Adult stem cell-derived complete lung organoid models emulate lung disease in COVID-19

  1. Courtney Tindle
  2. MacKenzie Fuller
  3. Ayden Fonseca
  4. Sahar Taheri
  5. Stella-Rita Ibeawuchi
  6. Nathan Beutler
  7. Gajanan Dattatray Katkar
  8. Amanraj Claire
  9. Vanessa Castillo
  10. Moises Hernandez
  11. Hana Russo
  12. Jason Duran
  13. Laura E Crotty Alexander
  14. Ann Tipps
  15. Grace Lin
  16. Patricia A Thistlethwaite
  17. Ranajoy Chattopadhyay  Is a corresponding author
  18. Thomas F Rogers  Is a corresponding author
  19. Debashis Sahoo  Is a corresponding author
  20. Pradipta Ghosh  Is a corresponding author
  21. Soumita Das  Is a corresponding author
  1. Department of Cellular and Molecular Medicine, University of California San Diego, United States
  2. HUMANOID CoRE, University of California San Diego, United States
  3. Department of Computer Science and Engineering, Jacobs School of Engineering, University of California San Diego, United States
  4. Department of Pathology, University of California San Diego, United States
  5. Department of Immunology and Microbiology, The Scripps Research Institute, United States
  6. Division of Cardiothoracic Surgery, University of California San Diego, United States
  7. Division of Cardiology, Department of Internal Medicine, UC San Diego Medical Center, United States
  8. Pulmonary Critical Care Section, Veterans Affairs (VA) San Diego Healthcare System, United States
  9. Division of Pulmonary and Critical Care, Department of Medicine, University of California, San Diego, United States
  10. Cell Applications Inc., United States
  11. Division of Infectious Diseases, Department of Medicine, University of California, San Diego, United States
  12. Department of Pediatrics, University of California, San Diego, United States
  13. Department of Medicine, University of California, San Diego, United States
10 figures, 10 tables and 1 additional file

Figures

Figure 1 with 1 supplement
A rationalized approach to building and validating human preclinical models of COVID-19.

A) Whisker plots display relative levels of angiotensin-converting enzyme II (ACE2) expression in various cell types in the normal human lung. The cell types were annotated within a publicly available single-cell sequencing dataset (GSE132914) using genes listed in Table 1. p-values were analyzed by one-way ANOVA and Tukey’s post hoc test. (B) Formalin-fixed paraffin-embedded sections of the human lung from normal and deceased COVID-19 patients were stained for SFTPC, alone or in combination with nucleocapsid protein and analyzed by confocal immunofluorescence. Representative images are shown. Scale bar = 20 µm. (C) Schematic showing key steps generating an adult stem cell-derived, propagable, lung organoid model, complete with proximal and distal airway components for modeling COVID-19-in-a-dish. See Materials and methods for details regarding culture conditions. (D) A transcriptome-based approach is used for cross-validation of in vitro lung models of SARS-CoV-2 infection (left) versus the human disease, COVID-19 (right), looking for a match in gene expression signatures.

Figure 1—figure supplement 1
Alveolar type II pneumocyte hyperplasia is a pathognomonic feature of lung injury in COVID-19.

(A) Whisker plots display relative levels of TMPRSS2 expression in various cell types in the normal human lung. The cell types were annotated within a publicly available single-cell sequencing dataset (GSE132914) using genes listed in Table 2. p-values were analyzed by one-way ANOVA and Tukey’s post hoc test. (B) Formalin-fixed paraffin-embedded (FFPE) sections of the human lung from deceased COVID-19 patients were analyzed by H&E staining. Representative fields are shown. Images on the right are magnified areas indicated with boxes on the left. Arrows indicate alveolar type II pneumocyte hyperplasia. (C, D) FFPE sections of the human lung from normal and deceased COVID-19 patients were stained for AT2 and club cell markers and either ACE2 or viral nucleocapsid protein and analyzed by confocal immunofluorescence. Representative images are shown. Scale bar = 50 µm. (E) FFPE sections of the human lung from normal and deceased COVID-19 patients were stained for viral nucleocapsid antibody. Representative images are shown. Arrows indicate infected cells.

Figure 2 with 5 supplements
Adult stem cell-derived lung organoids are propagatable models with both proximal and distal airway components.

(A) Schematic lists the various markers used here for qPCR and immunofluorescence to confirm the presence of all cell types in the 3D lung organoids here and in 2D monolayers later (in Figure 3). (B–H) Bar graphs display the relative abundance of various cell-type markers (normalized to 18S) in adult lung organoids (ALO), compared to the airway ( normal human bronchial epithelial cell [NHBE]) and/or alveolar (AT2) control cells, as appropriate. p-values were analyzed by one-way ANOVA. Error bars denote SEM; n = 3–6 datasets from three independent ALOs and representing early and late passages. See also Figure 2—figure supplement 2 for individual ALOs. (I, J). H&E-stained cell blocks were prepared using HistoGel (I). Slides were stained for the indicated markers and visualized by confocal immunofluorescence microscopy. Representative images are shown in (J). Scale bar = 50 µm. (K) 3D organoids grown in 8-well chamber slides were fixed, immunostained, and visualized by confocal microscopy as in (J). Scale bar = 50 µm. See also Figure 2—figure supplement 2. Top row (ACE2/KRT5-stained organoids) displays the single and merged panels as max projections of z-stacks (top) and a single optical section (bottom) of a selected area. For the remaining rows, the single (red/green) channel images are max projections of z-stacks; however, merged panels are optical sections to visualize the centers of the organoids. All immunofluorescence images showcased in this figure were obtained from ALO lines within passage #3–6. See also Figure 2—figure supplements 35 for additional evidence of mixed cellularity of ALO models, their similarity to lung tissue of origin, and stability of cellular composition during early (#1–8) and late (#8–15) passages, as determined by qPCR and flow cytometry.

Figure 2—figure supplement 1
Lung organoids are reproducibly established from three different donors and propagated in each case over 10 passages.

(A) Schematic displaying the key demographics of the patients who served as donors of the lung tissue as a source of adult stem cells for the generation of organoids. Three organoid lines were generated, ALO1-3. ALO, adult lung organoids. (B–D) Bright-field microscopy of organoids in 3D culture grown in different media/conditions (B), imaged serially over days (C), and at different passages (D). Scale bar = 100 µm. (E) Serial cuts of HistoGel-embedded organoids were analyzed by H&E staining. Scale bar = 50 µm.

Figure 2—figure supplement 2
Adult stem cell-derived lung organoids are propagatable models with both proximal and distal airway components.

