Proteomics and lipidomics analysis of the breast muscles to investigate the effect of dietary copper level on the meat quality of pigeons

Abstract

Pigeon meat, known for its high nutritional value and tender texture, can be influenced by various dietary factors. Copper, an essential trace mineral, plays a vital role in growth, development, and overall meat quality. However, its impact on pigeon meat has not been well studied. This study evaluated the effects of dietary copper supplementation on production performance, carcass traits, meat quality, fatty acid composition, and protein profiles in squabs. A total of 120 pairs of 60-week-old White King pigeon breeders (one male and one female per pair) were randomly assigned to five dietary treatment groups, each receiving diets containing 5.66, 9.66, 13.66, 17.66, or 21.66 mg/kg of copper. Feeding by parent pigeons, the squabs were reared to 28 days of age and then used for sampling and analyses. The result showed that copper deficiency led to increased lipid accumulation in the breast muscle, raising levels of total lipids, triglycerides, cholesterol, and free fatty acids, which impaired shear force and meat texture. Copper supplementation reduced saturated fatty acids and increased beneficial ω-3 polyunsaturated fatty acids (methyl linolenate). Proteomic analysis revealed that copper enhanced tubulin expression, which is crucial for muscle cell integrity, and influenced enzymes involved in fatty acid metabolism. Regional variation in copper supplementation highlighted the importance of optimizing copper levels in pigeon diets. Statistical analyses included one-way ANOVA and quadratic regression analysis, which identified the optimal dietary copper level for improving meat quality as 17.2∼18.4 mg/kg. These findings suggest that adequate copper supplementation can significantly improve both the texture and nutritional quality of pigeon meat, providing valuable insights into the pigeon industry and consumer health.

Introduction

Pigeon meat, the fourth most widely consumed poultry in China after chicken, duck, and goose, is valued for both its taste and nutritional benefits. This lean protein source is ideal for individuals aiming to maintain a healthy body weight and physique. According to the Compendium of Materia Medica (Bencao Gangmu) from the Ming Dynasty (A.D. 1590), pigeon meat is described as having a delicious taste and neutral properties, benefiting the liver and kidney meridians. It is known for its ability to nourish yin, tonify the kidneys, regulate essence, benefit qi, dispel wind, and detoxify. Modern Chinese medicine also recognizes pigeon meat as easily digestible, with properties that support nourishment, qi regulation, wind dispelling, and detoxification. It is believed to have therapeutic benefits for conditions such as post-illness weakness, blood deficiency, dizziness, fatigue, and memory decline. Despite extensive research on the quality of other types of meat, there is limited information on the quality and nutritional composition of pigeon meat. Previous studies have shown that pigeon meat is rich in linoleic acid, which plays an important role in regulating lipid metabolism and reducing cholesterol levels (Chang et al., 2017). Furthermore, pigeon meat serves as a substantial reservoir of essential vitamins and minerals, encompassing B vitamins, vitamin E, iron, and zinc (Yi, 2019).

Copper, a vital trace mineral, plays diverse physiological roles, such as functioning as a component of proteins (Cambrolle et al., 2015; Chen et al., 2022), supporting antioxidant activity (Gou et al., 2021; Liu et al., 2024), regulating lipid metabolism (Cui et al., 2022; Li et al., 2022a), and contributing to muscle contraction (Bao et al., 2020). Moderate copper intake is essential for muscle development and quality, as it facilitates protein synthesis and metabolism, processes crucial for muscle growth. Additionally, copper contributes to collagen synthesis, a structural protein vital for maintaining muscle tissue integrity (Roomi et al., 2015). Consequently, ensuring an adequate copper supply can effectively enhance both muscle development and quality. Moreover, copper significantly impacts the overall quality of meat products by aiding in the synthesis of myoglobin, a key protein that enhances both the visual appeal and sensory characteristics of meat (Bhattacharya et al., 2016; Ding et al., 2022). Copper also exhibits antioxidant properties, which mitigate oxidation, thereby extending meat's shelf life (Gou et al., 2021; Liu et al., 2024). Overall, providing a moderate copper supplement can effectively improve the gustatory experience and overall quality of meat products.

Although previous studies have explored the effects of copper on general animal growth and meat quality, the specific impacts of dietary copper levels on the proteomic and lipidomic profiles of breast muscle remain unknown. In particular, there is limited knowledge on how copper supplementation regulates key muscle-related proteins (such as tubulin and enzymes involved in fatty acid metabolism), alters fatty acid composition (including saturated fatty acids, monounsaturated fatty acids, and ω-3 polyunsaturated fatty acids), and modulates metabolic pathways linked to muscle structure, lipid metabolism, and oxidative stress.

Therefore, this study aims to fill these research gaps by comprehensively investigating the effects of different dietary copper concentrations on carcass traits, meat quality parameters (meat pH, drip loss, shear force, and cooking loss), lipid content, fatty acid composition, and proteomic profile in squabs. The integrated proteomics and lipidomics analyses will provide insights into copper-regulated proteins and fatty acids that contribute to improved meat quality in pigeons.

Material and method

All the experimental procedures of this study were approved by the Animal Care and Use Committee of the Institute of Animal Husbandry and Veterinary Medicine of Beijing Academy of Agriculture and Forestry Sciences (IAHVM-BAAFS), and the experimental procedures were carried out in strict accordance with the animal testing guidelines formulated by the National Institute of Health (IHVM11-2103-2).

Experimental design

This study aimed to examine the effects of various dietary copper supplemental levels (0, 4, 8, 12, and 16 mg/kg) on the development of carcass trait, breast muscle quality, fatty acid composition, and protein profile in pigeons. A total of 120 pairs of pigeon breeders, exhibiting comparable production performance, were randomly divided into five treatment groups. Each group was provided with one of the five experimental diets mentioned above. Each group contained eight replicates, and each replicate consisted of three breeding pairs of adult pigeons. Each breeding pair was rearing one pair of squabs.

Housing, diet, and management

Each pair of pigeon breeders was raised in a single cage (50 cm × 50 cm × 60 cm). After laying eggs, the pigeon breeders were fed with the experimental diet for 46 days, including an 18-day incubation period and a 28-day squab growth period. During the experiment, all the birds received diet and water ad libitum, with a cycle of 16 light hours and 8 dark hours. The basic diet consisted of pelleted feed containing corn, peas, soybeans, wheat, and sorghum. Excepted copper, the other dietary nutrition meets the pigeon nutritional requirements according to Management Techniques for Pigeon Rearing (T/CAAA 038-2020). The composition and nutritional levels of the basic diet are shown in Table 1. The copper level in the basal diet was analytically determined using atomic absorption spectrophotometry (GB/T 13885-2017), with a measured dietary copper level of 5.66 mg/kg. All of the diets were cold-pelleted at room temperature. After weighing the copper supplement, it is directly mixed with other trace elements to prepare a premix, which is then gradually blended with other diet materials until uniform. The copper supplement used crystalline copper sulfate pentahydrate (CuSO₄·5H₂O, purity > 98%, CAS No. 7758-99-8) was purchased from Sigma-Aldrich (St. Louis, MO).

Table 1.

Composition of the copper-deficient basal diet (% as-fed basis).

