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. 2024 Apr 5;103(6):103741. doi: 10.1016/j.psj.2024.103741

Differential innate immune responses to fowl adenovirus serotype 4 infection in Leghorn male hepatocellular and chicken embryo fibroblast cells

Xiaolan Hou ⁎,1, Lizhen Wang ⁎,1, Riteng Zhang ⁎, Gen Liu †, Ting Wang ⁎, Bo Wen ⁎, Wenchi Chang ⁎, Shuizhong Han ⁎, Jinjie Han ⁎, Junyang Fang ⁎, Xuefeng Qi ⁎, Jingyu Wang ⁎,2
PMCID: PMC11066554  PMID: 38670055

Abstract

Fowl adenovirus serotype 4 (FAdV-4) infections result in substantial economic losses in the poultry industry. Recent findings have revealed that FAdV-4 significantly suppresses the host immune response upon infection; however, the specific viral and host factors contributing to this immunomodulatory activity remain poorly characterized. Moreover, diverse cell types exhibit differential immune responses to FAdV-4 infection. To elucidate cell-specific host responses, we performed transcriptomic analysis of FAdV-4 infected leghorn male hepatocellular (LMH) and chicken embryo fibroblast (CEF) cells. Although FAdV-4 replicated more efficiently in LMH cells, it provoked limited interferon-stimulated gene induction. In contrast, FAdV-4 infection triggered robust antiviral responses in CEF cells, including upregulation of cytosolic DNA sensing and interferon-stimulated genes. Knockdown of key cytosolic DNA sensing molecules enhanced FAdV-4 replication in LMH cells while reducing interferon-stimulated gene expression. Our findings reveal cell-specific virus-host interactions that provide insight into FAdV-4 pathogenesis while identifying factors that mediate antiviral immunity against FAdV-4.

Key words: FAdV-4, LMH cells, CEF cells, transcriptomics, cytokines

INTRODUCTION

As the major pathogen of hepatitis-hydropericardium syndrome (HHS), FAdV-4 is highly transmissible and pathogenic in flocks. The poultry sector has suffered enormous economic damage since HHS emerged in China in 2015 (Wang et al., 2019; Chandra et al., 2000). The FAdV-4 virion contains a 45-kilobase pair linear, double-helical DNA genome, which codes for 11 structural polypeptides along with 32 nonstructural polypeptides. The external viral capsid is composed of 3 key structural proteins: hexon, fiber, and penton base (Wang and Zhao, 2019). The increased virulence of FAdV-4 may be caused by the mutated fiber 2 and hexon (Zhang et al., 2018b). Infection with FAdV-4 causes hepatic coloring, hepatomegaly, fragility, and localized necrosis (Vera-Hernandez et al., 2016). FAdV-4 can be extracted from liver homogenates of chickens that have been infected (Pan, et al., 2017). Furthermore, FAdV-4 can propagate in LMH cell lines, primary chicken kidney cells, chicken embryo liver cells, chicken embryo fibroblasts, and quail fibroblast (QT-35) cells (Li et al., 2017). Previous research has demonstrated that hypervirulent FAdV-4 infection results in necrosis and severe reduction of lymphocytes in the spleen, as well as a decline in the thymus's CD4 and CD8 T-lymphocyte counts (Schonewille et al., 2008; Liu et al., 2016). These findings suggest that the hypervirulent FAdV-4 infection has a significant inhibitory effect on the immune response. However, the molecular mechanisms underlying the immunosuppressive properties of this FAdV-4 strain remain uncharacterized.

High-throughput transcriptomics, a key bioinformatics tool in the postgenomic age, has been extensively used in functional genomic research, measurement of the levels of gene expression, and detection of the transcriptional structures of genes (Stark et al., 2019). Previous transcriptome analyses have determined gene expression profiles in adenovirus-infected cancer and non-cancerous cell lines, including HeLa cells and primary human lung fibroblasts infected with adenovirus serotype 2 (Zhao et al., 2003; Granberg et al., 2005; Zhao et al., 2007; Zhao et al., 2012). Researchers have also uncovered expression profiles in adenovirus serotype 5-infected human melanoma cells and primary mouse embryo fibroblasts (Volk et al., 2005; Hartman et al., 2007; Dorer et al., 2011). Transcriptomics is also commonly used in the detection of gene expression changes in chickens that survived or died and LMH cells after FAdV-4 infection, which helps to refine the virus-host interaction network (Zhang et al., 2018a; Ren et al., 2019; Chen et al., 2020). FAdV-4 molecular pathogenesis has just recently been investigated. Several time-series investigations have shown that FAdV-4 infection of the LMH cell line has implicated the TLR and MAPK signaling pathways (Zhang, et al., 2018a). Transcriptome changes in chicken liver caused by FAdV-4 infection at 7, 14, and 21 d showed that viral replication and proliferation were accompanied by modifications to the host lipid metabolism and innate immune response (Ren et al., 2019).

As the first line of defense protecting against foreign invaders, the innate immune system acts quickly to identify and destroy pathogens that enter the host body. Robust innate immune responses can prevent virus replication and contain its dissemination. Viruses, on the other hand, have evolved a variety of mechanisms to control cell death and suppress the host's antiviral response. As a result, it is critical to comprehend the interaction between the host and FAdV-4 (Zhao et al., 2020). Yin et al. reported that infection with FAdV-4 upregulated the expression of gga-miR-181a-5p in LMH cells, negatively regulating sting-mediated type I IFN production and ultimately promoting viral replication (Yin et al., 2021). Li et al. demonstrated that FAdV-4 replicates more efficiently in CEF cells compared to DEF cells. They also showed that mRNA expression of interleukin-6 (IL-6), interleukin-8 (IL-8), Mx, and OAS was significantly increased in CEF cells infected with FAdV-4 versus the levels in infected DEFs (Li et al., 2018). These previous data indicated the immune responses to FAdV-4 infection vary in different cells. However, the host transcriptome status during the proliferation phase of FAdV-4 infection and the difference in response after infection with cancer cell lines or non-cancerous cell lines are currently unclear. Fibroblast cells are widely distributed in various tissues and organs of animals and actively participate in innate and adaptive immune defense (Davidson et al., 2021; Cavagnero and Gallo, 2022). Furthermore, research has also shown that multiple immune cytokines are upregulated in FAdV-4-infected CEF cells (Li et al., 2018), indicating that CEF cells have generated robust antiviral responses. Therefore, CEF cells can be used as a cell model to elucidate the immune mechanisms triggered by FAdV-4 infection. In this study, Illumina NovaSeq 6000 sequencing was used to analyze the genome-wide transcriptome profile mRNA in LMH and CEF cells during the FAdV-4 proliferation stage (48 hpi, 72 hpi). The findings may provide crucial information for the fundamental investigation of the pathophysiology of FAdV-4 as well as fresh perspectives on the prevention of HHS.

MATERIALS AND METHODS

Viruses, Cells, and Antibodies

The LMH cells utilized in this research were kindly supplied by Professor Yunfeng Wang of the Harbin Veterinary Research Institute in Heilongjiang, China. LMH cells were cultured in Dulbecco's Modified Eagle Medium (DMEM) supplemented with 10% fetal bovine serum, 100 U/mL penicillin, and 100 μg/mL streptomycin at 37°C with 5% CO2. CEF cells were prepared from 9-day-old chicken embryos and cultured in DMEM supplemented with 10% FBS and penicillin/streptomycin. The FAdV-4 strain SX17 (GenBank: MF592716.1) was previously isolated and stocked in our laboratory. A rabbit polyclonal antibody against the FAdV-4 hexon protein was produced in our laboratory. Goat anti-rabbit IgG H&L secondary antibody and anti-α-tubulin were purchased from Proteintech (Wuhan, China).

Samples Preparation and RNA Extraction

LMH cells were seeded at 1.5×106 cells per well in 6-well plates and infected with FAdV-4 at a multiplicity of infection (MOI) of 1. After incubation for 2 h to permit virus adherence, the cells were washed twice with PBS to eliminate the unattached virus, and new DMEM media was supplemented. TRIzol biochemical (Takara, Japan) was utilized to obtain total RNA at the preestablished intervals (48 and 72 hpi) per the producer's guidelines.

Library Construction and RNA Sequencing

The NEBNext Ultra II RNA Library Prep Kit for Illumina was used to create the cDNA libraries in accordance with the accepted Illumina methodology. Using the RNA Nano 6000 Assay Kit and the Bioanalyzer 2100 system (Agilent Technologies, Santa Clara, CA), the total amount and integrity of RNA were calculated. Sample mRNA was purified using magnetic beads and oligo(dT), and then it was broken up into tiny pieces using the fragment buffer. First-strand cDNA was produced using random hexamer-induced reverse transcription, then second-strand cDNA synthesis was performed. To finish the repair process, the A-tailing mixture and RNA Index Adapters were introduced. Illumina NovaSeq 6000 was used to sequence the resultant cDNA library, producing 150bp paired-end reads. The study's raw data has been uploaded to NCBI under the accession number PRJNA1060326.

Data Processing and DEGs Analysis

The raw sequencing image files generated on the Illumina HiSeq platform were transformed into fastq format files containing the raw read sequences via CASAVA base calling. These raw fastq data were analyzed using in-house Perl scripts to remove reads containing adapters, poly-N sequences, and low-quality reads, resulting in clean read data used for downstream analysis. The cleaned reads were mapped to the Gallus gallus reference genome (accession GCF_016699485.2) using Hisat2 to determine their genomic location and characterize sample-specific sequences. To quantify gene expression levels, Fragments Per Kilobase of transcript per Million fragments mapped (FPKM) values were utilized. Differential expression analysis between experimental conditions was conducted by employing the DESeq2 R package (version 1.26.0), which utilizes a negative binomial distribution statistical model. The resulting p-values from this analysis were corrected by the Benjamini-Hochberg method to control for the false discovery rate. Genes were identified as statistically significantly differentially expressed if they met thresholds of FDR < 0.05 and absolute log2 fold change greater than or equal to 1.

Functional Annotation Analysis

Gene set enrichment analysis (GSEA) can be used to perform enrichment analysis of all genes based on their expression levels. Standard differential expression analysis focuses only on strongly up or down-regulated genes, overlooking genes without significant differential expression yet still possessing major biological relevance. However, GSEA identifies more subtle but consistent gene expression trends without imposing thresholds for calling differential expression. The KEGG pathway and the gene sets of the GO branches BP, CC, and MF are the gene sets of interest in this experiment's GSEA analysis. The gene set enrichment analysis used log2 fold changes for each comparison as the input gene set scores. GO enrichment analysis of DEGs was performed using the Wallenius noncentral hyper-geometric distribution-based GOseq R tools (Young et al., 2010). KEGG pathway enrichment analysis of differentially expressed genes was performed with the KOBAS software (Mao et al., 2005). The Cytoscape software and EnrichmentMap plugin are visualized to visualize GSEA results as a network diagram. Parameters used for network generation: P-value < 0.05, edge similarity > 0.2 using a Jaccard+overlap combined matrix (50% weight). The resulting edge and node information was exported to edge.csv and node.csv files for each edge and node. The AutoAnnotate Cytoscape plugin was then applied for pathway clustering using the Markov Clustering Algorithm (MCL) and automatic annotation by WordCloud to generate topic names for each cluster (Reimand et al., 2019)

Quantitative Real-Time PCR

Viral DNA was extracted using EasyPure DNA kits (TIANGEN) following the manufacturer's protocol. Viral copy number was determined by utilizing the laboratory-established standard curve. The standard curve equation was: y = –2.8454x + 34.563 with R2 = 0.9894 (Li, 2019). Total RNA extraction from LMH cells used TRIzol reagent (Takara), following the kit's manufacturer's guidelines. The extracted RNA was reverse transcribed into cDNA using M-MLV reverse transcriptase (TransGen Biotech), following the kit's protocol. qRT-PCR used an iQ5 qRT-PCR system (Bio-Rad) and a SYBR Green master mix (TransGen Biotech), following their respective manufacturer's protocols. The PCR cycling conditions consisted of 40 cycles of 15 s at 94°C and 45 s at 60°C, separated by 2 min at 95°C. Target mRNA expression levels were normalized to the internal GAPDH control in each sample using the 2−ΔΔCt method. Primer sequences are listed in Supplementary Table 1.

Western Blot Analysis

Protein samples were lysed in 5×SDS-PAGE buffer and boiled for 10 min. Proteins were separated on 10% SDS-PAGE gels and transferred onto nitrocellulose membranes. Membranes were blocked with 10% non-fat milk for 1 h, then probed with primary antibodies overnight at 4°C. After washing with TBST, membranes were incubated with HRP-conjugated goat anti-rabbit or anti-mouse secondary antibodies for 45 min at room temperature. Protein bands were detected using enhanced chemiluminescence reagent.

RNA Interference and Transient Transfection

LMH cells were seeded at 1.2×106 cells/well in 6-well plates and cultivated overnight. At 60 to 70% confluence, cells were transfected with the indicated siRNAs using TurboFect (Thermo Fisher, Waltham, MA) following the manufacturer's protocol. Sequences of siRNAs used are listed in Supplementary Table 2.

RESULTS

Leghorn Male Hepatocyte Cells and Chicken Embryo Fibroblasts are Permissive to Fowl Adenovirus Serotype 4 Infection

To confirm whether LMH cells and CEF cells were sensitive to FAdV-4 infection, the expression of viral capsid hexon protein was determined by WB and qPCR. WB results demonstrated that FAdV-4 could infect LMH cells and CEF cells at 1 MOI. Hexon was detected in LMH cells 24 hpi earlier than in CEF cells, and the protein expression was also higher than in CEF cells (Figure 1A). Viral load assays demonstrated that FAdV-4 exhibited significantly different replication kinetics in the 2 cell lines (Figure 1B). To observe FAdV-4 transcriptional dynamics in LMH cells and CEF cells in vitro, we infected 2 types of cells with FAdV-4 at an MOI of 1 (Figure 1C). RNA libraries were generated from cells at 48 and 72 hpi, and the libraries were sequenced using Illumina Sequencing Platform. Reads were aligned to the Gallus gallus reference genome at ≥96% overall mapping rate (Supplementary Table 3). Principal component analysis showed a clear separation between FAdV-4-LMH and FAdV-4-CEF groups, while biological replicates clustered together (Figure 1D).

Figure 1.

Figure 1

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FAdV-4 infection kinetics in LMH cells and CEF cells and RNA-seq analysis. (A) At the designated intervals after infection, LMH/CEF cells were infected with FAdV-4 at an MOI of 1 and subsequently harvested, and hexon was determined using the Western Blot. (B) LMH/CEF cells were infected with FAdV-4 at 1 MOI. The virus copy number was determined using Real-time PCR. (C) The procedure for gathering RNA-Seq samples for this investigation was represented by the workflow. (D) Principal component analysis (PC1, PC2, and PC3) was performed on 24 samples based on gene expression.

Gene Expression Profiles in FAdV-4-Infected LMH Cells

FAdV-4 infection altered global gene expression profiles in LMH cells, with 496 differentially expressed genes identified at 48 h post-infection (hpi) (204 upregulated and 292 downregulated) that largely persisted at 72 hpi (Figure 2A; Supplementary Table 4). The 20 genes exhibiting the greatest up- and down-regulation at each timepoint, ranked by log2 fold change magnitude, are displayed in Figure 2. These genes are mainly related to cellular metabolism and viral replication. Notably, FAdV-4 infection increased lncRNA LOC101749378 expression (Figure 2D), and RHO GTPases regulate immune cell processes like migration and inflammation via interactions with effector proteins (El Masri and Delon, 2021). GSEA revealed significant modulation of numerous biological processes and pathways following FAdV-4 infection. Among these, pathways related to fat metabolism such as the PPAR and adipocytokine signaling pathways were negatively enriched (NES < 0), confirming known adenovirus effects on metabolism (Yuan et al., 2021). FAdV-4 replicates very efficiently in LMH cells so "DNA replication" is positively enriched (NES > 0). Despite robust viral replication confirmed through multiple methods (Figure 1), FAdV-4 infection induced a dampened innate response in LMH cells. KEGG pathway and GO term analysis aligned to show muted modulation of immune pathways (Figures 3A and 3B). Specific innate marker genes displayed mixed expression changes (Figure 3C), with selective upregulation of some interferon-related and inflammatory genes (GBP1, NMI, CCL4), but consistent downregulation of NF-κB inhibitors (NFKBIA, TNFAIP3) across timepoints (Supplementary Table 5). This suggests that FAdV-4 actively restricts key antiviral response pathways during infection. In terms of signaling modulation, the Wnt pathway appeared prominently activated, mirroring FAdV-4 host interactions. Overall the FAdV-4 transcriptomic changes are similar to previous mammalian adenovirus infection studies (Zhao et al., 2012).

Figure 2.

Figure 2

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DEGs analysis between FAdV-4-infected LMH cells (FAdV-4-LMH group) compared to non-infected LMH control cells (NC-LMH group). (A–C) UpSet plots illustrate the distribution of DEGs at 48 and 72 hpi. The horizontal bars show the overall number of DEGs at various hpi, while each vertical bar shows the number of DEGs in a single distribution set. (D, E) Heatmaps display the top 20 up- and down-regulated DEGs at 48 and 72 hpi, ranked by log2 fold change values.

Figure 3.

Figure 3

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Functional annotations of DEGs identified in the FAdV-4-LMH group. (A) GO enrichment at various time intervals after infection. The picture was drawn according to P value < 0.05 filters paths (nodes in the graph), edge similarity edge_similarity >0.2. Nodes denote gene sets; node size indicates number of member genes. Edge width and color show similarity scores between sets. Node color represents hours postinfection (hpi). (B) Lollipop plot illustrating top differentially enriched KEGG pathways at each hpi. (C) Heatmap of DEGs associated with innate immune responses.

Gene Expression Profiles in FAdV-4-Infected CEF Cells

Interestingly, a distinct pattern of response was shown when FAdV-4 infected CEF cells; despite a lower infection level, as shown by WB, RT-qPCR, and percent viral reads, FAdV-4 triggered a broad spectrum of innate immune responses. When FAdV-4 infects CEF cells, compared to LMH cells, the quantity of DEG produced is minimal (Figure 4A). ISGs (such MX1, IFIT5, IFI6, and OASL) had greater transcript levels at 48 and 72 hpi in the FAdV-4-CEF group. Interestingly, at every observation point, AVBD10 annotation for antibacterial and anti-enveloped viral responses was markedly downregulated (Figure 4B). Gene Ontology terms and KEGG pathways associated with antiviral immune responses, including the RIG-I-like receptor, NOD-like receptor, and cytosolic DNA sensing pathways, showed significant and sustained positive enrichment across the time course examined (Figure 5A and B). A subset of interferon signaling pathway-related genes (including MX1, OASL, IFIT5, GBP1, TLR3, STAT1, IFIH1, PARP9, and IRF7) expressed themselves more in the FAdV-4-CEF group than in the NC-CEF group. In the FAdV-4-CEF group, several ILs (IL18, IL10RA, IL6) and chemokines (CCL5, CCL4, CCL20, CXCL14) expressed at lower levels (Figure 5C). By using RT-qPCR, 16 DEGs that were chosen from various comparison groups were verified. The RNA-seq data were validated by RT-qPCR analysis showing strong concordance for the expression changes of selected genes, with minor variations in the magnitude of differential expression for some genes (Figure 6).

Figure 4.

Figure 4

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DEGs analysis between FAdV-4-infected CEF cells (FAdV-4-CEF group) compared to non-infected CEF control cells (NC-CEF group). (A–C) UpSet plots illustrate the distribution of DEGs at 48 and 72 hpi. The horizontal bars show the overall number of DEGs at various hpi, while each vertical bar shows the number of DEGs in a single distribution set. (D, E) Heatmaps display the top 20 up- and down-regulated DEGs at 48 and 72 hpi, ranked by log2 fold change values.

Figure 5.

Figure 5

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Functional annotations of DEGs identified in the FAdV-4-CEF group. (A) GO enrichment at various time intervals after infection. The picture was drawn according to P-value <0.01 filters paths (present more nodes in the graph), edge similarity edge_similarity >0.1. Nodes denote gene sets; node size indicates number of member genes. Edge width and color show similarity scores between sets. Node color represents hours post-infection (hpi). (B) Lollipop plot illustrating top differentially enriched KEGG pathways at each hpi. (C) Heatmap of DEGs associated with innate immune responses.

Figure 6.

Figure 6

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Validation of RNA-sequencing data. A bar plot was generated to compare the RNA-sequencing and RT-qPCR results for 16 selected DEGs. The plot shows the mean (SD) for each gene from both platforms.

Effect of Cytosolic DNA-Sensing Pathway on FAdV-4 Infection

GSEA showed that both cell growth pathways and innate immune response patterns were activated in FAdV-4‐infected CEF and LMH cells, but activation of cytosolic DNA-sensing pathway in FAdV-4 plays an important role in immunological defense against double-stranded DNA viruses, was of particular interest to us (Figure 7A). We focused on genes associated with FAdV-4 infection in the published literature during the data analysis process and performed pathway and gene network diagram analysis on these genes (Figure 7B, Supplementary Table 6). We displayed the FPKM levels of 25 genes in a heat map (Figure 7C, Supplementary Table 7). The expression changes of IRF7 among these genes are relatively typical, and the expression levels were upregulated in 2 types of cells after exposure to the virus. These genes can interact in 4 ways, according to the protein-protein interaction network (Figure 7D), including experiments, co-expression, text mining, and databases.

Figure 7.

Figure 7

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Bioinformatics methods identified a series of cell growth and innate immune response factors in FAdV-4-infected LMH/CEF cells. (A) GSEA for the cell growth pathways and innate immune response pathways related pathways. (B) Pathway and gene network analysis diagram. Different colors of points reflect different routes in the KO pathway and gene network map, while line colors and thicknesses show the number of times genes appear in different differential grouping enrichment results. (C) Key gene heatmap Red denotes strong expressiveness, and blue denotes modest expression. The expression value increases with color depth. (D) Protein‐protein interaction networks of 25 Key genes. Different colors denote various interaction modes.

IRF7 was chosen as one of the DEGs in the sequencing data to determine the possible involvement of identified genes in controlling FAdV-4 replication. IRF7 expression was shown to be considerably higher in FAdV-4-infected CEF cells than in FAdV-4-infected LMH cells, which may lead to FAdV-4 proliferating less effectively in CEF cells than in LMH cells. To verify this speculation, we knocked down the IRF7 upstream signaling molecules. Since LMH cells are more suitable for siRNA transfection than CEF cells and have higher knockdown efficiency on target genes (Supplementary Figure 1), we knocked down IRF7 upstream signaling molecules in LMH cells. Subsequently, the expression of IRF7, downstream antiviral OASL genes, and FAdV-4 Hexon gene were examined using qPCR assay. It was observed that knockdown cGAS, STING, MDA5, and TBK1 could enhance the replication ability of FAdV-4 in LMH cells to varying degrees (Figures 8A–H).

Figure 8.

Figure 8

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IRF7-induced antiviral OASL gene expression inhibits FAdV-4 replication. LMH cells were transfected with siRNAs targeting cGAS, STING, MDA5, TBK1, or a nontargeting control (si-NC) for 24h and then infected with FAdV-4 at an MOI of 1. At 24 hpi, Hexon levels were determined by western blotting with Tubulin loading control (A, C, E, G). Bands were quantified using ImageJ to assess effects on viral protein expression (B, D, F, H). IRF7(I) and OASL(K) mRNA levels were measured by qRT-PCR. Extracellular viral genome copies were quantified by qPCR(J). Gene expression was calculated using the 2−ΔΔCT method and graphed as mean ± SE of 3 experiments. Mann-Whitney U tests evaluated differences between siRNA conditions. *P < 0.05; **P < 0.01; ***P < 0.001.

Furthermore, by qRT-PCR it was found that after knocking down the upstream signaling molecule to reduce the expression of IRF7 mRNA, the FAdV-4 virus copy number was enhanced, and the expression of the downstream signaling molecule OASL was also reduced accordingly (Figures 8I–K). There is an obvious correlation between the 3. Therefore, we infer that FAdV-4 infection activates the Cytosolic DNA-sensing pathway and increases the expression of the downstream effector molecules IRF7 and OASL, which inhibits the replication of FAdV-4 in cells. This may also be the reason for the poor proliferation ability of FAdV-4 in CEF cells because the innate immune response in CEF cells is significantly stronger than that in LMH cells.

DISCUSSION

The poultry sector is very important for the breeding industry in China. Since 2015, a widespread epidemic of HHS, caused by hypervirulent FAdV-4, has occurred in China, which led to severe mortality in broiler chickens and massive losses to the stakeholders. However, the exact mechanism of FAdV-4 pathogenesis and host immune responses to the virus infection remains incompletely understood. At present, research on the immunological reactions induced by FAdV-4 mainly focused on cytokines and has been restricted in extent and concentrated on a small number of. Our study demonstrated that the host responses induced by FAdV-4 were different in cancerous versus noncancerous cells, which may be related to the virus tissue tropism. FAdV-4 could facilely escape host defenses in permissive LMH cells, while cytosolic DNA sensing appears to limit viral replication in CEF cells. Further research should explore the mechanisms underlying this dichotomy. Delineating the cell or tissue-specific interactions between the host and pathogens will provide insights into FAdV-4 immunopathogenesis and identify potential therapeutic targets.

The LMH cells are more susceptible to FAdV-4 infection than CEF cells, which was demonstrated by the rapid increase of viral mRNA and the progeny viral Hexon protein in the infected LMH cells (Figures 1A and 1B). These results, at least in part, may explain that the liver is the principal site of viral replication and the major target organ of HHS disease. In this study, the GSEA approach was used to conduct functional enrichment analysis to determine the significance of differential gene annotation. This strategy efficiently avoids data loss caused by hard thresholds. Most of the classified enrichment results relate to cellular metabolism, viral replication, the cell cycle, translation, immune response, and other processes. Despite higher viral infection levels, it was showed a limited immune response to FAdV-4 infection in LMH, which was in stark contrast to the significant activation of innate immune responses in CEF cells (Figure 3). It was reported that Wnt/β-catenin signaling is critical for viral replication. Our results also revealed that activation of the Wnt signaling pathway during viral infection appears to be one of the most well-defined signaling pathways. You et al discovered that β-catenin, a highly conserved component of the Wnt signaling system, is critical for boosting type I interferon (IFN-I) production in the cGAS/STING signaling pathway (You et al., 2020). Nevertheless, our previous study demonstrated that the activation of Wnt/β-catenin signaling facilitated FAdV-4 replication via enhancing virus-induced autophagy and independent of the IFN-I response (Wang et al., 2023). Although the GO enrichment did not identify immune response genes as a significant group (Figure 3A), the changes in the “interferon-stimulated genes” and “NF-κB pathway inhibitory proteins” indicate that FAdV-4 infection can activate the NF-κB pathway in LMH cells (Figure 3C). A similar phenomenon discovered in a recent study showed that FAdV-4 uses the NF-kB pathway to enhance the gene expression of MHC molecules and its chaperone protein Ii (Li et al., 2021).

Crucially, we found that the CEF cells exhibited a strong innate immune response to FAdV-4, including inflammatory and antiviral response. The upregulation of multiple antiviral cytokines associated with interferon signaling pathways was detected using the gene-wide transcriptome analysis (Figure 5). Research has indicated that cytokines are believed to be crucial in the immune response mechanism, while there is a positive correlation between liver injury and a strong immune response (Lewis and Obbard, 2014). Multiple pro-inflammatory and immunological cytokines (IL-2, TNF-α, IL-1, IL-8, IL-6, IFNs, Mx, and OASL) were shown to have elevated mRNA expression in chicken tissues infected with hypervirulent FAdV-4 (Li et al., 2018; Yu et al., 2018; Niu et al., 2019a; Niu et al., 2019b). In recent years, significant advancements have been made in understanding of poultry IFN responses. Research shows that chcGAS activated STING/TBK1/IRF7-mediated innate immunity in CEF and LMH in response to dsDNA compounds and DNA damage-induced dsDNA. In addition, the rate of increase of downstream effectors (STING signaling axis) was significantly higher in the CEF infection group compared to the LMH infection group (Wang et al., 2020). Our findings also emphasized this fact. The cytosolic PRR MDA5 is essential for viral infection detection and interferon expression. In contrast to other species, chicken lacks RIG-I-like receptor, and the presence of MDA5 replaces the RIG-I-like receptor in recognizing PAMP to initiate the innate immune response (Chen et al., 2013). The ability of FAdV-4 replication in LMH cells was increased by knocking down cGAS, STING, MDA5, and TBK1, according to our experimental data (Figure 8). These findings further support the involvement of the STING signaling pathway in the innate immune response triggered by FAdV-4 infection. We can exploit this host-pathogen interaction for the treatment of HHS in chickens. Screening and evaluating STING agonists for inhibiting FAdV-4 replication warrants further study.

The amount of virus titers may be an important potential factor in the gene expression patterns as for immune response. Zaritsky et al. demonstrated that cells infected with a lower Sendai virus (SeV) MOI induced more type I IFN subtypes than cells infected with a higher MOI. In other words, the virus can induce different type I IFN profiles in the same cell type, depending on the MOI used to infect the cells (Zaritsky et al., 2015). However, our findings showed that the higher titers of FAdV-4 in LMH cells provoked limited interferon-stimulated gene induction. Inversely, FAdV-4 with lower titers triggered robust antiviral responses in CEF cells and inhibited viral replication. Consequently, the experimental protocol for virus-infected cells needs to be optimized to make sure that virus titers in both cells are equivalent at the same time point. This approach facilitates the comparison of host response differences between the 2 type cells at the same virus titer levels.

In summary, this study demonstrates that FAdV-4 induces different host responses in cancerous and noncancerous cells. Defective interferon activation and cytosolic DNA sensing may promote immune reactions to FAdV-4 infection in liver cells, underlying the virus hepatic tropism. In contrast, intact antiviral pathways in CEF cells likely contribute to the limitation of virus replication. These divergent dynamics of virus-host reaction lend new perspectives into the tissue tropisms, pathogenesis, and spread of FAdV-4 infection in poultry. Furthermore, the data shed light on the pivotal role of intracellular innate immune pathways like cytosolic nucleic acid sensing in mediating antiviral immunity against. Elucidation of these molecular mechanisms may provide a foundation to developing targeted strategies for the control of FAdV-4 infection.

ACKNOWLEDGMENTS

This work was supported by the National Natural Science Foundation of China (No. 32172843), and the Natural Science Basic Research Program of Shaanxi (No. 2023JC-QN-0190).

DISCLOSURES

The authors confirm that this study was performed without external funding or commercial affiliations that may represent potential conflicts of interest.

Footnotes

Supplementary material associated with this article can be found in the online version at doi:10.1016/j.psj.2024.103741.

Appendix. Supplementary materials

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mmc2.xlsx (11.4KB, xlsx)
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mmc5.xlsx (4.1MB, xlsx)
mmc6.xlsx (9.6KB, xlsx)
mmc7.xlsx (9.8KB, xlsx)
mmc8.xls (6KB, xls)

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Supplementary Materials

mmc1.docx (273.3KB, docx)
mmc2.xlsx (11.4KB, xlsx)
mmc3.xlsx (11.2KB, xlsx)
mmc4.xlsx (11.3KB, xlsx)
mmc5.xlsx (4.1MB, xlsx)
mmc6.xlsx (9.6KB, xlsx)
mmc7.xlsx (9.8KB, xlsx)
mmc8.xls (6KB, xls)

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