(A) Schematic lists the various markers used here for qPCR and immunofluorescence to confirm the presence of all cell types in the 3D lung organoids here and in 2D monolayers later (in Figure 3). (B–H) Bar graphs display the relative abundance of various cell-type markers (normalized to 18S) in adult lung organoids (ALO), compared to the airway ( normal human bronchial epithelial cell [NHBE]) and/or alveolar (AT2) control cells, as appropriate. p-values were analyzed by one-way ANOVA. Error bars denote SEM; n = 3–6 datasets. (I) 3D organoids grown in 8-well chamber slides were fixed, immunostained, and visualized by confocal microscopy, as in Figure 2K. Scale bar = 50 µm.

Figure 2—figure supplement 3
Adult stem cell-derived lung organoids (ALO) generally recapitulate cell-type-specific gene expression patterns observed in the adult lung tissue (ALT) from which they originate.

(A, B) Schematics depict the study goal in this figure, that is, analysis of cell-type-specific transcripts in ALO vs. ALT. (C–L) Bar graphs display the relative abundance of various cell-type markers (normalized to 18S) in adult lung organoids from early passage (ALO), compared to the adult lung tissue (ALT) from which they were derived. p-values were analyzed by one-way ANOVA. Error bars denote SEM; n = 3–6 datasets. Statistically significant differences were not noted in any of the transcripts analyzed.

Figure 2—figure supplement 4
Adult stem cell-derived lung organoids (ALO) generally maintain their cellular composition from early (E) to late (L) passages, as determined by cell-type-specific gene expression by qPCR.

(A, B) Schematics depict the study goal in this figure, that is, analysis of cell-type-specific transcripts in early (E) vs. late (L) passages of ALO1-3 lines. (C–K) Bar graphs display the relative abundance of various cell-type markers (normalized to 18S) in adult lung organoids from either early (E) or late (L) passages of ALO lines 1–3. p-values were analyzed by one-way ANOVA. Error bars denote SEM; n = 3–6 datasets. Statistically significant differences were not noted in any of the transcripts analyzed.

Figure 2—figure supplement 5
Adult stem cell-derived lung organoids (ALO) comprised both proximal and distal airway epithelial population and generally maintain such diversity from early (E) to late (L) passages, as determined by FACS.

Lung monolayers were dissociated into single cells and analyzed using flow cytometry. Gating strategy depicted in (A), isotype controls in (B) and (C) show various lung cell types. Numbers denote %.Table in (D) lists marker-positive cell fractions in ALO1-3, presented either as averaged over both early and late passages combined (column 2), or separated into early (column 3) or late (column 4) passages. These findings are consistent with others’ findings by multichannel FACS (Bonser et al., 2021) showing that although many of these markers are highly expressed in a certain cell type, they are shared at lower levels among other cell types.

Figure 3 with 3 supplements
Monolayers derived from lung organoids differentiate into proximal and distal airway components.

(A, B) Samples collected at various steps of lung organoid isolation and expansion in culture, and from the two types of monolayers prepared using the lung organoids were analyzed by bulk RNA seq and the datasets were compared for % cellular composition using the deconvolution method, CYBERSORTx. Schematic in (A) shows the workflow steps, and bar plots in (B) show the relative proportion of various lung cell types. (C, D) hiPSC-derived AT2 cells and alveolospheres (C) were plated as monolayers and analyzed by RNA seq. Bar plots in (D) show % cellular composition. (E, F) Submerged adult lung organoids (ALO) monolayers in transwells (E) or monolayers were grown as air-liquid interphase (ALI) models (F) were fixed and stained for the indicated markers and visualized by confocal immunofluorescence microscopy. The representative max projected z-stack images (left) and the corresponding orthogonal images (right) are displayed. Arrows in (E) indicate AT2 cells; arrowheads in (E) indicate club cells; asterisk in (F) indicates bundles of cilia standing perpendicular to the plane of the ALI monolayers; arrowheads in (F) indicate bundles of cilia running parallel to the plane of the ALI monolayers. Scale bar = 20 µm. (G) Monolayers of ALO1-3 were challenged with SARS-CoV-2 for indicated time points prior to fixation and staining for KRT5, SARS-COV2 viral nucleocapsid protein and DAPI and visualized by confocal microscopy. A montage of representative images are shown, displaying reticulovesicular network patterns and various cytopathic effects. Scale bar = 15 µm. (H) Monolayers of ALO, hiPSC-derived AT2 cells, and other alternative models (see Figure 3—figure supplements 12) were infected or not with SARS-CoV-2 and analyzed for infectivity by qPCR (targeted amplification of viral envelope, E gene). See also Figure 3—figure supplement 3B, C for comparison of the degree of peak viral amplification across various models. (I) ALO monolayers pretreated for 4 hr with either vehicle (DMSO) control or EIDD-parent (NHC) or its metabolite EIDD-2801/MK-4482 were infected with SARS-CoV-2 and assessed at 48 hpi for infectivity as in (H). Line graphs display the relative expression of E gene. Error bars display SEM. p value **<0.01; ***<0.001.

Figure 3—figure supplement 1
Monolayers derived from adult lung organoids (ALO) can form an epithelial barrier.

(A–G) Two different types of 2D polarized monolayers are prepared using adult lung organoids. Schematics in (A) and (E) show growth as submerged or air-liquid interphase (ALI) models, respectively. Panel (B) shows bar graphs with transepithelial electrical resistance (TEER) across submerged monolayers grown in transwells. Panel (C) shows bar graphs for relative fluorescence unit (RFU) of the FITC-labeled dextran flux from the apical to basolateral chambers of a submerged monolayer. (D) Brightfield images show representative fields of submerged monolayers grown on transwells. Scale bar = 100 µm. Arrows indicate self-organized vacuolar regions were seen. (F) Bar graphs with TEER across ALO-derived monolayers grown as ALI models. (G) Brightfield images show representative fields of ALI monolayers at two different time points during culture. Scale bar = 100 µm. (H, I) Submerged monolayers of ALO were fixed with methanol (H) or paraformaldehyde (I) prior to co-staining with DAPI (blue; nuclei) and either occludin (green [H] or phalloidin [red; I]). Scale bar = 20 µm. (J) ALO monolayers were grown as ALI models were fixed and co-stained for SFTPC (red), Ac-Tub (green), and DAPI (blue; nuclei) and visualized by confocal immunofluorescence microscopy. Scale bar = 20 µm. (K, L) Schematic in (K) shows the study design for challenging submerged monolayers with 500 ng/ml LPS, followed by TEER measurement. Bar graphs in (L) display the % change in TEER observed with or without LPS treatment normalized to the baseline TEER. p-values were analyzed by one-way ANOVA. Error bars denote SEM; n = 3–6 datasets. **p< 0.01.

Figure 3—figure supplement 2
Alternative models of lung epithelial cells used in this work for modeling SARS-CoV-2 infection and/or as a control for gene expression studies.

