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. 2025 Sep 5;104(11):105801. doi: 10.1016/j.psj.2025.105801

Integrated multi-omics reveals the molecular mechanism of antibiotic-free Wenchang chicken (Gallus Gallus domesticus)

Xinli Zheng a, Lihong Gu a,⁎, Xiaohui Zhang b, Yanxia Qi b, Lehuan Wu b, Yuanyuan Shang b, Fanghu Wu b, Tieshan Xu c, Anhong Chen d
PMCID: PMC12466252  PMID: 40961769

Abstract

Wenchang chicken is a special local breed in Hainan Province, China, known for its excellent adaptation to the tropical environment and good meat quality. In this study, we compared the differences in serum immunoglobulin levels, antioxidant indices, and liver transcriptome, proteome, phosphoproteomics between antibiotic-free Wenchang chickens (AFS) and normal Wenchang chickens (NS). The IgM level, activities of CAT, TAOC and GSH in serum were significantly higher in AFS Wenchang chickens than in NS Wenchang chickens, but MDA activity in serum was significantly lower in AFS Wenchang chickens. A total of 1,356 DEGs were identified by liver transcriptome analysis and mainly enriched in pathways such as response to bacterium, mitotic cell cycle process, anion binding, and so on. GSEA analysis further indicated that many of the gene sets were associated with immunity regulation and inflammatory responses. A total of 499 DAPs were identified in the liver proteome, mainly involved in the peroxisome, SNARE interactions in vesicular transport and glycerophospholipid metabolism pathways. Three proteins were identified as hubs in the protein interactions network: beta-2-microglobulin precursor (B2M), dedicator of cytokinesis protein 4 (DOCK4) and vesicle-associated membrane protein 3 (VAMP3). There was a weak Spearman’s correlation between mRNA expression and protein abundance in the liver. A total of 3,436 phosphoproteins, including 38,891 phosphorylation sites, were identified in the liver of Wenchang chicken. There are 356 phosphoproteins with differential phosphorylation sites, mainly enriched in six pathways, such as the insulin signaling pathway, tight junction and RNA transport pathway. Multi-omics analyses showed that protein phosphorylation in the liver of the Wenchang chicken is largely an independently regulated process. 143 proteins had both up- and down-regulated phosphorylation sites, suggesting that these proteins undergo complex phosphorylation regulation. The AFS Wenchang chickens have higher serum IgM levels and stronger serum antioxidant activity. Accordingly, signaling pathways related to immune and inflammatory responses are highly activated in the livers. The results provide basic data for the disease resistance breeding of Wenchang chicken in the future.

Keywords: Wenchang chicken, Antibiotics-free, Multi-omics, Disease resistance

Introduction

Chicken meat is not only rich in nutrients, but also inexpensive compared to beef, lamb and pork, and these factors have contributed to making chicken the second most consumed meat in the world. China is one of the world's leading producers and consumers of chicken, but unlike Europeans and Americans, who mainly consume white-feathered chickens, Chinese consumers prefer yellow-feathered chickens. In recent years, profits from yellow-feathered broilers in China have increased, while profits from white-feathered broilers have declined.

Wenchang chicken is a typical yellow-feathered broiler, famous for its golden feathers, high-quality meat and unique flavour, and is one of the high-quality local chicken breeds in China (Xiao et al., 2024). Wenchang chickens are mainly raised in a free-range manner, feeding on natural foods such as insects and grass seeds, supplemented by grains, which make their meat and eggs richer in nutrients (W. Zhang et al., 2024). Meanwhile, free-range Wenchang chickens get plenty of exercise, which makes them muscular and healthier. Wenchang chickens are heat-resistant and disease-resistant (Gu et al., 2024). By the end of 2023, the stock of Wenchang chickens had reached 67 million, making it the most important livestock in Hainan Province.

Along with the increase in the rearing density of Wenchang chickens, it leads to more and more disease problems. Antibiotics are used as feed additives and mixed in feed for chickens to prevent disease and promote growth (Mehdi et al., 2018). However, the misuse of antibiotics for chickens also leads to a series of problems, such as the emergence of antibiotic-resistant bacteria (Roth et al., 2019), drug residues (Muaz et al., 2018), and impacts on the ecosystem (Xu et al., 2022). These factors have prompted people to breed chickens with stronger disease resistance, thereby reducing the use of antibiotics. Immunocompetence and immune responsiveness are recognised as important characteristics for gene selection (Ask et al., 2007), and these parameters can be incorporated into animal selection without compromising growth (Hartcher and Lum, 2020). Gene editing of chickens is considered to be an effective way to rapidly breed pathogen-resistant chickens, but often leads to unexpected results, e.g. influenza A virus (IAV) can also replicate in chicken embryos that have been edited with CRISPR/Cas9 to remove the entire ANP32A gene (Idoko-Akoh et al., 2023). Disease resistance in chickens can be improved by traditional long-term artificial selection, such as the breeding of coccidiostat-resistant chickens (Iuspa et al., 2020). The antibiotics-free Wenchang chicken (AFS) is the result of artificial selection over many generations without the addition of antibiotics to the diet. However, the molecular basis underlying enhanced disease resistance in AFS Wenchang chickens remains unknown, especially at the integrated level of transcriptomics, proteomics, and phosphoproteomics. Therefore, this study compared serum immune indices and liver integrated multi-omics profiles between AFS Wenchang chickens and normal Wenchang chickens (NS), aiming to identify key molecular pathways associated with enhanced disease resistance from long-term artificial selection.

Materials and methods

Animal ethics

All procedures were conducted in accordance with the Regulations for the Administration of Affairs Concerning Experimental Animals (Ministry of Science and Technology, China, revised in March 2017). The protocol was approved by the Institutional Animal Care and Use Committee at the Experimental Animal Center of Hainan Academy of Agricultural Science (HNXMSY-20240427).

Experimental design and diets

A total of 120 female chickens were obtained from the breeding farm of Hainan Chuanwei Wenchang Chickens Industry Co. Ltd, including 60 AFS Wenchang chickens and 60 NS Wenchang chickens. Each group of 60 Wenchang chickens was divided into 6 replicates, with 10 chickens per replicate. The chickens were kept in an environmentally controlled room with artificial light and natural light, and a temperature of around 30 °C. All chickens had free access to feed and water, received routine immunizations.

Samples collection

At 120 days of age, one chicken was randomly selected from each replicate. The selected chickens (six chickens per group) were euthanized by gradually increasing CO2 inhalation for about 4-5 min time period, then humanely killed by puncturing the jugular vein and collecting the blood sample at the same time (AVMA., 2020). Subsequently, samples were collected from the same liver region, snap-frozen in liquid nitrogen, and then stored at −80°C. Blood samples (5 mL per bird) were centrifuged at 3000 × g at 4 °C for 15 min to get the serum, and then it was stored at −80 °C for subsequent analysis.

