Academic Editor

Article Metrics

  • Fig. 1.

    View in Article
    Full Image
  • Fig. 2.

    View in Article
    Full Image
  • Fig. 3.

    View in Article
    Full Image
  • Fig. 4.

    View in Article
    Full Image
  • Fig. 5.

    View in Article
    Full Image
  • Fig. 6.

    View in Article
    Full Image
  • Fig. 7.

    View in Article
    Full Image
  • Fig. 8.

    View in Article
    Full Image
  • Fig. 9.

    View in Article
    Full Image
  • Information

  • Download

  • Contents

Abstract

Background:

Water scarcity is a current, significant global concern that will only increase under the pressure of climate change. Improving water efficiency of poultry is a new and promising area to help temper agriculture's future impact on fresh water availability. Here, we explored the effects of acute heat stress (HS) on circulating stress and inflammatory markers in 2 lines of broilers divergently selected for water efficiency.

Methods:

Male chicks from low (LWE) and high water efficient (HWE) lines were raised in 12 environmental chambers (2 pens/chamber, 6 chambers/line, 20 birds/pen) under normal conditions until day 28. On day 29, birds were subjected to thermoneutral (TN, 25 °C) or HS (36 °C) conditions, resulting in four treatments (2 lines × 2 environmental conditions). After 3 h of HS, whole blood was collected (8 birds per line × environment) and analyzed for target gene expression and plasma cytokine levels. Data were analyzed by 2-way ANOVA, with line, environment, and their interaction as main factors, and means were compared using Tukey's multiple range test.

Results:

Gene expression of heat shock protein (HSP) 27, HSP70, interleukin (IL)-6, IL-18, c-reactive protein (CRP), tumor necrosis factor-α (TNFα), C-C motif chemokine ligand 4 (CCL4), CCL20, nucleotide-binding domain, leucine-rich repeat (NLR) family pyrin domain containing 3 (NLRP3), NLR family CARD domain containing 5 (NLRC5), and NLR family member X1 (NLRX1) were increased by HS, with no differences between the lines. HSP70, IL-10, and NLRC3 were lower in the HWE as compared to the LWE lines. Additionally, there were interactive effects between line and environment for HSP90, IL-4, and CCL4, where HS induced HSP90 expression in the LWE only, and IL-4 and CCL4 in HWE only. Arginine vasopressin (AVP) gene expression was significantly lower in the whole blood of the HWE line; however, plasma protein levels were not different.

Conclusions:

Overall, most of the effects seen on cyto (chemokines) and inflammatory markers were due to acute HS, with only a few genes differentially regulated between the lines. This likely indicates that the divergent selection for water efficiency for four generations did not elicit changes in inflammation and stress molecular signatures.

1. Introduction

Water scarcity is a real and pressing concern worldwide. Only approximately 3% of the world’s water is freshwater, and only 0.5% is usable [1]. Importantly, agriculture uses over 70% of freshwater resources [2]. As climate change and global population expansion will further tax an already strained resource, it is estimated that two thirds of the global population, or 4 billion people, will experience severe water shortages for at least one month a year [3]. Indeed, rising temperatures coupled with fluctuation in distribution and amounts of rainfall will dramatically change water resources and create uncertain availability. Although tackling water scarcity necessitates action at every level of use, agriculture is uniquely situated in that any reductions in water use must also maintain animal production and welfare standards to meet the needs of the growing population.