(A–D) Monolayers of primary airway epithelial cells (small airway epi; A B; bronchial epi; C, D) were visualized by bright field microscopy (A, C) or by fixing, staining, and visualizing by confocal microscopy (B, D). Representative images in (B) and (D) are presented as maximum projected z-stacks on the left and as an orthogonal view on the right. (E–G) hiPSC-derived AT2 cells, prepared using the i-HAEpC2 cell kit, were grown in monolayers on transwell inserts to form a polarized. Brightfield images are shown in (F). Monolayers were fixed and stained for several markers and analyzed by confocal microscopy. Representative images are shown in (G). Scale bar = 20 µm.

Figure 3—figure supplement 3
Proof of SARS-CoV-2 infectivity.

(A) Monolayers of ALO1-3 were challenged with SARS-CoV-2 for indicated time points prior to fixation and staining for KRT5 (red) and viral nucleocapsid protein (green) and DAPI (blue; nuclei) and visualized by confocal microscopy. Representative images are shown, displaying various cytopathic effects. Scale bar = 15 µm. (B) Monolayers of adult lung organoids (ALO) (either transwell submerged models or air-liquid interphase [ALI], left) and monolayers of hiPSC-derived AT2 cells (right) were infected or not with SARS-CoV-2 and analyzed for viral envelope gene (E gene). Bar graphs display the relative expression of E gene in infected ALO monolayers, indicative of viral infection. (C) Line graphs show the change in E gene expression in infected monolayers over 24 hr period (from 48 hpi to 72 hpi) where values at 72 hpi are normalized to that at 48 hpi. Data is presented as SEM of three independent repeats.

Figure 4 with 2 supplements
Gene expression patterns in the lungs of patients with COVID-19 (actual disease) are recapitulated in lung organoid monolayers infected with SARS-CoV-2 (disease model).

(A–C) Publicly available RNA seq datasets (GSE151764) of lung autopsies from patients who were deceased due to COVID-19 or noninfectious causes (healthy normal control) were analyzed for differential expression of genes (B). The differentially expressed genes (DEGs) are displayed as a heatmap labeled with selected genes in (C). See also Figure 4—figure supplement 1 for the same heatmap with all genes labeled. (D) Reactome-pathway analysis shows the major pathways up- or downregulated in the COVID-19-afflicted lungs. See also Figure 4—figure supplement 2 for visualization as hierarchical ReacFoam. (E) Bar plots display the ability of the DEGs in the test cohort (GSE151764) to classify human COVID-19 respiratory samples from four other independent cohorts. (F) Bar plots display the ability of the DEGs in the test cohort (GSE151764) to classify published in vitro models for SARS-CoV-2 infection where RNA seq datasets were either generated in this work or publicly available. (G, H) Bar (top) and violin (bottom) plots compare the relative accuracy of disease modeling in four in vitro models used in the current work, as determined by the induction of COVID-19 lung signatures in each model. (G) Monolayer (left) and air-liquid interphase (ALI) models (right) prepared using adult lung organoids (ALOs). (H) Primary human small airway epithelium (left) and hiPSC-derived AT2 monolayers (right). Table 6 lists details regarding the patient cohorts/tissue or cell types represented in each transcriptomic dataset.

Figure 4—figure supplement 1
Differential expression analysis of RNA seq datasets from lung autopsies (normal vs. COVID-19).

Publicly available RNA seq datasets (GSE151764) of lung autopsies from patients who were deceased due to COVID-19 or noninfectious causes (normal lung control) were analyzed for differential expression of genes and displayed as a heatmap.

Figure 4—figure supplement 2
Reactome-pathway analysis of differentially expressed genes in lung autopsies (normal vs. COVID-19).

Reactome-pathway analysis of the differentially expressed genes shows the major pathways upregulated in COVID-19-affected lungs. Top: visualization as flattened (left) and hierarchical (right, insets) reactome. Bottom: visualization of the same data as tables with statistical analysis indicative of the degree of pathway enrichment.

Figure 5 with 3 supplements
Genes and pathways induced in the SARS-CoV-2-infected lung organoid monolayers (disease model) are induced also in the lungs of COVID-19 patients (actual disease).

(A–C) Adult lung organoid monolayers infected or not with SARS-CoV-2 were analyzed by RNA seq and differential expression analysis. Differentially expressed genes (DEGs; B) are displayed as a heatmap in (C). While only selected genes are labeled in panel (C) (which represent overlapping DEGs between our organoid model and publicly available COVID-19 lung dataset, GSE151764), the same heatmap is presented in Figure 5—figure supplement 1 with all genes labeled. (D) Reactome-pathway analysis shows the major pathways upregulated in SARS-CoV-2-infected lung organoid monolayers. See also Figure 5—figure supplement 2 for visualization as hierarchical ReacFoam. (E) A Venn diagram showing overlaps in DEGs between model (current work; B) and disease (COVID-19 lung dataset, GSE151764; Figure 4). (F) Bar plots display the ability of the DEGs in infected lung monolayers to classify human normal vs. COVID-19 respiratory samples from five independent cohorts. (G–I) Bar (top) and violin (bottom) plots compare the accuracy of disease modeling in three publicly available human lung datasets, as determined by the significant induction of the DEGs that were identified in the SARS-CoV-2-challenged monolayers. See also Table 6, which enlists details regarding the patient cohorts/tissue or cell types represented in each transcriptomic dataset.

Figure 5—figure supplement 1
Differential expression analysis of RNA seq datasets from adult lung organoid monolayers, infected or not, with SARS-CoV-2.

Adult lung organoid (ALO)-derived grown in transwells as submerged monolayers were infected or not with SARS-CoV-2 were analyzed by RNA seq and differential expression analysis. Differentially expressed genes are displayed as a heatmap.

Figure 5—figure supplement 2
Reactome-pathway analysis of differentially expressed genes in lung organoid monolayers infected with SARS-CoV-2.

Reactome-pathway analysis of the differentially expressed genes shows the major pathways upregulated in SARS-CoV-2-infected lung organoid monolayers. Top: visualization as flattened (left) and hierarchical (right, insets) ReacFoam. Bottom: visualization of the same data as tables with statistical analysis indicative of the degree of pathway enrichment.

Figure 5—figure supplement 3
Head-to-head comparison of our adult lung organoid (ALO)-derived model of COVID-19 versus another lung organoid model in their ability to recapitulate the differentially expressed genes (DEGs) observed in lung tissues from fatal cases of COVID-19.

