Acute Heat Exposure Upregulates Zebra Finch Physiology While Avoiding DNA Damage Across Both Sexes

ABSTRACT

A recent increase in the frequency of extreme heat events has urged researchers to examine physiological responses to hot temperatures. Across species, there is variation in whether the sexes respond the same or differently to extreme temperatures. Accordingly, our study investigated the sex‐specific responses to an acute heat exposure. We assigned adult male and female zebra finches to a 5‐h control (22°C; female: n = 20, male: n = 19) or a heat treatment (43°C; female: n = 23, male: n = 22). We collected blood samples 2 weeks pre‐treatment and immediately post‐treatment to measure blood concentrations of corticosterone, glucose, ketones (beta‐hydroxybutyrate), and DNA damage. Additionally, we measured the core body temperatures of the birds via PIT tags. Heat exposure significantly increased body temperature, blood glucose, blood ketone, and plasma corticosterone levels. In contrast, we found no significant difference in DNA damage levels in the red blood cells. Finally, we found no sex differences in these physiological measures. To explore systematic interactions, we utilized Gaussian Graphical Models, which indicated that heat stress results in more coupled interactions between variables. Notably, ketones and glucose were positively correlated in the control group but negatively correlated in the heated group, suggesting a shift in metabolic fuel utilization. Our findings suggest that physiological and cellular responses to acute heat stress are consistent across sexes in adult zebra finches. These findings are an important step to better understand the physiological underpinnings of how birds respond to acute heat stress.

Summary

Acute heat in zebra finches increased body temperature, corticosterone, and blood glucose and ketones. Males and females responded similarly. Despite the physiological adjustments DNA damage was not detected after 5 h of acute heat exposure.

1. Introduction

Global temperatures have increased at staggering rates in recent years, fundamentally changing ecosystem dynamics. In response to extreme heat, mass mortality events are becoming more prevalent (McKechnie and Wolf ²⁰¹⁰; Conradie et al. ²⁰²⁰; McKechnie et al. ²⁰²¹). Additionally, studies show heat is causing populations to become smaller (Cruz‐McDonnell and Wolf ²⁰¹⁶; Conradie et al. ²⁰¹⁹), partly due to lower reproductive success (Barrett and Stein 2024). Moreso, heat can impact cognitive performance, organ function, and mating behavior of animals (Welbergen et al. 2008; Coomes et al. ²⁰¹⁹; Coomes and Derryberry ²⁰²¹; Danner et al. ²⁰²¹; Abdulkadir and Reddy ²⁰²³), which also has impacts on fitness and population demographics.

To fully understand how extreme heat impacts an organism, including fitness correlates and behavior, it is important to investigate the underlying physiological processes and associated biomarkers. To survive these extreme temperatures, birds initiate a complex suite of physiological responses to meet the metabolic demand of hotter temperatures (Nawaz et al. 2021). Elevated levels of key metabolic hormones, such as glucocorticoids, increase in response to heat (De Bruijn and Romero ²⁰¹⁸; Liu et al. ²⁰²²), and may maximize substrate availability to sustain metabolic processes during heat stress. For example, glucose and glucocorticoids both increase in the bloodstream of chickens experiencing heat stress (Beckford et al. 2020), while ketone bodies increase in Japanese quail experiencing heat stress (Pu et al. 2019). Both glucose and ketones are important molecules that serve as energy sources for metabolism (Gerich 2000; Tsuruta et al. ²⁰²⁴). To connect metabolic demands to survival, we must also understand the physiological consequences of heat, such as oxidative stress.

Oxidative damage occurs when reactive oxygen or nitrogen species exceed the cells' capacity to protect against them, resulting in the oxidation of lipids, proteins, and DNA (Pizzino et al. 2017). Thus far, there is mixed evidence regarding heat exposure and its impact on macromolecule damage. Some studies show increased damage after heat exposure (Belhadj Slimen et al. 2014; Haussmann et al. ²⁰²⁵), while others do not (Zhang et al. 2019; Li et al. ²⁰²¹). As multiple aspects of physiology are impacted by heat stress (Abdulkadir and Reddy 2023), investigating how they change together or independently allows us to evaluate how the physiological network is communicating with itself to favor organismal survival during exposure to extreme or prolonged heat.

While the physiological impacts of heat are widespread, the scale of these responses can be different between males and females. For example, in humans, males and females reached similar core body temperatures from exertional heat stroke; however, females spent half as much time in the hospital compared to males (Goodwin et al. 2024). Conversely, other studies found that while males experienced a higher incidence of heat stroke, females were more susceptible to exertional heat illnesses (Alele et al. 2020). Birds also show sex differences when exposed to heat. In yellow‐billed hornbills, males had higher evaporative water loss and resting metabolic rates compared to females when ambient temperatures were above 40°C (Van Jaarsveld et al. 2021). Male zebra finches acclimated their metabolic rates after 1 day of exposure to hotter temperatures, while female zebra finches were unable to acclimate (Pessato et al. 2023). However, another study found no sex‐specific differences in how red blood cell mitochondrial respiration responded to a daily 5‐h 40°C heat treatment lasting for 5 days (Pacheco‐Fuentes et al. ²⁰²³). Additionally, when the maximum ambient temperature was above 39°C for three consecutive days, male and female zebra finches did not exhibit differences in plasma corticosterone, glucose, or uric acid levels (Cooper et al. 2020). Although some studies suggest that sexes respond differently to heat, there are conflicting findings regarding whether one sex is more susceptible, suggesting that more research is necessary to understand these differences.

