Human iPSC-derived airway models enable comparative analysis of SARS-CoV-2 infection in healthy and COPD bronchial epithelium

Lisa Morichon; Jitendriya Swain; Nathalie Gros; Amel Nasri; Florent Foisset; Gaetan Galisot; Victor Racine; Said Assou; Arnaud Bourdin; John De Vos; Delphine Muriaux

doi:10.1016/j.isci.2026.114741

. 2026 Jan 23;29(3):114741. doi: 10.1016/j.isci.2026.114741

Human iPSC-derived airway models enable comparative analysis of SARS-CoV-2 infection in healthy and COPD bronchial epithelium

Lisa Morichon ^1,², Jitendriya Swain ^1,³, Nathalie Gros ¹, Amel Nasri ², Florent Foisset ², Gaetan Galisot ⁴, Victor Racine ⁴, Said Assou ², Arnaud Bourdin ^5,⁶, John De Vos ^2,^∗, Delphine Muriaux ^1,^3,^7,^∗∗

PMCID: PMC12955582 PMID: 41782833

Summary

SARS-CoV-2 causes severe and persistent lower respiratory tract infections, yet human models that recapitulate long-term tissue responses are limited. Here, we used a human induced pluripotent stem cell (hiPSC)-derived bronchial airway models (iALI) to investigate SARS-CoV-2 infection in healthy and COPD-derived tissues. Infection of iALI led to robust viral replication, persistent infection, cilia loss in infected ciliated epithelial cells, increased mucus secretion, and higher inflammatory cytokine release in COPD iALI. Notably, healthy iALI displayed a delayed innate immune response, whereas COPD iALI exhibited an earlier and stronger response, characterized by elevated IL-2, CCL5, G-CSF, and CXCL10 secretion, along with reduced sensitivity to antiviral treatment. These findings reveal donor-specific differences in bronchial epithelial responses to SARS-CoV-2 and establish iALI culture models as a powerful platform for studying long-term respiratory viral infections in both healthy and diseased contexts, especially COPD.

Subject areas: Immunology, Virology, Stem cells research, Infection control in health technology

Graphical abstract

Highlights

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Human iPSC-derived bronchial airway models (iALI)
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SARS-CoV-2 infection persists in healthy and COPD iALI over days
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Cilia loss and increased mucus upon SARS-CoV-2 infection in both iALI
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Enhanced innate and inflammatory response in COPD iALI

Immunology; Virology; Stem cells research; Infection control in health technology; Chronic Obstructiv Pulmonnary disease

Introduction

Chronic obstructive pulmonary disease (COPD) is the fourth leading cause of death worldwide, accounting for 3.5 million deaths in 2021, approximately 5% of all global deaths (WHO, November 4^th 2024). Primarily caused by exposure to harmful particles, particularly cigarette smoke in westernized countries, COPD is characterized by chronic bronchitis and emphysema.¹^,²^,³ This disease starts and progresses at the small airway level narrowed by thickened walls, excessive mucus secretion and chronic inflammation, worsened by loss of alveolar attachments. Recent studies have shown that COPD patients have a 4-fold increased risk for severe clinical outcomes—including hospitalization, ICU admission, and mortality—when infected with COVID-19.⁴^,⁵^,⁶^,⁷ This heightened susceptibility may be due to the elevated expression of ACE2 in the lungs of smokers and individuals with COPD,⁸^,⁹^,¹⁰ impaired muco-ciliary clearance (MCC)²^,¹¹^,¹²^,¹³^,¹⁴ and/or dysregulated immunity,¹^,²^,¹⁵^,¹⁶ although controversies persist. Traditionally, COPD research has relied on blood samples,¹⁷ lobectomies,¹⁸ or murine organoids.¹⁹^,²⁰ However, the recent development of lung organoid models has greatly broadened the scope of research. Since the onset of the COVID-19 pandemic, airway epithelium models have been extensively used to investigate SARS-CoV-2 pathophysiology.¹²^,²¹^,²²^,²³

In vitro airway models are created using progenitors derived either from primary samples of the upper (nasal or tracheal) or lower (bronchial or alveolar) airways, or by differentiation of induced pluripotent stem cells (iPSCs). The advantage of using primary progenitor cells lies in their origin from adult lungs, which retain both the genetic and epigenetic traces of each individual.²⁴^,²⁵ This allows mature epithelia to be obtained and pathological phenotypes to be reproduced,¹⁰^,²⁶ but also lead to high interindividual variability in results. Moreover, primary organoids are expensive and limited in quantity. In contrast, the process of reprogramming somatic cells into iPSCs, from blood mononuclear cells (PBMCs) for example,²⁷ eliminates epigenetic marks,²⁸^,²⁹ and allows them to be amplified in cell culture almost without limit. It is therefore possible to genetically modify iPSCs and reproduce all the experiments required for a project from a single donor. In addition, iPSCs differentiation produces both airway epithelium and mesenchyme, which provides physiological support for the epithelium and improves its survival³⁰ through time and aggressions. However, the epithelium obtained is less mature than those derived from primary cells.³¹^,³²^,³³

Few airway models derived from primary progenitors were used to investigate the response of COPD to SARS-CoV-2 infection.¹⁰^,³⁴^,³⁵^,³⁶ The first model involved an air liquid interface (ALI) culture of COPD human bronchial epithelial cells (NHBE), which successfully reproduced COPD phenotypes, including basal and goblet cell hyperplasia and squamous metaplasia. This model demonstrated a high susceptibility of goblet cells to SARS-CoV-2 infection.³⁴ A second study used NHBE and human nasopharyngeal epithelial cells and differentiated them in apical out airway organoids.¹⁰ These models also exhibited characteristics of the COPD phenotype, including goblet cells hyperplasia and reduced ciliary beat frequency. Both studies showed higher SARS-CoV-2 replication rates in COPD airway models, exacerbating the pathophysiology of COPD. In contrary, recent study demonstrated lower SARS-CoV-2 infection and inflammatory response in COPD human airway epithelia (HAE) as compared to healthy HAE, associated with protective characteristics of COPD HAE.³⁵ It is important to note, that all these studies focus on early response to infection and did not investigate tissue response on the long-term after infection. Overall, the available results still lack comparative data and investigation of long-term infection tissue impact.

Here, we propose another in vitro preclinical airway model, called iALI, derived from human induced pluripotent stem cells (iPSC) and cultured at the air-liquid interface (ALI), named iALI, to study COPD and SARS-CoV-2 infection.³⁰ Working on iPSC-derived bronchial epithelium obtained from healthy and COPD primary blood mononucleated cells, we demonstrated successful persistent infection of both healthy and COPD iALIs for up to 21 days. We highlight tissue response to infection, as well as the epithelium innate immune response. Our results show that the iALI model is relevant to study the COPD pathology, SARS-CoV-2 infection over the long term, antiviral drug testing as pre-clinical models and it opens the possibility to target molecular pathways and explore the long-term impact of SARS-CoV-2 infection in the airways.

Results

Human iPSC-derived bronchial models capture key features of COPD

Multi-ciliated bronchial epithelium were established by methods previously reported³⁰ from 3 different iPSC cell lines derived from 1 healthy donor (HY03) and 2 very severe and early COPD patients (iCOPD2 and iCOPD9) (Figure 1A).²⁷^,³⁷ Chronic obstructive pulmonary diseases (COPD) is known for impaired epithelial phenotype including goblet cells hyperplasia, basal cell hyperplasia, and inflammation.²^,¹⁶^,³⁴^,³⁸^,³⁹^,⁴⁰ HES staining of paraffin embedded cross section confirmed proper morphology of iALI with pseudostratified cylindrical bronchial epithelium, cilia at the apical side and under the basal membrane a thick layer of mesenchyme sometimes including cartilage (Figure 1B; Figure S1). Immunofluorescence staining of cross-sections demonstrated the presence of ciliated cells (CDHR3), goblet cells (MUC5AC), basal cells (KTR5 and P63), and club cells (SCGB1A1) (Figures 1C–1E). Quantification of gene expression in bronchial epithelial iALI models was done by RT-qPCR. Ciliated cells levels were evaluated by FOXJ1 and CCDC40 relative gene expression (Figure 2A), goblet cells with MUC5AC and MUC5B (Figure 2B), basal cells with KRT5 and P63 (Figure 2C), neuroendocrine cells with CHGA (Figure 2D), and club cells with SCGB1A1 (Figure 2E). Analysis of iALI revealed a significant increased relative expression of goblet cell markers (MUC5AC and MUC5B) and basal cell markers (KRT5 and P63) in the COPD iALI compared to healthy iALI (Figures 2B and 2C). Goblet cell hypertrophy was confirmed by analysis of PAS-BA stained cross sections that shows a significant increase in mucus containing cells especially in iCOPD9 and a tendency in iCOPD2 (Figure 2F). Quantification of P63 positively stained nucleus also validated a significant increase of basal cells levels both in iCOPD2 and iCOPD9 as compared to healthy iALI (Figure 2G).

