Skip to main content
NCBI home page
Poultry Science logoLink to Poultry Science
. 2024 Jul 17;103(10):104112. doi: 10.1016/j.psj.2024.104112

Effects of long-time and short-time heat stress on the meat quality of geese

Ying Yang †,‡,1, Shuai Zhang †,‡,1, Haoqi Peng †,‡, Genghua Chen †,‡, Qinghua Nie *,†,‡, Xiquan Zhang *,†,‡, Wen Luo *,†,‡,2
PMCID: PMC11343063  PMID: 39106699

Abstract

This investigation sought to reveal the effects of heat stress on the meat quality of geese. Wuzong geese were subjected to heat stress at 35°C for 25 d or 4 h to examine different heat stress time on meat quality. Short-time heat stress reduced muscle drip loss and meat color L* value while increasing pH value and meat color a* and b* values. Long-time heat stress decreased body weight and increased leg muscle pH value and meat color b* value. Amino acid profile of geese breast muscle revealed that both LHS and SHS can induce L-Cystine but reduced L-Cystathionine, which were positive correlated with cooking loss and meat color lightness, respectively. Lipidome analysis indicated that heat stress would alter the synthesis of unsaturated fatty acids, and the difference between LHS and SHS on lipids mainly focused on Hex1Cer and TG. Non-target metabolome analysis indicated effects of heat stress on Glycerolipid metabolism, Arachidonic acid metabolism, and Pyrimidine metabolism. Proteome analysis showed that heat stress mainly affects cellular respiration metabolism and immune response. These findings highlight the diverse effects of heat stress on meat quality, amino acid composition, lipidome, metabolome, and proteome in geese.

Key words: heat stress, meat quality, goose, multiomics

INTRODUCTION

Geese, a species of waterfowl, have been domesticated for their meat, eggs, and feathers (Zhu et al., 2021). Goose meat has a rich culinary history and is enjoyed in various preparations such as roasted, braised, and stewed. In recent years, the market share and sales of goose meat have shown a steady increase, particularly in China (Weng et al., 2021). Compared to chicken or turkey meat, goose meat typically exhibits a darker color, a more robust flavor, and a denser, chewier texture (Weng et al., 2021). Goose meat has long been recognized as a valuable source of protein, essential vitamins, and minerals, and has been a staple in various cultures for centuries. One notable health benefit of goose meat is its high content of healthy fats, including monounsaturated and polyunsaturated fats (Nemati et al., 2020). Both monounsaturated and polyunsaturated fats have been associated with a reduced risk of heart disease and stroke (Lada and Rudel, 2003; Larsson et al., 2012). Furthermore, the omega-3 fatty acids present in goose meat may contribute to the reduction of inflammation in the body (Massaro et al., 2010), which is linked to various chronic diseases.

Heat stress occurs when the body fails to regulate its internal temperature effectively in response to elevated environmental temperatures. This condition can have various detrimental effects on bodily functions, including alterations in cardiovascular, renal, and immune function (Crandall and Wilson, 2015; Gonzalez-Rivas et al., 2020; Knochel et al., 1974). The harmful impact of heat stress on the body is attributed to a range of underlying mechanisms. One primary mechanism involves the activation of the body's stress response system, resulting in the release of stress hormones like cortisol and adrenaline (Mazlomi et al., 2017). These hormones can elevate heart rate, blood pressure, and respiration, thereby placing additional strain on the cardiovascular system (Tianlong and Sim, 2019; Wang et al., 2022). Moreover, the elevated temperatures associated with heat stress can promote the production of reactive oxygen species, which have the potential to inflict damage on cells and tissues throughout the body (Slimen et al., 2014).

Heat stress poses a common challenge for livestock and poultry producers, especially in hot and humid environments. This environmental condition can significantly impact the quality of meat derived from these animals, affecting factors such as color, texture, flavor, and nutritional value (Gonzalez-Rivas et al., 2020; Zaboli et al., 2019). Studies have revealed that heat stress can induce heightened levels of oxidative stress, leading to lipid oxidation and the formation of reactive oxygen species. Consequently, meat may experience discoloration, appearing darker and losing its natural pink hue (Gonzalez-Rivas et al., 2020). In the context of growing Iberian pigs, chronic exposure to high temperatures did not significantly affect pH or meat color but exhibited positive effects on lightness, intramuscular fat content, and drip losses (Pardo et al., 2021). Conversely, broilers subjected to chronic heat stress demonstrated increased drip loss, cooking loss, shear force, and hardness, along with decreased pH and redness (Liu et al., 2022). However, the specific effects of heat stress on the meat quality of geese have yet to be systematically studied.

In order to assess the impact of temperature conditions on the quality of goose meat, 2 forms of heat stress was conducted: long-time heat stress (LHS) and short-time heat stress (SHS). The SHS was designed to simulate the heat stress experienced by geese when they are transported from the breeding base to the slaughterhouse, a common occurrence in southern China. The LHS aimed to simulate the heat stress of geese in hot summer climate in South China. To comprehensively evaluate the meat quality of geese, a range of analytical techniques were employed, including conventional meat quality measurements, non-targeted metabolomics, lipidomic profiling, amino acid profiling, and proteomics. These investigations will enhance our understanding of the effects of heat stress on goose meat quality, providing valuable insights for maintaining the quality and safety of meat for human consumption.

MATERIALS AND METHODS

Animals and Treatment

The experimental procedures were conducted following the guidelines and regulations set by the Institutional Animal Care and Use Committee of South China Agricultural University (SCAU-2022A031). The study utilized 12 commercially raised female Wuzong geese with similar body weight and healthy condition, aged 100 d, obtained from a poultry market in Guangdong Province. These geese were divided into three groups, with each group consisting of four geese. The first group, referred to as the NC group, was raised at a room temperature of 25°C for 21 d. The second group, named the LHS group, experienced 35°C heat stress for 4 h a day for 21 d, followed by 25°C for the remaining time. The third group, known as the SHS group, was kept at 25°C for 21 d and subjected to 35°C heat stress for 4 h prior to slaughter (Figure 1A). The animals were housed in air-conditioned rooms equipped with thermometers to maintain optimal conditions, while the heat stress sessions occurred in a separate enclosed room. A heater was utilized to raise the temperature to 35 degrees, after which the geese were transferred to the designated heat stress room. After heat stress, the geese were stunned by head-touching on the surface of an electrified pool (36 V), and then euthanized while unconscious by jugular vein dissection. Individual samples of breast muscle (the left pectoralis major muscles) were collected immediately for subsequent measurements of meat quality. A portion of the muscle sample from the same area is immediately snap-frozen in liquid nitrogen and stored at -80°C for further analysis.