It is estimated that broiler chickens consume 1.6–2.0 grams of water for each gram of feed [4]. Considering an average market age of 47 days for US broilers in 2023, and an average feed intake [5], this equals 8–10 kg (2.2–2.7 gallons) of water consumed per bird during production. The US alone produced 9.16 billion broilers in 2023, which equates to over 20 billion gallons of drinking water consumed by these birds. Additionally, during times of elevated environmental temperatures, productivity, in terms of growth, feed efficiency, meat yields, and livability, is decreased and the volume of water consumed can increase significantly [6], further impacting water usage. Even a small improvement in water efficiency in broilers could save billions of gallons of water annually, allowing that water to be diverted for other uses. Recently, our research group has published on 2 lines of chickens divergently selected for water efficiency (ratio of water consumed to body weight gain). We have shown an 18% reduction in water intake in the high water efficient (HWE) as compared to their low water efficient (LWE) counterparts, while maintaining body weight gain (BWG) and improving in feed conversion ratio (FCR) [7]. Additionally, the HWE line performed better under chronic cyclic heat stress (HS) conditions, despite consuming less water and having a higher core body temperature [7]. In that study, however, the cumulative, and possibly adaptive, effects of 20 days of HS were examined. As older and heavier broilers are more susceptible to the negative effects of HS [8], we undertook this study to determine the effect of acute (3 h) HS on 49 d-old LWE and HWE chickens. In particular, increased heat load has been shown to induce oxidative stress and the inflammatory response through alteration of cytokines, chemokines, and other inflammatory markers [9, 10, 11, 12], likely contributing to growth declines and HS-productivity losses seen in poultry [13]. What is unknown, however, is how selection for water efficiency may impact these parameters. Determining the profile of these factors would be of significant interest to the poultry industry, as robustness (defined as maintaining a high level of production while being adaptable to a wide variety of conditions [14]) is a key goal of breeding and selection programs. Here, in order to further characterize these divergently selected lines under HS conditions, we report the gene expression and relative levels of circulating chemokines, cytokines, and other inflammatory markers.

2. Materials and Methods
2.1 Animal Care and Study Design

All work was conducted in accordance with the National Institutes of Health recommendations guide for laboratory animal use and care. University of Arkansas Animal Care and Use Committee approved all procedures under protocol #23015. The genetic selection program for water efficiency was started in 2019, and has been previously described [7, 15]. HWE and LWE broiler chickens from the 4th generation were used in this study.

HWE and LWE chicks were hatched at the University of Arkansas hatchery. On the day of hatch, male chicks (240 chicks/line) were individually wing-banded for line identification and weighed. Chicks were assigned by body weight-matched groups and placed into 12 environmental chambers in the Poultry Environmental Research Laboratory at the University of Arkansas (2 floor pens/chamber, 6 chambers/line, 20 birds/pen, density of 0.096 m2/bird). Each pen was equipped with separate hanging feeders and water lines covered, and with clean pine wood shavings. Three-phase (starter, grower, and finisher) industry standard diets and water were provided ad libitum. The ambient temperature was gradually decreased from 32 °C to 25 °C by day 21. The lighting program provided was 24 h light for the first 3 days, 23 h light:1 h dark from Day 4–7, and 18 h light:6 h dark for the remainder of the study. The chambers’ temperature and humidity were continuously recorded using HOBO pro V2 data loggers (ONSET, Bourne, MA, USA), and relative humidity was maintained at ~30%–40%. At Day 49, birds were exposed to either thermoneutral (TN, 25 °C) or HS (36 °C for 3 h) environmental conditions, which resulted in four treatments (2 lines × 2 environmental conditions). Chamber temperature and relative humidity are presented in Fig. 1. After 3 h of HS, whole blood was collected from the wing vein from 8 randomly selected birds per line x temperature group in heparinized tubes, then either aliquoted for mRNA analysis or spun down to collect plasma. Samples were stored at –80 °C for subsequent analysis.

Fig. 1.

Chamber temperature and relative humidity. Chamber temperature (A) and relative humidity (B) on the day of blood sampling. Arrow indicates time of onset of HS. HS, heat stress; RH, relative humidity; TN, thermoneutral.

2.2 RNA Isolation and Quantitative Real-Time PCR

Whole blood was collected in Trizol LS reagent (Life Technologies, Carlsbad, CA, USA) and total RNAs were extracted based on the manufacturer’s guidelines. Total RNA concentration and quality were determined with use of the Take3 microvolume plate and the Synergy HTX multimode microplate reader (BioTek, Winooski, VT, USA). Reverse transcription was performed using qScript cDNA Synthesis Supermix (Quanta Biosciences, Gaithersburg, MD, USA), and cDNAs were amplified by real-time quantitative PCR (Applied Biosystems 7500 Real Time System, ThermoFisher Scientific, Waltham, MA, USA) with PowerUp SYBR green master mix (Life Technologies, Carlsbad, CA, USA) as previously described [16, 17]. Relative expression of the target genes was determined using the 2-Δ⁢Δ⁢CT method [18]. Ribosomal 18S (18S) gene expression was used for normalization. Oligonucleotide primer sequences specific for chicken are listed in Table 1.

