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. 2025 Jul 19;104(10):105589. doi: 10.1016/j.psj.2025.105589

Identification of the T-box transcription factor t-bet in chickens and its role in immune response

Yuxin Guo a,b,c, Zhaocan Zhou a,b,c, Hui Gao a,b,c, Shujun Zhang a,b,c, Zhi Chen a,b,c, He Chang a,b,c, Hong Cao a,b,c, Li Gao a,b,c, Yongqiang Wang a,b,c,⁎, Shijun J Zheng a,b,c,⁎
PMCID: PMC12332921  PMID: 40737904

Abstract

T-bet (T-box transcription factor TBX21), encoded by the Tbx21 gene, is a key regulator of T helper 1 (Th1) cell differentiation and cellular immunity. However, the role of T-bet in avian species remains elusive. To investigate the role of T-bet in avian immune response, we cloned chicken T-bet (chT-bet) from a White Leghorn chicken spleen-derived cDNA library. Multiple sequence alignments and structural analyses revealed that the amino acid sequence of chT-bet has 50.4 % and 51.1 % identity to its human and mouse orthologs, respectively, but the T-box DNA-binding domain remains conserved across species. We found that chT-bet is highly expressed in immune-related organs, particularly the spleen and thymus, and that Newcastle disease virus (NDV) infection significantly upregulated chT-bet expression both in virto and in vivo. Knockdown of chT-bet by RNAi markedly reduced the expression of IFN-γ but not IL-4 in MSB1 cells. Furthermore, chT-bet overexpression in DF-1 cells activated the promoter of IFN-γ while suppressing promoter activation of IL-2 and IL-4. Chromatin immunoprecipitation (ChIP) assays confirmed the direct binding of chT-bet to IFN-γ and IL-2 promoters. In contrast, chT-bet′s regulation of IL-4 appeared indirect. These findings establish chT-bet as a central orchestrator of Th1 immunity in chickens, directly driving IFN-γ production and regulating IL-2 and IL-4 expressions through distinct pathways, providing insights for vaccine development and disease control strategies.

Keywords: T-bet, Chicken, Th1 immune response, Cytokine regulation

Introduction

T-bet, encoded by the Tbx21 gene, belongs to the T-box family of transcription factors, which are characterized by a conserved DNA-binding domain known as the T-box domain(Afkarian et al., 2002). The T-box domain is responsible for specific DNA binding and plays a critical role in regulating gene expression by recognizing and binding to T-box consensus sequences in the promoters of target genes(Stirnimann et al., 2010; Papaioannou, 2014). T-bet is widely recognized as a master regulator of Th1 cell differentiation and essential for the production of IFN-γ, a key cytokine in cellular immunity(Lazarevic et al., 2013). In mammals, T-bet is predominantly expressed in immune-related tissues, such as the spleen, thymus, and lymph nodes, where it drives Th1 cell differentiation and suppresses Th2 immune response by inhibiting the expression of Th2-specific cytokines, including IL-4 and IL-5(Finotto et al., 2002; Hwang et al., 2005b; Djuretic et al., 2007). Furthermore, T-bet has been implicated in regulating other cytokines, including IL-2, which is critical for T-cell proliferation and survival(Grange et al., 2013; Oh and Hwang, 2014; Nosko et al., 2017).

The importance of T-bet in immune regulation is further highlighted by studies using knockout mice. T-bet-deficient mice exhibit severe defects in Th1 cell differentiation and IFN-γ production, leading to impaired immune response to intracellular pathogens such as Listeria monocytogenes and Mycobacterium tuberculosis(Finotto et al., 2002; Lugo-Villarino et al., 2003; Sullivan et al., 2005). Additionally, T-bet knockout mice develop spontaneous airway inflammation and hyperresponsiveness, resembling human asthma, due to an unchecked Th2 response(Finotto et al., 2002). These findings underscore the critical role of T-bet in maintaining the balance between Th1 and Th2 immune responses and highlight the central role of T-bet in orchestrating immune responses and its potential as a therapeutic target for immune-related diseases.

Despite the wealth of knowledge on T-bet in mammals, its function in avian species, particularly in chickens, remains largely unknown. Chickens, as a key model for avian immunology and a major agricultural species, possess a unique immune system distinct from that of mammals in organ architecture and molecular components. Key differences include the bursa of Fabricius—a central immune organ exclusive to birds that drives B cell development and maturation (analogous to mammalian bone marrow)—and a compartmentalized thymus that may uniquely shape T cell differentiation(Glick et al., 1956; Bódi et al., 2015). Unlike mammals, chickens lack lymph nodes but utilize mucosal lymphoid aggregates (e.g., gut-associated lymphoid tissue, Harderian gland etc.) for localized immunity(van Ginkel et al., 2009; Ceccopieri and Madej, 2024). At the molecular level, chickens lack cytokines such as IL-5 and IL-19 critical for eosinophil and B cell functions in mammals, yet harbor avian-specific genes like TLR15 and IL-26(Boyd et al., 2012; Truong et al., 2016; Bean and Lowenthal, 2022). These evolutionary adaptations highlight the divergence of avian immune regulation, making the study of conserved factors like T-bet essential to uncover both shared and species-specific mechanisms.

Recent studies have begun to shed light on the avian immune system, particularly the roles of transcription factors in regulating cytokine expression. For example, the role of GATA-3, a key regulator of Th2 responses in mammals, has been partially characterized in chickens, revealing both similarities and differences compared to its mammalian counterparts(Ishihara et al., 1995; Lilleväli et al., 2007; Li et al., 2022). Moreover, ETV-6 in chickens has also been reported as a pro-viral factor reducing host response by inhibiting TBK1 phosphorylation(Zhang et al., 2024). However, the role of T-bet in chickens remains poorly understood. This gap in knowledge limits our understanding of the avian immune system and hinders the development of targeted strategies for modulating immune responses in poultry.

In this study, we aimed to address this gap by cloning the chicken Tbx21 gene and performing bioinformatic analyses to characterize its sequence and functional regulatory elements. Furthermore, we investigated the impact of chT-bet on the expression levels of key cytokines, including IFN-γ, IL-2, and IL-4, and explored the underlying regulatory mechanisms. Our findings not only fill a significant gap in the understanding of T-bet function in avian species but also provide a foundation for further research into the immune regulation mechanisms in chickens. This study may contribute to the development of novel strategies for disease control in poultry through modulation of immune responses.

Materials and methods

Cells and viruses

DF-1 cells (immortalized chicken embryo fibroblasts) and MDCC-MSB1 cells (chicken lymphoblastoid cell line) were obtained from the American Type Culture Collection (ATCC). DF-1 cells were cultured in Dulbecco′s modified eagle medium (DMEM; Gibco, USA) supplemented with 10 % fetal bovine serum (FBS; Sigma, Switzerland). MSB1 cells were maintained in RPMI 1640 medium (Gibco, USA) supplemented with 10 % FBS. All cells were cultured in a 5 % CO2 incubator at 37°C. NDV Lasota was kindly provided by Professor Jinhua Liu (China Agricultural University, China).

