# Modeling viral and bacterial infections in human lung organotypic systems reveals strain specific host responses

Bárbara Faria Fonseca, Jérôme Wong Ng, Michael Connor, Héloïse Mary, Minhee Kim, Rémy Yim, Vincent Bondet, Vincent Michel, Hélène Strick Marchand, James P. Di Santo, et al.

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## To cite this version:

Bárbara Faria Fonseca, Jérôme Wong Ng, Michael Connor, Héloïse Mary, Minhee Kim, et al. Modeling viral and bacterial infections in human lung organotypic systems reveals strain specific host responses. 2025. pasteur-05114543v2

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Distributed under a Creative Commons Attribution 4.0 International License
Modeling viral and bacterial infections in human lung organotypic
systems reveals strain specific host responses

Bárbara Faria Fonseca¹, Jérôme Wong-Ng¹, Michael Connor², Héloïse Mary¹, Min Hee Kim¹,
Rémy Yim¹, Vincent Bondet³, Vincent Michel⁴, Hélène Strick Marchand⁵, James Di Santo⁵,
Darragh Duffy³, Mélanie Hamon², Nathalie Sauvonnet¹, Lisa A. Chakrabarti⁶, Samy Gobaa¹*

¹Institut Pasteur, Université Paris Cité, Biomaterials and Microfluidics core facility, France

²Institut Pasteur, Université Paris Cité, Chromatin and Infection laboratory, France

³Institut Pasteur, Université Paris Cité, Translational Immunology Unit, France

⁴Institut Pasteur, Université Paris Cité, Pathogenesis of Vascular Infections Unit, France

⁵Institut Pasteur, Université Paris Cité, Innate Immunity Unit, France

⁶Institut Pasteur, Université Paris Cité, Control of Chronic Viral Infections Group, Virus and Immunity Unit, France.

* Correspondence: samy.gobaa@pasteur.fr

Keywords: lung; organoid; organ-on-chip; pneumococcus; SARS-CoV-2

Highlights

• Human fetal epithelial lung stem cells can be expanded as multipotent organoids and differentiated into both airway or alveolar organoids

18 • Multipotent lung organoids efficiently produce functional epithelia of small airway or alveoli when grown on-chip.

20 • *Streptococcus pneumoniae* inoculation in alveoli-on-chip mimics the early stages of
21 bacterial colonization in lung epithelia

22 • Alveoli on-chip system recapitulates variant-specific interactions. SARS-CoV-2 Delta
23 replicates but not Omicron BA.5.

24 • Robust interferon response upon SARS-CoV-2 infection shows Alveoli on-chip can model
25 innate immune responses.

26

Abstract

In this study, we developed novel lung organoid-on-chip models that elucidate differential human tissue response to various strains of respiratory pathogens: *Streptococcus pneumoniae* and SARS-CoV-2. We show that human fetal-derived distal lung epithelial cells are readily expandable in 3D as organoids, thereby providing a highly sustainable source of lung progenitor cells. These 3D organoid progenitors can then be induced to produce airway and alveolar organoids on microfluidic devices. Upon challenge with *Streptococcus pneumoniae*, a bacterium known to cause pneumonia, a rapid and strain-dependent colonization was observed at the epithelial surface of alveolar chips. We also assessed SARS-CoV-2 infection in the alveoli-on-chip system and observed that the Delta variant exhibited greater infectivity as compared to the Omicron BA.5.
37 Both SARS-CoV-2 variants induced potent interferon responses and triggered the expression of
38 different interferon-stimulated genes. Our results demonstrate that strain-specific host defense
39 mechanisms can be recapitulated in human-organoid-based microfluidic systems, paving the way
40 for the use of such platforms for more targeted assessments of human response to novel
41 emergent pathogen strains.

42 **Introduction**

43 The epithelial lining of the human respiratory tract constitutes the major entry point for airborne
44 pathogens. At the tissue level, lung epithelia are supported by a highly specialized stroma, a richly
45 vascularized network and numerous populations of specialized immune cells. Collectively, this
46 complex system ensures tissue homeostasis, barrier function and efficient gas exchange while
47 facing constant viral and bacterial challenges. Host-microbe interactions start at the epithelial
48 apical surface. Resulting infections trigger early defense mechanisms including mucociliary
49 clearance and mucosal innate immunity ¹,². The complexity of the mounted responses is in part
50 determined by the heterogeneous histological composition of the tissues along the respiratory
51 tract. Ciliated and mucus-producing cells in the airways work together to remove airborne
52 pollutants and microbes. At the distal end of the tract, the alveolar epithelium can also mount a
53 complex immune response in response to pathogen invasion. Disentangling the lung tissue
54 response to airborne pathogens hinges on the establishment of advanced tissue models that
55 extend beyond what can be recapitulated in standard 2D, cell line-based assays.

56 The major challenge in devising advanced human lung disease models resides in
57 establishing a sustainable source of human cells. Ideally, the starting cell material should be
58 amenable to *in vitro* expansion while still capable of producing the complete range of cell types
59 that constitute the tissue of interest. Immortalized cell lines, such as A549 and Calu-3, can be
60 useful for drug screening and infection studies, but as they originate from lung carcinoma, they
61 poorly represent the biology of bona fide lung cells ³. On the other hand, primary adult cells can
62 be used to reconstitute nasopharyngeal, bronchial and alveolar tissues *in vitro* ⁴⁻⁶. However, these
63 largely postmitotic cells can be difficult to obtain and rapidly dedifferentiate ⁷. To overcome these
64 limitations, culturing primary lung cells as organoids has proven highly effective. Both human
65 bronchiolar and alveolar organoids can today be derived from human adult biopsies or from iPSC
66 cell culture ⁸⁻¹⁵. Lung organoids can be maintained for several passages and be used for lung
67 disease modeling ¹⁶,¹⁷.

68 Reproducing the apicobasal polarity of respiratory epithelia is crucial for correctly modeling
69 the entry of an airborne pathogen in a human lung cell. Most current lung organoid protocols lead
70 to the production of apical surfaces facing inward (lumen). Loading any inoculum on the apical
71 side can therefore be challenging. Various strategies were employed to partially overcome this
72 limitation including microinjection ¹⁸,¹⁹, inverted-polarity techniques ¹⁰ and organoid fragmentation
73 and re-formation ²⁰. However, these approaches often compromise throughput and reproducibility.
74 Alternatively, organ-on-chip technology was shown to be a powerful technique to reconstruct
75 accessible human epithelial tissues in an environment where tissue perfusion of media, drugs and
76 pathogens can be precisely controlled ⁴,²¹,²². This microfluidic-based approach also enables the
77 creation of interconnected channels and can allow the stretching of cultured epithelia ⁴,²³.
78 Additionally, organ-on-chip systems allow human lung epithelial cells to be cultured at an air-liquid
79 interface (ALI), further mimicking the function of the human respiratory tract. Leveraging these 80 technologies for investing host-pathogen interactions is gaining traction. However, new 81 developments remain pathogen-dependent.

82 In this study, we combined two organotypic models, organoids and organ-on-chips, to build 83 novel small airway and alveolar lung infection models. We expanded human distal lung bud 84 organoids 24-26 and steered them to differentiate, on-chip, into sample-matched airway or alveolar 85 tissues. We demonstrate that such advanced organ-on-chip devices can successfully model viral 86 and bacterial infections. We found that the engineered lung models can be used to identify cell 87 type-related susceptibilities to bacterial infection. We also show that the presented approaches 88 can be used to characterize variant-dependent human innate immune responses upon SARS- 89 CoV-2 infection.