Table 1. Oligonucleotide qPCR primers.
Gene Accession numbera Primer Sequence Orientation Product size, bp
IL-4 NM_001007079.2 GCTCTCAGTGCCGCTGATG F 60
GAAACCTCTCCCTGGATGTCAT R
IL-6 NM_204628.1 GCTTCGACGAGGAGAAATGC F 63
GGTAGGTCTGAAAGGCGAACAG R
IL8-L1 NM_205018.2 CAGAACCAAACCCAGGTGACA F 61
ACAGCCTTGCCCATCATCTT R
IL-10 NM_001004414.4 CGCTGTCACCGCTTCTTCA F 63
CGTCTCCTTGATCTGCTTGATG R
IL-18 NM_204608.1 TGCAGCTCCAAGGCTTTTAAG F 63
CTCAAAGGCCAAGAACATTCCT R
TNFα NM_204267.1 CGTTTGGGAGTGGGCTTTAA F 61
GCTGATGGCAGAGGCAGAA R
CRP NM_001039564.1 AAGCTCAGGACAACGAGATCCT F 71
TTTCCCCCCCACGTAGAAG R
IFNγ NM_205149.2 AAAGCCGCACATCAAACACA F 64
GCCATCAGGAAGGTTGTTTTTC R
NLRP3 NM_001348947.1 GTTGGGCAGTTTCACAGGAATAG F 63
GCCGCCTGGTCATACAGTGT R
NLRC5 NM_001318435.2 CTCGAAGTAGCCCAGCACATT F 81
CATGTCCAGAGGTGTCAGTCTGA R
NLRC3 XM_015294675.2 CTCCAACGCCTCACAAACCT F 93
GCCTTTGGTCATTTCCATCTG R
NLRX1 XM_004948038.3 GGCTGAAACGTGGCACAAA F 59
GAGTCCAAGCCCAGAAGACAAG R
CCL4 NM_204720.1 CCTGCTGCACCACTTACATAACA F 63
TGCTGTAGTGCCTCTGGATGA R
CCL20 NM_204438.2 TGCTGCTTGGAGTGAAAATGC F 62
CAGCAGAGAAGCCAAAATCAAA R
CCLL4 NM_001045831.2 CTTGCTGTCGGGTCCAATG F 60
CGAGGGAAGTGCTCTGTTTAAGA R
CXCL14 NM_204712.2 CCGGCTCGCCATGAAG F 54
ATCGCGATGACCAGCAGAA R
HSP27 XM_046936397.1 TTGAAGGCTGGCTCCTGATC F 58
AAGCCATGCTCATCCATCCT R
HSP60 NM_001012916.3 CGCAGACATGCTCCGTTTG F 55
TCTGGACACCGGCCTGAT R
HSP70 J02579 GGGAGAGGGTTGGGCTAGAG F 55
TTGCCTCCTGCCCAATCA R
HSP90 NM_001109785.2 TGACCTTGTCAACAATCTTGGTACTAT F 68
CCTGCAGTGCTTCCATGAAA R
AVP NM_205185.3 TCCGGGCACACTCAGCAT F 81
ATGTAGCAGGCGGAGGACAA R
18S AF173612 TCCCCTCCCGTTACTTGGAT F 60
GCGCTCGTCGGCATGTA R

