Throughout the study, we adhered to the principles of the Declaration of Helsinki. The cohort comprised three children (a 2-year-old boy, a 4-year-old girl, and a 7-year-old girl). Participants in our study presented with recurrent respiratory infections suggestive of primary ciliary dyskinesia (PCD), necessitating bronchoscopy-guided transmission electron microscopy (TEM) examination for definitive diagnosis. Ultimately, PCD was excluded due to negative TEM and whole-exome sequencing (WES) results, along with normal ciliary beat frequency (CBF). PCD exclusion was based on diagnostic criteria outlined in the European Respiratory Society guidelines (31). The study protocol was approved by the Ethics Review Committee of West China Second University Hospital, Sichuan University (KL118). All participating family members provided written informed consent.

The detailed procedures for obtaining NO and AO from bronchoscopy and nasal swab samples were previously described by our group (30). Briefly, nasal swabs and tracheal biopsy specimens from the same patient were preserved in DMEM and immediately transported to the laboratory on ice at 4°C. Tracheal biopsy samples were digested in digestion buffer at 37°C with shaking for 1 hour and agitated with a pipette tip every 30 minutes. Digestion was terminated with FBS, filtered through a 40-μm filter, and the cell pellet was obtained by centrifugation at 300g for 3 minutes. Nasal swabs were repeatedly rinsed with a 1-mL pipette tip to obtain sufficient cells, filtered through a 100-μm filter, and the cell pellet was obtained by centrifugation at 300g for 3 minutes. Both cell pellets were washed twice with wash buffer, centrifuged at 300g for 3 minutes, and supernatants discarded. 30 µl of Matrigel was added to each well of a 24-well plate and incubated at 37°C for 15 minutes to allow for solidification. Then, 500 µl of complete medium was added to each well, and the plate was incubated at 37°C with 5% CO₂;. The medium was changed every 4 days. Once the organoids reached a diameter of 200 µm, they were passaged and expanded. The sample was resuspended in wash medium and centrifuged at 200 g for 3 minutes. TrypLE 1× (Gibco, A1217701) was added, followed by incubation at 37°C for 10 minutes. The mixture was filtered through a 40 µm filter and centrifuged at 300g for 3 minutes to obtain the cell pellet. The pellet was washed twice with wash solution (centrifugation at 300 g for 3 minutes each time), the supernatant was discarded, and the cells were reseeded into Matrigel at a density of 5,000 cells per well. At each passage, a designated number of organoids were cryopreserved in cryopreservation solution (NCM Biotech, C40100) and stored in liquid nitrogen for future use. The WASH buffer consisted of premium DMEM/F12 containing 1× GlutaMAX, 10 mM HEPES, and antibiotics. The digestion solution comprised 1 mL of WASH buffer supplemented with 400 U/mL collagenase I (Sigma, St. Louis, MO, USA; 9001–12−1), 0.25 mg/mL trypsin E (Sigma, P5147), 10 μM Y27632 (Selleck, Houston, TX, USA; S6390), and 10 U/mL DNase I (Sigma, 10104159001). The complete medium was based on WASH buffer and contained 1× B27 (Gibco, Grand Island, New York, NY, USA, 0080085SA), 5 mM nicotinamide (Sigma, N0636), 1.25 mM N-acetylcysteine (Sigma, A0737), 500 nM SB202190 (Selleck, S1077), 500 nM A-8301 (Selleck, S8301), 500 ng/mL R-spondin1 (R&D, Minneapolis, MN, USA, 4645), 25 ng/mL recombinant human FGF7 (PeproTech, NJ, USA, 450-61), 100 ng/mL recombinant human FGF10, 100 ng/mL recombinant human Noggin (R&D, 6057), and 5 μM Y27632 (CST, Botton, MA, USA, 13624).

Total RNA was isolated from the organoids via an RNAprep Pure Micro Kit (Tiangen, Beijing, China, CA, DP420). cDNA was subsequently generated with a Transcriptor First Strand cDNA Synthesis Kit (Roche, Basel, Switzerland, 04897030001) following the manufacturer’s instructions.

Harvested organoids were fixed in 4% paraformaldehyde for 24 hours, dehydrated, embedded in paraffin, and sectioned into 5μm-thick slices. Sections underwent antigen retrieval by boiling in EDTA solution for 30 minutes, followed by blocking in 5% BSA buffer for 60 minutes to minimize non-specific staining. Primary antibodies targeting ACE-tubulin (Santa Cruz, Santa Cruz, CA, USA, sc-23950), P63 (Abcam, Cambridge, Waltham, MA, USA, ab124762), SCGB1A1 (Santa Cruz, CA, USA, sc-365992), MUC5AC (Abcam, Cambridge, Waltham, MA, USA, ab198294) were applied to the sections, followed by incubation at 4°C for 24 hours. After washing with PBS in three 10-minute intervals, sections were exposed to secondary antibodies labeled with Alexa Fluor 488 (Invitrogen, A11001) and Alexa Fluor 594 (Invitrogen, A11012) at room temperature for 1 hour. Cells were counterstained with Hoechst 33,342 (Invitrogen, Life Technologies, Carlsbad, CA, USA, H3570). The organoids were then washed three more times and sealed with anti-fluorescence quenching sealant (YEASEN, Shanghai, China, CA, 36307ES08). Finally, images were captured using a laser scanning confocal microscope (Olympus, Waltham, MA, USA).

RSV A2 (ATCC, Manassas, VA, USA VR-1540) obtained from Chongqing Medical University was cultured in HEp-2 cells (ATCC) and its viral titer was determined according to a standardized protocol (32). Infection with RSV virus was performed in a BSL-2 laboratory. Organoids with hollow lumens, grown in Matrigel domes, were gently dislodged by pipetting, digested with TrypLE for 1 min, washed twice, and centrifuged at 100g for 3 min. supernatant discarded. 2 μl virus (1 × 10⁸ pfu/ml) was added into 200μl organoid medium with sheared organoids in a 48-well plate (final virus concentration: 1 × 10⁶ pfu/mL, MOI = 10) (33). After 6 hours of incubation at 37°C and 5% CO₂;, infected organoids were washed twice with wash medium, then resuspended in Matrigel and re-seeded as described above. We added an equal volume of DPBS or interferon (1, 10, or 100 ng/mL) to the complete medium, as used in prior 2D experiments (34, 35). Plates were incubated at 37°C for 48 hours, after which supernatants and samples were collected for subsequent experiments. Based on previous cell line studies and our initial findings, the 48-hour time point was determined to be optimal for observing immune response and cellular activation (30, 36). The following human recombinant protein were exogenously added: Human IFN-α2a (PeproTech^®, Cat# 300-02AA-20UG), Human IFN-β (PeproTech^®, Cat#300-02BC-20UG), Human IFN-γ (PeproTech^®, Cat# 300-02-100UG), Human IL-29 (IFN-λ1) (PeproTech^®, Cat# 300-02L-20UG).

The droplet digital PCR procedures adhered to the manufacturer’s guidelines for the QX200 Droplet Digital PCR System utilizing the supermix for probes (no dUTP) from Bio-Rad, Hercules, CA, USA. The final reaction volume was 20 µL and comprised 10 µL of 2× supermix for probes (no dUTP) from Bio-Rad; 2 µL of cDNA derived from 100 ng of RNA from the target sample; 0.5 µL each of the RSV-N-F, RSV-N-R, and RSV-N-P primers; and 6.5 µL of nuclease-free water. The 20-µL mixture was subsequently transformed into droplets via a QX200 droplet generator from Bio-Rad. The droplet-partitioned samples were subsequently transferred to a 96-well plate, sealed, and subjected to cycling in a T100 Thermal Cycler (Bio-Rad) according to the following cycling protocol: an initial step at 95°C for 10 min for DNA polymerase activation, followed by 40 cycles of denaturation at 94°C for 30 s and annealing at 58°C for 1 min, and a final step at 98°C for 10 min, with a subsequent hold at 4°C. The cycled 96-well plate was then moved to a QX200 reader (Bio-Rad) for reading in the FAM and HEX channels.

Total RNA was extracted from the tissue using TRIzol^® Reagent according the manufacturer’s instructions. Then RNA quality was determined by 5300 Bioanalyser (Agilent) and quantified using the ND-2000 (NanoDrop Technologies). RNA purification, reverse transcription, library construction and sequencing were performed at Shanghai Majorbio Bio-pharm Biotechnology Co., Ltd. (Shanghai, China) according to the manufacturer’s instructions. The RNA-seq transcriptome library was prepared following Illumina^® Stranded mRNA Prep, Ligation (San Diego, CA) using 1μg of total RNA. the sequencing library was performed on NovaSeq X Plus platform (PE150) using NovaSeq Reagent Kit.

The raw paired end reads were trimmed and quality controlled by fastp with default parameters. Then clean reads were separately aligned to reference genome with orientation mode using HISAT2 software. The mapped reads of each sample were assembled by StringTie in a reference-based approach.

To identify DEGs (differential expression genes) between two different samples, the expression level of each transcript was calculated according to the transcripts per million reads (TPM) method. RSEM[4] was used to quantify gene abundances. Essentially, differential expression analysis was performed using the DESeq2 or DEGseq. DEGs with |log2FC|≧1 and FDR< 0.05(DESeq2) or FDR < 0.001(DEGseq) were considered to be significantly different expressed genes. In addition, functional-enrichment analysis including GO and KEGG were performed to identify which DEGs were significantly enriched in GO terms and metabolic pathways at Bonferroni-corrected P-value < 0.05 compared with the whole-transcriptome background. GO functional enrichment and KEGG pathway analysis were carried out by Goatools and Python scipy software, respectively.

Cytokines and chemokines secreted by NO-infected and AO-infected were measured and analyzed using the Bio-Plex Pro human Chemokine Panel (Bio-Rad) according to the manufacturer’s instructions. The kits used in this study included the human cytokine panel with Eotaxin, MIP-3beta, MCP-1, MIP-3alpha, PD-L1/B7-H1, MIP-1alpha, MIP-1beta, CD40 Ligand, GRO alpha, IP-10, GRO beta, IL-8, EGF, IFN-gamma, FIt-3 Ligand, G-CSF, GM-CSF, Granzyme B, IFN-alpha2, IFN-beta, TNF-beta, IL-10, IL-12p70, IL-13, IL-15, IL-17A, IL-17E, IL-9, IL-1beta, IL-1ra, IL-2, IL-3, IL-33,IL-4, IL-5, IL-6, IL-7, PDGF-AA, PDGF-AB/BB, RANTES, TGF-alpha, TNF-alpha, TRAIL, VEGF, FGF basic, IL-1alpha. Data were obtained with Luminex X-200 and analyzed with MILLIPLEX Analyst v5.1.0.0 standard build.

IFNa, IFNβ, IFN-γ levels in culture supernatants were determined with ELISA kits from R&D Systems(shanghai, China, Catalog No.VAL169,VAL137) or RayBiotech (Catalog No. ELH-IFNg) according to the manufacturer’s instructions.

The NO and AO were prepared at room temperature (25°C) for video microscopy with a 40× objective (Sprinter-HD Optronics) to eliminate the influence of environmental factors such as temperature. Three organoid model field images were available for each sample, and movies were recorded at 200 fps to record the ciliary beating frequency (CBF), which was analyzed blindly by two researchers. Kymographs of ciliary beating were depicted with a macro embedded in ImageJ (Supplementary Figure 3).

Each experiment was replicated at least three times. Statistical analyses of the demographic data were performed via Prism (version 8.3.0, GraphPad Software, San Diego, California). To compare the differences between the two groups, t tests were used for normally distributed data, whereas Wilcoxon matched-pairs signed rank tests were used for nonnormally distributed data. For comparisons between multiple groups, one-way and two-way analysis of variance (ANOVA) followed by Dunnett’s multiple comparisons test was used. The significant differences between the groups were denoted by * p < 0.05.

To investigate whether RSV triggers an innate immune response in children’s nasal and airway epithelium, we constructed the organoids and compared differences in the expression levels of various endogenous interferons in pediatric nasal and airway organoids before and after RSV infection. The highly differentiated NO and AO form hollow spheres (Supplementary Figure 1A), with no significant difference in diameter between the two types (Supplementary Figure 1C). Immunofluorescence staining confirmed the expression of all four cell types in the epithelium of both organoids under steady-state conditions (Supplementary Figure 1D). However, high-speed camera recordings of ciliary beating revealed that airway epithelial cilia beat at a higher frequency than nasal epithelial cilia (Supplementary Figure 1B), indicating structural differences between the two epithelial types.

Notably, RSV infection resulted in an increased expression of endogenous type I and II interferon mRNA expression in pediatric nasal epithelial organelles, while decreasing endogenous type I and II interferon mRNA expression in airway epithelial organelles (Figures 1A–C). Endogenous type III interferon mRNA expression levels significantly increased in both pediatric nasal and airway organoids subsequent to RSV infection (Figure 1D). Transcriptome sequencing further corroborated these findings, indicating elevated expression of IFNβ and IFNλ in nasal and airway epithelial following RSV infection (Figure 1E). To further characterize the expression levels of type I and II interferon proteins, we conducted ELISA assays. Results demonstrated that endogenous type I and II interferon protein expression in pediatric nasal and airway organoids exhibited certain limitations 48 hours after RSV infection (Figure 1F). Under bright-field microscopy, we observed significant morphological changes in both nasal and airway organoids 48 hours post-RSV infection. Organoids transformed from hollow to solid structures, exhibiting deformation and distortion (Figure 1G).

To assess whether exogenous interferon provides protection against RSV in pediatric nasal and airway epithelial models, and how this protection is influenced by the specific interferon type, dosage, and site of application. We divided pediatric nasal and airway epithelial organoids into control and intervention groups and infected with RSV for 48 hours. The intervention group received three concentration gradients (1 ng/ml, 10 ng/ml, 100 ng/ml) of four exogenous interferons (IFNa, IFNβ, IFNγ, IFNλ1) added to complete culture medium, while the control group received equivalent volumes of DPBS. Digital PCR results indicated that exogenous treatment with the four interferons (IFNa, IFNβ, IFNγ, IFNλ1) conferred protective effects on both pediatric nasal and airway epithelial cells. Digital PCR indicated that IFNα (100 ng/ml), IFNβ (10 ng/ml), IFNγ (100 ng/ml), and IFNλ1 (10 ng/ml) significantly reduced viral load in pediatric airway organoids (Figure 2A). IFNα (10 ng/ml), IFNβ (10 ng/ml), IFNγ (10 ng/ml) and IFNλ1 (100 ng/ml) significantly reduced viral load in pediatric nasal organoids (Figure 2B).

Next, to delineate the mechanism of type I interferon in pediatric nasal and airway epithelium, we performed RNA sequencing with KEGG and GSEA analyses. Volcano plots showed that IFNβ upregulates complement classical pathway components C1R and C1S in both epithelial types(Figure 3A). The Venn diagram revealed 13,315 shared genes in airway epithelium (583 unique to control, 522 unique to IFNβ), and 12,777 shared genes in nasal epithelium (437 unique to control, 817 unique to IFNβ) (Figure 3B). KEGG analysis indicated enrichment in the complement and coagulation cascades, IL-17 signaling pathway, and viral proteins interacting with cytokines-cytokine receptors (Figure 3D). GSEA analysis showed that IFNβ upregulated IFNα and IFNγ pathways but downregulated the TNFα–NFκB pathway (Figure 3C). Consistent with this, IFNβ treatment reduced mRNA levels of inflammatory cytokines (including IL6, CXCL8, IL-1a, TNF) except CXCL10 (Figure 3E), while elevating interferon-stimulated genes (ISGs) (Figure 3F). These results confirm that type I interferon suppresses pro-inflammatory cytokine expression while maintaining antiviral responses.

Similarly, to understand the mechanism of type II interferon in pediatric nasal and airway epithelium, we performed RNA sequencing with KEGG and GSEA analyses. Volcano plots showed that IFNγ upregulates human major histocompatibility complex components (HLA-A, CD74) and interferon-stimulated genes (GBP3, GBP2) in airway and nasal epithelium (Figure 4A). The Venn diagram revealed 12,814 shared genes in airway epithelium (1,084 unique to control, 707 unique to IFNγ), and 12,424 shared genes in nasal epithelium (469 unique to control, 790 unique to IFNγ) (Figure 4B). KEGG analysis indicated that in airway epithelium, IFNγ primarily enriched the Rap1 signaling pathway, PI3K-Akt signaling pathway and cellular senescence, while in nasal epithelium it mainly enriched cytokine-cytokine receptor interactions, antigen processing and presentation and viral proteins interacting with cytokines-cytokine receptors(Figure 4D). GSEA analysis showed that IFNγ upregulated IFNα and IFNγ signaling pathways in nasal epithelium, but downregulated the protein secretion pathway and PI3K-Akt-mtor pathway in airway epithelium (Figure 4C). Accordingly, IFNγ treatment upregulated CXCL10 in nasal organoids, while airway organoids exhibited increased mRNA expression of CXCL8, IL-1a, and TNF (Figure 4E). Interestingly, IFNγ broadly increased ISG mRNA expression in nasal epithelium, but only partially increased ISGs in airway epithelium (Figure 4F).

Finally, to elucidate the mechanism of type III interferon in pediatric nasal and airway epithelium, we performed RNA sequencing with KEGG and GSEA analyses. Volcano plots showed that IFNλ1 downregulates matrix metalloproteinase (MMP9) and cellular stress molecule (FOSB) in both epithelial types (Figure 5A). The Venn diagram revealed 13,434 shared genes in airway epithelium (464 unique to control, 509 unique to IFNλ1), and 12,812 shared genes in nasal epithelium (402 unique to control, 1,045 unique to IFNλ1) (Figure 5B). KEGG analysis indicated that in airway epithelium, IFNλ1 primarily enriched cell adhesion molecules, IL-17 signaling pathway and ECM-receptor interaction, while in nasal epithelium it mainly enriched cell cycle, cytokine-cytokine receptor interaction and cellular senescence (Figure 5D). GSEA analysis showed that IFNλ1 upregulated IFNα and IFNγ signaling pathways in both epithelial types (Figure 5C). Accordingly, IFNλ1 treatment decreased inflammatory cytokines (including IL6, CXCL8, IL-1a, TNF) except CXCL10 (Figure 5E), while elevating interferon-stimulated genes (ISGs) (Figure 5F). These results confirm that type III interferon also suppresses pro-inflammatory cytokine expression while maintaining antiviral responses.

To characterize host-specific changes in cytokine secretion during RSV infection, we performed a 46-cytokine Luminex assay on untreated and interferon-treated groups 48 hours post-RSV infection. The innate inflammatory response to RSV infection plays a critical role in determining disease severity, as excessive inflammation characterized by increased production of proinflammatory cytokines and chemokines is associated with more severe RSV disease, prolonged illness, and increased risk of secondary infections. To further explore inflammatory factor alterations, inflammatory factors were functionally categorized into 11 groups: chemokines, proinflammatory factors, regulatory factors, anti-inflammatory factors, hematopoietic stem cell response, allergic response, cell proliferation, antiviral response, apoptosis, Th1 response and angiogenesis.

Statistical analysis revealed distinct cytokine responses to interferon treatment in pediatric nasal and airway epithelium. For nasal epithelium (Supplementary Figure 2), IFN-λ1 treatment resulted in the most widespread suppression, significantly reducing levels of chemokines (MIP-1β, MIP-3α, MCP-1, RANTES), proinflammatory factors (GRO-β, TNF-α), hematopoietic factors (G-CSF, GM-CSF), and the cell proliferation factor TGF-α, along with angiogenesis factor VEGF. In contrast, IFN-β and IFN-γ increased the chemokines MCP-1 and RANTES, but suppressed MIP-1β, G-CSF, GM-CSF, and TGF-α. The anti-inflammatory factor IL-1α was downregulated by IFN-γ and IFN-λ but upregulated by IFN-β. For airway epithelium, IFN-γ triggered the most widespread response, significantly upregulating chemokines (MCP-1, RANTES), proinflammatory factors (GRO-α, GRO-β, IL-17A, IL-6), allergic response factors (IL-13, IL-17E, IL-9, IL-33, IL-4), and the hematopoietic factor G-CSF, while reducing the anti-inflammatory factor IL-1α. IFN-λ1 triggered a more targeted response, elevating a set of factors that included IP-10, MIP-3α, MIP-3β, GRO-α, and G-CSF. In contrast, IFN-β had a slight effect, increasing only IP-10 and the apoptosis factor TRAIL, while reducing G-CSF (Figure 6B–I).

Our data also demonstrated that the nasal epithelium mounted a more robust cytokine response than the airway epithelium following RSV infection (Figure 6A). In short, IFN-λ1 reduced the overall cytokine response in the nasal epithelium, whereas airway epithelium treated with IFN-β triggered only a minimal cytokine response.