Here, we investigated sex‐specific physiological responses to an acute heat exposure by exposing male and female zebra finches to either a control temperature treatment (22°C) or acute heat temperature treatment (43°C) for 5 h. We measured blood concentrations of corticosterone, glucose, ketones (ß‐hydroxybutyrate), and DNA damage 2 weeks before and immediately after the treatment. We also measured the core body temperature throughout the treatment period. We predict that physiological measures would increase as the body temperature rises. Furthermore, we aimed to determine if the physiological responses differed between males and females.

2. Materials and Methods

2.1. Animal Husbandry and Housing

Experimental zebra finches (Taeniopygia guttata castanotis) were housed at Auburn University at 22°C, on a 14:10‐h light:dark cycle. All birds utilized were adults of unknown ages. This study was conducted from March to May 2025. Animal husbandry and experimental protocols were approved by Auburn University's Institutional Animal Care and Use Committee (protocol # 2024‐5510).

2.2. Experimental Design

To determine the physiological effects of an acute heat exposure on male and female zebra finches, we randomly assigned males and females to a temperature treatment group: 22.0°C (control) or 43°C (heated). Previous studies in zebra finches have determined that the ambient temperature of 42°C–43°C induced oxidative damage, behavioral shifts, and alterations in gene regulation (Costantini et al. 2012; Lipshutz et al. ²⁰²²; Hoffman et al. ²⁰²⁵). Additionally, these temperatures are above the thermoneutral zone for zebra finches (Calder 1964; Wojciechowski et al. ²⁰²¹), so we expected birds to alter their physiology and expend energy to thermoregulate. The chosen 43°C treatment reflects ecologically relevant temperatures for the zebra finch. In Australia, these birds inhabit geographic ranges with average monthly maximum temperatures of 42.3°C and experience localized ambient extremes up to 46.2°C (Griffith et al. 2025). Finally, acute heat events have led to mass die‐offs (McKechnie et al. ²⁰²¹), so our acute heat treatment represents a potentially more dangerous exposure to heat when compared to the chronic heat zebra finches are exposed to in the wild (Cooper et al. 2019).

We used a cohort study design where a heated male, a heated female, a control male, and a control female were sampled each day over the time course of the experiment (Figure 1). Each cohort began by collecting a pre‐treatment blood sample approximately 2 weeks prior to the temperature exposure (median 14 days, range 10–16 days). After the pre‐treatment blood sample, a passive integrated transponder (PIT) tag was inserted intraperitoneally into each bird to measure core body temperature during the treatment period (Biotherm 13, Biomark, Boise, ID, USA; temperature monitoring range: 33°C to 43°C; but see Pessato et al. ²⁰²³; Freeman et al. ²⁰²⁴ for temperature validation above monitoring range). After PIT tag insertion, birds were weighed. Roughly 11 days later (11 ± 3 days; mean ± standard deviation), individuals were weighed again and moved into incubators to allow birds to acclimate to their new environment. The side of the incubator that males and females were housed on was balanced across treatments, incubators, and cohorts. For the next two mornings, incubators were set to 22°C, turned on at 8am, and turned off at 2 pm. The temperature exposure occurred on the third morning. On the temperature treatment day, the incubators were turned on at 8am for an approximate 50‐min ramp‐up period (47.67 ± 4.43 min; mean ± standard deviation) that allowed the incubators to reach the target temperature of 43°C. After the ramp‐up period, birds were kept at that temperature until 2 pm, totaling for approximately 5 h and 10 min of heat exposure. Birds were allowed food and water during the treatment to prevent additional stressors due to lack of access to food, water, and disturbance prior to treatment. Once the temperature treatment was complete, birds were removed from the incubator, a blood sample was drawn, and the bird was euthanized.

Figure 1.

Experimental design. On day 0 of the study, a blood sample was drawn to measure pre‐treatment levels of glucocorticoids, ketones, glucose, and DNA damage. Passive integrated transponder tags were then inserted intraperitoneally into each individual, and the bird was weighed. Approximately 11 days later, birds were moved into an incubator for an acclimation period. On day 14 of the study, incubators were turned on to their appropriate treatment temperature for 5 h. After which, a post‐treatment blood sample was drawn and birds were euthanized.