aAccession number refers to GenBank (NCBI) and primers were produced by Integrated DNA Technologies (IDT, Coralville, IA, USA); AVP, arginine vasopressin; CCL4, C-C motif chemokine ligand 4; CCL20, C-C motif chemokine ligand 20; CCLL4, chemokine-like ligand 4; CRP, c-reactive protein; CXCL14, C-X-C motif chemokine ligand 14; HSP27, heat shock protein 27; HSP60, heat shock protein 60; HSP70, heat shock protein 70; HSP90, heat shock protein 90; IFNγ, interferon gamma; IL-4, interleukin 4; IL-6, interleukin 6; IL8-L1, interleukin 8L1; IL-10, interleukin 10; IL-18, interleukin 18; NLRC3, nucleotide-binding domain, leucine-rich repeat (NLR) family CARD domain containing 3; NLRC5, NLR family CARD domain containing 5; NLRP3, NLR family pyrin domain containing 3; NLRX1, NLR family member X1; TNFα, tumor necrosis factor alpha; 18S, Ribosomal 18S.

2.3 Plasma Cytokine Analysis

Relative levels of circulating cytokines: caronte, interferon gamma (IFN-γ), interlukin (IL)-6, IL-10, IL-12, IL-16, IL-21, Netrin-2, Pentraxin-3 (PTX3), and C-C motif ligand 5 (CCL5), were measured using the Chicken Cytokine Array GS1 (RayBiotech, Peachtree Corners, GA, USA), according to manufacturer’s instructions. The array contained quadruplicate spots for 10 cytokines. Signal intensity medians were corrected for background, and the mean of the replicates were calculated. Relative amounts of measured cytokines in circulation were normalized to the LWE-TN group.

2.4 Western Blot of Arginine Vasopressin (AVP)

Total plasma proteins were quantified by the Bradford assay and subjected to western blot as previously described [19]. Primary antibodies utilized were rabbit anti-arginine vasopressin (AVP, 1:1000 dilution, #20069, ImmunoStar, Hudson, WI, USA) with rabbit anti-glyceraldehyde 3-phosphate dehydrogenase (GAPDH, 1:1000 dilution, #NB300-327, Novus Biologicals, Centennial, CO, USA) as a loading control. Membranes were incubated for 1 h at room temperature with secondary anti-rabbit IgG-HRP-linked antibody (1:5000, #7074S, Cell Signaling, Technology, Danvers, MA, USA). The protein signals were visualized by enhanced chemiluminescence (Super ECL, ABP Biosciences, Beltsville, MD, USA) and collected using the FluorChem M bioimager (Proteinsimple, Santa Clara, CA, USA). Image acquirement and analysis were achieved with AlphaView software (Version 3.4.0, 1993–2011, Proteinsimple, Santa Clara, CA, USA).

2.5 Statistical Analyses

Data were analyzed by 2-way ANOVA, with chicken line (LWE, HWE) and environmental temperature (TN, HS) as main factors. Means were compared using Tukey’s multiple range test when significant main effects were detected. When the line by environment interaction was not significant, the significant main effects were analyzed separately with Student’s t-test. Significance was considered at p < 0.05. All data were analyzed using GraphPad Prism v. 7.03 (GraphPad Software Inc. San Diego, CA, USA), and are presented as means ± SEM.

3. Results
3.1 Body Weight of LWE and HWE Birds during Acute HS

Body weight of the 4 groups is presented in Table 2. There were no significant differences in the body weights of the sampled birds in the 4 groups.

Table 2. Body weight (g) of LWE and HWE birds subject to acute heat stress.
LWE HWE p-value
TN HS TN HS L E LxE
3433 ± 58 3476 ± 131 3354 ± 107 3227 ± 103 0.1228 0.6883 0.4129

Data represent means ± SEM (n = 8/group). E, Environment; HS, heat stress; HWE, high water efficient; L, Line; LWE, low water efficient; TN, thermoneutral; LxE, line by environment interaction.