Animals

The specific-pathogen-free (SPF) White Leghorn chickens were purchased from Beijing Boehringer Ingelheim Vital Biotechnology Co., Ltd. A total of 12 SPF chickens were used in the experiment, the details of chicken groups are provided in the NDV infection experiments section. Animal experiments were conducted in an ABSL-2 biosafety laboratory with separate negative pressure isolators (temperature: 26-29°C; humidity: 50–60 %; 12 h light/dark cycle) for each group of chickens. Two-week-old SPF chickens of either sex were used in the experiment, receiving appropriate care throughout the experiment, including suitable feed, accommodation, and health monitoring. All animal procedures were approved by the Ethical Inspection Committee of China Agricultural University Laboratory Animal Welfare and Animal Experiment (Approval ID: Aw70013202-2-1) and conducted per its regulations and guidelines.

Reagents, chemicals and antibodies

All restriction enzymes were purchased from New England Biolabs (NEB, USA). Plasmid vectors pGL3-basic, pRL-TK, pRK5-Flag, and pEGFP-N1 were obtained from Clontech (USA). Endotoxin-free plasmid preparation kits were purchased from Aidlab (Beijing, China). QIAfilter plasmid kits were purchased from QIAGEN (Germany). All recombinant plasmids were constructed by standard molecular biology techniques.

Mouse monoclonal antibodies (mAbs) against chicken IL-2 (EU-0221), chicken IL-4 (EU-0222), and chT-bet (EU-0233) were purchased from SAE Biomed-tech (China) and biotinylated by Bioss (China). Biotin-conjugated anti-chicken IFN-γ mAb was purchased from Mabtech (MT7C10; Switzerland). Anti-Flag mAb was purchased from Sigma-Aldrich (F1804; USA). Anti-GAPDH mAb was purchased from Proteintech (60004-1-Ig; USA). Biotinylated mouse IgG isotype control was purchased from Thermo Fisher (13-4714-85; USA). Horseradish peroxidase (HRP)-conjugated goat anti-rabbit IgG (SH-0031) and goat anti-mouse IgG (SH-0011) were purchased from Dingguo Company (China). Streptavidin APC was purchased from Thermo Fisher (17-4317-82; USA).

chTbx21 gene assembly and cloning

The chTbx21 sequence was reconstructed using NCBI SRA accessions ERX321404 and ERX4283388-4283394. Initial BLAST searches against SRA datasets were performed using the partial chTbx21 sequence (GenBank: CB016768.1). Retrieved sequences were manually assembled using SeqMan software (DNASTAR, USA), with iterative BLAST searches conducted using generated contigs until complete ORF coverage was achieved.

The coding sequence (CDS) was amplified from a White Leghorn spleen-derived cDNA library using primers designed by the assembled sequence (Table 1). The cloned sequence was verified against digital reconstruction and deposited in GenBank (Accession: OQ784847.1).

Table 1.

Primers for gene cloning and vector construction.

Gene/Plasmid Sequence (5′→3′) *
chTbx21-CDS (fragmented amplified) F ATGAGCGGCTGAGCGGG
R CGCCTGCCCTGCTTGGTG
F GTGCAGGTGATGCTCAAC
R CCCTCCTCCTTGCCTTTCTC
F CTGGGCTGGTACCGGGAGCC
R GGCAGGGATGCCCTGCACTGG
pEGFP-N1-chT-bet F TTAGTGAACCGTCAGATCCGATGGGCGCGCTGGAG
R ATGGTGGCGACCGGTGGATCGTTCCCATAGAAGCC
pRK5-Flag-chT-bet F ACGACGATGACAAGGGATCCATGGGCGCGCTGGAG
R TGGGCCATGGCGGCCAAGCTTCAGTTCCCATAGAAG
pGL3-IfngLuc F CGTGCTAGCCCGGGCTCGAGCCAACATTTTGCCAA
R AGTACCGGAATGCCAAGCTTCAGTTCAAATGCTCA
PGL3-Il2Luc-1 F GTGCTAGCCCGGGCTCGAGTCTTCTTTAT
R CCGGAATGCCAAGCTTGGCAGTGTCC
PGL3-Il2Luc-2 F TTACGCGTGCTAGCCCGGGCGCTCAACAGGAAAT
R CCAACAGTACCGGAATGCCACTTCACTTTGCGCAT
PGL3-Il2Luc-3 F TTACGCGTGCTAGCCCGGGCGACTTGTTCAACTTG
R CCAACAGTACCGGAATGCCACTGTAGTACTTGTGC
PGL3-Il2Luc-4 F TTACGCGTGCTAGCCCGGGCATATGAGAGTGGCCT
R CCAACAGTACCGGAATGCCAAAGCTATTAGACAGG
PGL3-Il2Luc-5 F TTACGCGTGCTAGCCCGGGCCACGTTTACTTACCA
R CCAACAGTACCGGAATGCCACATAAGCAAGCTGGG
PGL3-Il2Luc-6 F TTACGCGTGCTAGCCCGGGCTTCTGAACATCCTCT
R CCAACAGTACCGGAATGCCAGAACAACTTCAGCGA
PGL3-Il2Luc-7 F TTACGCGTGCTAGCCCGGGCTAGCTCTGAATCAGC
R CCAACAGTACCGGAATGCCACACAAGAATGATCAG
PGL3-Il2Luc-8 F TTACGCGTGCTAGCCCGGGCCTGGTGTTTGATTCA
R CCAACAGTACCGGAATGCCACAGTACAGAAGTACT
PGL3-Il4Luc-1 F CGTGCTAGCCCGGGCTCGAGTGGGGGGAAC
R CCGGAATGCCAAGCTTGGTCTCTGGG
PGL3-Il4Luc-2 F TTACGCGTGCTAGCCCGGGCGTAGCACCTTCCCATTGCAC
R CCAACAGTACCGGAATGCCATGACAGGTCACATTGAGCTC
PGL3-Il4Luc-3 F TTACGCGTGCTAGCCCGGGCAACTCATTCACCTCCCAGC
R CCAACAGTACCGGAATGCCATGCTCCAGAGATCACATCTC
PGL3-Il4Luc-4 F TTACGCGTGCTAGCCCGGGCAACACTGCACCCTGCACAGT
R CCAACAGTACCGGAATGCCAGAGATGCTGGTTAGTGCTGT
PGL3-Il4Luc-5 F TTACGCGTGCTAGCCCGGGCACACCACTGGCGATGAACTT
R CCAACAGTACCGGAATGCCATAGAGGAACAGGAAGCAGAT
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* The underlined sequences indicate the restriction enzyme cleavage site or a sequence homologous to the respective gene.