Ingredient	Content
Corn	41.0
Pea	17.4
Soybean meal (44 % CP)	13.1
Wheat	12.8
Sorghum	10.4
Soybean oil	0.70
Limestone	1.35
Dicalcium phosphate	2.09
Sodium chloride	0.40
Corn starch	0.22
Vitamin premix 1	0.03
Mineral premix 2	0.14
Choline chloride	0.04
Lysine hydrochloride	0.16
DL-Methionine	0.13
Calculated composition
Metabolizable energy, ME/(MJ/kg)	11.89
Crude protein 3	15.70
Lysine	0.88
Methionine	0.36
Calcium	1.11
Non-phytate phosphorus	0.44
Copper, mg/kg 3	5.66

¹Complex vitamin is provided per kilogram of feed: VA 13500 IU, VD₃ 3600 IU, VE 36 IU, VK₃ 5 mg, VB₁ 5.0 mg, VB₁₂ 15 mg/kg, D-pantothenic acid 22 mg, nicotinamide 41.94 mg, folic acid 3 mg, biotin 0.25 mg, and VB₁₂ 0.039 mg.

²Trace components are provided per kilogram of feed: iron 150 mg, zinc 88 mg, manganese 70 mg, iodine 0.35 mg, and selenium 0.25 mg.

³The nutrient compositions are measured values; the others are calculated values.

Measurements

Carcass trait

At 28 days of age, after a 6-h fasting period, all squabs and the remaining feed in each replicate (n = 8 per group) were weighed. These data were used to calculate the average daily gain (ADG), average daily feed intake (ADFI), and feed conversion ratio (FDR) of the squabs from day 1 to day 28. Subsequently, one squab with a body weight closest to the replicate mean was selected from each replicate (n = 8), weighed, and humanely euthanized by CO₂ inhalation. According to Chinese agricultural standards (NY/T 823-2020), slaughter performance was evaluated and expressed as slaughter percentage, eviscerated percentage, and breast muscle percentage to account for variations in body size.

Meat quality

Meat pH, drip loss, shear force, and cooking loss were determined 24 h post-mortem. The pH was determined with a pH meter (HI99163; Hanna Instruments Inc., Woonsocket, RI) at three locations in each sample. To determine drip loss, about 5 g of breast muscle was weighed, kept in a bag at 4°C, and reweighed after 24 h. To determine shear force, five cores in cube shape (1.5 cm × 1.5 cm × 2.0 cm) vertical to the fiber direction were obtained. The cores were then sheared to a cross-section of the muscle fiber using a Warner-Bratzer shear blade with a TA-XT Plus Texture Analyzer (Stable Micro System Ltd., Godalming, UK). The shear force measurement parameters were set as follows: testing speed = 1.0 mm/s, distance = 25 mm, and trigger force = 5 g, according to the method described before (Huang et al., 2023; Pinheiro et al., 2019). To determine cooking loss, the weight of pigeon breast muscle before and after cooking was used to measure the cooking loss value of meat sample, according to the method described before (Oz and Kızıl, 2012). Using the difference between the weights, the cooking loss value was calculated as %.

Lipids analysis

The total lipids (TL) content of Breast muscle was extracted and analyzed by chloroform-methanol mixture (2:1), according to the method described before (Folch et al., 1957; Wen et al., 2014). After drying and weighing the extract, the TL was calculated. Subsequently, the dried extract is redissolved using a chloroform-methanol mixture. The triglyceride (TG), total cholesterol (T-CHO), and free fatty acid content (Chen et al., 1989) in the breast muscle are detected using commercial assay kits A110-1-1, A111-2-1, and A042-1-1, which were purchased from Nanjing Jiancheng Institute of Bioengineering (Nanjing, China).

Fatty acids profile

The free fatty acid composition and concentration in pigeon breast muscle were analyzed using gas chromatography-mass spectrometry (GC-MS, Agilent 7890B-5977B, Santa Clara, CA) (Wang et al., 2013; Zeng et al., 2016). The chromatographic column used was DB-FastFAME (90 m × 250 μm × 0.25 μm, Folsom, CA), with high-purity helium gas (> 99.999%) as the carrier gas. Tissue samples were placed in 1.5 mL EP tubes and 450 μL of extraction solution was added, vortexed; sonicated in an ice bath, followed by centrifugation for 15 min; the supernatant was dried with nitrogen gas; methanol and trimethylsilyl diazomethane was added, and left at room temperature; dried with nitrogen gas; reconstituted with n-hexane, centrifuged, and the supernatant was transferred to the injection vial; then analyzed by GC-MS. The injection volume was 1 μL, Front Inlet Septum Purge Flow was 3 mL/min, and Column Pressure was 46 psi. The column oven temperature program was as follows: hold at 75°C for 1 min → increase to 200°C at a rate of 50°C/min, hold for 15 min → increase to 210°C at a rate of 2°C/min, hold for 1 min → increase to 230°C at a rate of 10°C/min, and hold for 16.5 min. Front Injection Temperature was 240°C, Transfer Line Temperature was 240°C, Ion Source Temperature was 230°C, Quad Temperature was 150°C, and Electron Energy was -70 eV. For the fatty acids profile analysis, we included 8 biological replicates per group. In order to meet the assumptions of normality and homogeneity of variance, the lipid-related data in result were log-transformed prior to statistical analysis. The significance tests for these data were performed on the log-transformed values, and the results are presented accordingly.

Breast muscle protein profile

The three dietary copper level groups: 5.66 mg/kg (C group), 9.66 mg/kg (T1 group), and 21.66 mg/kg (T4 group) were selected for proteomics analysis based on the estimated copper requirements and experimental design. For the proteomics analysis, we included 6 biological replicates per group.

Protein extraction and digestion

Breast muscle tissue samples (∼100 mg) from each group were homogenized in SDT buffer (4% SDS, 100 mM Tris-HCl, pH 7.6, supplemented with 100 mM DTT) using a mechanical homogenizer. Lysates were sonicated on ice and centrifuged at 14,000 × g for 15 min at 4°C. The supernatant was collected, and total protein concentration was quantified using the BCA Protein Assay Kit (Bio-Rad, Hercules, CA). For each sample, 20 µg of protein was mixed with 5 × SDS-PAGE loading buffer, boiled at 95°C for 5 min, and separated on a 4–20% gradient SDS-PAGE gel (constant voltage, 120 V). Protein bands were visualized with Coomassie Brilliant Blue R-250 staining.

Protein digestion was performed using the Filter-Aided Sample Preparation (FASP) method. Briefly, proteins were reduced with 100 mM DTT at 60°C for 30 min and alkylated with 50 mM iodoacetamide (IAA) in the dark at room temperature for 30 min. Samples were transferred to 10 kDa ultrafiltration filters (Millipore), washed with UA buffer (8 M urea, 150 mM Tris-HCl, pH 8.5) and 25 mM ammonium bicarbonate, and digested overnight at 37°C with sequencing-grade modified trypsin (enzyme-to-protein ratio 1:50, Promega, Madison, WI). The peptides were collected by centrifugation, desalted using Sep-Pak C18 cartridges (Waters, Milford, MA), concentrated by vacuum centrifugation, and reconstituted in 0.1% formic acid. Peptide concentration was determined by UV absorbance at 280 nm.

