N-Carbamylglutamate Promotes Growth and Immunity in Danzhou Chickens via Gut Microbiota-Metabolite Interactions Involving Sphingolipid and mTOR Pathways

Abstract

This study evaluated the effects of dietary supplementation with N-Carbamylglutamate (NCG) on growth performance, immune function, intestinal metabolites, and microbiota in Danzhou chickens. In a 35-day feeding trial, a total of 480 one-day-old female chicks were randomly assigned to a control group (basal diet) and three experimental groups supplemented with 400, 800, or 1200 mg/kg NCG, with 120 chicks in each group (n = 120). The results demonstrated that NCG, particularly at 400 mg/kg, significantly improved growth parameters, including average daily gain and feed conversion ratio, while enhancing immune function by increasing serum levels of immunoglobulins (IgA, IgY) and malate dehydrogenase (p < 0.05). Metabolomic analysis revealed that NCG modulated key pathways such as sphingolipid metabolism and mTOR signaling pathway, leading to significant changes in metabolites including L-arginine, ceramide, and docosahexaenoic acid (p < 0.05). 16S rDNA sequencing indicated that NCG induced structural shifts in the gut microbiota, primarily affecting Bacteroidota and Firmicutes, with several bacterial genera showing strong correlations with the observed metabolic changes (p < 0.05). Mechanistically, NCG promotes growth by facilitating arginine synthesis via the urea cycle and activating the mTOR signaling pathway, while its regulation of sphingolipid metabolism enhances immunomodulatory capacity. In conclusion, NCG enhances feed efficiency and immune competence by orchestrating the gut microbiota-metabolite network, demonstrating its potential for poultry production.

1. Introduction

Arginine plays a crucial role in avian physiology, serving as an essential substrate for protein synthesis and as a precursor for various bioactive molecules, including nitric ox-ide, polyamines, and creatine [1]. Through these roles, it critically regulates immune function, intestinal health, hormone secretion, and nutrient metabolism. However, endogenous arginine synthesis in poultry is limited, a constraint that often restricts growth performance—especially during periods of rapid development [2]. The conventional practice of supplementing diets with crystalline arginine is often associated with excessive costs and variable efficacy [3]. Given these limitations, identifying feed additives that can effectively and economically stimulate endogenous arginine synthesis is of considerable importance. N-Carbamylglutamate (NCG) functions as a structural analog of N-Acetylglutamate, a compound that plays a crucial role as the essential activator of carbamoyl phosphate synthase-I, an enzyme that is pivotal in regulating the rate-limiting step of the endogenous arginine synthesis pathway [4]. Research has conclusively demonstrated that NCG effectively mimics the biological function of N-acetylglutamate by activating the urea cycle in the intestinal-renal axis, a process that significantly enhances endogenous arginine synthesis [5]. Moreover, studies in swine, ruminants, and some aquatic species have confirmed that supplementation with 500 mg/kg NCG significantly promotes the growth of weaned piglets [6], while a daily dosage of 2 g/d enhances milk yield in dairy cows [7]. These findings indicate that NCG can improve nitrogen utilization, enhance growth performance, strengthen immune function, and promote intestinal health [8]. Although NCG has been investigated in poultry—especially local chicken breeds—research on its use remains relatively scarce. The optimal supplementation dosage, the precise mechanisms underlying NCG’s actions, and its comprehensive effects on the intestinal microbiome remain unclear. To address these knowledge gaps, we employed multi-omics technologies combined with traditional physiological measurements to comprehensively evaluate NCG’s holistic effects on local chicken breeds and elucidate the underlying intricate mechanisms. In this context, circulating immunoglobulins and cytokines emerge as particularly reliable biomarkers of the body’s defensive capabilities, with elevated levels being associated with a lower incidence of disease and a diminished need for antibiotic interventions [9].

The gut microbiota, a complex community of microorganisms residing in the intestinal tract, engages in dynamic crosstalk with the host via metabolite secretion and signaling, thereby exerting profound influences on nutrient digestion and absorption, intestinal barrier function, immune response modulation, and overall host metabolism [10,11]. As the primary site of nutrient assimilation and the body’s largest immune organ, intestinal structural integrity—reflected by villus height, crypt depth, and the villus-to-crypt ratio—is a key determinant of growth potential and health status in animals [12,13]. Variations in these morphological parameters directly impact the nutrient absorptive surface area and intestinal epithelial turnover rate, both of which are closely linked to gut microbial homeostasis [14,15]. Additionally, circulating immunoglobulins, cytokines, and antioxidant factors—reliable biomarkers of immune competence and oxidative stress status—are intricately regulated by gut microbiota-metabolome interactions, with perturbations in these pathways often linked to increased disease susceptibility and compromised growth performance [16,17]. Thus, deciphering the gut microbiota-metabolome crosstalk induced by NCG supplementation is essential to elucidating its core mechanisms of action in poultry.

The Danzhou chicken, a highly esteemed indigenous breed originating from Hainan Province in China, exhibits considerable economic value and breeding potential, primarily attributed to its exceptional meat quality and remarkable adaptability [18,19]. Despite these advantageous traits, its growth performance and feed conversion efficiency still fall short of those of modern commercial breeds. In the contemporary livestock industry’s pursuit of improved efficiency, prudent resource conservation, and reduced emissions, developing safe and effective nutritional modulation strategies has become a key focus in animal nutrition research—especially for unlocking the latent potential of indigenous breeds [20,21,22]. Presently, the preponderance of research on NCG in poultry has been centered on growth performance, blood parameters, and intestinal morphology, whereas comprehensive studies that integrate microbiome and metabolome approaches to elucidate its underlying regulatory mechanisms on intestinal function are still relatively scarce. Consequently, this investigation utilizes the Danzhou chicken as a model to thoroughly examine the multifaceted impacts of dietary supplementation with varying levels of NCG, encompassing growth performance, serum immune parameters, intestinal morphology, as well as cecal content and microbial community. This study employs 16S rRNA gene sequencing in conjunction with untargeted metabolomics to thoroughly investigate the mechanisms by which NCG influences intestinal health and physiological function in Danzhou chickens. Through these advanced techniques, we aim to uncover the intricate pathways that underlie the beneficial effects of NCG. Furthermore, the integration of multi-omics analyses will offer a comprehensive and robust scientific basis, thereby facilitating the rational application of NCG as a novel green feed additive within sustainable poultry production systems.

2. Materials and Methods

2.1. Materials and Animals

NCG (purity > 99.5%) was purchased from Sigma-Aldrich (St. Louis, MO, USA).

One-day-old female Danzhou chickens, with an initial body weight of 25.91 ± 0.17 g, were obtained from the Hainan Rekeyuan Ecological Breeding Co., Ltd. (Danzhou City, China). All chickens shared uniform genetic backgrounds and health statuses.

The experiment was conducted at a standardized poultry facility located within the Livestock Farm of the Tropical Crops Genetic Resources Institute, Chinese Academy of Tropical Agricultural Sciences.