Figure 1.

Figure 1

Open in a new tab

Long-time and short-time heat stress alter the meat quality of geese. (A) Experimental design flow chart. (B) Live body weight of geese. (C) 24 h drip loss of geese skeletal muscle. (D) Cooking loss of geese skeletal muscle. (E) PH value of geese skeletal muscle. (F) Shear force of geese skeletal muscle. (G) Meat color value of geese skeletal muscle. *p < 0.05, **p < 0.01. n = 4.

Metabolomic Analysis for LC-MS

The breast muscle sample stored at -80°C was thawed on ice. An UHPLC system (1290 Infinity LC, Agilent Technologies) coupled with a quadrupole time-of-flight mass spectrometer (AB Sciex TripleTOF 6600) were used for HPLC analysis at Shanghai Applied Protein Technology Co., Ltd. After mass spectrometry, raw data was converted to MzXML format using Proteo Wizard. XCMS was used for peak extraction and alignment, followed by peak area correction and filtering using the "SVR" method. Metabolite identification was achieved by comparing them to an in-house database established with authentic standards.

Amino Acid Profilings Analysis

The sample extracts were analyzed using an LC-ESI-MS/MS system (UPLC: ExionLC AD, MS: QTRAP 6500+ System). The AB 6500+ QTRAP LC-MS/MS System with ESI Turbo Ion-Spray interface was used for ESI-MS/MS analysis. The instrument operated in positive and negative ion modes, controlled by Analyst 1.6 software (AB Sciex). ESI source parameters included ion source - turbo spray, source temperature - 550°C, ion spray voltage (IS) - 5500 V (Positive) and -4500 V (Negative). The curtain gas (CUR) was set at 35.0 psi. DP and CE values for MRM transitions were optimized, with specific sets monitored based on amino acid elution periods.

Lipidomic Analysis

LC analysis utilized a Vanquish UHPLC System (Thermo Fisher Scientific, Seattle, WA), while lipid molecule detection was performed on a Q Exactive instrument (Thermo Fisher Scientific). For mass spectrometric analysis, ESI-MSn experiments were conducted in positive (spray voltage: 3.5 kV) and negative (spray voltage: 2.5 kV) modes. Data-dependent acquisition (DDA) MS/MS experiments used HCD scan with a normalized collision energy of 30 eV. Dynamic exclusion was implemented to remove unnecessary information from the MS/MS spectra.

Protein extraction and proteome analysis

LC utilized a nanoElute UHPLC system (Bruker Daltonics, Germany). Approximately 200 ng of peptides were separated over 60 minutes at a flow rate of 0.3 μL/min. A reverse-phase C18 column with a CaptiveSpray Emitter (25 cm x 75 μm ID, 1.6 μm, Aurora Series with CSI, IonOpticks, Australia) was used for separation. The LC system was coupled online to a timsTOF Pro2 instrument (Bruker Daltonics, Germany) through a CaptiveSpray nano-electrospray ion source (CSI). MS raw data were analyzed using DIA-NN (v1.8.1) with a library-free approach. Deep learning algorithms and the SwissProt database (20425 entries) were employed to generate a spectra library. The DIA data was used to create a spectral library using the Minimum Biased Reference (MBR) option. The library was then utilized to reanalyze the data. To ensure high confidence, the False Discovery Rate (FDR) was adjusted to be less than 1% at the protein and precursor ion levels. Identified spectra were used for quantification analysis.

Correlation and Network Analysis

Correlation analysis between different omics datasets was performed using psych v2.3.9. This software calculated correlation coefficients and correlation significance tests for various molecules, employing the "pearson" method and adjusting for false discovery rate ("fdr") using the "adjust" parameter. A correlation with a p-value less than 0.05 was considered statistically significant. To visualize the correlation patterns, correlation heat maps were generated using Heatmap v1.0.12. In these heat maps, correlations with a p-value less than 0.001 were denoted as "***", those with a p-value less than 0.01 as "**", and those with a p-value less than 0.05 as "*". Moreover, Cytoscape was utilized to construct interaction networks between various molecules.

Statistical Analysis

All results are represented as mean ± sem. For the statistical analysis of the 2 contrasts, it was used an independent sample t-test through SPSS. p < 0.05 was considered to be statistically significant. ∗p < 0.05; ∗∗p < 0.01.

RESULTS AND DISCUSSION

Long-Time and Short-Time Heat Stress Alter the Meat Quality of Geese

To assess the impact of long-time heat stress (LHS) and short-time heat stress (SHS) on the quality of goose meat, it was conducted an analysis of meat quality data from different treatment groups (Figure 1A). Previous research has indicated that heat stress in chickens results in body weight loss and various physiological changes (Wastiet al., 2020). Our findings revealed that LHS caused a nonsignificant weight loss in geese (Figure 1B), possibly due to the relatively shorter duration of the heat stress. On the other hand, SHS had a more pronounced effect on meat quality compared to LHS (Figures 1C–1G). SHS not only reduced the 24-h drip loss of leg muscle (Figure 1C) and brightness (L* value) of leg muscle (Figure 1G), but also significantly increased the pH value of breast muscle (Figure 1E), breast muscle color a* value, and leg muscle color b* value (Figure 1G). LHS primarily increased the pH value of leg muscle and the color b* value of leg muscle (Figures 1E and 1G). Significant differences between LHS and SHS were mainly observed in terms of 24-hour drip loss and breast muscle color a* value (Figures 1C and 1G). It is worth noting that the results demonstrated that both SHS and LHS can lead to an increase in the pH of goose meat, which contradicts some findings regarding heat stress in chicken meat. In chickens, chronic heat stress (32°C) typically results in a decrease in meat pH (Li et al., 2023). However, heat stress can also elevate the PH value in turkey (Chiang et al., 2008), suggesting that the impact of heat stress on meat pH may be influenced by factors such as species, nutritional status, slaughtering techniques, and environmental conditions (Bejaoui et al., 2023). Overall, these results indicate that both long-time and short-time heat stress can alter the quality of goose meat, with SHS having a more pronounced effect compared to LHS.