2.3. Body Temperature Measurements

During the 5‐h temperature treatment, a small‐scale antenna (Biomark, Boise, ID, USA) was placed at the bottom of the incubator to read core body temperature of the zebra finches (Figure S1). Each PIT tag had a unique identification that allowed multiple birds to be distinguished from the same reader. The small‐scale monitoring system PIT tag reader would scan every 120 ms resulting in continuous, passive body temperature measurements for each individual. For the purposes of this study, the top 10% of body temperatures were averaged to understand the ‘maximum body temperature' of each bird during the temperature treatment. Due to technical error with the data logging software, a portion of the body temperature data was not recorded, resulting in a reduced sample size (heat: n = 37; control: n = 27).

2.4. Blood Sampling and Blood Metabolites

Blood samples were drawn via a puncture of the brachial vein with a sterile 26‐gauge needle and collected in heparinized capillary tubes. The total volume of blood taken did not exceed 1% of the birds' body mass. To clot the wound, styptic powder was dusted onto a cotton ball and pressure was applied to the puncture site. All blood samples were collected within 3 min of entering the room (2.12 ± 0.79 min; mean ± standard deviation). It is important to collect blood samples quickly after initially disturbing the bird, as blood concentrations of glucocorticoids increase significantly after 3 min (Romero and Reed 2005). Samples collected after this threshold will no longer reflect the concentration of glucocorticoids prior to the initial disturbance, making it difficult to determine if elevated levels are caused by heat or handling stress.

Whole blood samples were used to quantify circulating blood glucose and ß‐hydroxybutyrate (ketone) levels from point of care devices. Glucose was measured on the ReliOn Prime blood glucose monitoring device (Walmart Apollo LLC Bentonville, AR), and ketones were measured on the PrecisionXtra ketone monitoring device (Abbott; product #9881465). Both devices have been previously validated for our species (Pham et al. ^2025a, ^2025c). Glucose and ketones were measured in duplicate, but a third measure was collected if the duplicates varied more than 30 mg/dL or 0.2 mmol/L for glucose and ketones respectively. The average of the two closest measures was taken and used for the final analysis. The remaining blood was then centrifuged in the hematocrit tube at 14800xg for 10 min at room temperature. Plasma and red blood cells were then separated, flash frozen in liquid nitrogen, and stored at −80°C until further analysis.

2.5. Corticosterone Measurement

We quantified corticosterone concentrations from pre‐ and post‐treatment samples using an enzyme‐linked immunoassays (ELISAs) kit (Arbor Assays, Ann Arbor, MI) that has previously been used in our lab (Pham et al. ^2025a). Prior to the ELISA, steroid hormones were extracted from 10 µL of plasma with a triple ethyl acetate extraction and were left to evaporate overnight (Henry et al. 2025; Pham et al. ^2025a). In addition, a nonexperimental plasma sample was stripped of all steroid hormones with dextran‐coated charcoal and was spiked with a known concentration of corticosterone (10,000 pg/ml). To determine extraction efficiency, an aliquot of this spiked sample was extracted for each plate. The next morning, samples were reconstituted with 125 µL of assay buffer and were stored at −20°C. We followed the manufacturer's instructions when running the assay. Samples were randomly plated in duplicate, with all combinations of sexes and treatments included in each plate. Five samples fell below the detection limit and were assigned the lowest detectable value. Intra‐assay variation was 5.71% and inter‐assay variation was 2.14%.

2.6. DNA Extraction and DNA Damage Measurement

We extracted DNA using the PureGene Kit (Qiagen) protocol with modifications. DNA was extracted from pre‐ and post‐treatment samples of red blood cells, which had been stored at −80°C. Then, the 10 μL of red blood cells were mixed with Cell Lysis Solution and 1 μL of 20 mg/mL Proteinase K before being vortexed at a low speed until homogeneous. The blood mixture was then placed into a shaking incubator at 300 rpm, at 55°C for an hour. After incubation, Protein Precipitation Solution was added to each tube and vortexed vigorously. Tubes were incubated on ice for 5 min before being centrifuged at 16,000 g for 5 min, and the supernatant was kept. DNA was precipitated with isopropanol and washed with 70% ethanol before being resuspended in DNA hydration solution. The quantity of the DNA was determined using a nanodrop, and the quality was determined through visualization on a 1% agarose gel.

DNA lesions were measured using a modified Rapid Repair Assisted Damage Detection (RADD) protocol (Holton et al. 2018; Lee et al. ²⁰¹⁹; Gilat et al. ²⁰²⁰) as previously described by Coutts et al. ²⁰²⁵; Hoffman et al. ²⁰²⁵, and Pham et al. ^2025b. Briefly, a lesion processing cocktail (1x Thermo Pol Buffer, 1× NAD + , bovine serum albumin, UDG, FPG, T4PDG, AAG, EndoIV and EndoVIII) was incubated with 500 ng of DNA at 37°C for 1 h. Then, a gap‐filling cocktail (1× Thermo Pol Buffer, Klenow exo, and fluorescent ATTO‐550‐dUTP) was added to the reaction tube and was incubated for an additional hour at 37°C. DNA samples were then purified from excess fluorophores using an Oligo Clean and Concentrator kit for 96‐well plates (Zymo Research). Then, 1 μL labeled DNA was placed in a well on a positively charged Teflon‐coated microscope slide (Gilat et al. 2020). Slides were incubated for 14 min at 42°C and then for 24 min at 30°C in humid conditions before being washed with water and dried under nitrogen.