Serum antioxidant parameters and immunological assays

The levels of serum IgA, IgG and IgM were measured using the ELISA kits (Jiancheng Bioengineering Institute, Nanjing, China) following the manufacturer's instructions. The antioxidant parameters (CAT, T-SOD, MDA, GSH, and T-AOC) were determined in the serum using commercially specific biochemistry kits (Jiancheng Bioengineering Institute, Nanjing, China) following the manufacturer's instruction.

DIA-based proteomics mass spectrometry assay and data analysis

Liver sample was ground individually in liquid nitrogen and lysed with SDT (containing 100 mM NaCl) and 1/100 volume of DTT, followed by 5 min of ultrasonication on ice. After incubation 8-15 min at 95 °C and ice-bath for 2 min, the lysate was centrifuged at 12,000 g for 15 min at 4 °C, and the supernatant was subsequently alkylated with sufficient IAM for 1 h at room temperature in the dark. Then the samples were completely mixed with 4 times volume of precooled acetone by vortexing, and incubated at −20 °C for at least 2 h. Samples were then centrifuged at 12,000 g for 15 min at 4 °C and the precipitation was collected. After washing with 1 mL cold acetone, the pellet was dissolved completely by Dissolution Buffer (DB buffer). The containing proteins were quantified by Bradford and sodium dodecyl sulfate-polyacrylamide gel electrophoresis (SDS-PAGE). Trypsin Gold (Promega, Madison, WI, USA) was used to digest the proteins at 37°C. The peptides were desalinated and vacuum dried. The peptides were separated on a Vanquish Neo upgraded UHPLC system with a C18 pre-column of 174,500 (5 mm×300 μm, 5 μm, thermo). The peptides separated in liquid phase were ionized by an Easy-spray (ESI) ion source and then entered the Thermo Orbitrap Astral MS-MS (Thermo Fisher Scientific, San Jose, CA, USA) for DIA mode detection.

The raw files were searched and analyzed using the DIA-NN v1.8.1 library search software, according to the Gallus gallus protein database (27,535 entries). A protein with a fold change (FC) greater than or less than 1 and P < 0.05 was defined as a differentially expressed protein (DEP). Based on the quantitative results, DEPs between different comparison groups were searched and functional analysis of differentially enriched proteins was performed by R v4.4 software packages.

DIA-based phosphoproteomics mass spectrometry assay

Procedures for liver tissue preparation, protein quantification and proteolysis were the same as for DIA proteomics analysis. The peptide mixtures were added to the TiO2 column pre-treated with binding buffer, incubated at room temperature for 30 min, centrifuged at 2,000 g for 30 s and then washed once each with washing solution and water, centrifuged at 2,000 g for 30 s. The enriched phosphopeptides were collected into a new centrifuge tube and lyophilised. The phosphopeptides were separated on a Vanquish Neo upgraded UHPLC system and ionized by an Easy-spray ion source, and then entered the Thermo Orbitrap Astral MS-MS for DIA mode detection. The data analysis process and software were the same as for proteomics.

Transcriptome sequencing and analysis

Total RNA was extracted from liver tissues using TRIzol reagent (Invitrogen, Carlsbad, CA, USA). RNA quality and quantity were assessed using gel electrophoresis, a NanoDrop 2,000 spectrophotometer (Thermo Fisher Scientific, Wilmington, DE, USA), and an Agilent Bioanalyzer 2,100 Bioanalyzer (Agilent Technologies, Santa Clara, CA, USA). RNA-seq library construction and sequencing were performed by Beijing Novogene Biotechnology (Beijing, China).

Clean reads were obtained by removing adapters and low-quality reads using fastp v0.20.1. The clean reads were then mapped to the chicken reference genome (GCA_016699485.1) using HISAT2 v2.0.5. Subsequently, we assembled the mapped reads into transcripts and quantified the gene expression to fragments per kilobase of transcript per million mapped reads (FPKM) using StringTie v1.3.3b. Differentially expressed genes (DEGs) were identified using DESeq2 v1.20.0.

GO annotation and KEGG enrichment analysis

The DEGs and DEPs were functionally annotated using Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomics (KEGG) enrichment using the R package clusterProfiler v3.8.1.

Gene set enrichment analysis (GSEA)

All expressed genes, whether or not differentially expressed between the AFS and NS groups, were used for GSEA. GSEA was performed by the clusterProfiler package in R software (v4.4.2) based on org.Gg.eg.db KEGG gene set collections of chicken (MSigDB v7.0, Broad Institute, Cambridge, MA, USA). The significant enrichment of gene set was selected based on the absolute values of NES > 1, nominal P-value of NES ≤ 0.05, and false discovery rate (FDR) ≤ 0.05 (Vu et al., 2023).

Protein interactions network analysis

The STRING database (http://stringdb.org/) online tool was used for protein interaction network analysis of DEPs, and experimentally validated interactions with interaction scores > 0.4 were selected as significant. The Molecular Complex Detection Algorithm (MCODE) plug-in of Cytoscape was used to establish protein-protein interaction (PPI) network modules, and the screened networks were visualized using Cytoscape (v3.10.1).

Joint analysis of multiomics data

In order to better explore the intrinsic mechanisms underlying the differences in immunity between the two populations of Wenchang chickens, transcriptome–proteomics integrated analyses and proteomics–phosphoproteomics integrated analyses were performed. We calculated correlations between some important DEGs and DEPs or differentially expressed phosphorylated proteins (DPPs) based on Spearman's correlation to draw a correlation heatmap.

Verification of genes expression by RT-qPCR

Total RNA from liver was extracted using the TRIzol reagent (Thermo Fisher Scientific, 15596026) and RNA quality was detected by the Nanodrop spectrophotometer (Thermo Fisher Scientific, Waltham, MA) and 1 % agarose gel electrophoresis, respectively. Then the total RNA was reverse transcribed into the first strand of cDNA using a PrimeScript™ RT Reagent Kit with gDNA Eraser (TaKaRa, Dalian, China). qPCR was carried out in a BioRad CFX-96 thermal cycler (BioRad, California, USA). All qPCR assays were performed in triplicate, and the GAPDH gene was used for data normalization. The primer information was shown in Additional file 1. The fold change in relative gene expression was calculated using the standard 2−ΔΔCt method.

Statistical analysis

All experimental results were presented as mean ± SD, with six independent replicates. We used independent sample t-tests to compare 2 groups and considered differences statistically significant at P < 0.05.

Results

Serum antioxidant activities and immunoglobulin concentrations of AFS and NS Wenchang chicken

The serum concentration of IgM in AFS Wenchang chicken was significantly higher than that in NS Wenchang chicken (P < 0.01), as shown in Table 1. The serum CAT, TAOC and GSH activities were highly significantly higher in AFS Wenchang chicken than those in NS Wenchang chicken, but the MDA activity was highly significantly lower in NS Wenchang chicken (Table 1). Serum SOD activity was not significantly different between the two Wenchang chicken groups.