3.2 Circulating Heat Shock Protein Gene Expression in LWE and HWE Chickens during Acute HS

Gene expression of heat shock proteins (HSP) were differentially regulated in the blood of heat-stressed LWE and HWE chickens. HSP27 (Fig. 2A,B) and HSP70 (Fig. 2C,D) were significantly increased by HS (p < 0.005), regardless of line. Additionally, HSP 70 was significantly lower (p = 0.0022) in the HWE as compared to the LWE birds, regardless of environmental temperature (Fig. 2E). HSP90 showed significant interactive effects (p = 0.0114), where gene expression was increased during acute HS in the LWE (p = 0.0288), but was unchanged in the HWE line (p = 0.8173, Fig. 2G). HSP60 gene expression was unaffected by line and temperature (p > 0.05, Fig. 2F).

Fig. 2.

Blood heat shock protein gene expression in LWE and HWE Chicken Lines during Acute HS. HSP27 (A,B), HSP70 (C,D,E), HSP60 (F), and HSP90 (G). When the Line by Environment interaction was not significant, main effects were analyzed individually by Student’s t-test. Data represent means ± SEM (n = 8 per group). * and different letters indicate significant differences at p < 0.05. HS, heat stress; HSP, heat shock protein; HWE, high water efficient; LWE, low water efficient; TN, thermoneutral; Env, environment; LxE: line by environment interaction.

3.3 Circulating Inflammatory Markers in LWE and HWE Chickens during Acute HS

Overall, there was a significant effect of HS on pro-inflammatory cytokines gene expression, where IL-6, IL-18, c-reactive protein (CRP), and tumor necrosis factor-α (TNFα) were induced by HS, regardless of line (p < 0.001, Fig. 3A–H). There were no significant effects on IL-8L1 or interferon-γ (IFN-γ, p > 0.05, Fig. 3I,J). For the anti-inflammatory cytokines, there was an interactive effect between line and temperature on mRNA abundance of IL-4 (p = 0.0042), where it was significantly increased (p < 0.0001) by acute HS in the HWE, but not the LWE birds (Fig. 4A). IL-10 was significantly affected by line (p = 0.0120), with lower expression in the HWE as compared to the LWE birds (Fig. 4B,C). Gene expression of chemokines C-C motif ligand 4 (CCL4, p = 0.0240) and C-C motif ligand 20 (CCL20, p = 0.0043) were both significantly increased by HS, with no effect of line (Fig. 5A–D). There were no effects of line or temperature on chemokine-like ligand 4 (CCLL4) or C-X-C motif chemokine ligand 14 (CXCL14) mRNA abundance in blood (Fig. 5E,F). HS increased the mRNA abundance of the NLR family pyrin domain containing 3 (NLRP3, p = 0.0001, Fig. 6A,B), NLR family CARD domain containing 5 (NLRC5, p = 0.0031, Fig. 6C,D), and NLR family member X1 (NLRX1, p = 0.0289, Fig. 6G,H) inflammasomes, while the HWE line had significantly lower expression of NLR family CARD domain containing 3 (NLRC3, p = 0.0095, Fig. 6E,F) gene, as compared to the LWE line.

Fig. 3.

Pro-inflammatory marker gene expression in blood of LWE and HWE chicken lines during acute HS. The expression of IL-6 (A, B), IL-18 (C, D), CRP (E, F), TNFa (G, H), IL-8L1 (I), and INFg (J) was determined by qPCR. When the Line by Environment interaction was not significant, main effects were analyzed individually by Student’s t-test. Data represent means ± SEM (n = 8 per group). * p < 0.05. CRP, c-reactive protein; HS, heat stress; HWE, high water efficient; IFNγ, interferon gamma; IL, interleukin; LWE, low water efficient; TN, thermoneutral; TNFα, tumor necrosis factor alpha.

Fig. 4.

Anti-inflammatory marker gene expression in blood of LWE and HWE chicken lines during acute HS. IL4 (A) and IL-10 (B,C). When the Line by Environment interaction was not significant, the main effects were analyzed individually by Student’s t-test. Data represent means ± SEM (n = 8 per group). * and different letters indicate significant differences at p < 0.05. HS, heat stress; HWE, high water efficient; IL, interleukin; LWE, low water efficient; TN, thermoneutral.

Fig. 5.

