against environmental destructive effects and oxidative damage (Rimoldi et al. 2015). In the present study, the increase in the expression of the HSPB1 was not significant and the expression of HSPA2 was significant at a confidence level of 0.05, which could indicate that the response of these genes is not severe under acute heat stress, but it may increase under chronic heat stress. Meanwhile, indigenous chickens reveal greater resistance to temperature changes (Cedraz et al. 2017).
Figure 4 Protein-protein interaction in STRING
Table 3 Significant biological pathways in KEGG database (FDR<0.01) and Functional enrichments in gene ontology (GO) analysis
The different cell lines and tissues give different responses to heat. The set of these responses depends on the combination of several factors including the genetic composition of the target species, genomic changes caused by past environmental stresses and the present state of the stressor (Sonna et al. 2002).
In this study, it was shown that the liver of Khorasan native chickens had an appropriate ability to express the HSP genes. Under heat stress, HSPA2 and HSP110 had higher expression than the control group, whereas HSPB1, HSPB9 and SERPINH1 did not show any difference compared to the control group. Considering the vital role of these proteins in maintaining the stability of cellular proteins, as well as the absence of casualties, it is concluded that Khorasan native chickens have the ability to tolerate acute heat conditions. This ability can be used to increase the capacity of the chicken temperature compatibility and to develop native resistant strains. Furthermore, HSPA2 and HSP110 can be considered as candidate genes in the marker-assisted selection program to improve heat tolerance in Khorasan native chickens. However, RNA-Seq analysis provides a lot of information on how different genes function, interact and involve in different biological systems, that based on this information new candidate genes can be introduced for further study.
This study was sponsored by Torbat-e-Jam University with the code TP13947. The authors are grateful to thegenetic lab of Ferdowsi University of Mashhad for technical support.