Imaging characterization of bronchial epithelial structure in iALI models

(A) Schematic representation of iALI production protocol and epithelial cells composition.

(B) iALI epithelial morphology was confirmed by hematoxylin eosin safran (HES) staining.

(C–E) The epithelial cells presence was evaluated by immunofluorescence (IF) of iALI cross sections. Representative IF images of iALI stained for ciliated cells (green, CDHR3): (C), goblet cells (yellow, Muc5Ac): (D), basal cells (pink, KRT5): (D) and yellow, p63: (E) and club cells (pink, SCGB1A1): (E) Scale bar is 50 μm. See also Figure S1.

Comparison of the cellular gene composition and imaging of iALI bronchial models derived from iPS of healthy and COPD patients

(A–E) Epithelial cells presence in non-infected HY03 (N = 5, n = 7), iCOPD2 (N = 2, n = 4) and iCOPD9 (N = 4, n = 9) iALI was confirmed with the measure of gene expression relative to GAPDH by RT-qPCR. Human lung total RNA was used as a positive control to measure the expression of ciliated cells (*FOXJ1, CCDC40*: (A), goblet cells (*MUC5AC, MUC5B*: (B), basal cells (*KRT5, P63*: (C), club cells (*SCGB1A1*: (D) and neuroendocrine cells (*CHGA*: (E).

(F) Periodic acidic Schiff and blue alcian (PAS-BA) staining of HY03 (N = 2, n = 6), iCOPD2 (N = 1, n = 4), and iCODP9 (N = 2, n = 8) iALI allowed quantification of goblet cells (dark pink and purple).

(G) Quantitative analysis of basal cells levels (red, P63) in HY03 (n = 2), iCOPD2 (n = 2) and iCOPD9 (n = 2) iALI.

(A–G) ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001, NS represents not significant, (A–E) two-way ANOVA with Sidak multiple comparisons test. (F and G) one-way ANOVA with Dunnett’s multiple comparisons post-test. N= number of experiments, n = number of analyzed samples. See also Figure S2. Data are represented as mean ± SD.

FOXJ1 is a key transcription factor involved in ciliogenesis, and its expression increased significantly in iCOPD in comparison to healthy iALI (Figure 2A). This could suggest that iCOPD might contain a higher proportion of ciliated cells—the primary targets of SARS-CoV-2—and might therefore be more susceptible to infection. iCOPD cultures also showed significantly higher expression of MUC5AC and MUC5B, two marker genes of mucus-producing goblet cells, compared with healthy iALI cultures (Figure 2B). Consistently, PAS-BEA staining of iALI cross-sections revealed an increased number of goblet cells in iCOPD models (Figure 2F), which may influence infection dynamics (see next sections). Finally, basal-cell markers were more abundant in iCOPD cultures, as indicated by elevated KRT5 and p63 transcript levels (Figure 2C) and by increased protein abundance measured by quantitative immunofluorescence (Figure 2G), while club and neuroendocrine cells remain unchanged (Figures 2D and 2E), suggesting that iCOPD cultures might sustain infection over time, as basal cells can serve as a reservoir for the regeneration of ciliated cells.²¹

Our results validate proper differentiation of iPSc into main different cell types of the bronchial airway epithelium, but revealing some differences between healthy and COPD iALI models.

Furthermore, inflammation was assessed by measuring the relative expression of genes involved in innate immune response pathways. At steady state, CXCL5, CXCL10, IFI35, and OAS2 were significantly increased in iCOPD2 samples, but no difference was found in iCOPD9 samples at a non-stimulated state (Figure S2). Cytokine expression levels were also measured by flow immunoassay and revealed no difference at rest between healthy and COPD iALI (Figure S3). So, iALI derived from COPD iPSc reproduces COPD characteristics, that are signed by a hypertrophy of goblet cells accompanied with increased mucus, basal cells increase and a latent inflammatory state. These results suggest either a COPD’s genetic susceptibility present in both COPD donors or maintenance of some epigenetic features despite reprogramming process of iPSC.

SARS-CoV-2 infects ciliated epithelium in iPSC-derived bronchial iALI models

Air-liquid interface culture promotes tissue polarization, positioning epithelial cells on the apical surface of the iALI models as well as within certain deeper tissue invaginations (Figures S1 and S4). To assess the susceptibility of iALI to infection by the SARS-CoV-2 Delta variant, viral dilutions were applied to the apical side (Figure 3A) at an estimated multiplicity of infection (MOI) of 0.05 (2.5 × 10ˆ5 PFU/well). Successful infection was confirmed by positive staining of the SARS-CoV-2 membrane protein in cross-sections of healthy iALI at 3 and 11 dpi (Figure 3B). Virus was detected from day 1 to day 11 in airway epithelial cells at the iALI surface, as shown by immunostaining of infected healthy iALI, with a peak of infection at day 3 pi (Figure S4A). At later time points (days 18–24 pi), viral signal was observed deeper in tissue circonvolutions, most probably indicating viruses trapped in mucus plugs (Figure S4A). Consistently, HES-stained cross-sections reveal that the apical epithelial surface progressively decreases over the course of infection (Figures S4B and S4C).

SARS-CoV-2 infection in Healthy and COPD iALI models

(A) Schematic representation of iALI infection and collection parameters.

(B) SARS-CoV-2 infection was visualized by HES staining and labeling for SARS-CoV-2 membrane (Virus M, green) healthy non-infected and infected (3 dpi and11 dpi) iALI cross section.

(C) RT-qPCR analysis of viral envelope gene relative expression compared to GAPDH was done in the HY03 (N = 4), iCOPD2 (N = 3) and iCOPD9 (N = 5) infected iALI cells.

(D) RT-qPCR quantifications of apical wash viral envelope gene on HY03 (N = 5, n = 9), iCOPD2 (N = 4, n = 4), iCOPD9 (N = 4, n = 7).

(E and F) Viral titer was measured by plaque assay in apical wash of HY03 (N = 3), iCOPD2 (N = 4), iCOPD9 (N = 4). Representative images of plaque assays at 1- and 6-day post infection (E).

(G–I) HY03 and iCOPD2 iALI were treated with DMSO (0.1%) or Remdesivir (10 μM) 2 h prior infection by SARS-CoV-2 (Delta, MOI = 0, 05). (G) Viral RNA (gene E) relative expression to GAPDH was measured by RT-qPCR in iALI cell lysates 96 hpi. (H) Quantification by RT-qPCR of viral RNA (gene E) released every day post infection at the apical side of treated iALI is presented as gene E concentration. (I) Viral particles released at the apical 2dpi were quantify by plaque assays. (C–I) ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001, two-way ANOVA with Sidak’s (C and G) or Tukey’s (D and F) multiple comparisons post-test. N= number of experiments, n = number of analyzed samples. See also Figure S4. Data are represented as mean ± SD.

Infection levels were quantified by RT-qPCR analysis of SARS-CoV-2 gene E relative expression in iALI cell lysates at multiple time points post-infection (Figure 3C). Although some variability was observed between experiments, viral replication was significantly reduced in iCOPD9 iALI compared with healthy HY03 at 1 dpi, and at 3, 4, and 6 dpi compared with iCOPD2. In contrast, despite an initial decrease at 1 dpi, viral replication was significantly higher at 6 dpi in iCOPD2 iALI relative to HY03. Viral release was further assessed in daily apical washes by measuring the absolute concentration of gene E by RT-qPCR (Figure 3D) and by plaque assay to quantify infectious titers (Figures 3E and 3F). Across all samples, viral production peaked at 2–3 dpi and subsequently declined, yet remained detectable up to 21 dpi. Except for a lower gene E concentration in iCOPD9 iALI at 2 dpi compared with HY03, no significant differences were detected among HY03, iCOPD2, and iCOPD9 iALI. Moreover, ACE2 and TMPRSS2 relative gene expression levels were comparable in non-infected and infected iALI from HY03, iCOPD2, and iCOPD9 (Figures S1B and S1C), indicating that viral entry should be similar across samples.