(A) Venn diagrams show the number of overlapping and nonoverlapping DEGs (both up- and downregulated genes) between our organoid model and four human COVID-19 patient-derived samples (left). GSE151764 represents postmortem COVID-19 and normal lung tissues; GSE156063 represents upper airway samples from patients with COVID-19; GSE145926 represents sorted epithelial population from bronchoalveolar lavage fluid (BALF) derived from patients with varying severity of COVID-19; GSE157526 represents tracheal-bronchial cells infected with SARS-Cov2. (B) Venn diagrams as in (A), comparing a publicly available SARS-Cov2-infected human lung organoid model (GSE160435) and the same four human COVID-19 respiratory cohorts as in (A). (C) Venn diagrams show the DEGs between our organoid model and the publicly available lung organoid model. The comparison was carried out by calculating the percentage of the common up/down DEGs represented within the total up/down DEG for the two models in each Venn diagram.

Both proximal and distal airway components are required to model the overzealous host response in COVID-19.

(A) Schematic summarizing the immune signatures identified based on ACE2-equivalent gene induction observed invariably in any respiratory viral pandemic. The 166-gene ViP signature captures the cytokine storm in COVID-19, whereas the 20-gene subset severe ViP signature is indicative of disease severity/fatality. (B–D) Publicly available RNA seq datasets from commonly used lung models, Vero E6 (B), human bronchial organoids (C), and hPSC-derived AT1/2 cell-predominant lung organoids are classified using the 166-gene ViP signature (top row) and 20-gene severity signature (bottom row). (E–G) RNA seq datasets generated in this work using either human small airway epithelial cells (E), adult lung organoids as submerged or air-liquid interphase (ALI) models (left and right, respectively, in F) and hiPSC-derived AT2 cells (G) were analyzed and visualized as in (B–D). (H) Publicly available RNA seq datasets from fetal lung organoid monolayers (Lamers et al., 2021) infected or not with SARS-CoV-2 were analyzed as in (B–D) for the ability of ViP signatures to classify infected (I) from uninfected (U) samples. Receiver operating characteristics area under the curve (ROC AUC) in all figure panels indicate the performance of a classification model using the ViP signatures. (I) Summary of findings in this work, its relationship to the observed clinical phases in COVID-19, and key aspects of modeling the same. Table 6 lists details regarding the patient cohorts/tissue or cell types represented in each transcriptomic dataset.

Author response image 1
Publicly available RNA seq datasets (GSE153218) from Small Airway Epi (SAEp) monolayers12 infected or not with SARS-CoV-2 were analyzed for the ability of ViP signatures to classify infected (Inf) from uninfected (Uninf) samples.

ROC AUC indicate the performance of a classification model using the ViP signatures. Unlike the brochoalveolar monolayers (see Figure 6H in the revised manuscript) derived from fetal lung organoids in the same work, SAEp monolayers successfully induced the ViP signatures because the signatures were induced in infected monolayers.

Author response image 2
Author response image 3
Author response image 4

Tables

Table 1
A comparison of current versus existing lung organoid models available for modeling COVID-19.
AuthorSource of stem cellsPropagabilityCell typesSARS-COV-2 infectionDemonstrated reproducibility using more than one patientCost-effective (use of conditioned media)Notes
AT1AT2ClubBasalCiliatedGoblet
Zhou et alPMID: 29891677Small pieces of normal lung tissue adjacent to the diseased tissue from patients undergoing surgical resection for clinical conditions.Long term culture > 1 yInfection with H1N1 pandemic Influenza virusProximal differentiation (PD) of human Adult Stem Cell-derived airway organoid (AO) culture. Differentiation conditions (PneumaCult-ALI medium) increase ciliated cells. Serine proteases known to be important for productive viral infection, were elevated after PD.
Sachs et alPMID: 30643021Generation of normal and tumor organoids from resected surplus lung tissue of patients with lung cancers.long term culture for over 1 yearNot clearly mentionedairway organoid (AO) expressed no mesenchyme or alveolar transcripts. Strongly enriched for bulk lung and small airway epithelial signature limited to basal, club, and ciliated cells Withdrawal of R-spondin terminated AO expansion after 3–4 passages similar to the withdrawal of FGFs
Duan et alPMID: 32839764hPSC derived lung cells and macrophagesLowSARS-CoV-2 infection mediated damage onset by macrophages.Co-culture of lung cells and macrophages. Protocol followed enables alveolar differentiation process, although described presence of almost all lung cell types.
Salahudeen et alPMID: 33238290Cells sorted from human peripheral lung tissues.Distal Lung organoid with possibility of long-term cultureFrom differentiation of AT2After diff of basal cellsInfection and presence of dsRNA and nucleocapsidNo RNA seq of infected samples to compare with COVID Differentiation to different cell types SARS CoV2 infection in apical-out organoids (not polarized monolayers). The combination of EGF and the Noggin was optimal, without any additional growth-promoting effects of either WNT3A or R-spondin
Han et alPMID: 33116299hPSC-derived lung organoidsOrganoids were generated by 50 days of differentiationSARS-CoV-2 and SARS-CoV-2-Pseudo-Entry Viruses.AT1, AT2, stromal cells, low number of pulmonary neuroendocrine cells, proliferating cells, and airway epithelial cells were reported. Mostly AT2 based ACE2 receptor was used for virus infection. High throughput screen using hPSC-derived lung organoids identified FDA-approved drug candidates, including imatinib and mycophenolic acid, as inhibitors of SARS-CoV-2 entry.
Youk et alPMID: 33142113Adult alveolar stem cells isolated from distal lung parenchymal tissues by collagenase, dispase and sortingMultiple passages upto 10 monthsFrom AT2; Lost in higher passagesIn the organoid formSingle cell transcriptomic profiling identified two clusters and type I interferon signal pathway are highly elevated at three dpi
Mulay et alPMID: 32637946doi.org/10.1101/2020.06.29.174623Alv organoids with distal lung epithelial cells with lung fibroblast cellsIn the organoid formInfection of AT2 cells trigger apoptosis that may contribute to alveolar injury. Alteration of innate immune response genes from AT2 cells
Proximal airway ALI with heterogenous cellsInfection of ciliated and goblet cells Two separate models for SARS-CoV2 infection
Huang JPMID:32979316iPSC derived AT2 cell ALI modelBulk RNA seq after day 1 and day four infection. The infection induces rapid inflammatory responses.
Abo et alPMID: 32577635doi: 10.1101/2020.06.03.132639iPSC derived basal cells as oranoids or 2D ALIiPSCs transcripts match human lung better than cancer cell lines. iPSC AT2 cells express host genes mportant for SARS-CoV-2 infection.
iPSC AT2 cells as organoids or 2D ALI
Rock et alPMID: 19625615Bronchospheres were isolated from human lung tissue.Bronchospheres derived from human lung can act as stem cells and can differentiate into other cell types.
Lamers et alPMID: 33283287Lung organoids derived from fetal Lung epithelial bud tips and differentiated ALI model.14 passagesDetected SCGB3A2(ATII/club marker)2 subjects were mentionedOrganoid model derived from fetal lung bud tip tissue consists primarily of SOX2+ SOX9+ progenitor cells. Differentiation under ALI conditions is necessary to achieve mature alveolar epithelium. ALI model was found to contain mostly ATII and ATI cells, with small basal and rare neuroendocrine populations. SFTPC + Alveolar type II like cells were most readily infected by SARS-CoV-2. The infectious virus titer is much higher (five log) compared to other established model.
Suzuki et aldoi: https://doi.org/10.1101/2020.05.25.115600Commercially available adult HBEpC cells were used to generate human bronchial organoids.In the organoid formOrganoids derived from HBEpC cells undergo differentiation process to achieve mature phenotype. Organoids are lacking distal epithelial cell types SARS-CoV-2 infection was performed on organoids and only the basolateral region came in to contact with the virus. Treatment with a TMPRSS2 inhibitor prior to infection demonstrated a reduction in infectivity.
Tiwari et alPMID: 33631122Differentiated human iPSCs into lung organoids.80 daysIn the organoid formOrganoids originated from iPSC cells and have proximal and distal epithelial cells. Infected organoids with SARS-CoV-2 and pseudovirus. SARS-CoV-2 pseudovirus entry was blocked by viral entry inhibitors.
Tindle et al [Current study]Deep lung tissue sections surgically obtained from patients undergoing lobe resections for lung cancers.RNA Seq and cross-validation of COVID-19 model. Single model with all the cells types and infection of SARS-CoV2 in the 2D form with Apical accessibility that close to physiologic state.
  1. ACE2: angiotensin-converting enzyme II; ALI: air-liquid interphase; TMPRSS2: transmembrane serine protease 2.