4D label-free LC-MS/MS analysis

LC-MS/MS analysis was conducted using a timsTOF Pro mass spectrometer from Bruker, coupled with Nanoelute. Peptides were loaded onto a C18-reversed phase analytical column (Thermo Scientific Easy Column, Waltham, MA) and separated using a gradient of acetonitrile and formic acid at a flow rate of 300 nl/min. The mass spectrometer operated in positive ion mode with an electrospray voltage of 1.5 kV. Precursors and fragments were detected over a mass range of m/z 100-1700 at the TOF detector. The timsTOF Pro utilized parallel accumulation serial fragmentation (PASEF) mode, with parameters including an ion mobility coefficient range of 0.6 to 1.6 Vs cm² and 1 MS scan followed by 10 MS/MS PASEF scans. Active exclusion with a 24 s release time was enabled for data collection.

Data analysis

The raw MS data were analyzed using MaxQuant software (version 1.6.14). The search was conducted against the Columba livia reference proteome (UniProt, downloaded December 2023; ∼28,000 entries). Carbamidomethylation of cysteine was set as a fixed modification; oxidation of methionine and acetylation of the protein N-terminus were set as variable modifications. The precursor mass tolerance was set to 20 ppm for first search and 6 ppm for main search; fragment mass tolerance was set to 20 ppm. Trypsin was specified as the cleavage enzyme, allowing up to two missed cleavages. A 1% false discovery rate (FDR) was applied at both peptide-spectrum match (PSM) and protein levels.

For functional annotation and enrichment analysis, Gene Ontology (GO) and InterPro annotations were obtained using InterProScan-5. Protein family and pathway classification was conducted using Clusters of Orthologous Groups (COG) and KEGG pathway databases. Protein-protein interaction networks were predicted using STRING (version 11.5). Differentially expressed proteins (DEPs) were identified using a |fold change| > 1.5 and adjusted P-value < 0.05 (Benjamini-Hochberg correction). Enrichment analysis of GO terms and KEGG pathways was performed using the clusterProfiler package in R. The C group (5.66 mg/kg) was designated as the negative control group for comparisons with both the T1 (9.66 mg/kg) and T4 (21.66 mg/kg) groups, in order to assess the effects of increasing dietary copper supplementation. Additionally, for comparisons between the T1 and T4 groups, the T1 group (9.66 mg/kg) served as the negative control to evaluate the effects of a high copper level (21.66 mg/kg).

Statistical analyses

The data were assessed for normality using the Shapiro–Wilk test and for homogeneity of variances using Levene's test. Data with a normal distribution (Shapiro–Wilk test > 0.05) were analyzed by one-way ANOVA followed by Duncan's multiple comparisons (SAS 9.4, 2011, SAS Institute Inc, Cary, NC). For data that did not follow a normal distribution (Shapiro–Wilk test ≤ 0.05), the Kruskal–Wallis test was performed (SAS 9.4, P < 0.05 was considered statistically significant), and if significant, pairwise comparisons were conducted using the Dwass–Steel–Critchlow–Fligner test. Both quadratic and linear effects were analyzed using orthogonal polynomial contrasts, with significance at P ≤ 0.05. The reported P-values were adjusted using the Benjamini–Hochberg procedure. A P-value of < 0.05 was considered statistically significant. Based on the indices of shear force and TL concentration, which followed a quadratic curve, a quadratic regression equation:

$$y=a{x}^2+bx+c$$

y: index, x: dietary copper level was developed to estimate the copper requirements using curve regression analysis in SAS (SAS 9.4). Results are presented as the mean ± standard error of the mean (SEM).

Results

Effect of dietary copper level on growth performance and carcass traits of squabs

As indicated in Table 2, different levels of dietary copper supplements did not affect the average ADG, ADFI, and FDR of squabs (P > 0.05, Table 2). Similarly, there were no effects on body weight, slaughter weight, slaughter percentage, eviscerated weight, eviscerated percentage, breast muscle weight, or breast muscle percentage across different dietary copper levels (P > 0.05, Table 2).

Table 2.

Effects of dietary copper levels on carcass trait of squabs.

Variable	Dietary copper supplementation (mg/kg)					SEM	P-value	P-value Linear	P-value Quadratic
	5.66	9.66	13.66	17.66	21.66
ADG (g)	18.0	18.0	17.5	18.1	18.4	0.0831	0.201	0.996	0.930
ADFI (g)	75.0	75.6	75.7	75.5	76.6	0.286	0.786	0.238	0.651
FDR (g:g)	4.21	4.23	4.39	4.21	4.24	0.0272	0.574	0.661	0.740
Body weight (g)	505	489	463	495	501	17.2	0.509	0.946	0.141
Carcass weight (g)	421	414	390	429	425	16.2	0.530	0.676	0.290
Carcass percentage (%)	83.1	84.6	84.3	86.7	84.6	1.14	0.300	0.168	0.302
Half-Eviscerated weight (g)	324	309	300	338	341	17.7	0.456	0.571	0.260
Half-Eviscerated percentage (%)	63.8	63.1	64.6	67.9	67.7	1.85	0.243	0.129	0.728
Breast muscle weight (g)	77.7	68.5	68.0	71.4	70.9	4.22	0.533	0.443	0.196
Breast muscle (%)	24.2	22.1	23.1	21.5	20.7	1.22	0.380	0.0783	0.991

ADG, average daily weight gain; ADFI, average daily feed intake; FDR, feed conversion ratio.

Results are means with n = 8 per group.

Effect of dietary copper level on breast muscle quality and lipids of squabs

Dietary copper levels did not affect meat pH_{24 h}, drop loss, and cooking loss (P > 0.05, Table 3). However, the shear force of the breast muscle in the group with 5.66 mg copper/(kg diet) was the lowest (P < 0.05, Table 3), and it increased linearly or quadratically as the dietary copper level increased. The copper requirement was assessed to be 17.2 mg copper/(kg diet) through quadratic curve regression analysis (y = -0.188x² + 6.47x - 8.92, P = 0.0258, R² = 0.974, Fig. 1).

Table 3.

Effects of dietary copper levels on breast meat quality and lipids content of squabs.

Variable	Dietary copper supplementation (mg/kg)					SEM	P-value	P-value Linear	P-value Quadratic
	5.66	9.66	13.66	17.66	21.66
pH24h	5.63	5.62	5.62	5.60	5.54	0.0506	0.710	0.206	0.560
Drip loss (%)	0.667	1.44	2.16	2.03	1.11	0.332	0.192	0.792	0.802
Shear force (N/cm)	22.8c	33.5b	45.4a	48.1a	42.4a	2.91	<0.001	<0.001	0.001
Cooking loss (%)	17.4	20.2	17.4	19.2	19.6	1.69	0.671	0.531	0.983
TL (%)	5.92a	5.22b	3.65c	3.94c	4.12c	0.176	<0.001	<0.001	<0.001
TG (mmol/mg)	0.520a	0.415b	0.248c	0.260c	0.207c	0.0192	<0.001	<0.001	0.003
T-CHO (mmol/mg)	0.871a	0.531b	0.337c	0.346c	0.300c	0.0212	<0.001	<0.001	<0.001
FFA (umol/mg)	361a	222b	225b	228b	211b	7.60	<0.001	<0.001	<0.001

TL, total lipids; TG, triglyceride; T-CHO, total cholesterol; FFA, free fatty acid.