Slides were imaged using an Amersham Typhoon Biomolecular Imager using a 532 nm laser. After imaging the ATTO‐550 fluorophore, the DNA was stained with EvaGreen DNA dye (Biotium). Additionally, wells containing only water, with no DNA, were stained to obtain the background signal of the EvaGreen dye in the absence of DNA. The fluorescence intensity was quantified using ImageQuant analysis software. The background signal (fluorescence from wells containing only water) was subtracted from the ATTO‐550 fluorescence, which reports DNA damage, and from the EvaGreen fluorescence, which reports DNA content in the well. The corrected ATTO‐550 signal in each well was divided by the corrected EvaGreen signal. This ratio provides the relative DNA damage to the total DNA in the well.

2.7. Statistics

To analyze our response variables, we utilized linear mixed effect models, generalized linear mixed effect models, or linear models. All analyses were done in R (Core Team. ²⁰²⁵). Assumptions of each model were assessed visually, and significance was determined when p < 0.05. In all linear and generalized linear mixed effect models, we used the same predictor variables: treatment (22°C or 43°C), sex (male or female), and time point (pre‐ or post‐treatment). All linear mixed effect models started with the three‐way interaction (treatment by sex by time point), and backwards‐stepwise regression was used until only significant interaction terms or main effects remained. AIC scores were used to ensure that the backwards stepwise regression model was the most parsimonious model. Since we are interested in how sexes respond to heat, sex as a main effect was left in every model. Finally, in every linear mixed effect model, ‘individual' was included as a random effect to account for the non‐independence of data due to individuals being sampled at two time points (pre‐and post‐treatment).

Blood ketones and DNA damage were analyzed with general linear mixed effect models. However, glucose and corticosterone did not meet the assumption of normally distributed residuals. Blood glucose was log‐transformed and analyzed using a general linear mixed effect model. Corticosterone was analyzed using a generalized linear mixed effect model with a gamma distribution and log‐link function. Body temperature was only collected during the treatment period, meaning there was only one time point to analyze, so a linear model was used. The predictor variables of treatment, sex, and their interaction were used to analyze their impact on body temperature. If a significant interaction term was found, a post‐hoc analysis was completed using the Šidák adjustment factor from the emmeans package (Lenth 2023).

To evaluate the relationship between our physiological variables after heat exposure, we estimated Gaussian Graphical Models. To start, we estimated the partial correlation coefficient between each variable using the bootnet package (Epskamp et al. 2018). In short, this creates a correlation matrix that estimates the strength and direction of a relationship between two variables, while controlling for the influence of other variables (i.e., the relationship between glucose and ketones, which accounts for body temperature, corticosterone, and DNA damage). Because of this, only individuals that had no missing data for all measurements were included.

We used data only from the post‐treatment time point for the blood measures. Our nodes, or variables, included glucose, ketones, DNA damage, corticosterone, and body temperature. Using the qgraph package (Epskamp et al. 2012), we visualized these partial correlations as networks where nodes represent the biomarkers (i.e., glucose, ketones, etc.) and edges, or lines between nodes, represent the strength and direction of the relationships. We generated separate networks for the control group (n = 24) and the heated group (n = 25). To better understand which relationships were altered by heat, we calculated a ‘difference matrix' by subtracting the control network from the heat network. This method allowed us to visualize the network and inspect whether relationships were strengthened or weakened by the heat exposure.

We assessed global strength, or total connectivity, and network invariance, or structure of the network, using the NetworkComparisonTest package (van Borkulo et al. ²⁰²¹). Global strength was defined as the sum of the absolute values of all edge weights. This score served as a gauge for the how closely these markers are linked, reflecting the degree of physiological coordination during the heat challenge. Network invariance tested whether the overall pattern of connections differed between groups. Statistical significance was determined using a permutation test with 1,000 iterations.

Finally, we estimated sex‐specific heat networks to determine if heated males and females are responding differently to acute heat exposure. However, due to the limited sample size, we opted to use standard correlations rather than partial correlations. This is because standard correlations evaluate relationships between two variables at a time rather than controlling for the entire network simultaneously, this approach preserved sufficient statistical power to compare the sexes.

3. Results

3.1. Body Temperature

Core maximum body temperature was not impacted by the sex by treatment interaction (F = 0.15, p = 0.7), and so the interaction was removed from the model. As expected, heated individuals had significantly higher maximum body temperatures compared to the control individuals (F = 52.39, p < 0.001). On average, the heated birds had body temperatures 2.01°C higher than the control birds (heat: 44.39°C ± 0.32; control: 42.38°C ± 0.44; mean±95% confidence intervals; Figure 2). Sex had no effect on body temperature (F = 0.37, p < 0.54).

Figure 2.