  2. Blue color cells denote the presence of the features.

  3. Red color cells denote the absence of the features.

  4. Grey color cells denote information not found.

Table 2
Markers used to identify various cell types in the lung.
Cell typeMarkers
AT1AQP5*$, PDPN*$$, Carboxypeptidase M, CAV-1, CAV-2, HTI56, HOPX, P2R × 4*$$, Na+/K + ATPase$, TIMP3*++, SEMA3F PDPN* AQP5* P2R × 4* TIMP3* SERPINE*
AT2ABCA3*$$, CC10 (SCGB1A1*)+, CD44v6, Cx32, gp600++, ICAM-1++, KL-6, LAMP3*$$, MUC1, SFTPA1*$$, SFTPB*$, SFTPC*+, SFTPD*, SERPINE1
ClubCC10 (SCGB1A1*)+, CYP2F2*, ITAG6*$$, SCGB3A2*$$, SFTPA1*$$, SFTPB*$, SFTPD*
GobletCDX-2*, MUC5AC*, MUC5B*, TFF3*, UEA1+
CiliatedACT (ACTG2*)$, BTub4 (TUBB4A*), FOXA3*++, FOXJ1*, SNTN*
BasalCD44v6 (CD44*), ITGA6*$$, KRT5*$, KRT13*, KRT14*, p63 (CKAP4*), p75 (NGFR*)$$
Generic Lung LineageCx43 (GJA1*), TTF-1 (TTF1*; Greatest in AT2 & Club), EpCAM (EPCAM*)
  1. *Markers used for single-cell gating (Figure 1A).

  2. $ denotes markers used in this work for Immunofluorescence (IF).

  3. $$ denotes markers used in this work for qPCR.

  4. + denotes markers used in both IF and qPCR.

  5. ++ denotes obscure markers (Not a lot of research relative to lung).