Lastly, SARS-CoV-2 infection and replication in healthy and iCOPD2 iALI were inhibited by Remdesivir, an antiviral drug targeting the viral RNA-dependent RNA polymerase, confirming effective infection of the iALI models (Figures 3G–3I). The inhibitor reduced viral infectivity in both healthy and COPD iALI. Surprisingly, Remdesivir was less effective in iCOPD2 than in healthy iALI, with viral log10 reductions of 1.58 and 2.16 at 2 dpi, respectively (Figures 3G–3I). Overall, our data indicate that both HY03 and COPD iALI are susceptible to SARS-CoV-2 infection, although iCOPD are less sensitive to antivirals.

Enhanced mucus production in iALI models limits SARS-CoV-2 infection

The impact of SARS-CoV-2 infection on the healthy iALI model was first visualized and quantified using HES-stained cross-sectional images (see Materials and Methods), comparing infected and non-infected healthy iALI cultures over time. We observed a progressive decrease in the relative epithelial area over the course of infection (1–11 dpi) (Figures S4B and S4C) suggesting a destruction of the epithelium by the viral infection, with a marked decrease of the apical epithelial tissue layers (Figure S4C), which became strongly infected over time as shown by immunofluorescence (Figure S4A).

Further consequences of infection on the bronchial epithelium were assessed by measuring the relative expression of cellular biomarkers in infected versus non-infected iALI using RT-qPCR (Figure 4). Although no significant differences were detected, both HY03 and COPD iALI showed a trend toward increased expression of goblet cell and basal cell markers upon infection. Mucus-producing cells were also quantified in PAS-BA-stained cross-sections (Figures 5A and 5B). The results reveal a significant increase in goblet cell numbers in healthy iALI at 3 dpi and 11 dpi. As previously described, goblet cell abundance and area are significantly higher in iCOPD compared with HY03 iALI (Figures 2B and 2F). Interestingly, mucus levels in healthy iALI at 11 dpi and in iCOPD at 1 dpi are similar, suggesting that iCOPD models exhibit a strongly elevated basal mucus state. We next examined the impact of SARS-CoV-2 infection on ciliated cells (Figures 5C–5E). Cilia (TUBIV) and SARS-CoV-2 membrane protein (Virus M) were labeled in healthy and COPD iALI, both non-infected and infected (3 dpi) (Figure 5C). High-resolution fluorescence imaging confirmed infection, particularly in ciliated cells, and revealed marked cilia destruction in regions with high viral load. Quantification showed a significant reduction in ciliated cells in infected samples—approximately 25% in HY03 iALI and 30% in iCOPD iALI (Figures 5D and 5E). Thus, infected iALI models reproduce key pathological features observed in primary bronchial epithelium following SARS-CoV-2 infection (10, 34, and 35), including increased mucus secretion by goblet cells and loss of ciliated cells (Figure 5). Despite clear differences between infected and non-infected samples, no major differences were observed between HY03 and COPD epithelial responses to SARS-CoV-2 infection.

Impact of SARS-CoV-2 infection on the relative gene expression of known cellular biomarkers in healthy and COPD iALI models

(A–E) Epithelial cells presence in non-infected HY03 (N = 5, n = 7), iCOPD2 (N = 2, n = 4), and iCOPD9 (N = 4, n = 9) iALI and SARS-CoV2 infected HY03 (N = 6, n = 10), iCOPD2 (N = 3, n = 9), and iCOPD9 (N = 4, n = 9) iALI was confirmed with the measure of gene expression relative to GAPDH by RT-qPCR. Human lung total RNA was used as a positive control. The gene expression of known biomarkers of ciliated cells (*FOXJ1*, *CCDC40*: A), goblet cells (*MUC5AC*, *MUC5B*: B), basal cells (*KRT5*, *P63*: C), club cells (*SCGB1A1*: D) and neuroendocrine cells (*CHGA*: E) were assessed in HY and COPD iALI. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001, NS represents not significant, (A–E) two-way ANOVA with Tukey’s multiple comparisons test. Data are represented as mean ± SD.

Impact of SARS-CoV-2 infection on healthy and COPD iALI models

(A) Representative imaging of periodic acidic schiff and Blue acian (PAS-BA) staining of non-infected and infected HY03 and iCOPD2 iALI.

(B) Quantification of goblet cells (dark pink and purple) normalized to full sample area on non-infected and infected HY03 iALI (N = 2, n = 6), iCOPD2 (N = 1, n = 4), and iCODP9 (N = 2, n = 8). (B) High resolutions images confirmed infections by staining SARS-CoV-2 (green, Virus membrane) and cilia (orange, TubIV) on non-infected and infected (3 dpi) healthy and iCOPD2 iALI. Scale bars, 5 μm.

(C) High resolution 3D images of non-infected and infected (3 dpi) HY03 and iCOPD9 iALI stained for ciliated cell (Yellow, Tub IV), Virus (Virus membrane, green).

(D and E) Quantifications of the percentage of TubIV-positively stained area for both infected and non-infected (3 dpi) HY03 and iCOPD2 on 47 regions of interest (25 μm × 25 μm). Representative images, scale bars, 100 μm (A) 5 μM (C) and 50 μm (D). ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001, NS represents not significant, one-way ANOVA with Tukey’s multiple comparisons post-test (B), two-way ANOVA with Sidak multiple comparisons post-test (E). N= number of experiments, n = total number of analyzed samples. See also Figure S5. Data are represented as mean ± SD.

Further preliminary analyses were done to investigate the impact of mucus in SARS-CoV-2 infection. To enhance mucus production, healthy iALI were treated with 0, 10, or 30 ng/mL of IL13 one-week previous infection with SARS-CoV-2. We first confirmed that IL13 treatment increased the production of mucus by measuring expression of goblet cells marker by RT-qPCR and mucin quantity at the apical side by dot blot (Figures S5A, S5B, S5E, and S5F). IL13 treatment did not impact ciliated cells (Figures S5C–S5D) but impacted virus load in the cells and virus release at the apical side (Figures S5G–S5H). We observe that IL13 treatment increases the relative expression of intracellular viral RNA but decrease viral release suggesting that the virus might be trapped inside iALI, restraining its release outside the cells, due to an increase of mucus at the iALI surface.

If we apply this hypothesis to our results on HY and COPD iALI, we propose that the excess of mucus produce by iCOPD (Figures 5A and 5B) could trap the virus and cause a reduced viral release at the apical side (Figures 3D–3F) and an increase of virus inside, like for iCOPD2 (Figure 3C). In conclusion, COPD patients’ response to infection could depend on a balance between mucus trapping the virus in the airway epithelium and strong innate immune response. Thus, we explore and compare the innate immune response in SARS-CoV-2 infected healthy iALI and iCOPD.

iCOPD bronchial models exhibit an enhanced innate and inflammatory response to SARS-CoV-2

Innate immune response to infection was evaluated by measuring the expression of 25 common interferon-stimulated (ISG) using RT-qPCR for gene expression in HY03 iALI, iCOPD2, and iCOPD9 at 1, 4, 11, and 18 dpi (Figure 6A; Figures S2 and S6). Although not every experiment yielded samples at all time points, the experimental design was optimized to ensure that each donor was represented with at first three time points. At early time points in HY03 iALI, increased expression of only few of these genes was observed in infected conditions with only IFIT1, ISG15, and OAS2 significantly higher at 1 and 4 dpi, plus MX1 at 4 dpi. IFIT1 and ISG15 gene expressions were also always found significantly increased at 1, 4, and 11 dpi for both COPD iALI, as well as several others. For iCOPD2, we also found higher expressions of IFIH1, MX1, MX2, ITFM3, and OAS2 at 1 dpi and of MX1 and CXCL10 for iCOPD9. At 4 dpi for both COPD iALI, there was an overexpression of IFI35 and ITFM3. Infected iCOPD9 iALI presents a significant increased expression of these following genes at 4 dpi: CXCL10, IFI44, IFIT3, IFIH1, ISG15, MX1, MX2, OAS2, and ITFM1. At 11 and 18 dpi, we compared innate immune response in HY03 and iCOPD2 iALI. At 11 dpi, IFIT1, ISG15, and OAS1 were commonly significantly overexpressed. While iCOPD2 had a persistent significantly increased expression of only IFI35, surprisingly HY03 iALI showed a significant over expression of several interferon pathway genes: IFI27, IFIT3, MX1, MX2, and OAS2. At 18 dpi, although not statistically significant, we keep a similar pattern than at 11 dpi (Figure S6).

Cellular gene expression and protein secretion of inflammasome and innate immune responses in SARS-CoV-2 infected healthy and COPD iALI

(A) Relative gene expression levels of innate immune response genes in non-infected (NI) and infected (INF) healthy iALI (HY03), iCOPD2, and iCOPD9 models at 1, 4, 11, and 18 days post-infection (dpi). Relative gene expression of *CXCL10*, *CXCL20*, *IL6*, *IL32*, *IFI27*, *IFI35*, *IFI44*, *IFIT1*, *IFIT3*, *IFIH1*, *ISG15*, *IRF9*, *OAS1*, *MX1*, *MX2*, *ITFM1*, *ITFM3*, *CXCL3*, *NFKBIA*, *OAS2*, *CXCL5*, *PLOD2*, and *IL1b* were analyzed using RT-qPCR. Integrity of the tissue is shown by ITGB1 and GJA1 relative gene expression. Each value represents the difference from the log2 relative gene expression to GAPDH gene median and is depicted according to the color scale shown at the right (−15 to 5). Each experiment is coded with an alphabet letter (i.e., A to J).

(B) Significantly overexpressed genes in infected compared to non-infected samples at 1, 4, and 11 days post-infection (dpi) in one or more iALI models are represented as a Venn diagram.

(C) Protein secretion analysis of the innate immune response in SARS-CoV-2-infected iALI models at 4 days post-infection (dpi). Inflammation and innate immune responses in healthy (HY03) and COPD iALI models were assessed at the protein level using a multi-analyte flow assay targeting key cytokine storm effectors associated with COVID-19 (IL-6, CCL2, G-CSF, CCL5, IL-2, IL-7, CXCL8, TNFα, CXCL10, and IL-10) in non-infected and infected samples (4 dpi). Data are presented as a heatmap, where each value represents the deviation from the median of the log2-transformed protein concentration normalized to total protein. Values are depicted according to the color scale shown on the right (range: −5 to 5). Each experiment is coded with an alphabet letter (i.e., A to J).

(D) Mean innate immune response for CCL5 (RANTES), G-CSF, CXCL10, and IL-2 protein concentration measured by legend-plex and normalized to total protein concentration in non infected or 4 dpi from healthy iALI (HY03) and iCOPD (n = 3 independent experiments). Data are presented as the mean of the normalized protein concentration. ∗p < 0.05, ∗∗p < 0.01, ∗∗∗p < 0.001, ∗∗∗∗p < 0.0001, NS represents not significant, two-way ANOVA with Sidak’s multiple comparisons post-test. NI: non infected; INF: SARS-CoV-2 infected. See also Figures S3, S6 and Table S3. Data are represented as mean ± SD.

Our results show a reproducible heterogeneous pattern of the response to the SARS-CoV-2 infection between iCOPD9 and iCOPD2 iALI models over time, suggesting that COPD patients do not respond in an equivalent manner. It is also important to note that expression levels detected in infected iCOPD2 samples were often significantly higher than for HY03 and iCOPD9 iALI, for instance: CXCL20, IFI35, IFIH1, ISG15, CXCL5, ITFM3, and NFKBIA (Figure S2). In summary, innate immune response to SARS-CoV-2 infection was more important at 1 dpi for iCOPD2, at 4 dpi for iCOPD9 and 11 dpi for HY03 iALI. IFIT1 and ISG15 were overexpressed in every iALI at 1, 4, and 11 dpi. MX1, MX2, and OAS2 were successively overexpressed in iCOPD2 at 1 dpi, iCOPD9 at 4 dpi and HY03 at 11 dpi, so albeit that they represented a common pattern at the peak of innate immune response. COPD iALI responded earlier and stronger to SARS-CoV-2 infection with a common pattern to the 2 patients including overexpression of interferon-stimulated genes MX1 at 1 dpi, IFI35 and IFITM3 4 dpi, which are known cellular proteins involved in viral restriction.⁴¹^,⁴²^,⁴³^,⁴⁴^,⁴⁵^,⁴⁶

Moreover, pro-inflammatory cytokine secretion induced by SARS-CoV-2 infection of iALI models was evaluated by measuring cytokines released in apical wash at 4 dpi with flow immunoassays (Figure S3). CCL5, IL2, G-CSF, and CXCL10 relative expression was found significantly higher in infected COPD iALI. Interestingly, IL2 is one of the biomarkers in COPD patients to predict prognostic in respiratory failure.⁴⁷ Collectively, iALI cytokine secretion in response to SARS-CoV-2 infection is significantly more pronounced in iCOPD as compared to healthy iALI.

Overall, our results suggest that iALI bronchial models allowed for assessing individual innate immune response to infection. While our results are coherent with known SARS-CoV-2 induced ISG response, they revealed intrinsic differences between healthy and the two COPD patient response. Despite expected heterogeneities, further investigation could bring knowledge on COPD pathology and its response to viral infection for each individual.

Discussion

Our work shows that iPSC-derived bronchial iALI models are an excellent bronchial epithelium model for reproducing several COPD characteristics, and for studying long lasting virus replication in bronchial tissue from healthy and COPD patients, opening doors for mechanistic studies and a better understanding of the contribution of genetic or epigenetic changes to the disease. As previously published,³⁰ results confirm efficiency of our differentiation protocol of iPSC into functional airway epithelium. Nevertheless, we observed unexpected differences between iALI models produced from HY03 and COPD iPSC. Indeed, reprogramming of somatic cells into iPSC is known to erase most of the epigenetics features to reset gene expression to a pluripotent state.⁴⁸^,⁴⁹^,⁵⁰ Recent studies have nonetheless proven maintenance of some donor specific DNA methylation and gene expression in iPSC.⁵¹^,⁵²^,⁵³^,⁵⁴ In our work, iPSC were reprogrammed from blood cells and not airway cells that would most likely carry epigenetic marks induced by noxious particles exposition. So, we hypothesize that donors iCOPD2 and iCOPD9 have some genetic predisposition to COPD associated to impaired immune response to SARS-CoV-2 infection. Indeed, the two donors were considered light smokers compared to other COPD patients but still developed a severe form of COPD very early in life and reported a familial history of COPD (Table S1).

FOXJ1 gene expression involved in ciliogenesis increases significantly in iCOPD (Figure 2A). This suggests that iCOPD may contain a higher proportion of ciliated cells—the primary targets of SARS-CoV-2—and may therefore be more susceptible to infection than iCOPD. Thus, we expected a downregulation of FOXJ1 gene upon SARS-CoV-2 infection as the virus destroyed ciliated cells and as it was reported previously,⁵⁵ but we failed in observing such a decrease, most likely due to the fact that we looked at time points that might be too early after infection (1–4 dpi) (Figure 4A). Similarly, no apparent differences are observed between iALI and iCOPD9 in terms of ciliated-cell destruction as measured by immunofluorescence confocal microscopy (Figures 5C–5F). However, basal-cell markers are more abundant in iCOPD samples (Figure 2G) suggesting that iCOPD cultures may sustain infection over time as shown for SARS-CoV-2 infected iCOPD2 (Figures 3C and 3D), as basal cells can serve as a reservoir for the regeneration of ciliated cells²¹ that are destroyed by the virus upon the course of infection (Figures 5C–5E).

iCOPD cultures express significantly higher levels of MUC5AC and MUC5B, and have more mucus-producing goblet cells compared with healthy iALI (Figures 2B and 2F; Figures 5A and 5B). SARS-CoV-2-infected iCOPD also show increased expression of MUC5AC and MUC5B (Figure 4B), indicating that COPD cells secrete more mucus upon infection, as reported¹². The overproduction of mucus during SARS-CoV-2 infection and in the basal state of COPD can have two opposite consequences: the secretion of soluble mucins may interfere with viral entry and therefore act as an antiviral mechanism, but mucus can also accumulate and impair mucociliary clearance, an effect further exacerbated by the destruction of infected ciliated cells. Thus, the increase in mucin secretion during infection is likely to be harmful to bronchial lung tissue over the course of infection.

SARS-CoV-2 successfully infected iALI and impacted the airway epithelium similarly to what has been previously reported, notably cell shedding,¹¹ cilia disruption,¹¹^,²² and mucus secretion.⁵⁶^,⁵⁷ The early innate immune response observed is also consistent with results described in primary organoids.¹⁰^,³⁴^,³⁵ We especially note expression of well-known antiviral restriction ISGs such as OAS2, IFT1, IFITM3, and MX1.⁴¹^,⁴²^,⁴³^,⁴⁴^,⁴⁵^,⁴⁶^,⁵⁸ ISG15, IFIT1, IFIT3, IFI44, and CXCL10 were found over expressed in another primary air-liquid interface lung model.⁵⁹ MX1, ISG15, IFI44, and IFITM1 were significantly increased in infected bronchioalveolar air-liquid interface model derived from fetal lung bud tip organoids.⁶⁰ iPSC-derived models reported overexpression of OAS2, IFIT1, IFIT3, IFI44, MX1, and ISG15 in the airway⁶¹ and IFITM1 and IFI35 in the alveolus.³⁶ This pattern closely mirrors the induction seen in our iALI models and highlights the robust innate antiviral responses elicited by these systems. Together, these findings underscore the value of iPSC-derived airways as physiologically relevant platforms for studying antiviral restriction factors.

Our main finding at the protein level is the notable increase in the secretion of CCL5, IL-2, G-CSF, and CXCL10 in SARS-CoV-2-infected iALI cultures compared with non-infected controls, in both healthy and COPD models (Figures 6C and 6D). This correlates with a concomitant upregulation of IFIT1 and ISG15 genes in all infected samples and over time (Figures 6A and 6B), reflecting the activation of inflammatory and interferon-mediated antiviral responses in lung epithelial tissue upon SARS-CoV-2 infection (see Table S3) and a dysregulation of the immune response in the iALI tissue cultures upon SARS-CoV-2 infection. In addition, CCL5, CXCL10, and IL-2 concentrations were significantly higher in infected iCOPD cultures (Figure 6D), which was associated with increased expression of IFITM1/3, CXCL10, MX1/2, and other interferon-stimulated and inflammatory genes involved in viral restriction (Figures 6A and 6B). Furthermore, these markers were significantly more overexpressed in infected iCOPD samples compared with infected healthy iALI, suggesting that COPD-derived airway epithelia are more prone to inflammation and heightened antiviral signaling upon SARS-CoV-2 infection. The high secretion of IL-2, CCL5, CXCL10, and G-CSF by the infected iALI culture models (Figure 6D) reflects an inflammatory/antiviral response of the tissue to infection (see Table S3), which normally serves to recruit immune cells such as T cells and macrophages—cells that are absent in the iALI models. In addition, CXCL10, a pro-inflammatory cytokine, is highly secreted in SARS-CoV-2 infected iCOPD (Figure 6D), suggesting that a high inflammatory state of iCOPD upon infection (Figure 6) that suggests the tissue to be more prone to the uncontrolled cytokine release (“cytokine storm”). This phenotype was described associated with COVID-19 and CXCL10 was proposed as a biomarker of poor disease prognosis (https://doi.org/10.3390/ijms23073673).

Previous preclinical models of COPD developed from lung progenitor cells have produced conflicting results, as recently reported,¹⁰^,³⁴^,³⁵ notably showing a reduced innate immune response to SARS-CoV-2 infection.¹⁰^,³⁵ However, a major limitation of these previous studies may be the short duration (3–4 days post-infection, dpi) over which SARS-CoV-2 infection was assessed. In contrast, our iALI bronchial cultures contain a thick layer of mesenchymal cells, which likely contributes to maintaining epithelial viability and stability for more than three weeks.

From 4 dpi up to 18 dpi, our results demonstrate that SARS-CoV-2 infection persists over time and reveal distinct responses between iALI and iCOPD models. Notably, we observed donor-specific disparities between iCOPD cultures, particularly in the intensity of their innate immune responses to SARS-CoV-2 infection (Figure 6). The variation of innate immune response correlates with the viral RNA measured in iALI. At one day post-infection, it is striking that viral replication is significantly lower in COPD iALI than in healthy that do not show, yet, innate immune response. But at 4 days post-infection, iCOPD2 iALI shows highest viral replication and lowest innate immune response. In contrast, significantly lower intracellular viral replication was observed in iCOPD9 as compared to iCOPD2 iALI. Indeed, iCOPD9 shows the strongest innate immune response at 4 days post-infection. We thus observed an early and high innate interferon responses limiting viral replication in COPD iALI. In contrast, HY03 iALI donor only shows an innate immune response at 11 days post-infection, when the peak of viral infection has passed. Unfortunately, we were unable to analyze iCOPD9 iALI donors at 11 days post-infection to determine whether their innate immune response was sustaining further.

It is noteworthy that the level of mucus in iCOPD is already at a high level at 1 dpi in contrario to healthy iALI that never reach this level even 11 dpi which can have some consequences on (1) sensing SARS-CoV-2 and (2) on the antiviral responses. It was reported that upon SARS-CoV-2 infection ALI cultures secret more mucus with more inflammation and shows a destruction of the ciliated cells, that creates a decrease in the mucociliary clearance in infected ALI cultures.¹²^,⁵⁵^,⁶² In mirror to these studies, we propose that the excess of mucus production in iCOPD models (Figures 5A and 5B) is most probably due to a basal inflammation state in the iCOPD models (Figure 6). In consequences, this may contribute to a reduced viral release at the apical side (Figures 3D–3F) and an increased intracellular viral load observed in iCOPD2 (Figure 3C) due to a trapping of the virus in the oversecreted mucus that cannot be cleared due to the loss of cilia in infected ciliated cells (Figures 5B and 5C).

However, the lower viral load detected in iCOPD9 may be explained by its early and robust innate immune response (Figure 6). Overall, the response of COPD airway epithelium to SARS-CoV-2 infection may depend on a delicate balance between mucus-mediated viral trapping and the strength of the innate immune response. This balance could help explain why COPD patients are not necessarily more susceptible to SARS-CoV-2 infection, yet exhibit a 4-fold increased risk of developing severe clinical outcomes.⁴^,⁵^,⁶

Finally, a major limitation of viral infection response studies using iALI models, as well as those performed on primary airway epithelium, is the absence of immune cells. To improve physiological relevance, future developments of the iALI lung models should aim to incorporate co-cultures with immune cells derived from the same iPS line—an approach that remains technically challenging and difficult to achieve.

In conclusion, our study using iALI bronchial models revealed donor-specific differences that modulated their responses to airway infection. It is important to note that these variations, which we hypothesize may reflect genetic predispositions, could also arise from heterogeneous iPS reprogramming efficiency or differences in donor sex, age, and medical history (Table S1). A more definitive understanding of COPD-related mechanisms would require a larger cohort of donors, which was beyond the scope of the present study.

Overall, our results indicate that iALI models respond rapidly to SARS-CoV-2 infection with a strong functional and interferon-mediated response, consistent with findings reported in the literature.¹¹^,²²^,³⁶^,⁴¹^,⁴²^,⁴³^,⁴⁴^,⁴⁵^,⁴⁶^,⁵⁶^,⁵⁷^,⁵⁹^,⁶⁰ The observed variability between donors could be linked to our previous hypothesis of individual genetic predisposition to COPD, that might impact differently the cells and therefore the inflammation and innate immune response of the tissue, despite the absence of immune cells. Nevertheless, our results show a higher and earlier innate immune response to SARS-CoV-2 in COPD samples, which correlates with clinical data reporting high susceptibility to a severe form of COVID-19,⁴^,⁵^,⁶^,⁷ and suggests that SARS-CoV-2 infection is more likely to trigger an early cytokine storm in patients with COPD, less response to antivirals and more chance to develop severe COVID-19.

Limitations of the study

This study has several limitations. First, experiments were performed using in vitro iALI culture models, which may not fully recapitulate the complexity of the human airway in vivo, including immune cell interactions and systemic responses. Second, the number of biological donors was limited, which may restrict the generalizability of the findings across diverse patient populations. Third, while SARS-CoV-2 persistence was observed over several days, longer-term infection dynamics and potential viral evolution were not assessed. Finally, this study focused on a single viral strain; therefore, the impact of emerging variants on infection persistence and epithelial damage remains to be determined.

Resource availability

Lead contact

Further information and requests for resources and reagents should be directed to and will be fulfilled by the lead contact, Dr. Delphine Muriaux (delphine.muriaux@irim.cnrs.fr).

Materials availability

All unique reagents generated in this study are available from the lead contact with a completed Materials Transfer Agreement.

Data and code availability

Data: All data supporting the findings of this study are available from the lead contact upon reasonable request.

Code: All code supporting the findings of this study are available from the lead contact.

Other items: All other items supporting the findings of this study are available from the lead contact upon reasonable request.

Acknowledgments

We are grateful to CEMIPAI UAR3725 CNRS/University of Montpellier, France for supporting BSL3 facility and Microscopy and for excellent technical services. We especially thank Christine Chable-Bessia and Sebastien Lyonnais from CEMIPAI for BSL3 and Microscopy maintenance. We thank Carine Bourdais, Agathe Cœur, and Cecilia Urena from IRMB for iALI culture technical advices and their much-needed help for maintenance over week-ends. We also thank Romane Pisteur, master student, who draw the epithelium scheme.

We acknowledge the “Réseau d’Histologie Expérimentale de Montpellier”—RHEM facility for histology techniques and expertise. RHEM facility is supported by SIRIC Montpellier Cancer grant INCa_Inserm_DGOS_12553, REACT-EU (Recovery Assistance for Cohesion and the Territories of Europe), IBiSA, Ligue contre le cancer, the Occitanie/Pyrénées-Méditerranée and GIS FC3R whose funds are managed by Inserm.

This study was funded by the Centre National de la Recherche Scientifique en Biologie (the CNRS VIROCRIB project granted to D.M. and J.D.V.).

Author contributions

Conceptualization, resources: D.M. and J.D.V.; methodology, validation, data curation: D.M., J.D.V., N.G., J.S., F.F., A.N., L.M., V.R., and S.A.; formal analysis, investigation: L.M., J.S., and G.G.; writing – original draft: L.M. and D.M.; writing – review and editing: L.M., D.M., J.D.V., A.B., S.A., and V.R.; visualization: L.M., J.S., and D.M.; supervision, project administration and funding acquisition: D.M. and J.D.V.

Declaration of interests

V.R. and G.G. are employee and shareholder of QuantaCell company. V.R. is a founder of QuantaCell and a member of its scientific advisory board.

Declaration of generative AI and AI-assisted technologies in the writing process

During the preparation of this work the author(s) used ChatGPT in order to improve the quality of the English for manuscript editing. After using this tool/service, the author(s) reviewed and edited the content as needed and take(s) full responsibility for the content of the published article.

STAR★Methods

Key resources table

REAGENT or RESOURCE	SOURCE	IDENTIFIER
Antibodies

Rabbit Polyclonal anti-M SARS-CoV-2	Abnova	Cat#PAB31758
Mouse Monoclonal anti-β-TubIV	Sigma	Cat#T7941; RRID: AB_261775
Goat polyclonal anti-human anti-P63	R&D systems	Cat# AF1916; RIID: AB_2207174
Rabbit polyclonal anti-CDHR3	Sigma	Cat# HPA011218; RRIDAB_1078886
Mouse monoclonal anti-Muc5A	Abcam	Cat# ab3649; RRID: AB_2146844
Rabbit polyclonal anti-KRT5	Thermofisher	Cat# PA1-37974; RRID: AB_2134167
Rabbit polyclonal anti-CC10	Biovendor	Cat#RD181022220-01
Donkey anti-Rabbit Alexa Fluor 488	Invitrogen	Cat#A21206; RRID: AB_2535792
Donkey Anti-Goat IgG H&L (Alexa Fluor 488)	Abcam	Cat# ab150129; RRID: AB_2687506
Donkey polyclonal anti-Mouse IgG (H+L) (Alexa Fluor 555)	Invitrogen	Cat# A-31570, RRID: AB_2536180
Donkey anti-rabbit IgG H&L Alexa Fluor® 647	Abcam	Cat#ab150075; RRID: AB_2752244
Mouse monoclonal anti-MUC5AC antibody	Thermo Fisher	Cat#MA5-12178; RRID: AB_10978001
Goat anti-Mouse IgG (H+L), DyLight™ 800	Thermo Fisher	Cat#SA5-35521; RRID: AB_2556774

Bacterial and virus strains

Delta (B.1.617.2) hCoV-19/France/HDF-IPP11602i/2021	National Reference Centre for Respiratory Viruses hosted by Institut Pasteur (Paris, France)

Chemicals, peptides, and recombinant proteins

Ficoll-Paque PLUS density gradient	GE Healthcare	GE17-1440-02
foetal bovine serum (FBS)	Thermo Fisher
StemSpan Erythroid Expansion Medium	SSEM, StemCell Technologies	09860
DMEM F12	Thermo Fisher	31331028
E8 medium	Thermo Fisher	A1517001
RPMI 1640	Thermo Fischer	21875034
Versene Solution	Thermo Fisher	15040066
Geltrex	Thermo Fisher	A141302
B-27™ (50X) without A vitamin	Thermo Fischer	12587010
Activin A	Gibco	AF-120-14E; CAS: 1381885-28-4
Y-27632 dihydrochloride	Biotechne	1254/1 ; CAS : 129830-38-2
CHIR-99021	Biotechne	4423/10 ; CAS : 252917-06-9
LDN-193189	Biotechne	6053/1; CAS: 1435934-00-1
DAPT	Biotechne	2634/10; CAS: 208255-80-5
Remdesivir	Tebu-bio	T7766; CAS: 1809249-37-3
Xylene	VWR	28973.294; CAS:1330-20-7
Sodium citrate pH 6 buffer	Sigma	C9999, CAS: 68-04-2
PneumaCult-ALI Medium	Stem cell technologies	05001
4′,6-diamidino-2-phenylindole (DAPI)	Sigma	D9542; CAS: 28718-90-3
Aqueous mounting media	Biorad	BUF058B
Recombinant human IL-13	PeproTech	200-13
Blocking Buffer for Fluorescent Western Blotting	Tebubio	MB-070

Critical commercial assays

QIAshredder kit	QIAGEN	79656
RNeasy mini kit	QIAGEN	74104
Luna Universal One-Step RT-qPCR Kit	Biolabs	E3005E
NucleoSpin Dx Virus	Macherey-Nagel	740895.50
ELISA-based LEGENDplex COVID-19 Cytokine Storm Panel 1 (14-plex) with V-bottom Plate	Biolegend	741089
non-integrating CytoTune-iPSC 2.0 Sendai Reprogramming kit	ThermoFisher	A16517
Transwell (Ø 12mm)	DUTSCHER	3460

Deposited data

Original RTqPCR datasets of Figures 2 and 4		Supplemental Excel files

Experimental models: Cell lines

HY03	University Hospital of Montpellier (UHOM)	UHOMi002-A (RRID: CVCL_A1NX)
iCOPD2	University Hospital of Montpellier (UHOM)	UHOMi003-A (RRID: CVCL_A5ZX)
iCOPD9	University Hospital of Montpellier (UHOM)	UHOMi005-A (RRID: CVCL_A5ZZ)
Vero C1008	ECACC	85020206; RRID: CVCL_0574

Oligonucleotides

Tables S1 and S2: RTqPCR primer sequences

Software and algorithms

HistoMetriX: Quantacell company (Montpellier)		https://www.quantacell.com/fr/histometrix/
FIJI/ImageJ Trainable Weka Segmentation plugin	Imagej	https://imagej.net/plugins/tws/
GraphPad Prism v10.2.2	GraphPad	https://www.graphpad.com/

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Experimental model and study participant details

iALI culture models

The human iPSC-derived bronchial airway epitheliums on ALI (iALI) were generated from the hiPSC lines HY03 (UHOMi002-A) (healthy control), iCOPD2 (UHOMi003-A), and iCOPD9 (UHOMi005-A),²⁷^,⁶³ which characteristic details are provided in Table S1. Briefly, peripheral blood mononuclear cells (PBMCs) were obtained from one Healthy (UHOMi002-A) and 2 early severe CODP patients. Cells were reprogrammed into iCOPD2 (UHOMi003-A), iCOPD9 (UHOMi005-A) lines respectively using non-integrating CytoTune-iPSC 2.0 Sendai Reprogramming kit (ThermoFisher). PBMCs were isolated by Ficoll gradient centrifugation using Ficoll-Paque PLUS (GE Healthcare) then washed with PBS plus foetal bovine serum (FBS) 10%. PBMCs were cultured in StemSpan Erythroid Expansion Medium (SSEM, StemCell Technologies), according to the manufacturer’s instructions. Erythroid differentiation leads to erythroid progenitor cells expansion. The four reprogramming factors OCT3/4, SOX2, KLF4, and C-MYC were transiently expressed in the erythroid progenitor cells using the integration-free Sendai virus transduction method (as previously described²⁷). The colonies with an embryonic stem cells (ES)-like appearance were manually isolated based on morphologic features. iPSC cell lines were cultured on Geltrex coating (Thermo Fischer Scientific) prepared by 1/170 dilution in DMEM F12 (Thermo Fisher Scientific) with 1% penicillin and streptomycin. Then, E8 medium (Thermo Fisher Scientific) supplemented with 1% penicillin and streptomycine was used for cell growth. The cells were cultivated at 37°C/5% CO₂; the medium was changed daily and cells passaged manually. Cells were then selected morphologically by passaging them using EDTA dissociation (Versene Solution, Thermo Fisher Scientific) every week into clusters, using 1/10 split ratio. Once the correct morphology had been selected, the passages were carried out. The major stages of embryonic lung development were recapitulated as follows: stage 1, definitive endoderm (day 0–3) using RPMI 1640 (Thermo Fischer Scientific) supplemented with B-27™ (50X) without A vitamin (Thermo Fischer Scientific) and activin A (Thermo Fischer Scientific), Y-27632 (10μM, 1254 Bio-Techne), CHIR-99021 (3Mm, 4423 Bio-Techne) between 16 h and 40 h post plating, replace CHIR-99021 by LDN-193189 (250nM, 6053 Bio-Techne) between 40 h and 70 h post plating; stage 2, anterior foregut endoderm (day 4–7) without adding molecules; stage 3, after transfer into a transwell (Ø 12mm, 3460 DUTSCHER), lung progenitor specification (day 7-12); stage 4, polarized epithelial layer (day 12 -40), and day 40+: multi-ciliated bronchial epithelial layer. After 40 days, the airway epithelium on iALI displays morphologic and functional similarities with primary human airway epithelial cells and included different airway cell types (basal, secretory, and multi-ciliated cells).

SARS-CoV-2 virus stock and titration

The strains Delta (B.1.617.2) hCoV-19/France/HDF-IPP11602i/2021 were supplied by the National Reference Centre for Respiratory Viruses hosted by Institut Pasteur (Paris, France) and headed by Pr. Sylvie van der Werf. The human sample from which strain hCoV-19/France/HDF-IPP11602i/2021 was isolated has been provided by Dr Guiheneuf Raphaël, CH Simone Veil, Beauvais France. Moreover, the strain was supplied through the European Virus Archive goes Global (EVAg) platform, a project that has received funding from the European Union’s Horizon 2020 research and innovation program under the grant agreement No 653316. The viruses were propagated in VeroE6 cells with DMEM containing 25mM HEPES at 37°C with 5% CO2 and were harvested 72 hours post inoculation. Virus stocks were stored at -80°C. Virus titration was monitored using plaque assay.

Method details

Viral infection

iALI cultures were washed 24 h before infection by adding culture medium to the apical side at 37°C for 15 min. For SARS-CoV-2 infection, iALI apical side was covered with 350 μL of viral dilution in serum free DMEM (2,5 × 10⁵ PFU per sample, estimated MOI 0,05) for 1 h 30 min at 37°C. For remdesivir efficiency evaluation infection was done on smaller iALI at an estimated MOI 0,01 (0,5 × 10⁵ PFU per sample) Then, the inoculum was removed, and the culture was quickly washed with culture medium PneumaCult-ALI Medium (Stem cell technologies). The first point of the kinetic analysis (Day 0) was collected by adding culture medium to the apical side at 37°C for 15 min. Some iALI’s apical side were washed everyday with culture medium to collect kinetics samples. Other iALI were washed only at the time of collection (RLT or 4% PFA). SARS-CoV-2 infection experiments were conducted inside the BSL3 facility at the CEMIPAI institute.

Reverse transcription-quantitative polymerase chain reaction(RT-qPCR)

Cellular RNA of iALI were collected in RLT and extracted using the QIAshredder kit (QIAGEN, Redwood city, CA, USA) and the RNeasy mini kit (Qiagen, Redwood city, CA, USA) according to the manufacturer’s instructions. Gene expression was quantified by RT-qPCR in triplicate using the Luna Universal One-Step RT-qPCR Kit (New England Biolabs, Ipswich, MA, USA) and a BIORAD CFX Opus 384 system. Primers are described in Table S2. Relative gene expression was calculated by normalizing to GAPDH gene level or GAPDH and Epcam gene level (control) and using the ΔCt method. Cell type markers expression are displayed as relative expression on log2 scale. The gene expression of the innate immune response is presented as the difference from the log2 fold change gene median, with values depicted according to the color scale shown on the right.

Viral RNA was extracted of daily apical wash with NucleoSpin Dx Virus (Macherey-Nagel). Absolute quantification of the viral envelope E gene was done, in triplicate, via RT-qPCR as described above and by comparison to standard range. Data are presented as the concentration of viral RNA in the apical wash.

Samples embedding and cross sections

After collecting the apical wash, the iALI were quickly rinsed with PBS and fixed in 4% paraformaldehyde for 24 hours at 4°C. The samples were then embedded in 5% agarose and placed in 70% ethanol before being sent to the Montpellier histology platform (RHEM). RHEM services included paraffin embedding, 3-5μm cross-sections, hematoxylin-eosin-safran (HES) staining, and periodic acid-Schiff-blue alcian (PAS-BA) staining. The stained slides were scanned using a NanoZoomer, Hamamatsu, by the Montpellier Imagery Platform (MRI).

Quantification of epithelial compartments on HES-stained cross sections

Hematoxylin Eosin Safran (HES)–stained cross-sections of iALI models were analyzed with HistoMetriX (QuantaCell, France) to quantify epithelial area and thickness. Apical and deep epithelial compartments were segmented using U-Net–based convolutional neural networks trained on expert annotations from both infected and non-infected samples to capture the diversity of tissue morphologies. Following segmentation, epithelial layers were skeletonized to extract their central axis, and mean thickness was calculated as the average distance from this axis to the epithelial boundaries. The relative epithelial area (normalized to the total tissue surface) was then used for quantitative comparisons between conditions.

Immunofluorescence

Immunofluorescence was used to label the cross-section’s slides and unprocessed/cut iALI models. Fixation of iALI models for direct immunofluorescence was done by immersion in 4% paraformaldehyde for 30 minutes at room temperature. For cross-section (CS) slides, preliminary steps were needed to remove paraffin: A series of three-minute baths in xylene (28973.294, VWR), ethanol 100%, ethanol 96%, ethanol 70%, and ethanol 50% were used for rehydrating the samples. Slides were then washed with cold water and submerged for 20 minutes in sodium citrate pH 6 buffer (C9999, Sigma) at 100°C. Following a permeabilization period of 20-minute for CS and 2 h for iALI with PBS 0.5% triton, the slides were blocked for one hour for CS and two hours for iALI using blocking buffer (1% BSA, 0.1% Triton X-100, 10% donkey serum in PBS). Samples were incubated with primary antibodies (anti-M SARS-CoV-2 (PAB31758, Abnova), anti-TubIV (T7941, Sigma), anti-P63 (AF1916, R&D systems), anti-CDHR3 (HPA011218, Sigma), anti-Muc5A (ab3649, Abcam), anti-KRT5 (PA1-37974, Thermofisher) and anti-CC10 (RD181022220-01, Biovendor)) with appropriate dilutions (1:100 or 1:200) in staining buffer (1% BSA, 0.1% Triton X-100, in PBS) for overnight at 4°C, followed by washing three times with washing buffer (1% BSA, 0.025% Triton X-100 in PBS). The secondary anti-rabbit, -mouse or -goat antibodies were labelled with Alexa Fluor 488 (A21206, Invitrogen or ab150129, Abcam), 555 (A31570, Invitrogen), or 647 (A21447, Invitrogen or ab150075, Abcam) were incubated at a dilution of 1:1000 for 2 h at room temperature followed by three washes with PBS. Then, 4′,6-diamidino-2-phenylindole (DAPI) (D9542, Sigma) was incubated at dilution 1:2000 for 5 minutes for CS and 15 minutes for iALI and washed three times with PBS. Finally, aqueous mounting media (BUF058B, Biorad) was used to cover CS with a glass coverslip and mount iALI on glass slides, and glass coverslips were used to cover them.