Effects of Heat Stress on Amino Acids and Their Derivatives in Goose Skeletal Muscle

To investigate the impact of heat stress on the nutritional composition of goose meat, the amino acid profile of goose meat subjected to LHS and SHS was analyzed. A comprehensive identification of 79 amino acids and their derivatives was conducted (Figure 2A and Table S1). Glutathione oxidized exhibited the highest content of amino acids in goose meat, followed by succinic acid, creatine phosphate, and anserine (Figure 2B). Principal component analysis (PCA) revealed minimal differences in muscle amino acids and their derivatives between the 2 stress groups (Figure 2c), suggesting that heat stress had a limited impact on the content of amino acids and their derivatives in goose meat. This finding contrasts with a previous study that demonstrated impaired amino acid metabolism in broiler chickens under heat stress (Ma et al., 2021). Pairwise comparison highlighted only a few amino acids and their derivatives with differential expression between the groups (Figure 2B). Specifically, there were seven significantly differentially expressed amino acids between LHS and the control group (NC), as well as seven significantly differentially expressed amino acids between SHS and NC (Figure 2E). Both L-Cystine and L-Cystathionine exhibited differential expression in both LHS and SHS, indicating their sensitivity to heat stress. The amino acids and their derivatives with significant differences between groups were further classified into 10 subclasses based on their expression trends (Figure 2F). N8-Acetylspermidine, Kinurenine, and L-Cystine showed a significantly up-regulated trend in the heat stress group, while L-Cystathionine was the only amino acid derivative that showed significant down-regulation in the heat stress group (Figure 2F). The content of amino acids and their derivatives was correlated with meat quality traits, revealing significant correlations between 19 amino acids and their derivatives and meat quality traits (Figure 2G). Notably, heat stress-induced L-Cystine exhibited a positive correlation with cooking loss, while heat stress-repressed L-Cystathionine showed a positive correlation with the L* value, indicating color lightness (Figure 2G). L-Cystine has been reported to contribute to meat flavor, antioxidant capacity, texture, and shelf life (Yin et al., 2016; Additives et al., 2020; Fu et al., 2022a), making it an important component for understanding and optimizing meat quality. The specific impact of L-Cystathionine on meat quality, as part of the metabolic pathway related to L-Cysteine, has not been extensively studied or documented. Additionally, a correlation analysis between all amino acids and their derivatives was conducted, revealing significant correlations among many amino acids and their derivatives (Figure 2H). In conclusion, this study demonstrates discernible effects of heat stress on amino acid metabolism in goose breast muscle, and identifies correlations between the content of certain amino acids and their derivatives with meat quality traits in geese.

Figure 2.

Figure 2

Open in a new tab

Effects of heat stress on amino acids and their derivatives in goose skeletal muscle. (A) Expression heat map of muscle amino acids and their derivatives between different treatment groups. (B) The top 20 most abundant amino acids in geese breast muscle. (C) Principal component analysis (PCA) of identified amino acids and their derivatives between different comparative group. (D) Venn diagram of the differentially expressed amino acids and their derivatives in breast muscle between different comparative group. (e) Violin diagram of amino acids and their derivatives with significant differences between different comparative groups. (f) K-Means diagram of differential amino acids and their derivatives. (g) Correlation heatmap between differentially expressed amino acids and their derivatives and meat quality traits. (h) Correlation heatmap between amino acids and their derivatives. *p < 0.05, **p < 0.01. n = 4.

Lipidomic Analysis Reveals That Heat Stress Induces Changes in Lipid Metabolites in Goose Muscle

Lipid metabolites play a crucial role as flavor precursors (Fu et al., 2022b). To investigate the impact of heat stress on the muscle lipid composition of geese, a lipidomic analysis was conducted. A total of 2289 lipids were detected in the skeletal muscle of geese (Figure 3A and Table S2), which can be categorized into ten different types: triglyceride (TG, 22.42%), phosphatidylcholine (PC, 21.78%), phosphatidylethanolamine (PE, 13.07%), methyl-phosphatidylcholine (MePC, 8.59%), cardiolipin (CL, 7.78%), diacylglycerol (DG, 6.16%), ceramide (Cer, 5.87%), sphingomyelin (SM, 4.94%), hexosylceramide (Hex1Cer, 4.82%), and dimethyl phosphatidylethanolamine (dMePE, 4.59%) (Figure 3B). Orthogonal Projections to Latent Structures Discriminant Analysis (OPLS-DA) demonstrated that heat stress under different conditions could induce changes in the lipid profile of goose muscle (Figure 3C). A total of 37 significantly altered lipid molecules were identified between LHS and the control group (Figure 3D), with 15 lipids downregulated and 22 lipids upregulated in LHS (Figure 3E). Between SHS and the control group, 44 lipid molecules showed significant changes, with 24 lipids downregulated and 20 lipids upregulated in SHS (Figure 3F). Furthermore, a greater number of different lipid molecules were observed between the LHS and SHS groups, with 23 lipids upregulated and 75 lipids downregulated in SHS (Figure 3G). Subsequently, the correlation between lipid molecules and meat quality was examined (Figure 3H). The results revealed significant positive correlations between several types of triglycerides (TG) and drip loss and skin color a* value. Additionally, there was a significant positive correlation between polyunsaturated diacylglycerol (DG) with more than 24 carbon atoms and skin color a* value (Figure 3H).

Figure 3.