Table 1.

Results of serum antioxidant and immune assays.

Items AFS NS t-value P-value
IgA (μg/mL) 203.09 ± 39.26 178.60 ± 15.18 1.425 0.185
IgG (g/L) 6.51 ± 0.33 6.34 ± 0.20 1.092 0.300
IgM (μg/mL) 269.81 ± 10.88A 202.35 ± 14.32B 9.190 0.000
CAT (U/mL) 14.18 ± 2.91A 8.90 ± 1.59B 3.899 0.003
TAOC (U/mL) 13.11 ± 1.38A 7.48 ± 2.13B 5.437 0.000
MDA (nmol/mL) 0.83 ± 0.07A 1.48 ± 0.10B 13.299 0.000
SOD (U/mL) 155.94 ± 9.83 146.17 ± 10.23 1.686 0.123
GSH (U/mL) 3148.20 ± 99.22A 2677.71 ± 199.61B 5.170 0.001
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The values superscripted A and B on the same row indicate extremely significant differences (P < 0.01).

Global gene expression profiles of AFS and NS Wenchang chicken livers

RNA-seq generated 164.75 GB of clean reads, an average of 13.73 ± 0.81 GB of clean reads per sample. The raw data of the RNA-Seq were submitted to the SRA database and obtained the accession number PRJNA1309289. For all samples, at least 96.2 % of the reads had quality scores equal to or exceeding Q30, of which 85.29 %−88.87 % were uniquely mapped to the chicken reference genome (Additional file 2). A total of 1,356 DEGs were identified, of which 700 DEGs were up-regulated and 656 DEGs were down-regulated in the AFS group (Fig. 1A, Additional file 3). Partial Least Squares Discriminant Analysis (PLS-DA) showed comprehensive differences in gene expression between the two groups, and we observed a clear separation between the AFS group and NS group (Fig. 1B).

Fig. 1.

Fig 1

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Volcano and PLS-DA maps for liver transcriptome analysis. (A) Volcano map for liver transcriptome analysis; (B) PLS-DA plot for liver transcriptome analysis.

To validate the RNA-Seq results, we performed RT-qPCR to confirm the expression of the 10 candidate DEGs in the liver tissues of the AFS and NS groups. The expression differences obtained by RT-qPCR were similar to those obtained by RNA-seq (Fig. 2A). For example, both RNA-seq and RT-qPCR results showed that ACSL1, MBL2 and IGSF21 mRNAs were highly expressed in AFS chicken livers, and TCR2 and CD88 mRNAs were highly expressed in NS chicken livers. Linear regression between RNA-seq and RT-qPCR results showed a significant positive correlation, with a correlation coefficient (r) of 0.76, supporting the reliability of RNA-seq results (Fig. 2B).

Fig. 2.

Fig 2

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RT-qPCR validation of liver transcriptome. (A) The bar graph represents the results of RT-qPCR and the heat map represents the results of transcriptome analysis; (B) Correlation of transcriptome and RT-qPCR.

To further investigate the biological functions involved in AFS Wenchang chickens, we evaluated DEGs by KEGG and GO functional enrichment analysis. DEGs were mainly enriched in pathways such as response to bacterium, mitotic cell cycle process, anion binding, and so on (Fig. 3A). The main GO category is macromolecule localization, organic substance transport, protein transport, etc. (Additional file 4).

Fig. 3.

Fig 3

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KEGG and GSEA analysis of liver transcriptome. (A) KEGG analysis of the liver transcriptome; (B) GSEA analysis of the liver transcriptome.

In order to investigate new key biological pathways of antibiotic-free diets regulating disease resistance and immunity, we performed GSEA analysis of all genes expressed in the AFS and NS Wenchang chickens and identified 50 gene sets (Additional file 5). Many of the gene sets are associated with immunity regulation and inflammatory responses, such as IL6 JAK STAT3 signaling, interferon gamma response, P53 signaling pathway, etc., thus validating and supporting the accuracy of the GSEA results (Fig. 3B).

Proteomic profiling of liver tissue from AFS and NS Wenchang chickens

A total of 7,976 proteins were identified in the liver tissues of AFS and NS Wenchang chickens. Proteins with a quantitative fold change of > 2 or < 0.5 and P < 0.05 were identified as differentially abundant proteins (DAPs). A total of 400 up-regulated DAPs and 99 down-regulated DAPs were identified in the AFS group compared to the NS group (Fig. 4A, Additional file 6). Subsequently, a heat map was generated to depict differential protein expression between groups (Fig. 4B).

Fig. 4.

Fig 4

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Results of liver proteomics analysis. (A) Volcano map of liver proteomics; (B) GO analysis of liver proteomics; (C) KEGG analysis for liver proteomics; (D) PPI analysis of liver proteomics.

As determined by GO analysis, the most enriched GO were protein targeting to membrane, protein localization to membrane and single-organism membrane organization (Fig. 4B). DAPs were involved in various KEGG pathways, including peroxisome, SNARE interactions in vesicular transport and glycerophospholipid metabolism (Fig. 4C).

The enrichment analysis of GO and KEGG pathways provides valuable insights into the molecular regulation mechanism of the difference in disease resistance and immunity between AFS and NS Wenchang chicken. We identified several DAPs that were associated with inflammatory responses, such as bifunctional epoxide hydrolase 2 (EPHX2), hydroxyacid oxidase 1 (HAO1) and peroxisome biogenesis factor 13 (PEX13) in the peroxisome pathway. Interleukin-18 (IL-18), wiskott-Aldrich syndrome protein family member 2 (WASF2) and mitogen-activated protein kinase 11 (MAPK11) were identified in the Salmonella infection signaling pathway, which are associated with host infection. All of these DAPs were up-regulated in the liver tissues of AFS Wenchang chickens.

Protein interactions network analysis was used to identify interactions between DAPs. Three proteins were identified as hubs in the network: beta-2-microglobulin precursor (B2M), dedicator of cytokinesis protein 4 (DOCK4) and vesicle-associated membrane protein 3 (VAMP3) (Fig. 4D). In addition, ADP-ribosylation factor GTPase-activating protein 3 (ARFGAP3), thyroid hormone receptor-associated protein 3 (THRAP3), 40S ribosomal protein S26 (RPS26), mediator of RNA polymerase II transcription subunit 31 (MED31), starch-binding domain-containing protein 1 (STBD1) and mediator of RNA polymerase II transcription subunit 30 (MED30) were identified as key proteins.