Body temperature across treatments. Larger, black diamonds and error bars represent the mean and 95% confidence limits, respectively. The smaller points represent each individual, color represents treatment (control: grey and heat: red), and shape represents sex (female: circles and male: triangles). Different letters above each group represent statistically significantly different groups (p < 0.05). Sample size for treatment, including both sexes, is shown below the significance letters.

3.2. Corticosterone

Corticosterone was significantly impacted by the treatment by time point interaction (χ² = 7.08, p < 0.01), but sex had no impact on corticosterone levels (χ² = 0.004, p = 0.95). The post‐hoc analysis revealed that individuals from both heated and control treatments at the pre‐time point had the same corticosterone levels (p = 1.0). At the post‐time point, both the control and heated individuals increased corticosterone relative to the pre‐time point (Table 1). However, the heated group had higher levels of corticosterone compared to the control group at the post‐time point (p = 0.01, Figure 3).

Table 1.

Blood physiological variables in male and female zebra finches across treatments (control and heat) and time point (pre and post). Values represent the mean ± standard deviation, with sample sizes in parenthesis.

Treatment	Time point	Sex	Glucose (mg/dL)	Ketones (mmol/L)	Glucocorticoids (ng/mL)	DNA damage (AU)
Control	Pre	Female	214.3 ± 36.18 (n = 20)	0.45 ± 0.11 (n = 20)	1.13 ± 1.08 (n = 19)	0.75 ± 0.41 (n = 20)
		Male	215.63 ± 35.35 (n = 19)	0.45 ± 0.12 (n = 17)	1.72 ± 1.65 (n = 15)	0.7 ± 0.24 (n = 14)
	Post	Female	191.11 ± 37.89 (n = 18)	0.40 ± 0.09 (n = 18)	2.73 ± 2.52 (n = 18)	0.85 ± 0.62 (n = 18)
		Male	199.1 ± 32.59 (n = 18)	0.54 ± 0.17 (n = 18)	2.27 ± 2.58 (n = 18)	0.91 ± 0.58 (n = 18)
Heat	Pre	Female	225.75 ± 49.52 (n = 23)	0.45 ± 0.12 (n = 22)	1.34 ± 1.12 (n = 22)	0.77 ± 0.50 (n = 22)
		Male	216.14 ± 32.96 (n = 21)	0.42 ± 0.13 (n = 21)	1.29 ± 0.95 (n = 19)	0.73 ± 0.30 (n = 20)
	Post	Female	248.08 ± 65.70 (n = 19)	0.55 ± 0.22 (n = 18)	5.60 ± 7.13 (n = 19)	0.79 ± 0.39 (n = 19)
		Male	256.32 ± 64.62 (n = 17)	0.54 ± 0.19 (n = 17)	4.39 ± 2.97 (n = 15)	0.70 ± 0.37 (n = 16)

Figure 3.

Corticosterone levels across treatments and time points. Larger, black diamonds and error bars represent the mean and 95% confidence limits, respectively. The smaller points represent each individual, color represents treatment (control: grey and heat: red), and shape represents sex (female: circles and male: triangles). Different letters above each group represent statistically significantly different groups (p < 0.05) determined by post‐hoc testing. Sample size for treatment and time point, including both sexes, is shown below the significance letters.

3.3. Blood Metabolites

Glucose was significantly affected by the treatment by time point interaction (χ² = 13.74, p < 0.001). However, the sex by time point interaction did not impact glucose levels (χ² = 0.87, p = 0.35). The post‐hoc analysis revealed that individuals from the post‐heat group had higher blood glucose levels compared to all other treatment and time point combinations (all p < 0.01, Figure 4).

Figure 4.

Glucose levels across treatments and time points. Larger, black diamonds and error bars represent the mean and 95% confidence limits, respectively. The smaller points represent each individual, color represents treatment (control: grey and heat: red), and shape represents sex (female: circles and male: triangles). Different letters above each group represent statistically significantly different groups (p < 0.05) determined by post‐hoc testing. Sample size for treatment and time point, including both sexes, is shown below the significance letters.

Ketone levels were significantly affected by the treatment by time point interaction (χ² = 6.50, p = 0.01) and the sex by time point interaction (χ² = 4.91, p = 0.03). The post‐hoc analysis revealed that individuals from the post‐heat group had higher blood ketone levels compared to all other treatment and time point combinations (all p < 0.04, Figure 5). The post‐hoc analysis for the sex by time point interaction revealed that ketone levels increased in males from the pre‐ to post time point (p < 0.01), while there was no significant increase in females (p = 0.99). However, females did not differ from the males at any time point (all p > 0.05).

Figure 5.

Ketone levels across treatments and time points. Larger, black diamonds and error bars represent the mean and 95% confidence limits, respectively. The smaller points represent each individual, color represents treatment (control: grey and heat: red), and shape represents sex (female: circles and male: triangles). Different letters above each group represent statistically significantly different groups (p < 0.05) determined by post‐hoc testing. Sample size for treatment and time point, including both sexes, is shown below the significance letters.

