To understand the mechanisms of vaccine-enhanced disease of RSV infection, we first established a vaccinationchallenge model in experimental BALB/c mice (Fig. 1A). We investigated pulmonary viral loads and pathology of mice inoculated with PBS or UV-RSV upon RSV infection. Viral loads in the lungs of mice were measured using RT-qPCR with specific primers to RSV L gene (Lee et al.2010) and lungs of naïve mice without any treatment used as the negative control. Expectedly, pulmonary RSV titers of mice immunized with UV-RSV exhibited significantly lower levels compared to PBS-treated mice at four different time points. The viral loads in the lungs of immunized mice exhibited a slight increase at day 2 and 4 after RSV infection, but pulmonary RSV loads of PBS-treated mice reached to approximate peak with ~104 copies (50 ng total RNA) at one day post-infection (dpi) (Fig. 1B). Interestingly, significantly lower RSV loads were observed in the lungs of both mice inoculated with UV-RSV and PBS at 6 dpi compared to that at 4 dpi. Histopathological analysis showed that the pathological changes in lung tissues of both mice vaccinated with UV-RSV and PBS were observed at 1 dpi based on the thickness of interalveolar septa, inflammatory cell infiltration in peribronchial and perivascular areas. However, from 2 to 6 dpi, the histopathology scores in lung tissues of PBS-treated mice gradually reduced; in contrast, the pulmonary inflammation and tissue damage progressively increased in immunized mice (Fig. 1C, Table 1). These results revealed kinetics of viral loads and pathological changes in the lungs of mice vaccinated with inactivated RSV or PBS upon RSV infection, suggesting that the fourth day after virus infection is an ideal set-up for evaluating RSV virology and pathology in mice.
Figure 1. RSV load and histopathologic changes of lung tissues from PBS-treated and UV-RSV vaccinated mice upon RSV challenge. A The scheme of the vaccination and challenge. B Lungs from BALB/c mice inoculated with UV-RSV or PBS were harvested at days 1, 2, 4 and 6 post-challenge, and RSV L gene copies in lung tissues were measured by RT-qPCR. Data are presented as mean ± SD of two independent experiments for 6 individual mice, and pairwise comparisons of values were performed using a t test or oneway ANOVA. ***P < 0.001; **P < 0.01; ns, not significant. C Photomicrographs of lung tissue sections stained with hematoxylin and eosin (magnification, × 200). Arrows indicate inflammatory infiltration and injury.
dpi Groups Histopathology scorea Alveolar tissue Peribronchial spaces Perivascular spaces 1 PBS 2.38 ± 0.24 1.93 ± 0.36 1.92 ± 0.33 UV-RSV 2.62 ± 0.12 2.02 ± 0.12 1.97 ± 0.23 2 PBS 1.98 ± 0.33 1.72 ± 0.27 1.72 ± 0.37 UV-RSV 2.50 ± 0.28 2.02 ± 0.17 1.98 ± 0.20 4 PBS 1.42 ± 0.13 1.48 ± 0.21 1.48 ± 0.16 UV-RSV 3.55 ± 0.25 2.78 ± 0.19 2.73 ± 0.20 6 PBS 1.60 ± 0.17 1.62 ± 0.17 1.50 ± 0.18 UV-RSV 3.17 ± 0.47 2.50 ± 0.34 2.45 ± 0.34 aThe histological scores were blindly evaluated by the degree of inflammation in alveolar tissue, peribronchial and perivascular spaces. Scores ranged from 0 (normal) to 3 or 4 (severe), as described in Materials and Methods. Data represent the mean ± SD (n = 6).
Table 1. Histopathology score of lungs in PBS-treated and UVRSV vaccinated mice after RSV challenge.
Distinct CD4+ T cell subsets played key roles in RSV vaccine-enhanced immunopathology (Connors et al. 1992; Knudson et al. 2015). We investigated CD4+CD25+Foxp3+ regulatory T cells (Treg), IFN-γ-producing (IFN-γ+) (Th1) and IL-4- producing (IL-4+) CD4+ (Th2) T cell subsets in lungs of UV-RSV immunized and PBS-treated mice subsequent RSV infection at indicated time points, respectively (Fig. 2A). The total numbers of Treg-, Th1- and Th2- signature staining of CD4+ T cells in the lung from PBS treated and UV-RSV vaccinated mice were determined, and the ratios of Treg, Th1 and Th2 cell subsets to the total amount of CD4+ T cells were calculated, respectively. Importantly, at early time infection, similar numbers and ratios of Treg, Th1 and Th2 cell subsets were observed between UV-RSVimmunized and PBS-treated mice (P > 0.05) (Fig. 2B, 2C). However, mice immunized with UV-RSV exhibited significantly lower numbers and ratio of Treg cells and higher numbers and ratios of Th1 and Th2 T cell subsets compared to PBS-treated mice at days 4 and 6 following RSV challenge (Fig. 2B, 2C).
Figure 2. The percentage of Treg, Th1 and Th2 subsets of CD4+ T cells in lungs of UV-RSV vaccinated or PBS control mice after RSV challenge. The CD25+ Foxp3+ Treg, IFN-γ+ Th1 or IL-4+ Th2 cells in CD4+ T cells from lungs were measured by flow cytometry with specific antibody staining. A Representative Treg-, Th1- and Th2- signature staining of CD4+ T cells in the lung from PBS control and UV-RSV vaccinated mice. Plots were gated on CD4+ T cells. B The total numbers of Treg-, Th1- and Th2- signature staining of CD4+ T cells in the lung from PBS treated and UV-RSV vaccinated mice. C The percentage of Treg, Th1 and Th2 subsets within that gate. Data are shown as mean ± SD of five individual mice from two independent experiments. Pairwise comparisons of values were performed using a t test or one-way ANOVA. ***P < 0.001; **P < 0.01; *P < 0.05; ns, not significant.
Many T helper cell (Th) subsets are characterized by specific cytokine profiles. Cytokines produced by the Th subsets played a critical role in immune cell differentiation, activation of effector T cells and in preventing autoimmune and inflammatory diseases. We measured the concentrations of Th1-type (IFN-γ, IL-2, TNF-α), Th2-type (IL-4, IL-5, IL 10), Th17-related (IL-6, IL-17) and TNF-β cytokines in lung homogenates of UV-RSV immunized and PBS-treated mice upon RSV infection by cytokine ELISA. Data showed that compared to PBS-treated mice, cytokines IL-2, IL-4, IL-5, IL-10, TNF-α and TNF-β displayed higher concentrations and cytokines IL-6 and IL-17 were present at lower levels in UV-RSV immunized mice (Fig. 3). In UV-RSV immunized mice, IFN-γ concentration reached to approximate 20 × 103 pg/g lung tissue at 1 dpi and preserved a similar level at indicated time points (Fig. 3). However, in PBStreated mice, a low level of IFN-γ production was observed from 1 to 4 dpi and IFN-γ concentration significantly increased at 6 dpi (Fig. 3).
Figure 3. Cytokine profiles of lungs from vaccinated or control mice following RSV challenge. Th1-type (IFN-r, IL-2 and TNF-α), Th2- type (IL-4, IL-5 and IL-10), Th17-related (IL-6 and IL-17) and TNF-β cytokines concentrations were measured by ELISA. Data are presented as mean ± SD of five individual mice from two independent experiments. Pairwise comparisons of values were performed using a t test or one-way ANOVA. ***P < 0.001; **P < 0.01; *P < 0.05; ns, not significant.
To characterize the kinetics of host responses in immunized mice subsequent RSV challenge, the transcriptome profiles in lungs of the experimental mice were analyzed by RNA-sequencing (RNA-seq). We first identified differentially expressed genes between the PBS-treated or UVRSV-immunized mice and naïve mice for each time point using the following criteria: > two fold change; false-discovery rate [q] of < 0.05, as determined by Limma's empirical Bayes moderated t test (Fig. 4). In total, 5582 genes with 2974 up-regulated and 2608 down-regulated genes were differentially expressed in at least one treatment and at one point (Supplementary Table S1). For PBStreated mice, the host transcriptome response was immediate and a total of 2890 DE genes with 1695 up-regulated and 1195 down-regulated genes were observed at 1 dpi. At 2, 4 and 6 dpi, total DE genes were 2394, 1703 and 2986, respectively; and the number of DE genes reached the maximum number at 6 dpi (Fig. 4A; Supplementary Table S2). For mice vaccinated with UV-RSV, the host transcriptome profile showed decreased expression pattern at early infection. Total 1933 DE genes with 1178 upregulated and 755 down-regulated genes were observed at 1 dpi. The DE genes reached peak values with a total of 2950 (1623 up-regulated and 1327 down-regulated) at 4 dpi. At 2 and 6 dpi, total DE genes were 2063 and 2442, respectively (Fig. 4A; Supplementary Table S2). Among DE genes, the largest number of overlapping genes between two conditions existed at 6 dpi; but the least number of overlapping genes was observed at 4 dpi (Fig. 4B).
Figure 4. The gene expression profiles in lungs of UV-RSV vaccinated or PBS-treated (control) mice following RSV challenge. A Numbers of up-regulated (red) and down-regulated (green) differentially expressed (DE) genes after RSV infection compared to mocks. Criteria used for differential expression analysis are a q value of < 0.05 and |log2 FC| > 1. B Venn diagram showing the overlap of differentially expressed genes (up-regulated, red; down-regulated, green) in mouse lungs following RSV challenge. C The heatmap depicting the expression pattern of clustered DE genes at least one time point. DE genes were clustered in 6 clusters based on the expression pattern. Functional enrichment for each cluster is presented in Table 2 and in Supplementary Table S3. Data were generated from three individual mice in one experiment.
Using this DE profile, the 5582 DE genes were grouped in 6 clusters (Fig. 4C, Table 2). Total 2078 genes were upregulated and 1584 genes down-regulated in both PBStreated and UV-RSV vaccinated groups. The 344 upregulated and 389 down-regulated DE genes were observed in UV-RSV vaccinated mice, respectively. For PBS-treated mice, the 521 transcripts were up-regulated and 594 transcripts were down-regulated (Fig. 4C, Supplementary Table S3). Moreover, the DE genes in cluster 1, the early up-regulated transcription (at 1 & 2 dpi) was observed in PBS-treated and the late up-regulated responses (at 4 & 6 dpi) were observed in UV-RSV vaccinated mice (Fig. 4C). Th1-related genes such as Il18r1, Relb, Gadd45g, Sema4a, Ccr2, Il12rb1, and Il12b were up-regulated at 1 and 2 dpi in both PBS-treated and UV-RSV vaccinated mice. However, for UV-RSV vaccinated mice, the Th17-related genes (Il23a, Il21, and Il15) were down-regulated at 1 dpi; and Th2-associated genes (CD74, Il33, Idol, Mcm2, Arg1, Xcl1, Ccl1, Ccl11, Ccl8, Ccr5, Ccr9, and Ccr4), genes involved in CD8 T cell cytotoxicity (Gzmb, Ctsc, Ctsh, Serpinb9, Raet1e, and Raet1d) and positive regulation of B cells proliferation (Atad5, Il13, Nfatc2, and Cd38) were upregulated at 4 and 6 dpi.
Clusters Gene count Representative GO functional enrichmenta (P value) Cluster 1 2078 Immune system process, inflammatory response, immune response, response to virus, cell cycle, apoptotic process, antigen processing and presentation, TNF signaling pathway Cluster 2 521 Inflammatory response, immune system process, PI3K-Akt signaling pathway, TNF signaling pathway Cluster 3 344 Extracellular exosome, membrane, peptidase activity Cluster 4 594 Cilium movement, cell projection, Cluster 5 389 Angiogenesis, cell surface, calcium ion binding Cluster 6 1584 Cell adhesion, cilium movement, angiogenesis, multicellular organism development, cell surface, cell junction, Rap1 signaling pathway, Calcium signaling pathway, cAMP signaling pathway aRepresentative Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) categories are enriched by hypergeometric (FDR-adjusted P value < 0.05). Table S4 in the supplemental material for all enriched GO and KEGG categories and their corresponding P values.
Table 2. Representative GO and KEGG functional enrichment of six clusters.
Next, we performed Gene Ontology (GO) and Kyoto Encyclopedia of Genes and Genomes (KEGG) pathway analysis for each cluster. Among up-regulated DE genes in both conditions (Cluster 1), the biological processes were mainly involved in immune response, inflammatory response, and regulation of immune or inflammatory response (Supplementary Table S4). Up-regulated genes in both conditions involved in pathways mainly included immune response pathways such as cytokine-cytokine receptor interaction, antigen processing, and presentation, TLR signaling pathway, Jak-STAT signaling pathway, natural killer cell-mediated cytotoxicity (Supplementary Table S4). In contrast, downregulated DE genes in both conditions (Cluster 6) mainly mediated cell adhesion, angiogenesis, multicellular organism development, and intracellular signal transduction (Supplementary Table S4). The KEGG pathways were mainly involved in the Rap1 signaling pathway, calcium signaling pathway, cAMP signaling pathway, and circadian entrainment (Supplementary Table S4).
To explore regulatory mechanisms of DE genes for RSV vaccine-enhanced disease, we constructed dynamic networks by integrating gene expression data into PPI data. Eleven conserved high-influential modules (HMs) were recognized from the initial PPI network (Supplementary Table S5). Differential expression profiles of 11 HMs between PBS-treated and UV-RSV vaccinated mice were identified. Compared with PBS-treated mice, the lower expression patterns of DE genes in 11 HMs were observed in UV-RSV vaccinated mice at 1 and 2 dpi (Fig. 5).
Figure 5. Dynamic characteristics of high-influential modules in lungs of UV-RSV vaccinated or PBS-treated (control) mice following RSV challenge. Dynamic networks were constructed by integrating gene expression data into PPI data, and the corresponding modules were identified using ClusterONE algorithm (Nepusz et al. 2012) and a model-based framework (Li et al. 2015). Eleven high-influential modules were detected as highly connected groups of transcripts. Average log2 fold change values of DE genes in 11 high-influential modules were shown for PBS-treated and UV-RSV vaccinated groups. Transcripts and functional enrichment of 11 HMs were shown in Table 3 and in Supplementary Tables S5 & S6.
GO functional enrichment of the 11 HMs can be classified into 1195 categories (Supplementary Table S6). Representative GO functions and genes of each HM were shown in Table 3. The functional HMs were mainly grouped into the cell cycle and cell metabolism (HM1, HM4, HM5), signal transduction (HM2, HM3, HM7), and immune and inflammatory responses (HM6, HM8, HM9, HM10, HM11) (Table 3 and Supplementary Table S6). The largest high-influential module (HM1) consisting of 237 genes was mainly involved in fundamental biological processes including cell cycle, DNA replication, cellular response to DNA damage stimulus, and microtubule-based movement.
HMs Gene counts Representative GO functional enrichmenta (P value) Representative genes HM 1 237 Cell cycle, DNA replication, cellular response to DNA damage stimulus, microtubule based movement Cdk1, MCM7, MCM8, BRCA1, CHAF1B, TICRR HM 2 53 Protein ubiquitination, intracellular signal transduction, ubiquitin protein ligase activity, ubiquitin mediated proteolysis UBE2L6, KLHL13, SOCS3, SOCS1, SIAH1B PTGER4, GLP1R, PTGIR, CALCRL, PTGER2, GCGR, ADRB1 HM 3 41 Adenylate cyclase-activating G-protein coupled receptor signaling pathway, positive regulation of camp biosynthetic process, G-protein coupled receptor signaling pathway, camp-mediated signaling, neuroactive ligand-receptor interaction, vascular smooth muscle contraction, calcium signaling pathway Ly6k, Cpm, Lypd8, Cntn4, Vnn1, Vnn3 HM 4 28 Anchored component of membrane, cell adhesion molecules (cams), pantothenate and coa biosynthesis Col5a1, Col5a2, Col1a1 Col1a2, Col4a1, Col4a2, Col6a1 HM 5 39 Collagen fibril organization, cell adhesion, cellular response to amino acid stimulus, extracellular matrix structural constituent, metal ion binding, protein digestion and absorption, ECM-receptor interaction, PI3K-Akt signaling pathway Ifih1, Ifit3, Ifit1, Dhx58, Mx1, Dhx58 HM 6 78 Defense response to virus, negative regulation of viral genome replication, immune system process, innate immune response, double-stranded RNA binding, Influenza A, herpes simplex infection Avpr1a, Adra1b, Bdkrb1, Chrm3, Mchr1, P2ry1, P2ry6 HM 7 53 Signal transduction, G-protein coupled receptor signaling pathway, positive regulation of cytosolic calcium ion concentration, neuroactive ligand-receptor interaction, calcium signaling pathway H2-T23, H2-M3, Fcgr4, CD14, Tap2, Tap1, H2-T3 HM 8 61 Antigen processing and presentation of peptide antigen via MHC class I, immune system process, adaptive immune response, peptide antigen binding, receptor binding, phagosome, graft-versus-host disease Slc11a1, Cd59a, Cd59b, Cyba, Cd53, Cybb HM 9 44 Positive regulation of phagocytosis, cell surface receptor signaling pathway, respiratory burst, inflammatory response, complement and coagulation cascades Gsdmd, B2m, Orm2, Orm3, Pglyrp1 HM 10 41 Defense response to Gram-positive bacterium, acute-phase response, immune system process Psma5, Psma4, Psmb2, Psmb8, Psmb9, Psmb10 HM 11 37 Antigen processing and presentation of exogenous peptide antigen via MHC class I, TAP-dependent, proteolysis involved in cellular protein catabolic process, proteolysis, threonine-type endopeptidase activity, peptidase activity, proteasome, NF-kappa B signaling pathway Psma7 aRepresentative GO and Kyoto Encyclopedia of Genes and Genomes (KEGG)categories are enriched by hypergeometric (FDR-adjusted P value < 0.05). Table S6 in the supplemental material for all enriched GO and KEGG categories and their corresponding P values.
Table 3. The representative GO and KEGG functional enrichment of eleven conserved high-influential modules.
The characteristics of regulatory networks can be related to the degree of a node and the number of links that a node shares with nodes of a higher degree. It is commonly believed that nodes of a higher degree are more important and form the core of the network. We further analyzed network characteristics of two selected high-influential modules, HM5 (related to lung injury and fibrosis) and HM8 (related to immune response). At 1 dpi, the highly connected genes (hub genes) in HM5 networks were Col5a2, Col1a1, Col6a1, and Col11a2 in PBS-treated group or Col3a1 and Col6a2 in UV-RSV group; but in HM5 network at 4 dpi, the sixteen hub genes including Col3a1, Col5a2, Col1a2 and P4ha3 existed in PBS-treated group and the seventeen hub genes including Col5a1, Col1a2 Col1a1 Col3a1 and Plod2 in UV-RSV vaccinated group (Supplementary Fig. S1, up). For HM8 network, the twenty-two or thirty-two hub genes were observed in PBStreated or UV-RSV vaccinated group at 1 dpi, respectively. However, at 4 dpi, the number of the hub genes was twenty-two genes in the PBS-treated group or twenty-five genes in the UV-RSV group, respectively (Supplementary Fig. S1, down).
To verify the transcriptome data, eight selected genes (Col4a1, Col5a1, Col5a2, Col6a1, Cxcr2, Ptafr, Fpr1, Lilrb4a) were confirmed by RT-qPCR. Data showed that the mRNA expression levels of these genes were consistent with those determined from the transcriptome sequencing data (Fig. 6). Therefore, the DE genes database from transcriptional sequencing is reliable and may be further investigated.
Figure 6. Quantitative RT-PCR analysis of selected genes. Both gene expression levels from RNA sequencing data and quantitative values by RT-qPCR were shown. The glyceraldehyde-3-phosphate dehydrogenase (GAPDH) gene was used as an internal control, and the relative expression level of each gene was calculated by comparative 2-△△CT method. Data were presented as mean ± SD of five individual mice from two independent experiments.
So far, there is no licensed RSV vaccine for clinical use. The VED induced by inactivated RSV is a major obstacle to develop efficacious vaccines. Understanding the mechanisms of the RSV pathogenesis and the host response to RSV infection is important for the development of RSV vaccines. In this study, we first established an RSV vaccination-challenge mouse model and investigated the host immune response to RSV infection and immunopathology induced by inactivated RSV. Then, we performed a systematic analysis of the gene expression profiles in mouse lungs after RSV infection for 6 days, and described the dynamic host responses to RSV infection and VED immunopathology.
Previous studies demonstrated that the VED induced by inactivated RSV was ascribed to unbalanced, skewed Th2- type immune responses upon RSV challenge (Waris et al.1996). Some cytokines regulated immune responses by promoting the differentiation of T cell subsets and Treg cells, which could prevent Th2-biased immune responses during RSV infection (Durant et al. 2013; Yang et al.2020). In our study, the significantly higher expression levels of IL-4, IL-5, IL-10 and TNF-β in lungs of UV-RSV vaccinated mice were observed at four time points; in contrast, cytokines IL-6 and IL-17 were significantly lower in vaccinated mice. Compared to PBS-treated mice, the concentration of Th1 cytokines IFN-γ and IL-2 were significantly higher in vaccinated mice from 1 to 4 days after RSV infection. For the CD4+ T cells, a similar percentage of Treg, Th1 or Th2 among total CD4+ T cells was observed in PBS-treated and vaccinated groups at early time-points (1 and 2 dpi). At 4 and 6 dpi, there was a significantly higher proportion of Th1 or Th2 in lungs of vaccinated mice compared to that of PBS controls, indicative of a mixed Th1- and Th2-type response; but the percentage of Treg cells always kept at a low level in vaccinated mice from 1 to 6 dpi. Previous reports showed that Treg cells played a central role in preventing immunopathology induced by RSV infection by dampening pathological effector T cell responses and limiting Th2- type immune responses (Durant et al. 2013; Li et al. 2016). These results suggested that differentiation and activation of different CD4+ T cell subsets appeared prior to the changes of cytokine secretion. Our results first revealed the dynamic expression characteristic of different cytokines. In addition, we only employed BALB/c mice as an animal model in this study. Other mouse strains such as C57BL/6 (Gueders et al. 2009) should be used to investigate potentially different immune and transcriptome responses.
Dynamic data-driven meta-analysis of vaccinationchallenge mouse model will facilitate the understanding of the molecular pathogenesis of RSV vaccine-enhanced disease. Here, we generated the dynamic transcriptome data of lungs from UV-RSV vaccinated and PBS-treated mice from 1 to 6 dpi. We constructed dynamic networks by integrating DE gene expression data into PPI data and identified eleven high-influential modules in networks using ClusterONE algorithm (Nepusz et al. 2012) and a model-based framework (Li et al. 2015). The specific DE gene expression pattern and differential network characteristics were observed in vaccination-challenge mice. For PBS-treated mice, the minimum number of DE genes was observed at 4 dpi; but in UV-RSV vaccinated mice, the number of DE genes reached peak values at 4 dpi (Fig. 4A). However, the least overlapping DE genes between PBS-treated and UV-RSV vaccinated mice existed at 4 dpi (Fig. 4B).
Transcriptome analyses have been employed to investigate the functions of genes, host response to pathogens, and viral pathogenesis (Liu et al. 2017; Peng et al. 2011; Xue et al. 2014). Analysis of transcriptome profile showed that the maximum number of DE genes was clustered in Cluster 1 (up-regulated expression of both conditions) (Fig. 4C). Interestingly, these up-regulated transcripts were observed at early infection in PBS-treated mice, but at late infection in UV-RSV vaccinated mice (Fig. 4C). The genes were functionally enriched for immune and inflammatory response, apoptotic process, the extracellular matrix, and antigen processing and presentation (Table 2), suggesting that mice vaccinated with inactivated RSV resulted in delayed immune responses to RSV infection.
Network-based approaches are widely used to identify normal and disease states by exploring dynamic and network information of omics data from both animal models and clinical samples (Chen et al. 2012; Jin et al. 2014; Yang et al. 2018). We recognized eleven high-influential modules (HMs) (Table 3 and Supplementary Table S5) by network-based approaches. The genes in the HMs exhibited down-regulated expression in UV-RSV vaccinated mice at early RSV infection (Fig. 5). Our previous studies demonstrated that co-expression of immune regulators resulted in induction of balanced immune response to RSV, alleviating vaccine-enhanced disease (Yang et al. 2020; Zhang et al. 2016). By analyzing regulatory networks of two representative high-influential modules (HM5 and HM8), we identified that for HM5 associated with functions of the extracellular matrix (ECM), hub genes mainly existed at late infection. Dysregulation of the ECM composition and structure was closely related to some human diseases including fibrosis (Bonnans et al. 2014). In contrast, for HM8 associated with immune response and antigen processing and presentation, most of the hub genes encoded classical major histocompatibility complex class II (MHC-II) molecules. MHC-II presents antigens to CD4+ T cells, which is critical for the expansion and function of CD4+ T cells during host immune responses (Takeda et al.1996). The hub genes in HM8 were tightly co-regulated at one dpi in UV-RSV vaccinated groups (Supplementary Fig. S1). These results indicated that the regulatory networks associated with immunopathology functionally activated at late infection in both conditions. Actions of regulatory networks related to immune response initiated at one dpi in both conditions, but it was to a certain extent inhibited at late infection in vaccinated mice.
Taken together, our results provide valuable information to our understanding of immunopathology and antiviral immune responses by inactivated RSV vaccination. These findings could contribute to the development of novel RSV vaccines and the potential therapeutic interventions for RSV infection.