Sequence analysis

Conserved domains in chT-bet were predicted using the SMART database. Multiple sequence alignments of T-box domain amino acid sequences across species were performed using MEGA 11, with subsequent results visualized and enhanced by GeneDoc. A phylogenetic tree of Tbx21 was constructed via the Neighbor-Joining method in MEGA 11 with 1000 bootstrap replicates. Analyzed sequences included: Lathamus discolor (XM_065699105.1), Caloenas nicobarica (XM_065650921.1), Zonotrichia leucophrys (XM_064733513.1), Gallus gallus (OQ784847.1), Emys orbicularis (XM_065422698.1), Crocodylus porosus (XM_019548344.1), Mus musculus (NM_019507.2), Homo sapiens (NM_013351.2), Sus scrofa (NM_001315722.1), Salmo salar (NM_001199226.1), Danio rerio (NM_001170599.2), Ctenopharyngodon idella (XM_051915394.1), Pelobates fuscus (XM_063458842.1), and Bombina bombina (XM_053697631.1).

Quantitative real-time PCR (qRT-PCR) analysis

RNA was prepared from pooled tissue samples (spleen, thymus, bursa of Fabricius, heart, liver, kidney, lung, trachea, esophagus, crop, gizzard, proventriculus, duodenum, pancreas, jejunum, ileum, cecum, rectum, brain, and muscle; 50 mg/organ) of three White Leghorn chickens using an EASYspin Plus RNA Extraction Kit (Aidlab, China) per the manufacturer′s instructions. MDCC-MSB1 cells and splenic lymphocytes were similarly processed for RNA isolation to analyze the expression of cytokine or chT-bet. 3 μg of total RNA was used for cDNA synthesis by reverse transcription using a HiScript III All-in-one RT SuperMix kit (R333; Vazyme, China). The quantitative real-time PCR analysis was performed using Taq Pro Universal SYBR qPCR Master Mix (Q712; Vazyme, China) on a LightCycler 480II (Roche, USA) under the following thermal cycling protocol: initial denaturation at 95°C for 30 s; 45 cycles of 95°C for 5 s and 60°C for 30 s. A melting curve analysis (65–95°C, 0.5°C/s increment) was subsequently performed to confirm amplification specificity. The reaction mixture was 20 μL, containing 2 μL of template cDNA. All samples were tested in triplicate on the same plate. Gapdh was used as an endogenous control, with relative quantification calculated via the 2-ΔΔCt method. Primer sets used for qRT-PCR (Table 2) were designed according to literature or using Primer Premier 5 and have been reported or predicted to exhibit amplification efficiencies between 90 % and 110 % under similar reaction conditions(Wang et al., 2018).

Table 2.

Specific primers to amplify different target genes in RT-qPCR.

Gene Sequence (5′→3′) Length (bp) GenBank accession No.
chTbx21 F: CTGTCACTGCCTACCAGAACG 101 OQ784847.1
R: GGCTCCATACATCGAGTCAAAG
Ifng F: CACTGACAAGTCAAAGCCGC 87 NM_205149.2
R: ACCTTCTTCACGCCATCAGG
Il2 F: AGAGTCTTACGGGTCTAAATCACAC 106 NM_204153.2
R: CTCACAAAGTTGGTCAGTTCATGG
Il4 F: GTGAATGACATCCAGGGAGAGGTTT 178 NM_001007079.2
R: TCAGGAGCTGACGCATGTTGA
Gapdh F: TGCCATCACAGCCACACAGAAG 123 NM_204305.2
R: ACTTTCCCCACAGCCTTAGCAG
Ifng-promoter F: TGGCTCAGTTCAAATGCTCAGATAG 80 NC_052532.1
R: ACATAACTATTAGAAGCTGAAGCTCAC
Ifng-intron F: ATCAAAGTTCTGCCT 116 NC_052532.1
R: GATGTAATTTACTGCC
Il2-promoter F: GATAGCTCGTGACACTTT 121 NC_052535.1
R: GGTGTTAGGAGGAAAGG
Il4-promote F: TTGGATATGGGTGAGCAT 138 NC_052544.1
R: GAGCAGCATTCAGTGAGAT
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Subcellular localization

The chTbx21 CDS was cloned into pEGFP-N1 and transfected into DF-1 cells. Twenty-four hours post-transfection, cells were fixed and nuclei-stained with DAPI (C0060; Solarbio, China). EGFP fluorescence was visualized using an inverted fluorescence microscopy. Construction primers are listed in Table 1.

NDV infection experiments

Ex vivo analysis: Splenic lymphocytes were isolated from two-week-old uninfected SPF chickens using peripheral blood lymphocyte isolation kit (LTS1090C; TBD, China). The isolated lymphocytes were cultured in 10 % 1640 medium and seeded at a density of 5 × 107 in 12-well plates. Cells were infected with NDV Lasota at an MOI of 0.5 and harvested at different time points (6, 12, and 24 h) post-infection. Total cell lysates were prepared and subjected to qRT-PCR or Western Blot analysis, respectively, to detect the expression of chT-bet at an mRNA or protein level.

In vivo analysis: A total of twelve two-week-old SPF chicks were randomly allocated to NDV infection group (n = 6, 10⁶ EID₅₀/100 μL via ocular inoculation) or PBS-treated control group (n = 6). Birds from both groups were sacrificed on days 3 (n = 3 per group) and 7 (n = 3 per group) post-infection for organ collection (thymus, spleen, and bursa of Fabricius). The harvested tissues were immediately immersed in a 4 % paraformaldehyde solution for fixation. After 24 h of fixation, specimens underwent sequential dehydration through an ethanol gradient series and subsequent paraffin embedding. Sections of 5 μm thickness were obtained using a rotary microtome and mounted onto glass slides. After draining excess moisture, the slides were dried in a drying oven for 3 hours to complete the preparation. Standard immunohistochemistry (IHC) staining procedures were performed using anti-chT-bet pAbs. Finally, the stained sections were examined under a light microscope, with quantitative analysis of immunoreactivity determined by calculating the average optical density (AOD) using ImageJ. AOD = integrated option density (IOD)/region of interest (ROI) area.

Overexpression of chT-bet and RNA interference

To overexpress chT-bet in cells, MSB1 cells were suspended in Opti-MEM (5 × 10⁶ cells/100 μL) and were electroporated with 10 μg pRK5-Flag-chT-bet using an X-Porator H1 (Etta Biotech, China) under optimized parameters: 200 V pulse voltage, 1200 μs pulse duration, 4 consecutive pulses. For RNA interference, cells were transfected with 50 pmol chT-bet siRNA (5′-GGUGCAGGUGAUGCUCAACAATT-3′) or control siRNA (5′-UUCUCCGAACGUGUCACGUTT-3′; Hippobio, China) under the same parameters. Transfected cells were immediately transferred to 2 % 1640 medium.