Results are means with n = 8 per group.

^a-cMeans with different superscripts within the same column differ significantly (P < 0.05)

Fig. 1.

Quadratic regression analysis for copper requirements.

As shown in Table 3, the TL, TG, T-CHO, and FFA concentration in the breast muscle of the group with 5.66 mg copper/(kg diet) were highest (P < 0.05, Table 3), and linear or quadratic increased as dietary copper level increased. According to breast muscle TL concentration, the copper requirement was assessed to be 18.4 mg copper/(kg diet) through quadratic curve regression analysis (y = 0.00352x² – 0.130x + 1.48, P = 0.0248, R² = 0.976, Fig. 1).

Breast muscle fatty acid composition

The evaluation of the composition of breast muscle fatty acids is shown in Table 4. There were no significant differences among the five groups for total monounsaturated fatty acids (∑MUFA), total polyunsaturated fatty acids (∑PUFA), ∑PUFA/∑MUFA, or ∑PUFA/total saturated fatty acid (∑SFA) of breast muscle (P > 0.05, Table 4). However, compared to the group with 5.66 mg copper/(kg diet), other groups tended to have lower SFA concentrations in the breast muscle (0.05 < P < 0.01, Table 4). Specifically, with 9.66∼21.66 mg copper/(kg diet) decreased C11:0∼C15:0 and C17:0 concentration in breast muscle (P < 0.05, Table 4). In ∑PUFA, compared to the group with 5.66 mg copper/(kg diet), other groups had lower C14:1, C15:1, and C17:1 contents, and these increased linearly or quadratically as the dietary copper level increased. Moreover, the content of C18:3 methyl linolenate (MUFA) showed a trend of initially increasing and then decreasing with the increasing dietary copper level.

Table 4.

Effect of dietary copper level on fatty acid composition of squab breast muscle at 28 d.

Fatty acids, g/kg of lipids	Dietary copper supplementation (mg/kg)					SEM	P-value	P-value Linear	P-value Quadratic
	5.66	9.66	13.66	17.66	21.66
C11:0	69.2a	30.0b	21.2b	0.00b	0.00b	4.93	0.001	0.001	0.059
C12:0	85.1a	27.7b	12.1bc	1.90c	0.326c	6.31	<0.001	<0.001	0.006
C13:0	104a	49.5ab	15.9b	2.83b	8.03b	8.57	<0.001	<0.001	0.018
C14:0	119a	86.1ab	49.1bc	30.5c	28.7c	10.3	<0.001	<0.001	0.215
C14:1	174a	95.9b	57.8bc	23.9c	28.8c	12.9	<0.001	<0.001	0.022
C15:0	498a	332b	251bc	173bc	114c	46.1	<0.001	<0.001	0.293
C15:1	170a	87.8b	53.2b	36.4b	39.9b	16.3	0.024	0.002	0.332
C16:0	919	951	848	618	1035	165	0.368	0.859	0.343
C16:1	265	246	232	152	273	41.5	0.348	0.644	0.230
C17:0	171a	91.3b	95.6b	74.8b	60.3b	20.5	0.015	<0.001	0.011
C17:1	173a	35.0b	24.6b	11.0b	32.2b	20.6	<0.001	<0.001	<0.001
C18:0	803	726	824	632	920	126	0.450	0.758	0.354
C18:IT	645	613	638	427	903	149	0.276	0.453	0.185
C18:1	771	681	734	524	959	181	0.276	0.434	0.160
C18:2TT	781	732	711	529	950	118	0.186	0.662	0.108
C18:2	51.7	53.9	87.7	28.7	58.9	26.3	0.808	0.913	0.742
C18:3 METHYL GAMMA LINOLENA	206	400	114	193	128	42.0	0.149	0.073	0.361
C20:1	153	184	244	121	152	46.6	0.726	0.669	0.915
C18:3 METHYL LINOLENATE	94.8b	203a	171ab	78.8b	107b	22.6	0.028	0.262	0.271
C21:0	1875	1845	1653	1235	1615	379	0.824	0.451	0.583
C23:0	303	234	249	245	303	53.1	0.610	0.258	0.719
C24:0	764	613	299	350	366	116	0.690	0.437	0.879
∑SFA	4732a	3961ab	3177ab	2510b	3435ab	518	0.064	0.022	0.054
∑MUFA	2190	1787	1762	1203	2282	384	0.242	0.773	0.105
∑PUFA	1083	1062	955.5	669.5	1134	132	0.107	0.582	0.123
∑PUFA/∑MUFA	0.534	0.718	0.593	0.624	0.605	0.0750	0.612	0.744	0.502
∑MUFA/∑SFA	0.251	0.328	0.343	0.313	0.351	0.0403	0.435	0.096	0.670

∑SFA: total saturated fatty acids = C11:0 + C12:0 + C13:0 + C14:0 +C15:0 + C16:0 + C17:0 + C18:0 + C21:0+ C23:0+ C24:0. ∑MUFA: total monounsaturated fatty acids = C14:1 + C15:1 + C16:1 + C17:1 + C18:1T + C18:1 + C20:1. ∑PUFA: total polyunsaturated fatty acids = C18:2TT + C18:2 + C18:3 METHYL GAMMA LINOLENA + C18:3 METHYL LINOLENATE.

Results are means with n = 8 per group.

^a-cMeans with different superscripts within the same column differ significantly (P < 0.05)

Breast muscle protein profile

Overall, the proteomic analysis of the squab breast muscle identified 2562 proteins (Additional file 1). As shown in Table 6 and Fig. 2, dietary copper supplementation markedly affected breast muscle proteomics (Fig. 2A-F). Among them, 19 proteins were significantly enriched in C: copper 5.66 mg/kg vs. T1: copper 9.66 mg/kg (P < 0.05, |FoldChange| ≥ 1.5, Table 5 and Fig. 2G). Compared to the C group, the T1 group had 10 down-regulated proteins and 9 up-regulated proteins. 35 proteins were significantly enriched in C: copper 5.66 mg/kg vs. T4: copper 21.66 mg/kg (P < 0.05, |FoldChange| ≥ 1.5, Table 5 and Fig. 2H). Compared to the C group, the T4 group had 10 down-regulated proteins and 15 up-regulated proteins. 10 proteins were significantly enriched in T1 vs. T4 (P < 0.05, |FoldChange| ≥ 1.5, Table 5 and Fig. 2I), and these proteins were all up-regulated.

Table 6.

Functional enrichment analysis of differentially expressed proteins.