Figure 3

Open in a new tab

Lipidomic analysis reveals that heat stress induces changes in lipid metabolites in goose muscle. (A) Expression heat map of muscle lipidome between different treatment groups. (B) Pie chart of the proportion of different types of lipid molecules in geese skeletal muscle. (C) PCA of identified lipid molecules between different comparative group. (D) Venn diagram of the differential lipid molecules in breast muscle between different comparative group. (E–G) Heat maps of differential lipid molecules between different treatment groups. (H) Correlation heatmap between differentially expressed lipid molecules and meat quality traits. n = 4.

Subsequently, the structural characteristics of the lipidome was analyzed based on lipid class, focusing on fatty acid (FA) carbon number and saturation level. In the LHS group compared to the control group, we observed a decrease in AcCa, BisMePA, CerG3GNAc2, Hex2Cer, LPC, PG, and PS, while Cer, Hex1Cer, MePC, PA, PC, SM, and TG showed an increase (Figure S1A). Of particular note, TG exhibited a significantly higher abundance in the LHS group and represented the largest proportion of lipid species. Conversely, in the SHS group compared to the control group, it was observed a decrease in AcCa, Cer, LPC, SM, SPH, and WE, and an increase in MePC, PEt, PS, TG, and ZyE (Figure S1B). When comparing the LHS and SHS groups, it was found a significantly higher abundance of DG and TG in the LHS group (Figure S1C), indicating that LHS had a more pronounced impact on the glycerolipid structure in goose muscle compared to SHS. Taken together, these findings suggest that heat stress induces changes in lipidomic profiles and alters the synthesis of unsaturated fatty acids in the breast muscle of geese.

Characterizing Skeletal Muscle Metabolomics Profiles Associated With Heat Stress in Geese

To investigate the impact of heat stress on the muscle metabolome, liquid chromatography-tandem mass spectrometry (LC-MS) was employed to analyze the metabolome and key nutrients in goose skeletal muscle. A total of 2793 metabolites were quantified in the goose skeletal muscle samples using LC-MS (Table S3). These metabolites were classified into 24 categories (Figure 4A), with amino acids and their metabolites representing the highest proportion (17.69%), followed by benzene and substituted derivatives (13.71%), and heterocyclic compounds (12.28%). Principal component analysis (PCA) results indicated no significant difference in the metabolome between LHS and NC, while the difference between SHS and NC was more pronounced. Furthermore, there was no significant difference in metabolic profiles between LHS and SHS (Figure 4B). K-means cluster analysis was performed and identified six sub-classes of metabolites with distinct expression patterns (Figure 4C). Among these, sub-class 5 exhibited 133 downregulated metabolites in both LHS and SHS compared to the control group. Enrichment analysis of these 133 metabolites revealed their predominant enrichment in Glycerolipid metabolism (Figure 4D), which can contribute to the flavor and juiciness of meat (Setyabrata et al., 2021). Conversely, sub-class 6 showed 44 upregulated metabolites in both LHS and SHS. Enrichment analysis demonstrated that these 44 metabolites were primarily enriched in Phospholipid Biosynthesis (Figure 4E). Therefore, the impact of heat stress on goose muscle metabolites appears to primarily target lipid synthesis and metabolism.

Figure 4.

Figure 4

Open in a new tab

Characterizing skeletal muscle metabolomics profiles associated with heat stress in geese. (A) Proportion of different types of metabolites in geese breast muscle. (B) PCA of identified metabolites between different comparative group. (C) K-Means diagram of differential metabolites. (D) KEGG pathway enrichment of the 133 downregulated metabolites in sub class 5. (e) KEGG pathway enrichment of the 44 upregulated metabolites in sub class 6. (F) Venn diagram of the differential metabolites in breast muscle between different comparative group. (G) Expression level of Thymidine-5′-triphosphate, Val-Tyr-Gln-His-Val, Ala-Ala-Ala-Phe, and Taxol C. (h) KEGG pathway enrichment of the differentially expressed metabolites between LHS and NC. (I) KEGG pathway enrichment of the differentially expressed metabolites between SHS and NC. *p < 0.05, **p < 0.01. n = 4.

To further investigate the types and functions of differential metabolites between groups, it was compared the two heat treatment groups with the control group. The results revealed significant differences in metabolite profiles between the heat stress groups and the control group (Figure 4F). Among these differential metabolites, four were consistently different in all three comparison groups: Thymidine-5′-triphosphate, Val-Tyr-Gln-His-Val, Ala-Ala-Ala-Phe, and Taxol C (Figure 4G). Specifically, there were 128 significantly differentially expressed metabolites between LHS and NC (Figure S2A), with enrichment in arachidonic acid metabolism, fatty acid elongation, and steroid biosynthesis pathways (Figure 4H). Similarly, there were 228 significantly differentially expressed metabolites between SHS and NC (Figure S2B), enriched in pyrimidine metabolism, phenylalanine metabolism, and tryptophan metabolism pathways (Figure 4I). Lastly, 126 metabolites showed significant differences between LHS and SHS (Figure S2C), and they were enriched in fatty acid-related pathways such as biosynthesis of unsaturated fatty acids, fatty acid biosynthesis, fatty acid metabolism, and fatty acid degradation (Figure S2d). Previous studies have also demonstrated that prolonged thermal stress increases the content of saturated fatty acids in the breast and thigh muscles of broiler chickens, while chronic heat stress decreases the concentration of monounsaturated fatty acids in these muscles (El-Tarabany et al., 2021). Therefore, the differences between LHS and SHS in terms of geese meat quality may be attributed to variations in fatty acid composition.

To gain insights into the associations between differential metabolites within each control group, a network interaction map was created (Figures S2E–2G). These maps facilitate the understanding of interactions and connections among muscle metabolites under different heat stress conditions. Subsequently, the correlation between muscle metabolites and meat quality traits was analyzed. The results demonstrated significant associations between several metabolites and meat color b* value, indicating that the content of metabolites in the muscle has a greater influence on the red and yellow color of the meat (Figure S2h). Furthermore, meat color L* value, drip loss, and shear force were also found to be associated with certain metabolites. Specifically, Thymidine-5′-triphosphate and Val-Tyr-Gln-His-Val, which exhibited significant downregulation following heat stress (Figure 4g), showed a negative correlation with meat color b* value. Thymidine-5′-triphosphate was also positively correlated with meat color L* value. On the other hand, Ala-Ala-Ala-Phe and Taxol C, which were significantly upregulated after heat stress (Figure 4g), displayed a positive correlation with meat color b* value. Considering the significant upregulation of meat color b* value due to heat stress (Figure 1G), it is suggested that heat stress may indirectly regulate meat color b* value by influencing the content of key metabolites in the muscle.

Proteome Profile of Skeletal Muscle Identified the Differential Expressed Proteins After Heat Stress in Geese

A 4D-DIA proteome analysis was employed to investigate changes in protein expression in goose muscle following heat stress treatment. A total of 4,803 proteins were quantitatively analyzed (Table S4), with peptides ranging mostly in length from 7 to 20 amino acids (Figures 5A–5B). Principal component analysis (PCA) results revealed no significant differences in protein expression profiles among all groups (Figure 5C). Pairwise analysis identified 71 differentially expressed proteins (DEPs) between LHS and NC, 92 DEPs between SHS and NC, and 81 DEPs between LHS and SHS (Figures 5D–5E). K-means cluster analysis categorized proteins into seven sub-classes with distinct expression trends (Figure 5F). Among these, sub-classes 1 and 3 exhibited upregulation of 46 proteins in both LHS and SHS compared to the control group, while sub-classes 2 and 5 showed downregulation of 57 proteins in both LHS and SHS compared to the control group (Figure 5F). Interestingly, when analyzing the expression of the heat shock protein (HSP) family, we found that heat stress had minimal effect on HSPs expression in goose muscle. Specifically, LHS only significantly downregulated the expression of HSP-beta8, while SHS significantly decreased the expression of HSP-beta3 and HSP105-X1 (Figure 5G). In contrast, our previous studies demonstrated that heat stress at 40°C significantly increased the mRNA expression of HSP70 in goose muscle (Zhang et al., 2015). However, other studies have shown that heat stress at 37.8°C does not affect the expression of HSPs in chicken muscle, suggesting that the effects of heat stress on the HSP family may be tissue- and age-dependent (Zhang et al., 2015).

Figure 5.

Figure 5

Open in a new tab

Proteome profile of skeletal muscle identified the differential expressed proteins after heat stress in geese. (A) Statistical histogram of protein identification results. (B) Distribution of peptide length and number. (C) PCA of identified proteins between different comparative group. (D) Venn diagram of the differential expressed proteins in breast muscle between different comparative group. (E) Number of differential expressed proteins in breast muscle between different comparative group. (F) K-Means diagram of differential expressed proteins. (G) Expression of heat shock proteins family in different treatment groups. *p < 0.05. n = 4.

To gain a systematic understanding of the impact of heat stress on muscle protein function, functional enrichment analysis of the differentially expressed proteins (DEP) was conducted. The DEPs between NC and LHS exhibited enrichment in GO terms or KEGG pathways associated with cellular respiratory metabolism, such as NADH dehydrogenase activity and glycosphingolipid biosynthesis (Figures S3A–S3B). On the other hand, DEPs induced by SHS were primarily enriched in immune response-related processes, including adaptive immune response and immune network for IgA production (Figures S3C–S3D). Furthermore, the DEPs between LHS and SHS were predominantly enriched in innate immune-related processes (Figures S3E–S3F). These findings suggest that SHS primarily affects genes related to immune response, while LHS primarily affects cell respiration and metabolism in goose muscle. Subsequently, correlation analysis between the DEPs and meat quality traits was performed. The results revealed significant associations between numerous DEPs and drip loss as well as meat color b* value, while fewer associations were observed with other meat quality traits (Figure S3G). This indicates that the DEPs induced by heat stress primarily impact metabolic pathways related to drip loss and the yellow coloration of meat.

Combined Analysis of Proteomes With Amino Acids, Lipids and Metabolites in Goose Skeletal Muscle After Heat Stress

To gain a deeper understanding of the relationship between protein content and other metabolites in goose muscle, correlation analysis between different omics data was conducted. Initially, it was examined the correlation between proteins exhibiting significant differences between groups and amino acids, as well as their derivatives that displayed significant differences between groups. The results revealed predominantly positive correlations between most amino acids and the proteins (Figure 6A). Notably, hemopexin drew our attention as it exhibited significant associations with five amino acids and their derivatives, namely N-acetylaspartate, N-isovaleroylglycine, N-Propionylglycine, 5-Hydroxy-Tryptamine, and Kynurenic Acid (Figure 6A). Myelin-related proteins also displayed associations with amino acids and their derivatives. Multiple myelin-related proteins, such as myelin basic protein isoform X2, myelin basic protein isoform X1, myelin proteolipid protein isoform X1, myelin P2 protein, and myelin P2 protein, showed positive correlations with various amino acids and their derivatives (Figure 6A). Additionally, several structural proteins including collagen, neurofilament, and myocilin were significantly and positively associated with numerous amino acids and their derivatives (Figure 6A).

Figure 6.

Figure 6

Open in a new tab

Combined analysis of proteomes with amino acids, lipids and metabolites in goose skeletal muscle after heat stress. (A) Correlation heatmap between differentially expressed proteins and differential amino acids and their derivatives. (B) Correlation heatmap between differentially expressed proteins and differential metabolites.