Image acquisition and cilia quantifications

All images were acquired using a Cell Discovery 7 LSM900 confocal microscope located in the CMIPAI BSL3 facility (CNRS Montpellier, France). The same objective and microscope settings were maintained for all acquisitions. Z-stack images were taken at intervals of 0.5 μm in order to ensure total focus throughout the depth of the sample. For generating 2D representations, maximum intensity projections of the z-stacks images were created using FIJI/ImageJ. Cilia segmentation in all images was performed using the Trainable Weka Segmentation plugin in FIJI/ImageJ, which applies a combination of machine learning algorithms to generate pixel-based binary segmentations. The resulting segmented binary images were then manually analysed to quantify the percentage of cilia area within a 25 μm × 25 μm region of interest (ROI) for both infected and non-infected samples. The Cilia percentage per area measurements were obtained in FIJI/ImageJ using the command Analyse → Measure → Area Fraction.

Plaque assay

Virus titration from stocks and infected cell culture supernatants were monitored using plaque assays on a monolayer of VeroE6 cells, using 100μL of serially diluted samples. The plaque forming unit (PFU) values were determined using crystal violet coloration on cells and subsequent scoring the wells displaying cytopathic effects. Calculations allow to determine the titer as the number of PFU/mL.

IL13 treatment

Recombinant human IL-13 (ref. 200-13, PeproTech) was reconstituted at 0.1 mg/mL in sterile water. Healthy iALI models were treated daily on the basal side during the final week of differentiation (day 33 to day 40) by diluting the IL-13 stock solution into the culture medium. On day 40, apical washes were collected for mucus quantification, and cultures were subsequently infected with SARS-CoV-2 Delta (MOI = 0.05) as described previously. Following infection, the apical surface was washed daily for quantification of viral RNA release and mucus production. At 4 days post-infection (dpi), iALI cultures were lysed for cellular RNA extraction and biomarker expression analysis.

Dot blot for mucus quantification

Ten microliters of each sample (10-fold dilution) were spotted onto a nitrocellulose membrane. After air drying, the membrane was incubated for 1 h at room temperature in blocking buffer (Rockland MB-070, Tebu). It was then incubated overnight at 4°C with anti-MUC5AC antibody (MA5-12178, Thermo Fisher) diluted 1:800 in PBS containing 50% blocking buffer and 0.1% Tween-20. The membrane was washed three times with PBS containing 0.1% Tween-20, then incubated for 1 h at room temperature with the secondary antibody DyLight 800 (SA5-35521, Thermo Fisher) diluted 1:20,000 in PBS containing 50% blocking buffer and 0.1% Tween-20. After three final washes in PBS containing 0.1% Tween-20, the signal was detected using an Odyssey M Imaging System (LI-COR Biosciences) and quantified with Image Studio software.

Protein secretion

Quantification of secreted protein (cytokine) was done at 4 dpi on apical washes thanks to the ELISA-based LEGENDplex COVID-19 Cytokine Storm Panel 1 (14-plex) with V-bottom Plate (741089, Biolegend). Samples were measured at 2 dilutions, pure and with a 10-fold dilution to cover the standard range of all the analytes. Acquisition was done on the NovoCyte Flow 21000YB cytometer inside the CEMIPAI BSL3 facility (CNRS Montpellier France). Results were normalized to total protein levels as measured by pierce protein assay (BCA) (10177723, thermo fisher).

Quantification and statistical analysis

For normally distributed data, the mean was shown with standard error; where necessary, an analysis of variance (two-way ANOVA) or Student’s t test was employed to look for intergroup differences. ∗P < 0.05, ∗∗P < 0.01, ∗∗∗P < 0.001, and ∗∗∗∗P < 0.0001 demonstrate the degree of significance, with a p-value <0.05 being considered significant. Graphical representation and statistical analysis were performed using GraphPad Prism.

Published: January 23, 2026

Footnotes

Supplemental information can be found online at https://doi.org/10.1016/j.isci.2026.114741.

Contributor Information

John De Vos, Email: john.de-vos@umontpellier.fr.

Delphine Muriaux, Email: delphine.muriaux@irim.cnrs.fr.

Supplemental information

Document S1. Figures S1–S6 and Tables S1–S3

mmc1.pdf^{(1.7MB, pdf)}

Data S1. Original RTqPCR datasets, related to Figure 2

RTqPCR measurements for the genes FOKJ1, CCDC40, Muc5A, Muc5b, KRT5, p63, CHGA, and SCGB1A1, comparing HY to COPD iALI.

mmc2.xlsx^{(38.7KB, xlsx)}

Data S2. Original RTqPCR datasets, related to Figure 4

RTqPCR measurements for the genes FOKJ1, CCDC40, Muc5A, Muc5b, KRT5, p63, CHGA, and SCGB1A1, comparing non infected to SARS-CoV-2 infected iALI.

mmc3.xlsx^{(60.9KB, xlsx)}

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Associated Data

This section collects any data citations, data availability statements, or supplementary materials included in this article.

Supplementary Materials

Document S1. Figures S1–S6 and Tables S1–S3

mmc1.pdf^{(1.7MB, pdf)}

Data S1. Original RTqPCR datasets, related to Figure 2

RTqPCR measurements for the genes FOKJ1, CCDC40, Muc5A, Muc5b, KRT5, p63, CHGA, and SCGB1A1, comparing HY to COPD iALI.

mmc2.xlsx^{(38.7KB, xlsx)}

Data S2. Original RTqPCR datasets, related to Figure 4

RTqPCR measurements for the genes FOKJ1, CCDC40, Muc5A, Muc5b, KRT5, p63, CHGA, and SCGB1A1, comparing non infected to SARS-CoV-2 infected iALI.

mmc3.xlsx^{(60.9KB, xlsx)}

Data Availability Statement

Data: All data supporting the findings of this study are available from the lead contact upon reasonable request.

Code: All code supporting the findings of this study are available from the lead contact.

Other items: All other items supporting the findings of this study are available from the lead contact upon reasonable request.

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PERMALINK

Human iPSC-derived airway models enable comparative analysis of SARS-CoV-2 infection in healthy and COPD bronchial epithelium

Lisa Morichon

Jitendriya Swain

Nathalie Gros

Amel Nasri

Florent Foisset

Gaetan Galisot

Victor Racine

Said Assou

Arnaud Bourdin

John De Vos

Delphine Muriaux

Summary

Graphical abstract

Highlights

Introduction

Results

Human iPSC-derived bronchial models capture key features of COPD

Figure 1.

Figure 2.

SARS-CoV-2 infects ciliated epithelium in iPSC-derived bronchial iALI models

Figure 3.

Enhanced mucus production in iALI models limits SARS-CoV-2 infection

Figure 4.

Figure 5.

iCOPD bronchial models exhibit an enhanced innate and inflammatory response to SARS-CoV-2

Figure 6.

Discussion

Limitations of the study

Resource availability

Lead contact

Materials availability

Data and code availability

Acknowledgments

Author contributions

Declaration of interests

Declaration of generative AI and AI-assisted technologies in the writing process

STAR★Methods

Key resources table

Experimental model and study participant details

iALI culture models

SARS-CoV-2 virus stock and titration

Method details

Viral infection

Reverse transcription-quantitative polymerase chain reaction(RT-qPCR)

Samples embedding and cross sections

Quantification of epithelial compartments on HES-stained cross sections

Immunofluorescence

Image acquisition and cilia quantifications

Plaque assay

IL13 treatment

Dot blot for mucus quantification

Protein secretion

Quantification and statistical analysis

Footnotes

Contributor Information

Supplemental information

References

Associated Data

Supplementary Materials

Data Availability Statement

ACTIONS

PERMALINK

RESOURCES

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