Western blot assay

To examine the effects of chT-bet knockdown on endogenous chT-bet expression, MSB1 cells were harvested 24 h post-transfection and then lysed with cell lysis solution (50 mM Tris-HCl (pH 7.4), 150 mM NaCl, 1 % Triton Ⅹ−100, 5 mM EDTA, 10 % glycerol, and protease inhibitor) for 30 min on ice. Cell lysates were then boiled with 6 × SDS loading buffer for 10 min and centrifuged at 12,000 g at 4°C, for 10 min. The denatured protein samples were separated by electrophoresis on SDS-PAGE gels, and resolved proteins were transferred to PVDF membranes. After blocking with 5 % skimmed milk for 2 h at room temperature, the membranes were incubated with indicated antibodies, followed by incubation with appropriate HRP-conjugated secondary antibodies. Blots were developed using an ECL substrate (Affinibody, China).

Flow cytometry

To examine the effects of chT-bet knockdown on cytokine expression, MSB1 cells were transfected with 50 pmol of siRNA (chT-bet RNAi or control RNAi). Twenty-four hours post-transfection, MSB1 cells were maintained in fresh 10 % 1640 medium for 1-2 h. Cells were subsequently treated with Golgi transport inhibitors Brefeldin A (00-4506; Thermo Fisher Scientific, USA) in the presence or absence of Cell Stimulation Cocktail (00-4970; Thermo Fisher Scientific, USA) for 4-6 h.

Intracellular Fixation Permeabilization Buffer Set (88-8824; Thermo Fisher Scientific, USA) was used for intracellular staining. After fixation and permeabilization, cells were stained with biotin-conjugated mAbs against chicken IFN-γ, chicken IL-2, and chicken IL-4, followed by incubation with APC-labeled streptavidin. Fluorescence signals were acquired on flow cytometry (FACS Calibur; BD, USA) and analyzed with FlowJo.

Dual-luciferase reporter gene assay

For promoter analysis, DF-1 cells were seeded on 24-well plates and cultured overnight, followed by transfection with firefly luciferase reporter gene plasmids (pGL3-IfngLuc, pGL3-Il2Luc (from 1 to 8) or pGL3-Il4Luc (from 1 to 5)) using jetPRIME (Polyplus, France). To normalize transfection efficiency, another Renilla luciferase reporter gene plasmid (pRL-TK) was added to each transfection as a control. Twenty-four hours post-transfection, cells were lysed, followed by examination with luciferase reporter gene assays using a dual-luciferase reporter assay system (Promega, USA) and luminometer (GloMax®20/20, Promega, USA). Each reporter gene assay was repeated at least three times. The primers used to construct these fusion plasmids are listed in Table 1.

For transcription factors analysis, firefly luciferase reporter gene plasmids (pGL3-IfngLuc, pGL3-Il2-6Luc or pGL3-Il4-4Luc), transcription factor expression plasmids (pRK5-Flag-chT-bet or pRK5-Flag) and Renilla luciferase reporter gene plasmids (pRL-TK) were co-transfected into DF-1 cells. Luciferase reporter gene assays were performed 24 h post-transfection as described above.

Chromatin immunoprecipitation (ChIP) assay

For ChIP assay, 5 × 107 MSB1 cells overexpressing pRK5-Flag-chT-bet or 5 × 107 splenic lymphocytes from mock-control chickens were stimulated with a cell stimulation cocktail for 4-6 hours 24 h post-transfection. The ChIP assay was performed according to the instructions of the Pierce Magnetic ChIP Kit (MAN0016150, Thermo Fisher Scientific, USA). Briefly, cells were cross-linked, collected, and lysed to obtain nuclei. DNA was digested with micrococcal nuclease and the nuclear membrane was further disrupted by sonication. For each ChIP reaction, 10 μg of Flag/chT-bet mAbs or control IgG antibody was added. The mixture was incubated overnight and then co-incubated with protein A/G beads at 4°C for immunoprecipitation. IP elution and DNA recovery were then performed. The recovered DNA was sent to the company for library construction and sequencing. Meanwhile, the enrichment of the DNA template was analyzed by qPCR. The primers used are listed in Table 2.

Statistical analysis

Data are presented as mean ± SD. Statistical analyses were performed using GraphPad Prism 9.5, employing Student′s t-test. In the figures, statistical significance is indicated as follows: ***, p < 0.001; **, p < 0.01; *, p < 0.05; ns, not significant.

Results

Phylogenetic and sequence analysis of chTbx21

Using the partial chicken Tbx21 sequence (GenBank: CB016768.1) as a reference, we assembled its complete coding sequence through NCBI SRA database mining. The full-length chTbx21 CDS (1611 bp encoding 536 aa) was successfully cloned from a White Leghorn spleen-derived cDNA library, matching our bioinformatic prediction. Phylogenetic analysis revealed species-specific variations in Tbx21 sequences, with chTbx21 clustering with avian homologs while maintaining evolutionary proximity to reptilian and mammalian counterparts (Figure 1A), consistent with established vertebrate relationships (Prum et al., 2015; Delsuc et al., 2018). Like mammalian T-bet, chT-bet contained a conserved T-box DNA-binding domain (Figure 1B). Multiple sequence alignments revealed that chT-bet displays 50.4 % and 51.1 % amino acid sequence identity with human and mouse orthologs, respectively (data not shown), while exhibiting remarkable evolutionary conservation in the T-box DNA-binding domain across vertebrates (Figure 1C). These analyses validate the accuracy of the chTbx21 sequence we cloned and suggest functional conservation of chT-bet with its mammalian orthologs.

Fig. 1.

Fig 1

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Phylogenetic and sequence analysis of chTbx21. (A) Phylogenetic tree of the coding regions of Tbx21 from different species. The Neighbor-Joining method with 1000 bootstrap replicates was used to construct the tree. Gene names and GenBank accession numbers are provided. The scale bar represents the nucleotide substitution rate per site. (B) Schematic illustration of chT-bet protein structure. The T-box domain is denoted by a pentagon. (C) Multiple sequence alignment of the T-box domain of T-bet homologs from different species. Amino acid conservation is color-shaded, the darker shades, the higher conservation levels (100 %, 80 %, and 60 % from dark orange to light yellow).

Profiles of chT-bet mRNA expressions in different tissues and its subcellular localization

To characterize chT-bet expression patterns, we analyzed its mRNA levels in the different tissues (spleen, thymus, bursa of Fabricius, heart, liver, kidney, lung, trachea, esophagus, crop, gizzard, proventriculus, duodenum, pancreas, jejunum, ileum, cecum, rectum, brain, and muscle) of two-week-old chickens by qPCR. As a result, chT-bet exhibited tissue-specific expression, with the highest levels in the spleen/thymus and minimal detection in the brain (Figure 2A). Subcellular localization of chT-bet was detected by transfection of DF-1 cells with EGFP-chT-bet. Compared to vector control, EGFP-chT-bet fusions existed exclusively in the nucleus of EGFP-chT-bet-transfected cells, indicating that chT-bet contains the nuclear localization signal peptide (Figure 2B).