Treat	Function annotation	P-value	Enrichment	Gene	Proteins associated with function
C vs. T1	Lysine biosynthesis	0.013	1	ALDH7A1	aldehyde dehydrogenase (NAD(+))
	Fatty acid degradation	0.014	0.071	ALDH7A1, TrEMBL	aldehyde dehydrogenase (NAD(+)), Alcohol dehydrogenase 1-like
	Glycolysis / Gluconeogenesis	0.027	0.05	ALDH7A1, TrEMBL	aldehyde dehydrogenase (NAD(+)), Alcohol dehydrogenase 1-like
	Retinol metabolism	0.038	0.2	TrEMBL	Alcohol dehydrogenase 1-like
	Ascorbate and aldarate metabolism	0.044	0.167	ALDH7A1	aldehyde dehydrogenase (NAD(+))
	Ether lipid metabolism	0.050	0.143	ENPP6	glycerophosphocholine choline phosphodiesterase
C vs. T4	Insulin signaling pathway	0.017	0.067	PPP1R3D, GRB2, PRKAA2	Protein phosphatase 1, regulatory subunit 3D, Growth factor receptor-bound protein 2, 5′-AMP-activated protein kinase catalytic subunit alpha-2
	Lysosome	0.022	0.111	CLTC, AP3B1	Clathrin heavy chain, AP-3 complex subunit beta
	Lysine biosynthesis	0.024	1	ALDH7A1	aldehyde dehydrogenase (NAD(+))
	Glycine, serine and threonine metabolism	0.026	0.1	ALDH7A1, GATM	aldehyde dehydrogenase (NAD(+)), Glycine amidinotransferase
	FoxO signaling pathway	0.031	0.091	GRB2, PRKAA2	Growth factor receptor-bound protein 2, 5′-AMP-activated protein kinase catalytic subunit alpha-2
	Arginine and proline metabolism	0.039	0.08	ALDH7A1, GATM	aldehyde dehydrogenase (NAD(+)), Glycine amidinotransferase
	Gap junction	0.047	0.071	TrEMBL, GRB2	Tubulin alpha chain, Growth factor receptor-bound protein 2
	Apoptosis	0.050	0.069	TrEMBL, DIABLO	Tubulin alpha chain, Direct IAP-binding protein with low pI
T1 vs. T4	Butanoate metabolism	0.031	0.083	AACS	Acetoacetyl-CoA synthetase
	Propanoate metabolism	0.041	0.04	SUCLG2	Succinate–CoA ligase [GDP-forming] subunit beta, mitochondrial

Fig. 2.

Effect of dietary copper levels on the protein profile of squab breast muscle.

(A–C) Principal component analysis (PCA) score plots comparing the C and T1 groups (A), C and T4 groups (B), and T1 and T4 groups (C).

(D–F) Heatmap analysis comparing the C and T1 groups (D), C and T4 groups (E), and T1 and T4 groups (F).

(G–I) Volcano plots showing differentially expressed proteins (DEPs) between the C and T1 groups (G), C and T4 groups (H), and T1 and T4 groups (I).

(J–L) KEGG pathway enrichment analysis of DEPs between the C and T1 groups (J), C and T4 groups (K), and T1 and T4 groups (L).

C group (5.66 mg/kg dietary copper) served as the negative control when compared with the T1 (9.66 mg/kg dietary copper) and T4 (21.66 mg/kg dietary copper) groups. T1 group (9.66 mg/kg dietary copper) served as the negative control when compared with the T4 group (21.66 mg/kg dietary copper).

Table 5.

Effect of dietary copper level on protein profile of squab breast muscle at 28 d.

Treat	Accession number	Gene name	Protein name	P-value	FoldChange
C vs. T1	A0A2I0MJW1	LGALS1	Galectin	0.021	-2.81
	A0A2I0LST2	ERGIC1	Endoplasmic reticulum-Golgi intermediate compartment protein	0.042	-2.65
	A0A2I0MMZ6	ENPP6	glycerophosphocholine choline phosphodiesterase	0.008	-2.59
	A0A2I0MXW0	BPHL	Biphenyl hydrolase-like (Serine hydrolase)	0.049	-2.39
	R7VT25	PCMTD1	Protein-L-isoaspartate O-methyltransferase domain-containing protein 1	0.022	-2.31
	A0A2I0M8Z2	UniProtKB unreviewed (TrEMBL)	Alcohol dehydrogenase 1-like	0.002	-2.25
	A0A2I0LQV6	UniProtKB unreviewed (TrEMBL)	Protein ADP-ribosylarginine hydrolase	0.021	-2.05
	A0A2I0M3Y8	HSPA5	78 kDa glucose-regulated protein	0.025	-2.01
	A0A2I0MAW8	ITGB1BP2	Integrin beta 1 binding protein (Melusin) 2	0.025	-1.95
	A0A2I0MR21	CUL2	Cullin 2, transcript variant X1	0.048	-1.93
	A0A2I0MQK0	UniProtKB unreviewed (TrEMBL)	Obscurin-like	0.014	2.10
	A0A2I0LXC9	AK3	Adenylate kinase 3, transcript variant X2	0.034	2.31
	A0A2I0M1B6	MRPS36	Mitochondrial ribosomal protein S36	0.025	2.74
	A0A2I0LW64	GPX1	glutathione peroxidase	0.014	2.78
	A0A2I0M717	SPAG9	Sperm-associated antigen 9, transcript variant X3	0.044	2.80
	A0A2I0M7N0	ICT1	Large ribosomal subunit protein mL62	0.032	2.91
	A0A2I0LNR9	UniProtKB unreviewed (TrEMBL)	Tubulin alpha chain	0.041	3.27
	A0A2I0LS68	ALDH7A1	aldehyde dehydrogenase (NAD(+))	0.045	3.47
	A0A2I0LGK9	HINT2	Histidine triad nucleotide binding protein 2	0.039	4.36
C vs. T4	R7VTQ7	PBLD	Phenazine biosynthesis-like protein domain containing	0.032	-4.67
	A0A2I0M894	DIABLO	Direct IAP-binding protein with low pI	0.037	-2.77
	A0A2I0MCC0	PRKAA2	5′-AMP-activated protein kinase catalytic subunit alpha-2	0.002	-2.70
	A0A2I0MDF0	CLPX	Caseinolytic mitochondrial matrix peptidase chaperone subunit	0.022	-2.06
	A0A2I0MVL5	UniProtKB unreviewed (TrEMBL)	glutathione transferase	0.020	-2.04
	A0A2I0MQS9	FYCO1	FYVE and coiled-coil domain containing 1	0.040	-2.03
	A0A2I0LQB1	NIF3L1	NIF3-like protein 1	0.032	-2.02
	A0A2I0M4K7	MMGT1	Membrane magnesium transporter 1	0.041	-1.98
	R7VSV6	LRRC20	Leucine rich repeat containing 20	0.027	-1.90
	A0A2I0MRG1	GPD1L	Glycerol-3-phosphate dehydrogenase [NAD(+)]	0.049	-1.90
	A0A2I0MIU7	FN1	Fibronectin	0.036	1.94
	A0A2I0M7L1	GRB2	Growth factor receptor-bound protein 2	0.036	1.94
	A0A2I0LYH1	CLTC	Clathrin heavy chain	0.044	1.94
	A0A2I0M262	UniProtKB unreviewed (TrEMBL)	Small nuclear ribonucleoprotein-associated protein B'-like	0.013	2.02
	A0A2I0LNL2	LEMD2	LEM domain containing 2	0.031	2.03
	A0A2I0M665	PPP1R3D	Protein phosphatase 1, regulatory subunit 3D	0.007	2.07
	A0A2I0MD05	GATM	Glycine amidinotransferase	0.029	2.10
	A0A2I0MHQ3	UniProtKB unreviewed (TrEMBL)	Protein lin-7 homolog C	0.032	2.16
	A0A2I0MU51	MRPL19	Large ribosomal subunit protein bL19m	0.022	2.22
	A0A2I0M920	METAP1	Methionine aminopeptidase	0.016	2.29
	A0A2I0LGR3	MRPL43	Large ribosomal subunit protein mL43	0.044	2.42
	A0A2I0M604	TPD52L2	Tumor protein D52-like 2	0.012	2.47
	A0A2I0M1B6	MRPS36	Mitochondrial ribosomal protein S36	0.007	2.50
	A0A2I0MLD6	ACOT9	Acyl-CoA thioesterase 9	0.046	2.57
	A0A2I0MNL8	SLIRP	SRA stem-loop interacting RNA binding protein	0.023	2.58
	A0A2I0LKS0	UniProtKB unreviewed (TrEMBL)	Myosin heavy chain, embryonic smooth muscle isoform-like	0.023	2.61
	A0A2I0LUH9	UniProtKB unreviewed (TrEMBL)	Kinectin	0.028	2.62
	A0A2I0M804	CDH5	Cadherin-5	0.031	2.69
	A0A2I0M717	SPAG9	Sperm associated antigen 9, transcript variant X3	0.004	2.86
	A0A2I0M153	AP3B1	AP-3 complex subunit beta	0.028	2.95
	A0A2I0MEH2	ADD3	Adducin 3 (Gamma), transcript variant X2	0.044	3.03
	A0A2I0LS68	ALDH7A1	aldehyde dehydrogenase (NAD(+))	0.023	3.36
	A0A2I0LNR9	UniProtKB unreviewed (TrEMBL)	Tubulin alpha chain	0.023	3.38
	A0A2I0MS36	UniProtKB unreviewed (TrEMBL)	Complement C4	0.012	3.55
	A0A2I0MBK5	UniProtKB unreviewed (TrEMBL)	Histidine-rich glycoprotein	0.005	3.89
T1 vs. T4	A0A2I0LKH4	UniProtKB unreviewed (TrEMBL)	TNase-like domain-containing protein	0.048	2.30
	A0A2I0M8H6	AACS	Acetoacetyl-CoA synthetase	0.041	3.07
	A0A2I0M920	METAP1	Methionine aminopeptidase	0.047	1.94
	A0A2I0M9M5	SUCLG2	Succinate–CoA ligase [GDP-forming] subunit beta, mitochondrial	0.042	2.18
	A0A2I0MA37	VDAC1	Voltage-dependent anion-selective channel protein 1	0.039	2.82
	A0A2I0MH09	HNRNPDL	Heterogeneous nuclear ribonucleoprotein D-like, transcript variant X1	0.036	2.24
	A0A2I0MHR9	CAPRIN1	Cell cycle associated protein 1	0.043	2.56
	A0A2I0MJW1	LGALS1	Galectin	0.010	3.47
	A0A2I0MNF2	TMED10	Transmembrane emp 24 domain-containing protein 10	0.012	2.41
	A0A2I0MXD7	SNTB1	Syntrophin, beta 1 (Dystrophin-associated protein A1, 59kDa, basic component 1)	0.024	3.29