Table 3
Characteristics of patients enrolled into this study for obtaining lung tissues to serve as source of stem cells to generate lung organoids.
NameDate of surgeryAgeSexSmoking historyReason for surgeryHistology
ALO14/17/202064MaleCurrent, chronic smokerPacks/day: 0.50Years: 53Pack years: 26.5Lung carcinomaInvasive squamous cell carcinoma, non-keratinizing
ALO24/17/202059MaleNon-smokerLung carcinomaInvasive adenocarcinoma
ALO37/7/202046FemaleNon-smokerLeft lower lobe noduleInvasive adenocarcinoma
Table 4
Upregulated genes and pathways: healthy vs COVID-19 lung (GSE151764).
Genes
BRCA2XAGE1BCDK1SNAI2CXCL11
CYBBCCR5GBP1IFITM1IFI27
KRT5CCR2HLA-GGZMBIFI35
C1QBALOX15BIDO1CD163TDO2
FCGR1ACMKLR1ISG20CD38GZMA
IL10MX1LAG3BST2OAS3
IL6TNFRSF17MAD2L1BUB1POU2AF1
CD44CCR1CXCL9CCL20CXCL13
CD276CXCR3MKI67CCNB2GNLY
DMBT1SLAMF8IFIT2TNFSF18IFIT3
DDX58IL21IFIT1ISG15TOP2A
TNFAIP8FOXM1CXCL10CDKN3LILRB1
LAMP3IFIH1IRF4C1QAHERC6
KIAA0101IFI6PSMB9OAS1TNFSF13B
MELKPDCD1LG2CCL18OAS2IFI44L
PathwaysSTAT1
Namep-valueFDR
Interferon signaling1.11E-161.11E-14
Interferon alpha/beta signaling1.11E-161.11E-14
Cytokine signaling in immune system1.11E-161.11E-14
Immune ssystem1.11E-161.11E-14
Interleukin-10 signaling9.85E-137.88E-11
Interferon gamma signaling9.26E-126.11E-10
Chemokine receptors bind chemokines1.08E-106.17E-09
Signaling by interleukins6.81E-093.41E-07
Insulin-like growth factor-2 mRNA binding proteins (IGF2BPs/IMPs/VICKZs) bind RNA1.27E-070.000005581122619
Antiviral mechanism by IFN-stimulated genes0.0000019330583490.00007732233398
CD163 mediating an anti-inflammatory response0.0000077986761690.0002807523421
OAS antiviral response0.000010208709970.0003368874291
Peptide ligand-binding receptors0.000017140576870.0005142173062
Interleukin-4 and Interleukin-13 signaling0.00010149486610.002841856252
Cyclin A/B1/B2-associated events during G2/M transition0.00018878164650.00490832281
G0 and early G10.00036071218380.009017804596
Interleukin-6 signaling0.00046566784440.01071036042
ISG15 antiviral mechanism0.00083139919880.01745938317
Regulation of APC/C activators between G1/S and early anaphase0.00083139919880.01745938317
Polo-like kinase-mediated events0.0011105065130.02221013026
APC/C-mediated degradation of cell cycle proteins0.0013081035810.02354586446
Regulation of mitotic cell cycle0.0013081035810.02354586446
G2/M DNA replication checkpoint0.0017501563320.02975265764
Class A/1 (rhodopsin-like receptors)0.0023550630450.03537666782
Interleukin-6 family signaling0.0023584445210.03537666782
TNFs bind their physiological receptors0.0023584445210.03537666782
Table 5
Downregulated genes and pathways: healthy vs COVID-19 lung (GSE151764).
Genes
CX3CR1JAMLKLRB1GRAP2CD226
ARG1CX3CR1LY9MMP9CD160
MPOHLA-DQB2CCL17RORCFOXP3
IL2TNFRSF9CCL22CCR4CRTAM
BCL2CXCR5TCF7IRS1CCR6
CA4CD1CCXCR4ITKCEACAM8
IGF1RCD69CD83KLRG1PTGS2
Pathways
Namep-valueFDR
Chemokine receptors bind chemokines2.85E-114.98E-09
Immune system1.25E-101.09E-08
Interleukin-4 and interleukin-13 signaling2.82E-091.64E-07
RUNX1 and FOXP3 control the development of regulatory T lymphocytes (Tregs)4.31E-070.00001853717999
Peptide ligand-binding receptors6.71E-070.00002348305743
Signaling by Interleukins0.0000015036584930.0000436060963
Cytokine signaling in Immune system0.000026065058550.0006516264636
Dectin-1-mediated noncanonical NF-kB signaling0.000086405432150.001814514075
Immunoregulatory interactions between a lymphoid and a non-lymphoid cell0.00010833886750.002058438482
Class A/1 (rhodopsin-like receptors)0.00018330488280.003116183008
Interleukin-10 signaling0.00023669619340.0035504429
RUNX3 regulates immune response and cell migration0.00057918141130.007747184934
Extra-nuclear estrogen signaling0.00059593730260.007747184934
BH3-only proteins associate with and inactivate anti-apoptotic BCL-2 members0.00069925475230.008391057028
CLEC7A (Dectin-1) signaling0.00082280351450.00905083866
Generation of second messenger molecules0.0011719919080.01171991908
Innate immune system0.0016764040920.01572360367
GPCR ligand binding0.0017470670740.01572360367
Adaptive immune system0.0020598359910.01853852391
Estrogen-dependent nuclear events downstream of ESR-membrane signaling0.004670055830.03736044664
C-type lectin receptors (CLRs)0.005458044950.0436643596
Transcriptional regulation by RUNX30.0081243325990.05687032819
BMAL1:CLOCK, NPAS2 activates circadian gene expression0.0095182727090.06662790896
ESR-mediated signaling0.012073762370.08451633662
Transcriptional regulation by RUNX10.012881563710.08786708747
TCR signaling0.014644514580.08786708747
Table 6
The list of GSE numbers used in the figures.
GSE#Cell type/tissueReferencesFigure
GSE132914Tissue from idiopathic pulmonary fibrosis subjects and donor controlsPMID:32991815Figure 1A
GSE151764COVID-19 and normal lung tissue post-mortemPMID:33033248Figure 4A–E, Figure 5E–G
GSE155241hPSC lung organoids and colon organoids infected with SARS-CoV-2PMID:33116299Figure 4E,F, Figure 6D
GSE156063Upper airway of COVID-19 patients and other acute respiratory illnessesPMID:33203890Figure 4E, Figure 5F,H
GSE147507A549 cells and bulk lungPMID:32416070; PMID:33782412Figure 4E,F, Figure 5F
GSE145926Bronchoalveolar lavage fluid (BALF) immune cells from COVID-19 and healthy subjectsPMID:32398875Figure 4E, Figure 5F,I
GSE150819Human bronchial organoidsFrom commercially available HBEpCFigure 4F, Figure 6C
GSE149312Intestinal organoids infected with SARS-CoV or SARS-CoV-2PMID:32358202Figure 4F
GSE151803hPSC-derived pancreatic and lung organoids infected with SARS-CoV-2No publication yetFigure 4F
GSE153940Vero E6 control or SARS-CoV-2-infected cellsPMID:32707573Figure 6B
GSE153218SARS-CoV-2-infected bronchoalveolar cells derived from organoids grown using progenitor cells from human fetal lung but tip (LBT).PMID:33283287Figure 6H
Table 7
Upregulated genes and pathways: uninfected vs infected (48 hpi) lung organoid monolayers.
Genes
IFI35EPSTI1AMIGO2IFITM2
SLC4A11CMPK2WARS1FAAP100
APOL1OASLIFI27ISG15
OAS3IFI44LCD14SLC35F6
IFIT3IFI44SAMD9L
IFIT2PARP9SRP9P1
Pathways
Namep-valueFDR
Interferon signaling1.11E-164.22E-15
Interferon alpha/beta signaling1.11E-164.22E-15
Cytokine signaling in Immune system1.15E-102.89E-09
Immune system0.0000025401148790.00004826218271
OAS antiviral response0.00047645456630.007146818495