Integrated analysis of transcriptomics and proteomics data

Spearman's correlation coefficient between mRNA expression and protein abundance was low, but statistical analysis showed that they were highly significantly correlated (r = 0.27, P < 0.01) (Fig. 5). Among 7,976 mRNA–protein pairs, 1,101 (13.80 %) displayed significant positive correlations with Spearman’s coefficient > 0 and FDR < 0.05, whereas 118 (1.48 %) displayed significant negative correlations with Spearman’s coefficient < 0 and FDR < 0.05. Genes whose mRNA expression was significantly correlated with protein abundance were mainly enriched in signaling pathways such as Salmonella infection, peroxisome, drug metabolism, and so on. Several peroxisomal biogenesis factor (PEX) family members, such as PEX1, PEX3, PEX6, etc., which were significantly up-regulated in both mRNA expression and protein abundance in the liver of AFS Wenchang chickens, were screened, suggesting that peroxisomes were more abundant in the hepatocytes of AFS Wenchang chickens.

Fig. 5.

Fig 5

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Correlation analysis between gene expression levels and protein abundance in liver.

Identification of liver phosphoproteins in AFS and NS Wenchang chickens

The length of most peptides was between eleven and twenty-seven amino acids, which was in agreement with the general characteristics of tryptic peptides (Fig. 6A). A total of 3,436 phosphoproteins containing 38,891 phosphorylation sites were identified in AFS and NS Wenchang chicken livers (Additional file 7). Among these phosphorylation sites, 80.48 % were phosphorylated at serine residues, 16.55 % at threonine residues, and 2.97 % at tyrosine residues. According to the relative levels, the quantified proteins were divided into two categories: proteins with a quantitative ratio over 2 were considered upregulated, and proteins with a quantitative ratio less than 1/2 were considered downregulated. In the AFS Wenchang chicken liver, 2,841 phosphorylation sites of 207 phosphoproteins were significantly up-regulated, and 1848 phosphorylation sites of 149 phosphoproteins were significantly down-regulated (Fig. 6B).

Fig. 6.

Fig 6

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Results of protein phosphorylation analysis of liver. (A) Peptide length analysis; (B) Quantitative analysis of phosphoproteins and phosphorylation sites; (C) GO analysis of phosphoproteins; (D) KEGG analysis of phosphoproteins; (E) Up-regulated proteins and phosphoproteins; (F) Down-regulated proteins and phosphoproteins.

GO enrichment analysis revealed that the top two MF categories are nucleic acid binding and binding, the top two CC categories were nucleus and intracellular membrane-bounded organelle, and the top two BP categories were nucleic acid metabolic process and transcription from RNA polymerase II promoter (Fig. 6C). Seven KEGG pathways were significantly enriched, among which those related to cellular stress, inflammatory response, and apoptosis were MAPK signaling pathway, mTOR signaling pathway, Salmonella infection and autophagy in animal. (Fig. 6D).

We compared phosphoproteins with DAPs and found that only 75 of the 724 up-regulated phosphoproteins were up-regulated DAPs (Fig. 6E), and only 7 of the 523 down-regulated phosphoproteins were down-regulated DAPs (Fig. 6F), suggesting that protein phosphorylation is largely an independently regulated process. Interestingly, 143 proteins had both up- and down-regulated phosphorylation sites, suggesting that these proteins undergo complex phosphorylation regulation in the immune response. For example, protein tyrosine phosphatase receptor type C (PTPRC) has both negative and positive regulatory roles in T and B cell activation, and this function is achieved by phosphorylation or dephosphorylation of the PTPRC protein.

Discussion

Enhancing birds' inherent resistance to pathogenic bacteria is not only crucial for maintaining the stability of the poultry industry and safeguarding public food safety, but also an effective approach to reducing antibiotic usage. Many native chickens are more resistant to pathogenic bacteria than commercial strains (Kannaki et al., 2021). Correspondingly, natural antibody (IgG and IgM) levels and survival rates in the serum of native chickens were higher than those of commercial chickens (Wondmeneh et al., 2015). Natural antibodies are antibodies that are present in healthy individuals without prior exposure to exogenous antigens, so high natural antibody levels may contribute to general disease resistance (Bovenhuis et al., 2022). In this study, the serum IgM level of AFS Wenchang chicken was significantly higher than that of NS Wenchang chickens, suggesting that AFS Wenchang chicken is more resistant to general diseases.

Oxidative stress puts poultry in a sub-optimal state of health, leading to increased susceptibility to pathogenic microorganisms and diminished product quality (Lestingi et al., 2024). Vitamin E (VE) is a potent nutritional antioxidant, and broilers fed nano VE (NVE) exhibited significantly higher SOD and GSH-Px activity, as well as lower MDA levels in serum (Zhou et al., 2024). Tea polyphenols (TP) are natural antioxidants that can prevent and treat diseases by scavenging free radicals and modulating the activity of different types of oxidative enzymes in the body (Yan et al., 2020). Addition of tea polyphenols to broiler diets significantly increased serum T-SOD and T-AOC activities, as well as intestinal GST activity, and significantly reduced hepatic MDA content (Chen et al., 2024). In the present study, AFS Wenchang chicken had higher serum CAT, TAOC and GSH activities and lower MDA concentration, which indicated that AFS Wenchang chicken had strong antioxidant capacity, which might be related to long-term artificial selection and specific rearing environment.

Liver transcriptomes and proteomes are usually employed to screen for key genes and proteins associated with disease resistance and adaptive capacity in birds (Zhang et al., 2025). In this study, a number of immune-related genes, such as MBL2, LYZ, and TCR2, were identified using RNA-Seq. MBL recognizes pathogen-associated molecular patterns on the surface of many microorganisms and clears them by activating the complement system, enhancing phagocytosis, and modulating inflammation (Kalia et al., 2021). MBL also controls the release of cytokines and chemokines, and is an important component of avian innate immunity (Restrepo et al., 2022). Serum MBL concentration is regulated by the expression level of MBL2 mRNA, which is associated with various diseases in chicken (Kjærup et al., 2013). The LYZ gene encodes lysozyme, whose natural substrate is bacterial cell wall peptidoglycan, and lysozyme has antibacterial activity against a wide range of bacteria. Some feed additives that enhance the immune status of birds also increase serum lysozyme activity (Amer et al., 2022; Kishawy et al., 2024). In this study, MBL2 and LZY genes were found to be highly expressed in the liver of AFS Wenchang chickens, suggesting that AFS Wenchang chickens have higher disease resistance. By further GSEA analysis, there were significant differences in immune response and inflammatory response signaling pathways, such as IL6/JAK/STAT3 and interferon gamma response, between AFS and NS Wenchang chickens. The JAK/STAT signaling pathway is widely involved in physiological processes such as inflammation, apoptosis, and immunity in animals (Samra et al., 2025). In particular, the IL-6/JAK2/STAT3 signaling pathway, activated by inflammatory factors such as IL-6, is most closely related to inflammation and immunity (Zhang et al., 2019). In this study, the expression levels of JAK1 and STAT1 genes in AFS Wenchang chickens were significantly lower than those in NS Wenchang chickens, suggesting that AFS Wenchang chickens have a better health status and strong immunity.

Peroxisomes are essential multifunctional organelles of the organism and are considered to be important hubs in signaling networks such as redox, lipid, inflammation and innate immunity (Sarkar and Lipinski, 2024). In this study, many DAPs, such as HAO1 and PEX13, are located on the peroxisome signaling pathway. HAO1 is a liver-specific peroxidase that oxidizes glycolic acid to glyoxalate and releases H2O2. Knockdown of HAO1 exacerbates the inflammatory response, whereas overexpression of HAO1 suppresses the inflammatory response in mice (Chen et al., 2022). In addition, overexpression or silencing of HAO1 in vitro significantly affected the NF-κB signaling pathway, suggesting that HAO1 plays a key role in macrophage activation (He et al., 2021). EPHX2 encodes a soluble epoxide hydrolase that plays important regulatory roles in the cell cycle and apoptosis. The expression level of the EPHX2 gene is strongly associated with immune cell infiltration (especially tumor-associated macrophages), microsatellite instability, immunomodulators, and immunotherapy biomarkers (Hu et al., 2025). PEX13 is a peroxisomal membrane protein that plays a key role in the protein translocation step of the peroxisomal targeting signal 1 (PTS1) pathway (Ravindran et al., 2023). Deletion of the PEX13 gene results in impaired autophagic scavenging of peroxisomes and some viruses; thus, PEX13 plays a direct role in phagocytosis of peroxisomal and viral (Germain et al., 2024). Mammalian cells lacking PEX1 or PEX6 have fewer peroxisomes than wild-type cells, which was eventually attributed to pexophagy. In this study, HAO1, PEX13 and PEX1 were significantly highly expressed in the livers of AFS Wenchang chickens, implying that AFS Wenchang chickens have high immunity.

It is worth noting that gene expression at the transcriptome and translation levels does not always coincide, indicating that mRNA translation is also regulated by numerous factors, such as post-transcriptional, translational, and post-translational mechanisms. Joint analysis of transcriptomic and proteomic data can provide more comprehensive information on gene expression (Ye et al., 2021). The correlation coefficients between the proteome and the transcriptome were low in this study, and similar phenomena were found in chickens (Wang et al., 2025) and goats (Liu et al., 2022). MicroRNAs and RNA-binding proteins (RBPs) within hepatocytes significantly influence protein synthesis, leading to discrepancies between gene expression levels in the transcriptome and protein abundance in the proteome (Khoroshkin et al., 2024).

Mass spectrometry (MS)-based phosphoproteomics has become a major tool for measuring global protein phosphorylation events, enabling the reliable identification, localisation and quantification of thousands of phospho-sites in a single experiment (Muneer et al., 2025). By analysing phosphorylation networks and protein interaction networks, phosphoproteomics provides powerful tools and new perspectives to unravel complex intracellular signalling mechanisms (Zheng et al., 2025). Phosphoproteomics plays important roles in the analysis of signal transduction pathways, disease mechanisms, immunoregulatory mechanisms, and drug resistance mechanisms of pathogenic microorganisms. In this study, we found that AFS Wenchang chickens were significantly different from NS Wenchang chickens in MAPK signalling pathway, mTOR signalling pathway, Salmonella infection and autophagy pathway.

Natural killer (NK) cells mediate innate host defence against microbial infection, and the mTOR signalling pathway plays a key role in NK cell activation (Coulibaly et al., 2021). Activated mTORC1 promotes protein and lipid synthesis by phosphorylating translation initiation factors 4E-binding protein 1 (4E-BP1) and ribosomal protein S6 kinase B1 (S6K), which in turn regulates cell proliferation, metabolism, autophagy, inflammation, oxidative stress and DNA damage repair (Li et al., 2022). Many Chinese herbs and their active substances, such as Liensinine (G. Wang et al., 2024), Inulin(Q. Y. Zhang et al., 2024), Dihydromyricetin (X. Wang et al., 2024), and Anemoside B4 (Tian et al., 2024), attenuate inflammatory responses and excessive apoptosis by inhibiting the PI3K/Akt/mTOR pathway. The MAPK signaling pathway plays multiple roles in the immune response of birds, such as participating in the initiation of innate immunity, activation of adaptive immunity, and immune cell autophagy (Dong et al., 2002). In response to antigenic stimulation, T cells are required to proliferate and differentiate from a naïve state into helper T cells (Th cells) and cytotoxic T lymphocytes (CTLs), which is dependent on the MAPK signaling pathway. The signaling axis consisting of p38 MAPK and NF-κB is considered to be a classical pathway regulating the inflammatory response in many types of cells (Tong et al., 2021). In this study, a total of 75 differentially expressed phosphoproteins were identified in the MAPK signalling pathway, mTOR signalling pathway, Salmonella infection and autophagy pathway, of which 11 phosphoproteins appeared in 2 signaling pathways, such as PLA2, MAPK1, NFATC3, and so on. PLA2 is a key lipid metabolizing enzyme, abundantly found in the rough endoplasmic reticulum and lysosomes of phagocytes and monocytes, and is mainly involved in inflammatory responses, signal transduction and membrane phospholipid remodelling (Khan and Ilies, 2023). MAPK1 is a core member of the MAPK signaling pathway and promotes the release of inflammatory factors, such as TNF-α and IL-6, by phosphorylating downstream target proteins, and regulates the expression of antioxidant enzymes, such as SOD, to resist ROS damage (Moens et al., 2013). NFATC3 plays an important role in immune regulation, cell differentiation and development, and promotes the transcription of cytokines such as IL-2, IL-4 and IFN-γ (Angulo et al., 2018). These results suggest that the MAPK signalling pathway, mTOR signalling pathway, Salmonella infection and autophagy pathway play important roles in the regulation of immunity in AFS Wenchang chickens.

Conclusion

The AFS Wenchang chickens have higher serum IgM levels and stronger serum antioxidant activity than NS Wenchang chickens. Accordingly, signaling pathways related to immune and inflammatory responses, such as response to bacteria, peroxisome, IL6 JAK STAT3 signaling, etc., are highly activated in the livers. The results provide basic data for the disease resistance breeding of Wenchang chicken in the future.

CRediT authorship contribution statement

Xinli Zheng: Data curation, Funding acquisition, Methodology, Writing – original draft. Lihong Gu: Data curation, Project administration, Writing – review & editing. Xiaohui Zhang: Formal analysis, Methodology, Software. Yanxia Qi: Software, Visualization. Lehuan Wu: Data curation, Validation. Yuanyuan Shang: Formal analysis, Visualization. Fanghu Wu: Software. Tieshan Xu: Methodology. Anhong Chen: Resources.

Disclosures

No conflict of interest exits in this manuscript.

Acknowledgements

This research was funded by the Hainan Provincial Key R&D Program (ZDYF2024XDNY271) and the National Key R&D Program (2021YFD1300100).

Footnotes

Supplementary material associated with this article can be found, in the online version, at doi:10.1016/j.psj.2025.105801.

Appendix. Supplementary materials

mmc1.docx (14.2KB, docx)
mmc2.xlsx (12KB, xlsx)
mmc3.xlsx (208.2KB, xlsx)
mmc4.xls (107.9KB, xls)
mmc5.txt (19.5KB, txt)
mmc6.xlsx (190KB, xlsx)
mmc7.xlsx (968.7KB, xlsx)

Date availability

Data will be made available on request.

References

  1. American Veterinary Medical Association AVMA guidelines for the euthanasia of animals: 2020 edition. 2020. https://www.avma.org/KB/Policies/Documents/euthanasia.pdf Available from:
  2. Amer S.A., Attia G.A., Aljahmany A.A., Mohamed A.K., Ali A.A., Gouda A., Alagmy G.N., Megahed H.M., Saber T., Farahat M. Effect of 1,3-beta glucans dietary addition on the growth, intestinal histology, blood biochemical parameters, immune response, and immune expression of CD3 and CD20 in broiler chickens. Anim. (Basel) 2022;12(22):3197–3213. doi: 10.3390/ani12223197. [DOI] [PMC free article] [PubMed] [Google Scholar]
  3. Angulo C., Alamillo E., Ascencio F., Reyes-Becerril M. Characterization of nuclear factor of activated T-cells-c3 (NFATc3) and gene expression of upstream-downstream signaling molecules in response to immunostimulants in Pacific red snapper cells. Dev. Comp. Immunol. 2018;78:149–159. doi: 10.1016/j.dci.2017.10.001. [DOI] [PubMed] [Google Scholar]
  4. Ask B., van der Waaij E.H., Glass E.J., Bishop S.C. Modeling immunocompetence development and immunoresponsiveness to challenge in chicks. Poult. Sci. 2007;86(7):1336–1350. doi: 10.1093/ps/86.7.1336. [DOI] [PubMed] [Google Scholar]
  5. Bovenhuis H., Berghof T.V.L., Visker M., Arts J.A.J., Visscher J., van der Poel J.J., Parmentier H.K. Divergent selection for natural antibodies in poultry in the presence of a major gene. Genet. Sel. Evol. 2022;54(1):24. doi: 10.1186/s12711-022-00715-9. [DOI] [PMC free article] [PubMed] [Google Scholar]
  6. Chen H., Li X., Sun Y., Du Y., Wu S., Wu Y., Liu H., Liu Y., Wang Y., Zhao Q., Yin S. HAO1 negatively regulates liver macrophage activation via the NF-κb pathway in alcohol-associated liver disease. Cell Signal. 2022;99 doi: 10.1016/j.cellsig.2022.110436. [DOI] [PubMed] [Google Scholar]
  7. Chen X., Zeng D., Zeng X., Zeng Q. Effects of complex antioxidants added to chicken diet on growth performance, serum biochemical indices. Meat Qual. Antioxid. Capacity Anim. (Basel) 2024;14(3):360–371. doi: 10.3390/ani14030360. [DOI] [PMC free article] [PubMed] [Google Scholar]
  8. Coulibaly A., Velásquez S.Y., Kassner N., Schulte J., Barbarossa M.V., Lindner H.A. STAT3 governs the HIF-1α response in IL-15 primed human NK cells. Sci. Rep. 2021;11(1):7023. doi: 10.1038/s41598-021-84916-0. [DOI] [PMC free article] [PubMed] [Google Scholar]
  9. Dong C., Davis R.J., Flavell R.A. MAP kinases in the immune response. Annu. Rev. Immunol. 2002;20:55–72. doi: 10.1146/annurev.immunol.20.091301.131133. [DOI] [PubMed] [Google Scholar]
  10. Germain K., So R.W.L., DiGiovanni L.F., Watts J.C., Bandsma R.H.J., Kim P.K. Upregulated pexophagy limits the capacity of selective autophagy. Nat. Commun. 2024;15(1):375. doi: 10.1038/s41467-023-44005-4. [DOI] [PMC free article] [PubMed] [Google Scholar]
  11. Gu L.H., Wu R.R., Zheng X.L., Fu A., Xing Z.Y., Chen Y.Y., He Z.C., Lu L.Z., Qi Y.T., Chen A.H., Zhang Y.P., Xu T.S., Peng M.S., Ma C. Genomic insights into local adaptation and phenotypic diversity of Wenchang chickens. Poult. Sci. 2024;103(3) doi: 10.1016/j.psj.2023.103376. [DOI] [PMC free article] [PubMed] [Google Scholar]
  12. Hartcher K.M., Lum H.K. Genetic selection of broilers and welfare consequences: a review. World's. Poult. Sci. J. 2020;76(1):154–167. doi: 10.1080/00439339.2019.1680025. [DOI] [Google Scholar]
  13. He Z., Song Z., Meng L., Cheng W., Huang F., Zheng M., Xu W., Xiao R., Fang H., Zhu Y. Lipopolysaccharide-induced transcriptional changes in LBP-deficient rat and its possible implications for liver dysregulation during sepsis. J. Immunol. Res. 2021;2021 doi: 10.1155/2021/8356645. [DOI] [PMC free article] [PubMed] [Google Scholar]
  14. Hu W., Ding X., Wu X., Xi X., Xu J., Dai S., Chen J., Hu S., Zhao Q., Chen F. A comprehensive analysis of epoxide hydrolase 2 (EPHX2) in pan-cancer. Cancer Rep. (Hob.) 2025;8(3) doi: 10.1002/cnr2.70188. [DOI] [PMC free article] [PubMed] [Google Scholar]
  15. Idoko-Akoh A., Goldhill D.H., Sheppard C.M., Bialy D., Quantrill J.L., Sukhova K., Brown J.C., Richardson S., Campbell C., Taylor L., Sherman A., Nazki S., Long J.S., Skinner M.A., Shelton H., Sang H.M., Barclay W.S., McGrew M.J. Creating resistance to avian influenza infection through genome editing of the ANP32 gene family. Nat. Commun. 2023;14(1):6136. doi: 10.1038/s41467-023-41476-3. [DOI] [PMC free article] [PubMed] [Google Scholar]
  16. Iuspa M.A.M., Soares I., Belote B.L., Kawazoe U., Santin E. Comparing performance and resistance of two broilers breeds challenged by Eimeria acervulina. Vet. Parasitol. 2020;287 doi: 10.1016/j.vetpar.2020.109235. [DOI] [PubMed] [Google Scholar]
  17. Kalia N., Singh J., Kaur M. The ambiguous role of mannose-binding lectin (MBL) in human immunity. Open Med. (Wars) 2021;16(1):299–310. doi: 10.1515/med-2021-0239. [DOI] [PMC free article] [PubMed] [Google Scholar]
  18. Kannaki T.R., Priyanka E., Haunshi S. Research note: disease tolerance/resistance and host immune response to experimental infection with Pasteurella multocida A:1 isolate in Indian native Nicobari chicken breed. Poult. Sci. 2021;100(8) doi: 10.1016/j.psj.2021.101268. [DOI] [PMC free article] [PubMed] [Google Scholar]
  19. Khan S.A., Ilies M.A. The phospholipase A2 superfamily: structure, isozymes, catalysis, physiologic and pathologic roles. Int. J. Mol. Sci. 2023;24(2):1353–1388. doi: 10.3390/ijms24021353. [DOI] [PMC free article] [PubMed] [Google Scholar]
  20. Khoroshkin M., Buyan A., Dodel M., Navickas A., Yu J., Trejo F., Doty A., Baratam R., Zhou S., Lee S.B., Joshi T., Garcia K., Choi B., Miglani S., Subramanyam V., Modi H., Carpenter C., Markett D., Corces M.R., Mardakheh F.K., …, Goodarzi H. Systematic identification of post-transcriptional regulatory modules. Nat. commun. 2024;15(1):7872. doi: 10.1038/s41467-024-52215-7. [DOI] [PMC free article] [PubMed] [Google Scholar]
  21. Kishawy A.T.Y., Abd El-Wahab R.A., Eldemery F., Abdel Rahman M.M.I., Altuwaijri S., Ezz-Eldin R.M.M., Abd-Allah E.M., Zayed S., Mulla Z.S., El Sharkawy R.B., Badr S., Youssef W., Ibrahim D. Insights of early feeding regime supplemented with glutamine and various levels of omega-3 in broiler chickens: growth performance, muscle building, antioxidant capacity, intestinal barriers health and defense against mixed Eimeria spp infection. Vet, Q. 2024;44(1):1–20. doi: 10.1080/01652176.2024.2373287. [DOI] [PMC free article] [PubMed] [Google Scholar]
  22. Kjærup R.M., Norup L.R., Skjødt K., Dalgaard T.S., Juul-Madsen H.R. Chicken mannose-binding lectin (MBL) gene variants with influence on MBL serum concentrations. Immunogenetics. 2013;65(6):461–471. doi: 10.1007/s00251-013-0689-6. [DOI] [PubMed] [Google Scholar]
  23. Lestingi A., Alagawany M., Di Cerbo A., Crescenzo G., Zizzadoro C. Spirulina (Arthrospira platensis) used as functional feed supplement or alternative protein source: a review of the effects of different dietary inclusion levels on production performance, health status, and meat quality of broiler chickens. Life (Basel) 2024;14(12):1537–1618. doi: 10.3390/life14121537. [DOI] [PMC free article] [PubMed] [Google Scholar]
  24. Li X., Wang J., Lin W., Yuan Q., Lu Y., Wang H., Chen Y., Chen L., Dai P., Long H., Li X. circEXOC6B interacting with RRAGB, an mTORC1 activator, inhibits the progression of colorectal cancer by antagonizing the HIF1A-RRAGB-mTORC1 positive feedback loop. Mol. Cancer. 2022;21(1):135. doi: 10.1186/s12943-022-01600-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  25. Liu Y., Ding Y., Liu Z., Chen Q., Li X., Xue X., Pu Y., Ma Y., Zhao Q. Integration analysis of transcriptome and proteome reveal the mechanisms of goat wool bending. Front. Cell Dev. Biol. 2022;10 doi: 10.3389/fcell.2022.836913. [DOI] [PMC free article] [PubMed] [Google Scholar]
  26. Mehdi Y., Létourneau-Montminy M.P., Gaucher M.L., Chorfi Y., Suresh G., Rouissi T., Brar S.K., Côté C., Ramirez A.A., Godbout S. Use of antibiotics in broiler production: global impacts and alternatives. Anim. Nutr. 2018;4(2):170–178. doi: 10.1016/j.aninu.2018.03.002. [DOI] [PMC free article] [PubMed] [Google Scholar]
  27. Moens U., Kostenko S., Sveinbjørnsson B. The role of mitogen-activated protein kinase-activated protein kinases (MAPKAPKs) in inflammation. Genes. (Basel) 2013;4(2):101–133. doi: 10.3390/genes4020101. [DOI] [PMC free article] [PubMed] [Google Scholar]
  28. Muaz K., Riaz M., Akhtar S., Park S., Ismail A. Antibiotic residues in chicken meat: global prevalence, threats, and decontamination strategies: a review. J. Food Prot. 2018;81(4):619–627. doi: 10.4315/0362-028x.Jfp-17-086. [DOI] [PubMed] [Google Scholar]
  29. Muneer G., Chen C.S., Chen Y.J. Advancements in global phosphoproteomics profiling: overcoming challenges in sensitivity and quantification. Proteomics. 2025;25(1–2) doi: 10.1002/pmic.202400087. [DOI] [PMC free article] [PubMed] [Google Scholar]
  30. Ravindran R., Bacellar I.O.L., Castellanos-Girouard X., Wahba H.M., Zhang Z., Omichinski J.G., Kisley L., Michnick S.W. Peroxisome biogenesis initiated by protein phase separation. Nature. 2023;617(7961):608–615. doi: 10.1038/s41586-023-06044-1. [DOI] [PMC free article] [PubMed] [Google Scholar]
  31. Restrepo B.N., Marín K., Romero P., Arboleda M., Muñoz A.L., Bosch I., Vásquez-Serna H., Torres O.A. Role of cytokines, chemokines, C3a, and mannose-binding lectin in the evolution of the chikungunya infection. Am. J. Clin. Exp. Immunol. 2022;11(3):51–63. www.ajcei.us /ISSN:2164-7712/AJCEI0139604. [PMC free article] [PubMed] [Google Scholar]
  32. Roth N., Käsbohrer A., Mayrhofer S., Zitz U., Hofacre C., Domig K.J. The application of antibiotics in broiler production and the resulting antibiotic resistance in Escherichia coli: a global overview. Poult. Sci. 2019;98(4):1791–1804. doi: 10.3382/ps/pey539. [DOI] [PMC free article] [PubMed] [Google Scholar]
  33. Samra S., Bergerson J.R.E., Freeman A.F., Turvey S.E. JAK-STAT signaling pathway, immunodeficiency, inflammation, immune dysregulation, and inborn errors of immunity. J. Allergy Clin. Immunol. 2025;155(2):357–367. doi: 10.1016/j.jaci.2024.09.020. [DOI] [PubMed] [Google Scholar]
  34. Sarkar C., Lipinski M.M. Role and function of peroxisomes in neuroinflammation. Cells. 2024;13(19):1655–1667. doi: 10.3390/cells13191655. [DOI] [PMC free article] [PubMed] [Google Scholar]
  35. Tian X., Li J., Liu S., Dong Q., Fu Y., Luo R., Sun Y., Guo L., Lu Q., Ye C., Liu J., Fu S., Qiu Y. Anemoside B4 attenuates necrotic enteritis of laying hens induced by Clostridium perfringens via inhibiting NF-κb and PI3K/Akt/mTOR signalling pathways. Heliyon. 2024;10(12) doi: 10.1016/j.heliyon.2024.e33161. [DOI] [PMC free article] [PubMed] [Google Scholar]
  36. Tong C., Chen T., Chen Z., Wang H., Wang X., Liu F., Dai H., Wang X., Li X. Forsythiaside a plays an anti-inflammatory role in LPS-induced mastitis in a mouse model by modulating the MAPK and NF-κb signaling pathways. Res. Vet. Sci. 2021;136:390–395. doi: 10.1016/j.rvsc.2021.03.020. [DOI] [PubMed] [Google Scholar]
  37. Vu T.H., Heo J., Hong Y., Kang S., Tran H.T.T., Dang H.V., Truong A.D., Hong Y.H. HPAI-resistant Ri chickens exhibit elevated antiviral immune-related gene expression. J. Vet. Sci. 2023;24(1):e13. doi: 10.4142/jvs.22229. [DOI] [PMC free article] [PubMed] [Google Scholar]
  38. Wang G., Ma F., Xie K., Li X., Tan X., Xia Y., Wang Y., Dong J. Liensinine alleviates mouse intestinal injury induced by sepsis through inhibition of oxidative stress, inflammation, and cell apoptosis. Int. Immunopharmacol. 2024;127 doi: 10.1016/j.intimp.2023.111335. [DOI] [PubMed] [Google Scholar]
  39. Wang X., Li X., Ma X., Zhang L., Han T., Zhang D. Dihydromyricetin alleviates inflammatory bowel disease associated intestinal fibrosis by inducing autophagy through the PI3K/AKT/mTOR signaling pathway. Naunyn Schmiedeb. Arch. Pharmacol. 2024;397(6):4183–4194. doi: 10.1007/s00210-023-02856-0. [DOI] [PubMed] [Google Scholar]
  40. Wang Y., Liu L., Zhao Y., Ren Y., Miao X., Dong Y., Liu L., Li X. Transcriptomic and proteomic analysis reveals the mechanism of chicken cecum response to Salmonella enterica serovar Enteritidis inoculation. iScience. 2025;28(1) doi: 10.1016/j.isci.2024.111571. [DOI] [PMC free article] [PubMed] [Google Scholar]
  41. Wondmeneh E., Van Arendonk J.A., Van der Waaij E.H., Ducro B.J., Parmentier H.K. High natural antibody titers of indigenous chickens are related with increased hazard in confinement. Poult. Sci. 2015;94(7):1493–1498. doi: 10.3382/ps/pev107. [DOI] [PMC free article] [PubMed] [Google Scholar]
  42. Xiao L., Qi L., Fu R., Nie Q., Zhang X., Luo W. A large-scale comparison of the meat quality characteristics of different chicken breeds in South China. Poult. Sci. 2024;103(6) doi: 10.1016/j.psj.2024.103740. [DOI] [PMC free article] [PubMed] [Google Scholar]
  43. Xu L., Wang W., Xu W. Effects of tetracycline antibiotics in chicken manure on soil microbes and antibiotic resistance genes (ARGs) Env. Geochem. Health. 2022;44(1):273–284. doi: 10.1007/s10653-021-01004-y. [DOI] [PubMed] [Google Scholar]
  44. Yan Z., Zhong Y., Duan Y., Chen Q., Li F. Antioxidant mechanism of tea polyphenols and its impact on health benefits. Anim. Nutr. 2020;6(2):115–123. doi: 10.1016/j.aninu.2020.01.001. [DOI] [PMC free article] [PubMed] [Google Scholar]
  45. Ye Z., Yu J., Yan W., Zhang J., Yang D., Yao G., Liu Z., Wu Y., Hou X. Integrative iTRAQ-based proteomic and transcriptomic analysis reveals the accumulation patterns of key metabolites associated with oil quality during seed ripening of Camellia oleifera. Hortic. Res. 2021;8(1):157. doi: 10.1038/s41438-021-00591-2. [DOI] [PMC free article] [PubMed] [Google Scholar]
  46. Zhang C., Liu J., Yuan C., Ji Q., Chen D., Zhao H., Jiang W., Ma K., Liu L. JAK2/STAT3 is associated with the inflammatory process in periapical granuloma. Int. J. Clin. Exp. Pathol. 2019;12(1):190–197. [PMC free article] [PubMed] [Google Scholar]
  47. Zhang Q.Y., Zhong M.T., Gi M., Chen Y.K., Lai M.Q., Liu J.Y., Liu Y.M., Wang Q., Xie X.L. Inulin alleviates perfluorooctanoic acid-induced intestinal injury in mice by modulating the PI3K/AKT/mTOR signaling pathway. Environ. Pollut. 2024;342 doi: 10.1016/j.envpol.2023.123090. [DOI] [PubMed] [Google Scholar]
  48. Zhang S., Wang Q., Yao X., Dong J., Li G., Zang Y., Jiang S., Wang Y. Transcriptomic and proteomic analysis of the jejunum revealed the effects and mechanism of protocatechuic acid on alleviating Salmonella typhimurium infection in chickens. Poult. Sci. 2025;104(1) doi: 10.1016/j.psj.2024.104606. [DOI] [PMC free article] [PubMed] [Google Scholar]
  49. Zhang W., Jian X., Ding S., Chang J., Ji S., Chi Y. Insights into the gut microbiota characteristics between the organic and traditional feeding chickens based on amplicon and metagenomic sequencing. Front. Microbiol. 2024;15 doi: 10.3389/fmicb.2024.1509461. [DOI] [PMC free article] [PubMed] [Google Scholar]
  50. Zheng X., Zhou L., Xu T., Wang G., Peng Y., Wen C., Wu M., Tao H., Dai Y. Applications and prospects of phosphoproteomics in renal disease research. PeerJ. 2025;13 doi: 10.7717/peerj.18950. [DOI] [PMC free article] [PubMed] [Google Scholar]
  51. Zhou J., Li Z., Guo W., Wang Y., Liu R., Huang X., Li Y., Yang X., Liu L., Liu Y., Xu X. Nano vitamin E improved the antioxidant capacity of broiler chickens. J. Anim. Sci. 2024:102. doi: 10.1093/jas/skae095. [DOI] [PMC free article] [PubMed] [Google Scholar]

Associated Data

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

Supplementary Materials

mmc1.docx (14.2KB, docx)
mmc2.xlsx (12KB, xlsx)
mmc3.xlsx (208.2KB, xlsx)
mmc4.xls (107.9KB, xls)
mmc5.txt (19.5KB, txt)
mmc6.xlsx (190KB, xlsx)
mmc7.xlsx (968.7KB, xlsx)

Data Availability Statement

Data will be made available on request.

Articles from Poultry Science are provided here courtesy of Elsevier

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