90

91 **Results**

92 **Derivation of human multipotent lung organoids**

93 During human lung development, the epithelial lung bud tip forms a pool of multipotent stem cells 94 capable of generating both small airways and alveoli tissues. A complex interplay of signaling 95 pathways, primarily driven by WNT and fibroblast growth factor (FGF) activation, ensure the 96 plasticity of this fetal structure along the pseudoglandular and early-canalicular stages of lung 97 development 2. In vitro, reconstructing this signaling cocktail allows long-term expansion of lung 98 multipotent progenitors 24. In this study, we derived a stable culture of human fetal-derived lung 99 bud tip organoids that can be amplified and differentiated into either alveolar or small airway 100 epithelial cells (Figure 1A). Lung organoids cultured in self-renewing conditions grow as simple 101 epithelia that are SOX2+ and SOX9+ (Figure 1B & 1D) 2. These organoids could be split every 10 102 to 14 days, multiple times, to expand the number of available cells (Figure 1C). We also found that 103 stable multipotent organoid cultures can be successfully reestablished after multiple freeze-thaw 104 cycles, enabling the banking of this initial material, which greatly simplifies its use and 105 dissemination.

106 To steer lung multipotent organoids towards alveolar differentiation, we modified the culture 107 conditions by withdrawing FGF, maintaining WNT activation and adding NOTCH and TGF-β 108 inhibitors, as described in Lim et al 26. After two weeks in these differentiation conditions, 109 immunostaining revealed the presence of HT2-280 positive cells, a human lung-specific type II 110 pneumocytes (AT2) marker 27. Pro-surfactant protein C (pro-SFTPC), a typical surfactant protein 111 produced by bipotent alveolar progenitors and fully differentiated AT2 cells 2, was also identified in 112 several cells. These observations confirm the differentiation into AT2 cells (Figure 1E). Here, we 113 did not identify cells with positive labeling for the HT1-56, AQP5 and RAGE, markers of type I 114 pneumocytes (ATI). While extensive differentiation dynamics were not investigated, we speculate 115 that terminal AT1 differentiation within organoids requires additional extrinsic factors including 116 morphogens or physical cues to support their development. Previous studies with alveolar 117 organoids derived from primary adult lung cells also highlighted an absence of AT1 cells 8,28. 118 Interestingly, recent reports with iPSC-derived and fetal-derived alveolar organoids show that
withdrawal of WNT agonists, combined with YAP activators in the differentiation medium, is necessary for AT1 differentiation<sup>14,29</sup>.

Next, we sought to evaluate the capacity of multipotent organoids to differentiate into small airway tissues, lung organoids were treated with a pro-airway differentiation medium where WNT agonists were removed and FGF activation maintained <sup>9</sup>. A two-week treatment was sufficient to induce the differentiation into typical airway cell types such as beating multiciliated cells that are positive for acetylated tubulin (ac-TUB+) and basal cells expressing cytokeratin 5 (KRT5+). We also identified secretory cells, including goblet cells producing mucin (MUC5AC+) and club cells expressing secretoglobin family 1A member 1 (SCGB1A1+) (Figure 1F; Supplementary Movie 1). Our observations show that the morphology of differentiated organoids showed varying lumen sizes and different extents of folding but systematically appeared as pseudostratified when compared to multipotent organoids.

Altogether, we demonstrated that human fetal distal lung buds can be efficiently harvested and used as a reliable source material for the derivation of multipotent human lung organoids. We also showed that these organoids have the capacity to differentiate into either small airways or alveolar epithelia.

## On-chip differentiation of lung reconstituted epithelia

Devising human lung organotypic models to investigate infectious diseases relies first on the reconstitution of faithful mimics of human epithelia and second on straightforward access to the luminal compartment that is the classical entry point of airborne pathogens. While organoids can efficiently ensure an appropriate cell composition, their inward polarization renders infectious studies labor intensive<sup>18,19</sup>. Here we engineered an organ-on-chip approach that relies on the use of human organoids as a source of cells and where both the perfusion of fluids and the inoculum loading are fully controlled<sup>4,21,22</sup>.

Briefly, we seeded fragments of multipotent organoids on a commercial S1™ organ-on-chip device from emulate™ (Figure 2A). Two days of culture under self-renewing conditions were sufficient to produce a confluent epithelium on the chips. We also observed that adding sample-matched mesenchymal cells to the lower channel of the chip drastically improved lung epithelial cell survival and differentiation as previously reported<sup>6,8,26,30,31</sup>. Next, we induced differentiation by perfusing either airway or alveolar media optimized for organoid differentiation. Finally, air-liquid interface (ALI) was implemented to promote differentiation (Figure 2A). Both types of organoid-derived chips formed a simple epithelium expressing E-cadherin and ZO-1 proteins (Supplementary Figure 1). The produced epithelia maintained ALI for multiple days, suggesting that the junctions are tight.

Next, we analyzed the cell composition of chips induced to differentiate toward the alveolar lineage (Figure 2B-F). Immunostaining analysis revealed that approximately one third of the cells expressed pro-SFTPC (31.6% ±19.6), (Figure 2B, 2C). HT2-280, stained an average of 14.4% ±6.4 of cells, indicating that only 12 days in differentiation medium was sufficient to drive the differentiation of a substantial population of AT2 cells on-chip. Interestingly, AT1 cells could be identified with RAGE and HT1-56 antibodies, the latter labelling 9.0 ± 4.8% of the cells (Figure 2B, 2C). RT-qPCR analyses confirmed a down-regulation in the expression of bud tip markers (SOX2
and SOX9, Figure 2D) and an up-regulation on the expression of mature alveolar markers including LAMP3 (a member of the lysosomal-associated membrane protein family and marker of mature AT2 cells ³²) and chloride intracellular channel 5 (CLIC5), expressed by bona fide AT1 cells ³³ (Figure 2E, 2F). Finally, we checked for incidental airway differentiation on alveolar chips and found no evidence of the presence of ciliated, goblet or club cells presence. Basal cells, positive for cytokeratin 5 (KRT5) and transcription factor SOX2 but negative for SOX9, were very seldomly observed. We termed these devices AlveoChips.

When analyzing the cellular composition of small airway chips, immunostaining showed a standard profile of cells including ciliated cells (acTUB+), club cells (SCGB1A1+), goblet cells (MUC5AC+) and basal cells (KRT5+) (Figure 2G, 2H). In addition, a clearly polarized, pseudo-stratified epithelium was observed (Figure 2G). Time-lapse microscopy also showed the presence of beating cilia at the surface of the reconstituted airway epithelium (Supplementary Movie 2) after 20 days of differentiation. Basal cells accounted for 5.3% ± 4.3 and multi-ciliated cells for 3% ± 1.6 of the total cells in the epithelium (Figure 2H). These data show that, as for the organoid cultures, chips seeded with human fetal cells derived from multipotent organoids can be guided to produce either airway or alveolar microphysiological systems.

## 176 AlveoChip models *Streptococcus pneumoniae* alveolar colonization

S. pneumoniae colonizes the human upper respiratory tract where it is carried asymptomatically. However, when the bacterium invades the alveolar sacs, it can cause severe pneumoniae ³⁴. Our understanding of the infectious processes, at early stages of pneumococcal colonization, that drive asymptomatic carriage versus pathogenic invasion is limited. Therefore, studying the early events of S. pneumoniae in reconstituted human primary lung tissue is highly relevant. Due to the accurate epithelial cell composition of AlveoChips and the capacity to finely control the inoculum administration and subsequent infectious events through microfluidics, we aimed to model S. pneumoniae colonization on the alveolar epithelium. Here we used two S. pneumoniae strains, TIGR4 and 6B ST90, which are known to cause disease in human and in murine models, with TIGR4 being more invasive than 6B ST90 ³⁵. For comparison, we used Corynebacterium accolens (C. accolens), a commensal nasal microbiont that does not colonize the lungs ³⁶.