Antiviral mechanism by IFN-stimulated genes0.0010333472610.01240016713
Interferon gamma signaling0.0018896946190.02078664081
Transfer of LPS from LBP carrier to CD140.0063187722450.05686895021
TRIF-mediated programmed cell death0.020912675860.1656073329
MyD88 deficiency (TLR2/4)0.037337482710.1656073329
IRAK2-mediated activation of TAK1 complex upon TLR7/8 or 9 stimulation0.037337482710.1656073329
TRAF6-mediated induction of TAK1 complex within TLR4 complex0.039371738120.1656073329
IRAK4 deficiency (TLR2/4)0.039371738120.1656073329
Activation of IRF3/IRF7 mediated by TBK1/IKK epsilon0.041401833220.1656073329
Caspase activation via death receptors in the presence of ligand0.041401833220.1656073329
IKK complex recruitment mediated by RIP10.049480774760.1855013265
Table 8
Downregulated genes and pathways: uninfected vs. infected (48 hpi) lung organoid monolayers.
AC093392.1ARHGAP19HLA-VRN7SL718P
MT-TVAC138969.3AC016766.1
Pathways
Namep-valueFDR
rRNA processing in the mitochondrion0.018927312460.08366120773
tRNA processing in the mitochondrion0.021271491050.08366120773
Mitochondrial translation termination0.043991554460.08366120773
Mitochondrial translation elongation0.043991554460.08366120773
Mitochondrial translation initiation0.044909217620.08366120773
Mitochondrial translation0.047657678440.08366120773
Key resources table
Reagent type (species) or resourceDesignationSource or referenceIdentifiersAdditional information
AntibodyAnti-ACE2 (mouse monoclonal)Santa CruzCat# sc390851RRID::AB_2861379IF (1:100)
AntibodyAnti-human ACE2 (rat monoclonal)BioLegendCat# 375802RRID::AB_2860959IF (1:50)
AntibodyAnti-acetylated ɑ tubulin (mouse monoclonal)Santa CruzCat# sc23950RRID::AB_628409IF (1:500)FC (1:8000)
AntibodyAnti-AQP5 (mouse monoclonal)Santa CruzCat# sc514022RRID::AB_2891066IF (1:100)FC (1:800)
AntibodyAnti-CC10 (mouse monoclonal)Santa CruzCat# sc365992RRID::AB_10915481IF (1:100)
OtherDAPIInvitrogenCat# D1306RRID::AB_2629482IF (1:500)
AntibodyRecombinant anti-cytokeratin 5 (rabbit monoclonal)AbcamCat# ab52635RRID::AB_869890IF (1:100)FC (1:8000)
AntibodyRecombinant anti-mucin 5AC (rabbit monoclonal)AbcamCat# ab229451RRID::AB_2891067IF (1:150)FC (1:800)
AntibodyAnti-sodium potassium ATPase (rabbit monoclonal)AbcamCat# ab76020RRID::AB_1310695IF (1:400)
AntibodyAnti-occludin (mouse monoclonal)Thermo FisherCat# OC-3F10RRID::AB_2533101IF (1:500)
OtherPhalloidin, Alexa Fluor 594InvitrogenCat# A12381RRID:AB_2315633IF (1:500)
OtherPropidium iodideInvitrogenV13241FC (1:100)
AntibodySARS-CoV/SARS-CoV-2 nucleocapsid antibody (mouse monoclonal)Sino BiologicalCat# 40143-MM05RRID::AB_2827977IF (1:250)IHC (1:500)
AntibodyAnti-SARS spike glycoprotein (mouse monoclonal)AbcamCat# ab273433RRID::AB_2891068IHC (1:250)
Antibodyanti-SP-B (mouse monoclonal)Santa CruzCat# sc133143RRID::AB_2285686IF (1:100)FC (1:8000)
AntibodyAnti-prosurfactant protein C (rabbit polyclonal)AbcamCat# ab90716RRID::AB_10674024IF (1:150)
AntibodyGoat anti-rat IgG H&L secondary antibody, Alexa Flour 594InvitrogenCat# A-11007RRID:AB_10561522IF (1:500)
AntibodyGoat anti-rabbit IgG H&L secondary antibody, Alexa Fluor 594InvitrogenCat# A-11012RRID:AB_2534079IF (1:500)
AntibodyGoat anti-mouse IgG H&L secondary antibody, Alexa Fluor 488InvitrogenCat# A-11011RRID:AB_143157IF (1:500)FC (1:1000)
AntibodyGoat anti-rabbit IgG H&L secondary antibody, Alexa Fluor 488AbcamCat# ab150077RRID:AB_2630356FC (1:1000)
OtherCountess II Automated Cell CounterThermo Fisher ScientificAMQAX1000Section‘The preparation of lung organoid-derived monolayers’
OtherEpithelial Volt-Ohm (TEER) MeterMilliporeMERS00002Section ‘Permeability of lung monolayer using FITC-dextran’
OtherLeica TCS SPE ConfocalLeica MicrosystemsTCS SPESection‘Immunofluorescence’
OtherPower Pressure Cooker XLTristar ProductsSection‘Immunohistochemistry’
OtherCanon Rebel XS DLSRCanonFigure 2—figure supplement 1
OtherMiniAmp Plus Thermal CyclerApplied BiosystemsCat# A37835Section‘Quantitative (q)RT-PCR’
OtherQuantStudio5Applied BiosystemsCat# A28140 RRID:SCR_020240Section‘Quantitative (q)RT-PCR’
OtherLight Microscope (brightfield images)Carl Zeiss LLCAxio Observer, Inverted; 491917-0001-000Figure 2—figure supplement 1
OtherSpark 20 M Multimode Microplate ReaderTecanSection‘Permeability of lung monolayer using FITC-dextran’
OtherGuava easyCyte Benchtop Flow CytometerMilliporeGuava easyCyte 62LSection‘The characterization of lung cell types using flow cytometry’
Software, algorithmImageJImageJRRID:SCR_003070
Software, algorithmGraphPad PrismGraphPad PrismRRID:SCR_002798
Software, algorithmLAS AF SoftwareLAS AF Software
Software, algorithmQuantStudio Design & Analysis SoftwareQuantStudio Design & Analysis Software
Software, algorithmCIBERSORTxCIBERSORTx
Software, algorithmFlowJoFlowJo V10, BD BioSciencesRRID:SCR_008520
Chemical compound, drugZinc formalinFisher ScientificCat# 23-313096
Chemical compound, drugXyleneVWRCat# XX0060-4
Chemical compound, drugHematoxylinSigma-Aldrich IncCat# MHS1
Chemical compound, drugEthanolKoptecCat# UN1170
Chemical compound, drugSodium citrateSigma-AldrichCat# W302600
Chemical compound, drugDAB (10×)Thermo FisherCat# 1855920(1:10)
Chemical compound, drugStable peroxidase substrate buffer (10×)Thermo FisherCat# 34062(1:10)
Chemical compound, drug3%hydrogen peroxideTargetCat# 245-07-3628
Chemical compound, drugHorse serumVector LabsCat# 30022
Commercial assay or kitHRP Horse Anti-Rabbit IgG Polymer Detection KitVector LaboratoriesCat# MP-7401
Chemical compound, drugParaformaldehyde 16% Solution, EM GradeElectron Microscopy SciencesCat# 15710
Chemical compound, drug100%methanolSupelcoCat# MX0485
Chemical compound, drugGlycineFisher ScientificCat# BP381-5
Chemical compound, drugBovine serum albuminSigma-AldrichCat# A9647-100G
Chemical compound, drugTriton-X 100Sigma-AldrichCat# X100-500ML
Chemical compound, drugProLong GlassInvitrogenCat# P36984
Chemical compound, drugNail Polish (Rapid Dry)Electron Microscopy SciencesCat# 72180
Chemical compound, drugGill Modified Hematoxylin (Solution II)Millipore SigmaCat# 65066-85
Chemical compound, drugHistoGelThermo ScientificCat# HG4000012
Chemical compound, drugTrypLE SelectThermo ScientificCat# 12563-011
Chemical compound, drugAdvanced DMEM/F-12Thermo ScientificCat# 12634-010
Chemical compound, drugHEPES bufferLife TechnologiesCat# 15630080