In the second part of our analysis, it was examined the correlation between proteins exhibiting significant differences between groups and lipid molecules that displayed significant differences between groups. It was identified a group of differentially expressed proteins (DEP) that showed significant and positive correlations with TG, DG, and Hex1Cer (Figure 6B, highlighted in red box). Among these DEPs, ryanodine receptor 3 isoform X7, which controls the resting calcium ion concentration in skeletal muscle and was significantly downregulated in the SHS group compared to the NC group (Table S3), displayed a strong positive correlation with TG and DG. Similarly, iron-sulfur cluster assembly enzyme ISCU, a mitochondrial protein that was significantly downregulated in the SHS group, also exhibited a strong positive correlation with TG and DG. Additionally, DnaJ homolog subfamily B member 6 isoform X2, a co-chaperone of HSP70 that was downregulated in both the LHS and SHS groups, showed a strong positive correlation with Hex1Cer (Figure 6B). Furthermore, another group of 3 DEPs that displayed significant negative correlations with TG, DG, and Hex1Cer were identified (Figure 6B, highlighted in blue box). These three proteins included ADP-ribosylation factor-like protein 8A isoform X1 (ARL8A), receptor-type tyrosine-protein phosphatase mu (PTPRM), and voltage-dependent L-type calcium channel subunit beta-4 isoform X1 (CACB4). Interestingly, all three proteins exhibited upregulated expression under heat stress conditions (Table S3). In summary, these proteins that show significant correlation with TG, DG, and Hex1Cer may influence the levels of these lipid factors by participating in lipid synthesis and metabolism pathways during heat stress. Further investigation is warranted to better understand their specific roles and implications.

We proceeded with an analysis to examine the correlation between DEPs and differentially expressed metabolites (DEM). The outcomes demonstrated a complex network of interconnected proteins and metabolites (Figure S4). From this network, it was specifically identified metabolites and proteins that have previously demonstrated associations with meat quality traits. These interrelated metabolites and proteins will serve as the focal points for future investigations into meat quality (Figure S5). For instance, it was observed a positive correlation between guanine deaminase (GDA) and cooking loss as well as skin color b* value, while Hexylamine displayed a negative correlation with cooking loss and skin color b* value. Notably, a significant negative correlation between GDA and Hexylamine was found, indicating that GDA may impact meat quality by exerting a negative regulatory influence on Hexylamine. Hexylamine is a byproduct of microbial activity during meat spoilage. Elevated levels of amines in meat can contribute to undesirable flavors and unpleasant odors, signifying a decline in meat quality and freshness (Ruiz-Capillas and Herrero, 2019).

In the final step, it was carefully selected a set of differentially expressed proteins that demonstrated significant associations with differentially expressed amino acids, differentially expressed lipid molecules, differentially expressed metabolites, and meat quality traits. This selection process yielded 19 key DEPs. Notably, myelin-related proteins constituted a significant portion of these key DEPs, indicating their crucial involvement in the nutritional and quality changes of goose meat under heat stress conditions. To comprehensively integrate these 12 DEPs with their associated metabolites, amino acids, lipids, and meat quality traits, a correlation interaction network was constructed (Figure 7). This network also incorporates the expression patterns of these molecules under different heat stress conditions. The generated network provides valuable insights into how heat stress influences meat quality traits by modulating proteins and related metabolites in goose meat. It serves as a valuable resource for understanding the complex interplay between heat stress, protein regulation, metabolite composition, and meat quality in geese.

Figure 7.

Figure 7

Open in a new tab

The interaction network of key amino acids and their derivatives, lipids, metabolites and proteins affecting goose meat quality.

CONCLUSIONS

In this study, it was exposed geese to both long-time heat stress for 21 d and short-time heat stress for 4 h. Surprisingly, the impact of SHS on meat quality surpassed that of LHS was observed. The analysis of muscle amino acids and their derivatives revealed that heat stress only influenced a limited number of amino acids and their derivatives, with L-Cystine and L-Cystathionine emerging as the most influential ones. Muscle lipidomic analysis demonstrated significant differences between LHS and SHS in terms of muscle lipids, with TG and DG exhibiting the strongest correlation with goose meat quality. Furthermore, the muscle non-target metabolome analysis unveiled distinct effects of LHS and SHS on specific metabolic pathways. LHS predominantly affected arachidonic acid metabolism, fatty acid elongation, and steroid biosynthesis, while SHS primarily impacted pyrimidine metabolism, phenylalanine metabolism, and tryptophan metabolism. When examining the muscle proteome, it was observed minimal influence of heat stress on the expression levels of heat shock proteins in goose muscle. Instead, LHS primarily affected cellular respiratory metabolism, while SHS influenced processes related to immune response. Finally, by conducting a comprehensive joint analysis across the different groups, a core interaction regulatory network between the multi-molecules and meat quality in geese was constructed. These findings serve as a crucial reference for gaining a systematic understanding of the effects of heat stress on goose meat quality, and they lay a foundation for enhancing goose meat quality and ensuring human food safety.

DISCLOSURES

The authors declare no conflicts of interest.

ACKNOWLEDGMENTS

This work was supported by the Key-Area Research and Development Program of Guangdong Province (2020B020222003 and 2022B0202100001), Natural Scientific Foundation of China (32272861), Guangdong Special Branch Plans of Young Talent with Scientific and Technological Innovation (2019TQ05N470), China Agriculture Research System of MOF and MARA (CARS-41), and the Local Innovative and Research Teams Project of Guangdong Province (2019BT02N630).

Author Contributions: Ying Yang: Investigation, Data curation, Formal analysis, Methodology, Software, Writing—original draft. Shuai Zhang: Investigation, Methodology, Formal analysis, Methodology, Resources, Writing —original draft. Haoqi Peng: Investigation, Methodology, Resources. Genghua Chen: Investigation, Methodology, Writing—review and editing. Qinghua Nie: Visualization, Supervision. Xiquan Zhang: Visualization, Supervision. Wen Luo: Conceptualization, Funding acquisition, Methodology, Resources, Writing—original draft and review and editing.

Footnotes

Supplementary material associated with this article can be found in the online version at doi:10.1016/j.psj.2024.104112.

Appendix. Supplementary materials

Figure S1. Statistical heat map of differences in lipid structural characteristics.

mmc1.jpg (842.8KB, jpg)

Figure S2. Effects of different heat stress treatments on metabolome of goose meat. (A–C) Heat maps of differential metabolites between different treatment groups. (D) KEGG pathway enrichment of the differentially expressed metabolites between LHS and SHS. (E–G) Differential metabolites correlation network diagrams. (H) Correlation heatmap between differential metabolites and meat quality traits.

mmc2.jpg (3.2MB, jpg)

Figure S3. Effects of different heat stress treatments on proteome of goose meat. (A–F) GO and KEGG analysis between different comparative groups. (G) Correlation heatmap between differentially expressed proteins and meat quality traits.

mmc3.jpg (1.2MB, jpg)

Figure S4. Correlation heatmap between differentially expressed proteins and differential metabolites.

mmc4.jpg (3.4MB, jpg)

Figure S5. Correlation heatmap between differentially expressed proteins and differential metabolites correlated with meat quality traits.

mmc5.jpg (2.1MB, jpg)
mmc6.xlsx (23.5KB, xlsx)
mmc7.xlsx (1.3MB, xlsx)
mmc8.xlsx (1.1MB, xlsx)
mmc9.xlsx (1.1MB, xlsx)

REFERENCES

  1. Additives, E. P. o., Products or Substances used in Animal, F. Bampidis V., Azimonti G., Bastos M.L., Christensen H., Dusemund B., Kos Durjava M., Kouba M., Lopez-Alonso M., Lopez Puente S., Marcon F., Mayo B., Pechova A., Petkova M., Ramos F., Sanz Y., Villa R.E., Woutersen R., Cocconcelli P.S., Glandorf B., Herman L., Maradona M.P., Saarela M., Anguita M., Galobart J., Holczknecht O., Manini P., Pettenati E., Pizzo F., Tarres-Call J. Safety and efficacy of l-cystine produced using Pantoea ananatis strain NITE BP-02525 for all animal species. EFSA J. 2020;18:e06020. doi: 10.2903/j.efsa.2020.6020. [DOI] [PMC free article] [PubMed] [Google Scholar]
  2. Bejaoui B., Sdiri C., Ben Souf I., Belhadj Slimen I., Ben Larbi M., Koumba S., Martin P., M’Hamdi N. Physicochemical properties, antioxidant markers, and meat quality as affected by heat stress: a review. Molecules. 2023;28 doi: 10.3390/molecules28083332. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Chiang W., Booren A., Strasburg G. The effect of heat stress on thyroid hormone response and meat quality in turkeys of two genetic lines. Meat Sci. 2008;80:615–622. doi: 10.1016/j.meatsci.2008.02.012. [DOI] [PubMed] [Google Scholar]
  4. Crandall C.G., Wilson T.E. Human cardiovascular responses to passive heat stress. Compr Physiol. 2015;5:17–43. doi: 10.1002/cphy.c140015. [DOI] [PMC free article] [PubMed] [Google Scholar]
  5. El-Tarabany M.S., Ahmed-Farid O.A., Nassan M.A., Salah A.S. Oxidative stability, carcass traits, and muscle fatty acid and amino acid profiles in heat-stressed broiler chickens. Antioxidants (Basel) 2021;10 doi: 10.3390/antiox10111725. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Fu H., Pan L., Wang J., Zhao J., Guo X., Chen J., Lu S., Dong J., Wang Q. Sensory properties and main differential metabolites influencing the taste quality of dry-cured beef during processing. Foods. 2022;11:4. doi: 10.3390/foods11040531. [DOI] [PMC free article] [PubMed] [Google Scholar]
  7. Fu Y., Cao S., Yang L., Li Z. Flavor formation based on lipid in meat and meat products: a review. J. Food Biochem. 2022;46:e14439. doi: 10.1111/jfbc.14439. [DOI] [PubMed] [Google Scholar]
  8. Gonzalez-Rivas P.A., Chauhan S.S., Ha M., Fegan N., Dunshea F.R., Warner R.D. Effects of heat stress on animal physiology, metabolism, and meat quality: a review. Meat Sci. 2020;162 doi: 10.1016/j.meatsci.2019.108025. [DOI] [PubMed] [Google Scholar]
  9. Knochel J.P., Dotin L.N., Hamburger R.J. Heat stress, exercise, and muscle injury: effects on urate metabolism and renal function. Ann. Intern. Med. 1974;81:321–328. doi: 10.7326/0003-4819-81-3-321. [DOI] [PubMed] [Google Scholar]
  10. Lada A.T., Rudel L.L. Dietary monounsaturated versus polyunsaturated fatty acids: which is really better for protection from coronary heart disease? Curr. Opin. Lipidol. 2003;14:41–46. doi: 10.1097/00041433-200302000-00008. [DOI] [PubMed] [Google Scholar]
  11. Larsson S.C., Virtamo J., Wolk A. Dietary fats and dietary cholesterol and risk of stroke in women. Atherosclerosis. 2012;221:282–286. doi: 10.1016/j.atherosclerosis.2011.12.043. [DOI] [PubMed] [Google Scholar]
  12. Li Y., Fu B., Zhang J., Wang G., Gong W., Tian J., Li H., Zhang K., Xia Y., Li Z., Xie J., Kaneko G., Yu E. Effects of heat stress on the chemical composition, oxidative stability, muscle metabolism, and meat quality of Nile tilapia (Oreochromis niloticus) Food Chem. 2023;426 doi: 10.1016/j.foodchem.2023.136590. [DOI] [PubMed] [Google Scholar]
  13. Liu Z., Liu Y., Xing T., Li J., Zhang L., Jiang Y., Gao F. Transcriptome analysis reveals the mechanism of chronic heat stress on meat quality of broilers. J. Anim. Sci. Biotechnol. 2022;13:110. doi: 10.1186/s40104-022-00759-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Ma B., Zhang L., Li J., Xing T., Jiang Y., Gao F. Heat stress alters muscle protein and amino acid metabolism and accelerates liver gluconeogenesis for energy supply in broilers. Poult. Sci. 2021;100:215–223. doi: 10.1016/j.psj.2020.09.090. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Massaro M., Scoditti E., Carluccio M.A., Campana M.C., De Caterina R. Omega-3 fatty acids, inflammation and angiogenesis: basic mechanisms behind the cardioprotective effects of fish and fish oils. Cell Mol. Biol. (Noisy-le-grand) 2010;56:59–82. [PubMed] [Google Scholar]
  16. Mazlomi A., Golbabaei F., Farhang Dehghan S., Abbasinia M., Mahmoud Khani S., Ansari M., Hosseini M. The influence of occupational heat exposure on cognitive performance and blood level of stress hormones: a field study report. Int. J. Occup. Saf. Ergon. 2017;23:431–439. doi: 10.1080/10803548.2016.1251137. [DOI] [PubMed] [Google Scholar]
  17. Nemati Z., Alirezalu K., Besharati M., Amirdahri S., Franco D., Lorenzo J.M. Improving the quality characteristics and shelf life of meat and growth performance in goose fed diets supplemented with vitamin E. Foods. 2020;9 doi: 10.3390/foods9060798. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Pardo Z., Fernandez-Figares I., Lachica M., Lara L., Nieto R., Seiquer I. Impact of Heat Stress on Meat Quality and Antioxidant Markers in Iberian Pigs. Antioxidants (Basel) 2021;10 doi: 10.3390/antiox10121911. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Ruiz-Capillas C., Herrero A.M. Impact of Biogenic Amines on Food Quality and Safety. Foods. 2019;8 doi: 10.3390/foods8020062. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Setyabrata D., Cooper B.R., Sobreira T.J.P., Legako J.F., Martini S., Kim Y.H.B. Elucidating mechanisms involved in flavor generation of dry-aged beef loins using metabolomics approach. Food Res Int. 2021;139 doi: 10.1016/j.foodres.2020.109969. [DOI] [PubMed] [Google Scholar]
  21. Slimen I.B., Najar T., Ghram A., Dabbebi H., Ben Mrad M., Abdrabbah M. Reactive oxygen species, heat stress and oxidative-induced mitochondrial damage. A review. Int J Hyperthermia. 2014;30:513–523. doi: 10.3109/02656736.2014.971446. [DOI] [PubMed] [Google Scholar]
  22. Tianlong D., Sim Y.J. Effects of different recovery methods on postboxing sparring fatigue substances and stress hormones. J Exerc Rehabil. 2019;15:258–263. doi: 10.12965/jer.1938050.025. [DOI] [PMC free article] [PubMed] [Google Scholar]
  23. Wang C., Lin J., Niu Y., Wang W., Wen J., Lv L., Liu C., Du X., Zhang Q., Chen B., Cai J., Zhao Z., Liang D., Ji J.S., Chen H., Chen R., Kan H. Impact of ozone exposure on heart rate variability and stress hormones: A randomized-crossover study. J Hazard Mater. 2022;421 doi: 10.1016/j.jhazmat.2021.126750. [DOI] [PubMed] [Google Scholar]
  24. Wasti S., Sah N., Mishra B. Impact of heat stress on poultry health and performances, and potential mitigation strategies. Animals (Basel) 2020;10 doi: 10.3390/ani10081266. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Weng K., Huo W., Gu T., Bao Q., Cao Z., Zhang Y., Zhang Y., Xu Q., Chen G. Quantitative phosphoproteomic analysis unveil the effect of marketable ages on meat quality in geese. Food Chem. 2021;361 doi: 10.1016/j.foodchem.2021.130093. [DOI] [PubMed] [Google Scholar]
  26. Weng K., Huo W., Gu T., Bao Q., Hou L.E., Zhang Y., Zhang Y., Xu Q., Chen G. Effects of marketable ages on meat quality through fiber characteristics in the goose. Poult. Sci. 2021;100:728–737. doi: 10.1016/j.psj.2020.11.053. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Yin J., Ren W., Yang G., Duan J., Huang X., Fang R., Li C., Li T., Yin Y., Hou Y., Kim S.W., Wu G. L-Cysteine metabolism and its nutritional implications. Mol. Nutr. Food Res. 2016;60:134–146. doi: 10.1002/mnfr.201500031. [DOI] [PubMed] [Google Scholar]
  28. Zaboli G., Huang X., Feng X., Ahn D.U. How can heat stress affect chicken meat quality? - a review. Poult. Sci. 2019;98:1551–1556. doi: 10.3382/ps/pey399. [DOI] [PubMed] [Google Scholar]
  29. Zhang W.W., Xiao X., Gan J.K., Zhang X.Q., Kong L.N., Luo Q.B. Characterization of HSP70 and its expression in tissue: correlation with physiological and immune indices in goose (Anser cygnoides) serum. Genet. Mol. Res. 2015;14:12288–12298. doi: 10.4238/2015.October.9.17. [DOI] [PubMed] [Google Scholar]
  30. Zhu F., Yin Z.T., Wang Z., Smith J., Zhang F., Martin F., Ogeh D., Hincke M., Lin F.B., Burt D.W., Zhou Z.K., Hou S.S., Zhao Q.S., Li X.Q., Ding S.R., Li G.S., Yang F.X., Hao J.P., Zhang Z., Lu L.Z., Yang N., Hou Z.C. Three chromosome-level duck genome assemblies provide insights into genomic variation during domestication. Nat. Commun. 2021;12:5932. doi: 10.1038/s41467-021-26272-1. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Figure S1. Statistical heat map of differences in lipid structural characteristics.