Briefly, we inoculated AlveoChips TIGR4, 6B ST90 or C. accolens bacteria for 6 min under flow (1000ul/h). We then removed all the medium in the top channel and re-established an air-liquid interface (Figure 3A). A dose of 3.0x 10⁴ colony-forming units (CFU) was used on every AlveoChip (Figure 3B). At 24 hours post infection (hpi), we observed an approximate 1.5 order of magnitude increase of CFU counts in top channel effluents collected from both TIGR4 (median: 5.0.10⁵ total CFU) and 6B ST90 infected chips (median: 7.9.10⁵ total CFU) (Figure 3C). Interestingly, a 2-log decrease in the number of CFU counts was observed in effluents of chips treated with C. accolens (median: 3.3.10² total CFU). These results show that the two pneumococcus strains can successfully multiply in the modeled alveolar microenvironment. In contrast, C. accolens does not replicate and its inoculated population declines rapidly within the first 24hpi.

We next asked whether these microorganisms could be found in effluents of the bottom channel, suggesting a possible transmigration towards the mesenchyme-filled compartment. High levels of TIGR4 pneumococcus counts were detected at the bottom channel effluents (median:
202 4.1.10⁶ total CFU). Interestingly, while the commensal-like strain 6B ST90 could also be detected,
203 it was recovered at lower levels than that of TIGR4 (median: 3.9.10⁵ total CFU). CFU counts from
204 C. accolens treated chips were below the limit of detection, confirming the absence of growth of
205 this pathogen in alveolar chips (Figure 3D). CFU assays revealed that both pneumococcus strains,
206 which have contrasted effects in mice ³⁵, were able to proliferate in the AlveoChips.

207 Finally, immunolabeling after 24hpi revealed the presence of numerous TIGR4 and 6B
208 ST90 bacteria but no C. accolens, at the surface of the epithelial cells corroborating the CFU
209 results (Figure 3E). We could also detect TIGR4 and 6B ST90 within the pores of the chip
210 membrane, suggesting a transmigration across the barrier to the bottom chamber (Supplementary
211 Figure 2A). Interestingly when assessing the frequency of each cell type in infected chips, we
212 measured a strong decrease in HT2-280+ cell occurrence upon pneumococcal invasion (Figure
213 3F). This decrease seemed specific to type II pneumocytes as no variation in ATI or in total cell
214 numbers were observed after TIGR4 or 6B ST90 inoculation (Figure 3G, Supplementary Figure
215 2B). Our data demonstrate that S. pneumococcus is readily capable of colonizing the AlveoChip
216 model and of crossing the epithelial barrier within the first 24hpi.

217 AlveoChip unveils distinct replicative fitness of SARS-CoV-2 variants

218 To investigate the replication competence of SARS-CoV-2 on-chip, we infected AlveoChips with
219 the SARS-CoV-2 Delta variant. Chips where then analyzed at 4 days post infection (4dpi) (Figure
220 4A). Immunostaining experiments detected 1.9 ± 5.5 % of SARS-CoV-2 spike+ cells (Figure 4B
221 and 4C). Quantifications showed that 34.1 ± 27 % of the HT2-280+ were positive for the spike
222 viral protein (Figure 4D). Interestingly, in our experimental conditions, Delta infection did not trigger
223 major cell death as no significant differences were observed in the total number of HT2-280+ cells
224 or in the overall cell count on chip post-infection (Supplementary Figure 3A and 3B).

225 To compare the fitness of different SARS-CoV-2 variants, we infected AlveoChips with
226 equal titers of SARS-CoV-2 Delta or Omicron BA.5 variants and then quantified the apical release
227 of viral RNA over 4 days (Figure 4A). RT-qPCR data showed a steady replication of the Delta
228 variant that starts at 1dpi and reaches a peak around 4dpi (Figure 4E). In contrast, Omicron BA.5
229 did not replicate efficiently in our alveolar model: the corresponding viral RNA load, measured in
230 chip lavages, remained at significantly lower levels (Figure 4E). At the end of the experiment, the
231 apically released viral RNA for the two variants differed by four orders of magnitude (4.4.10⁵ copies
232 per mL for Delta versus 3.10¹ copies per mL for Omicron BA.5). Interestingly this significant
233 difference (p < 0.0001) was consistently observed across all the used organoid lines,
234 demonstrating the high reproducibility of the system (Figure 4F). At the end of the experiment, a
235 higher amount of viral RNA could also be detected in total cell RNA extracted from Delta-infected
236 chips (Figure 4G). Viral particles could be identified by scanning electron microscopy in chips
237 infected with Delta, but not in chips in mock-infected samples (Supplementary Figure 4). In
238 addition, immunostainings performed with an anti-viral nucleocapsid (NCP1) antibody, further
239 confirmed that SARS-CoV-2 infected cells could be detected in Delta-infected chips, but not in
240 Omicron BA.5 and mock-infected chips (Supplementary Figure 5). Taken together, these results
241 show that the AlveoChip model is susceptible to Delta infection, but not to Omicron BA.5,
242 recapitulating the lower replicative potential of Omicron in an alveolar environment ³⁷,³⁸. To our
knowledge, Alveochip is the first in vitro alveolar organ-on-chip system that recapitulates
differential variant sensitivity.

Finally, following viral infection, we quantified type I and III interferon (IFN) release on the luminal surface of lung epithelial cells to verify whether the reconstituted alveolar epithelia can mount an innate host-defense response. A significant increase in IFNα protein levels (expressed as IFNa17 equivalents) was observed at 4dpi in Delta-infected chips, compared to uninfected controls. Interestingly, despite the lower infectivity of Omicron BA.5 in this system, IFNα secretion was similarly high in epithelial cells challenged with this variant (Figure 4H). For IFNβ, average protein levels were higher in Omicron BA.5-infected chips, while no significant IFNλ3 production was detected at 4dpi for either variant (Supplementary Figure 6A and 6B). When looking at the transcription of interferon-stimulated genes (ISGs), both Delta and Omicron BA.5 infections triggered the upregulation of standard ISG such as IFIT1, ISG15 and MX2 (Figure 4I). Overall, these data show that, in our AlveoChip model, host epithelial cells respond to SARS-CoV-2 viral inoculation by secreting IFN molecules and expressing ISGs, thereby initiating an innate immune response. Interestingly, despite the lower replication competence of Omicron BA.5 compared to the Delta, the former still triggers a strong IFN response.

259

## Discussion

In this work, we assessed the potential of human fetal-derived lung organoids as starting material for building respiratory infection models. We showed that multipotent fetal lung organoids can be largely expanded *in vitro* while preserving their capacity to differentiate into small airway or alveolar epithelia. Using these lung organoids, we generated airway- and alveoli-on-chip systems which grant easy access to the apical side of epithelial cells and thus can be readily used for addressing airborne pathogen infections in well-controlled conditions.