Chemical compound, drugGlutamaxThermo ScientificCat# 35050-061
Chemical compound, drugPenicillin-streptomycinThermo ScientificCat# 15140-122
Chemical compound, drugCollagenase type IThermo ScientificCat# 17100-017
Chemical compound, drugMatrigelCorningCat# 354234
Chemical compound, drugB-27Thermo ScientificCat# 17504044
Chemical compound, drugN-acetyl-L-cysteineSigma-AldrichCat# A9165
Chemical compound, drugNicotinamideSigma-AldrichCat# N0636
Chemical compound, drugFGF-7 (KGF)PeproTechCat# 100-19-50ug
Chemical compound, drugFGF10PeproTechCat# 100-26-50ug
Chemical compound, drugA-83-01Bio-Techne Sales Corp.Cat# 2939/50
Chemical compound, drugSB202190Sigma-AldrichCat# S7067-25MG
Chemical compound, drugY-27632R&D SystemsCat# 1254/50
Chemical compound, drugDPBSThermo ScientificCat# 14190-144
Chemical compound, drugUltrapure WaterInvitrogenCat# 10977-015
Chemical compound, drugEDTAThermo ScientificCat# AM9260G
Chemical compound, drugHydrocortisoneSTEMCELL TechnologiesCat# 7925
Chemical compound, drugHeparinSigma-AldrichCat# H3149
OtherPneumaCult Ex-Plus MediumSTEMCELL TechnologiesCat# 5040Section‘The preparation of lung organoid-derived monolayers’
OtherPneumaCult ALI MediumSTEMCELL TechnologiesCat# 5001Section‘ALImodel of lung organoids’
Chemical compound, drugGoat serumVector LaboratoriesCat# MP-7401
Chemical compound, drugFetal bovine serumSigma-AldrichCat# F2442-500ML
Chemical compound, drugAnimal Component-Free Cell Dissociation KitSTEMCELL TechnologiesCat# 5426
Chemical compound, drugRed Blood Cell Lysis BufferInvitrogenCat# 00-4333-57
Chemical compound, drugCell Recovery SolutionCorningCat# 354253
Chemical compound, drugSodium azideFisher ScientificCat# S227I-100
Chemical compound, drugCyto-Fast Fix/Perm Buffer SetBioLegendCat# 426803
Chemical compound, drugFITC-dextranSigma-AldrichCat# FD10S
Commercial assay or kitQuick-RNA MicroPrep KitZymo ResearchCat# R1051
Commercial assay or kitQuick-RNA MiniPrep KitZymo ResearchCat#R1054
Chemical compound, drugEthyl alcohol, pureSigma-AldrichCat# E7023
Chemical compound, drugTRI ReagentZymo ResearchCat# R2050-1-200
Sequence-based reagent2x SYBR Green qPCR Master MixBimakeCat# B21203
Sequence-based reagentqScript cDNA SuperMixQuanta BiosciencesCat# 95048
Sequence-based reagentApplied Biosystems TaqMan Fast Advanced Master MixThermo ScientificCat# 4444557
Sequence-based reagent18S, Hs99999901_s1Thermo ScientificCat# 4331182
Sequence-based reagentE_Sarbeco_F1 Forward PrimerIDTCat# 10006888
Sequence-based reagentE_Sarbeco_R2 Reverse PrimerIDTCat# 10006890
Sequence-based reagentE_Sarbeco_P1 ProbeIDTCat# 10006892
Other12-well Tissue Culture PlateCytoOneCat# CC7682-7512Section‘Isolation and culture of human whole lung-derived organoids’
OtherTranswell Inserts (6.5 mm, 0.4µm pore size)CorningCat# 3470Section‘The preparation of lung organoid-derived monolayers’
OtherMicroscope Cover Glass (#1 Thickness) 24 × 50 mmVWRCat# 16004-098Section‘Immunofluorescence’
OtherMicroscope Cover Glass (#1 Thickness) 25 mm diameterChemglass Life SciencesCat# CLS-1760-025Section‘Immunofluorescence’
OtherMillicell EZ Slide 8-Well ChamberMillipore SigmaCat# PEZGS0816Section‘Immunofluorescence’
OtherTrypan Blue StainInvitrogenCat# T10282(1:2)
Other70µm Cell StrainerThermo Fisher ScientificCat# 22-363-548Section‘The preparation of lung organoid-derived monolayers’
Other100 µm Cell StrainerCorningCat# 352360Section‘Isolation and culture of human whole lung-derived organoids’
OtherNoyes Spring Scissors – AngledFine Science ToolsCat# 15013-12Section‘Isolation and culture of human whole lung-derived organoids’
Author response table 1
ApproachPROSCONSMajor conclusionCaution
FACS of dispersed cells from organoidsHighthroughputanalysisAnalyzes protein, nottranscriptsAb-related artifactsHas the potential to introduce artifactsduring dissociationMixed cellularity was confirmed in all 3 ALO lines.Mixed cellularity is retained despite the passageThis methodology, standalone, is not appropriate to draw conclusions regarding the absolute proportions of each cell type because of shared markers, and antibody limitations
Targeted qPCRHighly sensitive andspecificLow-throughputanalysis that only measures transcript, but does not inform about protein translationMixed cellularity was confirmed in all 3 ALO lines.Mixed cellularity is retained despite passagethis methodology, standalone, is not sufficient to draw conclusions regarding the proportions of each cell type because of shared transcripts between cell types.
RNASeq>deconvolution using CYBERSORTxhighthroughput analysisResults are as good as our collective knowledge of cell type markers, many of which are sharedMixed cellularity was confirmed in all 3 ALO lines.Mixed cellularity is retained despite the passagethis methodology, standalone, is not sufficient to draw conclusions regarding the proportions of each cell type because of shared transcripts between cell types
In situ detection of protein by immunostaining of3D/2D organoidsDetection of protein (not just transcript) and with fewerartifactsbecause of in situ analysisLow-throughput qualitative analysisWe prioritized this methodology over others and used two different approaches (FFPE samples after embedding in Histogel Figure 2I-J and direct fixation with PFA/methanol, Figure 2K) to reduce the fixation related aritfacts of any one particular methodology.Although this approach was the best way to show mixed cellularity in each line, and at times, within the same 3D organoid structure, it is low throughput and qualitative (not quantitative), and hence, not suitable to be used for serial imaging of markers to estimate % cellularity/composition.

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  1. Courtney Tindle
  2. MacKenzie Fuller
  3. Ayden Fonseca
  4. Sahar Taheri
  5. Stella-Rita Ibeawuchi
  6. Nathan Beutler
  7. Gajanan Dattatray Katkar
  8. Amanraj Claire
  9. Vanessa Castillo
  10. Moises Hernandez
  11. Hana Russo
  12. Jason Duran
  13. Laura E Crotty Alexander
  14. Ann Tipps
  15. Grace Lin
  16. Patricia A Thistlethwaite
  17. Ranajoy Chattopadhyay
  18. Thomas F Rogers
  19. Debashis Sahoo
  20. Pradipta Ghosh
  21. Soumita Das
(2021)
Adult stem cell-derived complete lung organoid models emulate lung disease in COVID-19
eLife 10:e66417.
https://doi.org/10.7554/eLife.66417