2.2. Experimental Design and Management

A single-factor completely randomized design was used in this study. A total of 480 healthy one-day-old female Danzhou chickens were randomly allocated to four distinct dietary treatments, with each treatment comprising six replicates, and each replicate consisting of 20 birds. The feed formulation was based on the Chinese Feeding Standard of Chicken (NY/T33-2004) [23], and the composition and nutritional levels of the basal diet are presented in Table S1. The control group (CON) received a basal diet, whereas the experimental groups were administered with NCG at varying doses of 400 mg/kg (N1), 800 mg/kg (N2), and 1200 mg/kg (N3), which were incorporated into the basal diet accordingly. The NCG supplementation levels (400, 800, and 1200 mg/kg) were selected based on published efficacy ranges in poultry and other monogastric animals [3]. NCG has excellent compatibility with conventional feed formulations, maintains stability under standard feed processing conditions, and exhibits no adverse interactions with common feed components (e.g., proteins, carbohydrates, and minerals) [5]. The mixtures were homogenized using a specialized feed mixer (JX-200; Jining, China) to ensure uniform consistency. During the first 3 days, the temperature in the poultry house was maintained at 32–34 °C. Subsequently, it was gradually decreased by 1–2 °C per week until stabilizing at 25–26 °C by the third week. In addition to temperature regulation, the humidity in the poultry house was carefully controlled to maintain an optimal level of 60–70%, ensuring a comfortable environment for the chicks. The poultry house was equipped with a ventilation system that operated on a schedule of 10-min intervals, with each ventilation cycle lasting for 5 min, providing a continuous exchange of fresh air. Additionally, the chickens were vaccinated against Marek’s disease on the first day, followed by Newcastle disease and infectious bronchitis at 7 days of age, and Gumboro disease at 14 days of age. Throughout the experimental period, the chicks were provided with ad libitum access to high-quality feed and clean water, and they were illuminated with continuous 24-h artificial lighting to promote growth and development. The experimental period spanned 35 days.

2.3. Sample Collection

During the experimental period, growth performance parameters were evaluated on the first and 35th days. The data collected encompassed initial body weight (IBW), final body weight (FBW), and daily feed intake. Subsequently, these recorded data were utilized to accurately calculate average daily gain (ADG), average daily feed intake (ADFI), and feed conversion ratio (FCR).

At the conclusion of the trial, a 12-h fasting period was enforced, during which water was provided ad libitum. Subsequently, from each of the six replicate pens within each treatment group, six Danzhou chickens were randomly selected for blood collection. Following blood collection, euthanasia was performed on the chickens via cervical dislocation in accordance with the American Veterinary Medical Association Guidelines for the Euthanasia of Animals (2020 Edition) [24], and their tissues were sampled. Blood samples were collected from the wing vein into pre-labeled 5 mL serum separator tubes and allowed to clot at room temperature. Subsequent to the collection process, the samples were subjected to centrifugation at a speed of 3000 rpm for a duration of 20 min, maintained at a temperature of 4 °C. Following centrifugation, the resulting serum supernatant was carefully aliquoted into 1.5 mL Eppendorf tubes and subsequently stored at −20 °C, preserving it for subsequent analysis. The contents of the ligated right cecum were extruded into pre-weighed tubes for collection. The samples were immediately snap-frozen on dry ice and stored at −80 °C for subsequent DNA/metabolite extraction. Approximately 2–3 cm segments of the duodenum, jejunum, and ileum were collected and gently flushed with 0.9% sodium chloride solution to remove luminal contents. Samples were then immersion-fixed in 4% paraformaldehyde to preserve tissue integrity for subsequent histological assessment of intestinal morphology. These intestinal segments were then embedded in paraffin, sectioned into thin slices, and stained using hematoxylin and eosin (H&E) to visualize cellular and tissue structures. Finally, after a series of dehydration and clearing steps, the sections were permanently mounted with neutral synthetic resin, ensuring their long-term stability for thorough morphological examination and analysis. Cecal content samples were collected, immediately flash-frozen in liquid nitrogen to ensure optimal preservation of their biological integrity, and then carefully transferred to a −80 °C freezer for long-term storage.

2.4. Serum Biochemical Analysis

The activities and serum concentrations of glutathione peroxidase (GSH-Px), superoxide dismutase (SOD), malate dehydrogenase (MDH), catalase (CAT), immunoglobulin A (IgA), immunoglobulin Y (IgY), immunoglobulin M (IgM), interleukin-10 (IL-10), interleukin-6 (IL-6), and tumor necrosis factor-alpha (TNF-α) were meticulously determined through the utilization of commercially available enzyme-linked immunosorbent assay kits, which were specifically manufactured by the Nanjing Jiancheng Bioengineering Institute. The activities of GSH-Px, SOD, MDH and CAT were measured using a spectrophotometer (UV-2600, Shimadzu, Shanghai, China). The concentrations of IgA, IgY, IgM, IL-10, IL-6, and TNF-α were determined using an enzyme-linked immunosorbent assay reader (Varioskan LUX, ThermoFisher, Shanghai, China). All assays were conducted in precise alignment with the comprehensive and standardized protocols stipulated by the manufacturers.

2.5. RNA Extraction and Quantitative Analysis of mRNA with RT qPCR

Total RNA was extracted from approximately 1.5–2.0 g of liver tissue using Trizol Up Reagent (TransGen, Beijing, China). RNA quality and integrity were evaluated by 2% agarose gel electrophoresis, while concentration and purity were determined using a NanoPhotometer^® spectrophotometer (NanoDrop Technologies, DE, USA). Only RNA samples with A260/A280 ratios ranging from 1.8 to 2.1 were used for subsequent analyses. Primer sequences used in this study are listed in Table 1. Complementary DNA (cDNA) was synthesized from 1 μg of total RNA using the PrimeScript^® RT Reagent Kit with gDNA Eraser (TaKaRa, Dalian, China) in a final reaction volume of 20 μL. Quantitative real-time PCR (RT-qPCR) was performed with the FastStart Universal SYBR Green Master Mix (with ROX reference dye) (Roche, Mannheim, Germany) on a StepOne Plus Real-Time PCR System (Applied Biosystems, Foster City, CA, USA). Each 20 μL reaction mixture contained 10 μL of SYBR Premix Ex Taq II (Tli RNaseH Plus, Takara Bio Inc., Kusatsu, Japan), 2 μL of cDNA, 0.4 μL of ROX Reference Dye II (50×), 0.8 μL each of forward and reverse primers (10 μM), and nuclease-free water to a final volume of 20 μL. The amplification program consisted of an initial denaturation at 95 °C for 3 min, followed by 40 cycles of 95 °C for 30 s, 60 °C for 30 s, and 72 °C for 10 s. Melting curve analysis was performed after amplification to confirm product specificity. Primer amplification efficiencies, determined by standard curve analysis, ranged from 95% to 105%. Each sample was analyzed in triplicate, and each treatment group included six independent biological replicates (n = 6). The reference genes β-actin and GAPDH, whose expression stability was confirmed using geNorm software (v3.2), were used for normalization. Relative mRNA expression levels of target genes were calculated using the 2^−ΔΔCt method, with the control group serving as the calibrator (expression level set to 1).

Table 1. Primers used for quantitative RT-qPCR.

Gene Name 1	Primer Sequence (5′-3′)	Length of Product (bp)	Accession Number
TIPRL	F: GCAGATGTGCTAACACAAAGGA	101	XM_416593.8
	R: TTGAGCTCAGTGGAGCTTCG
CPS1	F: GGAAAGGGTCGTGCTGGATT	167	NM_001045841.2
	R: CGCTGTCTGCGCAGTTTAAG
IGF1	F: TACCTTGGCCTGTGTTTGCT	170	NM_001004384.3
	R: CCCTTGTGGTGTAAGCGTCT
IgA	F: GTCACCGTCACCTGGACTACA	193	S_40610
	R: ACCGATGGTCTCCTTCACATC
IgY	F: ATCACGTCAAGGGATGCCCG	118	X_07174.1
	R: ACCAGGCACCTCAGTTTGG
JCHAIN	F: TCGTCCTTGTGGCAGGTTATC	173	NM_204263.2
	R: ATTCTCCCGGCTCTTGAGTG
MDH1	F: AACTGTCTGTGGCAATTGTGC	199	NM_001006395
	R: TGCGTTAGTAGCCAAGGCAT
MDH2	F: CACCAGCGCCCAGAACAAT	225	XM_415765
	R: CAGCCCTTCAAACATTCTGGC
LGR5	F: CCTCCTCCTTCTCCTGCTCT	176	XM_425441.7
	R: AGGTGAAGGCACTGAGGTTG
ACTB	F: GTGGATCAGCAAGCAGGAGT	182	NM_205518
	R: ATCCTGAGTCAAGCGCCAAA
GAPDH-	F: GGGCACGCCATCACTATCTT	187	NM_204305
	R: GGGCACGCCATCACTATCTT

TIPRL, TOR Signaling Pathway Regulator; CPS1, Carbamoyl-Phosphate Synthase 1; IGF1, Insulin Like Growth Factor 1; IgA, Immunoglobulin Alpha Heavy Chain; IgY, Chicken mRNA For IgG H-chain (HC36) D-J-C; JCHAIN, Joining Chain Of Multimeric IgA and IgM; MDH1, Malate Dehydrogenase 1; MDH2, Malate Dehydrogenase; LGR5, Leucine Rich Repeat Containing G Protein-Coupled Receptor 5; ACTB, Actin Beta; GAPDH, Glyceraldehyde-3-Phosphate Dehydrogenase.

2.6. Metabolomics Analysis

Approximately 50 mg of cecal content was accurately weighed into a 2 mL centrifuge tube, and 600 μL of methanol solution containing the internal standard 2-chloro-L-phenylalanine (4 ppm) was added. The mixture was vortexed for 30 s to ensure homogeneity. A steel bead was added, and the sample was homogenized at 50 Hz for 2 min using a tissue grinder, followed by ultrasonic extraction at room temperature for 10 min to facilitate metabolite release. The homogenate was then centrifuged at 12,000 rpm for 10 min at 4 °C, and the resulting supernatant was carefully collected and filtered through a 0.22 µm microporous membrane. The clear filtrate obtained was transferred into a liquid chromatography-tandem mass spectrometry (LC–MS) vial for subsequent instrumental analysis. Chromatographic resolution was accomplished on a Hypersil GOLD C18 column (2.1 × 100 mm, 1.9 µm; Thermo Scientific, Shanghai, China) thermostated at 40 °C, using a binary mobile phase composed of 0.1% formic acid in water (eluent A) and 0.1% formic acid in acetonitrile (eluent B), delivered at a constant flow rate of 0.3 mL/min through the following gradient profile: 5% B held from 0 to 1 min, ramped linearly to 95% B over the next 11 min, maintained at 95% B for 2 min, returned to 5% B within 0.1 min, and then re-equilibrated at 5% B for the final 1.9 min. Raw mass spectrometry data were converted to mzXML format using ProteoWizard MSConvert (v3.0.23038). Peak detection, peak alignment, and peak area extraction were then performed using the XCMS (v3.12.0) software package. A support vector regression-based correction algorithm was applied to process the data, and metabolites with a relative standard deviation (RSD) >30% in quality control (QC) samples were excluded. Orthogonal partial least squares-discriminant analysis (OPLS-DA) was employed to discriminate metabolite profiles between groups. Significant differential metabolites were screened based on a variable importance in projection score > 1 from the OPLS-DA model and a p-value < 0.05 from Student’s t-test.

2.7. Microbiome Data Processing and Bioinformatic Analysis

Total genomic DNA was extracted from samples using the E.Z.N.A.^® Soil DNA Kit (Omega Bio-tek, Norcross, GA, USA) according to the manufacturer’s instructions. DNA concentration and purity were determined using a NanoDrop 2000 spectrophotometer (Thermo Fisher Scientific, Waltham, MA, USA), and integrity was verified by 2% agarose gel electrophoresis. The V3–V4 hypervariable region of the 16S rRNA gene was subsequently amplified by polymerase chain reaction using the specific primers 338F (5′-ACTCCTACGGGAGGCAGCAG-3′) and 806R (5′-GGACTACHVGGGTWTCTAAT-3′), ensuring high fidelity and reproducibility of amplification for downstream sequencing analysis. The 25 μL PCR reaction mixture contained 50 ng of template DNA, 1 μM of each forward and reverse primer, and 2× Premix Taq (Takara Bio, Shiga, Japan) to ensure optimal amplification efficiency. The thermal cycling conditions were programmed to begin with an initial denaturation at 95 °C for 3 min, followed by 27 consecutive cycles comprising denaturation at 95 °C for 30 s, primer annealing at 55 °C for 30 s, and extension at 72 °C for 45 s, after which a final elongation step was carried out at 72 °C for 10 min to complete strand synthesis. The resulting PCR products were subsequently purified using the AxyPrep DNA Gel Extraction Kit (Axygen Scientific, Union City, CA, USA) and eluted with Tris-HCl buffer to obtain high-quality DNA fragments suitable for downstream analysis. The purified DNA was precisely quantified using a Qubit 4.0 Fluorometer (Thermo Fisher Scientific, Waltham, MA, USA) to ensure accurate concentration assessment, after which Illumina sequencing libraries were constructed in accordance with established protocols and subjected to high-throughput sequencing on the Illumina NovaSeq 6000 platform, generating PE250 paired-end reads with a targeted sequencing depth of approximately 60,000 reads per sample. Alpha diversity was assessed by calculating Observed OTUs, Chao1, and Shannon indices using the vegan (v2.6-4) package, and group comparisons were conducted using the Kruskal-Wallis test. Beta diversity was evaluated based on a Bray-Curtis distance matrix using Principal Coordinates Analysis, and significant differences in community structure between groups were tested using PERMANOVA (v7.0.13, Adonis, permutations = 9999). LEfSe (v1.0) analysis was employed to identify differentially abundant taxa across different taxonomic levels between groups. Intestinal content samples were submitted to the BioDeep Cloud Platform at https://www.biodeep.cn/(accessed on 13 July 2025) for microbial 16S rDNA sequencing and analytical identification. All sequencing data from this study have been deposited in the NCBI Sequence Read Archive under the BioProject accession number PRJNA1348119.

2.8. Statistical Analysis

Statistical analyses were performed using SPSS 27.0 (IBM, Armonk, NY, USA). Data were subjected to one-way analysis of variance (ANOVA), and significant differences among treatment means were separated using Duncan’s multiple range test. Results are presented as arithmetic means ± standard error of the mean (SEM), with statistical significance set at p < 0.05. Additionally, orthogonal polynomial contrasts were used to evaluate linear and quadratic responses to graded dietary NCG supplementation.

3. Results

3.1. Growth Performance

Dietary supplementation with different levels of NCG significantly affected the growth performance of Danzhou chickens, with all measured parameters except initial body weight (IBW) exhibiting significant quadratic responses (p < 0.05). Compared with the CON group, the N1 and N2 treatments significantly enhanced ADG and reduced the FCR. Notably, the N1 group achieved the optimal feed efficiency, with a significantly lower FCR than both the CON and N3 groups (p < 0.05) (Table 2).

Table 2. Effect of dietary supplementation of NCG on the growth performance of Danzhou chickens.

Items	Treatments				SEM	p-Value
	CON	N1	N2	N3		ANOVA	Linear	Quadratic
IBW, g	25.77	25.61	26.47	25.78	0.17	0.2885	0.5459	0.4249
FBW, g	251	264	264	255	2.38	0.1293	0.5506	0.0247
ADG, g	6.45 b	6.96 a	6.92 a	6.70 ab	0.14	0.0424	0.2183	0.0111
ADFI, g	11.28	11.92	11.88	11.48	0.12	0.1565	0.5904	0.0315
FCR	1.95 a	1.80 c	1.82 bc	1.87 ab	0.02	0.0083	0.3148	0.0015

^a,b,c Means in the row without common superscripts are significant difference (p < 0.05). IBW, initial body weight; FBW, final body weight; ADG, average daily gain; ADFI, average daily feed intake; FCR, feed conversion ratio; CON (n = 120), basal diet; N1 (n = 120), basal diet plus 400 mg/kg NCG; N2 (n = 120), basal diet plus 800 mg/kg NCG; N3 (n = 120), basal diet plus 1200 mg/kg NCG.

3.2. Serum Biochemical Parameters

No significant differences were observed among treatment groups for serum levels of GSH-Px, SOD, CAT, IL-10, IL-6, or TNF-α (p > 0.05). The MDH activity was significantly higher in all NCG-supplemented groups than in the CON group (p < 0.05), with the N2 group exhibiting the highest activity. Furthermore, the IgA concentrations were significantly elevated (p < 0.05) in all NCG-treated groups relative to the control. The IgY levels were highly significantly elevated (p < 0.01) in all NCG-supplemented groups compared to the control group (Table 3).

Table 3. Effect of dietary supplementation of NCG on the serum biochemical parameters of Danzhou chickens.

Items	Treatments				SEM	p-Value
	CON	N1	N2	N3		ANOVA	Linear	Quadratic
GSH-Px, umol/mL	8845	8230	7710	6683	409	0.3078	0.0711	0.7988
SOD, U/mL	27.41	29.22	34.60	34.19	2.33	0.6818	0.2824	0.8305
MDH, umol/mL	0.22 b	0.270 ab	0.33 a	0.32 a	0.015	0.0114	0.0030	0.1355
CAT, U/mL	6.12	8.26	2.07	7.01	0.94	0.0926	0.6349	0.4077
IgA, μg/mL	57.28 c	70.98 bc	137.09 ab	162.33 a	18.70	0.0208	0.0029	0.7496
IgY, μg/mL	129 c	184 ab	165 b	191 a	7.06	0.0003	0.0003	0.0802
IgM, μg/mL	1499	1580	1930	1862	144	0.7034	0.3110	0.8108
IL-10, ng/L	282	372	278	272	16.57	0.0851	0.3542	0.1149
IL-6, ng/L	50.01	86.10	106	115	16.25	0.5441	0.1746	0.6963
TNF-α, ng/mL	1083	1329	1399	1434	69.17	0.2874	0.0891	0.4440

^a,b,c Means in the row without common superscripts are significant difference (p < 0.05). Values represent the means of 6 replicate pens. GSH-Px, glutathione peroxidase; SOD, total antioxidant capacity; CAT, catalase; MDH, malate dehydrogenase; IgA, immunoglobulin A; IgY, immunoglobulin G; IgM, immunoglobulin M; IL-10, interleukin 10; IL-6, interleukin 6; TNF-α, tumor necrosis factor-alpha. CON (n = 120), basal diet; N1 (n = 120), basal diet plus 400 mg/kg NCG; N2 (n = 120), basal diet plus 800 mg/kg NCG; N3 (n = 120), basal diet plus 1200 mg/kg NCG.

3.3. Intestinal Morphology Analysis

No significant differences were observed in any morphological parameters of the duodenum and jejunum between the treatment groups and the control group (p > 0.05). Ileal villus height differed significantly among treatment groups (p < 0.05), showing a pronounced quadratic relationship (p < 0.01) that first increased and then decreased. Although the ileal villus-to-crypt ratio (VH/CD) showed no significant differences among groups, linear trend analysis revealed a significant decrease with increasing treatment levels (p < 0.05) (Table 4, Figure S1).

Table 4. Effect of dietary supplementation of NCG on the Intestinal morphology of Danzhou chickens.

Items	Treatments				SEM	p-Value
	CON	N1	N2	N3		ANOVA	Linear	Quadratic
Duodenum
Villus height (μm)	1090	1080	1158	1053	23.61	0.4742	0.8819	0.3306
Crypt depth (μm)	251	344	301	322	16.64	0.2466	0.2571	0.2804
VH/CD	4.96	3.32	4.08	3.33	0.28	0.1129	0.0901	0.4029
Jejunum
Villus height (μm)	921	936	894	902	30.9	0.9667	0.7308	0.9603
Crypt depth (μm)	190	302	241	259	17.40	0.1504	0.3393	0.1674
VH/CD	5.35	3.56	4.13	3.72	0.29	0.1038	0.0821	0.2054
Ileum
Villus height (μm)	825 b	960 a	848 ab	746 b	24.47	0.0170	0.0687	0.0087
Crypt depth (μm)	147	191	174	183	10.07	0.4597	0.3454	0.4001
VH/CD	6.07	5.18	5.18	4.17	0.30	0.1625	0.0354	0.9182

^a,b Means in the row without common superscripts are significant difference (p < 0.05). Values represent the means of 6 replicate pens. VH/CD, Villus height/Crypt depth; CON (n = 120), basal diet; N1 (n = 120), basal diet plus 400 mg/kg NCG; N2 (n = 120), basal diet plus 800 mg/kg NCG; N3 (n = 120), basal diet plus 1200 mg/kg NCG.

3.4. Validation of Target Genes by RT-qPCR

The relative expression levels of four genes—TIPRL, CPS1, IGF1, and LGR5—were significantly different between the CON group and the N1/N2 groups (p < 0.05). Significant differences were observed in the relative expression levels of IgA, IgY, and JCHAIN between the CON and experimental groups (p < 0.05). MDH1 and MDH2 expression levels were significantly different between the CON and N2, N3 groups (p < 0.05). The results are shown in Figure 1.

Figure 1. Effect of NCG on the Expression of Related Genes in Danzhou Chicken Liver. ^a,b,c Means in the row without common superscripts are significant difference (p < 0.05). Values represent the means of 6 replicate pens. (A) TIPRL, TOR Signaling Pathway Regulator; (B) CPS1, Carbamoyl-Phosphate Synthase 1; (C) IGF1, Insulin Like Growth Factor 1; (D) IgA, Immunoglobulin Alpha Heavy Chain; (E) IgY, Chicken mRNA For IgG H-chain (HC36) D-J-C; (F) JCHAIN, Joining Chain Of Multimeric IgA and IgM; (G) MDH1, Malate Dehydrogenase 1; (H) MDH2, Malate Dehydrogenase; (I) LGR5, Leucine Rich Repeat Containing G Protein-Coupled Receptor 5. CON, N1, N2, and N3 denote the control group and experimental groups supplemented with increasing levels of NCG, respectively. CON (n = 120), basal diet; N1 (n = 120), basal diet plus 400 mg/kg NCG; N2 (n = 120), basal diet plus 800 mg/kg NCG; N3 (n = 120), basal diet plus 1200 mg/kg NCG.

3.5. Metabolomic Analysis of Differential Metabolites

Principal Coordinates Analysis (PCoA) of metabolic profiles in both positive and negative ion modes revealed clear separation among the CON, N1, N2, and N3 groups, with distinct clustering of samples within each group (Figure S2A,B). Permutation testing yielded validation parameters of R² = 0.98, Q² = −0.01 and R² = 0.94, Q² = −0.08 for the respective models. The negative Q² values, combined with the fact that all permuted R² and Q² values remain below the original point estimates (represented by the rightmost blue R² and green Q² points in the plots), confirm the absence of overfitting and support the statistical validity of the models (Figure S2C,D). Metabolomic analysis identified a total of 2217 metabolites across all samples. Comparative analysis among CON, N1, N2, and N3 groups revealed 150 differentially abundant metabolites. Specifically, 138 differential metabolites were detected between N1 and CON (31 up-regulated, 107 down-regulated), 70 between N2 and CON (27 up-regulated, 43 down-regulated), and 193 between N3 and CON (13 up-regulated, 180 down-regulated). Inter-treatment comparisons showed 97 differential metabolites between N2 and N1 (48 up-regulated, 49 down-regulated), 187 between N3 and N1 (16 up-regulated, 171 down-regulated), and 145 between N2 and N3 (127 up-regulated, 18 down-regulated) (Figure 2H). Based on volcano plot filtering (Figure 2E–G) and the m/z versus p-value scatter plot (Figure 2I), key metabolites were subsequently identified, including Sphinganine, Cer(d18:1/18:0), docosahexaenoic acid (DHA), and L-Arginine (Figure 2A–D). KEGG enrichment analysis indicated that these differential metabolites are potentially involved in modulating multiple physiological pathways, such as mTOR signaling, fatty acid metabolism, neurotransmitter signaling, and sphingolipid metabolism (Figure S3).

Figure 2. Differential Metabolites. (A) Violin plot for L-arginine; (B) Violin plot for Sphinganine; (C) Violin plot for Cer (d18:1/18:0); (D) Violin plot for docosahexaenoic acid (DHA); (E) Volcano plot for N1 vs. CON; (F) Volcano plot for N2 vs. CON; (G) Volcano plot for N3 vs. CON; (H) Bar plot of metabolite counts; (I) Scatter plot of m/z versus p-value for differential metabolites. CON (n = 120), basal diet; N1 (n = 120), basal diet plus 400 mg/kg NCG; N2 (n = 120), basal diet plus 800 mg/kg NCG; N3 (n = 120), basal diet plus 1200 mg/kg NCG. * represents p < 0.05; ** represents p < 0.01.

3.6. Gut Microbiota

The Venn diagram of operational taxonomic units (OTUs) depicts the numbers of shared and unique OTUs among the four sample groups (CON, N1, N2, N3) (Figure 3). Analysis of these data revealed a core set of 566 OTUs common to all four groups, while the CON group contained 22 unique OTUs (Figure 3A). The N1, N2, and N3 groups contained 4, 4, and 6 unique OTUs, respectively. The CON group exhibited a considerably higher number of unique OTUs compared to the other groups, indicating a more divergent microbial community structure. Alpha diversity analysis (Chao1, Shannon, Simpson, and Observed species indices) revealed no significant differences among treatment groups (p > 0.05), indicating comparable microbial richness and evenness across all experimental conditions (Figure 3B–E). Beta diversity analysis, as determined by ANOSIM, revealed significant differences in the cecal microbial communities of Danzhou chickens among the treatment groups (p < 0.05; Figure 3F). Notably, although no significant differences were observed in within-group alpha diversity (Figure 3B–E), the overall community structure differed significantly among treatments (beta diversity, Figure 3F), indicating that NCG altered specific microbial members rather than the overall richness of the community. Specifically, the N1, N2, and N3 groups all exhibited significant separation (p < 0.05) from the CON group, indicating substantial dissimilarity in microbial community composition and low inter-group similarity.

Figure 3. Alpha and Beta Diversity Analysis. (A) Venn diagram of OTUs; (B) Observed species index; (C) Chao1 index; (D) Shannon index; (E) Simpson index; (F) ANOSIM box plot. CON (n = 120), basal diet; N1 (n = 120), basal diet plus 400 mg/kg NCG; N2 (n = 120), basal diet plus 800 mg/kg NCG; N3 (n = 120), basal diet plus 1200 mg/kg NCG.

The gut microbiota of Danzhou chickens was dominated by the phyla Firmicutes, Bacteroidota, Proteobacteria, and Desulfobacterota, with Firmicutes and Bacteroidota collectively accounting for over 90% of the total sequences. Notably, the relative abundance of Desulfobacterota exceeded 10% (Figure 4A). Furthermore, the relative abundance of Bacteroidota was significantly higher in the N1 group compared with the CON, N2, and N3 groups (p < 0.05). The intestinal microbiota of Danzhou chickens was enriched with Alistipes_A, Bacteroides_H, Faecalibacterium, and Parabacteroides_B (Figure 4B). Alistipes_A was identified as the predominant genus with a relative abundance exceeding 10%, while Bacteroides_H, Faecalibacterium, and Parabacteroides_B each accounted for over 5% of the sequenced microbiota (Figure 4B). No significant differences in the relative abundances of these genera were observed among the CON, N1, N2, and N3 groups (p > 0.05). LEfSe analysis (LDA score > 2.0) identified signature taxa significantly enriched in each group (Figure 4C,D). Furthermore, phylogenetic distribution analysis revealed substantial heterogeneity in microbial community structure among experimental groups, particularly between the CON and N1 treatments (Figure S4). The genera Photobacterium and Cutibacterium were significantly enriched in the CON group and were identified as key biomarkers distinguishing this group from the NCG-supplemented treatments (p < 0.05). The genus Phocaeicola was significantly enriched in the N2 group and identified as a distinctive biomarker for this treatment. LEfSe results demonstrated distinct microbial signatures between the control and NCG-supplemented groups, indicating substantial structural shifts in the gut microbiota.

Figure 4. Microbial Community Differential Analysis. (A) Microbial composition at the phylum level; (B) Microbial composition at the genus level; (C) LEfSe cladogram, This circular diagram illustrates the relative abundance of species across taxonomic levels and highlights differential biomarkers between groups using color-coding; (D) LEfSe LDA scores. CON (n = 120), basal diet; N1 (n = 120), basal diet plus 400 mg/kg NCG; N2 (n = 120), basal diet plus 800 mg/kg NCG; N3 (n = 120), basal diet plus 1200 mg/kg NCG.

3.7. Correlation Between Differentially Abundant Microbiota and Metabolites

Correlation analysis was performed between the top 20 differential metabolites and the top 20 differential bacterial genera, with results meeting the thresholds of |R| > 0.7 and p < 0.05 being presented (Figure 5). Significant correlations were identified between specific bacterial genera and metabolites: Mailhella showed negative correlations with Sphinganine and Cer (d18:1/18:0). Pseudomonas_E_647464 was positively correlated with 1-(4-Hydroxyphenyl)-1-decene-3,5-dione, Cer (d18:1/18:0), and Agavoside A. Both Jeotgalicoccus_A_310962 and Brachybacterium exhibited positive correlations with Sphinganine, whereas Phocaeicola_A_858004 was negatively correlated with this metabolite.

Figure 5. Spearman Correlation Heatmap. The vertical axis represents bacterial taxa, and the horizontal axis represents metabolites. * represents p < 0.05; ** represents p < 0.01; *** represents p < 0.001.

4. Discussion

As a nutritional additive, NCG improves protein utilization efficiency [25], leading to increased body weight and average daily gain in broilers [26]. Previous studies in broilers and swine have shown that NCG can effectively replace part of soybean meal, thereby reducing feed costs while improving overall production efficiency in livestock systems [1,27]. Hu et al. [28] reported that dietary supplementation with NCG constitutes an effective approach for promoting body weight gain in broiler chickens. NCG exhibits outstanding compatibility with conventional feed formulations, maintaining stability under standard feed processing conditions while exhibiting no adverse interactions with commonly used feed components, including proteins, carbohydrates, and minerals [5]. Therefore, NCG functions as a valuable feed additive by improving nitrogen utilization, thereby supporting enhanced growth performance and overall productivity in animal production systems.

Compared with the control group, the N1 and N2 treatments produced a significant increase in ADG and a reduction in FCR, with the most pronounced decrease in FCR observed in the low-dose NCG group (N1), while the overall response displayed a significant quadratic pattern, initially rising before subsequently declining. The observation that ADFI remained unchanged while ADG increased and FCR decreased indicates that NCG improves nutrient retention efficiency by enhancing endogenous arginine synthesis and optimizing nitrogen metabolism. The growth performance improvement observed in Danzhou chickens supplemented with 400 mg/kg NCG is consistent with the findings of Feng et al. [29]. and earlier studies indicating that NCG effectiveness is not strongly dose-dependent [30,31]. The responses observed in the N2 and N3 groups diverge from the dose-dependent growth promotion trends reported in previous studies [3,32], a discrepancy that may be explained by the distinctive physiological characteristics of this local chicken breed, and the results suggest that supplementation with low doses of NCG enhances feed conversion efficiency in Danzhou chickens, thereby presenting potential for reducing production costs, whereas higher supplementation levels appear to confer only marginal improvements in overall productivity.

This study shows that dietary NCG supplementation in Danzhou chickens significantly improves digestive function and modulates the intestinal microbiota, which in turn impacts systemic immune parameters. Specifically, NCG markedly enhanced humoral immune responses, as indicated by increased serum levels of IgY and IgA, and concurrently stimulated cellular energy metabolism, reflected by elevated MDH activity. IgY, the predominant serum immunoglobulin, serves as a core mediator of anti-infective defense, and its circulating level directly reflects the intensity of the body’s humoral immune response [9]. IgA, a key effector molecule of mucosal immunity, acts as a first line of defense at mucosal surfaces such as the respiratory and digestive tracts [33,34]. MDH, a key enzyme in the tricarboxylic acid cycle, typically exhibits increased activity during heightened cellular energy metabolism [16]. Notably, pro-inflammatory cytokines (IL-6 and TNF-α) exhibited a dose-dependent increase, suggesting mild inflammation associated with improved digestive efficiency. This suggests that high-dose supplementation may entail a physiological cost. IL-6, a central regulator of the acute-phase response, promotes the synthesis of proteins like C-reactive protein and is often significantly elevated in both acute and chronic inflammatory states [35]. TNF-α, a key mediator in inflammatory signaling pathways, is associated with impaired nutrient utilization under pathological conditions and may disrupt physiological homeostasis [36]. Overall, while NCG supplementation effectively enhanced immunity and maintained homeostatic balance, incremental increases in dosage may trigger inflammatory responses, potentially affecting overall production performance.

The ileum, the terminal segment of the small intestine, is a vital site for absorbing essential nutrients (e.g., amino acids and fatty acids). Its inherent morphological plasticity makes it highly responsive to dietary interventions, which likely explains the relatively pronounced effect of NCG on ileal villus height [13]. The health and productivity of animals are intimately associated with the structural integrity of the intestinal tract, where the villi, functioning as the principal sites for nutrient absorption, play a critical role in maintaining overall physiological efficiency [15]. Increased villus height expands the absorptive surface area, thereby enhancing nutrient uptake and supporting growth performance [12,37]. In this experiment, supplementation with NCG led to an increase in ileal villus height, indicating a potential enhancement of nutrient digestion and absorption in Danzhou chickens; however, as NCG dosage increased, the high-dose groups exhibited reduced villus height, deeper crypts, and a lower villus-to-crypt ratio—changes commonly associated with accelerated cellular turnover and the onset of an inflammatory response [14]. Increased crypt depth and a decreased villus-to-crypt ratio can elevate energy demands, diverting metabolic resources from nutrient absorption to cellular proliferation and ultimately reducing nutrient utilization efficiency [38]. Our findings differ from those of Liu et al. [3], who reported that 800 mg/kg NCG optimally preserved intestinal morphology and maximized animal productivity. This difference is likely due to the slower growth rate of Danzhou chickens and their corresponding lower endogenous arginine demand, suggesting that indigenous breeds may have a considerably lower NCG requirement than commercial lines.

TIPRL serves as a key regulator of the TOR signaling pathway and is a critical indicator of pathway activity [39]. CPS1, the rate-limiting initiating enzyme of the urea cycle, catalyzes the production of citrulline, thereby enhancing arginine synthesis [40]. As a key regulator of cell proliferation, growth, and survival, IGF1 is closely associated with chicken growth and development, while the immune factors IgA and IgY directly influence immune status [41,42]. JCHAIN acts as a bridging molecule that connects IgM and IgA immunoglobulin monomers by forming disulfide bonds at the C-terminus of their heavy chains, facilitating the assembly of IgM into pentamers and IgA into dimers [43]. These polymerized antibody structures exhibit increased stability and significantly enhanced antigen-binding affinity [44]. For instance, dimeric IgA in the chicken intestinal mucosa demonstrates superior efficiency in binding enteric pathogens [45]. MDH1 and MDH2 are distinct "executor" genes encoding enzymes that play central roles in cellular metabolism [46]. LGR5 activity directly determines the size and potency of the stem cell pool, thereby critically influencing villus height and integrity [47]. Validation via RT-qPCR demonstrated a consistent trend between the gene expression levels and their corresponding metrics, which increased the reliability of the experimental data. Among these, TIPRL and CPS1 were correlated with arginine expression levels, IGF1 with growth traits, IgA and IgY with their respective immune proteins, JCHAIN with the total levels of both immunoglobulins, MDH1 and MDH2 with MDH activity, and LGR5 with villus height. Simultaneously, TIPRL and CPS1 provide key evidence for elucidating the mechanism of action whereby NCG regulates the mTOR pathway via arginine.

L-arginine is the sole substrate for nitric oxide synthase, which catalyzes nitric oxide production to regulate vascular tone and microcirculatory function [48]. It also serves as a specific substrate for arginase, which hydrolyzes it to ornithine to support polyamine biosynthesis and promote cellular proliferation [49]. Furthermore, L-arginine is a pivotal metabolic intermediate in the urea cycle and plays a key role in hepatic ammonia detoxification. During the initial phase of the cycle, the rate-limiting enzyme carbamoyl phosphate synthase 1 (CPS1) is allosterically activated by N-acetylglutamate, promoting the conversion of ammonia and carbon dioxide to carbamoyl phosphate. This compound then proceeds through the citrulline synthesis pathway, ultimately facilitating arginine regeneration in the kidneys and intestinal tissues [50,51]. L-arginine has been shown to directly activate the mammalian target of rapamycin (mTOR) signaling hub [52], leading to the phosphorylation of downstream effectors such as ribosomal protein S6 kinase 1 and eukaryotic translation initiation factor 4E-binding protein 1, a cascade that enhances mRNA translation efficiency and exerts broad regulatory control over protein biosynthesis [53]. In addition, the L-arginine/nitric oxide pathway contributes to skeletal muscle development in chickens by selectively suppressing proteolysis through the mTOR/p70S6K signaling axis in a tissue-specific manner, thereby promoting muscle growth and functional maturation [54]. In summary, the observed enrichment of L-arginine in the NCG-supplemented groups appears to influence multiple physiological pathways, simultaneously modulating metabolic processes, supporting immune function, and promoting growth, which collectively contribute to the improvement of overall production performance in Danzhou chickens.

Sphinganine serves as a key intermediate in sphingolipid metabolism [55]. Sphingolipids, which are common constituents of eukaryotic cell membranes serving as platforms for intracellular signal transduction, undergo modifications in their biophysical properties primarily influenced by lipid metabolism [56]. As fundamental structural components of mammalian cell membranes, they activate various immune cells including monocytes and neutrophils, thereby playing pivotal roles in immune processes [57]. Sphingolipid metabolites, including ceramide, ceramide-1-phosphate, and sphingosine-1-phosphate, act as essential signaling molecules that orchestrate a wide range of critical biological processes, encompassing the regulation of cell growth and survival, the trafficking of immune cells, and the maintenance of vascular and epithelial integrity [58]. Among these metabolites, ceramide (Cer(d18:1/18:0)) has been shown to induce oxidative stress, arrest cellular growth, and promote both necrotic and apoptotic pathways. In addition, sphingolipid metabolites are capable of initiating the degradation of membrane phospholipids enriched in polyunsaturated fatty acids, thereby contributing to structural and functional damage of biological membranes [59]. Metabolomic analysis of intestinal contents showed that levels of sphinganine, sphingosine, and Cer (d18:1/18:0) were markedly higher in the N1, N2, and N3 groups than in the CON group. The observed dose-dependent effect of NCG supplementation enhances biomembrane metabolism, which may induce excessive degradation of membrane phospholipids and compromise membrane integrity [60]. The progressive accumulation of these metabolites at higher NCG concentrations could exacerbate oxidative stress and trigger processes such as apoptosis and necrosis [61], thereby suggesting the initiation of an inflammatory response that has the potential to negatively impact overall animal growth.

Docosahexaenoic acid (DHA), an essential polyunsaturated fatty acid, contributes to neural, visual, and metabolic health through multiple mechanisms [62], including modulation of the gut microbiota, the elicitation of anti-inflammatory responses [63], and the regulation of lipid metabolism via signaling pathways such as AMPK, collectively mitigating chronic inflammation and disturbances in lipid homeostasis. DHA alleviates lipid metabolic disorders induced by gut dysbiosis by modulating the gut microbiota–metabolism axis, and through a selective remodeling mechanism, it markedly decreases the abundance of Proteobacteria while simultaneously promoting the proliferation of beneficial genera, including Bacteroides and Lactobacillus [64]. Simultaneous dose-dependent increases in IL-10 and TNF-α, along with reduced DHA levels in NCG-supplemented groups, indicate that higher NCG doses may exert detrimental effects on both growth and immune function.

Microbiome analysis indicated that Bacteroidota and Firmicutes constituted the dominant phyla, a result that is consistent with the observations previously reported by Park et al. [65] thereby supporting the reliability of the current microbial profiling. Firmicutes was the dominant phylum in the gastrointestinal tract of Danzhou chickens, accounting for 40–78% of the total relative abundance—consistent with previous studies reporting that Firmicutes is the most prevalent phylum in broiler gut microbiota, followed by Bacteroidota and Proteobacteria [66]. Bacteroidota facilitate nutrient absorption by producing active enzymes (e.g., glycoside hydrolases and polysaccharide lyases) that break down complex dietary components such as non-starch polysaccharides, lignin, and macromolecular proteins [67]. Bacteria belonging to the phylum Firmicutes play a significant role in energy metabolism through the production of glycoside hydrolases and carbohydrate esterases, enzymes that catalyze the breakdown of complex polysaccharides into simple monosaccharides [68]. Members of the Firmicutes phylum possess the capacity to produce short-chain fatty acids, including acetate, butyrate, and lactate, via microbial fermentation, thereby contributing to host energy metabolism and intestinal health, while the observed enrichment of Bacteroidota in the N1 group indicates a potential link between this microbial profile and the enhanced growth performance recorded in this treatment.

Although studies on Cutibacterium in poultry are limited, this genus persistently colonizes the intestine and has been shown to produce propionate and various B vitamins under in vitro conditions [69]. The genus Photobacterium is a recognized microbial source of polyunsaturated fatty acids, with a particular focus on eicosapentaenoic acid production [70]. Several species within this genus, including P. profundum strains DSJ4 and SS9, P. frigidiphilum, and Photobacterium sp. SAMA2, have been shown to produce eicosapentaenoic acid at high concentrations, a biosynthetic capability that has been largely attributed to the presence of the polyketide synthase pathway, a mechanism that has been extensively characterized in previous studies [70,71,72]. The Pseudomonas toxin PlcHR₂ hydrolyzes sphingomyelin to produce ceramide, a process that subsequently exerts a profound inhibitory effect on the enzyme’s hydrolytic activity, thereby playing a key role in the regulation of host cell apoptosis [73,74]. The genus Victivallis demonstrates the ability to degrade cellobiose and plays a role in the production of acetate, as reported in previous studies [75,76]. Phocaeicola harbors enzymatic systems that enable the degradation of complex polysaccharides which are otherwise indigestible by the human host [77], and within the intestinal tract, the resulting monosaccharides are subjected to mixed-acid fermentation, producing a range of organic acids, including succinate, propionate, acetate, lactate, and formate [78]. Succinate and lactate are generally metabolized into propionate by specific gut bacteria, whereas formate undergoes hydrolysis to yield hydrogen and carbon dioxide, and the resulting fermentation products, propionate and acetate, are largely absorbed by the colonic epithelial cells of the host, thereby contributing to the host’s energy metabolism [79]. Existing literature demonstrates that these organic acids exert substantial effects on human health by modulating gut homeostasis, regulating metabolic pathways, supporting immune function, and contributing to cardiovascular well-being [70,80]. The observed enrichment of Phocaeicola and Faecalibacterium in the supplemented groups suggests that the treated animals possess an enhanced ability to utilize nutrients efficiently, reflecting potential improvements in overall gut microbial functionality.

NCG acts as a metabolic activator by stimulating pyrroline-5-carboxylate synthase and carbamoyl phosphate synthase 1 (CPS1), enhancing citrulline synthesis. Through the coordinated actions of argininosuccinate synthase and argininosuccinate lyase, this process subsequently promotes endogenous arginine production—predominantly L-arginine [32]. L-arginine has been shown to activate the TOR signaling pathway, thereby regulating intracellular protein turnover and modulating protein synthesis [52]. while the L-arginine/nitric oxide pathway contributes to skeletal muscle development by selectively suppressing proteolysis through the mTOR/p70S6K signaling axis in a tissue-specific manner [54]. Acting as a central mediator, L-arginine may exert beneficial effects on chicken skeletal muscle development through its interactions with specific gut microbes (e.g., Phocaeicola, Victivallis, and Mailhella), potentially by modulating microbial metabolism and metabolite availability. Among these microbes, Phocaeicola serves as a primary fermenter that contributes to host physiology by generating metabolites such as succinate through the fermentation of dietary fibers [78]. Succinate has been shown to promote the activation of mTOR signaling, while also functioning as a key precursor in the biosynthesis of arginine [54]. These findings indicate that Phocaeicola, through its provision of succinate, may work in concert with circulating L-arginine to stimulate the mTOR/p70S6K signaling pathway, thereby promoting protein synthesis and inhibiting proteolysis, which collectively support skeletal muscle development and contribute to enhanced production performance [52,54]. Furthermore, Victivallis, which has been implicated in fiber degradation, together with Mailhella, a well-established beneficial bacterium, may act synergistically to maintain a healthy gut environment [75,76,81], thereby facilitating the functional activity of Phocaeicola and promoting L-arginine homeostasis, ultimately reinforcing this growth-enhancing metabolic axis.

The observed positive correlation between Brachybacterium and sphinganine, along with the negative correlation between Jeotgalicoccus and sphinganine and the pronounced enrichment of the sphingolipid metabolism pathway, collectively suggests that NCG supplementation perturbs the sphingolipid metabolic network. This microbiota-metabolite interplay indicates that NCG modulates sphinganine levels by selectively influencing specific bacterial genera, which in turn activate sphingolipid metabolism. Since sphinganine is a critical intermediate in ceramide biosynthesis, these alterations may trigger downstream effects via ceramide-mediated signaling pathways, potentially impacting cellular processes such as apoptosis and inflammatory responses [55]. Previous studies have demonstrated that pro-inflammatory responses triggered by TNF-α and IL-1 involve the activation of neutral sphingomyelinase, resulting in the generation of ceramide [82]. Within the sphingolipid metabolic pathway, Cer (d18:1/18:0) is a key molecular species that exhibits a negative correlation with Cutibacterium and Photobacterium [58], and a positive correlation with Pseudomonas. The enrichment of Cutibacterium and Photobacterium in the CON group, in contrast to the predominance of Pseudomonas in NCG-supplemented groups, provides compelling evidence for NCG’s pronounced influence on sphingolipid metabolism. This effect is further supported by a dose-dependent increase in sphingolipid-related metabolites with increasing NCG dosage. Concurrently, these metabolic alterations are associated with elevated serum concentrations of IgA, IgY, MDH, IL-6, and TNF-α, along with ileal morphological changes (e.g., deepened crypts and a decreased villus-to-crypt ratio), indicating that NCG supplementation exerts both immunomodulatory and structural effects on the intestinal mucosa. Our findings indicate that high-dose NCG supplementation may induce mild intestinal inflammatory or stress signaling, as reflected by increased IL-10 and TNF-α concentrations. These cytokines in turn orchestrate enhanced humoral immune responses (evidenced by higher IgA and IgY levels) while promoting cellular energy metabolism, as indicated by increased MDH activity. This coordinated response is accompanied by activation of the sphingolipid metabolic pathway, leading to increased synthesis of bioactive signaling molecules (e.g., ceramide). This may serve as a homeostatic mechanism to stabilize intestinal lipid metabolism under metabolic challenge. Persistent upregulation of this pathway subsequently induces ileal morphological alterations, characterized by crypt deepening and a reduced villus-to-crypt ratio, thereby providing a mechanistic explanation for the observed reduction in production performance in high-dose NCG groups. Specifically, the hyperactivation of sphingolipid metabolism appears to perturb pre-existing metabolic equilibrium, with the concomitant decline in sphinganine levels reflecting a functional transition from growth promotion toward growth suppression.

5. Conclusions

This study elucidates the core mechanism by which dietary N-carbamylglutamate (NCG) supplementation improves the growth performance and immune function of Danzhou chickens via the gut microbiota–metabolite axis. The optimal supplementation level is 400 mg/kg, with favorable effects observed up to 800 mg/kg, including significantly increased average daily gain, reduced feed conversion ratio, and enhanced humoral immunity. Mechanistically, NCG first remodels the gut microbiota, which in turn reprograms the intestinal metabolome—marked by the enrichment of L-arginine and activation of the sphingolipid metabolism pathway. The enriched L-arginine, in synergy with specific beneficial bacteria, activates the mTOR signaling pathway, promoting protein synthesis and thereby driving growth (Figure 6). Meanwhile, the regulated sphingolipid metabolism mediates immune enhancement through the production of key signaling molecules such as ceramide. Notably, excessive supplementation (1200 mg/kg) leads to overactivation of the sphingolipid metabolism pathway, potentially inducing metabolic stress that counteracts growth benefits and revealing a dose-dependent “window of efficacy.” This work systematically elucidates the mechanism of action of NCG from microbial and metabolic perspectives, providing a solid theoretical foundation for the precise application of NCG as a green feed additive in the healthy breeding of local poultry.

Figure 6. Metabolic Mechanism of NCG in Danzhou Chicken. N-carbamoylglutamate (NCG) promotes arginine generation in mitochondria via the urea cycle, regulates mTORC1 signaling at the lysosomal membrane, and enhances protein synthesis. NCG acts on the intestine (modulating villus structure and gut microbiota) and systemic circulation (regulating MDH activity, immune factors IgA/IgY, and antioxidant status) to improve overall physiological status.