FoldChange in C vs. T1 is expressed as the ratio of the 4 mg/kg copper supplement group to the control (CON) group without copper supplementation. FoldChange in C vs. T4 is expressed as the ratio of the 16 mg/kg copper supplement group to the CON group without copper supplementation. FoldChange in T1 vs. T4 is expressed as the ratio of the 16 mg/kg copper supplement group to the 4 mg/kg copper supplement group. For down-regulated proteins, the fold change was transformed to the corresponding negative value.

Results are means with n = 6 per group.

In comparison between the C and T1 groups, differentially expressed proteins were enriched in the Lysine biosynthesis (P = 0.013, Table 6 and Fig. 2J), Fatty acid degradation (P = 0.014, Table 6 and Fig. 2J), Glycolysis / Gluconeogenesis (P = 0.0266, Table 6 and Fig. 2 J), Retinol metabolism (P = 0.038, Table 6 and Fig. 2J), Ascorbate and aldarate metabolism (P = 0.044, Table 6 and Fig. 2J), and Ether lipid metabolism (P = 0.050, Table 6 and Fig. 2J). In comparison between the C and T4 groups, differentially expressed proteins were enriched in the Insulin signaling pathway (P = 0.017, Table 6 and Fig. 2K), Lysosome (P = 0.022, Table 6 and Fig. 2K), Lysine biosynthesis (P = 0.024, Table 6 and Fig. 2K), Glycine, serine and threonine metabolism (P = 0.026, Table 6 and Fig. 2K), FoxO signaling pathway (P = 0.031, Table 6 and Fig. 2K), Arginine and proline metabolism (P = 0.039, Table 6 and Fig. 2K), Gap junction (P = 0.047, Table 6 and Fig. 2K), and Apoptosis (P = 0.050, Table 6 and Fig. 2K). In comparison between the T1 and T4 groups, differentially expressed proteins were enriched in the Butanoate metabolism (P = 0.031, Table 6 and Fig. 2L) and Propanoate metabolism (P = 0.041, Table 6 and Fig. 2L).

Compared with the C group, there were aldehyde dehydrogenase (NAD(+)) up-regulated involved in lysine biosynthesis, fatty acid degradation, glycolysis/gluconeogenesis, as well as ascorbate and aldarate metabolism; alcohol dehydrogenase 1-like down-regulated involved in fatty acid degradation, glycolysis/gluconeogenesis, and retinol metabolism; glycerophosphocholine choline phosphodiesterase down-regulated involved in Ether lipid metabolism by copper supplement with 4 mg/kg (T1, Table 6). Compared with the C group, there were two proteins (protein phosphatase 1 and growth factor receptor-bound protein 2) up-regulated and one protein (5′-AMP-activated protein kinase catalytic subunit alpha-2) down-regulated involved in the insulin signaling pathway; two proteins up-regulated (clathrin heavy chain and AP-3 complex subunit beta) involved in the lysosome; one protein up-regulated (aldehyde dehydrogenase (NAD(+))) involved in lysine biosynthesis; two proteins up-regulated (aldehyde dehydrogenase (NAD(+)) and glycine amidinotransferase) involved in the glycine, serine and threonine metabolism; one protein (growth factor receptor-bound protein 2) up-regulated and one protein (5′-AMP-activated protein kinase catalytic subunit alpha-2) down-regulated involved in FoxO signaling pathway; two proteins (aldehyde dehydrogenase (NAD(+)) and glycine amidinotransferase) up-regulated involved in arginine and proline metabolism, two proteins (tubulin alpha chain and growth factor receptor-bound protein 2) up-regulated involved in gap junction; one protein (tubulin alpha chain) up-regulated and one protein (direct IAP-binding protein with low pI) down-regulated involved in apoptosis by copper supplement with 16 mg/kg (T4, Table 6). Compared with the T1 group, there was one protein (acetoacetyl-CoA synthetase) up-regulated involved in butanoate metabolism and one protein (succinate-CoA ligase [GDP-forming] subunit beta) up-regulated involved in propanoate metabolism in T4 group (Table 6).