3.4. DNA Damage

DNA damage was marginally affected by the treatment by time point interaction (χ² = 3.76, p = 0.053). Sex had no impact on DNA damage (χ² = 0.21, p = 0.65). The post‐hoc analysis revealed that groups were not significantly different from each other (all p > 0.2).

3.5. Physiological Network

To evaluate how our physiological variables interact under different conditions, we estimated partial correlation networks for the control and heat treatment groups using Gaussian Graphical Models (Figures 6A, B) and calculated global network connectivity. Recall, the global network connectivity value is the sum of the absolute value of edge weights (i.e., the lines between nodes in Figure 6). So, we are calculating the intensity of all the relationships between variables in the control and heat treatment groups. We found that global network connectivity showed an increase in the heat treatment group (Network Global Strength: 2.414) compared to the control group (Network Global Strength: 1.516). This represents a 59.2% increase in global strength, suggesting that under heat stress, our physiological variables become more coupled. In other words, these relationships are becoming stronger in response to heat.

Figure 6.

Networks displaying the physiological relationships for the control group (A), heat group (B), and the difference between the networks for controls and heat group (heat network minus the control network; C). The numbers on the edges (i.e. lines between nodes) represent the partial correlation coefficient. Positive correlations are represented by blue edges and negative correlations are red. The thicker the edge, the stronger the correlation.

A permutation‐based network comparison test indicated that both global strength (S = 0.016, p = 0.086) and network invariance (M = 0.016, p = 0.086) showed a marginally significant trend towards differing in physiological coupling between the heat and control group. A qualitative analysis of the difference matrix (heat ‐ control) revealed that the increased connectivity was driven primarily between glucose and ketones. While under control conditions, the glucose and ketone levels are positively correlated, the relationship becomes negatively correlated under heat (Figure 6C).

We also compared heated male and female networks. Heated males (Network Global Strength: 3.262) had an increased global network connectivity relative to heated females (Network Global Strength: 2.325). This represents a 40.3% increase in global strength. However, the permutation‐based network comparison test indicated that neither the global strength (S = 0.94, p = 0.24), nor the network invariance (M = 0.93, p = 0.17) differed between sexes. Collectively, this result suggests that heat impacts the physiological coupling, and in our study, response to heat is largely consistent across both males and females.

4. Discussion

In this study, we set out to understand the physiological effects of a 5‐h acute heat exposure on blood biomarkers, and whether the response differed between sexes. Our findings showed that an acute heat exposure increased maximum body temperature and increased blood concentrations of corticosterone, glucose, and ketones. Interestingly, DNA damage in red blood cells was not significantly changed after 5 h of acute heat exposure. Additionally, we found that the physiological network becomes more coupled under heat, suggesting that there are many physiological variables that are working together to ensure organismal survival during acute heat exposure. Between sexes, we found no differences in body temperature nor differences in the physiological response. However, males did increase ketone levels from the pre‐ to post‐time point regardless of treatment. It should be noted that all birds had ad libitum access to food and water throughout the temperature treatment. So, individual variation in food and water consumption may have introduced metabolic or thermoregulatory variance. For example, a bird that drank more during heat treatment may have greater water stores to decrease body temperature through evaporative cooling (McKechnie et al. ²⁰¹⁶; Albright et al. ²⁰¹⁷; Cooper et al. ²⁰²⁰). Similarly, variation in food consumption may alter metabolic pathways (e.g., shifting between glycolysis and beta oxidation) during treatment. However, regardless of ad libitum access to food and water, heated individuals still increased body temperature, corticosterone, glucose, and ketone levels. Overall, our results indicate consistency across sexes in their response to an acute heat exposure, and we demonstrate that acute heat exposure alters and strengthens physiological relationships.

Our findings align with the growing consensus that metabolic and stress‐related variables increase with hotter temperatures. A meta‐analysis revealed that 76% of studies found animals, across all vertebrate taxa, increased glucocorticoids in response to temperature change (De Bruijn and Romero ²⁰¹⁸, also see Jessop et al. ²⁰¹⁶). Broiler chickens increase glucose and glucocorticoids after a heat exposure of 35°C for 8 h (Beckford et al. 2020). Japanese quails that were exposed to longer‐term heat stress (34°C for 4 h a day for ten days) increased blood metabolites, such as the ketone acetoacetic acid (Pu et al. 2019). Wild zebra finches that were exposed to a maximum daily temperature above 39°C for three consecutive days had higher blood glucose levels after a standardized capture and restraint challenge (Cooper et al. 2020). Collectively, these findings suggest that metabolic hormones and metabolites are increasing in response to heat across taxa. Importantly, these studies demonstrate that variables such as glucocorticoids, glucose, and ketones are consistently elevated across differing intensities and durations of heat. These results suggest increased glucocorticoids and blood metabolites are a conserved response to elevated temperatures.

While blood metabolites appear to increase consistently under heat stress, the impact of heat on oxidative damage has mixed results across broad taxa, including ectothermic and endothermic species. Understanding oxidative damage has been an area of interest across many fields. Oxidative damage, especially to DNA, has been linked to deleterious impacts on an organism's growth, reproduction, and life span (Harman 1956; Monaghan et al. ²⁰⁰⁹; Metcalfe and Alonso‐Alvarez ²⁰¹⁰; Meniri et al. ²⁰²²). Thus, understanding how exposure to hot temperatures affects oxidative damage dynamics can provide important life history information. While our study was only 5 h in duration, increases in DNA damage have been observed over shorter time periods. For example, endothermic storm petrel nestlings that were exposed to a 20‐min standardized capture and restraint stressor had increased levels of 8‐OHdG in their red blood cells (Lichtner et al. 2025). Additionally, acute thermal shifts over the span of just minutes show increased levels of 8‐OHdG in the red blood cells of ectothermic lizards (Haussmann et al. 2025). Some studies show that various thermal intensities and durations increase oxidative damage across tissue types and macromolecules. For example, endothermic chickens housed at 32°C for 7 days exhibited increased plasma concentrations of lipid peroxidation (malondialdehyde) and DNA damage (8‐OHdG). In the same study, chickens exposed to heat had increased levels of malondialdehyde, 8‐OHdG, and protein carbonyls in both breast and thigh muscle (Huang et al. 2015). Ectothermic invertebrate oysters exposed to both 28°C and 32°C for 7 days had higher levels of DNA damage (8‐OHdG and γH2AX, a marker for double‐strand breaks) compared to oysters exposed to 24°C (Rahman et al. 2023). In contrast, other studies, including ours, show no changes in oxidative damage after heat exposure. For example, Chinese soft‐shelled turtles, another ectothermic species, that were exposed to 33°C (15°C higher than control turtles) for 12 h found no changes in malondialdehyde in the plasma, brain, liver, and kidney (Zhang et al. 2019). Moreso, Zhang et al. (2019) found lower levels of malondialdehyde in the spleen of the heated turtles compared to the control group. Another study in Asian yellow pond turtles found no differences in malondialdehyde levels in the liver and skeletal muscle between the control and the heated group that was exposed to a 7‐day, 35°C heatwave (Li et al. 2021). The studies highlighted above show that heat exposure either increases or does not affect damage markers, and this could be for many reasons, such as the organism's thermoregulatory strategy, evolutionary history, and intensity of the stressor. The mixed results may also be due to heat having varying effects on types of macromolecules across various tissues. For example, four‐striped field mice exposed to 41°C for 6 h showed no changes in protein carbonyl levels in the brain, kidney, and liver, nor in lipid peroxidation (malondialdehyde) in the brain and liver. However, malondialdehyde levels in the kidney were increased significantly in the heated group compared to the control (25°C) group (Jacobs et al. 2020). A study on wall lizards found that a 4°C increase in brumation temperature for 3.5 months had no impact on plasma lipid peroxidation (malondialdehyde) levels, but the same temperature regime showed a trend of increased DNA damage (8OHdG) in skeletal tissue (Raselimanana et al. 2025). So, in future studies, it is important to consider the type of damage (lipid, protein, or DNA) and the tissue that may be most susceptible to heat.

We explicitly measured a broad spectrum of DNA lesions, including oxidative lesions, alkylating lesions, cross‐linked lesions, uracil, abasic sites, and strand breaks, as potential markers of oxidative stress. Our results show that a 5‐h heat exposure did not increase DNA damage in red blood cells, but several possible mechanisms may protect against DNA damage. Ketones have been demonstrated to act as antioxidants and signaling molecules to protect against DNA damage (Puchalska and Crawford 2017; Elamin et al. ²⁰¹⁸; Pinto et al. ²⁰¹⁸). One function of ketones, including ß‐hydroxybutyrate, is to scavenge hydroxyl radicals and other reactive oxygen species that cause damage to macromolecules (Maalouf et al. 2007; Haces et al. ²⁰⁰⁸; Greco et al. ²⁰¹⁶). Ketones also have many signaling properties that communicate where repair enzymes and proteins are needed (Shimazu et al. 2013). For example, high circulating ketones can be associated with increased poly (ADP‐ribose) polymerases (Elamin et al. 2018). Poly (ADP‐ribose) polymerases sense DNA base lesion nicks and strand breaks and signal for the DNA damage to be repaired through base excision or double‐strand break repair pathways (Grube and Bürkle 1992; Bürkle and Virág ²⁰¹³).

During the 5 h of heat in our study, birds increased blood concentrations of ß‐hydroxybutyrate, which could have acted as antioxidants and signaling molecules, reducing the formation of DNA adducts or enhancing DNA repair. Ketones are only one possible mechanism that may protect DNA from damage during heat stress. Other studies in zebra finches have found increased heat shock proteins (Hoffman et al. 2024), increased mitochondrial LEAK, which may allow for lowered reactive species production (Ton et al. 2021), and in broiler chickens increased levels of superoxide dismutase (Habashy et al. 2019). Future work is needed to determine if reactive species are scavenged under these conditions to maintain genomic stability or if both scavenging and increases in DNA repair machinery protect genomic stability. Maintaining genomic integrity is essential to life, so during an acute heat exposure, an organism will likely use multiple cellular pathways to ensure DNA integrity is maintained and remains undamaged.