mmc1.jpg (842.8KB, jpg)

Figure S2. Effects of different heat stress treatments on metabolome of goose meat. (A–C) Heat maps of differential metabolites between different treatment groups. (D) KEGG pathway enrichment of the differentially expressed metabolites between LHS and SHS. (E–G) Differential metabolites correlation network diagrams. (H) Correlation heatmap between differential metabolites and meat quality traits.

mmc2.jpg (3.2MB, jpg)

Figure S3. Effects of different heat stress treatments on proteome of goose meat. (A–F) GO and KEGG analysis between different comparative groups. (G) Correlation heatmap between differentially expressed proteins and meat quality traits.

mmc3.jpg (1.2MB, jpg)

Figure S4. Correlation heatmap between differentially expressed proteins and differential metabolites.

mmc4.jpg (3.4MB, jpg)

Figure S5. Correlation heatmap between differentially expressed proteins and differential metabolites correlated with meat quality traits.

mmc5.jpg (2.1MB, jpg)
mmc6.xlsx (23.5KB, xlsx)
mmc7.xlsx (1.3MB, xlsx)
mmc8.xlsx (1.1MB, xlsx)
mmc9.xlsx (1.1MB, xlsx)

Articles from Poultry Science are provided here courtesy of Elsevier

RESOURCES