Chemokine gene expression in blood of LWE and HWE chicken lines during acute HS. CCL4 (A,B), CCL20 (C,D), CCLL4 (E), and CXCL14 (F). When the Line by Environment interaction was not significant, main effects were analyzed individually by Student’s t-test. Data represent means ± SEM (n = 8 per group). * and different letters indicate significant differences at p < 0.05. CCL, C-C motif chemokine ligand; CCLL4, chemokine-like ligand 4; CXCL14, C-X-C motif chemokine ligand 14; HS, heat stress; HWE, high water efficient; LWE, low water efficient; TN, thermoneutral.

Fig. 6.

Inflammasome gene expression in blood of LWE and HWE chicken lines during acute HS. NLRP3 (A,B), NLRC (C,D), NLRC3 (E,F), and NLRX1 (G,H). When the Line by Environment interaction was not significant, main effects were analyzed individually by Student’s t-test. Data represent means ± SEM. * p < 0.05. HS, heat stress; HWE, high water efficient; LWE, low water efficient; NLRC3, NLR family CARD domain containing 3; NLRC5, NLR family CARD domain containing 5; NLRP3, NLR family pyrin domain containing 3; NLRX1, NLR family member X1; TN, thermoneutral;

In plasma, a significant interaction between line and environmental temperature was evident for circulating levels of caronte (p = 0.0013, Fig. 7A), pentraxin-3 (PTX3, p = 0.0039, Fig. 7B), and C-C motif ligand 5 (CCL5, p = 0.0490, Fig. 7C), but not for plasma netrin levels (Fig. 7D,E). Plasma caronte and PTX3 showed a similar pattern, where relative levels were lower in HWE birds under HS as compared to TN conditions, though no effects were seen in the LWE line. The chemokine CCL5, however, was increased by HS in the LWE line, with no effects in the HWE birds (Fig. 7C).

Fig. 7.

Plasma caronte, PTX3, CCL5, and netrin levels in LWE and HWE chicken lines during acute HS. Caronte (A), PTX3 (B), CCL5 (C), and Netrin (D,E). Data represent means ± SEM (n = 8 per group). Different letters indicate significant differences at p < 0.05. CCL5, C-C motif ligand 5; HS, heat stress; HWE, high water efficient; LWE, low water efficient; PTX3, pentraxin 3; TN, thermoneutral; Temp, temperature; LxT, line by temperature interaction.

For the (anti)pro-inflammatory cytokines, a significant interaction between line and environmental temperature was observed for circulating levels of INFγ (p = 0.0004, Fig. 8A), where the concentrations were higher in HWE as compared to LWE birds in TN conditions. Heat stress reduced plasma INFγ levels in HWE but not in LWE birds (Fig. 8A). No effects were seen in circulating IL-6, IL-10, IL-12, IL16, or IL-21levels (Fig. 8B–F).

Fig. 8.

Plasma cytokine levels in LWE and HWE chicken lines during acute HS. INFγ (A), IL-6 (B), IL-10 (C), IL-12 (D), IL-16 (E), and IL-21 (F). Data represent means ± SEM (n = 8 per group). Different letters indicate significant differences at p < 0.05. HS, heat stress; HWE, high water efficient; IL, interleukin; INFγ, interferon gamma; LWE, low water efficient; TN, thermoneutral.

3.4 Blood AVP Gene and Protein Expression in LWE and HWE Chickens during Acute HS

Gene expression of AVP in blood was significantly different between the lines, with lower expression in the HWE birds (p = 0.0044, Fig. 9A,B). There was no effect of temperature on AVP mRNA. However, AVP protein in the plasma was not significantly affected (p > 0.05) by line nor environmental temperature (Fig. 9C,D).

Fig. 9.

AVP gene Expression and plasma protein levels in LWE and HWE chicken lines during acute HS. Relative gene (A) and protein (B) expression of AVP. Representative western blot (C) and quantification (D) of AVP and GAPDH. Data represent means ± SEM (n = 8 per group). * p < 0.05. AVP, arginine vasopressin; GAPDH, glyceraldehyde 3-phosphate dehydrogenase; HS, heat stress; HWE, high water efficient; LWE, low water efficient; TN, thermoneutral.