Of course, DNA protection pathways represent just one component to a much broader, system wide response to thermal stress. Multiple relationships between our physiological variables are important to consider, and graphical modeling is a valuable tool to understand these relationships. While our linear models show how multiple variables increase in heat, we also found that heat is causing our physiological network to become more connected. In other words, the correlations, both positive and negative, between our variables became stronger. Meaning birds that were heated had a system‐wide response to the temperature exposure. From our Gaussian Graphical Models, we can see the strongest relationships after a heat exposure are between body temperature and glucose, as well as body temperature and ketones, suggesting that the higher body temperature an individual has, the more ketones or glucose they are putting into their circulation. The other interesting relationship shown from our Gaussian Graphical Models is the negative correlation between glucose and ketones after heat exposure. At the onset of the heat exposure, birds are likely mobilizing glucose into the bloodstream to provide energy to the body (Naga Raja Kumari and Narendra Nath ²⁰¹⁸). However, if birds are kept at high temperatures, it is possible they exhaust their glucose stores and use ketones to fuel their metabolism, as seen in migratory birds (Frias‐Soler et al. ²⁰²¹). It is possible that there is a certain span of time that birds are able to maintain glucose levels, depending on the magnitude and duration of heat (Siddiqui et al. 2021).

Another potential, non‐mutually exclusive, explanation for the relationship between glucose and ketones is the internal body temperature. Body temperature may serve as a threshold that communicates to the organism when to switch glucose metabolism to ketone metabolism. For example, mice studies show that body temperature, not ambient temperature, is the primary driver of glucose metabolism (Lee et al. 2025). Lee et al. (2025) demonstrated glucose metabolism changes when mice have decreased body temperatures, but it is possible that increasing body temperature could also impact an organism's glucose metabolism and metabolic fuel source. Measuring internal body temperature provides information about an individual's ability to regulate body temperature under thermal stress. In fact, our data show variation in body temperature within the heated group, ranging from 41.5°C to 47.5°C, and that body temperature is related to numerous physiological variables. Future studies determining the basis for this individual variation in body temperature regulation may help understand the factors contributing to vulnerability to thermal stress.

5. Conclusion

As an arid‐adapted species, wild zebra finches can withstand a wide variety of ecological conditions, including temperatures ranging from −5.2°C to 46.2°C. (Griffith et al. 2025). Previous studies, as well as this study, show zebra finches have the physiological plasticity that aids in surviving hot temperatures (Hoffman et al. 2018, ²⁰²⁴, 2025; Cooper et al. ²⁰¹⁹, ²⁰²⁰; Ton et al. ²⁰²¹; Pessato et al. ²⁰²³). However, understanding how thermally resilient organisms cope with sudden, acute heat stress remains critical, particularly because abrupt temperature spikes can be lethal for arid adapted species (McKechnie and Wolf ²⁰¹⁰; Conradie et al. ²⁰¹⁹; McKechnie et al. ²⁰²¹). To a zebra finch, these acute thermal events present a challenge to survival. To counteract this risk of mortality, environmental and selective pressures may have uniquely adapted the zebra finch to actively defend against cellular and DNA damage.

Our results may suggest that zebra finch blood cells can avoid DNA damage during acute heat exposure, or that they can rapidly repair the DNA damage so it does not accrue. These findings are an important step toward better understanding the physiological underpinnings of the response to acute heat stress. Future studies should aim to determine how other physiological variables, such as membrane fluidity and the capacity to repair oxidative damage, may be impacted by heat stress. Finally, understanding how extreme thermal exposure, like temperature near the species' critical thermal maximum, may, or may not, affect males and females differently is important in predicting an impact of extreme heat events on population dynamics. This is especially true as some birds show increased body temperatures during reproductive seasons (Nilsson and Nord 2018), leaving them potentially vulnerable to rising ambient temperatures. It is well documented that Australian temperatures will continue to rise in the coming years (Trancoso et al. 2020) and understanding how populations will respond and adapt to these increased temperatures should remain a priority.

Ethics Statement

All the animal husbandry and experimental protocols found in this manuscript were approved by Auburn University's Institutional Animal Care and Use Committee (approval number:2024‐5510).

Conflicts of Interest

The authors declare no conflicts of interest.

Supporting information

Supporting File

Haussmann, B. D. , McGrath M. R., Vo D. H., et al. 2026. “Acute Heat Exposure Upregulates Zebra Finch Physiology While Avoiding DNA Damage Across Both Sexes.” Journal of Experimental Zoology Part A: Ecological and Integrative Physiology 345: 859–870. 10.1002/jez.70120.

Data Availability Statement

The data and code used for analyses are available at: https://github.com/bdh0075/Blerd---AcuteHeat2.git.