Culturing primary adult lung cells as organoids has been extensively explored in the past decade 8-10,39. Both biochemical and mechanical cues provided by the extracellular matrix facilitate the self-organization and differentiation of stem cells and progenitors into faithful tissue mimics. However, several limitations, including dedifferentiation, limited supply, and donor-to-donor variations, remain to be solved. While fetal lung tissue is undeniably in very short supply, fetal lung bud tips can be expanded *in vitro* to form self-renewing organoids that preserve key markers of multipotent progenitors 24. On the other hand, induced pluripotent stem cells (iPSCs) can also generate lung organoids for infection studies 40,41. However, because it is necessary to recapitulate all the differentiation steps to reach the lung progenitor state, iPSC protocols tend to be longer and more labor-intensive than fetal lung cultures 11-15. Consequently, our approach provides a valuable addition to existing lung-on-chip models 4,23,42-45, as our system recapitulates lung epithelia composition *in vitro* without constantly relying on primary cell sourcing or on less physiological immortalized cell lines.

Airborne pathogens typically infect through the apical region of epithelial cells. To mimic this aspect *in vitro*, it is necessary to precisely control the inoculum amount, timing and cell targeting, which can be highly challenging in organoid systems 18,19. To address this, we employed an organ-on-chip technology to gain inoculation precision and reproducibility. When installed onto
284 microfluidic chips, fetal-derived lung cells proliferated, differentiated and polarized in response to
285 signaling cues present in the differentiation media. Multipotent organoid-derived cells
286 differentiated on the airway chips and produced the expected goblet, club, basal, and multiciliated
287 cell populations. The number of multiciliated cells derived on-chip was consistent with previous
288 reports on primary cells cultured in this medium 9. Further optimization could include adding Notch
289 inhibitors and BMP activators, as demonstrated by Van der Vaart et al. 46, to better control the ratio
290 between the different cell types. In the case of alveolar chips, we observed a robust production of
291 bona fide AT2 cells (SFTPC+, HT2-280+ and LAMP3+). This is in line with recent advancements
292 for the generation of mature AT2 cells derived from fetal material 6,26,47. Previous efforts struggled
293 with sustaining differentiated AT2 cells for more than few days in culture 7. Additionally, we
294 observed a significant number of AT1 cells, detected with characteristic markers such as HT1-56,
295 RAGE and CLIC5. AT1 cells were less abundant than AT2 cells in this model, with a 1:1.6 ratio
296 based on HT1-56 and HT2-280 markers; however, this ratio is consistent with in vivo findings (1:2
297 or 1:3 ratio, as reported by Crapo et al. and Foster et al. 48,49). While increasing the AT1 population
298 was not the focus of this study, it may be achievable on-chip by inducing AT2-to-AT1
299 transdifferentiation, as demonstrated in other studies 14,29,43,48. Overall, our characterization of the
300 Alveochips validates their use for modeling airborne infections from the colonization steps to the
301 innate immune response.

302 Previous studies have demonstrated the effects of S. pneumoniae infection in human
303 immortalized cell lines 35, bronchial epithelial cultures 50 and alveolar organoids 41. Our work
304 confirms the capacity of TIGR4 and 6B ST90 strains to colonize human alveolar epithelia. In
305 murine models, the 6B ST90 strain does not cause disease whereas TIGR4 presents a highly
306 invasive phenotype 35. Interestingly, in our model TIGR4 crosses the epithelial barrier to a greater
307 extent than the 6B ST90 strain, partially phenocopying in vivo observations 35,51. In our
308 experimental conditions, limited barrier damage was observed upon TIGR4 infection. While TIGR4
309 infection is commonly associated with epithelial cell death in most model systems 34, our
310 AlveoChips experiments reveal a different dynamic. After 24hpi, high levels of TIGR4 counts were
311 recovered from the chip bottom channel without a visible effect on the epithelial barrier, which was
312 confirmed by cell counting and ZO-1 staining. These observations suggest that, at an early time
313 point, TIGR4 can cross the epithelium without causing widespread damage. Altogether, our model
314 provides a unique model for future investigations into how barrier level destruction may occur as
315 disease progresses and whether recruitment of innate immune cells such as macrophages and
316 neutrophils exacerbates this. Indeed, it is known that murine pneumococcal challenge with
317 invasive disease favouring isolates leads to two waves of neutrophil infiltration within the lungs.
318 Interestingly, the second wave coincides with rapid increase in bacterial burden and tissue
319 damage, as opposed to the first being able to partially control pneumococci 52. On the other hand,
320 we also found that C. accolens, a commensal nasal species, did not infect alveolar chips.-Previous
321 studies have shown that C. accolens is highly abundant in the upper airways, where it can inhibit
322 pneumococcal growth and colonization of the respiratory tract 36,53. Future work could explore
323 whether co-culturing C. accolens and S. pneumoniae before chip inoculation affects
324 pneumococcal infection of alveolar cells. The engineered AlveoChip system is capable of
325 supporting investigations on pneumococcal transmigration events and host responsiveness within
326 an alveolar epithelium, which are still poorly understood.
The COVID-19 pandemic showcased the continuous emergence of novel variants of concern, each using different mechanisms for viral spread and immune evasion to increase infectivity within the respiratory tract <sup>54,55</sup>. SARS-CoV-2 effects have been widely investigated in airway and alveolar-like *in vitro* systems such as reconstructed airway epithelia in transwells <sup>5,30,56-58</sup>, organoids <sup>10,39,57,59</sup> and organ-on-chip models <sup>45,60,61</sup>. The general consensus is that novel variants, from the Omicron sublineage, replicate faster and more efficiently in the upper respiratory tract epithelium compared to earlier variants, which likely contributes to its increased transmissibility <sup>37,56,62</sup>. In contrast, in *ex vivo* explant cultures of human lungs, Omicron replicates less efficiently than earlier variants such as Delta <sup>37</sup>. Other studies using an immortalized alveolar cell line <sup>63</sup>, iPSC-derived alveolar cells in micropatterned wells <sup>64</sup> and adult-derived alveolar organoids <sup>38</sup> also report the lower infectivity of Omicron in the alveolar microenvironment when compared to Delta. In this work we found that the AlveoChip model can recapitulate these replication differences between Delta and Omicron BA.5 variants.

Interestingly, we observed a marked increase in IFNα secretion following SARS-CoV-2 infection in AlveoChips. Both Delta and Omicron BA.5 triggered a robust release of IFNα, detectable at 4dpi. Our data also showed that IFN-β was also secreted mainly in Omicron BA.5-infected chips. The expression of ISGs following Delta and Omicron infection reflected the increased IFN secretion. Despite similar induction of the IFN response, the two variants displayed different replication efficiencies, suggesting that they vary in their ability to evade IFN signaling. In the airway microenvironment, Omicron is known to be highly replicative and appears to be resistant to IFN signaling. These characteristics seem to underlie its higher transmissibility and fitness <sup>62,65</sup>. Recent single-cell RNA sequencing findings suggest that IFN resistance may be cell-type dependent <sup>57</sup>. For instance, ciliated cells infected with SARS-CoV-2 elicit a clear IFN response, but secretory cells, which can also become infected, produce an even stronger IFN response, impeding viral replication at later stages <sup>57</sup>. In pediatric nasal epithelial cells, goblet cells show a robust IFN expression, and consistently produce fewer viral particles than ciliated cells <sup>58</sup>. Our findings that the strong IFN induction in alveolar cells exposed to Omicron viruses correlates with Omicron's lower replication in this tissue suggest that SARS-CoV-2 exhibits cell- or tissue-specific IFN susceptibility.

In summary, our study presents a novel approach to building organ-on-chip models derived from human multipotent lung organoids. This strategy allowed the production of airway and alveolar faithful mimics. We showed that our model can recapitulate the early events following bacterial or viral infection in vitro. Our work also provides mechanistic understandings on early pathogenesis events and on human immune responses, that are otherwise inaccessible.