Fig. 2.

Fig 2

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mRNA expression profiles of chT-bet in different tissues and its subcellular localization. (A) Quantitative RT-PCR analysis of chT-bet mRNA expression in different chicken tissues. Tissues were collected from the spleen, thymus, bursa of Fabricius, heart, liver, kidney, lung, trachea, esophagus, crop, gizzard, proventriculus, duodenum, pancreas, jejunum, ileum, cecum, rectum, brain, and muscle of two-week-old SPF chickens (n = 3). Gapdh was used as an internal control. The relative expression levels were calculated using the 2-ΔΔCt method and normalized to that of spleen tissue. Data represent mean ± SD from three independent experiments. ns, p > 0.05; *, p ≤ 0.05. (B) Subcellular localization of chT-bet-EGFP fusion protein in DF-1 cells. Cells were seeded in 24-well plates and transfected with pEGFP-N1 or pEGFP-N1-chT-bet plasmids (500 ng/well). Twenty-four hours after transfection, nuclei were stained with DAPI, and fluorescence was visualized using an inverted fluorescence microscope. Images were merged using ImageJ software. Scale bar = 20 μm.

NDV infection upregulated chT-bet expression in vitro and in vivo

To explore if chT-bet is involved in immune response to viral infection, we analyzed its expression during NDV infection. We cultured splenocytes from two-week-old SPF chickens, infected them with NDV Lasota at an MOI of 0.5, and examined the expression of chT-bet at mRNA and protein levels at different time points by qPCR and Western Blot assays respectively. As a result, the mRNA expression of chT-bet in splenocytes with NDV infection markedly increased compared to that of mock-infected controls 12 h post-infection (Figure 3A), so did the protein expression of chT-bet in NDV-infected splenocytes 24 and 36 h post-infection (Figure 3B&C). Furthermore, we infected two-week-old SPF chickens with 106 EID50 of NDV Lasota and examined chT-bet expressions in different tissues (the bursa of Fabricius, spleen, and thymus) of these chickens by immunohistochemistry (IHC). Our data show that NDV-infected chickens exhibited visible expansions of nuclear-localized chT-bet+ cells in immune organs 3 days post-infection, particularly in the bursa of Fabricius (Figure 3D). This response was transient, returning to baseline by day 7 (Figure 3D). These results demonstrate the involvement of chT-bet in immune response to NDV infection, and reveal unique tissue-specific amplification in chickens, suggesting conserved yet adapted roles for chT-bet in antiviral immunity.

Fig. 3.

Fig 3

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NDV infection upregulated chT-bet expression both in vitro and in vivo. (A) mRNA expression of chT-bet increased in NDV-infected lymphocytes. Splenic lymphocytes were mock-infected or infected with NDV (MOI = 0.5). Total RNA was extracted at different time points (6, 12, and 24 h post-infection) and subjected to qRT-PCR analysis. GAPDH served as an internal control for normalization. Data represent mean ± SD from three independent experiments. *, p ≤ 0.05. (B & C) Protein expression of chT-bet increased in NDV-infected lymphocytes. Cells were infected as described in (A). Cell lysates were prepared at 12, 24, and 36 h post-infection and analyzed by Western Blot using specific antibodies against chT-bet, NDV Fusion protein, and GAPDH. Endogenous GAPDH expression was used as an internal control. The band intensities for chT-bet in (B) were quantitated by densitometry as shown in (C). Data represent mean ± SD from three independent experiments. **, p ≤ 0.01; ns, p > 0.05. (D) Immunohistochemical analysis of chT-bet expression in chicken organs after NDV infection. Black arrows indicate typical chT-bet positive cells. Three and seven days post-infection, bursa, spleen, and thymus tissues were prepared for immunohistochemical staining using chT-bet polyclonal antiserum. Scale bar = 30 μm. (E) Quantitative analysis of chT-bet expression in tissues performed using ImageJ. Data represent mean ± SD from three independent microscopic fields. **, p ≤ 0.01; ***, p ≤ 0.001.

Knockdown of chT-bet by RNAi differentially affected cytokine expression in MSB1 cells

In mammals, T-bet regulates Th1 cytokine expression while suppressing Th2 cell immune response (Lugo-Villarino et al., 2003; Djuretic et al., 2007; Kanhere et al., 2012). To determine the regulatory effects of chT-bet on Th1/Th2 cytokines, we knocked down chT-bet expression in MSB1 cells by RNAi (Figure 4A&B) and analyzed the expression of IFN-γ, IL-2, and IL-4 in PMA-stimulated cells. As a result, knockdown of chT-bet significantly reduced IFN-γ and IL-2 mRNA expression in MSB1 cells compared to that of RNAi controls (p < 0.001)(Fig. 4C&D), while IL-4 mRNA expression relatively increased (Fig. 4E). Furthermore, we examined the expression of IFN-γ, IL-2 and IL-4 in chT-bet knockdown cells with flow cytometry by intracellular staining. After gating viable MSB1 cells (Fig. 5A), the expression of IFN-γ, IL-2 and IL-4 in these cells were analyzed by flow cytometry (Fig. 5B-H), and the results show that knockdown of chT-bet markedly reduced IFN-γ expression in cells post PMA-Ionomycin stimulation (Fig. 5C&D). Interestingly, IL-2 expression increased (Fig. 5E&F), and IL-4 protein remained unaffected (Fig. 5G&H). These findings suggest that chT-bet plays a dual role in regulating Th1 cytokine expression in chickens.

Fig. 4.

Fig 4

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knockdown of chT-bet by RNAi inhibited the transcription of Ifng and Il2 in MSB1 cells. (A&B) Effects of chT-bet knockdown on endogenous chT-bet expression in MSB1 cells. Cells were transfected with 50 pmol of siRNA (chT-bet RNAi or control RNAi). Twenty-four hours post-transfection, cytosolic proteins were analyzed by Western Blot using anti-chT-bet and anti-GAPDH antibodies. Endogenous GAPDH expression was used as an internal control. The band intensities for chT-bet in (A) were quantitated by densitometry as shown in (B). (C-E) Effects of chT-bet knockdown on cytokine expression at an mRNA level. MSB1 cells were treated as described in (A). Twenty-four hours post-transfection, cells were maintained in fresh 2 % 1640 medium for 1-2 h, followed by stimulation with a cell stimulation cocktail (containing PMA and ionomycin) for 4-6 hours. mRNA expression levels of IFN-γ (C), IL-2 (D), and IL-4 (E) were quantified by qRT-PCR using gene-specific primers. Gapdh was used as an internal control. Data represent mean ± SD from three independent experiments. ***, p < 0.001; **, p < 0.01; *, p < 0.05.