Discussion

Previously, we investigated the role of copper as an essential trace element in regulating egg quality, tissue copper deposition, and antioxidant status in squabs (Liu et al., 2024). While these findings highlighted the physiological importance of copper, they did not address its potential influence on traits directly related to consumer preference_such as meat quality and muscle development. Given that an animal’s nutritional and metabolic status can significantly affect carcass characteristics and meat quality (Mendonça et al., 2020), we hypothesized that copper supplementation may influence meat traits through its role in redox homeostasis, mitochondrial function, and muscle protein synthesis. Therefore, this study aimed to evaluate the effects of different dietary copper levels on growth performance, slaughter traits, and breast muscle quality in squabs, while also exploring potential underlying mechanisms through lipid profile and proteomic analysis.

Growth performance and carcass traits

Although no significant differences were observed in ADG, ADFI, and FDR among the different dietary copper levels, these findings are still meaningful in the context of production economics. The absence of negative effects on growth performance suggests that increasing dietary copper up to 21.66 mg/kg did not impair feed intake or growth, thereby offering flexibility in nutritional strategies. This may be particularly relevant when dietary copper is supplemented to enhance meat quality or improve health-related traits. Maintaining stable performance parameters while modifying feed composition ensures that producers do not compromise economic returns while aiming to enhance product quality.

Muscle shear force and lipid concentration

Muscle shear force is one of the common indicators used to evaluate meat quality and is a reliable measure of tenderness. Both excessively low and high shear forces are detrimental to meat texture, with low shear force leading to overly soft meat, which lacks the preferred firm texture (Wang et al., 2021). In this study, low dietary copper levels significantly reduced the shear force of pigeon breast muscle, approximately halving it compared to the groups receiving copper supplementation (13.66∼21.66 mg/kg), thereby decreasing the chewiness of pigeon meat. In chewiness evaluations, both excessively low and high shear forces can adversely affect texture. Low shear force, in particular, leads to overly soft meat, lacking in elasticity and the fresh, while moderately firm texture that consumers prefer (Wang et al., 2021). Meat that is too soft, often characterized as PSE (pale, soft, exudative), tends to be less favored by consumers, who typically seek firmer, more vibrant red meat, as it negatively impacts their sensory perception of freshness. The shear force of meat is affected by factors such as age, moisture content, muscle fiber, and lipid content (Bulgaru et al., 2022; Li et al., 2022b). In this study, increased concentrations of TL, TG, T-CHO, and FFA were observed in the breast muscle of copper-deficient pigeons, supporting the hypothesis that lipid accumulation disrupts normal muscle structure and contributes to the reduction in shear force. This is consistent with previous findings that excessive intramuscular lipids can impair meat quality by altering muscle fiber spacing and water-holding capacity (Li et al., 2021; Peng et al., 2021).

Therefore, the reduction in muscle shear force under copper-deficient conditions likely arises from a mechanism: increased intramuscular fat accumulation caused by altered lipid metabolism. These changes ultimately compromise the integrity and texture of breast muscle.

Fatty acid composition

The accumulation of lipids in the breast muscle can affect not only muscle texture but also the fatty acid composition, which plays a pivotal role in the overall nutritional quality of the meat. Copper is an essential trace element involved in lipid metabolism regulation through its role as a cofactor in multiple enzymes, including cytochrome c oxidase and superoxide dismutase. These enzymes are critical for mitochondrial function and oxidative stress defense. Copper deficiency has been associated with impaired mitochondrial fatty acid β-oxidation, leading to increased lipid deposition and altered fatty acid profiles in muscle tissue. In the present study, we observed that in parallel with the increase in beneficial fatty acids, appropriate copper supplementation significantly reduced the total saturated fatty acid (∑SFA) content in pigeon breast muscle, particularly for odd-chain SFAs such as C11:0, C13:0, C15:0, and C17:0. SFA accumulation is commonly associated with increased tissue fat deposition and adverse lipid profiles, which may negatively impact both meat quality and consumer health. High SFA intake has been linked to elevated serum cholesterol and a heightened risk of cardiovascular diseases (Jörg et al., 2016; Zhuang et al., 2020). Therefore, in the current study, copper deficiency in pigeon feed led to an increase in ∑SFA content, which could diminish the texture, nutritional, and health benefits of pigeon meat by promoting undesirable lipid profiles. The results suggested that dietary copper levels can influence the balance between saturated and unsaturated fatty acids, which are crucial determinants of meat quality and health value.

In contrast, ∑PUFA content remained unchanged across different copper treatment groups. However, a more nuanced effect was observed at the level of individual fatty acids. Specifically, dietary copper at 9.66 mg/kg significantly elevated the concentration of C18:3 methyl linolenate, an ω-3 PUFA with well-documented health benefits. This compound not only contributes to the fresh, clean aroma of meat-enhancing sensory appeal-but also offers anti-inflammatory, cholesterol-lowering, and skin health-promoting effects (Kratz et al., 2013; Nuiyen et al., 2022). The incorporation of ω-3 PUFAs such as methyl linolenate into the diet is increasingly recognized as a beneficial strategy for improving the nutritional quality of animal products. In the present study, 9.66 mg copper/(kg diet) increased the levels of methyl linolenate in pigeon breast muscle, which suggests that adding an appropriate amount of copper can be advantageous for enhancing overall health, improving the quality, nutritional value, and health benefits of pigeon meat. These findings supported the notion that moderate copper supplementation can selectively enhance beneficial fatty acids like ω-3 PUFAs without affecting total PUFA content, which may improve the nutritional profile of pigeon meat.

This dual regulatory copper effect-a shift in SFA content coupled with the enrichment of functional ω-3 PUFA-demonstrates the potential of moderate copper supplementation to optimize the fatty acid composition of pigeon meat. Importantly, this modulation occurs without altering the total PUFA levels, indicating a qualitative rather than quantitative enhancement. Such improvements are of both nutritional and commercial value, contributing to the development of healthier meat products aligned with consumer demand for functional animal source foods.

Nevertheless, it is important to acknowledge certain methodological limitations of the lipidomics approach used in this study. Firstly, the LC-MS/MS-based lipidomics analysis is inherently semi-quantitative, relying on relative peak intensities rather than absolute concentrations, which may introduce variability when comparing lipid abundances across groups. Secondly, despite the use of high-resolution mass spectrometry and stringent quality control procedures, the potential for isomer misidentification cannot be fully excluded, as structurally similar isomers may not be completely resolved under the chromatographic conditions applied. These limitations should be taken into account when interpreting the lipidomic results. However, the consistency of lipid profile alterations across biological replicates, together with the integration of complementary phenotypic and biochemical data, strengthens the robustness and validity of the key findings.

Protein profiles

In addition to shifts in free fatty acid profiles, the present study reveals significant alterations in protein expression profiles in response to dietary copper levels, indicating that copper may influence meat quality through both metabolic and structural pathways.