# 361
## 362 Methods

### 363 Procurement of human fetal lung tissue

Human fetal lung tissues were obtained from Advanced Bioscience Resources Inc. (CA, USA). Sourcing, import and organoid derivation were carried out as per national and institutional regulations and guidelines (import authorization number IE-2022-2353 and file number: 2022-075_Alveolar organoids at Institut Pasteur). Samples aged from 15 to 24 post-conception weeks.
All the samples used for the current study had no known genetic abnormalities and were tested negative for Syphilis HIV, HBV, HCV, HSV, and CMV.

## Primary culture of human fetal lungs and establishment of organoid cultures

The procedure is based on protocols described by Nikolic et al. and Miller et al.²⁴,²⁵. Briefly, distal regions of fetal lung lobes were cut into small 2 mm³ pieces in washing medium (100 units.mL⁻¹ Penicillin, 100 µg.mL⁻¹ Streptomycin and 0.25 µg.mL⁻¹ Amphotericin B in HBSS). After several washes in the same medium, lung fragments were dissociated for 1h at 37 °C with intermittent agitation in a dissociation medium consisting of 1mg/ml Collagenase/Dispase (Roche), 40 U Dnase I (Thermo), 100 units.ml⁻¹ Penicillin, 100 µg.ml⁻¹ Streptomycin and 0.25 µg.mL⁻¹ Amphotericin B in HBSS in RPMI base medium. The enzymatic reaction was inactivated by adding 10% Fetal Bovine Serum (FBS) and the samples were filtered through a 70 µm cell strainer, to filter out non-dissociated lung pieces. After centrifugation for 5min at 250 g, the samples were resuspended in a small volume of Advanced DMEM/F12 base medium with 100 units.ml⁻¹ Penicillin, 100 µg.mL⁻¹ Streptomycin and 1x Glutamax, then mixed with Geltrex (Thermo) in a 1:3 ratio. 40 µL drops were placed in 24 well plates and incubated at 37 °C for 30 min to solidify the gel. Finally, 400 µL of human self-renewal medium (hSRm) (Supplementary Table 1) were added to each drop and plates incubated under standard cell culture conditions (37 °C; 5% CO₂). Medium was changed twice a week.

After 10-14 days of primary culture, lung organoids are ready for passage or cryopreservation. For passage, the medium was removed and 500 µL of cold Organoid Harvesting Solution (Cultrex) added to each well. Geltrex drops were removed, mechanically dissociated and collected in a 15 mL tube. Cold Advanced DMEM/F12 base medium was added up to 10 mL and the samples were centrifugated for 5 min at 100 g. The pellet was resuspended in undiluted Geltrex according to the desired splitting ratio (1:2 to 1:4). After gel solidification, 400 µL of hSRm medium was added in each well.

For freezing, Geltrex drops were detached and dissociated as described for passaging. After centrifugation, the pellets were resuspended in cold freezing medium (50% hSRm + 40% FBS + 10% DMSO), transferred overnight to the -80 °C freezer then to the liquid nitrogen for long term storage.

## Human fetal lung mesenchyme culture

During the first passaging of lung organoids, lung mesenchymal cells that had attached to the bottom of the well were recovered using 0.25% Trypsin-EDTA solution, followed by enzyme inactivation with 10% FBS in PBS. These cells were also retrieved after organoid centrifugation by collecting part of the supernatant above the organoid pellet. The cells were then incubated in 25 cm² flasks coated with type I collagen (Sigma) and cultured in Advanced DMEM/F12 base medium supplemented with 10% FBS. Medium was changed twice a week until confluence. Lung mesenchymal cells were passaged several times and cryopreserved in the freezing medium detailed above.

## Airway and alveolar differentiation of lung organoids
407 Lung organoids were maintained in hSRm medium up to passage 5. Just after passaging this
408 medium was replaced with either airway 9 or alveolar differentiation medium 26(Supplementary
409 Table 1). Organoids were then cultured for an additional 2 weeks until fixation and immunostaining.

410 Whole mount immunostaining of organoids

411 Organoids immunostaining was performed following the protocol described in Dekkers et al 66.
412 Lung organoids were recovered from Geltrex drops and washed with cold DPBS (MgCl2+/CaCl2+)
413 after centrifugation. Organoids were gently transferred to 1% bovine serum albumin (BSA) coated
414 15 mL tubes and fixed with 4% formaldehyde overnight at 4 °C. On the next day, the 15 mL tube
415 was filled with 1% Tween in DPBS (MgCl2+/CaCl2+) (PBT) up to 10 mL, gently mixed, centrifugated
416 at 70 g for 5 min at 4 °C. Organoids were either stored in PBT or used for immunolabeling.

417 For immunolabeling, organoids were first blocked for 1h in organoid washing buffer (OWB:
418 0.1% Triton + 0.2% BSA in DPBS) and then incubated overnight with primary antibodies using the
419 same solution, with mild shaking at 4 °C. On the next day, the samples were washed with OWB
420 for approximately 8 hours. The solution was changed every 2 hours. Secondary antibodies were
421 incubated overnight in OWB with mild shaking at 4 °C. Samples were counterstained with 4',6-
422 diamidino-2-phenylindole (DAPI), transferred to imaging dishes (Ibidi) and imaged with a spinning
423 disk confocal microscope Nikon Ti2E (Nikon). Images acquisition was performed with the NIS-
424 Elements software (Nikon). The list of the primary and secondary antibodies used are shown in
425 Supplementary Table 2.

426 Lung on chip culture

427 Microfluidic S1TM chips were purchased from Emulate Inc (Boston, USA). Chip handling and
428 activation was performed as per the manufacturer's indications. Briefly, one day before chip
429 seeding, the devices were activated using ER1/ER2 reagents. Subsequently, top and bottom
430 channels were incubated with 200 µg.mL-1 of human Collagen IV (C5533, Sigma) and 30 µg.mL-1
431 of Fibronectin (354008, Corning) at 37 °C overnight. The next day (day 0, see Figure 2A), the
432 coating solution was removed and washed with DPBS, the chips were then ready for cell seeding.

433 Lung organoids up to passage 3 were recovered from Geltrex matrix as performed for
434 passaging. The equivalent of 2 drops containing organoids were used for each chip. The organoids
435 pellet was resuspended with an appropriate amount of hSRm medium (40 µL per chip) and
436 mechanically fragmented using a P200 pipette. The level of fragmentation was verified by a
437 standard benchtop microscope, to avoid the seeding of isolated cells. Chips were seeded with few
438 microliters of cell suspension in the top channel and placed in an incubator at 37 °C overnight.
439 The next day, hSRm medium was added to the cells. Non adherent cells were gently washed
440 away. On day 2, sample-matched lung mesenchymal cells were detached from the culture flasks
441 and seeded on the bottom channel at a density of 0.5 x 10⁶ cells per mL. In the meantime, Alveolar
442 or Airway differentiation media (Supplementary Table 1) were added into top and bottom channel
443 inlet reservoirs of the Pods (Emulate). When good cell attachment was reached, the chips were
444 inserted into the Pods, placed into a ZOE CM1 device (Emulate) and top and bottom channels
445 were perfused with medium at flow rate of 30 µL.h⁻¹. On day 7, when the epithelial layer had
446 reached 100% confluence, an air-liquid interface (ALI) was established by emptying media from
447 the top channel. Thereafter, lung epithelial cells were fed through the bottom channel, perfused
448 by the same differentiation medium. Chips were finally used for experiments on day 14 (alveolar chips) and day 21 (airway chips).
449