Fig. 5.

Fig 5

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knockdown of chT-bet inhibited the expression of IFN-γ but promoted the expression of IL-2 and IL-4 in MSB1 cells. MSB1 Cells were transfected with siRNA (chT-bet RNAi or control RNAi) as described in Fig. 4. Twenty-four hours post-transfection, cells were maintained in fresh 10 % 1640 medium for 1-2 h, followed by stimulation with PMA and ionomycin in the presence or absence of Brefeldin A for 4-6 h. Intracellular cytokine staining was performed to detect IFN-γ, IL-2, and IL-4 expressions in cells using flow cytometry. (A) Viable MSB1 cells were gated for further analysis. (B) Antibody isotype staining was used as nonspecific staining controls. Cells were stained with isotype-matched IgG for nonspecific staining controls. (C—H) Examination of IFN-γ, IL-2 and IL-4 positive cells by flow cytometry via intracellular staining. Flow cytometry contour plots of IFN-γ+ cells were shown in (C), and the bar graph for percentage of IFN-γ+ cells in (C) were shown in (D). Flow cytometry contour plots of IL-2+cells were shown in (E), and the percentage IFN-γ+ cells in (E) were shown in (F). Flow cytometry contour plots of IL-4+cells were shown in (G), and the percentage IFN-γ+ cells in (G) were shown in (H). Data represent mean ± SD from three independent experiments. **, p ≤ 0.01; ns, p > 0.05.

chT-bet overexpression regulated cytokine promoter activity

It was reported that in mammals, T-bet directly regulates IFN-γ expression through promoter binding while indirectly suppressing IL-2 and IL-4(Lugo-Villarino et al., 2003; Hwang et al., 2005a; Djuretic et al., 2007). Thus, we set out to determine the effect of chT-bet overexpression on activation of cytokine promoter to explore the mechanisms of regulating cytokine expression by chT-bet. We first analyzed genomic architectures of Ifng, Il2, and Il4 using UCSC data (Fig. 6A), and found that chicken Ifng gene contains 4 exons with a 116 bp upstream of the non-coding region, Il2 comprises 5 exons preceded by a 7677 bp non-coding sequence, and Il4 features 6 exons flanked by 2967 bp upstream region. To identify functional promoter regions, we made a series of truncated constructs as indicated, and performed luciferase reporter gene assays in DF-1 cells. As shown in Fig. 6B-D, the luciferase activity of pGL3-IfngLuc, pGL3-Il2-6Luc, and pGL3-Il4-4Luc significantly increased compared to that of controls, indicating that Ifng, Il2 and Il4 promoters were located in the −2000∼+80, −8095∼−6155 and −4869∼−2792 regions respectively.

Fig. 6.

Fig 6

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chT-bet promoted the activity of the Ifng promoter, but inhibited Il2 and Il4 promoter activation in DF-1 cells. (A) Genomic organization of chicken Ifng, Il2, and Il4 genes and predicted chT-bet binding sites in their promoter regions. Binding site predictions were performed using the JASPAR database. Schematic illustration shows gene structures: Black lines represent introns, gray boxes indicate exons, red squares denote coding regions, and ovals indicate the predicted binding positions of T-bet. (B-D) Identification of the promoters of Ifng, Il2 and Il4. DF-1 cells were co-transfected with 500 ng of pGL3-Ifng-Luc (B), pGL3-Il2-Luc (C), or pGL3-Il4-Luc (D) together with 20 ng of pRL-TK as an internal control. Cell lysates were prepared 24 h post-transfection, and luciferase reporter gene assays were performed. (E-G) Effect of chT-bet overexpression on promoter activation of Ifng, Il2 and Il4. DF-1 cells were co-transfected with pGL3-Ifng-Luc (E), pGL3-Il2-Luc (F), or pGL3-Il4-Luc (G) together with either pRK5-Flag-chT-bet or empty pRK5-Flag vector. pRL-TK plasmid was added to each transfection as a control. Cell lysates were prepared 24 h post-transfection, and luciferase reporter gene assays were performed. Data represent mean ± SD from three independent experiments. **, p ≤ 0.01; *, p ≤ 0.05.

Since we determined the promoter region of Ifng, Il2, and Il4, we utilized the JASPAR databases to predict the potential transcription factor binding sites (TFBS) in the promoter regions of Ifng, Il2, and Il4, and found that there were seven T-bet binding sites in Il2's promoter, one in Il4's promoter, and a conserved intronic site (+553∼+563) in Ifng as indicated in Fig. 6A. Thus, we made pRK5-Flag-chT-bet construct, transfected DF-1 cells with the plasmid together with pGL3-IfngLuc/pGL3-Il2-6Luc/pGL3-Il4-4Luc, and performed luciferase reporter gene assays 24 h post-transfection. As shown in Fig. 6E-G, overexpression of chT-bet enhanced Ifng promoter activity by 1.3-fold while suppressing Il2 and Il4 promoter activity by 32 % and 26 %, respectively. These data show that chT-bet mainly activates Ifng promoter.

chT-bet bound to the promoters of Ifng and Il2 directly

As transfection of cells with pRK5-Flag-chT-bet affecte supported d cytokine expression and promoter activity, we next determined if chT-bet bound to cytokine promoter by ChIP assays. The expression level of chT-bet in pRK5-Flag-chT-bet transfected cells was comparable to that of endogenous PMA-stimulated chT-bet (Fig. 7A&B), ensuring the physiological relevance of ChIP data from pRK5-Flag-chT-bet transfected models. Approximately 15 % of genome-wide chT-bet binding events localized to promoter/TSS regions (Fig. 7C), consistent with the binding characteristics of transcriptional regulators. Our data show that ChIP-seq identified multiple chT-bet binding events at the Ifng and Il2 loci (Fig. 7D). Interestingly, despite computational predictions favoring the Ifng intronic region, an empirical enrichment peak was observed in its promoter (Fig. 7D). ChIP-qPCR confirmed significant chT-bet binding at Ifng promoter (1.3-fold), Ifng intron (3.0-fold), and Il2 promoter (3.6-fold), but not at Il4 promoter (Fig. 7E), indicating the direct binding of chT-bet to Ifng and Il2 promoters. To investigate the binding pattern of chT-bet on a genome-wide scale, we performed a de novo analysis using the Homer tool and identified a predominant motif (38.12 % frequency) matching mammalian T-bet's binding specificity (Fig. 7F), and the Subsequent motifs included JunB (14.76 %), DIG1 (24.3 %), IGF2BP3 (20.18 %), and ttk (0.26 %) (Fig. 7F), indicating shared DNA-binding specificity and potential cooperative/competitive regulatory interactions with chT-bet. While sharing identical core T-box sequences with mammals (5′-AAGGTGTGAA-3′), chT-bet exhibited greater flanking region variability (Fig. 7G&H). Meanwhile, using known motif analysis, we identified significant motif matches including T-box family factors (Tbx5/6, Tbr1, Eomes) and bZIP family members (JunB, Atf3, Fra1, BATF) (Fig. 7I), suggesting potential regulatory interactions.