4. Discussion

Water availability is already a concern for roughly a quarter of the world’s cities, which experience perennial water shortages [20]. As climate change and global warming will likely lead to more frequent and intense heat waves [21], the need for water, which is already limited, will increase. The poultry industry is particularly susceptible to HS [22], as modern chickens have high metabolic activity, increased body heat production, and decreased thermotolerance [6]. Therefore, the combined impact of these environmental challenges must be addressed in order to not only maintain, but improve productivity of a critical, efficient, and affordable protein source for a growing world population.

It is imperative to understand potential associated changes, whether positive or negative, that can arise during the selection process in broilers. Indeed, intensive genetic selection for improved growth rate and feed efficiency for more than 80 years has given rise to unintended negative traits that are now concerns for the industry [23]. Here, overall, we show that the impact of 4 generations of selection for improved water efficiency had minimal impact on circulating inflammatory markers in acute heat-stressed broilers. As we measured gene expression in whole blood, it encompasses a heterogeneous mix of cell types, including white blood cells, the traditional players in the immune and inflammatory response, as well as red blood cells. This is of importance, as in chickens, red blood cells are nucleated, and therefore are transcriptionally active and have protein synthesis abilities, and likely substiantially impact the immune response, through both sending and receiving cellular signals [24]. Additionaly, obtaining a blood sample is minimally invasive, and can allow for monitoring of health status or response to specific stressors (such as HS) within a breeding program.

Some of the spotted effects of HS might be associated with dysregulation of protein homeostasis-induced by protein misfolding and aggregation. To counter these detrimental effects, the cell activates the survival pathways through systematization of highly conserved responses. Contingent on the stress type, severity, intensity, amplitude, and duration, cells can activate a rapid and efficient stress response and protein quality control systems (refolding, degradation, etc.) to ensure their survival or start off the cell-death pathway [25]. At the cellular and molecular levels, a well known standard rapid response to HS is induced synthesis of heat shock proteins (HSPs). Based on their known functions, elevated HSP expression due to acute HS was not unexpected, and has been previously shown in multiple tissues in poultry [11, 26, 27]. The differences seen in HSP70 gene expression between the lines, however, are more intriguing. Lower blood HSP70 expression in the HWE line, regardless of environmental temperature, may indicate an improved state of intracellular homeostasis in these birds as compared to the LWE line, as HSP70 is a highly inducible molecular chaperone that catalyzes proper folding of nascent proteins under normal conditions and assist in refolding and clearing damaged proteins under stress conditions [28]. Further studies are needed to define the role and mechanisms of HSP70 in protein homeostasis, cell survival, and thermotolerance in HWE birds.

Unsurprisingly, HS increased gene expression of the majority of cytokines and chemokines as has been previously reported [9, 10, 29], and alteration of the innate cytokine and chemokine response by stressors is well noted [29, 30]. The fact that the induction of these factors was to a similar extent in both HWE and LWE lines indicates that there were neither detriments nor improvements to this response associated with selection for water efficiency. However, IL-10, IL-4, and CCL4 were differentially expressed between the two lines. IL-10 is increased in circulation in response to inflammatory challenges, such as viruses, bacteria, fungi, protozoa and helminths [31]. Studies have shown it to exhibit immunosuppressive properties, through inhibition of cytokines such as IFN-γ [32], IL-8 [33], IL-12 [34], and TNFα [35]. IL-4 plays a key role in the promotion of T-helper 2 cell differentiation and can suppress synthesis or function of many proinflammatory cytokines [36]. Similarly, CCL4 helps orchestrate the immune response to infection or inflammation, as it is a chemoattractant for monocytes/macrophages, T-lymphocytes, natural killer cells and dendritic cells [37]. As IL-4 and CCL4 gene expression were upregulated in HWE chicken during HS, but not in LWE birds, it may indicate a more robust response to the HS challenge and promote anti-inflammatory properties, which may help explain the improved performance of this line during HS [7]. However, these cytokines and chemokines are not well studied in avian species; therefore, research targeting the mechanism by which they may regulate growth and production during HS stress challenges is necessary.