450 **Immunostaining on-chip**

451 Chips were unmounted from the Pods and fixed in formaldehyde 4% for 30 min, rinsed with DPBS and carefully cut in half using a scalpel blade. The samples were then placed in 24-well plates and treated with a permeabilization solution (0.1% Triton in DPBS) for 30 min, followed by blocking (2% BSA in DPBS) for 1 hour at room temperature. Next, primary antibodies diluted in 1% BSA in DPBS were incubated overnight at 4 °C. On the following day, secondary antibodies, diluted in 1% BSA in DPBS, were added for 2 hours. Samples were counterstained with DAPI and mounted in FluoromountG (Thermo Fisher Scientific) before observation with a spinning disk confocal microscope Nikon Ti2E (Nikon). Images were acquired with the NIS-Elements software (Nikon). Details of the primary and secondary antibodies and corresponding dilutions used are listed in Supplementary Table 2.
452
453
454
455
456
457
458
459
460

461 To quantify the percentage of positively stained cells, maximal intensity projections were 462 generated using Fiji 67 and analyzed with QuPath version 0.5.1 68 softwares. QuPath built-in tools 463 were used for nuclei segmentation followed by cell classification using an interactive machine 464 learning based approach. Percentage of positively stained cells was calculated as (number of 465 stained cells/total nuclei number) x 100. Quantification of cell number per µm² (Supplementary 466 Figures 2A and 3A) was based on the ratio of counted nuclei per area of the chip. 467

467 **RNA extraction and quantitative real-time PCR**

468 For RNA preparation, cells on chips were lysed with 350 µL of RNeasy Lysis buffer + 2% DTT 469 (w/v). Total RNA was isolated using RNeasy microRNA kit according to the manufacturer's 470 instructions (Qiagen). RT-qPCR was performed in technical triplicates using the Luna Universal 471 One-Step RT-qPCR Kit (New England Biolabs), following the manufacturer's instructions. qPCR 472 was performed on a QuantStudio 6 Flex thermocycler (Applied Biosystems, Thermo). Results are 473 presented as relative RNA levels quantified by the 2-ΔΔCt method 69 and normalized to the 474 endogenous control beta-actin. The gene expression profile was obtained from at least three 475 independent experiments. Primer sequences are shown in Supplementary Table 3. 476

476 **Bacterial challenge of alveolar chips and bacterial enumeration**

477 Inoculates of the Corynebacterium accolens (Ca) strain C781 were grown overnight in BHI broth 478 supplemented with 1% Tween 80 70. Experimental starter cultures of Streptococcus pneumoniae 479 (Spn) isolates TIGR4 and 6B ST90 were prepared and grown as previously described in ref 35. 480 Briefly, stationary phase Ca or midlog Spn were collected by centrifugation, washed three times 481 in DPBS followed by a 1:100 dilution in DPBS and dilution to 500 organisms per microliter using 482 isolate specific CFU OD600 per mL conversion factors to make a challenge inoculum of 800 µL. 483 Alveolar chips were challenged with 100 µl (50,000 organisms) of the challenge inoculum by 484 perfusion through the apical input reservoir of the Emulate Pod at 1000 µL.h⁻¹. Chips where 485 exposed to the inoculum for 6 min. 486

486 Post-challenge inoculate was recovered from the output reservoir of the Emulate pod,
487 pelleted, and suspended in 200 µL DPBS for CFU serial dilution plating (1:6). Bacterial adherence
within the device was determined by subtracting the recovered post-challenge inoculate CFU
counts from the counts of the challenge inoculum. Apical bacterial burden of the alveolar chips
was determined by flushing the apical side with 500 µL of DPBS at 1000 µL.h⁻¹ flow rate and
collection of the perfused DPBS from the output reservoir. This was then pelleted and suspended
in 200 µL DPBS for CFU serial dilution plating (1:6). Transmigrated bacteria across the alveolar
barrier into the bottom chamber perfusion was determined by collecting total media from the
bottom chamber output reservoir of the Emulate pod. This sample was pelleted by centrifugation
and suspended in 200 µL DPBS for CFU serial dilution plating (1:6). All bacterial dilutions were
plated on 5% Columbia blood agar plates and grown overnight at 37 °C with 5% CO₂.

497 SARS-CoV-2 infection of alveolar chips

498
Alveolar chips were cultured for 7 days in ALI conditions prior to SARS-CoV-2 infection. Chips and
499
pods were then transferred from the ZOE CM1 device to a biosafety cabinet within a BSL3
500
laboratory. For each chip, 10⁶ RNA viral copies per µL of Delta and Omicron BA.5 viral stocks
501
were used ⁷¹,⁷². Viral inputs were diluted in DMEM/F12 medium to a final volume of 200 µL and
502
added into the pod's top channel inlet reservoir. A 1 min pulse at a flow rate of 1000 µL.h⁻¹ was
503
programmed on the ZOE CM1 machine for viral inoculation. Chips were then incubated for 3 h at
504
37 °C, 5% CO₂ under static conditions. Control chips were mock-treated with DMEM/F12 for the
505
same duration. Post-infection, the remaining viral inoculum in the pods were collected for RT-
506
qPCR analysis, and the chips were subjected to a series of washes. Briefly, 200 µL of DPBS was
507
added to the top channel inlet reservoirs, followed by three 5 min pulses at 1000 µL.h⁻¹ on a ZOE
508
CM1 machine. In between each pulse we let the chips 5 min without perfusion, resulting in a total
509
washing time of 30 min. A last pulse with DMEM/F12 was performed, followed by 20 min
510
incubation at 37 °C. After this step, the media was collected in the outlet for RT-qPCR analysis.
511
ALI conditions were then re-established. Apically released viruses were collected daily by loading
512
200 µL Advanced DMEM/F12 in the pod top channel inlet reservoir, followed by 1 min pulse at
513
1000 µL.h⁻¹ in ZOE and by 20 min incubation at 37 °C. ALI was re-established after this step. On
514
day 4, chips were either fixed in formaldehyde 4% for 30 min or the cellular RNA was isolated with
515
RNeasy microRNA kit (Qiagen). Samples were stored until further analysis.

516 Viral RNA quantification

517
Top and bottom channel effluents collected at days 0, 1 2 and 4 post-infection were inactivated
518
for 20 min at 80 °C and subsequently subjected to RT-qPCR analysis with the Luna Universal
519
One-Step RT-qPCR Kit (New England Biolabs), following the manufacturer's instructions. SARS-
520
CoV-2 RNA was quantified in a final volume of 5 µL per reaction in 384-well plates using SARS-
521
CoV-2 N-specific primers on a QuantStudio 6 Flex thermocycler (Applied Biosystems, Thermo).
522
Standard curve was performed in parallel using purified SARS-CoV-2 viral RNA ⁵.

523 Scanning electron microscopy

524
Samples were fixed with 2.5% glutaraldehyde in 0.1 M cacodylate buffer for 1 h at room
525
temperature and then for 12 h at 4 °C to inactivate SARS-CoV-2. Samples were then washed in
526
0.1 M cacodylate buffer and several times in water and incubated for 1 h at room temperature in
527
1% osmium tetraoxide. After dehydration by incubation in increasing concentrations of ethanol,
samples were critical point dried with hexamethyldisilazabe, mounted on a stub, and analyzed by
field emission scanning electron microscopy with a Jeol IT700HR microscope operating at 3 kV.

530 Quantification of Interferons using ultra-sensitive digital ELISA (Simoa) assays

531 Prior to protein analysis, samples were treated in a BSL3 laboratory for viral inactivation as
532 described by Robinot et al ⁵. Briefly, 2.5 µL of 10% Triton X-100 solution (Sigma) were added to
533 25 µL of each lung-on-chip apical lavage supernatant sample (1% final concentration) to be
534 analyzed for IFNα, IFNβ and IFNλ3. Samples were then incubated 1 h at room temperature. Prior
535 to Simoa quantification, inactivated samples were diluted 1:5 by adding 110 µL of Diluent B
536 (Quanterix, Billerica, MA, USA) containing 11 µL of 10% Triton X-100 solution (1% final
537 concentration). To estimate the limit of quantification, 8 blanks containing only detector/sample
538 diluent were treated similarly.

539 IFNα, IFNβ and IFNI3 protein supernatant concentrations were quantified by Simoa digital
540 ELISA assays developed with Quanterix Homebrew kits as previously described ⁷³⁻⁷⁵. After
541 checking the absence of cross-reactivity, the three assays were multiplexed to decrease sample
542 volumes needed. The SBG enzyme concentration was 150 pM.

543 For the IFNα assay, which quantifies all IFNα subtypes with a similar sensitivity, the 8H1
544 antibody clone was used as a capture antibody after coating on paramagnetic beads (0.3 mg.mL⁻¹),
545 the 12H5 clone was biotinylated (biotin/antibody ratio = 30/1) and used as the detector at a
546 concentration of 0.3 µg.mL⁻¹, and the 11150 recombinant human IFNα17 protein (PBL Assay
547 Science, Piscataway, NJ, USA) was used as the standard. The limit of detection of the assay was
548 0.022 fg.mL⁻¹ and the mean of the blanks was 0.46 fg.mL⁻¹, including the dilution factor used (5.5).

549 For the IFNβ assay, the 710906-9 IgG1, kappa, mouse monoclonal antibody (PBL Assay
550 Science) was used as a capture antibody after coating on paramagnetic beads (0.3 mg.mL⁻¹), the
551 710323-9 IgG1, kappa, mouse monoclonal antibody (PBL Assay Science) was biotinylated
552 (biotin/antibody ratio = 40/1) and used as the detector antibody at a concentration of 1 µg.mL⁻¹,
553 and the 11415 recombinant human IFNβ protein (PBL Assay Science) was used to quantify IFNβ
554 concentrations. The limit of detection of the assay was 0.029 pg.mL⁻¹ and the mean of the blanks
555 was 0.17 pg.mL⁻¹, including the dilution factor used (5.5).

556 For the IFNλ3 assay, the 21730-1 IgG1, kappa, mouse monoclonal antibody (PBL Assay
557 Science) was used as a capture antibody after coating on paramagnetic beads (0.3 mg.mL⁻¹), the
558 MAB52591R IgG2a, mouse monoclonal antibody (R&D Systems, Minneapolis, MN, USA) was
559 biotinylated (biotin/antibody ratio = 60/1) and used as the detector antibody at a concentration of
560 0.3 µg.mL⁻¹, and the 5259-IL-025/CF recombinant human IFNλ3 protein (R&D Systems) was used
561 as calibrator. The limit of detection of the assay was 0.006 pg.mL⁻¹ and the mean of the blanks
562 was 0.82 pg.mL⁻¹, including the dilution factor used (5.5).

563 Statistics and reproducibility

Statistical analyses were performed with the Prism software v8.4.3 (GraphPad). Unless stated
564 otherwise, we used the nonparametric Mann-Whitney or Kruskal-Wallis tests. Statistical
565 significance was assigned when p values were <0.05. The nature of statistical tests and the
566 number of experiments (n) are reported in the figure legends.
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739 Acknowledgements

740 The authors would like to thank Olivier Schwartz and Florence Guivel-Benhassine for providing

741 SARS-CoV-2 virus samples, Hugo Mouquet for providing anti-spike and anti-N antibodies and

742 Sarah Vreugde for sharing bacterial strains. We thank the Single Cell Biomarkers UTechS of the
743 Institut Pasteur for support in conducting this study. We acknowledge the Flow Cytometry
744 Platform at Institut Pasteur for support in conducting this work. We thank the Biometrics Platform
745 (C2RT, Institut Pasteur) that is supported by France Génomique (ANR-10-INBS-09) and IBISA.
746 We gratefully acknowledge the UtechS Photonic BioImaging, (C2RT, Institut Pasteur) supported
747 by the French National Research Agency (France BioImaging; ANR-10-INBS-04; Investments for
748 the Future). Experimental work benefited from the support of ultrastructure bioimaging core
749 facilities of Institut Pasteur.

750

751 **Funding**

752 SG and LAC were supported by *the Pasteur COVID-19 RP call* for the COROCHIP project and by
753 the ANRS-23-PEPR-MIE-0006 *call in the frame of the* France 2030 program for the 3D-LUNGO
754 PEPR project. SG funded the purchase of chips with the support of *Institut Carnot Pasteur
755 Microbes et Santé (ANR 20 CARN 0023-01)* program. LAC was also supported by *the Urgence
756 COVID-19 Fundraising Campaign of Institut Pasteur (PFR4 project)*.

757

758 **Author contributions**

759 BFF designed and conducted most of the experiments including organoid, organ-on-chip and
760 SARS-CoV-2 infections; JWG derived lung bud organoid cultures and performed organoid
761 differentiation experiments; MC carried out and analyzed bacterial infection experiments; HM and
762 MHK assisted with organ-on-chip experiments; RY contributed to organoid and organ-on-chip
763 experiments; VB performed Simoa analyses; VM performed electron microscopy; JDS and HSM
764 contributed to the organoid derivation protocol; DD supervised the Simoa experiments; MH
765 supervised the bacterial experiments, helped secure funding and edited the manuscript; NS
766 assisted with the experimental designs and reviewed the data; LAC contributed to project
767 conceptualization, SARS-CoV-2 infections and acquired funding for the project; SG
768 conceptualized the project, secured funding, designed experiments and analyzed the data; BFF
769 and SG wrote the manuscript. All authors read, edited and approved the final version.
Figures

<figure><img src="image_3.png" /><figcaption>**Figure 1.** Derivation of three types of human fetal lung organoids for the production of airway and alveolar cell types. (A) Schematic representation of the cell culture pipeline used to produce different fetal lung organoid types. (B) Brightfield images of multipotent lung organoids in self-renewing conditions at passage 1 (left) and passage 2 (right). (C) Expansion of the organoid cultures over multiple passages. Each line corresponds to one experiment with a distinct organoid line. (D) Multipotent lung organoids showing positive immunostainings for SOX2 and SOX9 markers (E) Alveolar organoids showing typical alveolar type 2 cells identified with HT2-280 and anti-pro-SFTPC immunolabeling. (E') Higher magnification of the region depicted in (E). (F) Immunostaining of airway organoids showing typical cell types including basal (KRT5+), ciliated</figcaption></figure>
(ac-TUB+), club (SCGB1a1+) and goblet (MUC5AC+) cells. Scale bars: 75 µm (B), 50 µm (D and E), 20 µm (F).
<figure><img src="image_4.png" /><figcaption>**Figure 2: Characterization of human airway-on-chip and alveoli-on-chip systems.** (A) Schematic representation of the protocol used to derive alveolar and airway organoid-on-chip devices. (B) Immunolabelling of the alveoli-on-chip system. Left: AT1 (HT1-56+), AT2 (HT2-280+); middle: AT1 (RAGE+); right: AT2 (HT2-280+, pro-SFTPC+). (C) Percentage of cells labelled with the following alveolar markers: HT1-56, HT2-280 and pro-SFTPC. Each dot color corresponds to a different organoid line. Mean +/- standard deviation (SD) are plotted. (D-F) Comparative RT-qPCR analyses between multipotent organoids versus lung cells in the alveolar chips showing the relative expression of typical lung multipotent markers (SOX2 and SOX9) (D), the mature AT2 marker LAMP3 (E) and the mature AT1 marker CLIC5 (F) (D-F: Median +/- interquartile range are plotted and statistically significant differences are assessed with the Mann-Whitney test. n=4</figcaption></figure>
independent experiments with 4 different samples). (G) Immunolabelling of airway cell types in the airway-on-chip system. Left: ciliated (ac-TUB+) and goblet (MUC5AC+) cells; middle: ciliated (ac-TUB+) and club (SCGB1A1+) cells; right: ciliated (ac-TUB+) and basal (KRT5+) cells. (H) Percentage of ciliated (ac-TUB+) and basal (KRT5+) cells in airway chips. Mean +/- SDs are plotted. (B, G) Scale bars: 50µm.
A

① Innoculation

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② ALI

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③ Lavages

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④ IF

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B
Inoculum

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C
Top channel eff. (24hpi)

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D
Bottom channel eff. (24hpi)

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E
HT1-56/DAPI

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F
% AT2 cells

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G
% AT1 cells

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**Figure 3: Streptococcus pneumoniae strains infect the human alveoli on-chip system.** (A) Schematic representation of the infection protocol with *S. pneumoniae* strains (TIGR4 and 6B ST90) or *C. accolens* (commensal control). ALI: air-liquid-interface, IF: immunofluorescence (B) Colony forming unit (CFU) counts the bacteria inoculum. (C) CFU counts of respective bacteria collected after 24h in the top channel effluent. (D) CFU counts of respective bacteria collected after 24h in the bottom channel effluent. Median +/- interquartile range are plotted and statistically significant differences between bacteria were compared with Kruskal-Wallis test. (n= 3 independent experiments with 3 different organoid lines; geometric means of 2 technical counts per chip are shown). Dotted green in lines B-D: limit of detection value (20 total CFU). (E) Representative images of bacterium infection in alveolar chips. HT1-56 and HT2-280 immunolabeling identifies AT1 and AT2 cells, respectively. hpi: hours post-infection. Scale bars: 50µm. (F and G) Percentages of AT2 and AT1 cells upon bacterial infections on-chip. Mean +/- standard deviation, n=2 independent experiments. Minimum cell count per experiment above 20000.
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**Figure 4: SARS-CoV-2 variant Delta, but not Omicron BA.5, replicates in human alveolar chips.** (A) Schematic representation of SARS-CoV-2 infection protocol in alveoli-on-chip system. ALI: air-liquid-interface (B) Detection of SARS-CoV-2 (Delta) infected cells by immunolabeling with anti-spike antibodies (red staining). HT2-280 antibody (in cyan) stains AT2 cells. Counterstaining with DAPI and F-actin (phalloidin, in gray). Orange arrows: spike and HT2-280 co-labelled cells. Scale bars: 50 µm. (C) Percentage of spike+ cells in Delta versus mock-infected conditions. Median +/- interquartile range (IQR) are plotted and statistically significant differences are compared with the Mann-Whitney test. (n= 4 independent experiments with 3 organoid lines). (D) Proportion of HT2-280+ cells among spike+ cells. Mean +/- standard deviation (SD) are plotted. (E) Kinetics of SARS-CoV-2 viral load in top channel effluents measured by RT-qPCR. Mean +/- SD are plotted. (F) Viral RNA load in top channel effluent at 4 dpi. Median +/- IQR are plotted and statistically significant differences are compared with the Mann-Whitney test. Each dot color represents a different organoid line. (E-F, n= 6 independent experiments with 6 organoid lines). (G) Viral RNA detection in cellular extracts at 4 dpi. Median +/- IQR are plotted and statistically significant differences are compared with the Mann-Whitney test. Each dot color represents a different organoid line. (n= 3 independent experiments with 3 organoid lines). (H) IFNα protein concentrations, expressed as IFNα17 equivalents, detected in top channel washes recovered at 4 dpi (n= 5 independent experiments with 5 organoid lines. Each dot color represents an organoid line. Median +/- interquartile range are plotted and Kruskal-Wallis tests are used for addressing statistically significant differences). (I) Relative RNA expression of ISG15, MX2 and IFIT1 at 4 dpi (n=3 independent experiments with 3 organoid lines. Median +/- IQR are plotted and statistically significant differences are compared with the Kruskal-Wallis test. Each dot color represents a different organoid line).
<figure><img src="image_27.png" /><figcaption>**Supplementary Figure 1: Multipotent lung organoids form a simple and tight epithelium on-chip.** Cell adherent and tight junctions revealed with E-cadherin and ZO-1 immunolabeling, respectively. DAPI was used to counterstain nuclei. Scale bars: 100 µm.</figcaption></figure>
<figure><img src="image_28.png" /><figcaption>**Supplementary Figure 2:*** *Streptococcus pneumoniae* infection in human alveolar chips. (A) Quantification of number of cells per chip based on the ratio of nuclei number per um² chip area. (B) Streptococcus immunolabeling of bacteria specimens surrounding the bottom channel lung mesenchyme at 24 hours postinfection (hpi). Scale bars: 100 µm.</figcaption></figure>
A

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B

<figure><img src="image_30.png" /><figcaption>**Supplementary Figure 3: Effects of SARS-CoV-2 infection on alveolar cell populations.** (A) Quantification of number of cells per chip based on the ratio of nuclei number per um² chip area. (B) Percentage of total HT2-280+ cells per condition. Median +/- interquartile range are plotted and statistically significant differences are compared with the Kruskal-Wallis test.</figcaption></figure>
<figure><img src="image_31.png" /><figcaption>**Supplementary Figure 4: Ultrastructural features of AT2-like cells upon SARS-CoV-2 infection on-chip.** (A) Scanning electron microscopy images evidence abundant small projections similar to microvilli in cells of an uninfected alveolar chip (arrows in A and A'). (B) Scanning electron microscopy images of a SARS-CoV-2 infected chip. (C) Viral particles observed at a higher resolution image than B.</figcaption></figure>
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**Supplementary Figure 5: Comparison of SARS-CoV-2 variant infections in human alveolar chips.** (A) Immunolabeling of SARS-CoV-2 infected cells with anti-NCP1-antibody (green). Alveolar cells are identified with an anti-pro-SFTPC antibody (magenta). DAPI is used to counterstain nuclei. Scale bars: 50 µm (B) Percentage of NCP1+ cells in different conditions at 4 dpi. (C) Percentage of pro-SFTPC+ cells in different conditions at 4 dpi. Median +/- interquartile range are plotted and statistically significant differences are compared with the Kruskal-Wallis test.
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<figure><img src="image_34.png" /><figcaption>Supplementary Figure 6. IFN host-response to SARS-CoV-2 infection in alveolar chips. (A)</figcaption></figure>

IFNβ and (B) IFNλ3 proteins detected in top channel washes recovered at 4 days post-infection. (n=5 independent experiments with 5 different organoid lines. Each dot color represents an organoid line. Median +/- interquartile range are plotted and Kruskal-Wallis tests are used for addressing statistically significant differences).