Fig. 7.

Fig 7

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Binding of chT-bet to Ifng and Il2 promoters. (A&B) The ectopic expression level of chT-bet by transfection was comparable to that of PMA-stimulated expression of chT-bet. MSB1 cells were either transfected with 50 pmol pRK5-Flag-chT-bet or stimulated with PMA. Cell lysates were prepared 24 h post-transfection or 6 h post-stimulation with PMA, and examined with Western Blot analysis using anti-chT-bet and anti-GAPDH antibodies. GAPDH served as an internal control. The band intensities for chT-bet in (A) were quantitated by densitometry as shown in (B). Data are presented as mean ± SD from three independent experiments. ns, p > 0.05. (C) Annotation of binding events across different genomic features, including promoters, exons, introns, and intergenic regions. (D) ChIP-seq enrichment profiles of Flag-tagged chT-bet across Ifng, Il2, and Il4 genomic loci. Light-yellow boxes indicate regions analyzed by ChIP-qPCR, centered on predicted T-bet binding motifs or enrichment peaks. Scale bar = 1 kb. (E) Quantitative analysis of Flag-chT-bet binding to Ifng, Il2, and Il4 promoters by ChIP-qPCR. Data represent mean ± SD from three independent experiments. (F) De novo motif analysis of top five enriched transcription factor binding motifs in MSB1 cells. (G) Position weight matrix of the chicken T-bet binding motif. (H) Position weight matrix of the human T-bet binding motif, obtained from the JASPAR database. (I) Known motif analysis of top ten enriched transcription factor binding motifs in MSB1 cells. (J) ChIP-seq enrichment profiles of endogenous chT-bet across Ifng, Il2, and Il4 genomic loci. Light-yellow boxes indicate regions analyzed by ChIP-qPCR, centered on predicted T-bet binding motifs or enrichment peaks. Scale bar = 1 kb. (K) Quantitative analysis of endogenous chT-bet binding to Ifng, Il2, and Il4 promoters by ChIP-qPCR. Data represent mean ± SD from three independent experiments. ***, p < 0.001; **, p < 0.01; *, p < 0.05; ns, p > 0.05.

For further validation, we also performed ChIP on PBMCs using specific anti-chT-bet mAbs. Similarly, the results of ChIP assay showed 5.8/9.8-fold and 3.4-fold enrichments at the Ifng and Il2 loci respectively, versus 2.7-fold at the Il4 locus (Fig. 7J&K). These results demonstrate chT-bet's selective binding to Ifng and Il2 regulatory elements for transcriptional regulation of target gene expression.

Discussion

T-bet, encoded by the Tbx21 gene, is widely recognized as the master regulator of Th1 immune responses(Afkarian et al., 2002; Lazarevic et al., 2013). In mammals, T-bet plays a critical immunoregulatory role in host defense against intracellular pathogens, autoimmune diseases, and cancer, and drives antiviral immunity by inducing Th1-related cytokines such as IFN-γ and TNF-α(Sullivan et al., 2005; Nath et al., 2006; Kao et al., 2011; Saeidi et al., 2018). Although the role T-bet in mammalian immunity is well-established, its function in avian species remains poorly understood. This study provides the first comprehensive characterization of chT-bet and determined its role in regulating Th1 immune response. Our findings reveal the conserved features of chT-bet that share with mammalian T-bet, highlighting its unique mechanism of regulating immune response and reflecting the evolutionary adaptations of avian immune system.

In this study, we first demonstrate that chT-bet clusters phylogenetically with avian species and shares a conserved T-box domain with mammals, supporting its sequence fidelity and functional conservation across vertebrates. Second, our data reveal that NDV infection significantly upregulated chT-bet expression both in vitro and in vivo, suggesting its involvement in antiviral Th1 immune responses. Third, tissue expression profiling and subcellular localization analysis showed that chT-bet was predominantly expressed in immune-related organs (e.g., spleen and thymus) and localized to the nucleus, aligning with its canonical function as a transcriptional regulator. Fourth, the knockdown of chT-bet in MSB1 cells markedly reduced IFN-γ production but enhanced IL-4 levels, indicating its regulatory effects on the Th1/Th2 cytokine balance. Interestingly, while IL-2 mRNA levels decreased upon chT-bet knockdown, its protein levels increased. Fifth, chT-bet overexpression enhanced activation of Ifng promoter but suppressing Il2 and Il4 promoter activity, suggesting its direct transcriptional regulation of these cytokines. Finally, ChIP assays confirmed the direct binding of chT-bet to Ifng and Il2 promoters, with motif analysis revealing conserved DNA-binding specificity akin to mammalian T-bet, while its regulation of Il4 might be in an indirect way. These findings establish chT-bet as a critical regulator of Th1 immunity in chickens, orchestrating IFN-γ induction and modulating IL-2/IL-4 expression through distinct modes. To our knowledge, this is the first comprehensive study delineating T-bet′s role in avian species, uncovering both conserved and species-specific regulatory features in immune response modulation.

Phylogenetic analysis revealed that chTbx21 clustered within an avian-specific clade, maintaining closer evolutionary proximity to reptilian and mammalian Tbx21 homologs while showing distinct divergence from amphibian and piscine lineages (Fig. 1A). This evolutionary pattern aligns with the conserved trajectory of immune regulatory factors across vertebrates(Evans, 2009; Prum et al., 2015). The phylogenetic conservation of the T-box domain across species, from teleosts to mammals, underscores its fundamental role in DNA binding and transcriptional regulation(Stirnimann et al., 2010). Notably, chT-bet displays a unique tissue-specific expression profile, with high mRNA levels in the pancreas but undetectable protein (data not shown), suggesting avian-specific post-transcriptional regulation. Similar phenomena have been reported in chicken Foxp3 and cGas genes(Chang et al., 2022; Jiao et al., 2023), implying potential non-canonical immune functions in the avian pancreas. Mammalian studies reveal that miR-29 suppresses T-bet translation by targeting its 3′UTR(Amirian et al., 2023) while RNA-binding proteins like HuR stabilize T-bet mRNA to promote Th1 differentiation(Chen et al., 2020). Further investigations should explore whether similar post-transcriptional regulatory mechanisms exist in chickens.

Our data show that NDV infection significantly upregulated chT-bet expression in splenic lymphocytes and tissues (Fig. 3), which is consistent with its mammalian role in driving IFN-γ production against intracellular pathogens(Sullivan et al., 2005; Lazarevic et al., 2013). Intriguingly, remarkably elevated expression of chT-bet was observed in the bursa of Fabricius, a primary site for avian B-cell development and maturation (Cooper et al., 1965), contrasting with a relatively low expression of chT-bet in the spleen and thymus of NDV infected chicken. This parallels IBDV-induced upregulation of GATA3 and ETV6 in the bursa(Li et al., 2022; Zhang et al., 2024), suggesting microenvironmental modulation of immune regulators in this organ. Interestingly, unlike IBDV, the target organ of NDV is not the bursa of Fabricius (Hussein et al., 2019). It was found that in mammal, certain B cell subsets (such as regulatory B cells or effector B cells) express T-bet and actively modulate Th1 immune responses during chronic infection or inflammation(Knox, 2017), raising questions about analogous functions in avian B cells. These observations highlight the bursa′s potential as a hub for immune regulation, arousing interest in further exploration of avian B-cell plasticity. chT-bet knockdown robustly suppressed IFN-γ while augmenting IL-4 expression (Fig. 4), recapitulating its evolutionarily conserved role as a Th1-polarizing master regulator(Afkarian et al., 2002; Djuretic et al., 2007; Tripathi and Lahesmaa, 2014). However, the discordant IL-2 regulation—reduced mRNA but elevated protein—reveals avian-specific regulatory complexity. The discordance between IL-2 transcript and protein levels in chickens may arise from either technical constraint inherent to the cell model used in this study or the evolutionary adaptations of chicken immune regulation, particularly given the remarkably extended architecture of the chicken Il2 locus. The 5′ non-coding region of chicken Il2 spans 7677 bp, contrasting sharply with its mammalian counterparts (285 bp in human(Durand et al., 1988), 48 bp in house mouse(Lyon et al., 1979)), suggesting potential evolutionary divergence in transcriptional regulation. Mechanistically, while mammalian T-bet indirectly suppresses IL-2 through inhibiting RelA activity (an activator of IL-2)(Hwang et al., 2005a), our ChIP assays demonstrated direct binding of chT-bet to the Il2 promoter (Fig. 7), revealing a phylogenetically distinct repression mechanism. Comparative proteomic and RNA stability analyses are required to dissect this paradox, which may reflect evolutionary adaptations balancing cytokine expressions in avian immunity.

Although endogenous ChIP-qPCR detected a 2.7-fold enrichment of chT-bet at the Il4 promoter region, complementary experimental evidence did not support this observation, including exogenous ChIP-qPCR using Flag-tagged chT-bet (revealing no binding), and genome-wide ChIP-seq visualization (lacking peaks at the Il4 promoter region). This apparent signal likely reflects antibody cross-reactivity with chromatin-associated proteins. Analogous to mammalian systems(Li et al., 2022; Zhang et al., 2024), chT-bet may indirectly suppress IL-4 via GATA3 competition or epigenetic silencing or mechanisms unkonwn.

By de novo motif analysis, we identified a core chT-bet binding sequence (AAGGTGTGAA), which mirrors the mammalian T-bet motifs (AAGGTGTGAA)(Jolma et al., 2013). However, the flanking nucleotides exhibited striking lineage-specific degeneracy (Fig. 7G&H), suggesting that chT-bet has evolved enhanced motif plasticity while retaining ancestral core recognition. This structural divergence likely enables suboptimal site binding, explaining the low but reproducible chT-bet-dependent Ifng promoter activation (1.3-fold, p < 0.05, Fig. 6E), as well as the binding of chT-bet to the Ifng promoter region in ChIP assays (Fig. 7E&K), despite the absence of predicted canonical motifs. Strikingly, ChIP-qPCR revealed a dominant 9.8-fold enrichment of chT-bet at the first intron (Fig. 7G), where functional T-box-like motifs are located, indicating a hierarchical regulatory architecture. The coexistence of weak promoter engagement and intronic enhancer dominance may reflect an evolutionary adaptation to decouple basal IFN-γ priming (via low-affinity promoter interactions) from robust pathogen-inducible responses (via high-affinity intronic hubs). This mechanism is evolutionarily conserved across species. For instance, the drosophila Drosomycin gene relies on low-affinity STAT binding to its promoter under resting conditions, whereas pathogen infection triggers intronic enhancers to recruit high-density STAT complexes via chromatin looping, enabling rapid induction of antimicrobial peptides(Charroux and Royet, 2010). Similarly, mammalian IFN-β and IL-4 exhibit analogous regulatory mechanisms for inducible expression(Lee et al., 2003; Panne et al., 2007).

In this study, de novo motif analysis revealed JunB and BATF as potential chT-bet co-regulators. While direct interactions remain to be proven, functional antagonism is suggested by mammalian paradigms: BATF/JunB complex drives Th17 differentiation(Vierbuchen et al., 2017), whereas T-bet suppresses Th17 via RORγt inhibition, indicating the antagonism between T-bet and BATF/JunB. Notably, the co-enrichment of T-box family motifs (Tbx5, Tbx6, Tbr1, Eomes) in known motif analysis recapitulates conserved cooperative mechanisms observed across vertebrates, exemplified by the T-bet/Eomes synergy that amplifies IFN-γ production in cytotoxic T lymphocytes(Gordon et al., 2012; Kaech and Cui, 2012). Concurrently, overlaps with bZIP (JunB, Atf3, Fra1, BATF) further increase the possibility that chicken T-bet may play a role in synergy or antagonism with JunB and BATF. These findings underscore both conserved and lineage-specific features of T-bet-dependent immune regulation. Chromatin conformation capture assays coupled with CRISPR-mediated multiplex gene editing will be needed to elucidate these evolutionary trajectories.

In summary, in this study, we cloned and identified chicken T-bet, demonstrating its pivotal regulatory role in chicken Th1 immune responses. Importantly, we found that chT-bet directly binds to the promoters of Ifng and Il2 to enhance IFN-γ production and modulate IL-2 expression, while suppressing IL-4 through indirect mechanisms. These findings advance our understanding of avian immune regulation and provide insights into potential strategies for enhancing antiviral responses in poultry.

Disclosures

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

Acknowledgments

We thank Drs. Nianzhi Zhang and Jinhua Liu for their assistance.

This work was supported by the National Key Research and Development Program of China (2022YFD1800300) and the earmarked fund for CARS-40, China.

The founding sponsors had no role in the design of the study, in the collection, analyses, or interpretation of data, in the writing of the manuscript, and in the decision to publish the results.

Footnotes

Scientific Section: Immunology, Health and Disease.

Contributor Information

Yongqiang Wang, Email: vetwyq@cau.edu.cn.

Shijun J. Zheng, Email: sjzheng@cau.edu.cn.

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