The inflammasomes are a group of intracellular multimeric protein complexes that influence inflammation and the protective immune response [38]. Multiple members of the NLR family exist, with differences in stimuli and activated pathways, and both inflammatory and anti-inflammatory properties [39, 40]. Here, the mRNA abundances of the NLRP3, NLRC5, and NLRX1 inflammasomes were all upregulated in circulation by HS, without any differences between the water efficiency broiler lines. NLRP3 is the most well studied inflammasome, and is generally considered pro-inflammatory. Although NLRC5 and NLRX1 are less well understood, NLRC5 has been shown to have inflammatory properties via association with NLRP3 [41] and through IFN production, but may also be able to suppress IFN and nuclear factor kappa-light-chain-enhancer of activated B cells (NF-κB) signaling [42], depending on the cell-type and experimental conditions. Here, its role is still unclear. Gene expression patterns between NLRP3 and NRLC5 are similar; however, circulating IFNγ is decreased during HS in the HWE lines. Interestingly, NLRC3 gene expression was lower in the blood of HWE as compared to the LWE line. It had been shown that the NLRC3 inflammasome has an anti-inflammatory role via inhibition of the NF-κB pathway [43], and can inhibit pyroptosis through blocking the formation of NLRP3 inflammasomes [44]. As these inflammasomes are not well defined in chickens, further exploration to their roles is merited.

The brain is a critical regulator and protector of homeostasis via neuroendocrine responses which guard set-points of body water concentration and volume [45]. AVP is a key hormone in fluid balance, as it is released from the posterior pituitary in response to increased plasma osmolarity, and acts to increase water retention at the kidney [46]. There are several studies in human medicine examining the difference between individuals with low and high habitual fluid intake [47]. In both intake groups, plasma osmolarity and sodium levels remain within normal ranges; however, one of the hallmarks is higher levels of circulating AVP in those that consume less [47]. Here, we found no differences in circulating AVP protein, although gene expression was lower in the HWE as compared to the LWE line. Other research has shown AVP expression in peripheral tissues [48, 49], therefore it is plausible that AVP produced by circulating cells may have autocrine effects separate from, or in addition to, centrally produced AVP. Studying these cells in isolation could help define the role of this locally produced AVP. Overall, our data suggests that although HWE birds are drinking less water, their blood inflammasome and chemocytokine expression profile seemed to not be altered. It is plausible that the HWE birds have more efficient metabolic water production and water (re)absorption in the gut, allowing overall homeostasis to be maintained in the body. Further research is warranted to examine other physiological, cellular and molecular pathways in the HWE birds with more selection generations to make sure that there are no undesirable changes occur.

5. Conclusions

In conclusion, water scarcity is a global concern that must be addressed at all levels of water use, but modifications in agricultural systems must also maintain optimal production levels. Herein, to the best of our knowledge, we are the first to report that broilers selected for high or low water efficiency displayed an overall similar expression pattern of circulating inflammatory markers in response to acute HS. This likely indicates that selection for improved water efficiency has not negatively impacted inflammation status in these birds.

Availability of Data and Materials

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

Author Contributions

SD designed the research study. ESG, TT, WGB, SO, and SD performed the research. ESG analyzed the data and wrote the manuscript. SD edited the manuscript. All authors contributed to editorial changes in the manuscript. All authors read and approved the final manuscript. All authors have participated sufficiently in the work and agreed to be accountable for all aspects of the work.

Ethics Approval and Consent to Participate

This study was conducted in accordance with the National Institutes of Health recommendations guide for laboratory animal use and care. All the procedures in this study were approved by the University of Arkansas Animal Care and Use Committee under protocol #23015.

Acknowledgment

Authors would like to thank the University of Arkansas Poultry Research farm and the University of Arkansas feed mill for their assistance.

Funding

This study was supported by a grant from USDA NIFA Sustainable Agriculture Systems (#2019 69012-29905) to S.D.

Conflict of Interest

The authors declare no conflict of interest.

References

Publisher’s Note: IMR Press stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.