As a spherical molecule, Tubulin plays a vital role in the formation of the cell cytoskeleton structure and the intracellular transport of substances (Ambit et al., 2011; Mckean et al., 2001). At the same time, tubulin is a highly conserved protein that can maintain stable expression levels. Consequently, it is commonly utilized as a reference protein in numerous experiments. However, it is important to acknowledge that alterations in the tubulin expression level could potentially impact the structural stability of cells. In this study, we found that tubulin protein expression was significantly upregulated in response to increased dietary copper levels. Specifically, compared with the low-copper group (5.66 mg/kg), the expression of tubulin was upregulated by 3.27-fold in the 9.66 mg/kg group and by 3.38-fold in the 21.66 mg/kg group. This pattern suggests a positive regulatory effect of copper on tubulin synthesis or stabilization. One plausible explanation involves the redox-regulatory role of copper. Copper is a key component of the antioxidant enzyme CuZn-SOD, and our previous study showed that CuZn-SOD activity was significantly reduced in the low-copper group (Liu et al., 2024). The resulting oxidative stress may destabilize or impair the synthesis of structural proteins such as tubulin, consistent with prior reports that oxidative stress can modify tubulin function and reduce its polymerization efficiency (Keshavarzian et al., 2003; Landino et al., 2004). Thus, adequate copper supplementation may indirectly promote cytoskeletal protein stability by improving the intracellular redox environment. This mechanism may have downstream implications for meat quality. Tubulin is essential for maintaining muscle fiber organization and mechanical strength, which are closely related to meat texture parameters such as shear force and chewiness. Therefore, copper-mediated preservation of cytoskeletal integrity could be one of the molecular bases for the improved meat texture observed in the medium- and high-copper groups.

Further proteomic analysis revealed that aldehyde dehydrogenase (NAD(+)) and alcohol dehydrogenase 1-like were significantly enriched in the fatty acid degradation pathway. These enzymes are pivotal in fatty acid metabolism.

Aldehyde dehydrogenase is responsible for converting toxic aldehyde intermediates, which accumulate during fatty acid oxidation, into less harmful acids. Its reduced expression in the low-copper group suggests compromised fatty acid oxidation and increased aldehyde accumulation. The impaired clearance of aldehydes may exacerbate oxidative stress and mitochondrial damage, ultimately inhibiting energy metabolism and muscle development (Rahadiani et al., 2011; Rassouli et al., 2016).

Alcohol dehydrogenase 1-like is another key enzyme, dependent on zinc as a cofactor. Its downregulation in the low-copper group may also be explained by copper–zinc interactions. Copper deficiency has been reported to impair zinc absorption and transport, thereby affecting the activity of zinc-dependent enzymes (Arredondo et al., 2006). This cross-talk between trace elements reveals how copper deficiency may indirectly disrupt fatty acid degradation and energy homeostasis by affecting zinc metabolism.

Disruption of energy metabolism not only affects lipid balance but also impairs the development of muscle fibers, which require high levels of ATP during proliferation and differentiation (Demling, 2009). This may help explain the lower shear force observed in the breast muscle of pigeons fed a copper-deficient diet.

Moreover, the disruption of fatty acid oxidation may lead to a shift in lipid composition. As fatty acid β-oxidation is impaired, saturated fatty acids (SFA), which are metabolized more slowly, may accumulate. This is consistent with our observation that SFA levels were significantly increased in the low-copper group. Combined with our earlier finding that copper did not significantly change the total PUFA content but significantly increased the content of beneficial ω-3 PUFA (C18:3 methyl linolenate), we suggest that copper selectively modulates fatty acid profiles by enhancing oxidation of SFA and promoting deposition of functional PUFAs.

Taken together, our data suggest that dietary copper plays an integrated role in regulating both structural proteins (tubulin) and metabolic enzymes (aldehyde and alcohol dehydrogenases), thereby maintaining redox balance, cytoskeletal stability, lipid metabolism, and ultimately improving meat quality traits. These findings may provide novel mechanistic insights into how trace element nutrition, particularly copper, influences muscle biology and meat quality in pigeons. To our knowledge, this is the first study to systematically demonstrate how dietary copper modulates both cytoskeletal stability and fatty acid oxidation pathways in pigeon breast muscle.

For pigeon industry

Compared with other poultry species such as chickens, ducks, and turkeys, the research on copper requirements and supplementation strategies remains relatively limited. In these species, standardized nutritional requirements have been well-established (NRC, 1994), yet studies specifically investigating optimal dietary copper levels are scarce. Recent literature in chickens and turkeys has predominantly focused on the adverse effects of excessive copper supplementation, such as oxidative stress, liver damage, and microbiota dysbiosis (Zhong et al., 2024; Li et al., 2024). In contrast, the nutritional research on pigeons remains underdeveloped, and internationally recognized nutritional standards for this species are still lacking. The present study designed a gradient of dietary copper concentrations to explore the responses in pigeons. Importantly, our results indicate that the tested copper levels did not induce toxic effects, suggesting that these supplementation levels are safe and physiologically appropriate for pigeons. These findings provide valuable baseline data to help establish species-specific copper nutritional guidelines for pigeons, which differ from those of other poultry species.

We collected full-price feed samples for pigeons from various regions in China and conducted an analysis. The results revealed that the copper supplementation levels in the feed ranged from 3.8 mg/kg to 64.8 mg/kg (Supplement Table 1), showing significant variation. This discrepancy suggests substantial differences in copper levels in pigeon feed across different regions, which may be influenced by factors such as production standards, formulation design, and the source of raw materials. The variation in copper supplementation levels across different regions may impact the health status and meat quality of pigeons. Therefore, it is recommended to adjust dietary copper level formulations appropriately to ensure the nutritional value of pigeon meat. Conversely, in other regions, dietary copper level were insufficient, which may cause copper deficiency, adversely affecting the pigeons' growth and immune function.

To address this issue, and based on our experimental data, we employed quadratic regression analysis to assess the optimal copper supplementation level in pigeon feed. The regression analysis revealed that the optimal range for dietary copper supplementation was 17.2∼18.4 mg/kg. This range not only meets the physiological growth requirements of pigeons but also ensures adequate copper absorption without causing potential toxicity. More importantly, the recommended copper supplementation level is designed to meet the growth and development needs of pigeons while also enhancing the nutritional content of pigeon meat, thereby increasing its health value. This will contribute to providing high-quality, health-promoting pigeon meat products to consumers.

Conclusion

The results of this study suggest that appropriate dietary copper supplementation (17.2∼18.4 mg/kg) may enhance the chewiness and nutritional quality of pigeon meat by promoting tubulin protein expression and supporting lipid metabolism under the specific experimental conditions. These findings provide practical insights that could help guide the optimization of dietary copper levels to potentially improve certain meat quality traits and nutritional value in pigeon production.

Funding

This work was supported by the exploration project of the Beijing Academy of Agriculture and Forestry Sciences (TSXM202524), the Beijing Academy of Agriculture and Forestry Sciences agricultural science and technology demonstration extension project (JJP2024-029), the BAAFS foreign high-end expert “Import” project (2024-12), the innovation capacity building project of the Beijing Academy of Agriculture and Forestry Sciences (KJCX20230114).

Data availability

Data will be made available on request.

Conflict of interest

The authors declare no competing interests.

CRediT authorship contribution statement

Bo Zhang: Investigation, Formal analysis, Writing – original draft. Wenli Liu: Methodology, Validation. Li Shen: Data curation. Yusheng Gao: Investigation. Yuxin Shao: Validation. Yipu Li: Methodology. Yangyang Wang: Methodology. Dongdong Zhao: Methodology. Jing Li: Validation. Zheng Wang: Supervision, Project administration.

Disclosures

The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper.