Abstract Duck hepatitis A virus genotype 3 (DHAV-3) is the major cause of viral hepatitis in ducks in Asia. Previous studies have shown that ducklings younger than 21 days are more susceptible to DHAV-3. To elucidate the mechanism by which age affects the differential susceptibility of Pekin ducks to DHAV-3, intestinal (n = 520), liver (n = 40) and blood (n = 260) samples were collected from control and DHAV-3-infected ducks at 7, 10, 14, and 21 days of age. Comparisons of plasma markers, mortality rates, and intestinal histopathological data showed that the resistance of Pekin ducks to DHAV-3 varied with age. 16 S sequencing revealed that the ileal microbial composition was influenced by age, and this correlation was greater than that recorded for caecal microbes. Candidatus Arthromitus, Bacteroides, Corynebacterium, Enterococcus, Romboutsia, and Streptococcus were the differntially abundant microbes in the ileum at the genus level after DHAV-3 infection and were significantly correlated with 7 differentially expressed genes (DEGs) in 7- and 21-day-old ducklings. 3 immunity-related pathways were significantly different between 7- and 21-day-old ducklings, especially for IFIH1-mediated induction of the interferon-alpha/beta pathway, which induces differential production of CD8(+) T cells and was influenced by a combination of differentially abundant microbiota and DEGs. We found that microbes in the ileum changed regularly with age. The intestinal microbiota was associated with the expression of genes in the liver through IFIH1-mediated induction of the interferon-alpha/beta pathway, which may partially explain why younger ducklings were more susceptible to DHAV-3 infection. Keywords: Pekin duck, Intestinal microbiota, Age, DHAV-3, Resistance differences Graphical Abstract [41]ga1 [42]Open in a new tab 1. Introduction The poultry industry is the focus of livestock farming development because of its favourable meat-to-feed ratio and short production cycle. Globally, meat consumption has shifted towards poultry meat, with almost all countries increasing their consumption of poultry meat [43][1], [44][2]. Pekin ducks constitute a major part of the global poultry industry. These ducks exhibit a high growth rate, good feed conversion, a high lean meat percentage, a low skin/fat ratio, and a high dressing percentage and have become the most widely reared ducks in the duck industry [45][3]. More than 200 million ducks are slaughtered for their meat in the United States and the European Union each year [46][4], [47][5]. Although the Pekin duck industry is large, few studies have investigated the effects of the composition and structure of the intestinal flora on the growth, development, and health of Pekin ducks [48][6], [49][7]. The intestinal flora influences the ability of host animals to digest and absorb nutrients [50][8], the immune response [51][9], the synthesis of amino acids and vitamins [52][10], and the proliferation of pathogenic microbes [53][11]. Therefore, the study of the composition and structure of the intestinal flora of ducks is essential for the healthy development of the duck industry. The rate of infection for susceptible individuals varies significantly with age [54][12], and younger individuals are more susceptible to infection, playing a strong role in the transmission of pathogens [55][13]. One reason for this finding is that younger individuals have an inadequate immune response, resulting in a lower resistance to infection than in adults [56][14]. Some studies have reported a general pattern, suggesting that infection rates increase in early childhood years and then decrease with age [57][15]. Similar results have also been reported in livestock diseases; for example, young sheep have significantly lower proportions of CD4(+) and CD8(+) lymphocytes. In addition, their blood lymphocytes produce less interferon-7 in culture and have a weaker antibody response than those of mature animals [58][16]. In the Pekin duck industry, duck viral hepatitis (DVH) is a highly contagious, fatal disease of young ducklings, and ducklings less than three weeks old are highly susceptible to this disease [59][17]. DVH can cause up to 95% mortality in ducklings less than one week old [60][18]. Age of Pekin ducklings strongly influences the differences in susceptibility to DVH. In another study, we showed that high genomic copy numbers of DHAV-3, which is the most prevalent pathogen causing DVH in the Asian duck industry [61][19], [62][20], occurred in the intestinal tissues of susceptible ducklings. Additionally, the viral load in the intestinal tissues of resistant ducks was significantly lower than that in the intestinal tissues of susceptible ducks [63][21], suggesting that the intestinal load is associated with the susceptibility of Pekin ducks to DHAV-3. None of these studies investigated the changes induced in the intestinal microbiota of Pekin ducks following viral infection, although the microbiota is known to be the primary mediator and regulator of innate and adaptive immune functions. We conducted this study to understand the influence of host–microbe interactions on different susceptibilities from the perspective of the "gut-liver axis". In this study, the composition and structure of the intestinal microbiota of Pekin ducks on different days were determined, as well as the changes in intestinal microbes that occurred after viral infection and the relationship between the intestinal microbiota and disease resistance. To conduct this study, we designed three experiments. We assessed the intestinal microbiota of 7-day-old, 10-day-old, 14-day-old, and 21-day-old Pekin ducks, all of which had the same genetic background. We analysed the intestines of ducklings of different age groups after DHAV-3 infection to determine the effect of the virus on intestinal microbes, using the uninfected group as a control. Finally, transcriptomic analysis was performed to identify differentially expressed genes (DEGs) for different age groups, and the results were combined with an analysis of differentially abundant microbes to determine the influence of these microbes on the disease resistance in Pekin ducks. 2. Materials and methods 2.1. Ethics statement Animal experiments were performed following the guidance and under the approval of the Animal Welfare and Ethics Committee of China Agricultural University and the animal care and use committee of the Institute of Animal Sciences of the Chinese Academy of Agricultural Sciences (IAS2022–116). 2.2. Virus DHAV-3 112803 was originally isolated from a dead duckling during an outbreak of DVH in China in 2011 [64][22]. The virus was propagated in 9-day-old embryonating Pekin duck eggs and stored at − 80 °C. Using 10-day-old duck embryos, the titre of DHAV-3 was determined to be 10^6.25 50% egg lethal dose (ELD[50])/0.1 mL. 2.3. Animal experimental design The Z2 strain of Pekin ducks was used in this study. When the ducks reached approximately 30 weeks of age, 10 males and 40 females were collected to construct families. The females were fed separately, each male was mated with only four fixed females, and the ducks were reared separately and fed a grower diet (air-dried basis, 12.6 MJ/kg ME and 17.6 g/kg CP). When the ducks reached 40 weeks of age, eggs were collected in four batches and marked according to the pedigree. All ducks were raised with common diets, and all nutrients met the recommendations for ducks established in the Nutrient Requirements of Meat-type Ducks of China [65][23]. Feed and water were provided ad libitum during the experiment. For DHAV-3 challenge, ducklings from the 7-day group (n = 100), 10-day group (n = 100), 14-day group (n = 100) and 21-day group (n = 100) from the same families were selected and named In7, In10, In14 and In21, respectively, and these ducklings were infected on the same day by intramuscular injection. As a control, ducklings from the 7-day (n = 15), 10-day (n = 15), 14-day (n = 15) and 21-day (n = 15) groups from the same families were selected and named C7, C10, C14 and C21, respectively, and these ducklings were inoculated with PBS. The mortality was observed every 6 h during the 12–72 h post inoculation (hpi). 2.4. Tissues collection Two hundred ducklings from the challenge group and 60 ducklings from the control group were selected, and samples were taken at 18 hpi. The remaining ducks were used to observe mortality, and the mortality rates of each group were recorded in detail. A total of 260 ileum, 260 caecum, and 260 blood samples were collected, and five duck livers from C7, C10, C14, C21, In7, In10, In14 and In21 were collected. Ileum and caecum mucosa samples were stored at − 80 °C and subjected to 16 S sequencing; blood samples were subjected to plasma biochemical assays; and liver tissues were subjected to RNA-seq. Three ducks were randomly selected from each group for tissue collection. A total of 24 samples were included, including 12 ileum tissues and 12 caecum tissues. These tissues were subjected to haematoxylin-eosin (H&E) staining analysis. The number of DHAV-3 copies in the ileum was determined as described previously [66][20]. 2.5. DNA extraction, 16 S rRNA sequencing and library preparation of ileum and caecum A total of 520 intestinal samples (260 ileum mucosa and 260 caecum mucosa samples) were collected, and 0.2 g of each sample was added to a PowerBead tube. Extraction was performed using the MagPure Stool DNA LQ Kit (Magen, Guangzhou, China) following the manufacturer’s instructions. The DNA was checked for purity on a Nanodrop (Thermo Scientific, USA), and DNA concentrations were measured using a Qubit 2.0 fluorometer (Thermo Fisher Scientific, MA, USA). The DNA was stored at − 80 °C until sequencing. The V3-V4 region of the 16 S rRNA gene was amplified using the primers 341 F/805 R. The PCR program was performed under the following conditions: denaturation for 3 min at 95 °C; 25 cycles of denaturation at 95 °C for 30 s, 55 °C for 30 s, and 72 °C for 15 s; and a final extension at 72 °C for 5 min. The purified DNA samples were subsequently quantified using a Qubit 2.0 fluorometer, sequencing libraries were constructed using the NEBNext® Ultra™ II DNA Library Prep Kit for Illumina (New England Biolabs, MA, USA) following the manufacturer’s instructions, and index codes were added. The library quality was assessed using a Qubit 2.0 fluorometer. Finally, the library was sequenced on an Illumina NovaSeq 6000 platform at Wuhan Benagen Technology Company Limited (Wuhan, China). 2.6. 16 S rRNA gene data processing and bioinformatic analysis Cutadapt (v.3.5) software [67][24] was used to identify and remove primer sequences, and length filtering was performed to obtain clean sequences. For the identification of feature sequences (amplicon sequence variants, ASVs), DADA2 [68][25] was used to filter the raw data, splice paired-end reads and remove chimeric sequences. Then, QIIME2 software [69][26] was used to filter the low-abundance ASVs, and all samples were flattened with the minimum number of sequences. Subsequently, the bacterial ASVs were assigned to taxonomic groups using the SILVA database ([70]https://www.arb-silva.de/) for species annotation. The alpha diversity indices, including the Shannon, Simpson, Chao1 and ACE indices, were calculated using QIIME2 software. The beta diversity was calculated using the R package to investigate the community dissimilarities among the treatments. In addition, analysis of similarities (ANOSIM) was conducted to examine the significance of the differences between groups and the significance of the differences in distance between and within groups. Statistical significance was determined through one-way analysis of variance (ANOVA) followed by post hoc Tukey’s test. Functional inference was made from the Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway and Clusters of Orthologous Groups of proteins (COG) databases. 2.7. Liver RNA extraction and transcriptome sequencing Forty liver tissues were used; 15 mg of each liver sample was weighed, ground in liquid nitrogen and extracted using a Total RNA Kit I (Omega: No. R6834–02). Libraries were constructed using the MGIEasy RNA Library Prep Kit for BGI® and sequenced by combining probe anchored polymerization (cPAS) technology (DNBSEQ, BGI) with an average sequencing depth of approximately 6 × . 2.8. Analyses of RNA-seq data To ensure the reliability of the information analysed, the raw sequencing data were filtered to remove low-quality and contaminated reads, thus obtaining clean reads. Quality control of the filtered data was performed using fastQC (v0.11.9) [71][27]. The filtered sequences were aligned with the reference genome (GenBank assembly accession: GCA_015476345.1) using STAR (v2.7.9a) [72][28]. The number of reads per sample compared to that of each transcript was obtained using RSEM [73][29] and converted to fragments per kilobase per million bases (FPKM) values. DEGs were screened using DESeq2 (v1.26.0) [74][30] with screening thresholds of a false discovery rate (FDR) < 0.05 and |log[2]FoldChange| > 1. 2.9. Enzyme-linked immunosorbent assay (ELISA) Blood samples were collected in anticoagulant-free tubes and centrifuged at 3000 × g for 15 min to obtain the serum. Standard wells, blank wells and sample wells were set up. Fifty microlitres of each of the standards at different concentrations was added to the standard wells. Colorants A and B and termination solution were added to the blank wells for zeroing. Fifty microlitres of sample and 50 μl of antigen working solution were added to each sample well. After gently shaking and mixing, the plates were covered with sealing film and incubated at 37 °C for 30 min. The sealing film was removed, the liquid was discarded, the plates were shaken dry, and each well was filled with washing solution and allowed to rest for 30 s before the solution was discarded. This process was repeated 5 times, after which the wells were patted dry. HRP-conjugate reagent (100 μl) was added to each well, and the mixture was allowed to react at 37 °C for 30 min. The plates were washed 5 times again and patted dry. Chromogen Solution A (50 μl) and Chromogen Solution B (50 μl) were added to each well, and the plate was incubated in the dark for 15 min at 37 °C. Then, 50 μl of Stop Solution was added to each well to terminate the reaction. The optical density of each well was measured sequentially at 450 nm using a blank well as the zero value. The regression equation for the standard curve was calculated using ELISAcalc based on the concentration and OD values, and the logistic curve was chosen as the fitting model. Immunoglobulin A (IgA), interferon alpha (IFN-α) and C-reactive protein (CRP) levels were determined by ELISA. The ranges of IgA, IFN-α and CRP were 0–6.1 g/L, 0–125 pg/mL and 0–500 pg/mL, respectively. The R^2 values of the standard curves were 0.99998, 0.99993 and 0.99997. The sensitivity of the kit was < 7 in each batch, and the recovery rate was approximately 103%. 2.10. H&E staining and villus height (VH) measurement The ileum tissues were fixed in 4% buffered formaldehyde solution (pH 7.4) for 24 h. Following dehydration, the tissues were embedded in paraffin and cut into 5-µm-thick sections. Sections were stained with haematoxylin and eosin and observed under a light microscope (Olympus, Japan). Observations were made under an optical microscope (SONY, Alpha6000), and Image-Pro Plus 6.0 software was used to measure the VH at 100 × . 2.11. Flow cytometry The flow cytometry procedure was performed as previously described [75][31]. The antibody used for the CD8(+) T-cell assay was APC/Cyanine7-conjugated anti-human CD8 (No. 344714; Biolegend). Blood samples treated with anticoagulant agents were taken from 3 individuals in each group. 2.12. Distance correlations between DEGs and differentially abundant microbes We used Euclidean distances for transcriptomic data and Bray distances for phenotypic data. Mantel tests were performed between DEGs and differentially abundant microbes. The “linkET” [76][32], “ggtext”, “dplyr” and “ggplot2” R (v4.2.2) software packages ([77]http://github.com) were used in these analyses. 2.13. Data analysis Phenotypic data are expressed as the mean ± standard deviation (SD). Differences between two groups were compared using Student’s t test in GraphPad Prism 6.0 (GraphPad Software, Inc., San Diego, CA, USA). The Kruskal—Wallis test was used for multiple-group comparisons. P < 0.05 was considered to indicate statistical significance. 3. Results 3.1. Intestinal development and blood immunity indices in Pekin ducks at different ages VH was measured in the ileum and caecum of C7, C10, C14, and C21. As shown in [78]Fig. 1A, the VH in the caecal tissues fluctuated but increased overall with age, with the VH at 14 days being significantly greater than that at 7, 10 and 21 days. In the ileum, the VH increased with age and was significantly greater at 21 days than at 7, 10 and 14 days. Fig. 1. [79]Fig. 1 [80]Open in a new tab Age-related changes (in days) in the ileum and caecum. A. Villus height in ileal and caecal tissues of Pekin ducks at 7, 10, 14, and 21 days after hatching. B. Plasma levels of immunoglobulin A (IgA), interferon alpha (IFN-α) and C-reactive protein (CRP) in Pekin ducks at 7, 10, 14, and 21 days after hatching. C. Principal coordinate analysis (PCoA) of the microbial composition of the ileum and caecum based on the Bray—Curtis distance. D. Heatmap of microbes in the ileum and caecum at the phylum level. Canonical correlation analysis (CCA) of microbial and phenotypic indicators in the ileum (E) and caecum (F); * , P < 0.05; ** , P < 0.01; *** , P < 0.001. The concentrations of IgA, IFN-α and CRP were measured in the different control groups. As shown in [81]Fig. 1B, IgA showed an increasing trend, and its concentration in C21 was significantly higher than that in the other three groups (P < 0.05). There was no significant difference in the IgA concentration among the three groups (C7, C10 and C14). IFN-α followed the same trend as IgA, but only the C7 group had significantly lower concentrations of IFN-α than the C10, C14 and C21 groups. The concentration of CRP decreased and then increased with age, but the difference was not significant. 3.2. Sequencing result summary In total, 520 samples were sequenced, and 55,625,518 paired reads were obtained after Illumina sequencing (Additional file 1: [82]Table S1). Rarefaction curves generated from the amplicon sequence variants (ASVs) suggested that high sampling coverage was achieved in all samples, suggesting that the sequencing depth was sufficient for the investigation of the intestinal microbiota (Additional file 2: [83]Fig. S1). The number of ASVs (including those in the control and challenge groups) at 7 days of age was lower than that in the other three age groups, and the number of cooccurring ASVs increased with age, as expected (Additional file 2: [84]Fig. S2). 3.3. Ileal microbial diversity and composition showed age-related changes The richness (Chao1 and ACE) and diversity (Shannon and Simpson) indices of the ileum increased with age, although there were no significant differences between C10 and C14 (P > 0.05). However, there were no age-related changes in microbial diversity in the caecum (Additional file 2: [85]Fig. S3). Based on the Bray—Curtis distance, the scatter distances in the principal coordinate analysis (pCoA) plots of the ileal group showed that the samples within the C21 group were less different and clearly separated from the other three groups. C7, C10 and C14 showed a certain trend with age in days, with C7 being separable from C14 ([86]Fig. 1C). Hierarchical clustering based on ASV information was also generated. Ileum samples from C7 and C10 were grouped tightly, followed by those from C14, and the ASVs from the four groups could be separated into two lineages. Similar results were also found via pCoA using weighted and unweighted UniFrac metrics (Additional file 2: [87]Fig. S4). However, the results for the relationships of the four groups from the caecum differed among the multiple variants. In the ileum, Firmicutes was the most abundant phylum, accounting for more than 60% of the total resident bacteria. Firmicutes was the most abundant phylum in the caecum of the C21 group, and Bacteroidetes was the most abundant phylum in C7, C10 and C10 (Additional file 2: [88]Fig. S5). In the ileum, the abundance of Firmicutes decreased with age, and the opposite was true for Bacteroidota, Desulfobacterota and Deferribacterota. In the caecum, the abundance of Firmicutes and Actinobacteria increased with age, and that of Bacteroidetes decreased with age. The ileum and caecum showed significant differences in Firmicutes and Bacteroidetes abundances ([89]Fig. 1D; Additional file 1: [90]Table S2) (Kruskal—Wallis test, P < 0.05). The canonical correlation analysis (CCA) results for microbial composition and plasma immunological indicators for different ages are shown in [91]Figs. 1E and [92]1F. In C7, C10 and C14, the IgA, IFN-α and CRP levels were negatively correlated with age. Some of the microbial components of the ileum were shared among C7, C10 and C14, and the PERMANOVA test confirmed highly significant differences between these three groups and C21 (P = 0.004). The abundances of various taxa showed that microbial composition was much more strongly correlated with age than with other factors (P < 0.001, r^2 = 0.1816). However, most of the microbial composition of the caecum was shared among C7, C10 and C14, and age was the most relevant factor (P < 0.001, r^2 = 0.1162). 3.4. Phenotypic changes in ducklings and ileal microbial composition after infection with DHAV-3 As shown in [93]Fig. 2A, after infection with DHAV-3, the mortality rate of ducklings was 68% in the In7 group, 34% in the In10 group, 4% in the In14 group and 0% in the In21 group. The IgA concentrations were significantly higher in the In7 and In21 groups than in the control group. IFN-α levels were significantly higher in the In7 group than in the C7 group, but no significant differences were observed in the other three groups. CRP levels at 7 days of age were not influenced by DHAV-3 infection, but they were significantly different in the In10, In14 and In21 groups compared with those in the control group ([94]Fig. 2B). Fig. 2. [95]Fig. 2 [96]Open in a new tab Phenotypic changes after DHAV-3 infection. A. Mortality curves of ducklings infected with DHAV-3 at 7, 10, 14, and 21 days after hatching. B. Changes in plasma immunoglobulin A (IgA), interferon alpha (IFN-α) and C-reactive protein (CRP) levels after infection with DHAV-3 in ducklings at 7, 10, 14, and 21 days after hatching. C. Detection of viral load in challenge groups. The number of viral genomic copies was calculated as log[10] virus RNA copies/mg. For each group, ileum tissues were sampled at 18 h p.i. ns, P > 0.05; *** , P < 0.001. D. Pathological histology of ileal tissue after DHAV-3 infection; 200 × . The black arrow indicates haemorrhage and congestion, the green arrow indicates focal lymphocytic aggregations. In the ileum, the number of DHAV-3 genome copies was greatest in the In7 subgroup, significantly greater than that in the In14 and In21 groups, but not significantly different from that in the In10 group ([97]Fig. 2C). Pathological histological analysis revealed that the degree of damage to the intestine caused by DHAV-3 infection decreased with age ([98]Fig. 2D), with severe haemorrhage and inflammatory cell infiltration observed in the intestinal tissues of 7-day-old ducklings and with the number of lesions decreasing with age. The ileum showed more regular age-related changes in microbial composition than did the caecum. Therefore, the ileum was used to study changes in microbial composition following DHAV-3 infection. As shown in [99]Fig. 3A, the number of ASVs per group increased more than 2-fold after infection, with the highest increase of 6-fold observed in the 7-day-old group. DHAV-3 infection significantly altered the composition of microbes in the ileum (Additional file 1: [100]Table S3). The CCA results showed that age and viral infection were positively correlated with microbial diversity, and the amount of variance explained by their interaction was 1.1141 (P < 0.001; [101]Fig. 3B). The results of the LEfSe analysis showed that the predominance of microbes decreased in each group after infection, but there were no significant changes in the four microbes at the genus level after infection ([102]Fig. 3C; Additional file 1: [103]Table S4). Fig. 3. [104]Fig. 3 [105]Open in a new tab Ileal microbial changes after DHAV-3 infection. A. Number of amplicon sequence variants (ASVs) in the ileum of ducklings before (left) and after (right) DHAV-3 infection at 7, 10, 14, and 21 days after hatching. B. Canonical correlation analysis (CCA) of microbial and phenotypic indicators in the ileum. *** , P < 0.001. C. LEfSe analysis in ileal microbial of Pekin ducks at 7, 10, 14, and 21 days after hatching. Microbes marked in red were present before and after infection with DHAV-3. 3.5. Significantly differences were found in 3 immunity-related pathways The results of the Gene Ontology (GO) enrichment analysis of the DEGs revealed that 16 GO terms were significantly enriched in the In7 subgroup, 10 in the In10 subgroup, 5 in the In14 subgroup and 4 in the In21 subgroup ([106]Fig. 4A; Additional file 1: [107]Table S5). The results of the KEGG pathway enrichment analysis were similar to those of the GO enrichment analysis, and the number of significantly enriched pathways decreased with age ([108]Fig. 4B; Additional file 1: [109]Table S6). Fig. 4. [110]Fig. 4 [111]Open in a new tab Screening of candidate genes and Mantel correlation analysis of differentially abundant microbes. A. GO enrichment analysis of differentially expressed genes (DEGs) in the livers of ducklings at 7, 10, 14, and 21 days after infection. B. KEGG enrichment analysis of differentially expressed genes in the livers of 7-, 10-, 14-, and 21-day-old ducklings. Boxes indicate pathways that were significantly enriched in each group. C. Venn diagram analysis of DEGs in the livers of ducklings at 7, 10, 14, and 21 days after hatching. D. Heatmap analysis of the genes obtained from the venn diagram analysis was performed using the K-means method, and the expression trends of the DEGs according to age were shown. E. Venn diagram analysis of DEGs obtained from GO enrichment, KEGG enrichment, and venn diagram analyses. The variation in the level of expression with age for the DEGs was shown. F. Pairwise comparisons of differentially abundant microbes and candidate DEGs were shown. The level of expression of DEGs was related to each phenotype by partial (geographic distance–corrected) Mantel tests. The edge width indicates Mantel’s r statistic for the corresponding distance correlations, and the edge colour indicates the statistical significance based on 9999 permutations. Boxes indicate the mortality rates for each group infected with DHAV-3. A total of 135 genes were found in the four groups by Venn diagram analysis ([112]Fig. 4C; Additional file 1: [113]Table S7). The 135 genes were clustered and partitioned by K-means, and the results were divided into 6 regions with different expression patterns (Additional file 1: [114]Table S8). The FPKM values of the six regions were analysed, and the expression levels of genes in the red, yellow, blue and orange regions were significantly different between the challenge group and the control group ([115]Fig. 4D). The expression trends of the 4 modular genes were determined. Furthermore, we performed another Venn diagram analysis based on the genes enriched in the biological process (BP) GO category (GO0051607: defence response to virus; GO0006955: immune response) and the genes involved in the enriched KEGG pathways (apla04060: Cytokine—cytokine receptor Interaction; apla04622: RIG-1-like receptor signalling pathway; apla05164: Influenza A) and the expression trends of the 4 modular genes. Finally, 7 key genes were identified ([116]Fig. 4E; Additional file 1: [117]Table S9). According to the LEfSe analysis, six key microbes were identified, including four that were consistently present before and after infection and two that showed discrepancies ([118]Fig. 3C); additionally, Mantel test analysis was performed on these six microbes with the seven key candidate genes. Candidatus Arthromitus was significantly correlated with DHX58, IFIH1 and LOC101798847 at 7 days of age. There was no significant correlation between DEGs and differentially abundant microbes in the 10- and 14-day-old groups. In the 21-day-old group, six differentially abundant microbes were significantly associated with the candidate DEGs, among which DHX58 was significantly associated with five microbes, followed by IFIH1 and LOC101798847 ([119]Fig. 4F; Additional file 1: [120]Table S10). Interestingly, three genes, DHX58, IFIH1 and LOC101798847, are involved in the same signalling pathway, namely, IFIH1-mediated induction of interferon-alpha/beta signalling. 3.6. Identification of key age-related microbes and genes related to resistance to DHAV-3 infection In addition, the differentially abundant microbes of C7 v.s. C21 and In7 v.s. In21 groups were identified, and KEGG and COG functional enrichment were performed. The differentially abundant microbes in the C7 vs. C21 comparison were enriched in 155 pathways. Nineteen disease-related pathways were selected, and 3 immunity-related pathways, Fc gamma R-mediated phagocytosis, the RIG-1-like receptor signalling pathway and the haematopoietic cell lineage, were found to be significantly different between 7-day-old and 21-day-old ducklings ([121]Fig. 5A; Additional file 1: [122]Table S11). These pathways mainly perform two functions: information storage and processing and cellular processes and signalling. Fig. 5. [123]Fig. 5 [124]Open in a new tab Functional prediction analysis of microbes in the ileum at 7 and 21 days of age before and after infection with DHAV-3. A. The results were divided into two modules, KEGG (left) and COG (right). The number indicates the log[2]FoldChange. A positive value indicates that the pathway was upregulated at 7 days of age. B. Comparative analysis of differentially abundant microbes at 7 and 21 days of age. Variance analysis was performed using graphical presentation (below). Candidatus Arthromitus and Bacteroides were the dominant microbes in the C7 and C21 groups, respectively. The abundance of Candidatus Arthromitus decreased significantly in the 7-day-old group after DHAV-3 infection, but it was still the most abundant taxon. Similarly, the abundances of Candidatus Arthromitus, Romboutsia, Corynebacterium and Enterococcus increased significantly, and these became the main microbes in 21-day-old ducklings ([125]Fig. 5B). The expression levels of genes involved in IFIH1-mediated induction of the interferon-alpha/beta pathway were compared between In7 and In21 cells. The results showed that the abundances of these genes related to this pathway were significantly greater in the In7 group than in the In21 group ([126]Fig. 6A). The expression of these genes was significantly upregulated at 7 days after DHAV-3 infection ([127]Fig. 6B-F). IFIH1 is the key sensor that induces the IFN-I needed for CD8(+) T-cell responses; thus, the percentages of CD8(+) T cells in both groups were also examined, with higher numbers of CD8(+) T cells being found in the In7 group (P < 0.05; [128]Fig. 7). The results suggested that 7-day-old ducklings produced more interferon and CD8(+) T cells after infection with DHAV-3. Fig. 6. [129]Fig. 6 [130]Open in a new tab Demonstration and analysis of the involvement of differentially expressed genes in pathways. A. Differences in the expression of genes involved in IFIH1-mediated induction of the interferon-alpha/beta pathway in the liver were compared between the 7- and 21-day-old groups after infection with DHAV-3. * , P < 0.05; ** , 0.05 < P < 0.01; *** , P < 0.001. Expression levels of DHX58 (B), MAVS (C), IRF7 (D), IFIH1 (E) and TBK1 (F) in the livers of 7-day-old and 21-day-old Pekin ducks before and after infection with DHAV-3. NS, P > 0.05; ** , 0.05 < P < 0.01; *** , P < 0.001. Fig. 7. [131]Fig. 7 [132]Open in a new tab The levels of CD8(+) T cells in the blood at 7 and 21 days of age were compared after infection with DHAV-3 * , P < 0.05. 4. Discussion As Pekin ducks are an important part of the meat industry, they are suitable for the selection and breeding of mating lines for meat duck [133][33]. In this study, the microbial compositions of the ileum and caecum at different ages (days after hatching) were compared. We found that the ileal microbial composition and changes in microbial composition varied with age. We analysed the ileal microbiota of ducks of different ages before and after DHAV-3 infection, and six microbes at the genus level were significantly different between the 7-day-old and 21-day-old ducklings. Additionally, seven genes associated with DHAV-3 infection were identified by RNA-seq, and these genes were significantly associated with microbes in the 7-day-old and 21-day-old groups. These seven candidate genes are involoved in IFIH1-mediated induction of the interferon α/β pathway, stimulating the production of interferons and CD8(+) T cells. Phenotypic data revealed that IgA and CRP levels significantly increased in the blood of C21 ducks and that the CRP concentration decreased after DHAV3 infection in 21-day-old ducks. We believe that the presence of IgA and CRP at a certain level allows for rapid activation of a highly effective anti-infective immune response at any time; therefore, at 21 days of age, there is strong DHAV-3 resistance in the same feeding environment. To determine the effect of age on intestinal microbes, the host genetic background, feeding environment, and feed composition were controlled. The function of the duck intestine is closely related to the spatial distribution of the ileal and caecal flora. Therefore, using microbes from the ileum and caecum of these ducks at different ages, we showed that the composition of ileal microbes was more susceptible to the effects of age ([134]Fig. 1E), which was consistent with the findings related to the effect of age on the intestinal flora of broiler chickens [135][34]. This laid the foundation for our subsequent experiments. Viral infection strongly alters the structure of the intestinal microbiota [136][35]. We analysed the microflora in the ileum of Pekin ducks of the same age group before and after DHAV-3 infection. Candidatus Arthromitus was found to be the dominant genus in 7-day-old ducks and remained the dominant genus after infection with DHAV-3, although its abundance decreased significantly. Candidatus Arthromitus is an important microbe that drives the development of T helper 17 (Th17) cells in the gastrointestinal tract [137][36]. It can directly reduce the enterovirus load and affect the migration and shedding of enterocytes by promoting epithelial cell proliferation/replacement-related gene expression, which in turn affects viral passage rates and alters host viral resistance [138][37]. This difference might also explain the significant increase in the abundance of Candidatus Arthromitus in the ileum of 21-day-old ducklings infected with DHAV-3 ([139]Fig. 5B). Viral infection also increased the abundance of some microbes that are harmful to the host, e.g., Romboutsia, Corynebacterium, and Enterococcus, in 21-day-old ducklings. In this study, the percentage of beneficial bacteria decreased significantly, and the percentage of other microbial genera increased from 6.8% to 40.9% in 7-day-old ducklings. However, in 21-day-old ducklings, the increase in the level of beneficial bacteria was extremely significant, and the abundance of other microbial genera decreased from 82.7% to 32.1%, which significantly changed the microbial structure of both groups. This difference might be related to the differences in resistance to DHAV-3 in both age groups ([140]Fig. 5B). Moreover, the findings of these studies suggested that some probiotics, such as Candidatus Arthromitus, could be appropriately added to the diet to improve the resistance of ducks to DHAV-3. The intestinal flora communicates with the liver via the portal vein and bile ducts. The liver is the largest immune organ and target organ for DHAV-3 infection. Hence, we collected liver tissues for transcriptome sequencing and identified seven key DEGs. Analysis of the correlations between DEGs and differentially abundant microbes showed correlations only in the 7-day-old and 21-day-old ducklings, probably due to extreme phenotypic differences. The differences in the microbial communities between 7-day-old and 21-day-old ducklings were compared based on the KEGG pathway analysis, and the log[2]FoldChange of the immune system pathways between C7 and C21 was 1.5-fold greater than that between In7 and In21 (P < 0.05; [141]Fig. 5A). We found significant differences in antigen recognition (haematopoietic cell lineage and the RIG-I-like receptor signalling pathway) and clearance (Fc gamma R-mediated phagocytosis) between 7-day-old and 21-day-old ducklings. Haematopoietic stem cells can differentiate into a common lymphoid progenitor or a common myeloid progenitor [142][38], and specific retinoic acid-inducible gene 1-like receptors (including RIG-1, MDA5, and LGP2) are responsible for detecting viral pathogens [143][39]. The above two pathways are essential for the development of the innate immune response. Additionally, Fc gamma receptors recognize pathogens and strongly influence host defence by taking up and destroying infectious pathogens [144][40]. This might partly explain the greater susceptibility of younger ducklings. The MDA5 protein, encoded by the gene IFIH1, is a key participant in the RIG-1 signalling pathway, suggesting a link between the intestinal and liver tissue. IFIH1 is the key sensor that induces IFN-I needed for CD8(+) T-cell responses, and Fc gamma receptors can mediate the activation of T cells [145][41]. To determine whether this pathway differed between 7-day-old and 21-day-old ducklings, the percentages of CD8(+) T cells in both groups were examined. CD8(+) T cells are responsible for destroying infected cells. The presence of many CD8(+) T cells indicates that many cells are infected, as observed in this study. The long double-stranded RNA (dsRNA) produced during replication by picornaviruses can be detected in MDA5 [146][42], and DHAV-3 is a member of the family Picarnoviridae ([147]https://www.picornaviridae.com22vihepatoviruss22vihepatoviruss.ht ml). However, whether the dsRNA produced during DHAV-3 replication interacts directly with MDA5 requires further investigation. This result also provides a basis for further investigation into the pathogenesis of DHAV-3 to identify more effective molecular tags for disease resistance breeding. In this study, we investigated the changes in intestinal microbes within the same genetic background and their relationship with disease resistance from the perspectives of age-related changes and viral infection. We found that intestinal microbes participate in age-related changes and disease resistance, which provides new information for understanding the susceptibility of young animals to viruses and lays the foundation for subsequent breeding programs for enhancing disease resistance. Furthermore, the microbial composition in the ileum was correlated with age (in days). Six microbes exhibited significant differences in abundance after infection with DHAV-3. These microbes were significantly associated with seven immune-related DEGs in 7-day-old and 21-day-old ducklings. Among the seven DEGs, IFIH1 and DHX58 were involved in the pathways that induce interferon and CD8(+) T-cell production. Our findings provide a comprehensive understanding of the susceptibility of ducklings of different ages to viruses. Ethics approval and consent to participate Not applicable. Ethics Animal experiments were performed following the guidance and under the approval of the Animal Welfare and Ethics Committee of China Agricultural University and the animal care and use committee of the Institute of Animal Sciences of the Chinese Academy of Agricultural Sciences (IAS2022–116). Consent for publication Not applicable. CRediT authorship contribution statement Suyun Liang: Methodology, Data curation, Investigation, Writing – original draft. Shuisheng Hou: Resources, Data curation, Supervision, Funding acquisition. Meixi Lu: Data curation, Validation, Writing – review & editing. Daxin Yu: Data curation, Methodology. Guangnan Xing: Data curation, Methodology. Zhanqing Ji: Data curation, Methodology, Zhanbao Guo: Investigation. Qi Zhang: Investigation. Wei Huang: Investigation. Ming Xie: Investigation. All authors read and approved the final manuscript. Declaration of Competing Interest The authors declare that they have no competing interests. Acknowledgements